Miracle-dz/UniFAR-FTUs huggingface dataset:
Immediate Effects of Kinesio-taping and Joint Mobilisation on Shoulder in Over-head Athletes with Glenohumeral Internal Rotation Deficit

The purpose of this study was to compare efficacy of kinesio taping (K-taping) and joint mobilization as immediate interventions for treating athletes with glenohumeral internal rotation deficit (GIRD). Thirty-two asymptomatic players were recruited from basketball, volleyball and handball who had a loss of shoulder internal rotation range of motion (IR ROM) of 10 degrees or more on their dominant compared to non-dominant side. They were randomly assigned to 1 of 2 groups: K-taping (n = 16) or joint mobilization (n = 16). Participants in taping group were treated with K-tape for inhibition of external rotators of shoulder and participants in joint mobilization group were treated with grade four Maitland’s mobilization technique for increasing glenohumeral internal rotation. Shoulder internal and external ROM were measured before and after the intervention with a universal goniometer. Both the methods produced significant improvement in IR ROM. The unpaired t-test showed significant change in IR ROM within both the groups (p = 0.003). No significant change was found on comparing both the groups (p = 0.373). There were no significant differences between results of the three sports (p = 0.592). K-taping and joint mobilization both are equally effective in improving the IR ROM in over-head players with GIRD.
Feature First: Advancing Image-Text Retrieval Through Improved Visual Features

Current image-text retrieval methods mainly utilize region features that provide object-level information to represent images, making the retrieval results more accurate and interpretable. However, there are several issues with region features, such as lack of rich contextual information, loss of object details and risk of detection redundancy. The ideal visual features in image-text retrieval should have three characteristics: object-level, semantically-rich, and language-aligned. To this end, we propose a novel visual representation framework to capture more comprehensive and powerful visual features. Specifically, since these region feature disadvantages are the grid feature advantages, we first build a two-step interaction model to explore the complex relationship between them from the spatial and semantic perspectives to integrate their complementary information, making the fused visual features both object-level and semantic-rich. Then, we design a text-integrated visual embedding module that utilizes textual information as guidance to filter redundant regions, further endowing visual features with language-aligned capabilities. Finally, we develop a multi-attention pooling module to better aggregate these enhanced visual features in a more fine-grained manner. Extensive experiments demonstrate that our proposed model achieves state-of-the-art performance on the benchmark datasets Flickr30K and MS-COCO.
Temperature-Insensitive Vibration Sensor With Kagomé Hollow-Core Fiber Based Fabry–Perot Interferometer

Based on Fabry–Perot interferometer, an all-fiber temperature-insensitive vibration sensor using a Kagomé hollow-core photonic crystal fiber, is investigated. The Fabry–Perot cavity is realized by splicing a ∼18.5 mm Kagomé fiber with two single-mode fibers. Owing to the essential characteristic features of Kagomé fiber, this vibration sensor possesses advantageous properties, such as compact size, enhanced sensitivity and good immunity to temperature fluctuations. It has extended single-frequency response spanning from 1 to 20000 Hz, as well as flexible detection of complex vibration signals. The experimental results show that, within a certain range of 0.2–5 m/s2, the output signal of the sensor changes linearly to the vibration acceleration. The temperature-induced fringe shift is also measured at 0.57 pm/°C in the range from 30 °C to 100 °C, indicating that the vibration sensing is quite insensitive to ambient temperature fluctuations. This temperature-insensitive vibration sensor shows promising potentials in structural health monitoring and environmental surveillance.
Effects of fingerroot (boesenbergia rotunda) powder on egg performance, and quality, egg yolk malondialdehyde in laying hens

