Am 10.11.2018 hatten Einrichtungen und Institute der Leibniz Universität Hannover im Rahmen des Novembers der Wissenschaft erneut die Möglichkeit, einen Einblick in ihre Forschung zu gewähren. Zusammen mit dem Forschungszentrum L3S von der Universität Hannover konnten das Institute for Sustainable Urbanism (ISU) der TU Braunschweig und 1KLANG®, die Marke der PROJEKTIONISTEN® GmbH, das Forschungsprojekt Data4UrbanMobility vorstellen.
Studenten, Schüler und andere Forschungsinteressierte konnten sich über die Ergebnisse in Bezug auf die entwickelten Apps und das Dashboard informieren (s. unter Ergebnisse: https://data4urbanmobility.l3s.uni-hannover.de/index.php/de/ergebnisse/).
Besonders vorgestellt werden konnte dabei die neue iOS-Version der MiC App, die nun auch über eine Apple Watch gesteuert werden kann.

Wir freuen uns über die zahlreichen Gespräche, die geführt werden konnten und die neuen Tester, die uns bei der Citizen Science App „MiC – Move in the City“ unterstützen möchten.

• Integrating the landscape scale supports SAR-based detection and assessment of the phenological development at the field level. Löw, Johannes; Hill, Steven; Otte, Insa; Friedrich, Christoph; Thiel, Michael; Ullmann, Tobias; Conrad, Christopher (2025). 6(161005) 17.

  Climate change and increasing weather and seasonal dynamics challenge agricultural landscapes. To cope with this challenge information on crop performance is key. This study presents a novel framework for bridging landscape-scale vegetation dynamics with field-level crop phenology using Sentinel-1 radar time series. Unlike previous approaches that focus on local algorithm optimisation or SAR feature selection, this work integrates two scales: (1) landscape patterns derived from annual distributions of time series metrics (TSMs) and (2) field-level phenology, both linked to growing degree days (GDD). TSMs were generated through breakpoint analyses over different smoothing intensities for Sentinel-1 polarisation (PolSAR) and interferometric coherence (InSAR) features, capturing crop, orbit and sensor-specific responses. The framework quantifies uncertainties inherent in both remote sensing and ground observations, and evaluates trackable progress (phenological stage detectability) and tracking range (GDD variance around stages) to assess accuracy under variable acquisition geometries, weather and smoothing parameters. Applied to the DEMMIN site (Germany), the analysis revealed consistent TSM-GDD relationships for wheat, rape, and sugar beet, with descriptors such as soil fertility and water availability explaining spatial patterns (R2 ≈ 0.8). Key novelties include the identification of low tracking ranges in drought years, the demonstration of the impact of orbit-specific incidence angles on monitoring fidelity, and the highlighting of Sentinel-1’s ability to resolve phenological variance across fragmented landscapes. By harmonising multi-scale SAR time series with agro-meteorological data, this approach advances transferable methods for operational crop monitoring, supporting precision agriculture and regional yield assessment beyond localised models.
• ‘I dropped a C-bomb into Tolstoy’: one man’s quest to translate War and Peace into ‘bogan Australian’ This article is more than 3 months old. Marsh, Walter (2025).
• HybridReg: Robust 3D Point Cloud Registration with Hybrid Motions. Du, Keyu; Xu, Hao; Li, Haipeng; Qu, Hong; Fu, Chi-Wing; Liu, Shuaicheng T. Walsh, J. Shah, Z. Kolter (eds.) (2025). 2789–2797.
• Efficient Bearing Sensor Data Compression via an Asymmetrical Autoencoder with a Lifting Wavelet Transform Layer. Zhu, Xin; Çetin, Ahmet Enis (2025). 1–5.
• A Hybrid Framework for Predicting Citation Harm from Retracted Papers. Zhao, Jiahui; Li, Hao; Tang, Suqin (2025). 411–416.
• HoloDiT: Exploring 3D Diffusion Transformer Models Using 2D Images. Li, Hao; Zhao, Jiahui; Gu, Daixuan (2025). 7–11.
• Ladder: A Convergence-based Structured DAG Blockchain for High Throughput and Low Latency. Hu, Dengcheng; Wang, Jianrong; Liu, Xiulong; Xu, Hao; Wu, Xujing; Shahzad, Muhammad; Liu, Guyue; Li, Keqiu T. A. Benson, R. N. Mysore (eds.) (2025). 779–794.
• Mind the Location Leakage in LEO Direct-to-Cell Satellite Networks. Liu, Weisen; Lai, Zeqi; Wu, Qian; Li, Hewu; Weng, Yuxuan; Liu, Wei; Zhang, Qi; Li, Jihao; Li, Yuanjie; Liu, Jun M. Blanton, W. Enck, C. Nita-Rotaru (eds.) (2025). 1064–1080.
