Miracle-dz/UniFAR-FTUs huggingface dataset:
A comparative study of functional outcome of extra articular distal femur fractures treated, with retrograde nailing versus locking compression plate

Aim: To compare the functional outcome of supracondylar fractures of distal femur managed by Supracondylar nailing (retrograde) and locking femoral compression plate. Introduction: Early before 1980, supracondylar fractures of femur were treated with non locking plates. Plaster immobilization and traction were mode of treatment for non-operative patients. Nowadays the knowledge of internal fixation has evolved as to treat complex fractures by cancellous screws, 95 degree blade plate, dynamic condylar screw and plate, condylar buttress plates, locking femoral compression plate and supracondylar nailing (retrograde). Trending procedures for supracondylar fractures of femur are supracondylar nail (retrograde) and locking femoral compression plate. Materials and Methods: Totally 30 patients of extra articular distal femur fractures treated in Rajah Mathai Medical College from May 2019 to June 2021. Patients were treated by random allocation as 15 patients by retrograde nailing and other 15 patients by distal femur locking compression plate. Functional outcome was compared between them according to Neer’s Scoring System at 24 weeks. Results: In our study, the patients were screened upto 1 year. Assessment was based on both radiologically and clinical scoring. Neer's score was higher in nailing (54%) compared to plating (46%). Conclusion: From our study, nailing proved to have good functional outcome in terms of early weight bearing, knee flexion and less union time. Both nailing and plating have excellent results with proper preoperative planning.
pH Dependent Binding Energies of Broadly Neutralizing Antibodies

Understanding how pH modulates underlying protein-protein interaction requires in-depth analysis across combinations of HIV proteins and broadly neutralizing antibodies (bnAbs). Traditional labs are not practical to screen all sequence variations and titrate of pH, highlighting the need to analyze such interactions theoretically. To fill this need, we generate homology models of predetermined HIV-1 gp120 in complex with bnAbs, through computational simulations to observe the binding energies as environmental pH varies. We compare simulation data to experimental data of the same structures at pH 5.5 and pH 7.4 specifically to present an 83.3% agreement between the two approaches to support the hypothesis that binding is stronger at lower pH. We then make observations of binding energy predictions across broad spectrum pH to provide insight into factors limiting the effectiveness of bnAbs in vivo. We conclude that theoretical models, and simulations involving them, provide data that closely mimic those of laboratory results.
The Resilience of Small-Scale Fishing Households to the Anthropogenic Environmental Shocks

The Resilience of Small-Scale Fishing the Anthropogenic Environmental Shocks. Abstract The marine environmental incident causing mass fish death in Central Vietnam by Formosa Ha Tinh Steel Plant in 2016 severely impacted people's livelihoods in four provinces. Several previous studies have indicated that diversifying livelihoods is one of the best solutions to increase the resilience of households to overcome such incidents. This study investigated the relationship between livelihood diversification and the stability of small-scale fishing households. Our findings showed that impact levels and resilience capacity under family perception are important aspects for impact assessment in the context of the environmental shock. Local families can diversify their livelihoods based on their resources as well as through government-supporting policies. The livelihood diversification of impacted households is significantly valuable in increasing the resilience process after the Formosa incident. Families with more livelihood activities related to income sources have better resilience than families with less livelihood activities. By the effort of households and government support policies, impacted households have gradually improved their livelihood resilience.
The Spatial Distribution of the House Mouse, Mus musculus domesticus, in Multi-Family Dwellings

