The accelerating digital transformation in manufacturing enhances automation and production efficiency, requiring employees to develop new skills to meet evolving demands. This case study examines how Siemens embeds a human-centric bottom-up approach to empower employee re- and upskilling through innovative digital learning. Aligned with Siemens’ actions, we present a four-phase model on leveraging information systems to address skill gaps, enhance adaptability and tackle re- and upskilling challenges. Moreover, we provide five recommendations for organizations fostering lifelong learning in dynamic manufacturing environments.

Macrophages have a dual role in tissue healing after injury as they perform tissue repair functions but can also precipitate tissue damage or promote fibrosis. Platelets, beyond their role in thrombosis and hemostasis, are crucial mediators of inflammation and interact with macrophages. Platelet-macrophage interactions have been proposed to modulate macrophage phenotype, including their profibrotic functions, but the full extent of the platelet impact on the macrophage transcriptome is unknown. Here, we aimed to investigate how platelets affect macrophage activation in vitro. Using experimental myocardial infarction (MI) in mice as a model of sterile tissue injury, we readily visualized the direct interaction of platelets with macrophages in the ischemic heart using fluorescence microscopy. Bulk RNA-sequencing of mouse bone marrow-derived macrophages co-cultured in vitro with thrombin-activated platelets showed a widespread pro-inflammatory activation, with up-regulation of genes associated with inflammation (Il1b, Trem1, Tlr2, Cd14), angiogenesis (Vegfa) and response to hypoxia (Hif1a). Resting platelets also led to activation of inflammatory gene expression by macrophages, albeit to a much lesser extent. Activated or resting platelets, or the platelet-derived chemokine CXCL4, had a limited impact on macrophage expression of pro-fibrotic genes (Spp1, Fn1). Using a transwell assay, we further demonstrate that the pro-inflammatory effects of platelets on the macrophage transcriptome was largely contact dependent. Altogether, our work shows that platelets interact with macrophages in the ischemic heart and polarize macrophages towards a pro-inflammatory phenotype in vitro, with potential implications for cardiac macrophage inflammatory activation after acute experimental MI.

Desmosomes play an underexplored role in intestinal homeostasis and are linked to the pathogenesis of inflammatory bowel diseases. We found a novel function of the desmosomal plaque protein Plakoglobin (JUP) in initiating the innate immune response to facilitate intestinal inflammation. Tissue samples from Crohn's disease (CD) patients revealed a loss of JUP, which was mirrored in a mouse model of dextran sodium sulfate-induced (DSS) colitis. Inducible intestinal epithelial-specific knock-out of Jup (iVilCreERT2Jupfl/fl) in mice resulted in increased submucosal infiltration of macrophages and neutrophils, along with activation of the inflammasome. This was paralleled by p38MAPK phosphorylation while loss intestinal epithelial barrier function was absent. In DSS-colitis, epithelial Jup-deficiency impaired recovery and enhanced IL23/IL17-signaling. Intestinal organoids lacking Jup demonstrated NLRP1 inflammasome activation, indicated by increased IL1β and IL18 levels, which was attenuated by p38MAPK inhibition. In silico analysis and co-immunoprecipitation confirmed a direct interaction between JUP and p38MAPK, revealing a regulatory mechanism where JUP limits inflammasome signaling in intestinal epithelial cells. These effects were blunted by NLRP1/3 inhibitor ADS032.. These findings identify JUP as a critical modulator of epithelial innate immunity in the gut. The loss of JUP in tissues from CD patients underscores its potential relevance in disease pathology.

Nerve growth factor (NGF) is released after injury from macrophages and other cell types and induces an inflammatory response in neurons, characterized by local subcellular reactions and transcriptomic modulation. NGF-induced axonal transcriptome modulation may be crucial for pain initiation and maintenance. To explore these acute modulations, we cultured dorsal root ganglion neurons in microfluidic chambers and stimulated the axons with NGF. We found that axonal levels of the Il7 transcript encoding interleukin-7 (IL-7) are increased after NGF stimulation, followed by IL-7 release from axons. In growth cones of sensory neurons, we also observed a reorganization of the ribosomal subunits 60S and 40S in response to NGF stimulation. In addition, a dynamic change in the spatio-temporal distribution of the Tropomyosin Kinase B (TrkB) receptor occurs at the plasma membrane of sensory neuron growth cones. TrkB is recruited from the endoplasmic reticulum (ER) leading to increased cell surface levels. De-novo synthesis of TrkB seems to be limited to somatic regions of sensory neurons. Thus, cytosolic mechanisms within distal regions of the sensory neurons may autonomously regulate signaling and translation in response to external NGF stimuli.

A major focus of human genetics is to identify severely pathogenic variants, both to help diagnose patients and as an entry point into understanding disease mechanisms. To that end, it is often argued that we should sequence large samples from every genetic ancestry group, to not miss variants at high frequency in one group but rare in another. Yet modeling predicts that highly deleterious alleles should be at similar frequencies across ancestry groups. Here, we show model predictions to be a good fit to the data for variants most likely to be highly deleterious, notably protein-coding disruptions. The implication is that we should expect such variants to occur at similarly low frequencies across ancestry groups. A major focus of human genetics is to map severe disease mutations. Increasingly, that goal is understood as requiring huge numbers of people to be sequenced from every broadly defined genetic ancestry group, so as not to miss “ancestry-specific variants.” Here, we consider whether this focus is warranted. We start from first principles considerations, based on models of mutation–drift-selection balance, which suggest that since severe disease mutations tend to be strongly deleterious, and thus evolutionarily young, they will be kept at relatively constant frequency through recurrent mutation. Therefore, highly pathogenic alleles should be shared identically by descent within extended families, not broad ancestry groups, and sequencing more people should yield similar numbers regardless of ancestry. We test the model predictions using gnomAD genetic ancestry groupings and show that they provide a good fit to the classes of variants most likely to be highly pathogenic, notably sets of loss of function alleles at strongly constrained genes. These findings clarify that strongly deleterious alleles will be found at comparable rates in people of all ancestries, and the information they provide about human biology is shared across ancestries.