• BitsAI-CR: Automated Code Review via LLM in Practice. Sun, Tao; Xu, Jian; Li, Yuanpeng; Yan, Zhao; Zhang, Ge; Xie, Lintao; Geng, Lu; Wang, Zheng; Chen, Yueyan; Lin, Qin; Duan, Wenbo; Sui, Kaixin; Zhu, Yuanshuo L. Montecchi, J. Li, D. Poshyvanyk, D. Zhang (eds.) (2025). 274–285.
• Enhancing Code LLM Training with Programmer Attention. Zhang, Yifan; Huang, Chen; Karas, Zachary; Nguyen, Dung Thuy; Leach, Kevin; Huang, Yu L. Montecchi, J. Li, D. Poshyvanyk, D. Zhang (eds.) (2025). 616–620.
• Fast and Scalable Selective Retransmission for RDMA. Huang, Peihao; Chen, Guo; Zhang, Xin; Liu, Can; Wang, Hongyu; Shen, Huijun; Bian, Ying; Lu, Yuanwei; Ruan, Zhenyuan; Li, Bojie; Zhang, Jiansong; Liu, Yongfeng; Chen, Zhigang (2025). 1–10.
• Beschäftigtenorientiertes People Analytics: ein kommentierter Foliensatz Köhne, Sonja; Richthofen, Georg von; Send, Hendrik; Buß, Nele; Klöpper, Miriam (2025, August).

  Datengestützte Analysen sind ein zentrales Tool im Personalmanagement. Das Projekt „Zwischen Autonomie und Überwachung“ zeigt, wie auch Beschäftigte und Betriebsräte davon profitieren können.
• BrokerAS: Towards Fault-tolerant Atomic Cross-chain Swaps. Shi, Gaowei; Liu, Xiulong; Wang, Huan; Li, Yuhan; Xu, Hao; Ma, Liyuan; Li, Keqiu (2025). 1–10.
• Creative Through Constraints: How Old Mechanical Automata Fosters Innovation in Shadow Puppetry. Yao, Yuan; Li, Zhi; Ma, Ben N. Yamashita, V. Evers, K. Yatani, S. X. Ding (eds.) (2025). 159:1–159:7.
• Dedicated prostate DOI-TOF-PET based on the ProVision detection concept. Vo, Hong Phuc; Williams, Themistoklis; Doroud, Katayoun; Williams, Crispin; Rafecas, Magdalena (2025).
• AIGC-CM: An Efficient and Scalable Blockchain Solution for AIGC Copyright Management. Ma, Liyuan; Hu, Dengcheng; Liu, Xiulong; Xu, Hao; Wang, Jianrong; Li, Keqiu (2025). 1–10.
• Tuning Spatial Distributions of Selection Pressure to Suppress Emergence of Resistance. Tunstall, Thomas; Madgwick, Philip G.; Kanitz, Ricardo; Möbius, Wolfram (2024).

  Control measures such as insecticides or antimicrobials are used to contain biological agents such as pathogenic bacteria and vectors of human and plant diseases, respectively. Following control measure application, a resistant subpopulation may eventually rise to such frequency that the control measure will be rendered ineffective: The timescale over which this occurs is the textquotelefteffective lifetimetextquoteright of the control measure. Prolonging this timescale relaxes urgency at which novel control measure needs to be developed. Spatial heterogeneity in control measure application can influence the rate at which resistance to the control measure evolves; in the agricultural context, this fact is exploited by distributing insecticides in mosaics across cropping regions in order to slow the rate of resistance evolution.Contemporary and historical modeling practices, which aim to inform agricultural practices, often employ assumptions which squeeze out the impact of the spatio-temporal heterogeneity endemic to nature. In this paper, we present a minimal model of continuous dispersal and spatio-temporal heterogeneity in selection pressure distribution which exhibits a novel dynamic: The spatial distribution of selection pressure may be tuned in order to minimize the initial rate at which resistance evolves, thus increasing the effective lifetime of a pesticide.Author summary There are many contexts in which humans apply control measures to biological agents: pesticides are applied in fields to kill the pests that damage crops, mosquito nests are distributed to prevent the spread of malaria, and cancer drugs are applied to kill off tumors in humans. These control measures are examples of textquoteleftselection pressurestextquoteright, which select against strains which are susceptible to them. If a mutation occurs which confers resistance, the control agent will select for the resistant strain, thus reducing the efficacy of the control agent as the frequency of resistance increases in the population. This necessitates more of the control agent to be applied, or for a novel control agent to be developed. The former may have unintended consequences on the local environment, and the latter is expensive and time-intensive. It is preferable to carefully tune how the control agent is applied - perhaps instead of one massive compact region of control measure application, it is better to apply the control measure over multiple smaller regions? Here, we use a toy model of motile organisms to demonstrate that an optimal distribution exists for a variety of scenarios.Competing Interest StatementThe authors have declared no competing interest.