Simple Summary The management of house mice, Mus musculus domesticus, in low-income high-rise multi-family dwellings (MFDs) is often frustrated by the limited resources available through low-bid contracting. An improved understanding of the small-scale distribution of this important public health pest could allow the pest management industry to better allocate its limited time and resources to better managing infestations. This study utilized data from two research projects that measured house mouse infestation rates from four urban low-income MFDs to determine if a significant correlation between neighboring units exists in their infestation status. Results show that such a correlation exists whereby apartments that share a wall, ceiling or floor with a neighboring apartment that has a current infestation are more likely to have existing house mouse activity. This information can be utilized by the pest management industry to design monitoring strategies, during integrated pest management activities, to better ensure the elimination of house mice in low-income high-rise MFDs. Abstract The house mouse, Mus musculus domesticus, creates significant public health risks for residents in low-income multi-family dwellings (MFDs). This study was designed to evaluate the spatial distribution of house mice in MFDs. Four low-income high-rise apartment buildings in three cities in New Jersey were selected for building-wide monitoring on two occasions with approximately one year between the monitoring events. The presence of a house mouse infestation was determined by placing mouse bait stations with three different non-toxic baits for a one-week period in all accessible units as well as common areas. Permutation tests were conducted to evaluate house mouse infestation spatial patterns. All four analyzed buildings exhibited a significant correlation between apartments with house mouse infestations and whether they share a common wall or ceiling/floor at both sampling periods except one building during the second inspection, which contained a high number of isolated apartments. Foraging ranges, speed of locomotion, and dispersal behavior of house mice are relatively larger, faster, and more common, respectively, compared to common urban arthropod pests. This could lead to the conclusion that house mice are as likely to infest non-neighboring apartments as those that share a wall or floor/ceiling. However, these results demonstrate that house mouse infestations tend to occur among apartments that share common walls or ceilings/floors. This spatial distribution pattern can be utilized in rodent management plans to improve the efficiency of house mouse management programs in MFDs.
IFRS Convergence and Disclosure Quality: The Role of Audit Quality Moderation (Study on Multinational Companies in Indonesia)

IFRS convergence was initiated through the agreement of the G20 leadership meeting in Washington at 2008. The meeting agreed to use IFRS as an international accounting standard. Adopting IFRS as a single global accounting standard can make Indonesian companies ready and able to transact across countries, or mergers and acquisitions. IFRS supports the readiness of industry in Indonesia to be competitive at the global level. Financial statements based on IFRS produce information more relevant, accurate and more comparable. IFRS can produce valid information on company assets, liabilities, equity, income and expenses. Management will have a high level of accountability to run the company. This study examined the role of audit quality as moderating variable in the relationship between the IFRS convergence and disclosure quality, and studies on multinational companies listed the Indonesian Stock Exchange 2012-2018 period. The research used 63 multinational companies and it tested using the SPSS 25 statistical test tool. The research has proven the effect of IFRS convergence on disclosure quality, and the role of audit quality in strengthening the relationship between the two variables. IFRS convergence applied requires the role of external audit to provide assurance or assurance that the financial statements presented have complied with the standards for preparing financial statements and are fairly presented without material errors.
Relationship between Event Prevalence Rate and Gini Coefficient of Predictive Model

Predictive models are currently used for early intervention to help identify patients with a high risk of adverse events. Assessing the accuracy of such models is a crucial part of the development process. To measure the predictive performance of a scoring model, quantitative indices such as the K-S statistic and C-statistic are used. This paper discusses the relationship between Gini coefficients and event prevalence rates. The main contribution of the paper is the theoretical proof of the relationship between the Gini coefficient and event prevalence rate.
Two-stage beamforming training for multi-user millimetre wave systems

Hybrid analogue/digital precoding technique is widely considered for multi-user millimetre wave (mmWave) systems to reduce the cost and power consumption of radio frequency chains, where beamforming (BF) training is required for the configuration of analogue BF/combining vectors of multiple user equipments (UEs). However, the conventional BF training algorithms suffer from high training overhead increasing with the number of UEs. To address this problem, a two-stage BF training mechanism is proposed for multi-user mmWave systems with time division duplex mode by dividing the BF training process into downlink broadcasting and uplink training. Consequently, multiple UEs can be trained simultaneously and the feedback operation is eliminated. Simulation results demonstrate that the proposed two-stage BF training scheme approaches the optimal performance of exhaustive search with much reduced training overhead.
Single-Phase to Single-Phase Three-Wire Power Converters Based on Two-Level and Three-Level Legs

