scholarly journals Characterization of COVID-19’s Impact on Mobility and Short-Term Prediction of Public Transport Demand in a Mid-Size City in Spain

Sensors ◽  
2021 ◽  
Vol 21 (19) ◽  
pp. 6574
Author(s):  
Ana Belén Rodríguez González ◽  
Mark R. Wilby ◽  
Juan José Vinagre Díaz ◽  
Rubén Fernández Pozo
Keyword(s):  
Public Transport ◽  
High Performance ◽  
Monitoring Network ◽  
Traffic Monitoring ◽  
Health Economy ◽  
Accurate Information ◽  
Short Term ◽  
Public And Private ◽  
The Impact

COVID-19 has dramatically struck each section of our society: health, economy, employment, and mobility. This work presents a data-driven characterization of the impact of COVID-19 pandemic on public and private mobility in a mid-size city in Spain (Fuenlabrada). Our analysis used real data collected from the public transport smart card system and a Bluetooth traffic monitoring network, from February to September 2020, thus covering relevant phases of the pandemic. Our results show that, at the peak of the pandemic, public and private mobility dramatically decreased to 95% and 86% of their pre-COVID-19 values, after which the latter experienced a faster recovery. In addition, our analysis of daily patterns evidenced a clear change in the behavior of users towards mobility during the different phases of the pandemic. Based on these findings, we developed short-term predictors of future public transport demand to provide operators and mobility managers with accurate information to optimize their service and avoid crowded areas. Our prediction model achieved a high performance for pre- and post-state-of-alarm phases. Consequently, this work contributes to enlarging the knowledge about the impact of pandemic on mobility, providing a deep analysis about how it affected each transport mode in a mid-size city.

scholarly journals Short-Term Forecasting of Off-Street Parking Occupancy

2021 ◽  
pp. 036119812110363
Author(s):  
Elisabeth S. Fokker ◽  
Thomas Koch ◽  
Marco van Leeuwen ◽  
Elenna R. Dugundji
Keyword(s):  
Information And Communication Technologies ◽  
Public Transport ◽  
Short Term Memory ◽  
Sunshine Duration ◽  
Influential Factors ◽  
Time Variability ◽  
Weather Variables ◽  
Short Term ◽  
Average Wind Speed ◽  
The Impact

Information and communication technologies have opened the way to guide recent developments in the field of parking. In this paper these technologies are applied to model a decision support system that gives insight into 6-months ahead parking occupancy forecasts for 57 off-street parking locations in Amsterdam. An effect analysis was conducted into the influence of weather-, event-, parking tariff-, and public transport attributes on parking occupancy. The most influential factors on the parking occupancy were the scheduling of artistic and sports events, the addition of a public transport line, and the weather variables thunderstorm, average wind speed, temperature, precipitation, and sunshine duration. Parking tariffs did not significantly contribute to model performance, which could have been because of the lack of data and time variability in the parking tariffs of the examined parking locations. The forecasting algorithms compared were the seasonal naive model as a benchmark approach, the Box–Jenkins seasonal autoregressive integrated moving average with and without exogenous regressors (SARIMAX and SARIMA, respectively), exponential smoothing models, and the long short-term memory neural network. The SARIMAX model outperformed the other algorithms for the 6-months ahead forecasts according to the lowest root mean square error (RMSE). By including the event factor, the model improved by 24% based on the RMSE. Weather variables improved the predictive performance by 8%. Future studies could focus on the addition of more event variables, extension into an online model, and the impact of spatial–temporal features on parking occupancy.

Performance Evaluation of Modelling and Simulation of Lead Acid Batteries for Photovoltaic Applications

2016 ◽  
Vol 7 (2) ◽  
pp. 472 ◽  
Author(s):  
A. Selmani ◽  
A. Ed-Dahhak ◽  
M. Outanoute ◽  
A. Lachhab ◽  
M. Guerbaoui ◽  
...  
Keyword(s):  
Performance Evaluation ◽  
High Performance ◽  
Accurate Information ◽  
Lead Acid Batteries ◽  
Internal Parameters ◽  
Photovoltaic Applications ◽  
Charging Mode ◽  
The Impact ◽  
Storage Units ◽  
Lead Acid

