Data4UrbanMobility nimmt an der Ausstellung „Marktplatz der Möglichkeiten“ bei dem Leibniz Startup & Industry Event “Künstliche Intelligenz” teil. Die Veranstaltung findet am 20.11.2018 im Lichthof der Leibniz Universität Hannover statt und wird vom Forschungszentrum L3S organisiert.

• On a symplectic quantum Howe duality. Bodish, Elijah; Tubbenhauer, Daniel (2025).
• Photofunctional cyclophane host–guest systems. Garain, Swadhin; Würthner, Frank (2025). 61(15) 3081–3092.

  Modulation of optical properties through smart protein matrices is exemplified by a few examples in nature such as rhodopsin (absorption wavelength tuning) and the green fluorescence protein (emission), but in general, the scope found in nature for the matrix-controlled photofunctions remains rather limited. In this review, we present cyclophane-based supramolecular host–guest complexes for which electronic interactions between the cyclophane host and mostly planar aromatic guest molecules can actively modulate excited-state properties in a more advanced way involving both singlet and triplet excited states. We begin by highlighting photofunctional host–guest systems for on–off fluorescence switching and chiroptical functions using bay-functionalized perylene bisimide cyclophanes. Next, we examine the impact of π-extension in perylene bisimide cyclophanes for multiple guest binding, showcasing photofunctional properties including circularly polarized luminescence (CPL). We then focus on triplet-generating cyclophanes, i.e. coronene bisimide cyclophane, with high intersystem crossing (ISC) rates, where we demonstrate modulation of excited state pathways upon guest encapsulation and triplet sensitization through phosphorescence and thermally activated delayed fluorescence (TADF). Furthermore, using supramolecular strategies, we advance non-covalent designs, involving either heavy-atom-based Pt(acac)2 guests or heavy-atom free charge transfer complexes, for triplet harvesting under ambient conditions and demonstrate the role of supramolecular nanoenvironments in stabilizing triplet excitons in aerated solutions. Additionally, we showcase examples for triplet–triplet annihilation (TTA) upconversion in defined cyclophane complexes in aqueous solutions and the application of host–guest chemistry in organic light-emitting diodes (OLEDs).
• Association between sociodemographic variables, healthy habits and stress with metabolic syndrome. A descriptive, cross-sectional study. López-González, Á A; Martínez-Almoyna Rifá, E; Paublini Oliveira, H; Martorell Sánchez, C; Tárraga López, P J; Ramírez-Manent, J I (2025). 51(6) 102455–102455.

  INTRODUCTION: Metabolic syndrome (MS) is a pathological condition that encompasses various cardiometabolic risk factors, such as obesity, dyslipidemia, hyperglycemia, and elevated blood pressure levels. It is considered a multifactorial pathological condition. The aim of this study is to assess how variables such as age, sex, socioeconomic status, tobacco and alcohol consumption, physical activity, adherence to the Mediterranean diet, and stress are associated with the prevalence of MS, determined using two different criteria. MATERIALS AND METHODS: This is a descriptive, cross-sectional study conducted on 24,224 Spanish workers, evaluating the association between sociodemographic variables, health habits, and stress with MS, determined using two criteria: the National Cholesterol Education Program, Adult Treatment Panel III (NCEP ATP-III), and the International Diabetes Federation (IDF). RESULTS: All the variables analyzed showed an association with the presence of MS when applying both criteria. Among them, the variables with the strongest association were age: odds ratio 5.55 (95% CI: 4.80-6.30) for MS using the NCEP ATP-III criteria and 6.71 (95% CI: 5.30-8.13) for IDF criteria; and type of job: odds ratio 3.42 (95% CI: 2.95-3.90) for NCEP ATP-III and 3.57 (95% CI: 3.12-4.03) for IDF. CONCLUSIONS: The profile of an individual at higher risk of developing MS under both criteria would be an older male, manual laborer, smoker, habitual alcohol consumer, sedentary, with low adherence to the Mediterranean diet, and experiencing high levels of stress.
• Gravitational Effects of a Small Primordial Black Hole Passing Through the Human Body. Scherrer, Robert J. (2025).
• Gravitational Effects of a Small Primordial Black Hole Passing Through the Human Body. Scherrer, Robert J. (2025).
• DESI dark secrets. Abreu, Matilde Lopes; Turner, Michael S. (2025).
• DESI dark secrets. Abreu, Matilde Lopes; Turner, Michael S. (2025).
• Efficacy and Safety of Glucagon-Like Peptide-1 Receptor Agonists for Weight Loss Among Adults Without Diabetes: A Systematic Review of Randomized Controlled Trials. Moiz, Areesha; Filion, Kristian B.; Toutounchi, Helia; Tsoukas, Michael A.; Yu, Oriana H.Y.; Peters, Tricia M.; Eisenberg, Mark J. (2025).
• Malaria vaccine introduction in Africa: progress and challenges. Impouma, Benido; Adidja, Amani; Mboussou, Franck; Cabore, Joseph; Moeti, Matshidiso (2025). 405(10478) 521–524.
• GEE‐PICX: generating cloud‐free Sentinel‐2 and Landsat image composites and spectral indices for custom areas and time frames – a Google Earth Engine web application. Pflumm, Luisa; Kang, Hyeonmin; Wilting, Andreas; Niedballa, Jürgen (2025).
• Assessing the suitability of a one-time sampling event for close-kin mark-recapture: A caribou case study. Merriell, Brandon D.; Manseau, Micheline; Wilson, Paul J. (2024). 14(9) e70230.

