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Transforming the public transport sector in the Philippines through service contracts: A program evaluation study

Transportation Research Procedia 2025年 82卷 890-907页

作者： Varsolo Sunio Wilhansen Li Joemier Pontawe Albert Dizon Alexis Fillone Science Engineering and Management Research Institute University of Asia and the Pacific Pasig City Metro Manila 1600 Philippines Toulan School of Urban Studies and Planning Portland State University Oregon 97201 United States Sakay Mobility Philippines Corporation Quezon City Metro Manila 1110 Philippines Department of Information Systems and Computer Science School of Science and Engineering Ateneo de Manila University Quezon City Metro Manila 1108 Philippines School of Architecture and Planning The University of Auckland New Zealand Civil Engineering Department De La Salle University Manila Metro Manila 1004 Philippines

We evaluate two schemes of service contracting (SC) program implemented for the first time in the Philippines: gross-cost and net-cost. Using an automatic vehicle location (AVL) dataset generated using a mobile application, we examine the supply and performance of jeepney, a form of paratransit, on 20 routes during the pandemic. Ten of these routes are under gross-cost, and the other ten are under net-cost. Our evaluation suggests that gross-cost SC has resulted in more kilometer-run travelled, more arrivals at the stop, shorter headway duration, which are indicative of increased supply, compared to net-cost. However, we obtain mixed results for metrics associated with performance (headway regularity, dwell time and route compliance) for gross- and net- cost. We recommend that for SC to maximize its impact and raise performance, the government should set standards on metrics associated with fleet management and enforce strict compliance. Since SC is typically applied for the management of formal public transport, our work represents a novel contribution on the application of SC on the management of paratransit in the Global South.

关键词： service contract public transport reform Global South paratransit

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THE ELECTRICAL TASKS COURSE IN THE SPECIAL engineering program

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INTERNATIONAL JOURNAL OF ELECTRICAL engineering EDUCATION 1985年第3期22卷 197-204页

作者： OCONNOR, B AINSCOUGH, J RAKOWSKI, R Department of Engineering and Management Systems Brunei University England

A course is described, where the students learn new material in the area of electronics not through lectures but by a process of problem-solving, experimental work, report writing and oral presentations. Experience of... 详细信息

关键词： engineering EDUCATION

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Facilitating Emergency Vehicle Passage in Congested Urban Areas Using Multi-agent Deep Reinforcement Learning

arXiv

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arXiv 2025年

作者： Su, Haoran University of California Berkeley United States Transportation Systems program Tandon School of Engineering New York University United States C2SMARTER Center Tier-1 University Transportation Research Center United States Department of Transportation United States

Emergency Response Time (ERT) serves as a pivotal metric of urban resiliency and public safety, encapsulating a city’s capacity to respond promptly and effectively to medical, fire, and crime emergencies. Over the last decade, increasing urbanization and traffic congestion have severely exacerbated ERT, undermining emergency management systems and public trust. In New York City (NYC), average ERT for medical emergencies has surged by 72% from 7.89 minutes in 2014 to 14.27 minutes in 2024, with over 50% of delays attributable to prolonged Emergency Vehicle (EMV) travel times. These escalating delays have dire consequences: every minute of delay during a stroke can lead to the loss of 2 million brain cells, and survival rates for cardiac arrest diminish by 7–10% per minute. This underscores the urgency of addressing EMV travel inefficiencies through advanced routing and traffic management strategies. This dissertation responds to these critical challenges by advancing the state of EMV facilitation through three substantive contributions. First, it introduces EMVLight, a decentralized multi-agent reinforcement learning (MARL) framework that dynamically integrates EMV routing and adaptive traffic signal pre-emption. EMVLight leverages real-time traffic data and decentralized coordination between agents to optimize EMV travel paths while reducing disruptions to non-EMV traffic. Experimental results demonstrate a 42.6% reduction in EMV travel times and a 23.5% decrease in the average travel time for non-EMVs across synthetic and real-world traffic networks. Second, the dissertation develops the Dynamic Queue-Jump Lane (DQJL) system, which employs Multi-Agent Proximal Policy Optimization (MAPPO) to enable coordinated lane-clearing maneuvers in mixed-traffic environments comprising autonomous and human-driven vehicles. By dynamically forming queue-jump lanes in response to real-time traffic conditions, DQJL minimizes lane-change maneuvers and reduces EMV travel times by up