OBJECTIVES: There are currently no validated screeners that evaluate diet and lifestyle of people living with and beyond cancer (PLWBC). The purpose of this study was to reach a consensus among an international expert panel on the essential items to include in this type of instrument. DESIGN: A scientific committee developed the initial list of items, which were presented to an expert panel in a two-round-modified electronic Delphi. Panellists were asked to rate the adequacy, relevance and feasibility of self-reporting each item. Qualitative assessments were encouraged. SETTING: Four countries (Spain, UK, USA and Portugal). PARTICIPANTS: Experts working in a cancer-related health profession or cancer-related research were recruited. MAIN OUTCOME MEASURES: Items were initially categorised into seven domains (body composition, physical activity, diet, alcohol, smoking, sleep and psychosocial distress). A content validity index per item (CVI-i) and a scale-level CVI (S-CVI) were calculated (acceptable≥0.78). All items with a CVI-i≥0.78 were submitted to a final consensus meeting. RESULTS: A total of 108 items were proposed to the panel. In Round 1, 77 items were accepted, 10 items were excluded and 6 new items were proposed. During Round 2, 4 items were accepted and 19 were excluded. Diet and alcohol were merged into one domain. The final consensus meeting decided on 61 items categorised into six domains (S-CVI:0.94): body composition, physical activity, diet and alcohol, smoking, sleep and psychosocial distress. CONCLUSIONS: We identified the main items to be considered when developing a screener to evaluate diet and lifestyle in PLWBC in a clinical setting, and the results obtained will guide the content of the screener in the following validation study.

Although conversational agents are successfully applied in teaching, it is largely unclear which communication principles should be employed to optimise learning. We examine the influence of common ground (i.e. shared knowledge on which to build during conversation) on learning. In an in-class experiment, students studied with one of two pedagogical conversational agents. The control version provided information without emphasising grounding, whereas the common ground version emphasised grounding, for example, by encouraging students to monitor and repair common ground. After the learning unit, students evaluated their learning experience and the pedagogical conversational agent, after which they were tested on the studied material. Students in the common ground (vs. the control) condition performed better in a post-study knowledge test and engaged longer with the pedagogical conversational agent. Thus, the common ground emphasis facilitated learning with a conversational agent, indicating that grounding principles should be incorporated when designing conversational agents.

Once hardware is manufactured, it becomes immutable, and any design flaws or vulnerabilities are permanent. Therefore, comprehensive testing of hardware designs is essential before production. However, the increasing complexity of modern processors makes static analysis and formal verification increasingly challenging. Fuzzing is a highly effective technique for detecting software vulnerabilities but adapting it to hardware presents unique challenges due to the fundamental differences between software and hardware. However, the current state-of-the-art in hardware fuzzing still has significant limitations, particularly in terms of performance, practicality, and the need for human intervention. To address these issues, we introduce RLFuzz, a novel hardware fuzzer that employs reinforcement learning to explore processors autonomously, achieving faster and more comprehensive coverage. Reinforcement learning enables the fuzzer to learn from its interactions with the processor without requiring labeled data, allowing it to more effectively select modifications for test cases and target previously unexplored areas. RLFuzz uses an asynchronous training mechanism that permits concurrent fuzzing and neural network training. To optimize RLFuzz, we performed an extensive evaluation of various deep Q-learning optimization techniques and hyper-parameters. We then tested the optimized fuzzer on three complex RISC-V cores-the Rocket core, CVA6, and BOOM-and compared its performance to a current hardware fuzzer, TheHuzz [20]. Our results show that RLFuzz achieved up to 1.77% higher coverage, and on average 2.35 times faster, and demonstrated a maximum speedup of up to 6.93 times. For branch coverage, the average speedup was 7.85 times, with a peak speedup of 92.98 times. Additionally, RLFuzz needed less time to complete 100,000 test cases and did not require any human intervention.

Three years in, one of AI’s enduring impacts is to make people feel like they’re losing it.

Altermagnets constitute a novel, third fundamental class of collinear magnetic ordered materials, alongside with ferro- and antiferromagnets. They share with conventional antiferromagnets the feature of a vanishing net magnetization. At the same time they show a spin-splitting of electronic bands, just as in ferromagnets, caused by the atomic exchange interaction. On the other hand, topology has recently revolutionized our understanding of condensed matter physics, introducing new phases of matter classified by intrinsic topological order. Here we connect the worlds of altermagnetism and topology, showing that the electronic structure of the altermagnet CrSb is topological. Using high-resolution angle-resolved photoemission spectroscopy, we observe the large momentum-dependent spin-splitting in CrSb that induces altermagnetic Weyl nodes. We observe the related topological Fermi-arcs, which in electronic structure calculations are spin polarized. This indicates that in altermagnets the large energy scale intrinsic to their spin-splitting creates its own realm of robust electronic topology.

We measured the I(V) and dV/dI(V) characteristics of TiTe2-based point contacts (PCs) from room to helium temperatures. Features indicating the emergence of charge density wave (CDW) were detected. They represent symmetrical relatively V = 0 maxima in dV/dI(V) around ±150 mV at liquid helium temperatures, which disappear above 150 K, similar to the case of sister CDW compound TiSe2. Applying higher voltages above 200 mV, we observed resistive switching in TiTe2 PCs from a metallic-like low-resistance state to a non-metallic type high-resistance state with a change of resistance by an order of magnitude. A unique diode-like effect was registered in “soft” TiTe2 PCs with hysteretic I(V) at the negative voltage on TiTe2. Discovering the resistive switching and diode effect adds TiTe2 to the transition-metal dichalcogenides, which could be useful in developing non-volatile ReRAM and other upcoming nanotechnologies.