• AlN Sputtering Parameter Estimation Using A Multichannel Parallel DCT Neural Network. Luo, Yingyi; Khan, Talha M.; Hamdan, Emadeldeen; Zhu, Xin; Pan, Hongyi; Ozevin, Didem; Çetin, A. Enis (2024). 1–5.
• SkyCastle: Taming LEO Mobility to Facilitate Seamless and Low-latency Satellite Internet Services. Li, Jihao; Li, Hewu; Lai, Zeqi; Wu, Qian; Liu, Weisen; Wang, Xiaomo; Li, Yuanjie; Liu, Jun; Zhang, Qi (2024). 541–550.
• In-Orbit Processing or Not? Sunlight-Aware Task Scheduling for Energy-Efficient Space Edge Computing Networks. Liu, Weisen; Lai, Zeqi; Wu, Qian; Li, Hewu; Zhang, Qi; Li, Zonglun; Li, Yuanjie; Liu, Jun (2024). 881–890.
• Trace-agnostic and Adversarial Training-resilient Website Fingerprinting Defense. Qiao, Litao; Wu, Bang; Li, Heng; Gao, Cuiying; Yuan, Wei; Luo, Xiapu (2024). 211–220.
• Your Mega-Constellations Can Be Slim: A Cost-Effective Approach for Constructing Survivable and Performant LEO Satellite Networks. Lai, Zeqi; Wang, Yibo; Li, Hewu; Wu, Qian; Zhang, Qi; Hou, Yunan; Liu, Jun; Li, Yuanjie (2024). 521–530.
• Service Satisfaction Evaluation from Gaits Using Local Low-level and Global Co-occurrence Features. Li, Hao; Huang, Lulu; Cheng, Wenzhuo; Wang, Xiaoyi; Wu, Chao (2024). 216–222.
• Brief Analysis of False Data Injection Attacks Based on Two Data Modalities in IoTs-based Solar Insecticidal Lamps. Su, Qin; Shu, Lei; Zhao, Qingsong; Yang, Xing; Jiang, Zitian; Fang, Jiarui; Chin, Huihsin (2024). 1–6.
• Online GNN Evaluation Under Test-time Graph Distribution Shifts. Zheng, Xin; Song, Dongjin; Wen, Qingsong; Du, Bo; Pan, Shirui (2024).
• Sleep No Mosquitoes: Compensating Distance-Aware Compression in a VR Audio Game. Li, Zhi; Yao, Yuan F. ’Floyd’ Mueller, P. Kyburz, J. R. Williamson, C. Sas (eds.) (2024). 293:1–293:6.
• Radical Basis Neural Network Based Anti-swing Control for 5-DOF Ship-Mounted Crane. Li, Zhi; Chuanjing, Hou; Liu, Can in Communications in Computer and Information Science, H. Zhang, X. Li, T. Hao, W. Meng, Z. Wu, Q. He (eds.) (2024). (Vol. 2181) 18–29.
• Uncovering and Mitigating the Impact of Code Obfuscation on Dataset Annotation with Antivirus Engines. Gao, Cuiying; Wu, Yueming; Li, Heng; Yuan, Wei; Jiang, Haoyu; He, Qidan; Liu, Yang M. Christakis, M. Pradel (eds.) (2024). 553–565.
• Debunking Fake News in Online Social Networks Without Text Analysis. Su, Xing; Yang, Jian; Wu, Jia; Qiu, Zitai E. Baralis, K. Zhang, E. Damiani, M. Debbah, P. Kalnis, X. Wu (eds.) (2024). 450–459.
• COSMO: A Large-Scale E-commerce Common Sense Knowledge Generation and Serving System at Amazon. Yu, Changlong; Liu, Xin; Maia, Jefferson; Li, Yang; Cao, Tianyu; Gao, Yifan; Song, Yangqiu; Goutam, Rahul; Zhang, Haiyang; Yin, Bing; Li, Zheng P. Barceló, N. Sánchez-Pi, A. Meliou, S. Sudarshan (eds.) (2024). 148–160.
• A One-Point-Trimmed 18.4 ppm/°C On-Chip Oscillator with Capacitively-Biased-Diode-based Quasi-Digital Temperature Compensation. Kuang, Yonghong; Chen, Yekan; Cai, Tianyi; Zhang, Qi; Cheng, Zipeng; Zhao, Bo; Luo, Yuxuan (2024). 1–5.
• A 2T P-Channel Logic Flash Cell for Reconfigurable Interconnection in Chiplet-Based Computing-In-Memory Accelerators. Li, Weizeng; Wang, Linfang; Li, Zhi; Ye, Wang; Zhou, Zhidao; Zhou, Haiyang; Gao, Hanghang; Yue, Jinshan; Hu, Hongyang; Liu, Fengman; Luo, Qing; Dou, Chunmeng (2024). 1–4.