  Abstract Abundance estimation is frequently an objective of conservation and monitoring initiatives for threatened and other managed populations. While abundance estimation via capture–mark–recapture or spatially explicit capture–recapture is now common, such approaches are logistically challenging and expensive for species such as boreal caribou (Rangifer tarandus), which inhabit remote regions, are widely dispersed, and exist at low densities. Fortunately, the recently developed ‘close-kin mark–recapture’ (CKMR) framework, which uses the number of kin pairs obtained within a sample to generate an abundance estimate, eliminates the need for multiple sampling events. As a result, some caribou managers are interested in using this method to generate an abundance estimate from a single, non-invasive sampling event for caribou populations. We conducted a simulation study using realistic boreal caribou demographic rates and population sizes to assess how population size and the proportion of the population surveyed impact the accuracy and precision of single-survey CKMR-based abundance estimates. Our results indicated that abundance estimates were biased and highly imprecise when very small proportions of the population were sampled, regardless of the population size. However, the larger the population size, the smaller the required proportion of the population surveyed to generate both accurate and reasonably precise estimates. Additionally, we also present a case study in which we used the CKMR framework to generate annual female abundance estimates for a small caribou population in Jasper National Park, Alberta, Canada, from 2006 to 2015 and compared them to existing published capture–mark–recapture-based estimates. Both the accuracy and precision of the annual CKMR-based abundance estimates varied across years and were sensitive to the proportion of pairwise kinship comparisons which yielded a mother–offspring pair. Taken together, our study demonstrates that it is possible to generate CKMR-based abundance estimates from a single sampling event for small caribou populations, so long as a sufficient sampling intensity can be achieved.
• A Study of Cat Facial Landmark Detection Using HRNetV2. Ishihara, Hideyasu; Goto, Tomio (2024). 30–34.
• A Time-Distributed CNN-LSTM with Attention Model for Speech Based Emotion Recognition. Deshpande, Kedar; Sodhi, Manjit Singh; Raniyer, Nidhi; Rao, Madhav (2024). 67–71.
• Optimizing Medical Imaging: High-Performance Hardware for Image Processing, Machine Learning. Surya, Kalyan Chakravarthy Nidamanuri; Balapanur, Mouli Chandra; Pandian, Arun Nambi; Pulikanti, Jyothi; D, Prasad; Masood, Jafar Ali Ibrahim Syed (2024). 112–116.
• Revolutionizing Medical Diagnostics: Cutting-Edge Image Detection and Recognition Techniques. M, Sharada Mani; S, Shaik Heena; Babu, Jajula Hari; S, Sarath Chandra; M, Mohamed Kalith Oli (2024). 42–46.
• Unveiling the Complexities of the Human Body: Advanced Computational Anatomy for Precision Medicine. A, Lakshmi Parvathi; V, Lavanya; M, Muthamizh Selvam; I, Venu Gopal; R, Raihana Parveen; V, Vijayarajan (2024). 117–123.
• Deep Learning in Medical Imaging: Image Processing - From Augmenting Accuracy to Enhancing Efficiency. Prasad, G. Lakshmi Vara; A, Murali; V, Bhaskar Reddy Y.; Marturi, Haribabu; Paul, Valeru Vision (2024). 101–106.
• Improvement of Face Detection Accuracy for Blurred Mask Wearers. Kito, Koshi; Goto, Tomio (2024). 11–16.
• Progressive Enhancement of Anatomical Structural and Medical Feature Learning for Cephalometric Landmark Detection. Li, Mengqi; Qi, Senrong; Zhu, Xuemei; Niu, Kai; Han, Jianhui; Li, Ying; He, Zhiqiang (2024). 22–29.
• Detecting Bacteria from Gram Stained Smears Images by the Family of YOLOs. Kashino, Ukyo; Taira, Kyosuke; Hirata, Kouichi (2024). 6–10.
• Harnessing Medical Big Data: Integrating Computational Insights for Enhanced Patient Outcomes. Masood, Jafar Ali Ibrahim Syed; Vinayagam, Jai Kumar; Onteru, Ranjit Kumar; Kopparapu, Umamaheswararao; Parabathini, Bulah Pushpa Rani (2024). 94–100.
• Detecting Phagocytotic Activity of Leukocytes in Gram Stained Smears Images. Nakajo, Ryunosuke; Hirata, Kouichi (2024). 17–21.
• Transformative Techniques in Medical Imaging: Advancing Precision through Computer Vision and Image Analysis. A, Swathi; Prasad, Siva; M, Madhavi; Gopal, Venu; K, Nihaal Ahmed. (2024). 107–111.
• Deblurred Image Quality Improvement by Learning-based Deblurring Method Utilizing ConvNeXt-V2. Aoi, Masaki; Goto, Tomio (2024). 62–66.
• Detection of Diabetic Retinopathy in Retinal Fundus Images Using Gabor Filters and ConvNeXt. Kurniawan, Adrian Richardy; Irmawati, Irmawati (2024). 47–52.
• Hardware Implementation of Image Processing Morphological and Convolution Operations as SoC on FPGAs. Moussa, Alfred M.; Groves, Richard; Rafla, Nader (2024). 72–77.
• Advanced Medical Image Reconstruction Using the Dual Encoder Split Path Autoencoder (DESPAE) Architecture. Mohammadi, Khatereh; Hadoune, Oussama; Belhaouari, Samir Brahim (2024). 78–83.
• Vision Transformer for Audio-Based Depression Detection on Multi-Lingual Audio Data. Pratiwi, Monica; Sanjaya, Samuel Ady (2024). 35–41.
• Deep Learning Assisted Anatomical Landmark Segmentation in Endoscopic Third Ventriculostomy Videos. Reddy, Pranav; Prudhvi, Madamanchi; Deepika, Pon; Vazhayil, Vikas; Rao, Madhav (2024). 88–93.
• Predicting Yeast-Like Fungi from Gram Stained Smears Images. Tanaka, Tsubasa; Kagemoto, Kouya; Hirata, Kouichi (2024). 84–87.
• Improved CPSoS Security: An Enhanced Anomaly-Based Intrusion Detection Architecture. Stadler, Marco; Riegler, Michael; Sametinger, Johannes; Schönegger, Christoph in Communications in Computer and Information Science, B. Moser, L. Fischer, A. Mashkoor, J. Sametinger, A.-C. Glock, M. Mayr, S. Luftensteiner (eds.) (2024). (Vol. 2169) 3–13.
• Risk Assessment in AI System Engineering: Experiences and Lessons Learned from a Practitioner’s Perspective. Fuchs, Magdalena; Fischer, Lukas; Montuoro, Alessio; Kumar, Mohit; Moser, Bernhard Alois in Communications in Computer and Information Science, B. Moser, L. Fischer, A. Mashkoor, J. Sametinger, A.-C. Glock, M. Mayr, S. Luftensteiner (eds.) (2024). (Vol. 2169) 67–76.
• Uncertainty Estimation for Energy Consumption Nowcasting. Rey-Arnal, Danel; Laña, Ibai; Bringas, Pablo García in Communications in Computer and Information Science, B. Moser, L. Fischer, A. Mashkoor, J. Sametinger, A.-C. Glock, M. Mayr, S. Luftensteiner (eds.) (2024). (Vol. 2169) 102–114.
• FLocalX - Local to Global Fuzzy Explanations for Black Box Classifiers. Fernández, Guillermo; Guidotti, Riccardo; Giannotti, Fosca; Setzu, Mattia; Aledo, Juan A.; Gámez, José A.; Puerta, José M. in Lecture Notes in Computer Science, I. Miliou, N. Piatkowski, P. Papapetrou (eds.) (2024). (Vol. 14642) 197–209.
• Messung, Modellierung und Vorhersage der Netzwerkqualität mit Fokus auf das Internet der Dinge (IoT). Technical Report (PhD dissertation), Herrnleben, Stefan (2024).
• Messung, Modellierung und Vorhersage der Netzwerkqualität mit Fokus auf das Internet der Dinge (IoT). Technical Report (PhD dissertation), Herrnleben, Stefan (2024).
• Messung, Modellierung und Vorhersage der Netzwerkqualität mit Fokus auf das Internet der Dinge (IoT). Technical Report (PhD dissertation), Herrnleben, Stefan (2024).
• Multi-target Stain Normalization for Histology Slides. Ivanov, Desislav Nikolaev; Barbano, Carlo Alberto; Grangetto, Marco in Lecture Notes in Computer Science, Y. Huo, B. A. Millis, Y. Zhou, K. Younis, X. Wang, Y. Tang (eds.) (2024). (Vol. 15371) 36–44.
• Intensity Inhomogeneity Correction for Large Panoramic Electron Microscopy Images. Dzyubachyk, Oleh; Koster, Abraham J.; Lelieveldt, Boudewijn P. F. in Lecture Notes in Computer Science, Y. Huo, B. A. Millis, Y. Zhou, K. Younis, X. Wang, Y. Tang (eds.) (2024). (Vol. 15371) 45–54.
• From Feature Maps to Few-Shot Cell Segmentation. Vadineanu, Serban; Pelt, Daniël Maria; Dzyubachyk, Oleh; Batenburg, Kees Joost in Lecture Notes in Computer Science, Y. Huo, B. A. Millis, Y. Zhou, K. Younis, X. Wang, Y. Tang (eds.) (2024). (Vol. 15371) 14–24.
• On the Solvability of the XOR Problem by Spiking Neural Networks. Moser, Bernhard Alois; Lunglmayr, Michael in Communications in Computer and Information Science, B. Moser, L. Fischer, A. Mashkoor, J. Sametinger, A.-C. Glock, M. Mayr, S. Luftensteiner (eds.) (2024). (Vol. 2169) 57–66.
• Knowledge Guided Clustering Medieval Polychromy. Sobieczky, Florian; Sobieczky, Elisabeth in Communications in Computer and Information Science, B. Moser, L. Fischer, A. Mashkoor, J. Sametinger, A.-C. Glock, M. Mayr, S. Luftensteiner (eds.) (2024). (Vol. 2169) 115–125.
• An Automated Ontology-Based Requirements Traceability Technique in Agile Software Development Context. Khan, Saif Ur Rehman; Aslam, Uswa; Mashkoor, Atif; Inayat, Irum; Nisa, Habib Un in Communications in Computer and Information Science, B. Moser, L. Fischer, A. Mashkoor, J. Sametinger, A.-C. Glock, M. Mayr, S. Luftensteiner (eds.) (2024). (Vol. 2169) 29–43.
• Assessing the Maturity of Blockchain-Based Implementations with Software Reliability Growth Models. Azeem, Muhammad; Khan, Saif Ur Rehman; Mashkoor, Atif; Yousafzai, Abdullah; Nisa, Habib Un in Communications in Computer and Information Science, B. Moser, L. Fischer, A. Mashkoor, J. Sametinger, A.-C. Glock, M. Mayr, S. Luftensteiner (eds.) (2024). (Vol. 2169) 14–28.
• Ground‐dwelling mammal and bird diversity in the southern Annamites: Exploring complex habitat associations and the ghost of past hunting pressure. Nguyen, An; Tilker, Andrew; Le, Duy; Niedballa, Jürgen; Pflumm, Luisa; Pham, Xuan Hoan; Le, Van Son; Luu, Hong Truong; Tran, Van Bang; Kramer‐Schadt, Stephanie; Sollmann, Rahel; Wilting, Andreas (2024). 6(4)
• Uncertainty Estimation of Raters’ Performance and Ground Truth Through a Bayesian Extension of STAPLE. Cazzorla, Davide; Mencar, Corrado in Communications in Computer and Information Science, B. Moser, L. Fischer, A. Mashkoor, J. Sametinger, A.-C. Glock, M. Mayr, S. Luftensteiner (eds.) (2024). (Vol. 2169) 91–101.
• Development of Peptide-Based Probes for Molecular Imaging of the Postsynaptic Density in the Brain. Fernandes, Eduardo F. A.; Palner, Mikael; Raval, Nakul Ravi; Jeppesen, Troels E.; Danková, Daniela; Bærentzen, Simone L.; Werner, Christian; Eilts, Janna; Maric, Hans M.; Doose, Sören; Aripaka, Sanjay Sagar; Kaalund, Sanne Simone; Aznar, Susana; Kjaer, Andreas; Schlosser, Andreas; Haugaard-Kedström, Linda M.; Knudsen, Gitte M.; Herth, Matthias M.; Stro̷mgaard Kristian (2024). 67(14) 11975–11988.