关键词： Travel time

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Mo-terminated edges in two-dimensional molybdenum disulfide for site-specific hydrolysis and DNA cleavage

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Materials Today 2025年 86卷 162-171页

作者： Wang, Cong Wu, Menghan Li, Muqing Zhao, Yingcan Zhao, Mingchuang Zhang, Yunhao Bai, Yichao Gao, Jianxiang Wang, Xiaoxia Tian, Xilin Zhang, Han Chang, Liang Zou, Xiaolong Liu, Bilu Kang, Feiyu Terrones, Mauricio Lei, Yu Institute of Materials Research Shenzhen Key Laboratory of Advanced Layered Materials for Value-added Applications Guangdong Provincial Key Laboratory of Thermal Management Engineering and Materials & Center of Double Helix Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen518055 China Institute of Materials Research & Shenzhen Geim Graphene Center Shenzhen Key Laboratory of Advanced Layered Materials for Value-added Applications Tsinghua-Berkeley Shenzhen Institute and Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen518055 China Environmental Science Program Department of Life Sciences Beijing Normal University-Hong Kong Baptist University United International College Guangdong519087 China Tsinghua Shenzhen International Graduate School Tsinghua University Shenzhen518055 China Department of Physics Department of Chemistry Department of Materials Sciences Center for 2-Dimensional and Layered Materials The Pennsylvania State University University ParkPA16802 United States International Collaborative Laboratory of 2D Materials for Optoelectronics Science and Technology of Ministry of Education Institute of Microscale Optoelectronics Shenzhen University Shenzhen518060 China

The hydrolysis of DNA serves as the foundational principle for gene engineering that enable precise gene cleavage at the molecular level. This process typically occurs in biological nucleases, which exhibit nucleobase-selective and catalytic hydrolysis capabilities rarely replicated in abiotic nanomaterials. Here, we demonstrate that molybdenum-terminated (Mo-terminated) edges of molybdenum disulfide (MoS2) possess the unique ability to abstract a proton (H+) from water molecules, thereby facilitating catalytic hydrolysis reactions that cleave the phosphodiester bonds in DNA through the action of hydroxide ions. The enhanced proton absorption at Mo-terminated edges of MoS2 significantly reduces the activation energy required for the DNA hydrolysis reaction. Furthermore, the favorable interaction between the Mo-terminated edges and thymine nucleobases promotes both charge transfer and P-O bond cleavage, enabling targeted DNA hydrolysis at 'TTTTTTT' sequences under dark conditions. This discovery underscores the potential of MoS2 as a stable, efficient nanosystem for precise genetic editing, heralding advanced applications in the field of gene engineering. © 2025 The Author(s)

关键词： Activation energy

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Neutronic study on the effect of first wall material thickness on tritium production and material damage in a fusion reactor

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Nuclear Science and Techniques 2022年第4期33卷 33-50页

作者： HacıMehmet S¸ahin Güven Tunc¸ Alper Karakoc¸ Melood Mohamad Omar Department of Energy Systems Engineering Technology FacultyKarabuk UniversityKarabukTurkey Department of Energy Systems Engineering Technology FacultyGazi UniversityAnkaraTurkey Department of Energy Systems Engineering Institute of Graduate ProgramsKarabuk UniversityKarabukTurkey

In this study,the effects of changing first wall materials and their thicknesses on a reactor were investigated to determine the displacement per atom(DPA)and gas production(helium and hydrogen)in the first wall,as well as the tritium breeding ratio(TBR)in the coolant and tritium breeding ***,the modeling of the magnetic fusion reactor was determined based on the blanket parameters of the International Thermonuclear Experimental Reactor(ITER).Stainless steel(SS 316 LNIG),Oxide Dispersion Strengthened Steel alloy(PM2000 ODS),and China low-activation martensitic steel(CLAM)were used as the first wall(FW)*** family molten salt materials(FLiBe,FLiNaBe,FLiPb)and lithium oxide(LiO_(2))were considered the coolant and tritium production material in the blanket,*** transport calculations were performed using the wellknown 3D code MCNP5 using the continuous-energy Monte Carlo *** built-in continuous energy nuclear and atomic data libraries along with the Evaluated Nuclear Data file(ENDF)system(ENDF/B-V and ENDF/B-VI)were ***,the activity cross-section data library CLAW-IV was used to evaluate both the DPA values and gas production of the first wall(FW)*** interface computer program written in the FORTRAN 90 language to evaluate the MCNP5 outputs was developed for the fusion reactor *** results indicated that the best TBR value was obtained for the use of the FLiPb coolant,whereas depending on the thickness,the first wall replacement period in terms of radiation damage to all materials was between 6 and 11 years.