Thin-film lasers based on organic semiconductors offer significant potential for miniaturized sensing and optical memory. We present a new method for creating first-order distributed feedback (DFB) Bragg gratings using laser-induced periodic surface structures (LIPSS) as the optical resonator. These subwavelength structures, fabricated via femtosecond laser micromachining, exhibit stable periodicities and provide sufficient feedback for lasing in an Alq3:DCM film. The laser emission wavelength can be widely tuned by varying the LIPSS periodicity defined by the pulse spacing of the structuring laser. While lasing is limited by LIPSS imperfections, we demonstrate that individual LIPSS gratings optically couple into a coherent macroscopic supermode. This coupling dramatically increases lasing efficiency and reduces thresholds by two orders of magnitude compared to a single LIPSS element. This straightforward fabrication enables solid-state organic DFB lasers as integrated, on-chip coherent light sources, eliminating complex external coupling into photonic circuits.

Conductive ferroelectric domain walls (DWs) represent a promising topical system for the development of nanoelectronic components and device sensors to be operational at elevated temperatures. DWs show very different properties as compared to their hosting bulk crystal, in particular with respect to the high local electrical conductivity. The objective of this work is to demonstrate DW conductivity up to temperatures as high as 400°C which extends previous studies significantly. Experimental investigation of the DW conductivity of charged, inclined DWs is performed using 5mol% MgO-doped lithium niobate single crystals. Current–voltage (IV ) curves are determined by DC electrometer measurements and impedance spectroscopy and found to be identical. Moreover, impedance spectroscopy enables to recognize artifacts such as damaged electrodes. Temperature dependent measurements over repeated heating cycles reveal two distinct thermal activation energies for a given DW, with the higher of the activation energies only measured at higher temperatures. Depending on the specific sample, the higher activation energy is found above 160°C to 230°C. This suggests, in turn, that more than one type of defect/polaron is involved, and that the dominant transport mechanism changes with increasing temperature. First principles atomistic modeling suggests that the conductivity of inclined domain walls cannot be solely explained by the formation of a 2D carrier gas and must be supported by hopping processes. This holds true even at temperatures as high as 400°C. Our investigations underline the potential to extend DW current based nanoelectronic and sensor applications even into the so-far unexplored temperature range up to 400°C.

The combination of thermoelectricity and electronic band topology has emerged as a frontier area of research, promising to provide new mechanisms for enhancing thermoelectric performance in various material systems. Topological materials, including topological insulators and Weyl/Dirac/nodal line topological semimetals, exhibit unique electronic properties such as band inversion, protected surface states, linear band dispersion, and nontrivial Berry curvature, all of which significantly influence thermoelectric transport phenomena. These features contribute to enhanced thermoelectric performance through mechanisms such as band inversion-driven warping and the anomalous Nernst effect. This article summarizes the current landscape of topological materials in thermoelectrics, emphasizing its potential to revolutionize energy technologies and outlining future research directions aimed at discovering new candidates.

The European Academy of Allergy and Clinical Immunology (EAACI) is currently developing guidelines on immunomodulation and nutrition. To inform these recommendations, a scoping review will be conducted to synthesize and map the available empirical evidence on how complementary feeding affects immune health in infants and toddlers to explore the association between complementary feeding during the first year of life and immune health outcomes in children up to 3 years of age. The scoping review will be conducted using the Preferred Reporting Items for Systematic Reviews and Meta-analysis Scoping Review Extension for scoping reviews (PRISMA-ScR) guidelines. We have developed inclusion criteria using the PCC (Population, Concept and Context) format: the population will include healthy infants; the concept refers to specific factors related to introduction of complementary feeding; and the context will focus on studies conducted in settings representative of everyday nutrition and feeding practices for infants and toddlers. Evidence sources include systematic reviews. We will search in MEDLINE and Epistemonikos. Data will be extracted using a standardized form developed in REDCap, and the findings will be synthesized narratively. Only published literature will be included in this systematic review. Therefore, no ethical approval is required. The final review paper will be published in a peer-reviewed journal. OSF registration DOI: 10.17605/OSF.IO/T5F8.

Synthetic data generation has emerged as a promising solution to overcome the challenges which are posed by data scarcity and privacy concerns, as well as, to address the need for training artificial intelligence (AI) algorithms on unbiased data with sufficient sample size and statistical power. Our review explores the application and efficacy of synthetic data methods in healthcare considering the diversity of medical data. To this end, we systematically searched the PubMed and Scopus databases with a great focus on tabular, imaging, radiomics, time-series, and omics data. Studies involving multi-modal synthetic data generation were also explored. The type of method used for the synthetic data generation process was identified in each study and was categorized into statistical, probabilistic, machine learning, and deep learning. Emphasis was given to the programming languages used for the implementation of each method. Our evaluation revealed that the majority of the studies utilize synthetic data generators to: (i) reduce the cost and time required for clinical trials for rare diseases and conditions, (ii) enhance the predictive power of AI models in personalized medicine, (iii) ensure the delivery of fair treatment recommendations across diverse patient populations, and (iv) enable researchers to access high-quality, representative multimodal datasets without exposing sensitive patient information, among others. We underline the wide use of deep learning based synthetic data generators in 72.6 % of the included studies, with 75.3 % of the generators being implemented in Python. A thorough documentation of open-source repositories is finally provided to accelerate research in the field.

