Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effect of the Crow Hop on Elbow Stress During an Interval Throwing Program

Background: Postoperative rehabilitation protocols after ulnar collateral ligament (UCL) reconstruction typically involve a structured interval throwing program. In an effort to minimize torque placed on the UCL, athletes are often instructed to throw with a crow hop, even at short throwing distances. However, the effect of the crow hop on medial elbow stress is unknown. Purpose/Hypothesis: The purpose was to determine whether elbow stress differs with and without a crow hop across the throwing distances of a typical interval throwing program. We hypothesized that crow hop throws would generate lower torque on the elbow than standing throws at each distance of the interval throwing program. Study Design: Controlled laboratory study. Methods: Healthy high school and collegiate pitchers and position players were recruited from the surrounding area. Each player was outfitted with a wearable athletic sleeve and device that recorded elbow torque (Newton-meters), arm slot (degrees), arm speed (revolutions per minute), and shoulder rotation (degrees). Ball velocity (miles per hour) was measured using a radar gun. Players were instructed to perform 3 crow hop throws and 3 standing throws at distances of 30, 45, 60, 90, 120, 150, and 180 feet. A repeated measures analysis of variance was used to compare ball velocity, elbow torque, arm slot, arm speed, and shoulder rotation between crow hop and standing throws at each throwing distance. Results: Twenty athletes participated in this study (average age, 17.8 years; range, 15-25 years). The average medial elbow torque increased at each distance for both crow hop and standing throws at distances of 30, 45, 60, and 90 feet (P < .05), after which there were no significant increases in elbow torque (P > .05). The average torque was higher for crow hop throws than standing throws at distances of 30 feet (13.9 N·m vs 12.0 N·m; P = .002), 45 feet (21.8 N·m vs 19.3 N·m; P = .005), and 60 feet (28.0 N·m vs 24.5 N·m; P = .02). Conclusion: Crow hop throws generated greater medial elbow torque than standing throws at distances up to 60 feet; however, there were no differences in elbow torque at distances greater than 60 feet between the 2 throw types. For both crow hop and standing throws, elbow stress increased at each distance interval up to 90 feet before plateauing at distances greater than 90 feet. The crow hop throwing technique does not reduce medial elbow stress during a simulated interval throwing program, and it may actually increase torque at shorter throwing distances. Clinical Relevance: The results of our study indicate that it would be prudent for players to initially perform standing throws at shorter distances and only later be allowed to employ a natural crow hop at greater distances to minimize torque placed on the medial elbow during UCL rehabilitation protocols.
Protein phosphatase PPM1B inhibits DYRK1A kinase through dephosphorylation of pS258 and reduces toxic tau aggregation

Down syndrome (DS) is mainly caused by an extra copy of chromosome 21 (trisomy 21), and patients display a variety of developmental symptoms, including characteristic facial features, physical growth delay, intellectual disability, and neurodegeneration (i.e., Alzheimer’s disease; AD). One of the pathological hallmarks of AD is insoluble deposits of neurofibrillary tangles (NFTs) that consist of hyperphosphorylated tau. The human DYRK1A gene is mapped to chromosome 21, and the protein is associated with the formation of inclusion bodies in AD. For example, DYRK1A directly phosphorylates multiple serine and threonine residues of tau, including Thr212. However, the mechanism underpinning DYRK1A involvement in Trisomy 21-related pathological tau aggregation remains unknown. Here, we explored a novel regulatory mechanism of DYRK1A and subsequent tau pathology through a phosphatase. Using LC-MS/MS technology, we analyzed multiple DYRK1A-binding proteins, including PPM1B, a member of the PP2C family of Ser/Thr protein phosphatases, in HEK293 cells. We found that PPM1B dephosphorylates DYRK1A at Ser258, contributing to the inhibition of DYRK1A activity. Moreover, PPM1B-mediated dephosphorylation of DYRK1A reduced tau phosphorylation at Thr212, leading to inhibition of toxic tau oligomerization and aggregation. In conclusion, our study demonstrates that DYRK1A autophosphorylates Ser258, the dephosphorylation target of PPM1B, and PPM1B negatively regulates DYRK1A activity. This finding also suggests that PPM1B reduces the toxic formation of phospho-tau protein via DYRK1A modulation, possibly providing a novel cellular protective mechanism to regulate toxic tau-mediated neuropathology in AD of DS.
Palmitoylation of acetylated tubulin and association with ceramide-rich platforms is critical for ciliogenesis