关键词： ITER First wall material Material damage Tritium breeding ratio Fluorides family molten salt materials

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Accelerating exploitation and integration of global renewable energy

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Innovation 2025年

作者： Wang, Jianxiao Chen, Xinjiang Zhuang, Minghao Li, Yan Ruan, Ziwen Wang, Yuhan Zhang, Ning Song, Jie He, Kebin Lu, Xi National Engineering Laboratory for Big Data Analysis and Applications Peking University Beijing100871 China Department of Industrial Engineering and Management College of Engineering Peking University Beijing100871 China Peking University Ordos Research Institute of Energy Ordos017000 China State Key Laboratory of Nutrient Use and Management College of Resources and Environmental Sciences China Agricultural University Beijing100193 China College of Environmental Science and Engineering Tongji University Shanghai200092 China School of Environment State Key Joint Laboratory of Environment Simulation and Pollution Control Tsinghua University Beijing100084 China State Key Lab of Power Systems Department of Electrical Engineering Tsinghua University Beijing100084 China Institute for Carbon Neutrality Tsinghua University Beijing100084 China

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Cyberoception: Finding A Painlessly-Measurable New Sense In The Cyberworld Towards Emotion-awareness In Computing 25

Cyberoception: Finding A Painlessly-Measurable New Sense In ...

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Proceedings of the 2025 CHI Conference on Human Factors in Computing systems

作者： Tadashi Okoshi Zexiong Gao Yi Zhen Tan Takumi Karasawa Takeshi Miki Wataru Sasaki Rajesh Krishna Balan Faculty of Environment and Information Studies Keio University Fujisawa Kanagawa Japan Graduate School of Interdisciplinary Information Studies The University of Tokyo Tokyo Tokyo Japan School of Computing and Information Systems Singapore Management University Singapore Singapore Singapore Graduate School of Media and Governance Keio University Fujisawa city Kanagawa Pref Japan Department of Engineering University of Cambridge Cambridge Cambridge United Kingdom Graduate School of Science and Technology Nara Institute of Science and Technology Ikoma Nara Japan

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A Two-stage Reconfiguration in Network Function Virtualization: Toward Service Function Chain Optimization

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IEEE Transactions on Network and Service management 2025年

作者： Assis, Karcius D. R. Almeida, Raul C. Baghban, Hojjat Santos, Alex F. Boutaba, Raouf Electrical and Computer Engineering Department Salvador Brazil University of Waterloo David R. Cheriton School of Computer Science Canada Department of Electronics and Systems Recife Brazil Chang Gung University Department of Artificial Intelligence Taiwan Chang Gung University College of Intelligent Computing Taiwan Center of Science and Technology in Energy and Sustainability Brazil Postgraduate Program in Computer Science Bahia Brazil

Network Function Virtualization (NFV), as a promising paradigm, speeds up the service deployment by separating network functions from proprietary devices and deploying them on common servers in the form of software. Any service in NFV-enabled networks is achieved as a Service Function Chain (SFC) which consists of a series of ordered Virtual Network Functions (VNFs). However, migration of VNFs for more flexible services within a dynamic NFV-enabled network is a key challenge to be addressed. Current VNF migration studies mainly focus on single VNF migration decisions without considering the sharing and concurrent migration of VNF instances. In this paper, we assume that each deployed VNF is used by multiple SFCs and deal with the optimal placement for the contemporaneous migration of VNFs based on the actual network situation. We formalize the VNF migration and SFC reconfiguration problem as a mathematical model, which aims to minimize the VNF migration between nodes or the total number of core changes per node. The approach is a two-stage MILP based on optimal order to solve the reconfiguration. Extensive evaluation shows that the proposed approach can reduce the change in terms of location or number of cores per node in a 6-node and 14-node networks while ensuring network latency compared with the model without reconfiguration. © 2004-2012 IEEE.