  The postsynaptic density (PSD) comprises numerous scaffolding proteins, receptors, and signaling molecules that coordinate synaptic transmission in the brain. Postsynaptic density protein 95 (PSD-95) is a master scaffold protein within the PSD and one of its most abundant proteins and therefore constitutes a very attractive biomarker of PSD function and its pathological changes. Here, we exploit a high-affinity inhibitor of PSD-95, AVLX-144, as a template for developing probes for molecular imaging of the PSD. AVLX-144-based probes were labeled with the radioisotopes fluorine-18 and tritium, as well as a fluorescent tag. Tracer binding showed saturable, displaceable, and uneven distribution in rat brain slices, proving effective in quantitative autoradiography and cell imaging studies. Notably, we observed diminished tracer binding in human post-mortem Parkinson’s disease (PD) brain slices, suggesting postsynaptic impairment in PD. We thus offer a suite of translational probes for visualizing and understanding PSD-related pathologies.
• The neuropeptide pigment-dispersing factor signals independently of Bruchpilot-labelled active zones in daily remodelled terminals of Drosophila clock neurons. Hofbauer, Benedikt; Zandawala, Meet; Reinhard, Nils; Rieger, Dirk; Werner, Christian; Evers, Jan Felix; Wegener, Christian (2024). 59(10) 2665–2685.