Abstract Microtubules are polymers composed of αβ-tubulin subunits that provide structure to cells and play a crucial role in in the development and function of neuronal processes and cilia, microtubule-driven extensions of the plasma membrane that have sensory (primary cilia) or motor (motile cilia) functions. To stabilize microtubules in neuronal processes and cilia, α tubulin is modified by the posttranslational addition of an acetyl group, or acetylation. We discovered that acetylated tubulin in microtubules interacts with the membrane sphingolipid, ceramide. However, the molecular mechanism and function of this interaction are not understood. Here, we show that in human induced pluripotent stem cell–derived neurons, ceramide stabilizes microtubules, which indicates a similar function in cilia. Using proximity ligation assays, we detected complex formation of ceramide with acetylated tubulin in Chlamydomonas reinhardtii flagella and cilia of human embryonic kidney (HEK293T) cells, primary cultured mouse astrocytes, and ependymal cells. Using incorporation of palmitic azide and click chemistry–mediated addition of fluorophores, we show that a portion of acetylated tubulin is S-palmitoylated. S-palmitoylated acetylated tubulin is colocalized with ceramide-rich platforms in the ciliary membrane, and it is coimmunoprecipitated with Arl13b, a GTPase that mediates transport of proteins into cilia. Inhibition of S-palmitoylation with 2-bromo palmitic acid or inhibition of ceramide biosynthesis with fumonisin B1 reduces formation of the Arl13b-acetylated tubulin complex and its transport into cilia, concurrent with impairment of ciliogenesis. Together, these data show, for the first time, that ceramide-rich platforms mediate membrane anchoring and interaction of S-palmitoylated proteins that are critical for cilium formation, stabilization, and function.
Anodic Dissolution of 304 Stainless Steel Using Atomic Emission Spectroelectrochemistry

In this work a new spectroelectrochemical method based on an inductively coupled plasma atomic emission spectrometry has been developed and used to measure the elementary dissolution rates of Fe, Cr, Ni, Mn, Mo, and Cu simultaneously during linear scan voltammetry of a 304 stainless steel in the active region. Simultaneous dissolution was observed for all elements with the exception of copper, which appeared in solution at a potential approximately 100 mV more positive. The Tafel slopes for Fe, Cr, Ni, and Mn partial dissolution rates were measured around the corrosion potential and found to be identical within experimental error, between 59 and 68 mV/decade. The anodic dissolution of copper in acidic chloride and sulfate solutions was used to establish the quantitative relationship between the concentration transients and the dissolution rate. The residence time distribution of the electrochemical flow cell was determined using galvanostatic pulses of copper or stainless steel dissolution. The experimental residence time distribution could be approximated to a high degree of accuracy at both long and short times by a log-normal distribution. The effect of the residence time distribution on the shape of partial elemental current transients during linear scan voltammetry was investigated by numerical simulation.
Adsorption onto fibrous activated carbon : Applications to water treatment

The adsorption of polluted waters is performed by activated carbon fibers (ACF). This new material is characterized by scanning electronic microscopy. BET surface areas and pore volumes are determined. Adsorption of natural organics (humic substances) and micropollutants (aromatic compounds such as benzene and toluene) is carried out in a batch or dynamic reactor. Classical models are applied and kinetic constants calculated. The results show that the performance of ACF is significantly higher than that of granular activated carbon (GAC) in terms of adsorption velocity and selectivity for micropollutants. These higher performances are due to some ACF physical properties, such as their high BET surface area and micropore volume. Moreover, the micropores are directly connected on the external surface area of fibers, which allows smaller mass transfer resistance. In a dynamic reactor, the breakthrough curves obtained with ACF beds are particularly steep, suggesting a smaller mass transfer resistance than tha.
Volatile constituents of Centaurea pelia DC., C. thessala Hausskn. subsp. drakiensis (Freyn & Sint.) Georg. and C. zuccariniana DC. from Greece

The volatile constituents of the aerial parts of Centaurea pelia, C. thessala ssp. drakiensis and C. zuccariniana (Asteraceae) were extracted by steam distillation and analysed by gas chromatography–mass spectroscopy (GC–MS). Their components were represented by a homologous series of alkanes, alkenes, related aliphatic alcohols, aldehydes and ketones, as well as fatty acids and terpenoids. Copyright © 2000 John Wiley & Sons, Ltd.
The hydration of alite: a time-resolved quantitative X-ray diffraction approach using the G-factor method compared with heat release

The classical external-standard method derived from the work of O'Connor & Raven [Powder Diffr. (1988), 3, 2–6] was used to examine the hydration of the major phase, alite, of ordinary Portland cements at different temperatures and different water/alite ratios. In order to estimate the accuracy of the method, heat-flow curves were calculated from the alite dissolution curves obtained from X-ray diffraction in situ experiments. The heat-flow curves calculated in this way were compared with heat-flow curves recorded using a calorimeter. It is shown that the calculated curves agree well with the curves obtained from heat-flow experiments.
A Neuro-fuzzy Model as a Predictive Tool for the Vapor-liquid Equilibrium of Binary Mixtures