Lead-acid batteries have been the most widely used energy storage units in stand-alone photovoltaic (PV) applications. To make a full use of those batteries and to improve their lifecycle, high performance charger is often required. The implementation of an advanced charger needs accurate information on the batteries internal parameters. In this work, we selected CIEMAT model because of its good performance to deal with the widest range of lead acid batteries. The performance evaluation of this model is based on the co-simulation LabVIEW/Multisim. With the intention of determining the impact of the charging process on batteries, the behaviour of different internal parameters of the batteries was simulated. During the charging mode, the value of the current must decrease when the batteries’ state of charge is close to be fully charged.

scholarly journals Performance characterization of containerization for HPC workloads on InfiniBand clusters: an empirical study

2021 ◽  
Author(s):  
Peini Liu ◽  
Jordi Guitart
Keyword(s):  
High Performance ◽  
Virtual Machines ◽  
Memory Access ◽  
Memory Allocation ◽  
Bare Metal ◽  
Fine Grain ◽  
The Impact ◽  
Performance Computing ◽  
Memory Affinity

AbstractContainerization technology offers an appealing alternative for encapsulating and operating applications (and all their dependencies) without being constrained by the performance penalties of using Virtual Machines and, as a result, has got the interest of the High-Performance Computing (HPC) community to obtain fast, customized, portable, flexible, and reproducible deployments of their workloads. Previous work on this area has demonstrated that containerized HPC applications can exploit InfiniBand networks, but has ignored the potential of multi-container deployments which partition the processes that belong to each application into multiple containers in each host. Partitioning HPC applications has demonstrated to be useful when using virtual machines by constraining them to a single NUMA (Non-Uniform Memory Access) domain. This paper conducts a systematical study on the performance of multi-container deployments with different network fabrics and protocols, focusing especially on Infiniband networks. We analyze the impact of container granularity and its potential to exploit processor and memory affinity to improve applications’ performance. Our results show that default Singularity can achieve near bare-metal performance but does not support fine-grain multi-container deployments. Docker and Singularity-instance have similar behavior in terms of the performance of deployment schemes with different container granularity and affinity. This behavior differs for the several network fabrics and protocols, and depends as well on the application communication patterns and the message size. Moreover, deployments on Infiniband are also more impacted by the computation and memory allocation, and because of that, they can exploit the affinity better.

scholarly journals CHARACTERIZATION, FORECASTING AND ASSESSMENT OF AGRICULTURAL DROUGHT IMPACTS IN THE SUDANO-SAHELIAN CLIMATE OF GOURMA PROVINCE IN BURKINA FASO

2020 ◽  
Vol 5 (1) ◽  
pp. 01-09
Author(s):  
Julius Okoth Omondi ◽  
Isaac Chitedze ◽  
Judith Kumatso
Keyword(s):  
Crop Yields ◽  
Potential Evapotranspiration ◽  
Agricultural Drought ◽  
Accurate Information ◽  
Economic Activities ◽  
Governmental Organizations ◽  
Non Governmental Organizations ◽  
Decision Making Processes ◽  
The Impact

Natural hazards such as agricultural droughts impact negatively on crop yields and economic activities. Characterization of agricultural droughts provides precise and accurate information for decision making processes during agricultural drought events. Planning and responding to the hazards by government, and non-governmental organizations in the Sudano-Sahelian belt has been limited in the past due to knowledge gap on the nature and impact of the hazard. This study seeks to characterize historical agricultural droughts, assess their impact on crop yields and people’s susceptibility to undernourishment and through forecasting, unravel what the future holds. Annual effective reconnaissance drought index values are computed using mean monthly potential evapotranspiration and effective precipitation data. To assess the impact of agricultural drought, the index’s values are compared to crop yields and prevalence to undernourishment data. Results show that agricultural drought events of 1983 and 2008 are mild and ephemeral while the 1999 – 2006 event is severe and protracted. While there is 26% chance of materialization of an agricultural drought in Gourma, the chance of being ephemeral and of moderate category is the highest (8%). It has been determined that an ephemeral and moderate agricultural drought would trigger below average yields for maize, sorghum and millet. Mild, moderate and severe events increase prevalence to undernourishment by 2.9 %, 4.3 % and 5.8 % respectively. From 2020 to 2030, a continued materialization of agricultural droughts is expected