• SiMA-Hand: Boosting 3D Hand-Mesh Reconstruction by Single-to-Multi-View Adaptation. Wang, Yinqiao; Xu, Hao; Heng, Pheng-Ann; Fu, Chi-Wing M. J. Wooldridge, J. G. Dy, S. Natarajan (eds.) (2024). 5704–5712.
• DiffMoCa: Diffusion Model Based Multi-modality Cut and Paste. Zhang, Junjie; Wu, Shaojin; Gao, Junbin; Yu, Fusheng; Xu, Hao; Zeng, Zhigang in Lecture Notes in Computer Science, X. Le, Z. Zhang (eds.) (2024). (Vol. 14827) 153–162.
• Poster: Jakiro: Spitting RDMA and TCP over Virtual Private Cloud. Liu, Yirui; Jiang, Lidong; Li, Deguo; Kang, Daxiang; Wei, Zhaoyang; Chai, Yuqi; Niu, Bin; Lin, Ke; Ding, Xiaoning; Pi, Jianwen; Luo, Hao V. Gopalakrishnan, J. Wang, I. A. Qazi, G. Tyson (eds.) (2024). 31–32.
• Multi-feature Electric Load Forecasting Based on AVMD-LSTM-Informer Model. Zhang, Yukun; An, Yisheng; Li, Ting; Li, Nandong; Li, Hao; Yang, Peng; Gao, Zhengge X. Chen, J. Fang (eds.) (2024). 491–496.
• Motif-Based Linearizing Graph Transformer for Web API Recommendation. Zheng, Xin; Wang, Guiling; Zhang, Yuqi; Han, Boyang; Yu, Jian in Lecture Notes in Computer Science, W. Gaaloul, M. Sheng, Q. Yu, S. Yangui (eds.) (2024). (Vol. 15405) 138–145.
• Optimized Method for Dynamic Allocation of Driving Rights and Trajectory Tracking under Human-Machine Co-driving. Li, Hao; An, Yisheng; Li, Ting; Li, Nandong; Zhang, Yukun; Yang, Peng; Gao, Zhengge X. Chen, J. Fang (eds.) (2024). 127–132.
• Adaptive Cooperative Ant Colony Optimization: A Task Scheduling Method on Heterogeneous Multi-Core Processors. Li, Nandong; An, Yisheng; Li, Ting; Li, Hao; Zhang, Yukun; Yang, Peng; Gao, Zhengge X. Chen, J. Fang (eds.) (2024). 519–525.
• Characterization of flow-blurring atomization with Smoothed Particle Hydrodynamics (SPH). Ates, Cihan; Gundogdu, Cansu; Okraschevski, Max; Bürkle, Niklas; Koch, Rainer; Bauer, Hans-Jörg (2023). 164 104442-.

  The liquid atomization process relies on the disturbance of the liquid surface by various forces. In the case of “flow-blurring” (FB) atomization, this is achieved by inducing flow instabilities near the liquid channel exit. In this study, we analyze the underlying dynamics of these coherent turbulent structures and their role in the primary atomization within the FB regime. For that purpose, Smoothed Particles Hydrodynamics (SPH) simulations have been conducted using alternative FB nozzle geometries at different operating conditions. An in-house developed visualization and data exploration platform (postAtom) was used to capture the time-resolved Lagrangian coherent structures (LCSs) via the finite-time Lyapunov exponent (FTLE) fields. Simulations were conducted at different gas/liquid momentum ratios at the nozzle exit by changing the mass flow rate of the gas phase and/or changing the position of the liquid injector. The effect of outer chamber design on the atomization performance is further assessed. The results indicate that the design of the mixing chamber can trigger an oscillatory behavior at the nozzle exit, which has a direct impact on the evolution of the micro-ligaments and the consecutive primary atomization. Comparisons between different operating points further reveal that FB atomization may not be achieved if the gas momentum is below a certain threshold value.
• IDMUNet : An effective network for liver tumor segmentation. Wu, Caihong; Song, Changming; Cheng, Dongxu; Ren, Siyv; Li, Zenghui; Chen, Kang; Li, Hao (2023). 49–56.
• Characterize and Optimize Dense Linear Solver on Multi-core CPUs. Fu, Xiao; Su, Xing; Dong, Dezun; Yang, Weiling (2023). 1833–1842.
• A Novel Classification Model for Automatic Multi-Label ICD Coding via BERT-LSTM. Wen, Luhan; Zhou, Dongmei; Luo, Hao; Cheng, Yongjian (2023). 1–7.