This study aimed to determine the effect of fingerroot powder supplementation on the performance of laying hens, egg quality, and malondialdehyde in the egg yolk. A total of 192 Hy-Line brown laying hens aged 43 weeks were divided into four treatment groups with 48 hens in each group (8 replicates; 6 birds each). The treatments were the control (basal diet), basal diet supplemented with vitamin E at 250 mg/kg, basal diet plus 20 g fingerroot powder/kg, and basal diet plus 40 g fingerroot powder/kg. Performance parameters were analyzed in the following two experimental period: 1 to 3 week and 4 to 6 week of treatment administration. Egg quality was evaluated twice at 3 and 6 weeks after feeding. The malondialdehyde (MDA) was measured in egg yolk at 0, 7, 14, and 21 days after storage at room temperature. No significant differences were observed in egg weight, laying rate, egg mass, feed intake and feed conversion ratio among the groups during the first experimental period. In the last period 4 to 6 week of experiment, dietary inclusion of 20 g fingerroot powder improved egg weight (P < 0.05) compared with control. The performance showed that during 6 weeks of feeding, the group supplemented with 40 g fingerroot powder had a decreased feed intake, but its feed conversion ratio was improved. The low feed intake in this group did not affect the laying rate, egg weight, and egg mass. There was no significant difference in egg quality for all variables except yolk color at 3 weeks of feeding. The yolk color was significantly lower in the feed supplemented with fingerroot powder at 40 g (P < 0.05). The egg quality at 6 weeks of feeding showed that 20 g fingerroot powder group had higher albumen and shell weight (P < 0.05). The experimental diets did not affect MDA levels in fresh or stored eggs. However, MDA level was affected by storage time and increased at 21 days. In this study, vitamin E� or fingerroot powder did not show their antioxidant activity on the egg yolk. In conclusion, the addition of fingerroot powder has beneficial effects on egg weight, FCR, albumen and shell weights.
Remoción de cromo en aguas residuales industriales mediante el uso de biomasa de Spirulina sp, sedimentación primaria y precipitación química

El cromo es un metal pesado ampliamente usado a nivel industrial y vertido comúnmente de manera directa a fuentes hídricas, lo que conlleva a un deterioro de las mismas. Por lo tanto, esta investigación busca comprobar la remoción de cromo ejercida mediante tratamiento físico, químico y biológico en aguas residuales industriales, con el fin de determinar cuál alternativa resulta más sostenible.Para ello se implementaron a escala laboratorio ocho reactores con agua residual industrial de una empresa del sector metalmecánico; inicialmente se evaluó la remoción de cromo mediante sedimentación primaria logrando remociones del 16%; posteriormente, se verificó el efecto llevado a cabo mediante precipitación química con sulfato de aluminio y oxido de calcio; por último, se evaluó la capacidad de biosorción de la microalga Spirulina sp utilizando biomasa viva y muerta a las 24 y 96 horas. Encontrando que existen mecanismos de fácil implementación para evitar vertimientos directos, además se encontró que el tratamiento químico logra disminuir el cromo a valores inferiores de 0.1 mg/l, con remociones del 99%, sin embargo, genera más del 30% de lodos y no favorece la separación del metal. Con el uso de biomasa se alcanzaron remociones de hasta el 96.5% en las primeras 24 horas y un valor final de cromo de 1.02 mg/l, presentando la ventaja que este método genera menos del 10% de lodos y permite recuperar el cromo para su posterior uso. De modo que, se recomienda la implementación de un tratamiento físico-biológico, puesto que mejora la sostenibilidad del proceso.
FDI spillover channels on Chinese provincial economic growth 


China has been opened to the world over several years and make great success in economic growth. Most of the previous literatures have analyzed the determinants of economic growth and the effect of FDI on economic growth in China. However, seldom of them analyze the relationship of FDI and its spillover effect on economic growth through R&D and human capital channels using provincial data. The study employs provincial panel data during period 2006-2018 to estimate the relationship of FDI, FDI spillover from R&D and human capital, R&D, and human capital on economic growth under the consideration of Special economic Zone and Free Trade Zone in China. The analysis suggests that FDI has a significant positive contribution on the growth rate of real GDP per capita in China. Therefore, government should maintain high inflow of FDI and make more preferential policies to attract FDI to invest in China. The result also shows that population growth rate would help promote economic growth. The government should keep the population growth rate to help stimulating growth. Moreover, the empirical result shows that current inflation is also a factor to foster economic growth. This study cannot prove the contribution of human capital, R&D and FDI spillover through human capital and R&D on growth rate due to lack of skilled labor in provincial data and the decline of R&D efficiency in China. The study suggests that more favorable policies and measures can be used to target FDI in industries with high technology. In addition, stimulating advanced R&D level and technological transfer could accelerate economic growth.
Vegetation Impacts of Recurring Fires on Sagebrush Ecosystems in Washington: Implications for Conservation and Rehabilitation

