bluuebunny/crossref_metadata_2025_split huggingface dataset:
Tibio‐Femoral Contact Force Distribution of Knee Before and After Total Knee Arthroplasty: Combined Finite Element and Gait Analysis
Authors: Du Mingming , Sun Jun , Liu Yancheng , Wang Yingpeng , Yan Songhua , Zeng Jizhou , Zhang Kuan 
Published: June 2022

ObjectiveTo assess the tibio‐femoral contact forces before and after total knee arthroplasty (TKA) in patients with knee osteoarthritis (KOA) by three‐dimensional (3D) finite element analysis (FEA) models and gait analysis.MethodsTwo hospitalized patients with Kellgren–Lawrence grade IV varus KOA and two healthy subjects were enrolled in this study. Both patients underwent unilateral TKA. FEA models were established based on CT and MR images of the knees of the patients with KOA and healthy subjects. Gait analysis was performed using a three‐dimensional motion capture system with a force plate. Three direction forces at the ankle joints were calculated by inverse dynamic analysis, which provided the load for the FEA models. The total contact forces of the knee joints were also calculated by inverse dynamic analysis to enable comparisons with the results from the FEA models. The total knee contact forces, maximum von Mises stress, and stress distribution of the medial plateau were compared between the patients and healthy subjects. The distributions of the medial plateau force at 2 and 6 months postoperatively were compared with the distributions of the forces preoperatively and those in the healthy subjects.ResultsDuring static standing, the medial plateau bore the most of the total contact forces in the knees with varus KOA (90.78% for patient 1 and 93.53% for patient 2) compared with 64.75 ± 3.34% of the total force in the healthy knees. At the first and second peaks of the ground reaction force during the stance phase of a gait cycle, the medial plateau bore a much higher percentage of contact forces in patients with KOA (74.78% and 86.48%, respectively, for patient 1; 70.68% and 83.56%, respectively, for patient 2) than healthy subjects (61.06% ± 3.43% at the first peak and 72.09% ± 1.83% at the second peak). Two months after TKA, the percentages of contact forces on the medial tibial plateau were 79.65%–85.19% at the first and second peaks of ground reaction forces during the stance phase of a gait cycle, and the percentages decreased to 53.99% – 68.13% 6 months after TKA.ConclusionFEA showed that TKA effectively restored the distribution of tibio‐femoral contact forces during static standing and walking, especially 6 months after the surgery. The changes in the gait were consistent with the changes in the contact force distribution calculated by the FEA model.
Female labor force participation in Egypt and Palestine: An age–period–cohort analysis*
Authors: Lassassi Moundir , Tansel Aysit 
Published: June 2022

AbstractThis paper considers female labor force participation (FLFP) behavior over the past two decades in two MENA (Middle East and North Africa) countries, namely Egypt and Palestine. Low FLFP rates in these countries, as in other MENA countries, are well documented. We conduct synthetic panel analysis using age–period–cohort (APC) methodology and decompose the FLFP rates into age, period, and cohort effects. We present our results with Hanoch–Honig–Deaton–Paxson normalization and maximum entropy estimation approaches to the APC method to observe the robustness of our results. The analysis is carried out by aggregate FLFP as well as by stratification by rural–urban location and educational attainments. Most of our results are similar in Egypt and Palestine with some exceptions. The two salient findings are as follows. The year effects display an initial U‐shape followed by an inverted U‐shape in both countries. The declining arm of the inverted U‐shape is compatible with the “MENA paradox” observed in both countries. The increase in the participation of the younger cohorts of the below‐secondary educated women, which is a low‐educated group, may be an indication of the wearing away of the social norms in Palestine that are considered to hinder the participation of women.
Social identity, confidence in institutions, and youth: Evidence from the Arab Spring
Authors: Fakih Ali , Khayat Rasha 
Published: June 2022

AbstractObjectiveDuring the political transition, people lose their confidence in their leaders, faith in the so‐called “democratic” elections, and no longer trust their political institutions. The issue of trust in institutions is highly regarded in social sciences research, as it reflects people's perceptions and valuation of how well their institutions are functioning. Therefore, the main objective of this article is to investigate the case of the Middle East and North African Region following the Arab Spring uprisings that began in 2011. Specifically, the relationship between youth self‐perception identity and confidence in various institutions is examined in the post‐Arab Spring era.MethodWe use a microlevel data set extracted from the SAHWA Youth Survey conducted in 2016. The sample consists of around 10,000 randomly and nationally representative youth aged 15 to 29 years. The survey includes 2000 observations from Lebanon, 1970 observations from Egypt, 2000 from Tunisia, and 2036 and 1854 from Algeria and Morocco, respectively. The empirical analysis is carried out through the ordered probit model.ResultsControlling for a comprehensive set of socioeconomic characteristics, we find that religious associations are not confined to people who belong to an Arab, global, national, or even religious identity. Young people who identify with citizens of the world only seem to confide in the police. Additionally, Arab identity is correlated with absolute positive confidence in the elections. Coherent with previous literature, we note that a nationalistic identity increases politicians’ and administrations’ confidence despite the domestic turmoil. We also find that religious identity is negatively correlated with all institutions except elections, including religious associations.ConclusionThis research highlights that policies that are up‐to‐date and secure gender equality may create a modernist atmosphere that allows people to retrieve trust and confidence in the institutions and administrations in the countries.
Automated People Mover Technology Review - A Mobility Tool for Large Capacity Airports and Connecting Transit Systems
Authors: Barbosa Fábio C. 
Published: June 2022