• Simulations of the insulin-like growth factor receptor signaling pathway with randomly sampled parameters. Yan, Yan; Zhang, Xinan; Tian, Tianhai X. Jiang, H. Wang, R. Alhajj, X. Hu, F. Engel, M. Mahmud, N. Pisanti, X. Cui, H. Song (eds.) (2023). 3848–3854.
• AoI-Minimal Power and Trajectory Optimization for UAV-Assisted Wireless Networks. Zhang, Xin; Hu, Yun; Chang, Zheng; Min, Geyong (2023). 1–6.
• Sum-Rate Capacity Scaling Law in Massive MIMO With Antenna Selection. Ouyang, Chongjun; Xu, Hao; Zang, Xujie; Yang, Hongwen (2023). 1–6.
• Reflecting Intelligent Surface Aided Downlink Transmission in Ultra-Dense LEO Satellite Networks. Zhang, Xin; Ma, Ting; Qin, Xiaohan; Wang, Yilei; Zhou, Haibo (2023). 1123–1128.
• Analysis of Co-Frequency Interference Avoidance Effect of Downlink Between Giant NGSO Constellations Based on MESINR Satellite Selection. Li, Yuan; He, Yuanzhi (2023). 1214–1218.
• On the Minimum Depth of Circuits with Linear Number of Wires Encoding Good Codes. Drucker, Andrew; Li, Yuan in Lecture Notes in Computer Science, W. Wu, G. Tong (eds.) (2023). (Vol. 14423) 392–403.
• Applications of Deep Learning in Satellite Communication: A Survey. He, Yuanzhi; Sheng, Biao; Li, Yuan; Wang, Changxu; Chen, Xiang; Liu, Jinchao in Communications in Computer and Information Science, Q. Yu (ed.) (2023). (Vol. 2057) 17–33.
• Trajectory Optimization and Resource Allocation for Time Minimization in the UAV-Enabled MEC System. Zhang, Xin; Chang, Zheng; Zhang, Guopeng; Li, Ming; Hu, Yulin (2022). 333–338.
• Image Description Generation Method Based on X-Linear Attention Mechanism. Qiao, Pingan; Li, Yuan; Shen, Ruixue (2022). 581–586.
• Review of Flow Blurring Atomization: Advances and Perspectives. Kourmatzis, Agisilaos; Jaber, Othman J.; Singh, Gajendra; Masri, Assaad R. (2022). 36(8) 4224–4233.

  This review summarizes the state of the art of flow blurring atomization, focusing both on fundamental aspects of this atomization mode as well as key observations made from applications of flow blurring. Flow blurring is an internal-twin fluid atomization method that offers effective interphase turbulent mixing and very fine liquid sprays. The features of this mode of liquid breakup make it attractive for applications in liquid fuel spray combustion, although it also offers potential benefits to applications requiring the atomization of non-Newtonian liquids, for example, such as in polymer filament manufacturing. This review concisely covers features of the internal nozzle flow of flow blurring atomizers, the effect of the orifice geometry on the spray, the behavior of the near-field spray region, the effect of liquid physical properties on droplet behavior, and general observations of reacting flow blurring sprays. Consistencies among the various research conducted is highlighted throughout the review, and this information, along with identified gaps in our understanding, is used to offer suggestions for future research.
• lncRNAMalat1and miR-26 cooperate in the regulation of neuronal progenitor cell proliferation and differentiation. Was, Nina; Sauer, Mark; Fischer, Utz; Becker, Matthias (2022). 29(1) 69–81.
• Ratgeber berufsbegleitende Promotion : Eine Entscheidungshilfe Staab, Thomas; Matusiewicz, David in UTB (2022). (Vol. 5845) Budrich.
• SFC Enabled Data Delivery for Ultra-Dense LEO Satellite-Terrestrial Integrated Network. Qin, Xiaohan; Ma, Ting; Tang, Zhixuan; Zhang, Xin; Liu, Xiaoyu; Zhou, Haibo (2022). 668–673.
• Joint Subchannel Allocation and Beamforming for Multicast in Ultra-Dense LEO Backbone Network. Ma, Ting; Qian, Bo; Qin, Xiaohan; Zhang, Xin; Cheng, Nan; Zhou, Haibo (2022). 1625–1630.
• Exploiting Lens Antenna Arrays in Uplink mmWave MU-MIMO Networks: Joint Beamforming Optimization. Ouyang, Chongjun; Xu, Hao; Zang, Xujie; Yang, Hongwen (2022). 1–6.
• Distributed Massive MIMO Cooperation With Low-Dimensional CSI Exchange. He, Zhenyao; Xu, Wei; Shen, Hong; Sun, Yan; You, Xiaohu; Fu, Jiewei (2022). 699–704.
• Research on Image Description Generation Method Based on G-AoANet. Qiao, Pingan; Shen, Ruixue; Li, Yuan (2022). 631–636.