  The small ventrolateral neurons (sLNvs) are key components of the central clock in the Drosophila brain. They signal via the neuropeptide pigment-dispersing factor (PDF) to align the molecular clockwork of different central clock neurons and to modulate downstream circuits. The dorsal terminals of the sLNvs undergo daily morphological changes that affect presynaptic sites organised by the active zone protein Bruchpilot (BRP), a homolog of mammalian ELKS proteins. However, the role of these presynaptic sites for PDF release is ill-defined. Here, we combined expansion microscopy with labelling of active zones by endogenously tagged BRP to examine the spatial correlation between PDF-containing dense-core vesicles and BRP-labelled active zones. We found that the number of BRP-labelled puncta in the sLNv terminals was similar while their density differed between Zeitgeber time (ZT) 2 and 14. The relative distance between BRP- and PDF-labelled puncta was increased in the morning, around the reported time of PDF release. Spontaneous dense-core vesicle release profiles of sLNvs in a publicly available ssTEM dataset (FAFB) consistently lacked spatial correlation to BRP-organised active zones. RNAi-mediated downregulation of brp and other active zone proteins expressed by the sLNvs did not affect PDF-dependent locomotor rhythmicity. In contrast, down-regulation of genes encoding proteins of the canonical vesicle release machinery, the dense-core vesicle-related protein CADPS, as well as PDF impaired locomotor rhythmicity. Taken together, our study suggests that PDF release from the sLNvs is independent of BRP-organised active zones, while BRP may be redistributed to active zones in a time-dependent manner.
• Deep Learning Based Image Detection Model for Pavement Cracks and Potholes. Byun, Joonho; Byun, Siwoo (2024). 1–5.
• Toward a Knowledge-Based Anomaly Identification System for Detecting Anomalies in the Smart Grid. Paudel, Sarita; Shaaban, Abdelkader Magdy in Communications in Computer and Information Science, B. Moser, L. Fischer, A. Mashkoor, J. Sametinger, A.-C. Glock, M. Mayr, S. Luftensteiner (eds.) (2024). (Vol. 2169) 44–53.
• Adaptive Weighted-Rosette Trajectories Based on Sparse Models and Nuclear Norm Regularization for Fast MRI Restoration. Xu, Wen; Tian, Qiaoyu; Xu, Qiuyi; Liao, Junmei; Xu, Jin (2024). 53–61.
• PS-SA: An Efficient Self-Attention via Progressive Sampling for User Behavior Sequence Modeling. Hu, Jiacen; Chan, Zhangming; Zhang, Yu; Han, Shuguang; Lou, Siyuan; Liu, Baolin; Zhu, Han; Jiang, Yuning; Xu, Jian; Zheng, Bo I. Frommholz, F. Hopfgartner, M. Lee, M. Oakes, M. Lalmas, M. Zhang, R. L. T. Santos (eds.) (2023). 4639–4645.
• COPR: Consistency-Oriented Pre-Ranking for Online Advertising. Zhao, Zhishan; Gao, Jingyue; Zhang, Yu; Han, Shuguang; Lou, Siyuan; Sheng, Xiang-Rong; Wang, Zhe; Zhu, Han; Jiang, Yuning; Xu, Jian; Zheng, Bo I. Frommholz, F. Hopfgartner, M. Lee, M. Oakes, M. Lalmas, M. Zhang, R. L. T. Santos (eds.) (2023). 4974–4980.
• Leveraging Watch-time Feedback for Short-Video Recommendations: A Causal Labeling Framework. Zhang, Yang; Bai, Yimeng; Chang, Jianxin; Zang, Xiaoxue; Lu, Song; Lu, Jing; Feng, Fuli; Niu, Yanan; Song, Yang I. Frommholz, F. Hopfgartner, M. Lee, M. Oakes, M. Lalmas, M. Zhang, R. L. T. Santos (eds.) (2023). 4952–4959.
• Rec4Ad: A Free Lunch to Mitigate Sample Selection Bias for Ads CTR Prediction in Taobao. Gao, Jingyue; Han, Shuguang; Zhu, Han; Yang, Siran; Jiang, Yuning; Xu, Jian; Zheng, Bo I. Frommholz, F. Hopfgartner, M. Lee, M. Oakes, M. Lalmas, M. Zhang, R. L. T. Santos (eds.) (2023). 4574–4580.
• Provectories: Embedding-Based Analysis of Interaction Provenance Data. Walchshofer, Conny; Hinterreiter, Andreas; Xu, Kai; Stitz, Holger; Streit, Marc (2023). 29(12) 4816–4831.

  Understanding user behavior patterns and visual analysis strategies is a long-standing challenge. Existing approaches rely largely on time-consuming manual processes such as interviews and the analysis of observational data. While it is technically possible to capture a history of user interactions and application states, it remains difficult to extract and describe analysis strategies based on interaction provenance. In this article, we propose a novel visual approach to the meta-analysis of interaction provenance. We capture single and multiple user sessions as graphs of high-dimensional application states. Our meta-analysis is based on two different types of two-dimensional embeddings of these high-dimensional states: layouts based on (i) topology and (ii) attribute similarity. We applied these visualization approaches to synthetic and real user provenance data captured in two user studies. From our visualizations, we were able to extract patterns for data types and analytical reasoning strategies.
• Neural Model-Applying Network (Neuman): A New Basis for Computational Cognition. Roth, Frederick T. Ray, R. A. Sarker, X. Li (eds.) (2023).
• GIFT: Graph-guIded Feature Transfer for Cold-Start Video Click-Through Rate Prediction. Cao, Yi; Hu, Sihao; Gong, Yu; Li, Zhao; Yang, Yazheng; Liu, Qingwen; Ji, Shouling M. A. Hasan, L. Xiong (eds.) (2022). 2964–2973.
• Query Rewriting in TaoBao Search. Li, Sen; Lv, Fuyu; Jin, Taiwei; Li, Guiyang; Zheng, Yukun; Zhuang, Tao; Liu, Qingwen; Zeng, Xiaoyi; Kwok, James T.; Ma, Qianli M. A. Hasan, L. Xiong (eds.) (2022). 3262–3271.
• GCF-RD: A Graph-based Contrastive Framework for Semi-Supervised Learning on Relational Databases. Chen, Runjin; Li, Tong; Shen, Yanyan; Qiu, Luyu; Li, Kaidi; Cao, Caleb Chen M. A. Hasan, L. Xiong (eds.) (2022). 222–231.
• FwSeqBlock: A Field-wise Approach for Modeling Behavior Representation in Sequential Recommendation. Qian, Hao; Wu, Qintong; Li, Minghao; Wu, Zhengwei; Zhang, Zhiqiang; Zhou, Jun; Gu, Lihong; Gu, Jinjie M. A. Hasan, L. Xiong (eds.) (2022). 4404–4408.
• Anti–contactin-1 Antibodies Affect Surface Expression and Sodium Currents in Dorsal Root Ganglia. Grüner, Julia; Stengel, Helena; Werner, Christian; Appeltshauser, Luise; Sommer, Claudia; Villmann, Carmen; Doppler, Kathrin (2021). 8(5) e1056-.