Characterization of Traffic Noise and Honking Assessment of an Indian Urban Road

2018 ◽  
Vol 17 (04) ◽  
pp. 1850031 ◽  
Author(s):  
Ritesh Vijay ◽  
T. Chakrabarti ◽  
Rajesh Gupta
Keyword(s):  
Traffic Noise ◽  
Traffic Monitoring ◽  
Traffic Volume ◽  
Time Interval ◽  
Highway Traffic ◽  
Noise Levels ◽  
Additional Noise ◽  
Road Width ◽  
The Impact

To study the traffic noise on an Indian urban highway, traffic noise levels (Leq, Lpeak, Lmax and Lmin), traffic volume, speed and honking incidents were measured in peak traffic hours in the morning and evening. An attempt has been made to characterize the traffic noise including the impact of honking. Honking of horn was positively correlated with Leq and negatively correlated with traffic speed. In case of traffic volume and road width, no significant correlation was established with Leq. Based on the observed honking and Leq in each time interval, statistical analysis was performed for assessing the impact of honking on traffic noise and its estimation through trend analysis. Further, quantification of honking noise was carried out considering frequency analysis of audio spectrum of traffic noise. Both the analyzes confirm the honking contributed an additional noise of 1–4[Formula: see text]dB(A) over and above the traffic monitoring noise. The study suggests that honking noise must be included as a factor while monitoring traffic noise in some places where honking is common practice. This study will help in characterizing the traffic noise and the impact of honking for further abatement studies.

scholarly journals Characterization of Short-Term Temperature, Exposure, and Solubilization Effects on Library Compound Quality

2011 ◽  
Vol 16 (9) ◽  
pp. 1112-1118 ◽  
Author(s):  
John W. Eschelbach ◽  
Dorothy Zhuomei ◽  
Breanne Grady ◽  
Wolfgang Goetzinger
Keyword(s):  
High Performance ◽  
Room Temperature ◽  
Elevated Temperatures ◽  
High Demand ◽  
Short Term ◽  
Time Period ◽  
Temperature Exposure ◽  
Time Required ◽  
Storage Times ◽  
The Impact

Many compound collections are stored under the same temperature conditions, which can limit flexibility by increasing the processing time required for high-demand compounds. In this study, the authors wanted to evaluate the impact of a hybrid-storage approach where high-demand compounds are stored for a shortened time period at room temperature to expedite processing operations. The use of a Covaris adaptive-focused acoustics platform was also characterized as a potential enhancement or alternative to storage at elevated temperatures. This study evaluated the impact of temperature, exposure, and solubilization on overall compound quality for short-term storage. A small library of 25 representative compounds was evaluated over an 18-week period to monitor the change in purity and concentration by high-performance liquid chromatography with ultraviolet detection. The authors concluded that temperature had a significant impact on compound concentration, and the effects due to exposure cycles were minimal. A storage time of 12 weeks at room temperature resulted in minimal compound loss, but storage times beyond this would be unacceptable because of a >20% decrease in concentration. Finally, the acoustic solubilization protocol also increased the number of compounds at the target concentration with no impact on overall purity, leading to a potential for increased storage times at frozen temperatures.

Societal Costs of Child and Adolescent Mental Health Disorders

2018 ◽  
Author(s):  
Frances L. Lynch ◽  
John F. Dickerson
Keyword(s):  
Mental Health ◽  
Health System ◽  
Conceptual Model ◽  
Point Of View ◽  
Short Term ◽  
Public And Private ◽  
Scarce Resources ◽  
The Impact

Costs related to mental health and neurodevelopmental conditions (MHNCs) in childhood are experienced by multiple groups, including families, public and private service systems, and society as a whole. This chapter provides a conceptual model of MHNC-related costs, reviews estimates of short-term and long-term costs, and discusses the role of economic evaluation of services. Our conceptual model suggests that it is critical to consider costs from a broad point of view, but current literature on cost of MHNCs is uneven, with significant focus on short-term health system costs and very little emphasis on long-term costs or costs outside the health system, such as costs to families. There is a growing body of literature on MHNC costs, but more emphasis is needed in areas where there is little data to ensure that decision-makers have comprehensive data on the impact of MHNCs in order to manage scarce resources equitably and efficiently.