关键词： Network function virtualization

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Eliminating Meteorological Dependencies in Solar Power Forecasting: A Deep Learning Solution With NeuralProphet and Real-World Data

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IEEE Access 2025年 13卷 93287-93301页

作者： Necati Aksoy Alper Yılmaz Gökay Bayrak Mehmet Koç Department of Electrical and Electronics Engineering Renewable Energy Systems and Smart Grids Laboratory Bursa Technical University Bursa Türkiye Electric Vehicles Application and Research Center Bursa Technical University Bursa Türkiye Uludağ Elektrik Dağıtım A.Ş. (UEDAŞ) Bursa Türkiye Graduate School Bursa Technical University Bursa Türkiye

Forecasting solar power generation is essential for efficient energy management and grid stability. However, existing predictive models often rely on external datasets, such as meteorological and sensor data, to make accurate predictions. This dependency introduces complexities and limits their application in data-sparse scenarios. In this study, we propose a novel forecasting approach based on the NeuralProphet algorithm, a deep learning model that predicts solar power generation solely from its historical data, eliminating reliance on additional input data. To evaluate the proposed approach, we conducted two case studies. The first utilized a 10-month dataset from a 1.2 kW small-scale solar power unit at Bursa Technical University’s Smart Grids laboratory, recorded at 15-minute intervals. Despite the limited dataset, the model achieved an R-squared value exceeding 0.74, demonstrating promising predictive capability. The second case study applied the NeuralProphet-based model to a large-scale dataset of nationwide solar power generation in Germany, spanning five years and collected at 15-minute intervals. Models trained on this dataset achieved R-squared values exceeding 0.99, highlighting the algorithm’s capacity to effectively capture seasonal and temporal patterns at a national scale. Our results indicate that the NeuralProphet-based forecasting approach offers a viable and efficient alternative for solar power prediction, achieving high accuracy without external data dependencies.

关键词： Forecasting Predictive models Solar power generation Accuracy Prediction algorithms Long short term memory Deep learning Training Temperature distribution Renewable energy sources

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Split Fine-Tuning for Large Language Models in Wireless Networks

arXiv

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arXiv 2025年

作者： Zhang, Songge Cheng, Guoliang Huang, Xinyu Li, Zuguang Wu, Wen Song, Lingyang Shen, Xuemin School of Electronic and Computer Engineering Peking University Shenzhen518000 China Frontier Research Center Pengcheng Laboratory Shenzhen518055 China State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Beijing100871 China School of Electronic and Computer Engineering Peking University Shenzhen Graduate School Shenzhen518055 China Department of Electrical and Computer Engineering University of Waterloo WaterlooN2L 3G1 Canada

Fine-tuning is the process of adapting the pre-trained large language models (LLMs) for downstream tasks. Due to substantial parameters, fine-tuning LLMs on mobile devices demands considerable memory resources, and suffers from high communication overhead and long fine-tuning delay. In this paper, we propose an efficient LLM fine-tuning scheme in wireless networks, named Split Fine-Tuning (SFT), which can accommodate LLM fine-tuning on mobile devices. Specifically, an LLM is split into a server-side part on the edge server and a device-side part on the mobile device to satisfy the device-side memory constraint. All devices share a server-side model and perform parallel fine-tuning to reduce fine-tuning delay. In addition, to reduce significant communication overhead incurred by data exchange between devices and the edge server, we propose a data compression scheme by jointly leveraging sparsification, stochastic quantization, and lossless encoding methods. Furthermore, we formulate a fine-tuning delay minimization problem under accuracy and memory constraints, taking device heterogeneity and channel dynamics into account. To solve the problem, the nonlinear mixed-integer problem is decoupled into two subproblems in different timescales. The two-timescale resource management algorithm is proposed to jointly optimize the compression rate and transformer block allocation in the large timescale using the augmented Lagrangian method, and determine spectrum resource allocation in the small timescale via sequential quadratic programming. Extensive simulation results demonstrate that the proposed scheme can reduce the fine-tuning delay by up to 80.2% and communication overhead by 93.6% compared to state-of-the-art benchmarks, while satisfying device-side memory and model accuracy constraints. Copyright © 2025, The Authors. All rights reserved.

关键词： Quadratic programming

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