Abstract
The Automated People Mover (APM) technology has been systematically used to handle increasing airport local passenger demands and for connecting transit systems, into short rides, with medium capacity vehicles (up to 300 passengers per ride), short headways (up to 60 seconds), and, hence, with a high service level.
The APM technology enables the use of the decentralized passenger terminals layout, required for large capacity airports, in order to ensure its operational feasibility, through the safe integration of remote located passenger concourses, as well as assuring reasonable walking distances (up to 300m/1,000 ft) to both airport terminals (passenger boarding, transfers and connections), parking facilities and transit system connections.
The APM can be classified as an advanced transportation system, which uses driverless automated, operating on fixed guideways (single or multicar trains) along an exclusive right-of-way (RoW), on steel or concrete guideways, with capacities ranging from 1,000 to 16,000 passengers per hour direction (pphd), with the ability to operate in an on demand mode, especially during off-peak hours, to minimize the energy used, as well as a ride quality comparable with the best of any transit system.
The APM vehicles are electric-powered, rubber tired, steel wheeled or air cushion suspended, as well as tractioned by onboard electric motors, drawn by cables or pneumatically driven, with different guiding, switching, and control concepts, depending on the technology adopted.
The APM technology was firstly implemented in the United States (U.S.), at the Tampa International Airport, in the early 70’s, followed by other systems in other U.S. and North American airports, as a tool to address the increasing walking distances, caused by the passenger terminals growing, required to accommodate the large passenger traffic. In the late 80’s and early 90’s, the APM technology was also introduced in Asia and Europe for both airports and amusement parks, while in the early 2000’s, in Latin America, for both airports and transit systems.
This work presents an overview of the APM technology, in a review format, based on the available technical literature, followed by an assessment of the APM’s technical and operational features, associated with the different technologies. It also reports some case studies of the main APM systems worldwide and ongoing projects to be implemented.
Pilot Field Test of an Onboard Wireless Condition Monitoring System for Railroad Rolling Stock
Authors: Barrera Marco A. , Cantu Lee R. , Tarawneh Constantine , Foltz Heinrich , Wilson Brent , Porter Byron 
Published: June 2022

Abstract
The “internet of things” has revolutionized the methods in which many industries have optimized performance and component defect detection by providing real-time feedback through the implementation of data processing and wireless communication. Despite these advancements, the railway industry has lingered stagnant in its approach of adopting these advanced prognostic detection systems, and instead relies on discretely (25–40 miles) placed trackside condition monitoring systems, aka wayside. These wayside systems are primarily used to detect abnormal operating conditions in railcar rolling stock components. However, while they have been used for decades to address imminent threats to derailments and/or safety, they have unfortunately been shown to erroneously flag and misdiagnose components. These “false positive” cases usually result in unnecessary and costly delays and train stoppages. In worst case scenarios, these wayside systems have been known to mis-identify problematic components which can potentially lead to catastrophic derailments, risking property and safety. Overall, these limitations to established methods, and current technological innovations, allow for the introduction of a pioneering technology that addresses these deficiencies to enable constant, reliable, and precise onboard component health monitoring through vibration and temperature tracking. With these advancements, railroad car owners and operators can preemptively assess any rolling stock maintenance issue well in advance of an anticipated catastrophic failure.
To validate the efficacy of these onboard sensors, a field study was conducted using 40 such monitoring devices that were affixed to the bearing adapters of randomly selected railcars in a dedicated coal service route. After the span of two months of ongoing testing, three wheelsets were selected for removal based on data collected that indicated non-normative operating conditions. The wheelsets were inspected, analyzed, and the corresponding bearings were shipped to the University Transportation Center for Railway Safety (UTCRS) for laboratory evaluation and testing. This paper summarizes some of the preliminary results acquired from this field test and provides a comparison between the field and laboratory data, demonstrating their agreement and the prospective integration of these sensor technologies into the rail industry.
Intelligent Transit Thru Imaging: Using CCTV Cameras for Evaluating Real Time Demand
Authors: Saxena Kshitij 
Published: June 2022