This article presents two single-phase to single-phase three-wire converters based on two-level and three-level neutral-point-clamped legs. The converters present a shared-leg between the grid and load. A space-vector pulsewidth modulation technique considering the harmonic distortion and the semiconductor losses is presented, besides the dc-link voltage-balance technique to balance the neutral-point voltage. The converters can supply the loads with constant amplitude and frequency under grid voltage disturbances. These characteristics make the proposed converters suitable for applications as uninterrupted power supply. The proposed converters are compared to a conventional two-level converter from simulated results for evaluating the semiconductor losses and harmonic distortion. The experimental results are provided to illustrate and validate the operation of the proposed systems.
Crop and weed classification based on AutoML

CNN models already play an important role in classification of crop and weed with high accuracy, more than 95% as reported in literature. However, to manually choose and fine-tune the deep learning models becomes laborious and indispensable in most traditional practices and research. Moreover, the classic objective functions are not thoroughly compatible with agricultural farming tasks as the corresponding models suffer from misclassifying crop to weed, often more likely than in other deep learning application domains. In this paper, we applied autonomous machine learning with a new objective function for crop and weed classification, achieving higher accuracy and lower crop killing rate (rate of identifying a crop as a weed). The experimental results show that our method outperforms state-of-the-art applications, for example, ResNet and VGG19.
Expect: EXplainable Prediction Model for Energy ConsumpTion

With the steady growth of energy demands and resource depletion in today’s world, energy prediction models have gained more and more attention recently. Reducing energy consumption and carbon footprint are critical factors for achieving efficiency in sustainable cities. Unfortunately, traditional energy prediction models focus only on prediction performance. However, explainable models are essential to building trust and engaging users to accept AI-based systems. In this paper, we propose an explainable deep learning model, called Expect, to forecast energy consumption from time series effectively. Our results demonstrate our proposal’s robustness and accuracy when compared to the baseline methods.
Development and validation of a predictive model for early functional recovery in the post-hip fracture surgery population

INTRODUCTION With a growing ageing population, the incidence of hip fractures and the consequent burden of care are expected to increase. [1,2] To cope with this, effective discharge planning from the acute setting will be paramount. Functional recovery is pertinent to facilitate discharge planning for the elderly population following hip fracture surgery. At present, there is a lack of prognostication studies that can offer insights into functional recovery to guide discharge planning in the acute setting. Our study aimed to identify and analyse pre‐ and postoperative day (POD) one factors in order to develop and validate a predictive model that can prognosticate functional recovery during the early acute stage (i.e. POD 4). This time frame was chosen, as it is usually when most patients are discharged from the acute setting.
Design and Development of Monitoring and Early-warning System for Hazardous Chemicals Transport Vehicles

Necessity and pressure of constructing monitoring system for hazardous chemicals carrying vehicles is analyzed. Following the standards and regulations of hazardous chemicals transport vehicles and integrating various technologies such as computer technique, control theory, communication technique, space positioning and safety management science, overall structure and function diagram for vehicle monitoring and pre-warning system is proposed, seven features of the system are represented. The hardware elements of vehicle terminals, the functions like automatic monitoring, alarm, safe protection and data, video and audio signals communications and the constitution and structure of monitoring center are designed and developed. Approach to monitor transport vehicles from other places is put forward. 5 types of wireless communication modes are compared.
STUDY ON THE GROWTH PATTERNS OF HERRING SCAD, ALEPES VARI (CUVIER, 1833) COLLECTED FROM THE KARACHI COAST OF PAKISTAN