  Background and Objectives: As autoantibodies to contactin-1 from patients with chronic inflammatory demyelinating polyradiculoneuropathy not only bind to the paranodes where they are supposed to cause conduction failure but also bind to other neuronal cell types, we aimed to investigate the effect of anti–contactin-1 autoantibodies on contactin-1 surface expression in cerebellar granule neurons, dorsal root ganglion neurons, and contactin-1–transfected human embryonic kidney 293 cells. Methods: Immunocytochemistry including structured illumination microscopy and immunoblotting was used to determine expression levels of contactin-1 and/or sodium channels after long-term exposure to autoantibodies from 3 seropositive patients. For functional analysis of sodium channels, whole-cell recordings of sodium currents were performed on dorsal root ganglion neurons incubated with anti–contactin-1 autoantibodies. Results: We found a reduction in contactin-1 expression levels on dorsal root ganglion neurons, cerebellar granule neurons, and contactin-1–transfected human embryonic kidney 293 cells and decreased dorsal root ganglion sodium currents after long-term exposure to anti–contactin-1 autoantibodies. Sodium channel density did not decrease. Discussion: Our results demonstrate a direct effect of anti–contactin-1 autoantibodies on the surface expression of contactin-1 and sodium currents in dorsal root ganglion neurons. This may be the pathophysiologic correlate of sensory ataxia reported in these patients.
• SIFN: A Sentiment-aware Interactive Fusion Network for Review-based Item Recommendation. Zhang, Kai; Qian, Hao; Liu, Qi; Zhang, Zhiqiang; Zhou, Jun; Ma, Jianhui; Chen, Enhong G. Demartini, G. Zuccon, J. S. Culpepper, Z. Huang, H. Tong (eds.) (2021). 3627–3631.
• Self-Supervised Learning on Users’ Spontaneous Behaviors for Multi-Scenario Ranking in E-commerce. Gu, Yulong; Bao, Wentian; Ou, Dan; Li, Xiang; Cui, Baoliang; Ma, Biyu; Huang, Haikuan; Liu, Qingwen; Zeng, Xiaoyi G. Demartini, G. Zuccon, J. S. Culpepper, Z. Huang, H. Tong (eds.) (2021). 3828–3837.
• EdgeRec: Recommender System on Edge in Mobile Taobao. Gong, Yu; Jiang, Ziwen; Feng, Yufei; Hu, Binbin; Zhao, Kaiqi; Liu, Qingwen; Ou, Wenwu M. d’Aquin, S. Dietze, C. Hauff, E. Curry, P. Cudré-Mauroux (eds.) (2020). 2477–2484.
• MTBRN: Multiplex Target-Behavior Relation Enhanced Network for Click-Through Rate Prediction. Feng, Yufei; Lv, Fuyu; Hu, Binbin; Sun, Fei; Kuang, Kun; Liu, Yang; Liu, Qingwen; Ou, Wenwu M. d’Aquin, S. Dietze, C. Hauff, E. Curry, P. Cudré-Mauroux (eds.) (2020). 2421–2428.
• On Multiview Robustness of 3D Adversarial Attacks. Yao, Philip; So, Andrew; Chen, Tingting; Ji, Hao G. A. Jacobs, C. A. Stewart (eds.) (2020). 372–378.
• Anti-CNTN1 IgG3 induces acute conduction block and motor deficits in a passive transfer rat model. Doppler, Kathrin; Schuster, Yasmin; Appeltshauser, Luise; Biko, Lydia; Villmann, Carmen; Weishaupt, Andreas; Werner, Christian; Sommer, Claudia (2019). 16(1) 73-.

  Autoantibodies against the paranodal protein contactin-1 have recently been described in patients with severe acute-onset autoimmune neuropathies and mainly belong to the IgG4 subclass that does not activate complement. IgG3 anti-contactin-1 autoantibodies are rare, but have been detected during the acute onset of disease in some cases. There is evidence that anti-contactin-1 prevents adhesive interaction, and chronic exposure to anti-contactin-1 IgG4 leads to structural changes at the nodes accompanied by neuropathic symptoms. However, the pathomechanism of acute onset of disease and the pathogenic role of IgG3 anti-contactin-1 is largely unknown.
• Hierarchical Multi-label Text Classification: An Attention-based Recurrent Network Approach. Huang, Wei; Chen, Enhong; Liu, Qi; Chen, Yuying; Huang, Zai; Liu, Yang; Zhao, Zhou; Zhang, Dan; Wang, Shijin W. Zhu, D. Tao, X. Cheng, P. Cui, E. A. Rundensteiner, D. Carmel, Q. He, J. X. Yu (eds.) (2019). 1051–1060.
• Triangulated categories of mixed motives. Cisinski, Denis-Charles; Déglise, Frédéric (2019).
• Cross-modal Image-Text Retrieval with Multitask Learning. Luo, Junyu; Shen, Ying; Ao, Xiang; Zhao, Zhou; Yang, Min W. Zhu, D. Tao, X. Cheng, P. Cui, E. A. Rundensteiner, D. Carmel, Q. He, J. X. Yu (eds.) (2019). 2309–2312.
• Query-based Interactive Recommendation by Meta-Path and Adapted Attention-GRU. Zhu, Yu; Gong, Yu; Liu, Qingwen; Ma, Yingcai; Ou, Wenwu; Zhu, Junxiong; Wang, Beidou; Guan, Ziyu; Cai, Deng W. Zhu, D. Tao, X. Cheng, P. Cui, E. A. Rundensteiner, D. Carmel, Q. He, J. X. Yu (eds.) (2019). 2585–2593.
• What You Look Matters?: Offline Evaluation of Advertising Creatives for Cold-start Problem. Zhao, Zhichen; Li, Lei; Zhang, Bowen; Wang, Meng; Jiang, Yuning; Xu, Li; Wang, Fengkun; Ma, Wei-Ying W. Zhu, D. Tao, X. Cheng, P. Cui, E. A. Rundensteiner, D. Carmel, Q. He, J. X. Yu (eds.) (2019). 2605–2613.
• Practical Machine Learning with Python Sarkar, Dipanjan; Bali, Raghav; Sharma, Tushar (2018). Apress.