Abstract
Ubiquitous CCTV cameras are a commonplace in cities with their presence on street intersections, bus stops, train stations and ferry terminals, etc. This paper presents an idea to use Artificial Intelligence in devising heat maps whereby traffic density is mapped from CCTV camera image grab of a location. When fed into the Traffic Management System (TMS), relevant alerts can be issued to the Traffic Controllers, consequently, deploying a bus or a metro train to meet that extra rush of passengers. Intelligent models can be developed that create novel routes during specific events in the city. New demand and response models can be created within TMS thru use of data science. Routes can be temporarily modified, with crowded stops added and uncrowded ones removed. Passengers are given adequate notice thru live alerts. Ethical issues related to data privacy are handled by specialized software. Such an intelligent system can help control crime. By active monitoring, the response time in attending accidents can be lessened. Necessary warnings are issued to bus operators concerning elderly and people with special needs, enabling better onboarding experience.
Numerical Simulation of Train-Track Switch Interactions in the Presence of Surface Rail Defects for Determining Physical Sensor Placement for Structural Health Monitoring
Authors: Pillai Nikhil , Shih Jou-Yi , Roberts Clive 
Published: June 2022

Abstract
A novel approach that utilizes numerical simulations of train-track interactions to determine the placement of sensors for the condition monitoring of railway switches has been demonstrated. The locations on the switches that would need to be monitored for the development of a specific RCF fault were obtained by utilizing the results from holistic MBS train-turnout interaction simulations in a damage prediction model. A detailed three-dimensional (3D) solid Finite Element (FE) model for replicating the similar track dynamic behavior and rolling contact interaction as the holistic MBS model was developed and validated. A 3D squat fault was introduced into the railhead of the FE model and simulations were run to help determine the placement of strain measurement sensors on the rail to detect its development. The results for the contact forces, Von-Mises stress and the engineering strains have been obtained from the simulations to help estimate the placement of sensors for the effective detection of the RCF squat fault.
Bringing damage control surgery simulation to life: developing a novel surgical anatomy model within immersive military trauma surgery simulation
Authors: Swain C S , Cohen H M L , Stannard A , Faulconer E R , Pallister I 
Published: June 2022

Haemorrhage from junctional injuries remains the most common cause of battlefield death. Changes to surgical training have meant acquiring and maintaining trauma surgical skills is becoming more difficult for military surgeons. The multidisciplinary Military Operational Specialist Team Training (MOSTT) course is designed to bridge the gap between civilian practice and the deployed environment, as part of predeployment trauma training. It involves immersive team simulation and uses cadaveric dissection for surgical skills practice.A novel surgical anatomy model, featuring junctional haemorrhage surgical task trainers of the groin and shoulder, was designed using reconstructed CT and MRI images obtained from a human volunteer. The model is designed to look and feel as realistic as possible, with the added dimension of pulsatile ‘blood’ flow from a simulation gunshot injury.This surgical anatomy model has been trialled, as part of the MOSTT course, by 90 surgeons and perioperative practitioners, with feedback analysis used for iterative model development. Feedback demonstrated that, alongside more traditional cadaveric dissection, this surgical anatomy model adds value to current predeployment training delivered within the immersive simulation of the MOSTT course. Research by the authors about the effects of this model on surgical ability and performance is ongoing. However, there is clear potential for this model to be used in other environments, including on exercises and as part of consolidation training while deployed.
Consent for orthopaedic trauma surgery during the COVID-19 pandemic
Authors: Selmi Hussain , Davies Andrew , Walker Joseph , Heaton Toby , Sabharwal Sanjeeve , Dani Melanie , Fertleman Michael , Reilly Peter 
Published: June 2022

IntroductionThe COVID-19 pandemic has brought a series of new challenges to the management of surgical patients. The consent process relies on a foundation of open and non-coerced discussion between clinician and patient, which includes all the potential risks of surgery. This must be updated to incorporate the additional risks of surgery during the pandemic including infection with the SARS-CoV-2 and increased risks of complications with the potential requirement for intensive care support.AimThe aim of this multi-cycle quality improvement project was to ensure all patients were fully informed of the risks of developing COVID-19 and the possible need for intensive care unit (ICU) support.MethodsWe investigated the quality of the consent process for patients undergoing surgery for trauma at our major trauma centre. Our baseline data collection included a review of all orthopaedic trauma consent forms over a 4-week period in March 2020. We subsequently undertook three further Plan-Do-Study-Act (PDSA) cycles over separate 4-week periods. First, in June 2020, after education measures and presentation of baseline data, second in July 2020 after further education and regular digital reminders were sent to staff, and third in September 2021 after the implementation of an electronic consent form.ResultsAt baseline, only 2.6% of consent forms mentioned the risk of COVID-19 and none mentioned the risk of requiring ITU support. Through three PDSA cycles this increased to 97% of cases where consent forms displayed the additional risks of COVID-19 and the potential need for ITU admission.ConclusionOur quality improvement project improved the informed consent procedure at our trust. By incorporating these additional risks into the template of an electronic consent form, we hope to achieve sustained improvement in practice.
Altered excitability of motor neuron pathways after stroke: more than upper motor neuron impairments
Authors: Li Pingping , Chen Chunyong , Huang Baozi , Jiang Zimu , Wei Jiating , Zeng Jinsheng 
Published: June 2022

