Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessing The Public Health Benefits of Parkrun By Modelling Performance And Participation At Events In Scotland

Background: parkrun is a hugely successful public health initiative that encourages inactive people to exercise. The parkrun results database is likely to contain a wealth of potentially important public health information on the fitness benefits and participation patterns of parkrun, yet this resource has been ignored. The aim was to identify patterns in performance and attendance of participants at parkrun events in Scotland to enhance the future health benefits of parkrun through widening participation particularly by identifying features of events that overcome barriers to women taking part.Study design: The study conducted linear and binomial mixed models of age-graded performance, sex ratio and age of participants at parkrun events held in Scotland. Predictor variables were age, sex, parkrun ID number, number of runs, elevation gain, surface type and travelling time to the next nearest parkrun event. The data were generated from parkrun results pages for 56 events in Scotland. Results: There was a decline in the mean performance of participants at events, however individual performances improved over time. The sex ratio was male biased but the proportion of female participants has been increasing. Events in the most remote parts of Scotland had the lowest age graded performance scores and the highest proportion of female participants with the remotest events exhibiting a female bias in participation. Events on slower surfaces had a higher proportion of female participants.Conclusion: This study reports that parkrun events are becoming more inclusive with new participants being increasingly unfit women. In remoter parts of Scotland the traditional male bias in participation in sport has actually become a slight female bias revealing parkrun has seemingly overcome traditional barriers to female participation in sport. Events with slower surfaces had more female participants. Prioritising the creation of events at more remote locations and on slower surfaces could increase inclusivity and widen participation further. These findings could also help general practitioners prescribe those events that are most likely to benefit new participants making the parkrun practice initiative more effective. For example, women might be encouraged to attend traditionally slower events than men.
Evaluation of blood glucose level control in type 1 diabetic patients using deep reinforcement learning

Diabetes mellitus is a disease associated with abnormally high levels of blood glucose due to a lack of insulin. Combining an insulin pump and continuous glucose monitor with a control algorithm to deliver insulin is an alternative to patient self-management of insulin doses to control blood glucose levels in diabetes mellitus patients. In this work, we propose a closed-loop control for blood glucose levels based on deep reinforcement learning. We describe the initial evaluation of several alternatives conducted on a realistic simulator of the glucoregulatory system and propose a particular implementation strategy based on reducing the frequency of the observations and rewards passed to the agent, and using a simple reward function. We train agents with that strategy for three groups of patient classes, evaluate and compare it with alternative control baselines. Our results show that our method is able to outperform baselines as well as similar recent proposals, by achieving longer periods of safe glycemic state and low risk.
Behavior of Non-Shear-Strengthened UHPC Beams under Flexural Loading: Influence of Reinforcement Percentage

In the present work, the structural responses of 12 UHPC beams to four-point loading conditions were experimentally and analytically studied. The inclusion of a fibrous system in the UHPC material increased its compressive and flexural strengths by 31.5% and 237.8%, respectively. Improved safety could be obtained by optimizing the tensile reinforcement ratio (ρ) for a UHPC beam. The slope of the moment–curvature before and after steel yielding was almost typical for all beams due to the inclusion of a hybrid fibrous system in the UHPC. Moreover, we concluded that as ρ increases, the deflection ductility exponentially increases. The cracking response of the UHPC beams demonstrated that increasing ρ notably decreases the crack opening width of the UHPC beams at the same service loading. The cracking pattern the beams showed that increasing the bar reinforcement percentages notably enhanced their initial stiffness and deformability. Moreover, the flexural cracks were the main cause of failure for all beams; however, flexure shear cracks were observed in moderately reinforced beams. The prediction efficiency of the proposed analytical model was established by performing a comparative study on the experimental and analytical ultimate moment capacity of the UHPC beams. For all beams, the percentage of the mean calculated moment capacity to the experimentally observed capacity approached 100%.
Biometric Blockchain-based Multifactor Privacy Perserving Authentication Scheme for VANETs