  Master the essential skills needed to recognize and solve complex problems with machine learning and deep learning. Using real-world examples that leverage the popular Python machine learning ecosystem, this book is your perfect companion for learning the art and science of machine learning to become a successful practitioner. The concepts, techniques, tools, frameworks, and methodologies used in this book will teach you how to think, design, build, and execute machine learning systems and projects successfully. Practical Machine Learning with Python follows a structured and comprehensive three-tiered approach packed with hands-on examples and code. Part 1 focuses on understanding machine learning concepts and tools. This includes machine learning basics with a broad overview of algorithms, techniques, concepts and applications, followed by a tour of the entire Python machine learning ecosystem. Brief guides for useful machine learning tools, libraries andframeworks are also covered. Part 2 details standard machine learning pipelines, with an emphasis on data processing analysis, feature engineering, and modeling. You will learn how to process, wrangle, summarize and visualize data in its various forms. Feature engineering and selection methodologies will be covered in detail with real-world datasets followed by model building, tuning, interpretation and deployment. Part 3 explores multiple real-world case studies spanning diverse domains and industries like retail, transportation, movies, music, marketing, computer vision and finance. For each case study, you will learn the application of various machine learning techniques and methods. The hands-on examples will help you become familiar with state-of-the-art machine learning tools and techniques and understand what algorithms are best suited for any problem. Practical Machine Learning with Python will empower you to start solving your own problems with machine learning today! What You'll Learn Execute end-to-end machine learning projects and systems Implement hands-on examples with industry standard, open source, robust machine learning tools and frameworks Review case studies depicting applications of machine learning and deep learning on diverse domains and industries Apply a wide range of machine learning models including regression, classification, and clustering. Understand and apply the latest models and methodologies from deep learning including CNNs, RNNs, LSTMs and transfer learning. Who This Book Is For IT professionals, analysts, developers, data scientists, engineers, graduate students
• Cross-domain Aspect/Sentiment-aware Abstractive Review Summarization. Yang, Min; Qu, Qiang; Zhu, Jia; Shen, Ying; Zhao, Zhou A. Cuzzocrea, J. Allan, N. W. Paton, D. Srivastava, R. Agrawal, A. Z. Broder, M. J. Zaki, K. S. Candan, A. Labrinidis, A. Schuster, H. Wang (eds.) (2018). 1531–1534.
• Quantification of sweat gland innervation in patients with Fabry disease: A case-control study. Kokotis, Panagiotis; Üçeyler, Nurcan; Werner, Christian; Tsivgoulis, Georgios; Papanikola, Nektaria; Katsanos, Aristeidis H.; Karandreas, Nikos; Sommer, Claudia (2018). 390 135–138.

  Hypohidrosis and heat intolerance, frequently reported by men and women with Fabry disease (FD), is thought to be related not only to the deposition of globotriaosylceramide (Gb3) in eccrine sweat glands, but also to reduced sweat gland sympathetic innervation. Methods We performed a case-control study to compare the density of sweat gland innervation between patients with FD and healthy controls by examining lower leg skin punch biopsies. We used a standardized grid of circles superimposed upon the immunofluorescent specimen to create a simple pattern of circles over the sweat gland. Nerve fibers that crossed within the circles were manually counted (“crossed circles”). Nerve fibers that touched the edge of the circle but did not enter were spared (“uncrossed circles”). The percentage of crossed circles from all circles was determined. Results Biopsy specimens were available of 37 FD patients (median age 44 years, 19–67; n = 18 men) and 16 controls (median age 48 years, 24–83, n = 7 men). Totally there were 153 sweat glands from FD patients and 63 from controls, in which innervation was quantified. While mean sweat gland innervation per biopsy did not differ between the entire FD cohort and controls, data stratification for the reported sweating phenotype revealed a stepwise lower innervation in women with FD and hypohidrosis (n.s.) and anhidrosis (p < .05) compared to women reporting normal sweating. Conclusion Sweat gland innervation is reduced in women with FD and anhidrosis compared to female patients without sweating impairment. Loss of sweat gland innervation may play a role in FD associated anhidrosis, at least in women.
• Integrating Side Information for Boosting Machine Comprehension. Wang, Yutong; Xu, Yixin; Yang, Min; Zhao, Zhou; Xiao, Jun; Zhuang, Yueting E.-P. Lim, M. Winslett, M. Sanderson, A. W.-C. Fu, J. Sun, J. S. Culpepper, E. Lo, J. C. Ho, D. Donato, R. Agrawal, Y. Zheng, C. Castillo, A. Sun, V. S. Tseng, C. Li (eds.) (2017). 2355–2358.
• Defective synaptic transmission causes disease signs in a mouse model of juvenile neuronal ceroid lipofuscinosis. Grünewald, Benedikt; Lange, Maren D; Werner, Christian; O’Leary, Aet; Weishaupt, Andreas; Popp, Sandy; Pearce, David A; Wiendl, Heinz; Reif, Andreas; Pape, Hans C; Toyka, Klaus V; Sommer, Claudia; Geis, Christian (C. Rosenmund, ed.) (2017). 6 e28685-.

  Juvenile neuronal ceroid lipofuscinosis (JNCL or Batten disease) caused by mutations in the CLN3 gene is the most prevalent inherited neurodegenerative disease in childhood resulting in widespread central nervous system dysfunction and premature death. The consequences of CLN3 mutation on the progression of the disease, on neuronal transmission, and on central nervous network dysfunction are poorly understood. We used Cln3 knockout (Cln3Δex1-6) mice and found increased anxiety-related behavior and impaired aversive learning as well as markedly affected motor function including disordered coordination. Patch-clamp and loose-patch recordings revealed severely affected inhibitory and excitatory synaptic transmission in the amygdala, hippocampus, and cerebellar networks. Changes in presynaptic release properties may result from dysfunction of CLN3 protein. Furthermore, loss of calbindin, neuropeptide Y, parvalbumin, and GAD65-positive interneurons in central networks collectively support the hypothesis that degeneration of GABAergic interneurons may be the cause of supraspinal GABAergic disinhibition.
• Dual Learning for Cross-domain Image Captioning. Zhao, Wei; Xu, Wei; Yang, Min; Ye, Jianbo; Zhao, Zhou; Feng, Yabing; Qiao, Yu E.-P. Lim, M. Winslett, M. Sanderson, A. W.-C. Fu, J. Sun, J. S. Culpepper, E. Lo, J. C. Ho, D. Donato, R. Agrawal, Y. Zheng, C. Castillo, A. Sun, V. S. Tseng, C. Li (eds.) (2017). 29–38.
• Training Deep Nets with Sublinear Memory Cost. Chen, Tianqi; Xu, Bing; Zhang, Chiyuan; Guestrin, Carlos (2016).
• Visual Analytics: Data, Analytical and Reasoning Provenance. Varga, Margaret; Varga, Caroline V. L. Lemieux (ed.) (2016). 141–150.

  Analysts and decision makers are increasingly overloaded with vast amounts of data/information which are often dynamic, complex, disparate, conflicting, incomplete and, at times, uncertain. Furthermore, problems and tasks that require their attention can be ambiguous, i.e. they are ill-defined. In order to make sense of complex data and situations and make informed decisions, they utilize their intuition, knowledge and experience. Provenance is fundamental for the user to capture and exploit effectively the explicit data and implicit knowledge within the decision making process. Provenance can usefully be considered at three conceptual levels, namely: data (what), analytical (how) and reasoning (why). This paper explores visual analytics in the exploitation of provenance within the decision making process.
• WEB SERVICE COMPOSITION PROCESSES: A COMPARATIVE STUDY. AlSedrani, Aram; Touir, Ameur (2016). 7(1) 01–21.