Research into High Performance Zeolite/Monomer Casting Nylon 6 (MCPA6) Composites

2013 ◽  
Vol 442 ◽  
pp. 134-137
Author(s):  
Bo Fen Huang ◽  
Han Xuan Liang ◽  
Zhi Yuan Li ◽  
Yan Chao Bai
Keyword(s):  
Thermal Decomposition ◽  
Impact Strength ◽  
High Performance ◽  
In Situ Polymerization ◽  
Nylon 6 ◽  
Experimental Results ◽  
The Impact

Zeolite / MC nylon 6 composites were prepared , followed by morphology and properties characterization of composites. The results demonstrated that a large number of pearlitic structures appeared at the interphase between the organic phases and the inorganic phases, indicating that caprolactam had happened anionic in-situ polymerization within the zeolite. The zeolite played a role of molecular rivet in zeolite / MCPA6 composites. The experimental results also showed that the composites performances were largely improved compared with pure MCPA6. When zeolite was 1 Phr, the impact strength of the composite was increased by 58%, temperature of thermal decomposition was rised by 92.9 °C. When zeolite reached 5 Phr, the composite shrinkage rate was reduced by 33%.

scholarly journals The Impact of DMARD and Anti-TNF Therapy on Functional Characterization of Short-Term T-Cell Activation in Patients with Rheumatoid Arthritis – A Follow-Up Study

PLoS ONE ◽  
2014 ◽  
Vol 9 (8) ◽  
pp. e104298 ◽  
Author(s):  
Balázs Szalay ◽  
Áron Cseh ◽  
Gergő Mészáros ◽  
László Kovács ◽  
Attila Balog ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
T Cell ◽  
T Cell Activation ◽  
Cell Activation ◽  
Functional Characterization ◽  
Short Term ◽  
Follow Up Study ◽  
The Impact

scholarly journals Global-Scale Metabolomic Profiling of Human Hair for Simultaneous Monitoring of Endogenous Metabolome, Short- and Long-Term Exposome

2021 ◽  
Vol 9 ◽  
Author(s):  
Ying Chen ◽  
Jian Guo ◽  
Shipei Xing ◽  
Huaxu Yu ◽  
Tao Huan
Keyword(s):  
High Performance ◽  
High Resolution Mass Spectrometry ◽  
Global Scale ◽  
Short Term ◽  
Experimental Conditions ◽  
Hair Samples ◽  
Wide Range ◽  
Endogenous Metabolites ◽  
The Impact

Hair is a unique biological matrix that adsorbs short-term exposures (e. g., environmental contaminants and personal care products) on its surface and also embeds endogenous metabolites and long-term exposures in its matrix. In this work, we developed an untargeted metabolomics workflow to profile both temporal exposure chemicals and endogenous metabolites in the same hair sample. This analytical workflow begins with the extraction of short-term exposures from hair surfaces through washing. Further development of mechanical homogenization extracts endogenous metabolites and long-term exposures from the cleaned hair. Both solutions of hair wash and hair extract were analyzed using ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS)-based metabolomics for global-scale metabolic profiling. After analysis, raw data were processed using bioinformatic programs recently developed specifically for exposome research. Using optimized experimental conditions, we detected a total of 10,005 and 9,584 metabolic features from hair wash and extraction samples, respectively. Among them, 274 and 276 features can be definitively confirmed by MS2 spectral matching against spectral library, and an additional 3,356 and 3,079 features were tentatively confirmed as biotransformation metabolites. To demonstrate the performance of our hair metabolomics, we collected hair samples from three female volunteers and tested their hair metabolic changes before and after a 2-day exposure exercise. Our results show that 645 features from wash and 89 features from extract were significantly changed from the 2-day exposure. Altogether, this work provides a novel analytical approach to study the hair metabolome and exposome at a global scale, which can be implemented in a wide range of biological applications for a deeper understanding of the impact of environmental and genetic factors on human health.

Sign in / Sign up

Export Citation Format

Share Document