Border Gateway Protocol (BGP) provides a way of exchanging routing information to help routers construct their routing tables. However, due to the lack of security considerations, BGP has been suffering from vulnerabilities such as BGP hijacking attacks. To mitigate these issues, two data sources have been used, Internet Routing Registry (IRR) and Resource Public Key Infrastructure (RPKI), to provide reliable mappings between IP prefixes and their authorized Autonomous Systems (ASes). Each of the data sources, however, has its own limitations. IRR has been well-known for its stale Route objects with outdated AS information since network operators do not have enough incentives to keep them up to date, and RPKI has been slowly deployed due to its operational complexities. In this paper, we measure the prevalent inconsistencies between Route objects in IRR and ROA objects in RPKI. We next characterize inconsistent and consistent Route objects, respectively, by focusing on their BGP announcement patterns. Based on this insight, we develop a technique that identifies stale Route objects by leveraginga machine learning algorithm and evaluate its performance. From real trace-based experiments, we show that our technique can offer advantages against the status quo by reducing the percentage of potentially stale Route objects from 72% to 40% (of the whole IRR Route objects). In this way, we achieve 93% of the accuracy of validating BGP announcements while covering 87% of BGP announcements.

The Routing Policy Specification Language (RPSL) enables operators to specify routing policies in public registries. These policies contain information for traffic engineering, troubleshooting routing incidents, and automatically configuring route filters to improve security. RPSL information is also valuable for researchers to better understand the Internet. However, the RPSL's complexities make these policies challenging to interpret programmatically. We introduce RPSLyzer, a tool that can parse and interpret 99.99% of RPSL policies. We use RPSLyzer to characterize the RPSL policies of 78,701 Autonomous Systems (ASes) and verify 779 million BGP routes against these policies. We find RPSL usage varies widely among ASes, identify common RPSL misuses that explain most route verification failures, and offer operators recommendations to improve RPSL usage.

The Venezuelan crisis, unfolding over the past decade, has garnered international attention due to its impact on various sectors of civil society. While studies have extensively covered the crisis's effects on public health, energy, and water management, this paper delves into a previously unexplored area - the impact on Venezuela's Internet infrastructure. Amidst Venezuela's multifaceted challenges, understanding the repercussions of this critical aspect of modern society becomes imperative for the country's recovery.Leveraging measurements from various sources, we present a comprehensive view of the changes undergone by the Venezuelan network in the past decade. Our study reveals the significant impact of the crisis captured by different signals, including bandwidth stagnation, limited growth on network infrastructure growth, and high latency compared to the Latin American average. Beyond offering a new perspective on the Venezuelan crisis, our study can help inform attempts at devising strategies for its recovery.

The Internet Routing Registry (IRR) is a set of distributed databases used by networks to register routing policy information and to validate messages received in the Border Gateway Protocol (BGP). First deployed in the 1990s, the IRR remains the most widely used database for routing security purposes, despite the existence of more recent and more secure alternatives. Yet, the IRR lacks a strict validation standard and the limited coordination across different database providers can lead to inaccuracies. Moreover, it has been reported that attackers have begun to register false records in the IRR to bypass operators' defenses when launching attacks on the Internet routing system, such as BGP hijacks. In this paper, we provide a longitudinal analysis of the IRR over the span of 1.5 years. We develop a workflow to identify irregular IRR records that contain conflicting information compared to different routing data sources. We identify 34,199 irregular route objects out of 1,542,724 route objects from November 2021 to May 2023 in the largest IRR database and find 6,373 to be potentially suspicious.

An organization-level topology of the Internet is a valuable resource with uses that range from the study of organizations’ footprints and Internet centralization trends, to analysis of the dynamics of the Internet’s corporate structures as result of (de)mergers and acquisitions. Current approaches to infer this topology rely exclusively on WHOIS databases and are thus impacted by its limitations, including errors and outdated data. We argue that a collaborative, operator-oriented database such as PeeringDB can bring a complementary perspective from the legally-bounded information available in WHOIS records. We present as2org+ , a new framework that leverages self-reported information available on PeeringDB to boost the state-of-the-art WHOIS-based methodologies. We discuss the challenges and opportunities with using PeeringDB records for AS-to-organization mappings, present the design of as2org+ and demonstrate its value identifying companies operating in multiple continents and mergers and acquisitions over a five-year period.

The numerical calculation of single-phase flows may be broadly separated into three classes depending on their spatial resolution, as illustrated in Figure 8.1. An introduction to these methods may be found in Ferziger and Peric (2002) together with details about discretization schemes and solution procedures. The first approach, direct numerical simulations (DNS) in principle resolves all relevant flow scales down to the Kolmogorov scales (i.e. the turbulent dissipation scales). Consequently, the numerical grid should be smaller than these scales to ensure proper resolution. This, however, implies that the size of the computational domain is limited due to the limited number of numerical control volumes that can be handled by today’s computers. Consequently, DNS is not able to resolve the entire spectrum of vortex scales or wave numbers, and hence, there is a cutoff at larger scales. Moreover, the ratio of macro-scale vortices to the Kolmogorov scale is proportional to Re¾. As a result, the flow Reynolds number considered in DNS has a limitation too. Typically, the maximum Re is between 5,000 and 10,000. Therefore, the application of DNS is limited to simple flow conditions, such as homogeneous isotropic turbulence, shear flows, and channel flows. Nevertheless, the DNS method is very helpful in analyzing and understanding basic phenomena in turbulence research.