The current study explains the estimation of growth patterns of Herring scad Alepes vari (Cuvier, 1833) collected from Karachi coast, Pakistan. A total of 100 samples (44 males and 56 females) were caught from January to December 2019. The length-weight relationships (LWR) along with correlation coefficients (r) calculated for the combined sexes, males and females of Alepes vari had showed Log Wt = - 1.36 + 2.56 Log TL (r = 0.853), Log Wt = -1.84 + 2.90 Log TL (r = 0.965), and Log Wt = - 0.96 + 2.28 Log TL (r = 0.760). In this study, the general growth pattern for combined sexes, males, and females were observed only positive allometric type (A+) with b -values ranged between 2.28 to 2.90, respectively. The overall results revealed that all length-weight relationships were strongly correlated with ‘r’ values ranging from 0.760 to 0.965, which shows a good health condition of this species. Moreover, the average values of Relative condition factor (Kn) ranging from 0.8 to 1.0, which revealed that both abiotic and biotic factors of the Karachi coast were found in acceptable limits for this species. Thus, our present study will provide useful information on growth patterns and management of Alepes vari along the Karachi coast of Pakistan.
Enhanced Class-Specific Spatial Normalization for Image Generation

We propose enhanced class-specific spatial normalization, a simple yet effective layer to generate a photorealistic image given a spatial-class map. Under the assumption that pixels belonging to the same class share the same distribution in the feature space, we intuitively split an image into classes according to the map. By learning the class-specific distributions, our generator can distinguish one class from other classes. Further, our spatial normalization combines the spatial-class map and the class-specific distributions, by which our generator can produce instances in the desired locations. We apply the proposed normalization not only in semantic image generation but also in object transfiguration. The experimental results demonstrate that the proposed method encourages neural networks to use the spatial-class map efficiently with competing performances, yet much fewer parameters.
Motivation Differences between Youth Single-Sport, Multi-Sport, and Single-Sport Specialized Athletes in the Western United States

The motivation for youth sport involvement may differ for single-sport (non-specialists), multi-sport, and single-sport specialized athletes. To investigate differences between adolescent single-sport athletes (NSSA), multi-sport athletes (MSA), and single-sport specialized athletes (SSSA) on measures of sport enjoyment and motivation. A secondary aim was to compare these variables between age groups. Adolescent sport participants in 6th, 7th, and 8th grade from the Western United States (n=306, age=13.0±1.0 yrs) completing the Sources of Enjoyment in Youth Sport Questionnaire (SEYSQ) that assesses sport enjoyment in the subscales of self-referenced competency (SRC), other-referenced competency and recognition (ORCR), effort expenditure (EE), competitive excitement (CE), affiliation with peers (AP), and positive parental involvement (PPI). The participants also reported their age, gender, grade, years of sport participation and sport status (NSSA, MSA, SSSA). SSSA reported significantly more enjoyment in all subscales except PPI when compared to NSSA (p<0.05; ES 0.4 – 0.99). MSA and SSSA showed significant differences in the subscales of SRC and EE; however, effect size was small (0.37 and 0.33, respectively). Overall scores for intrinsic and extrinsic motivation were significantly lower among NSSA compared to MSA and SSSA (p<0.01) with no differences between MSA and SSSA (p>0.05). Results revealed no significant differences in the SEYSQ’s subscales for age (p>0.05). Within the parameters of this study, adolescents that specialize in a single sport or those who compete in multiple sport both rely on intrinsic and extrinsic sources of enjoyment for motivation in very similar ways; whereas adolescent NSSA are less motivated and experience less enjoyment from sport participation compared to MSA and SSSA. Keywords: adolescent, enjoyment, SEYSQ, motivation, sport psychology
Allan variance analysis on error coefficients of MEMS inertial components