  Service composition is the process of constructing new services by combining several existing ones. It considered as one of the complex challenges in distributed and dynamic environment. The composition process includes, in general, the searching for existing services in a specific domain, and selecting the appropriate service, then coordinating composition flow and invoking services. Over the past years, the problem of web service composition has been studied intensively by researchers. Therefore, a significant amount of solutions and new methods to tackle this problem are presented. In this paper, our objective is to investigate algorithms and methodologies to provide a classification of existing methods in each composition phase. Moreover, we aim at conducting a comparative study to discover the main features and limitation in each phase in order to assist future research in this area.
• Exploiting analysis history to support collaborative data analysis. Sarvghad, Ali; Tory, Melanie in GI ’15 (2015). 123–130.

  Coordination is critical in distributed collaborative analysis of multidimensional data. Collaborating analysts need to understand what each person has done and what avenues of analysis remain uninvestigated in order to effectively coordinate their efforts. Although visualization history has the potential to communicate such information, common history representations typically show sequential lists of past work, making it difficult to understand the analytic coverage of the data dimension space (i.e. which data dimensions have been investigated and in what combinations). This makes it difficult for collaborating analysts to plan their next steps, particularly when the number of dimensions is large and team members are distributed. We introduce the notion of representing past analysis history from a dimension coverage perspective to enable analysts to see which data dimensions have been explored in which combinations. Through two user studies, we investigated whether 1) a dimension oriented view improves understanding of past coverage information, and 2) the addition of dimension coverage information aids coordination. Our findings demonstrate that a representation of dimension coverage reduces the time required to identify and investigate unexplored regions and increases the accuracy of this understanding. In addition, it results in a larger overall coverage of the dimension space, one element of effective team coordination.
• Interactions of Human Autoantibodies with Hippocampal GABAergic Synaptic Transmission – Analyzing Antibody-Induced Effects ex vivo. Haselmann, Holger; Röpke, Luise; Werner, Christian; Kunze, Albrecht; Geis, Christian (2015). 6

  Autoantibodies (aAB) to the presynaptic located enzyme glutamate decarboxylase 65 (GAD65) are a characteristic attribute for a variety of autoimmune diseases of the central nervous system including subtypes of limbic encephalitis, stiff person-syndrome, cerebellar ataxia, and Batten’s disease. Clinical signs of hyperexcitability and improvement of disease symptoms upon immunotherapy in some of these disorders suggest a possible pathogenic role of associated aAB. Recent experimental studies report inconsistent results regarding a direct pathogenic influence of anti-GAD65 aAB affecting inhibitory synaptic transmission in central GABAergic pathways. We here provide a method for direct evaluation of aAB-induced pathomechanisms in the intact hippocampal network. Purified patient IgG fractions containing aAB to GAD65 together with fixable lipophilic styryl dyes (FMdyes) are stereotactically injected into the hilus and the dentate gyrus in anesthetized mice. Twenty-four hours after intrahippocampal injection, acute hippocampal slices are prepared and transferred to a patch-clamp recording setup equipped with a fluorescence light source. Intraneural incorporated FMdyes show correct injection site for patch-clamp recording. Whole-cell patch-clamp recordings are performed from granule cells in the dentate gyrus and extracellular stimulation is applied in the border area of the dentate gyrus-hilus region to stimulate GABAergic afferents arising from parvalbumin positive basket cells. GABA-A receptor mediated inhibitory postsynaptic currents (IPSC) and miniature IPSC are recorded after blocking glutamatergic transmission. This approach allows investigation of potential aAB-induced effects on GABA-A receptor signaling ex vivo in an intact neuronal network. This offers several advantages compared to experimental procedures used in previous studies by in vitro AB preincubation of primary neurons or slice preparations. Furthermore, this method requires only small amounts of patient material that are often limited in rare diseases.
• Stiff person-syndrome IgG affects presynaptic GABAergic release mechanisms. Werner, Christian; Haselmann, Holger; Weishaupt, Andreas; Toyka, Klaus V.; Sommer, Claudia; Geis, Christian (2015). 122(3) 357–362.

  The majority of patients with stiff person-syndrome (SPS) are characterized by autoantibodies to glutamate decarboxylase 65 (GAD65). In previous passive-transfer studies, SPS immunoglobulin G (IgG) induced SPS core symptoms. We here provide evidence that SPS-IgG causes a higher frequency of spontaneous vesicle fusions. Sustained GABAergic transmission and presynaptic GABAergic vesicle pool size remained unchanged. Since these findings cannot be attributed to anti-GAD65 autoantibodies alone, we propose that additional autoantibodies with so far undefined antigen specificity might affect presynaptic release mechanisms.
• Truth Discovery in Data Streams: A Single-Pass Probabilistic Approach. Zhao, Zhu; Cheng, James; Ng, Wilfred J. Li, X. S. Wang, M. N. Garofalakis, I. Soboroff, T. Suel, M. Wang (eds.) (2014). 1589–1598.
• SocialTransfer: Transferring Social Knowledge for Cold-Start Cowdsourcing. Zhao, Zhu; Cheng, James; Wei, Furu; Zhou, Ming; Ng, Wilfred; Wu, Yingjun J. Li, X. S. Wang, M. N. Garofalakis, I. Soboroff, T. Suel, M. Wang (eds.) (2014). 779–788.
• A model-based approach for RFID data stream cleansing. Zhao, Zhu; Ng, Wilfred X. wen Chen, G. Lebanon, H. Wang, M. J. Zaki (eds.) (2012). 862–871.
• Leveraging read rates of passive RFID tags for real-time indoor location tracking. Yan, Da; Zhao, Zhu; Ng, Wilfred X. wen Chen, G. Lebanon, H. Wang, M. J. Zaki (eds.) (2012). 375–384.
• Top Manufacturer of Orthocoir Sheets, Coir Cake & China Coir. Coir, We (W. Coir, ed.) (2012).
• Monochromatic and bichromatic reverse nearest neighbor queries on land surfaces. Yan, Da; Zhao, Zhu; Ng, Wilfred X. wen Chen, G. Lebanon, H. Wang, M. J. Zaki (eds.) (2012). 942–951.
• Characterizing users’ visual analytic activity for insight provenance. Gotz, David; Zhou, Michelle X. (2008). 123–130.