Vapor liquid equilibrium (VLE) data are important for designing and modeling of process equipments. Since it is not always possible to carry out experiments at all possible temperatures and pressures, generally thermodynamic models based on equations of state are used for estimation of VLE so that new models are then highly required. Therefore, an effort has been made to develop an alternative to a classical equation of state. The authors outline a new approach using a neural fuzzy model based on an adaptive network–based fuzzy inference system (ANFIS) was proposed to high-pressure VLE-related literature data to develop and validate a model capable of predicting VLE for the binary systems. The statistical methods, such as the mean absolute percentage error, mean square error, root mean squared errors, and the coefficient of multiple determinations (R 2) are given to compare the predicted and actual values for model validation. Furthermore, the comparison in terms of statistical values between the predicted results for the whole temperature range and literature results are predicted by the conventional Redlich-Kwang-Soave equation of state. The ANFIS model predictions showed better agreement with experimental data than the thermodynamic model predictions.
Field evaluation of soil moisture deficit thresholds for limits to trafficability with slurry spreading equipment on grassland

This study investigated the extent of soil damage caused by field traffic associated with different levels of soil moisture deficit (SMD). The hybrid SMD model was used for computing temporal patterns of SMD which can be accurately predicted for a range of soil types in Ireland. The aim of this study was to determine SMD threshold limits to trafficability for incorporation into a decision support system for safe slurry spreading. A tractor and a fully loaded single‐axle slurry tanker (total weight ca. 18 tonnes) were driven over well, moderate and poorly drained soils at SMD values of 0, 5, 10 and 20 mm during drying phases. The change in soil bulk density (SBD) was used as an indicator of soil compaction, and rut profile measurements were taken to determine soil deformation indicative of surface damage. The effect of traffic on the grass crop was determined by measuring dry matter yield at 30 and 60 days posttraffic in the wheel‐rut and nontrafficked area. Results showed that the SMD at the time of traffic had a significant (P < 0.05) effect on the magnitude of the changes in SBD on soils of different drainage status, and on rut dimensions following traffic. DMY was significantly (P < 0.05) reduced on the wheeled compared with the nonwheeled soil. No differences in the magnitude of DMY loss were identified between the sites having different drainage status. An SMD value of 10 mm was suggested as an SMD threshold for trafficability for safe slurry spreading purposes.
An online parameter and property database for the TraPPE force field

The transferable potentials for phase equilibria (TraPPE) force field aims to be accurate, computationally efficient and applicable to a wide range of chemical compounds, state points and thermophysical properties. When new users wish to implement TraPPE models into their chosen simulation program, they face several obstacles: the TraPPE models are dispersed over many separate publications and misinterpretations of the primary literature are possible; the TraPPE force field makes specific choices for standard conventions that may require non-trivial code modifications for some simulation software. Therefore, the TraPPE developers report here a resource website and online searchable parameter and property database designed to provide new and experienced users with tools for successful implementation and validation (http://www.chem.umn.edu/groups/siepmann/trappe/).
Q UANTIFYING E XPOSURE B IAS FOR O PEN - ENDED L ANGUAGE G ENERATION

The exposure bias problem refers to the incrementally distorted generation induced by the training-generation discrepancy, in teacher-forcing training for autoregressive neural network language models (LM). It has been regarded as a central problem for LMs trained for open-ended language generation. Although a lot of algorithms have been proposed to avoid teacher forcing and therefore alleviate exposure bias, there is little work showing how serious the exposure bias problem actually is. In this work, we propose novel metrics to quantify the impact of exposure bias in the generation of MLE-trained LMs. Our key intuition is that if we feed ground-truth data prefixes (instead of prefixes generated by the model itself) into the model and ask it to continue the generation, the performance should become much better because the training-generation discrepancy in the prefix is removed. We conduct both automatic and human evaluation in our experiments, and our observations are two-fold: (1) We confirm that the prefix discrepancy indeed induces some level of performance loss. (2) However, the induced distortion seems to be limited, and is not incremental during the generation, which contradicts the claim of exposure bias.
Lightened SphereFace for face recognition