The integration of global navigation satellite system (GNSS) and inertial navigation system(INS) plays more and more important part in many applications. With development of technology, micro-electromechanical systems (MEMS) are introduced into low cost INS. MEMS inertial components has small volume and low power consumption which is fit for the low cost implementations. However, MEMS inertial components have large errors. For the purpose of analyzing and compensating for them, Allan variance method can be used to process the long-term data of inertial components. This paper firstly analyzes the typical error items of MEMS inertial components, and then introduces the principle and algorithm of Allan variance method. Afterward, Allan variance is used to process the long-term static data recorded from commercial MEMS gyroscopes and accelerometers. Results show that Allan variance method can effectively recognize the error coefficients of the inertial components which can be used to model the inertial errors and help to implement and improve the performance of the GNSS/INS integrated navigation systems.
THE CORRELATION BETWEEN WOMEN ENTREPRENEURSHIP AND GENDER UNIFORMITY

This study explores that how the economy depends upon different factors, including quality, gender direction association and the possibility of business. Gender reasonableness and women's undertaking are key factors for monetary unforeseen development. To take a gender at the association between gender consistency and women's undertaking rates, this paper examines how gender direction express financial activities and women's ambitious soul relate. The study depicts the association between the Gender headway rates familiarized by the UN and the dissimilar periods of female business (made by the Global Entrepreneurial Monitor, GEM) through comparability examination. Our results show that women's undertaking is not in a general sense associated with gender correspondence. Keywords: Female undertaking, Gender direction consistency, money related unforeseen development
Combining vascular and nerve fiber layer thickness measurements to model glaucomatous focal visual field loss

We compare the focal structure–function correlation of structural measurements of peripapillary retinal nerve fiber layer thickness (RNFL‐T) using optical coherence tomography (OCT), capillary density (CD) measurements using OCT‐angiography (OCT‐A), or a combination of both, with visual field deviation (VFD) in early to advanced glaucoma. Primary open angle glaucoma patients (n = 46, mean ± SD age: 67 ± 10 years; VF mean deviation: −10.41 ± 6.76 dB) were included in this cross‐sectional study. We performed 30–2 standard automated perimetry OCT (3.5‐mm diameter ring scan) and 15°×15° OCT‐A (superficial vascular complex slab). Based on a nerve fiber trajectory model, each VF test spot was assigned to an OCT‐A wedge and an OCT ring‐sector. Two univariate linear models (Mv and Mt) using either CD‐based vascular (Mv) or RNFL‐T–based thickness information (Mt) and one multivariate model using both (Mv:t) were compared in their associations with measured focal VFD, which were higher for the multivariate model Mv:t (mean ± SD correlation coefficient: 0.710 ± 0.086) than for either nested model (0.627 ± 0.078 for Mv and 0.578 ± 0.095 for Mt). Using a focal visual field approach, the combination of RNFL‐T and CD showed better structure–function correlations than thickness or vascular information only.
The Performance Measurement of Generalized Sharpe Ratio and Economic Performance Measure: A Hedge Funds Example

Prior literature documents that the Sharpe ratio (SR) generates biases in performance evaluation if returns distribution deviates from normal distribution because SR is derived under the mean-variance model with the strict assumption of either quadratic preferences or customarily distributed returns. When the return distributions deviate from normality, it may lead to unreasonable results. Therefore, this study examines which performance measurement approaches are efficient for non-normality on the distribution of asset returns. We collect monthly returns of 14 Credit Suisse (CS) hedges fund indexes from April 1994 to June 2021. The hedge fund index returns exhibit high negative skewness or high positive kurtosis, implying non-normal distribution. Then, we employ the Sharpe ratio (SR) and two performance measures, which extend the Sharpe ratio, the generalized Sharpe ratio (GSR), and the economic performance measure (EPM), to evaluate the performances of hedge funds. In addition, both the nonparametric and parametric estimation methods of the GSR and the EPM are utilized. Our findings indicate that the nonparametric GSR and the nonparametric EPM produce more similar rankings than the SR. Among the three parametric estimation methods of the GSR and EPM, only the method proposed by [1] produces similar rankings with the nonparametric GSR and the nonparametric EPM. Finally, our study contributes the practical approach for fund managers to evaluate their fund performance efficiently.