To provide the most suitable or compatible scheme to work against various attack toward vehicular ad hoc networks (VANETs) is very challenging. Not only that the high authentication and communication overhead also became a problem for VANETs. Thus, in this paper we use multifactor authentication that could resist various attack toward VANETs. A biometric blockchain-based multifactor privacy-preserving authentication scheme for VANETs. This scheme is proposed by using a new robust pseudo-identity multifactor VANET scheme based on Physical Unclonable Functions (PUF) and biometric data of the vehicle’s authorized user. To calculate the computational cost and the authentication overhead, we compare three of our computational cost and authentication overhead below. From the complexity analysis this proposed scheme has a lower authentication overhead and offers better security level and a low computational cost can be achieved. From the perspective of future, we hope that the cost that involve in this scheme still can be reduce as we offer a high security level. Not only that, but we also hope that this scheme can be implemented practically.
Research on Lightweight Citrus Flowering Rate Statistical Model Combined with Anchor Frame Clustering Optimization

At present, learning-based citrus blossom recognition models based on deep learning are highly complicated and have a large number of parameters. In order to estimate citrus flower quantities in natural orchards, this study proposes a lightweight citrus flower recognition model based on improved YOLOv4. In order to compress the backbone network, we utilize MobileNetv3 as a feature extractor, combined with deep separable convolution for further acceleration. The Cutout data enhancement method is also introduced to simulate citrus in nature for data enhancement. The test results show that the improved model has an mAP of 84.84%, 22% smaller than that of YOLOv4, and approximately two times faster. Compared with the Faster R-CNN, the improved citrus flower rate statistical model proposed in this study has the advantages of less memory usage and fast detection speed under the premise of ensuring a certain accuracy. Therefore, our solution can be used as a reference for the edge detection of citrus flowering.
A closed-form analytical forward transit time model considering specific models for bandgap-narrowing effects and concentration-dependent diffusion coefficients for BJT devices operating at 77 K

The authors report a closed-form analytical low-temperature forward transit time model considering bandgap-narrowing effects and concentration-dependent diffusion coefficients based on the entire shape of the emitter and base doping profiles for bipolar junction transistor (BJT) devices operating at 77 K. As verified by the PISCES simulation results, the new closed-form analytical model provides a better low-temperature forward transit time model compared to the model in which bandgap-narrowing effects and concentration-dependent diffusion coefficients are not considered. >
Dynamics of the spatial organization of recreation in the zone of influence of St. Petersburg in the second decade of the 21st century

The results of research on the key area "Sestra River" (229 km2), located within St. Petersburg and the Leningrad region, are considered. The study of recreational development of the territory was carried out in 2009-2010 and 2019-2020 using field surveys, analysis of topographic maps of different times and satellite images. Maps of recreational development of the model territory for the 1960s, 2010, and 2020 were compiled. In 2010, 16 types of land use were identified as the territories that have a recreational function as the main or additional one; this number does not include complexes with a primary residential and additional recreational function (cottage settlements, etc.). In 2020, 17 types of such territories were identified. Comparison of maps of recreational development revealed qualitative changes in various recreational complexes in 2010-2020: collective gardens, social dachas, year-round and seasonal complexes with low-rise buildings, cultural entertainment and sports-entertainment centers, etc. Over 10 years, the share of the area of recreational and residential-recreational complexes at the "Sestra River" key area has increased from 4.8 to 5.2 %. Recreational activities are being diversified. While preserving its traditional types, new types appear: farms with a recreational function, rope parks, entertainment complexes, etc. Recreational complexes for year-round use with low-rise buildings on forest land are being created. Cottage development becomes comparable to recreational development of the territory. A significant part of the houses in cottage and dacha settlements and collective gardens are used as permanent residence; at the same time, their recreational function becomes additional. Increasing the area of cottage settlements on forest land reduces the availability of landscapes of high recreational value for the population. Recreational transformation of territories, which is inseparable from suburbanization in the zones of influence of major cities, is rapidly changing the landscapes.
Groundwater Flow Modeling: A Case Study of the Lower Rusizi Alluvial Plain Aquifer, North-Western Burundi