• A Double Full Diversity Unitary Space Time Precoded V2V MIMO Communication System. Deng, Tao; Zhang, Lin; Feng, Yan; Jiang, Yuan (2022). 99–104.
• Research Hotspots and Evolution Trend of Virtual Power Plant in China: An Empirical Analysis Based on Big Data. Zhang, Yan; Liu, Pengcheng; Xu, Hao; Wang, Mulan in Communications in Computer and Information Science, Y. Tian, T. Ma, Q. Jiang, Q. Liu, M. K. Khan (eds.) (2022). (Vol. 1796) 105–121.
• Joint Mode Selection and Dynamic Pricing in Ultra Dense LEO Integrated Satellite-Terrestrial Networks. Zhang, Xin; Qin, Xiaohan; Qian, Bo; Ma, Ting; Zhou, Haibo (2022). 1090–1094.
• QoS-Centric Handover for Civil Aviation Aircraft Access in Ultra-Dense LEO Satellite Networks. Wang, Yilei; Qin, Xiaohan; Tang, Zhixuan; Ma, Ting; Zhang, Xin; Zhou, Haibo (2022). 1085–1089.
• FINet: Dual Branches Feature Interaction for Partial-to-Partial Point Cloud Registration. Xu, Hao; Ye, Nianjin; Liu, Guanghui; Zeng, Bing; Liu, Shuaicheng (2022). 2848–2856.
• A 98.1-dB SNDR 188-dB FoMS Noise-Shaping SAR ADC Using Series Connection Capacitors. Jing, Xixin; Lan, Zhechong; Zhang, Bing; Dong, Li; Xin, Youze; Guo, Zhuoqi; Xue, Zhongming; Geng, Li (2021). 10–13.
• Social-Computing Based Long-Term Task Offloading in D2D-Enhanced MEC Networks. Long, Hao; Xu, Chen; Zhang, Zhanpeng; Li, Zewu (2021). 934–939.
• Optimisation for the product configuration system of Renault: towards an integration of symmetries. Xu, Hao; Baarir, Souheib; Ziadi, Tewfik; Hillah, Lom-Messan; Essodaigui, Siham; Bossu, Yves M. R. Mousavi, P.-Y. Schobbens (eds.) (2021). 86–90.
• MEC in NOMA-HetNets: A Joint Task Offloading and Resource Allocation Approach. Zheng, Guangyuan; Xu, Chen; Long, Hao; Zhao, Xiongwen (2021). 1–6.
• Service Caching Based Task Offloading and Resource Allocation in Multi-UAV Assisted MEC Networks. Zheng, Guangyuan; Xu, Chen; Long, Hao; Sheng, Yun (2021). 1024–1029.
• A Bayesian framework for inferring heterogeneity of cellular processes using single-cell data. He, Wenlong; Xia, Peng; Zhang, Xinan; Tian, Tianhai Y. Huang, L. A. Kurgan, F. Luo, X. Hu, Y. Chen, E. R. Dougherty, A. Kloczkowski, Y. Li (eds.) (2021). 2142–2146.
• Evaluation of Phenotyping Errors on Polygenic Risk Score Predictions. Li, Ruowang; Tong, Jiayi; Duan, Rui; Chen, Yong; Moore, Jason H. E. D. Maria, A. Fred, H. Gamboa (eds.) (2020). 123–130.
• A Novel Pose Estimation Method of Object in Robotic Manipulation Using Vision-Based Tactile Sensor. Zhao, Dan; Sun, Fuchun; Zhou, Quan; Wang, Zongtao in Communications in Computer and Information Science, F. Sun, H. Liu, B. Fang (eds.) (2020). (Vol. 1397) 266–275.
• A combined experimental and computational study of flow-blurring atomization in a twin-fluid atomizer. Murugan, Raju; Kolhe, Pankaj S.; Sahu, Kirti Chandra (2020). 84 528–541.

  A twin-fluid pneumatic injector system with coaxial liquid and air streams mixed slightly upstream of the outlet, is studied in a cross-flow arrangement to understand its working principle. The gap between the orifice and the liquid tube, where the air and liquid cross-flow occurs, is known to determine the modes of working of the atomizer for the given operating flow rates of air and liquid. The two distinct modes, namely the flow focusing (FF) and flow blurring (FB) are observed in the present study, and the transition from FF to FB mode is explored using optical visualization. The characteristics of the internal two-phase flow mixing that occurs due to backflow recirculation in FB mode are also investigated by performing large eddy simulation (LES) using the volume of fluid (VoF) approach. The results of the numerical simulation are validated with experimental observations for the length of backflow recirculation observed in the liquid tube. The present study demonstrates the development of multiple microjets, which explains experimental observations of the lack of core jet and the almost uniform distribution of radial Sauter mean diameter (SMD) reported in the literature. The high-resolution backlit image of a scaled-up transparent injector with a 6 mm orifice diameter validates the numerical results that describe the internal two-phase flow.