BackgroundPrevious studies have suggested that impairment occurs in the lower motor neuron (LMN) pathway after stroke, but more research remains to be supported.ObjectiveIn this study, we tested the hypotheses: (1) both motor cortex and peripheral nerve pathways have decreased excitability and structural damage after stroke; (2) parameters of transcranial magnetic stimulation motor evoked potentials (TMS-MEP) can be used as predictors of motor function and stroke prognosis.MethodsWe studied five male cynomolgus monkeys with ischaemic stroke. TMS-MEP, cranial MRI, behavioural assessment, neurological scales and pathology were applied.ResultsElevated resting motor threshold (RMT) (p<0.05), decreased TMS-MEP amplitudes (p<0.05) and negative RMT lateralisation were detected in both the affected motor cortex (AMC) and the paretic side median nerve (PMN) at 2 weeks poststroke. Disturbed structure and loose arrangement of myelin sheaths were observed in the PMN through H&E staining and LFB staining at 12 weeks poststroke. The primate Rankin Scale (used for assess the stroke prognosis) scores at 2–12 weeks after middle cerebral artery occlusion were [1, (1; 3)], [1, (1;2)], [1, (1; 1.5)] and [1, (1; 1.5)], respectively. The RMT and RMT lateralisation (AMC) were predictors of stroke prognosis, and the RMT lateralisation of PMN and latency of AMC were predictors of motor impairment.ConclusionsBoth upper motor neuron (UMN) and LMN pathway excitability is reduced after stroke, and structural damage in median nerve 12 weeks after stroke occur. In addition, RMT and RMT lateralisation are predictors of stroke prognosis and motor impairment.
Higher dimensional charged static and rotating solutions in mimetic gravity
Authors: Bakhtiarizadeh Hamid R. 
Published: June 2022

AbstractWe find new solutions to the Einstein–Maxwell equations in the presence of mimetic field in D dimensions, all of which are asymptotically anti-de Sitter. We derive the solutions in five-dimensional spacetime, in detail. By extending the calculations to six and seven dimensions, we obtain a general form for solutions in dimensions larger than four. The results describe electrically charged static and rotating solutions, which have spherical, toroidal or cylindrical horizons. The solutions, depending on their global identifications, can be regarded as black holes, or black strings/branes. Some physical properties of solutions such as horizons, singularities as well as entropy, mass, and angular momenta of rotating solutions are also investigated.
Development of a resource-efficient FPGA-based neural network regression model for the ATLAS muon trigger upgrades
Authors: Ospanov Rustem , Feng Changqing , Dong Wenhao , Feng Wenhao , Zhang Kan , Yang Shining 
Published: June 2022

AbstractThis paper reports on the development of a resource-efficient FPGA-based neural network regression model for potential applications in the future hardware muon trigger system of the ATLAS experiment at the Large Hadron Collider (LHC). Effective real-time selection of muon candidates is the cornerstone of the ATLAS physics programme. With the planned ATLAS upgrades for the High Luminosity LHC, an entirely new FPGA-based hardware muon trigger system will be installed that will process full muon detector data within a 10 $${\upmu }\text {s}$$

μ
s

latency window. The large FPGA devices planned for this upgrade should have sufficient spare resources to allow deployment of machine learning methods for improving identification of muon candidates and searching for new exotic particles. Our neural network regression model promises to improve rejection of the dominant source of background trigger events in the central detector region, which are due to muon candidates with low transverse momenta. This model was implemented in FPGA using 157 digital signal processors and about 5000 lookup tables. The simulated network latency and deadtime are 122 and 25 ns, respectively, when implemented in the FPGA device using a 320 MHz clock frequency. Two other FPGA implementations were also developed to study the impact of design choices on resource utilisation and latency. The performance parameters of our FPGA implementation are well within the requirements of the future muon trigger system, therefore opening a possibility for deploying machine learning methods for future data taking by the ATLAS experiment.