The study area, in northwestern Burundi, is an alluvial plain consisting of fine clayey sands and coarse sands with mixed lithology. The aquifer of the lower Rusizi plain could be considered as confined under a clay layer. A 2D horizontal groundwater flow model was developed under steady-state conditions using the Modflow software. The study aims to determine the most productive areas of this confined alluvial aquifer and the main aquifer inflow and outflow values together with the recharge and river–aquifer interactions. The groundwater potential is dependent on the spatial distribution of hydraulic conductivity and aquifer thickness values providing the local transmissivity values. The calibrated model made it possible to assess the spatial distribution of the hydraulic conductivity values at the regional scale, which ranged from 6 × 10−6 (contact between alluvial plain and Precambrian basement) to 7.5 × 10−3 m/s (coastal barriers). The results also provided the computed groundwater flow directions, and an estimation of the groundwater levels in areas not yet investigated by drilling. The results of the computed groundwater flow budget allowed us to deduce that recharge and river–aquifer interaction constitute the main inflow while the downwards boundaries (where piezometric heads could be prescribed) are the main zones where outflows occur. The results of this model can be used in the planning of pumping test programs, locating areas with high groundwater potential to plan water supply for different private and public users. This predictive tool will contribute to the resolution of problems related to the use and integrated management of the groundwater resource in this part of Burundi.
The Intersection of Reproductive, Work-Life Balance and Early-Education and Care Policies: ‘Solo’ Mothers by Choice in the UK and Spain

This article focuses on women who have opted to be mothers on their own by choice in the UK and Spain, and how their access to assisted reproductive technologies in the National Health Service was affected because they were 35 years old or older, forcing them to go to private clinics for their treatment. Having given birth to their children, the participants face a second obstacle: the lack of policies that support work-life balance. A third obstacle also arises, in the form of a lack of childcare and early-education provision, particularly in the UK. The last two obstacles affect the whole population, but they are intensified in the case of solo-mother-families where the mother is responsible for simultaneously being the caregiver and the sole economic provider. Solo motherhood by choice highlights the impact of the absence of these policies, and the inequalities that result from current contemporary conceptualizations of family, woman and early-childhood-care and education. This article draws on ethnographic research that took place in the UK and Spain where I conducted 60 in-depth interviews and participant observations. The aim is to provide an analysis capable of capturing and confronting how inequalities affect women-mothers-workers and their children.
Conformal four-beam antenna arrays with reduced sidelobes

Investigations on sidelobe reduction in multibeam conformal antenna arrays are presented. The recently presented concept of sidelobe reduction in planar multibeam antenna arrays in conjunction with the phase compensation technique has been applied for the design of reduced sidelobe multibeam conformal antenna arrays. Six- and eight-element antenna arrays fed by modified Butler matrices have been investigated and minimum radii have been found for which the sidelobe level is comparable to the respective planar multibeam arrays. A novel fully integrated six-element four-beam antenna array has been successfully designed in which sidelobes equal -14 dB for all four beams have been achieved.
Automatic License Plate Recognition Using Deep Learning Techniques

ix Chapter One: Introduction . 1 1.1 Automatic license plate recognition system . 1 1.1.1 Difficulties . 2 1.2 Machine learning fundamentals . 2 1.2. 1 Supervised vs unsupervised learning . 2 1.2. 1.1 Supervised learning . 2 1.2. 1.2 Unsupervised learning . 4 1.3 Introduction to the deep learning . 4 1.3.1 Deep learning vs conventional learning . 5 1.3. 2 Cost functions . 6 1.3. 3 Numerical optimization . 7 1.4 Organization of thesis . 7 Chapter Two: Background . 9 Chapter Three: License Plate Segmentation . 13 3.1 Preprocessing of license plate . 15 3.1.1 Anisotropic diffusion . 16 3.1.2 Histogram equalization . 17
Research on Service Effort Coordination of E-tailer Supply Chain Based on Differential Game