• Robust-ODAL: Learning from Heterogeneous Health Systems Without Sharing Patient-LevelData. Tong, Jiayi; Duan, Rui; Li, Ruowang; Scheuemie, Martijn J.; Moore, Jason H.; Chen, Yong (2020). 695–706.
• Location Aided Intelligent Deep Learning Channel Estimation for Millimeter Wave Communications. Lin, Xintong; Zhang, Lin; Jiang, Yuan (2020). 489–494.
• How Autonomy is Used in Information Systems Research: Status Quo and Prospective Opportunities. Weber, Sebastian; Klesel, Michael; Oschinsky, Frederike Marie; Niehaves, Björn (2020). 1–9.
• Progress in the Smoothed Particle Hydrodynamics Method to Simulate and Post-process Numerical Simulations of Annular Airblast Atomizers. Chaussonnet, G.; Dauch, T.; Keller, M.; Okraschevski, M.; Ates, C.; Schwitzke, C.; Koch, R.; Bauer, H.-J. (2020). 105(4) 1119–1147.

  This paper illustrates recent progresses in the development of the smoothed particle hydrodynamics (SPH) method to simulate and post-process liquid spray generation. The simulation of a generic annular airblast atomizer is presented, in which a liquid sheet is fragmented by two concentric counter swirling air streams. The accent is put on how the SPH method can bridge the gap between the CAD geometry of a nozzle and its characterization, in terms of spray characteristics and dynamics. In addition, the Lagrangian nature of the SPH method allows to extract additional data to give further insight in the spraying process. First, the sequential breakup events can be tracked from one large liquid blob to very fine stable droplets. This is herein called the tree of fragmentation. From this tree of fragmentation, abstract quantities can be drawn such as the breakup activity and the fragmentation spectrum. Second, the Lagrangian coherent structures in the turbulent flow can be determined easily with the finite-time Lyapunov exponent (FTLE). The extraction of the FTLE is particularly feasible in the SPH framework. Finally, it is pointed out that there is no universal and ultimate non-dimensional number that can characterize airblast primary breakup. Depending on the field of interest, a non-dimensional number (e.g. Weber number) might be more appropriate than another one (e.g. momentum flux ratio) to characterize the regime, and vice versa.
• The Quantum Shor Algorithm Simulated on FPGA. Zhang, Xin; Zhao, Yaqian; Li, RenGang; Li, Xuelei; Guo, Zhenhua; Zhu, XiaoMin; Dong, Gang (2019). 542–546.
• Perry’s Chemical Engineers’ Handbook Green, Don W.; Southard, Marylee Z. (2019). (Ninth ) McGraw-Hill Education, New York.

  Up-to-Date Coverage of All Chemical Engineering Topics―from the Fundamentals to the State of the Art Now in its 85th Anniversary Edition, this industry-standard resource has equipped generations of engineers and chemists with vital information, data, and insights. Thoroughly revised to reflect the latest technological advances and processes, Perry's Chemical Engineers' Handbook, Ninth Edition, provides unsurpassed coverage of every aspect of chemical engineering. You will get comprehensive details on chemical processes, reactor modeling, biological processes, biochemical and membrane separation, process and chemical plant safety, and much more. This fully updated edition covers: Unit Conversion Factors and Symbols • Physical and Chemical Data including Prediction and Correlation of Physical Properties • Mathematics including Differential and Integral Calculus, Statistics , Optimization • Thermodynamics • Heat and Mass Transfer • Fluid and Particle Dynamics *Reaction Kinetics • Process Control and Instrumentation• Process Economics • Transport and Storage of Fluids • Heat Transfer Operations and Equipment • Psychrometry, Evaporative Cooling, and Solids Drying • Distillation • Gas Absorption and Gas-Liquid System Design • Liquid-Liquid Extraction Operations and Equipment • Adsorption and Ion Exchange • Gas-Solid Operations and Equipment • Liquid-Solid Operations and Equipment • Solid-Solid Operations and Equipment •Chemical Reactors • Bio-based Reactions and Processing • Waste Management including Air ,Wastewater and Solid Waste Management* Process Safety including Inherently Safer Design • Energy Resources, Conversion and Utilization* Materials of Construction
• ODAL: A one-shot distributed algorithm to perform logistic regressions on electronic health records data from multiple clinical sites. Duan, Rui; Boland, Mary Regina; Moore, Jason H.; Chen, Yong R. B. Altman, A. K. Dunker, L. Hunter, M. D. Ritchie, T. E. Klein (eds.) (2019). 30–41.