Ancestry connects genetics and society in fundamental ways. For many people it has cultural, religious or even political significance, and can play a key role in shaping personal and public identities. People’s desire to discover their own ancestry drives the multibillion-dollar genealogy industry, which has grown rapidly in the era of consumer genomics. Companies such as 23andMe and Ancestry now claim tens of millions of customers worldwide. In parallel, our scientific understanding of the human past is being transformed by studies of ancient and modern genetic data, which allow us to track changes in ancestry over space and time. Sophisticated methods have been developed to infer and visualise these relationships. Thus, it seems that both scientists and the wider public are learning more and more about ancestry, and there is an optimistic sense that genetic data provide an exhaustive repository of ancestral information. However, although frequently discussed, ancestry itself is rarely defined. We argue that this reflects widespread underlying confusion about what it means in different contexts and what genetic data can really tell us. This leads to miscommunication between researchers in different fields, and leaves customers open to spurious claims about consumer genomics products and overinterpretation of individual results. In wider usage, the terms ancestry and ancestors often indicate a general connection to people or things in the past. But in a genetic context they have a more specific meaning: your ancestors are the individuals from whom you are biologically descended and ancestry is information about them and their genetic relationship to you. Even here however, confusion arises from the way that ancestry is presented and discussed. Rather than emphasising its complex structure, results are often simplified in terms of discrete categories. While convenient and sometimes useful, ultimately this is misleading about the nature of ancestry. These labels can also impose contemporary political or cultural divisions which may be misrepresentative of ancestral relationships. Another source of confusion is that three distinct concepts–genealogical ancestry, genetic ancestry, and genetic similarity–are frequently conflated. We discuss them in turn, but note that only the first two are explicitly forms of ancestry, and that genetic data are surprisingly uninformative about either of them. Consequently, most statements about ancestry are really statements about genetic similarity, which has a complex relationship with ancestry, and can only be related to it by making assumptions about human demography whose validity is uncertain and difficult to test.

Despite its critical role in Internet connectivity, the Border Gateway Protocol (BGP) remains highly vulnerable to attacks such as prefix hijacking, where an Autonomous System (AS) announces routes for IP space it does not control. To address this issue, the Resource Public Key Infrastructure (RPKI) was developed starting in 2008, with deployment beginning in 2011. This paper performs the first comprehensive, longitudinal study of the deployment, coverage, and quality of RPKI.We use a unique dataset containing all RPKI Route Origin Authorizations (ROAs) from the moment RPKI was first deployed, more than 8 years ago. We combine this dataset with BGP announcements from more than 3,300 BGP collectors worldwide. Our analysis shows the after a gradual start, RPKI has seen a rapid increase in adoption over the past two years. We also show that although misconfigurations were rampant when RPKI was first deployed (causing many announcements to appear as invalid) they are quite rare today. We develop a taxonomy of invalid RPKI announcements, then quantify their prevalence. We further identify suspicious announcements indicative of prefix hijacking and present case studies of likely hijacks.Overall, we conclude that while misconfigurations still do occur, RPKI is "ready for the big screen," and routing security can be increased by dropping invalid announcements. To foster reproducibility and further studies, we release all RPKI data and the tools we used to analyze it into the public domain.

In recent times, fake news and misinformation have had a disruptive and adverse impact on our lives. Given the prominence of microblogging networks as a source of news for most individuals, fake news now spreads at a faster pace and has a more profound impact than ever before. This makes detection of fake news an extremely important challenge. Fake news articles, just like genuine news articles, leverage multimedia content to manipulate user opinions but spread misinformation. A shortcoming of the current approaches for the detection of fake news is their inability to learn a shared representation of multimodal (textual + visual) information. We propose an end-to-end network, Multimodal Variational Autoencoder (MVAE), which uses a bimodal variational autoencoder coupled with a binary classifier for the task of fake news detection. The model consists of three main components, an encoder, a decoder and a fake news detector module. The variational autoencoder is capable of learning probabilistic latent variable models by optimizing a bound on the marginal likelihood of the observed data. The fake news detector then utilizes the multimodal representations obtained from the bimodal variational autoencoder to classify posts as fake or not. We conduct extensive experiments on two standard fake news datasets collected from popular microblogging websites: Weibo and Twitter. The experimental results show that across the two datasets, on average our model outperforms state-of-the-art methods by margins as large as ~ 6% in accuracy and ~ 5% in F1 scores.

Hypergiants, such as Google or Netflix, are important organisations in the Internet ecosystem, due to their sheer impact in terms of traffic volume exchanged. However, beyond naming specific instances, the research community still lacks a sufficiently crisp understanding of them. In this paper we analyse PeeringDB data and identify features that differentiate hypergiants from the other organisations. To this end, we first characterise the organisations present in PeeringDB, allowing us to identify discriminating properties of these organisations. We then use these properties to separate the data in two clusters, differentiating hypergiants from other organisations. We conclude this paper by investigating how hypergiants and other organisations exploit the IXP ecosystem to reach the global IPv4 space.

Although the rock art of southern Africa is overwhelmingly concerned with ritual, there are few depictions of the initiation rites so important to hunter-gatherer identity. This study presents the first definitive evidence of women's initiation based on evidence from rock art and archaeological features at the site of /Ui-//aes in Namibia. The evidence reveals multiple links between initiation, women's work in gathering wild grass seed, and the importance of the female kudu as a metaphor of positive social values. These links show that the beliefs underlying ritual practice also form part of everyday subsistence activity, extending the same precepts from mundane artefacts such as grindstones, to the habits of desert antelope.

Peering infrastructures, namely, colocation facilities and Internet exchange points, are located in every major city, have hundreds of network members, and support hundreds of thousands of interconnections around the globe. These infrastructures are well provisioned and managed, but outages have to be expected, e.g., due to power failures, human errors, attacks, and natural disasters. However, little is known about the frequency and impact of outages at these critical infrastructures with high peering concentration.In this paper, we develop a novel and lightweight methodology for detecting peering infrastructure outages. Our methodology relies on the observation that BGP communities, announced with routing updates, are an excellent and yet unexplored source of information allowing us to pinpoint outage locations with high accuracy. We build and operate a system that can locate the epicenter of infrastructure outages at the level of a building and track the reaction of networks in near real-time. Our analysis unveils four times as many outages as compared to those publicly reported over the past five years. Moreover, we show that such outages have significant impact on remote networks and peering infrastructures. Our study provides a unique view of the Internet's behavior under stress that often goes unreported.