In a supply chain consisting of an e-tailer and a third-party logistics (TPL) supplier, both logistics service effort and the level of brand goodwill can affect the demand of commodity. This paper studies the coordination of supply chain in the context of logistics service effort. Using differential game theory, the optimal results of logistics service effort and brand goodwill are obtained both in centralized and decentralized decision-making scenarios, and the market demand and total profit of the supply chain system are compared through numerical experiments. The results show that the logistics service effort, market demand and total profit of the supply chain are the largest under the centralized decision-making scenario. It can be seen that the centralized decision-making can achieve the largest efficiency of the supply chain system. The contract provided by the e-tailer can incentives the TPL to work hard, but the total profit of the supply chain is reduced under the decentralized decision-making scenario. This paper can provide a theoretical basis for the scientific decision-making of supply chain members in service level improvement behavior, incentive mechanism design, and choice of game structure.
Engineered Exosomes for the Targeted Delivery of a Novel Therapeutic Cargo to Enhance Sorafenib-Mediated Ferroptosis in Hepatocellular Carcinoma.

Background Sorafenib is one of the few effective first-line drugs approved for the treatment of advanced hepatocellular carcinoma (HCC). However, the development of drug resistance is common among individuals with HCC. Thus, there is an urgent need to solve this problem. Results Recent evidence indicated that the anticancer activity of sorafenib mainly relies on the induction of ferroptosis. In our study, genes that suppress ferroptosis, especially GPX4 and DHODH, were enriched in sorafenib-resistant cells and primary tissues and were associated with poor prognosis of HCC patients who received sorafenib treatment. Therefore, silencing GPX4 and DHODH might be a novel and effective strategy to overcome sorafenib resistance. Here, a novel ferroptosis inducer comprising a multiplex small interfering RNA (multi-siRNA) capable of simultaneously silencing GPX4 and DHODH was created. Then, exosomes with high multi-siRNA loading and HCC-specific targeting were established by fusing the SP94 peptide and the N-terminal RNA recognition motif (RRM) of U1-A with the exosomal membrane protein Lamp2b. The results from the in vitro and in vivo experiments indicate that this tumor-targeting nanodelivery system (ExoSP94−lamp2b−RRM-multi-siRNA) could enhance sorafenib-induced ferroptosis and overcome sorafenib resistance, which might open a new avenue for clinically overcoming sorafenib resistance. Conclusions We designed HCC-targeted exosomes (ExoSP94−Lamp2b−RRM) that can deliver a novel ferroptosis inducer. Our data show that ExoSP94−lamp2b−RRM-multi-siRNA could enhance sorafenib-induced ferroptosis by silencing GPX4 and DHODH expression and consequently increase HCC sensitivity to sorafenib. This is the first study to describe the use of engineered exosomes to overcome acquired sorafenib resistance with respect to ferroptosis.
Effects of Modified Thermoplastic Starch on Crystallization Kinetics and Barrier Properties of PLA

This study reports on using reactive extrusion (REX) modified thermoplastic starch particles as a bio-based and biodegradable nucleating agent to increase the rate of crystallization, percent crystallinity and improve oxygen barrier properties while maintaining the biodegradability of PLA. Reactive blends of maleated thermoplastic starch (MTPS) and PLA were prepared using a ZSK-30 twin-screw extruder; 80% glycerol was grafted on the starch during the preparation of MTPS as determined by soxhlet extraction with acetone. The crystallinity of PLA was found to increase from 7.7% to 28.6% with 5% MTPS. The crystallization temperature of PLA reduced from 113 °C to 103 °C. Avrami analysis of the blends showed that the crystallization rate increased 98-fold and t1/2 was reduced drastically from 20 min to <1 min with the addition of 5% MTPS compared to neat PLA. Observation from POM confirmed that the presence of MTPS in the PLA matrix significantly increased the rate of formation and density of spherulites. Oxygen and water vapor permeabilities of the solvent-casted PLA/MTPS films were reduced by 33 and 19% respectively over neat PLA without causing any detrimental impacts on the mechanical properties (α = 0.05). The addition of MTPS to PLA did not impact the biodegradation of PLA in an aqueous environment.
Collaborative supply chain planning using the artificial neural network approach