• Malware Detection on Highly Imbalanced Data through Sequence Modeling. Oak, Rajvardhan; Du, Min; Yan, David; Takawale, Harshvardhan C.; Amit, Idan L. Cavallaro, J. Kinder, S. Afroz, B. Biggio, N. Carlini, Y. Elovici, A. Shabtai (eds.) (2019). 37–48.
• Fast Sparse Coding Inference with Historical Information. Zhang, Zhenchang; Jiang, Fei; Shen, Ruimin J. Wang, K. Shim, X. Wu (eds.) (2019). 1462–1467.
• Comparing adverse effects of Hepatitis C drugs using FAERS data. Huang, Jing; Zhang, Xinyuan; Tong, Jiayi; Du, Jingcheng; Duan, Rui; Yang, Liu; Moore, Jason H.; Chen, Yong; Tao, Cui H. J. Zheng, Z. Callejas, D. Griol, H. Wang, X. Hu, H. H. H. W. Schmidt, J. Baumbach, J. Dickerson, L. Zhang (eds.) (2018). 1653–1656.
• Performance analysis of quad-LED complex spatial modulation in visible light communication system. Zhang, Qi; Bai, Zhiquan; Zhang, Na; Sun, Shangqian; Han, Tao; Kwak, Kyung Sup (2018). 1–5.
• Making data-driven porting decisions with Tuscan. Khazem, Kareem; Barr, Earl T.; Hosek, Petr F. Tip, E. Bodden (eds.) (2018). 276–286.
• Comparing Pharmacovigilance Outcomes Between FAERS and EMR Data for Acute Mania Patients. Zhang, Xinyuan; Duan, Rui; Du, Jingcheng; Huang, Jing; Chen, Yong; Tao, Cui (2018). 57–59.
• Atomization and Sprays Lefebvre, Arthur H.; McDonell, Vincent G. in Combustion (2017). Taylor & Francis, CRC Press, Boca Raton.

  The second edition of this long-time bestseller provides a framework for designing and understanding sprays for a wide array of engineering applications. The text contains correlations and design tools that can be easily understood and used in relating the design of atomizers to the resulting spray behavior. Written to be accessible to readers with a modest technical background, the emphasis is on application rather than in-depth theory. Numerous examples are provided to serve as starting points for using the information in the book. Overall, this is a thoroughly updated edition that still retains the practical focus and readability of the original work by Arthur Lefebvre.
• vCFI: Visible Control Flow Integrity for Cloud Tenants. Li, Yuan; Zhang, Chao; Luo, Xiapu (2017). 6:1–6:2.
• An improved algorithm for symbol segmentation of mathematical formula images. Wang, Haiyan; Wang, Yu; Lu, Liying; Liu, Jianhang; Li, Shibao; Zhang, Yang (2016). 461–464.
• Extended Sunflower Hidden Markov Models for the recognition of homotypic cis-regulatory modules. Lemnian, Ioana M.; Eggeling, Ralf; Grosse, Ivo (2013).
• New analytical framework for the products of independent RVs with wireless applications. Chen, Yunfei; Karagiannidis, George K.; Lu, Hao; Cao, Ning (2012). 103–108.
• Handbook of Atomization and Sprays : Theory and Applications Ashgriz, N. (2011). Springer, New York.

  Atomization and sprays are used in a wide range of industries: mechanical, chemical, aerospace, and civil engineering; material science and metallurgy; food; pharmaceutical, forestry, environmental protection; medicine; agriculture; meteorology and others. Some specific applications are spray combustion in furnaces, gas turbines and rockets, spray drying and cooling, air conditioning, powdered metallurgy, spray painting and coating, inhalation therapy, and many others. The Handbook of Atomization and Sprays will bring together the fundamental and applied material from all fields into one comprehensive source. Subject areas included in the reference are droplets, theoretical models and numerical simulations, phase Doppler particle analysis, applications, devices and more.
• Genealogies and Geography. Barton, N H; Wilson, I P. H. Harvey, A. J. Leigh Brown, J. Maynard Smith (eds.) (1995).
• Liquid–Gas Systems. Fair, J. R.; Steinmeyer, D. E.; Penney, W. R.; Crocker, B. B. R. H. Perry, D. W. Green, J. O. Maloney (eds.) (1984). (Sixth )
• Spray Drying Handbook Masters, K. (1979). (Third ) G. Godwin ; Halsted Press, London, New York.
• Spray Drying. Dombrowski, N.; Munday, G. N. Blakegrough (ed.) (1968). (Vol. 2) 209–320.
• The phenomena of fluid motions Brodkey, Robert S. in Addison-Wesley series in chemical engineering (1967). (Fourth ) Addison-Wesley, Reading, Massachusetts.
• The Phenomena of Fluid Motions. Brodkey, Robert S. (1967).
• Atomization and Spray Drying Marshall, Jr. in Chemical Engineering Progress Monograph Series (1954). (Vol. 50) American Institute of Chemical Engineers, New York.