Thousands of hectares of high quality shrub steppe burned in large fires in 2000 and 2007 in the Arid Lands Ecology (ALE) Reserve on the Hanford Reach National Monument. Extensive permanent vegetation monitoring plots were established throughout this area in the mid-1990s, and many of these plots were remonitored following the 2000 fire. In addition, rehabilitation efforts to control invasive species (e.g., Bromus tectorum) and establish native species took place following this fire. This combination of monitoring and rehabilitation treatments provide a unique opportunity to better understand the individual and cumulative effects of recurring fires in this landscape. These fires may have significantly altered the trajectory of
Comments on the genus Amyzon (family Catostomidae)

At least four of the seven described species of Amyzon are valid species with doubtful status given to Amyzon pandatum Cope, 1874, and Amyzon fusiforme Cope, 1875. Amyzon gosiutensis Grande, Eastman, and Cavender, 1982, is a junior synonym of Amyzon aggregatum Wilson, 1977b. The Klondike Mountain Formation specimens examined from Republic, Washington, are identified as Amyzon aggregatum Wilson, 1977b. The known range of A. aggregatum is extended south to Republic, Washington, and southeast to the Laney Shale Member of the Green River Formation, Wyoming.
Improving Alzheimer’s Disease Classification in Brain MRI Images Using a Neural Network Model Enhanced with PCA and SWLDA

The examination of Alzheimer’s disease (AD) using adaptive machine learning algorithms has unveiled promising findings. However, achieving substantial credibility in medical contexts necessitates a combination of notable accuracy, minimal processing time, and universality across diverse populations. Therefore, we have formulated a hybrid methodology in this study to classify AD by employing a brain MRI image dataset. We incorporated an averaging filter during preprocessing in the initial stage to reduce extraneous details. Subsequently, a combined strategy was utilized, involving principal component analysis (PCA) in conjunction with stepwise linear discriminant analysis (SWLDA), followed by an artificial neural network (ANN). SWLDA employs a combination of forward and backward recursion methods to choose a restricted set of features. The forward recursion identifies the most interconnected features based on partial Z-test values. Conversely, the backward recursion method eliminates the least correlated features from the same feature space. After the extraction and selection of features, an optimized artificial neural network (ANN) was utilized to differentiate the various classes of AD. To demonstrate the significance of this hybrid approach, we utilized publicly available brain MRI datasets using a 10-fold cross-validation strategy. The proposed method excelled over existing state-of-the-art systems, attaining weighted average recognition rates of 99.35% and 96.66%, respectively, across all the datasets.
Automatic cardioembolic stroke prediction using clinical features and non-contrast CT images

Cardioembolic stroke is a dangerous subtype of ischemic stroke. The patients with this subtype need special treatments to prevent recurrent events. The prevention is vital since only one more event could result in fatal damage. Hence, the classification into the categories of cardioembolic and non-cardioembolic subtypes is essential. We developed a multimodal machine learning model that can integrate the basic clinical information and non-contrast CT images to predict the risk of cardioembolic stroke. Our method reached the areas under the receiver operating characteristic curve (ROC-AUC) of 0.840 by using a dataset of only 227 samples of stroke patients. Besides the capability to classify the stroke subtypes, the method can provide the interpretability of the model decision in the forms of the heatmap for large infarct localization and the feature impacts for interpretation. Our approach can be widely applied since we need only the basic clinical information and non-contrast CT which are commonly available in general hospitals.
Multi‐fidelity Gaussian processes for an efficient approximation of frequency sweeps in acoustic problems