The purpose of this paper is to show how the concepts of collaborative agents and artificial neural networks (ANNs) can work together to enable collaborative supply chain planning (SCP). An agent‐based supply chain network is decomposed into multiple ANNs in a way that the actual customer requirements and the agents' goals and constraints are matched in different stages. An error‐minimising algorithm which models the agents' collaboration mechanism is used to train three ANNs, namely the supply net, the production net and the delivery net, for pursuing complete order fulfilment across the supply chain. In the example problem, the collaborative SCP paradigm is applied to determine the supply plan of an alliance of small firms, which provides assemble‐to‐order goods with short delivery lead‐time to a regional market. The calculation results showed that the ANN approach achieved complete order fulfilment and significantly increased the resource utilisation of all supply chain agents.
Microsatellite Instability Analysis (MSA) for Bladder Cancer: Past History and Future Directions

Microsatellite instability (MSI), the spontaneous loss or gain of nucleotides from repetitive DNA tracts, is a diagnostic phenotype for gastrointestinal, endometrial, colorectal, and bladder cancers; yet a landscape of instability events across a wider variety of cancer types is beginning to be discovered. The epigenetic inactivation of the MLH1 gene is often associated with sporadic MSI cancers. Recent next-generation sequencing (NGS)-based analyses have comprehensively characterized MSI-positive (MSI+) cancers, and several approaches to the detection of the MSI phenotype of tumors using NGS have been developed. Bladder cancer (here we refer to transitional carcinoma of the bladder) is a major cause of morbidity and mortality in the Western world. Cystoscopy, a gold standard for the detection of bladder cancer, is invasive and sometimes carries unwanted complications, while its cost is relatively high. Urine cytology is of limited value due to its low sensitivity, particularly to low-grade tumors. Therefore, over the last two decades, several new “molecular assays” for the diagnosis of urothelial cancer have been developed. Here, we provide an update on the development of a microsatellite instability assay (MSA) and the development of MSA associated with bladder cancers, focusing on findings obtained from urine analysis from bladder cancer patients as compared with individuals without bladder cancer. In our review, based on over 18 publications with approximately 900 sample cohorts, we provide the sensitivity (87% to 90%) and specificity (94% to 98%) of MSA. We also provide a comparative analysis between MSA and other assays, as well as discussing the details of four different FDA-approved assays. We conclude that MSA is a potentially powerful test for bladder cancer detection and may improve the quality of life of bladder cancer patients.
Evaluating the Dominant Controls of Water Erosion in Three Dry Valley Types Using the RUSLE and Geodetector Method

The dry valley is a unique geographic phenomenon in Southwest China with severe water erosion. However, little is known regarding its dominant controls and the discrepancies between dry valley subtypes, leading to the poor management of water erosion. To solve these problems, the revised universal soil loss equation (RUSLE) and Geodetector method were used in a dry temperate (DT), dry warm (DW), and dry hot (DH) valley. Results indicated that dry valleys suffer severe water erosion with a value of 64.78, 43.85, and 33.81 t·ha−1·yr−1. The Geodetector method is proven to be an efficient tool to quantify the dominant factor of water erosion. It was established that land use types (LUT) have the closest relationship with water erosion. The controls for water erosion could be better explained by multi-factor interactions analysis, particularly for the combination of slope and LUT in DW (q = 0.71) and DH (q = 0.66). Additionally, regions at high risk of water erosion were characterized by steep slope (>30°) and low vegetation coverage (<50%) in DT, while the opposite is shown in DH. These findings could provide insight for guiding soil erosion management and ecological restoration strategies that balance economic and environmental sustainability.