The highest accuracy object detectors to date are based on a two-stage approach popularized by R-CNN, where a classifier is applied to a sparse set of candidate object locations. In contrast, one-stage detectors that are applied over a regular, dense sampling of possible object locations have the potential to be faster and simpler, but have trailed the accuracy of two-stage detectors thus far. In this paper, we investigate why this is the case. We discover that the extreme foreground-background class imbalance encountered during training of dense detectors is the central cause. We propose to address this class imbalance by reshaping the standard cross entropy loss such that it down-weights the loss assigned to well-classified examples. Our novel Focal Loss focuses training on a sparse set of hard examples and prevents the vast number of easy negatives from overwhelming the detector during training. To evaluate the effectiveness of our loss, we design and train a simple dense detector we call RetinaNet. Our results show that when trained with the focal loss, RetinaNet is able to match the speed of previous one-stage detectors while surpassing the accuracy of all existing state-of-the-art two-stage detectors. Code is at: https://github.com/facebookresearch/Detectron.

Internet eXchange Points (IXPs) are core components of the Internet infrastructure where Internet Service Providers (ISPs) meet and exchange traffic. During the last few years, the number and size of IXPs have increased rapidly, driving the flattening and shortening of Internet paths. However, understanding the present status of the IXP ecosystem and its potential role in shaping the future Internet requires rigorous data about IXPs, their presence, status, participants, etc. In this work, we do the first cross-comparison of three well-known publicly available IXP databases, namely of PeeringDB, Euro-IX, and PCH. A key challenge we address is linking IXP identifiers across databases maintained by different organizations. We find different AS-centric versus IXP-centric views provided by the databases as a result of their data collection approaches. In addition, we highlight differences and similarities w.r.t. IXP participants, geographical coverage, and co-location facilities. As a side-product of our linkage heuristics, we make publicly available the union of the three databases, which includes 40.2% more IXPs and 66.3% more IXP participants than the commonly-used PeeringDB. We also publish our analysis code to foster reproducibility of our experiments and shed preliminary insights into the accuracy of the union dataset.

We describe a new computational method for estimating the probability that a point mutation at each position in a genome will influence fitness. These 'fitness consequence' (fitCons) scores serve as evolution-based measures of potential genomic function. Our approach is to cluster genomic positions into groups exhibiting distinct 'fingerprints' on the basis of high-throughput functional genomic data, then to estimate a probability of fitness consequences for each group from associated patterns of genetic polymorphism and divergence. We have generated fitCons scores for three human cell types on the basis of public data from ENCODE. In comparison with conventional conservation scores, fitCons scores show considerably improved prediction power for cis regulatory elements. In addition, fitCons scores indicate that 4.2-7.5% of nucleotides in the human genome have influenced fitness since the human-chimpanzee divergence, and they suggest that recent evolutionary turnover has had limited impact on the functional content of the genome.

Back-propagation has been the workhorse of recent successes of deep learning but it relies on infinitesimal effects (partial derivatives) in order to perform credit assignment. This could become a serious issue as one considers deeper and more non-linear functions, e.g., consider the extreme case of non-linearity where the relation between parameters and cost is actually discrete. Inspired by the biological implausibility of back-propagation, a few approaches have been proposed in the past that could play a similar credit assignment role. In this spirit, we explore a novel approach to credit assignment in deep networks that we call target propagation. The main idea is to compute targets rather than gradients, at each layer. Like gradients, they are propagated backwards. In a way that is related but different from previously proposed proxies for back-propagation which rely on a backwards network with symmetric weights, target propagation relies on auto-encoders at each layer. Unlike back-propagation, it can be applied even when units exchange stochastic bits rather than real numbers. We show that a linear correction for the imperfectness of the auto-encoders, called difference target propagation, is very effective to make target propagation actually work, leading to results comparable to back-propagation for deep networks with discrete and continuous units and denoising auto-encoders and achieving state of the art for stochastic networks.

Population genetic studies suggest that most amino-acid changing mutations are deleterious. Such mutations are of tremendous interest in human population genetics as they are important for the evolutionary process and may contribute risk to common disease. Genomic studies over the past 5 years have documented differences across populations in the number of heterozygous deleterious genotypes, number of homozygous derived deleterious genotypes, number of deleterious segregating sites and proportion of sites that are potentially deleterious. These differences have been attributed to population history affecting the ability of natural selection to remove deleterious variants from the population. However, recent studies have suggested that the genetic load is the same across populations and that the efficacy of natural selection has not differed across human populations. Here I show that these observations are not incompatible with each other and that the apparent differences are due to examining different features of the genetic data and differing definitions of terms.

In this study we mine one of the few sources of public data available about the interdomain peering ecosytem: PeeringDB [1], an online database where participating networks contribute information about their peering policies, traffic volumes and presence at various geographic locations. Although established to support the practical needs of operators, this data also provides a valuable source of information to researchers. Using BGP data to cross-validate three years of PeeringDB snapshots, we find that PeeringDB membership is reasonably representative of the Internet's transit, content, and access providers in terms of business types and geography of participants, and PeeringDB data is generally up-to-date. We find strong correlations among different measures of network size -- BGP-advertised address space, PeeringDB-reported traffic volume and presence at peering facilities, and between these size measures and advertised peering policies.