This paper presents a multi‐fidelity model for the acceleration of frequency sweep analyses in acoustics. In traditional analyses, the frequency‐dependent Helmholtz equation is repetitively solved at each frequency. Using the boundary element method requires then a plethora of evaluations resulting in high computational costs. In the proposed method, the fidelity levels are realized as Gaussian processes, which are conditioned on observations obtained by boundary element simulations. A coarse boundary element mesh is considered as the low‐fidelity model, whereas a fine mesh is adopted as the high‐fidelity model. To validate the proposed framework, the vehicle interior noise problem is investigated. The results demonstrate that multi‐fidelity Gaussian processes efficiently accelerate the frequency sweep analysis, as they provide accurate and fast predictions across the entire frequency range of interest. As a beneficial side effect, the present method takes uncertainties into account. This allows to consider limited information on the model, which is particularly important in early design phases.
A First Look at the Spatial and Temporal Variability of Internet Performance Data in Hyperlocal Geographies

Measuring Internet access network performance has been a persistent challenge for researchers and policymakers alike. Unfortunately, existing “speed test” datasets typically lack comprehensive data across both space and time. Specifically, our past work has highlighted that tools like Ookla’s Speed TestandMeasurementLab’sNDTrelyheavilyonconveniencesamples(user-initiatedtestsfromself-selectedparticipants), resultinginasamplethatmaynotgeneralizeacrosseither timeorgeography.Ourongoingresearchseekstoaddress theseissuesbydevelopinginnovativesamplingmethodsandstatisticalmodelstoprovideamoreholisticviewofInter-netperformance.Initialfindings,focusingonend-to-endla-tencyacrosshyper-localregionswithinasinglelargecity intheUnitedStates(Chicago,Illinois),revealthatspatial proximityoftendoesnotcorrelatewithsimultaneousperfor-manceanomalies.Theseinsightsunderscoretheneedfor advancedmethodstogeneralizeInternetperformancedata acrosstimeandspace.Improvedmethodscanultimatelyen-ableabetterunderstandingoftheeffectsofinfrastructure investmentsontheevolutionofInternetperformance.
Body weight support treadmill training improves blood glucose regulation in persons with 1 incomplete spinal cord injury 2

The impact of a six month body weight supported treadmill (BWST) training program on glucose 2 homeostasis and muscle metabolic characteristics was investigated. Nine individuals (31±3 yr, 3 8.1±2.5 yr post-injury; means±SE) with incomplete spinal cord injury (SCI) trained three times 4 weekly for a total of six months. Training session duration and intensity (velocity) increased by 5 54 ± 10% (P<0.01) and 135 ± 20%, respectively. Muscle biopsies and a modified glucose tolerance test 6 (100g glucose with [U- 13 C]glucose) were performed before (PRE) and after training (POST). 7 Training resulted in a reduction in area under the curve (AUC) of glucose x time (-15±4%) and 8 insulin x time (-33±8%; both P<0.05). Oxidation of exogenous (ingested) glucose increased as a 9 result of training (PRE = 4.4 ± 0.7 g/h, POST = 7.4 ± 0.6g/h; P<0.05), as did oxidation of endogenous 10 (liver) glucose (PRE = 3.8 ± 0.3 g/h, POST = 5.2 ± 0.3 g/h; P<0.05). Training resulted in increased 11 muscle glycogen (80 ± 23%; P<0.05) and GLUT-4 content, and hexokinase II enzyme activity 12 (126 ± 34% and 49 ± 4%, respectively, both P<0.01). Resting muscle PCr content also increased 13 following training (PRE = 62.1 ± 4.3, POST = 78.7 ± 3.8, both mmol/kg dry weight and P<0.05). Six 14 months of thrice weekly BWST training in persons with an incomplete spinal cord injury improved 15 blood glucose regulation by increasing oxidation and storage of an oral glucose load. Increases in the 16 capacity for transport, and phosphorylation glucose in skeletal muscle are likely playing a role in 17 these adaptations. (GLUT 4) content and improve whole body insulin action (9,25,27,37). These results indicate that skeletal responds to involuntary activity with the induction of the skeletal muscle GLUT 4 transporter protein, which is due to a local contractile stimulus. Moreover, the chronic 3 increase in muscle GLUT 4 transporter content induced by FES is insulin-responsive (9,25,37). In 4 persons with an incomplete SCI, some forms of voluntary exercise are still possible. Moreover, 5 persons with a SCI frequently identify functional ambulation as one of their rehabilitation goals. Body weight supported treadmill (BWST) training (Laufband therapy) has been shown to restore a degree of ambulatory capacity in some individuals with incomplete spinal cord injuries No information is currently available, however, on how BWST training affects oral glucose tolerance or insulin sensitivity.
Biometrics and moult of Grey-backed Sparrow-lark Eremopterix verticalis in the Karoo, September 2023