  Insight provenance - a historical record of the process and rationale by which an insight is derived - is an essential requirement in many visual analytics applications. While work in this area has relied on either manually recorded provenance (e.g., user notes) or automatically recorded event-based insight provenance (e.g., clicks, drags, and key-presses), both approaches have fundamental limitations. Our aim is to develop a new approach that combines the benefits of both approaches while avoiding their deficiencies. Toward this goal, we characterize userspsila visual analytic activity at multiple levels of granularity. Moreover, we identify a critical level of abstraction, Actions, that can be used to represent visual analytic activity with a set of general but semantically meaningful behavior types. In turn, the action types can be used as the semantic building blocks for insight provenance. We present a catalog of common actions identified through observations of several different visual analytic systems. In addition, we define a taxonomy to categorize actions into three major classes based on their semantic intent. The concept of actions has been integrated into our labpsilas prototype visual analytic system, HARVEST, as the basis for its insight provenance capabilities.
• Handling of Interference Using Power Penalty Analysis and Frequency Assignment Problem Approach in Communication. Kulkarni, Anju V.; Ambudkar, Bhavna J. Bi, K. Chin, C. Dini, L. Lehmann, D. C. Pheanis (eds.) (2008). 18–23.
• Examining Statistics of Workflow Evolution Provenance: A First Study. Lins, Lauro; Koop, David; Anderson, Erik W.; Callahan, Steven P.; Santos, Emanuele; Scheidegger, Carlos E.; Freire, Juliana; Silva, Cláudio T. B. Ludäscher, N. Mamoulis (eds.) (2008). 573–579.

  Provenance (also referred to as audit trail, lineage, and pedigree) captures information about the steps used to generate a given data product. Such information provides documentation that is key to determining data quality and authorship, and necessary for preserving, reproducing, sharing and publishing the data. Workflow design, in particular for exploratory tasks (e.g., creating a visualization, mining a data set), requires an involved, trial-and-error process. To solve a problem, a user has to iteratively refine a workflow to experiment with different techniques and try different parameter values, as she formulates and test hypotheses. The maintenance of detailed provenance (or history) of this process has many benefits that go beyond documentation and result reproducibility. Notably, it supports several operations that facilitate exploration, including the ability to return to a previous workflow version in an intuitive way, to undo bad changes, to compare different workflows, and to be reminded of the actions that led to a particular result [2].
• Probe-It! Visualization Support for Provenance. Del Rio, Nicholas; da Silva, Paulo Pinheiro G. Bebis, R. Boyle, B. Parvin, D. Koracin, N. Paragios, S.-M. Tanveer, T. Ju, Z. Liu, S. Coquillart, C. Cruz-Neira, T. Müller, T. Malzbender (eds.) (2007). 732–741.

  Visualization is a technique used to facilitate the understanding of scientific results such as large data sets and maps. Provenance techniques can also aid in increasing the understanding and acceptance of scientific results by providing access to information about the sources and methods which were used to derive them. Visualization and provenance techniques, although rarely used in combination, may further increase scientists' understanding of results since the scientists may be able to use a single tool to see and evaluate result derivation processes including any final or partial result. In this paper we introduce Probe-It!: a visualization tool for scientific provenance information that enables scientists to move the visualization focus from intermediate and final results to provenance back and forth. To evaluate the benefits of Probe-It!, in the context of maps, this paper presents a quantitative user study on how the tool was used by scientists to discriminate between quality results and results with known imperfections. The study demonstrates that only a very small percentage of the scientists tested can identify imperfections using maps without the help of knowledge provenance and that most scientists, whether GIS experts, subject matter experts (i.e., experts on gravity data maps) or not, can identify and explain several kinds of map imperfections when using maps together with knowledge provenance visualization.
• Provenance and Annotation for Visual Exploration Systems. Groth, D.P.; Streefkerk, K. (2006). 12(6) 1500–1510.

  Exploring data using visualization systems has been shown to be an extremely powerful technique. However, one of the challenges with such systems is an inability to completely support the knowledge discovery process. More than simply looking at data, users will make a semipermanent record of their visualizations by printing out a hard copy. Subsequently, users will mark and annotate these static representations, either for dissemination purposes or to augment their personal memory of what was witnessed. In this paper, we present a model for recording the history of user explorations in visualization environments, augmented with the capability for users to annotate their explorations. A prototype system is used to demonstrate how this provenance information can be recalled and shared. The prototype system generates interactive visualizations of the provenance data using a spatio-temporal technique. Beyond the technical details of our model and prototype, results from a controlled experiment that explores how different history mechanisms impact problem solving in visualization environments are presented.
• QMPE: Estimating Lognormal, Wald, and Weibull RT distributions with a parameter-dependent lower bound. Heathcote, Andrew; Brown, Scott; Cousineau, Denis (2004). 36(2) 277–290.

  We describe and test quantile maximum probability estimator (QMPE), an open-source ANSI Fortran 90 program for response time distribution estimation.1 QMPE enables users to estimate parameters for the ex-Gaussian and Gumbel (1958) distributions, along with three “shifted” distributions (i.e., distributions with a parameter-dependent lower bound): the Lognormal, Wald, and Weibull distributions. Estimation can be performed using either the standard continuous maximum likelihood (CML) method or quantile maximum probability (QMP; Heathcote & Brown, in press). We review the properties of each distribution and the theoretical evidence showing that CML estimates fail for some cases with shifted distributions, whereas QMP estimates do not. In cases in which CML does not fail, a Monte Carlo investigation showed that QMP estimates were usually as good, and in some cases better, than CML estimates. However, the Monte Carlo study also uncovered problems that can occur with both CML and QMP estimates, particularly when samples are small and skew is low, highlighting the difficulties of estimating distributions with parameter-dependent lower bounds.
• Earth System Science Workbench: a data management infrastructure for earth science products. Frew, J.; Bose, R. (2001). 180–189.

  The Earth System Science Workbench (ESSW) is a non-intrusive data management infrastructure for researchers who are also data publishers. An implementation of ESSW to track the processing of locally received satellite imagery is presented, demonstrating the Workbench's transparent and robust support for archiving and publishing data products. ESSW features a Lab Notebook metadata service, an ND-WORM (No Duplicate-Write Once Read Many) storage service, and Web user interface tools. The Lab Notebook logs processes (experiments) and their relationships via a custom API to XML documents stored in a relational database. The ND-WORM provides a managed storage archive for the Lab Notebook by keeping unique file digests and name-space meta-data, also in a relational database. ESSW Notebook tools allow project searching and ordering, and file and meta-data management.
• Defacement : public secrecy and the labor of the negative Taussig, Michael T. (1999). Stanford University Press, Stanford, California.
• Uloga džamije Mehmed-bega Stočanina u formiranju Gornjeg Vakufa: povodom nove izgradnje džamije Hadžijahić, Muhamed; Mujezinović, Mehmed; Hadžiabdić, Fahrija (1971). 48. Odbor islamske zajednice Gornji Vakuf, Gornji Vakuf.