This document describes an architecture for an infrastructure to support improved security of Internet routing. The foundation of this architecture is a Resource Public Key Infrastructure (RPKI) that represents the allocation hierarchy of IP address space and Autonomous System (AS) numbers; and a distributed repository system for storing and disseminating the data objects that comprise the RPKI, as well as other signed objects necessary for improved routing security. As an initial application of this architecture, the document describes how a legitimate holder of IP address space can explicitly and verifiably authorize one or more ASes to originate routes to that address space. Such verifiable authorizations could be used, for example, to more securely construct BGP route filters. This document is not an Internet Standards Track specification; it is published for informational purposes.

Internet Routing Registries(IRR) have been around for quite some time now[1] with the sole purpose of providing the place for service providers to store their administrative, routing policy information which can be used in case of BGP malicious/misconfiguration events. Are there any useful service providers policy data stored in IRR? What current limited research has able to answer is that "Quality" of IRR databases is not known". By "Quality" we mean validity of Internet Number Resources e.g. IPv4, IPv6, AS Number registration, routing policy registration, etc by different network service providers in IRR. We have tried to answer this question by looking into the public IRR datasets of approximately last 4 years [2006--2010]. We have found out that current IRR datasets has a lot to offer than its known/practiced i.e. IRR has approximately 50k full peering available. We are investigating how many peering are in harmony with what BGP is announcing and also which is currently published in well known topology datasets like UCLA IRL[25]. As we believe that if accurate peering can be extracted from IRR than they can provide number of new links which are missing in Internet Topology datasets. It can also reduce the usage of active measurements which in itself is burden on the network. We are also designing BGP Security framework based on IRR which will more accurately perform origin AS authentication as well as inferring the complete policy(what is stored in IRR) of AS.

We describe an on-line service, and its underlying methodology, designed to extract BGP peerings from the Internet Routing Registry. Both the method and the service are based on: a consistency manager for integrating information across different registries, an RPSL analyzer that extracts peering specifications from RPSL objects, and a peering classifier that aims at understanding to what extent such peering specifications actually contribute to fully determine a peering. A peering graph is built with different levels of confidence. We compare the effectiveness of our method with the state of the art. The comparison puts in evidence the quality of the proposed method.

At the inter-domain level, the Internet topology can be represented by a graph with Autonomous Systems (ASes) as nodes and AS peerings as links. This AS-level topology graph has been widely used in a variety of research efforts. Conventionally this topology graph is derived from routing tables collected by Route Views or RIPE RIS. In this work, we assemble the most complete AS-level topology by extending the conventional method along two dimensions. First, in addition to using data from RouteViews and RIPE RIS, we also collect data from many other sources, including route servers, looking glasses, and routing registries. Second, in addition to using routing tables, we also accumulate topological information from routing updates over time. The resulting topology graph on a recent day contains 44% more links and 3% more nodes than that from using RouteViews routing tables alone. Our data collection and topology generation process have been automated, and we publish the latest topology on the web on a daily basis.

Investigations into the single-phase velocity field of a model aeroengine bearing chamber are presented. Adequately resolving the airflow field is important to subsequent computational modeling of two-phase fluid transport and heat transfer characteristics. A specially designed test rig, representing the features of a Rolls Royce Trent series aeroengine bearing chamber, was constructed. Experimental data for the airflow field was obtained using particle image velocimetry (PIV). The results show a strong influence of shaft rotation and chamber geometry on the flow features within the bearing chamber. A computational fluid dynamics (CFD) simulation was carried out using the commercial CFD code FLUENT 6. Flow features were adequately modeled, showing the features of secondary velocities. Turbulence modeling using the differential Reynolds stress (RSM) model shows good agreement with the experimental data.

Investigations into the single-phase velocity field of a model aero-engine bearing chamber are presented. Adequately resolving the airflow field is important to subsequent computational modelling of two-phase fluid transport and heat transfer characteristics. A specially designed test rig, representing the features of a Rolls-Royce Trent series aero-engine bearing chamber, was constructed. Experimental data for the airflow field was obtained using particle image velocimetry (PIV). The results show a strong influence of shaft rotation and chamber geometry on the flow features within the bearing chamber. A computational fluid dynamics (CFD) simulation was carried out using the commercial CFD code FLUENT 6. Flow features were adequately modelled, showing the features of secondary velocities. Turbulence modelling using the differential Reynolds stress (RSM) model shows good agreement with the experimental data.

The age of an allele can be estimated both from genetic variation among different copies (intra-allelic variation) and from its frequency. Estimates based on intra-allelic variation follow from the exponential decay of linkage disequilibrium because of recombination and mutation. The confidence interval depends both on the uncertainty in recombination and mutation rates and on randomness of the genealogy of chromosomes that carry the allele (the intra-allelic genealogy). Several approximate methods to account for variation in the intra-allelic genealogy have been derived. Allele frequency alone also provides an estimate of age. Estimates based on frequency and on intra-allelic variability can be combined to provide a more accurate estimate or can be contrasted to show that an allele has been subject to natural selection. These methods have been applied to numerous cases, including alleles associated with cystic fibrosis, idiopathic torsion dystonia, and resistance to infection by HIV. We emphasize that estimates of allele age depend on assumptions about demographic history and natural selection.

A method for simulating two-phase flows including surface tension is presented. The approach is based upon smoothed particle hydrodynamics (SPH). The fully Lagrangian nature of SPH maintains sharp fluid?fluid interfaces without employing high-order advection schemes or explicit interface reconstruction. Several possible implementations of surface tension force are suggested and compared. The numerical stability of the method is investigated and optimal choices for numerical parameters are identified. Comparisons with a grid-based volume of fluid method for two-dimensional flows are excellent. The methods presented here apply to problems involving interfaces of arbitrary shape undergoing fragmentation and coalescence within a two-phase system and readily extend to three-dimensional problems. Boundary conditions at a solid surface, high viscosity and density ratios, and the simulation of free-surface flows are not addressed. Copyright ? 2000 John Wiley & Sons, Ltd.