The biometrics of Grey-backed Sparrow-larks Eremopterix verticalis in the handbooks are based on small samples. We summarize wing-length, tail-length and mass of a sample of 130 Grey-backed Sparrow-larks mistnetted during ringing on the farm New Holme, Hanover District, Northern Cape, South Africa, in September 2023. The habitat was Grassy Karoo with, on average, March being the month of peak annual rainfall. The sample consisted of 58 females and 72 males. We examined birds for primary moult; 5% had moulted either one or two primaries, indicating that moult was commencing in the population as a whole. This observation, set in the context of an observation made in Namibia, suggests that this species undertakes a pre-breeding moult in spring and summer, prior to breeding in late summer and autumn.
Examining the Summertime Ozone Formation Regime in Southeast Michigan Using MOOSE Ground‐Based HCHO/NO2 Measurements and F0AM Box Model

Ambient ozone (O3) concentrations in Southeast Michigan (SEMI) can exceed the U.S. National Ambient Air Quality Standard. Despite past efforts to measure O3 precursors and elucidate reaction mechanisms, changing emission patterns and atmospheric composition in SEMI warrant new measurements and updated mechanisms to understand the causes of observed O3 exceedances. In this study, we examine the chemical drivers of O3 exceedances in SEMI, based on the Phase I MOOSE (Michigan‐Ontario Ozone Source Experiment) field study performed during May to June 2021. A zero‐dimensional (0‐D) box model is constrained with measurement data of meteorology and trace gas concentrations. Box model sensitivity simulations suggest that the formaldehyde to nitrogen dioxide ratio (HCHO/NO2) for the transition between the volatile organic compounds (VOCs)‐ and nitrogen oxides (NOx)‐limited O3 production regimes is 3.0 ± 0.3 in SEMI. The midday (12:00–16:00) averaged HCHO/NO2 ratio during the MOOSE Phase I study is 1.62 ± 1.03, suggesting that O3 production in SEMI is limited by VOC emissions. This finding implies that imposing stricter regulations on VOC emissions should be prioritized for the SEMI O3 nonattainment area. This study, through its use of ground‐based HCHO/NO2 ratios and box modeling to assess O3‐VOC‐NOx sensitivities, has significant implications for air quality policy and the design of effective O3 pollution control strategies, especially in O3 nonattainment areas.
Applying Active Learning in Undergraduate Research Methods

ABSTRACT This article introduces a bundle of active learning activities for an introductory undergraduate course in research methods. In particular, the activities aim to help students develop core knowledge and skills that provide a foundation for reading and conducting quantitative and qualitative research. Active learning is a pedagogical practice with well-established benefits such as better student attitudes and improved content comprehension and application. I build on this conventional wisdom by applying a student-centred evaluation method, demonstrating that students perceive active learning as an effective complement to traditional lecturing and assignments for learning core methodological topics in political science.
Tour into the picture: using a spidery mesh interface to make animation from a single image

A new method called TIP (Tour Into the Picture) is presented for easily making animations from one 2D picture or photograph of a scene. In TIP, animation is created from the viewpoint of a camera which can be three-dimensionally "walked or flownthrough" the 2D picture or photograph. To make such animation, conventional computer vision techniques cannot be applied in the 3D modeling process for the scene, using only a single 2D image. Instead a spidery mesh is employed in our method to obtain a simple scene model from the 2D image of the scene using a graphical user interface. Animation is thus easily generated without the need of multiple 2D images. Unlike existing methods, our method is not intended to construct a precise 3D scene model. The scene model is rather simple, and not fully 3D-structured. The modeling process starts by specifying the vanishing point in the 2D image. The background in the scene model then consists of at most five rectangles, whereas hierarchical polygons are used as a model for each foreground object. Furthermore a virtual camera is moved around the 3D scene model, with the viewing angle being freely controlled. This process is easily and effectively performed using the spidery mesh interface. We have obtained a wide variety of animated scenes which demonstrate the efficiency of TIP. CR