An experimental investigation of primary breakup of nonturbulent round liquid jets in gas crossflows is described. Pulsed shadowgraph measurements of jet primary breakup regimes, jet deformation properties, time of onset of primary breakup, and liquid column and liquid surface disturbance wavelengths were obtained for air crossflows at normal temperature and pressure, the test range included crossflow Weber numbers of 0−200, liquid jet Weber numbers of 0−1,600,000, liquid jet Reynolds numbers of 0−800,000, liquid/gas momentum ratios of 100−8000, liquid/gas density ratios of 700−1100, and Ohnesorge numbers of 0.00006−0.3. The results suggest qualitative similarities between the primary breakup of nonturbulent round liquid jets in crossflows and the secondary breakup of drops, with relatively little effect of the liquid/gas momentum ratio over the present test range. Effects of liquid viscosity were also small for Ohnesorge numbers less than 0.1, but larger Ohnesorge numbers modified primary breakup because unusually long ligaments developed that also are seen during the secondary breakup of drops.

Covering the basics of liquid atomization, this book familiarizes readers with the physical processes of liquid atomization, the main types of atomizers and their design, measurements of spray characteristics, experimental investigations of atomizers, and application of atomizers. It demonstrates how to calculate and design atomizers and how to mea

PROTEINS often differ in amino-acid sequence across species. This difference has evolved by the accumulation of neutral mutations by random drift, the fixation of adaptive mutations by selection, or a mixture of the two. Here we propose a simple statistical test of the neutral protein evolution hypothesis based on a comparison of the number of amino-acid replacement substitutions to synonymous substitutions in the coding region of a locus. If the observed substitutions are neutral, the ratio of replacement to synonymous fixed differences between species should be the same as the ratio of replacement to synonymous polymorphisms within species. DNA sequence data on the Adh locus (encoding alcohol dehydrogenase, EC 1.1.1.1) in three species in the Drosophila melanogaster species subgroup do not fit this expectation; instead, there are more fixed replacement differences between species than expected. We suggest that these excess replacement substitutions result from adaptive fixation of selectively advantageous mutations.

The problems of estimating the time of extinction of a mutant allele and other re- lated quantities have been of considerable interest to population geneticists [1-4]. Nei and Li's work [2-4] are particularly relevant to human genetics, since they have estimated not only the number of individuals who will be affected in the future by presently known deleterious genes but also the time required for these genes to disappear from the population. It seems also interesting to ask a reverse question: Given that the present number of genes of a particular mutant allele occurring in a population is known, how long has the mutant persisted in the population? That is, what is the "age" of a mutant gene? This problem has been studied for selec- tively neutral genes by Kimura and Ohta [5] and Maruyama [6] independently. The topic of this note is to determine the average age of a rare mutant gene in large populations. There are many mutant genes, particularly deleterious ones, which appear to be very few in number and to be localized in a specific area of a human population. It is meaningless to assign them a gene frequency because such genes usually originate from a single mutant; they spread in a fairly restricted area and disappear in a few generations. Therefore the frequency varies depending upon the choice of reference population. For this type of situation, it is better to use a branching process model in which each gene reproduces independently of the other genes of the same mutant allele. This branching process model also assumes that there is no local density-dependent regulation of the population. Throughout this note, it is assumed that each mutant allele has unique origin and that there is no further mutation of the same type. An equivalent assumption is that the mutation rate multiplied by the number of the local population is much less than one. The mutant allele under consideration is denoted by A.

The age of an allele segregating in a finite population may be defined in two ways. They are (1) the age of a mutant gene that has never reached fixation in the population, and (2) the age including any fixation period in the past. Theoretical expressions for these are derived on the assumption that every mutant is unique.

EVOLUTION iS the transformation of species through time; but it is also the formation of differences among populations of the same species (or among species) that occupy differing environments. The two pheno- mena-differentiation in time and space-are naturally complementary aspects of the same process. Palaeont- ology has demonstrated that evolutionary trans- formations take place slowly; genetics has shown why this should be so. It is not at all surprising, therefore, that in human evolution long periods of time can elapse before substantial changes take place. Actually, some of the transformations characteristic of the evolution into Homo (such as the trebling in the capa- city of the hominid skull in a couple of million years) are among the fastest evolutionary changes observed. When we look at the variation between the human ethnic groups now living, we are amazed by the magnitude of such variation. In particular, skin colour inevitably impresses us very deeply, being a conspicuous, though in many respects superficial, difference. Other traits, mostly facial ones, are well- known aids in diagnosing the racial origin of an individual. Even a child learns soon to distinguish a white man from a black man or from an oriental. But when many more 'races' are distinguished, assign- ment of an individual to one of them on the basis of his external attributes is usually less successful. A test on this basis of the validity of taxonomies of human races has not been done. Probably, if one tried to allocate an individual, on the basis of his or her external appearance, to one of the thirty or so races which Garn (1961) distinguishes, for instance, the diagnosis would be in error relatively often. Most of the difficulties for taxonomy of human races arise from the fact that no matter how races are defined almost no measurable trait shows really sharp discontinuities from one 'race' to the next. On a map most traits-be they anthropometrics or gene frequencies-show gradual transitions or patterns of clinal variation. This suggests that during human evolution the extent of crossing must have been fairly large. Naturally, ethnic maps will show this clinal behaviour if in our analysis we concentrate on aboriginal populations and avoid those known or suspected major dis- placements over the last five hundred years or so. Otherwise we are confronted with extensive hetero- geneities. There are many communities of blacks and orientals and caucasians living side by side in many countries with very little, if any intermixture. Social barriers to interbreeding have in some cases survived over the short time elapsed since these migrations took place.