Abstract. Convolutional neural networks (CNN) have immensely promoted the development of face recognition (FR) technology. In order to achieve global accuracy, CNN models tend to be deeper or multiple local facial patch ensembles, leading to excessive amounts of calculation. We address these deep FR problems and propose a lightened deep learning framework under an open-set protocol to achieve a good classification effect and streamline the model itself. To this end, we improve the SphereFace that enables the deep network to learn angularly discriminative features more efficiently. First, global average pooling (GAP) is introduced to replace the original fully connected (FC) layer, which greatly reduces the storage of the model. Compared to the widely used FC layer, GAP can reduce the number of parameters and avoid overfitting. Then multilayer perceptron is added between convolution layers, which increases the ability to characterize features. These models are trained on the CASIA-WebFace dataset and evaluated on the Labeled Faces in the Wild and YTF datasets, which show the excellent performance of lightened SphereFace (L-SphereFace) in FR tasks. At the same time, computational cost is reduced in comparison with the released SphereFace model. The storage space of the model is also greatly compressed.
GoSPo: a goniospectropolarimeter to assess reflectance, transmittance, and surface polarization as related to leaf optical properties

Abstract. Visible-near infrared (VIS-NIR) spectral data are widely used for remotely estimating a number of crop health metrics. In general, these indices and models do not explicitly account for leaf surface characteristics, which themselves can be indicators of plant status or environmental responses. To explicitly include leaf surface characteristics, data are required linking optical properties to surface characteristics. We present the design and experimental validation of a goniospectropolarimeter (GoSPo) that combines the capabilities of a spectrometer, goniometer, and polarimeter. GoSPo was designed with the objective of studying the relationships between leaf surface characteristics and the resulting light reflectance, transmission, and polarization as functions of both direction and VIS-NIR spectra. Using six motors, a pneumatic system, two spectrometers, and a combination of lenses, polarizers, and mirrors, GoSPo can examine a leaf from a particular angle, approximate hemispherical transmittance and reflectance (with root-mean-square error values of 0.0189 and 0.0216 for reflectance and transmittance, respectively, compared to a spectrophotometer and integrating sphere), and obtain spectral polarization measurements without disrupting the sample between measurements. The data collected with GoSPo will aid in model development for remote sensing applications.
SNPP VIIRS RSB on-orbit radiometric calibration algorithms Version 2.0 and the performances, part 2: the performances

Abstract. In part I (Lei et al., J. Appl. Remote Sens., Vol. 14, Issue 4), we gave detailed reviews of the algorithms Version 2.0 used for the on-orbit radiometric calibration of the reflective solar bands (RSBs) of the first Visible Infrared Imaging Radiometer Suite (VIIRS) instrument. These algorithms improve the accuracy of the measured on-orbit change factor of the solar diffuser bidirectional reflectance distribution function, the H-factor, and reveal that the H-factor is angle dependent. With the help of lunar observations and the improved H-factor, the algorithms give more accurate values for the RSB detector on-orbit F-factor changes (F-factor is a correction factor to the initially retrieved scene spectral radiance). We review the RSB radiometric calibration performances. We show the H-factor temporal trend, the estimated uncertainty of the retrieved H-factor, and the F-factor temporal trend. Additionally, we show the detector signal-to-noise ratio (SNR), the estimated uncertainty of the top-of-the-atmosphere solar spectral reflectance, the reflectance temporal trend for the Libya 4 desert, and the differences in the reflectances among the Suomi National Polar-orbiting Partnership (SNPP) and the NOAA-20 VIIRS and the Aqua Moderate-Resolution Imaging Spectroradiometer (MODIS). Our results show that, although the SNRs trend downward, they exceed the requirements by large margins. The reflectances from the Libya 4 desert show that the SNPP VIIRS’ reflectance is higher than those of the Aqua MODIS and the NOAA-20 VIIRS.
Hyperspectral anomaly detection using a background endmember signature

Abstract. Due to lacking use of prior information, the anomaly detection results are not always satisfactory. However, with the establishment of the spectral library, it becomes possible to obtain one or more spectra of the background in the image to be detected. If we can make use of such background information that is always ignored or discarded, the detection result is very likely to be improved. Hence, we proposed a hyperspectral anomaly detection method using a background endmember signature. To better separate the anomaly from the background, we first perform spectral unmixing to estimate the abundance matrix for further study instead of the original spectral data. In this process, we introduce a non-negative matrix factorization-based unmixing method and a corresponding initialization method using a background endmember. Then the low-rank property contained in the abundance matrix is exploited. A low-rank decomposition method is used to separate the anomalies. The proposed algorithm is evaluated on both synthetic and real data sets. Experiment results show the effectiveness of the proposed method and the improvement brought by the usage of a known background endmember.
A framework for the management of donated medical devices based on perspectives of frontline public health care staff in Ghana

Background: Transnational funders provide up to 80% of funds for medical devices in resource-limited settings, yet sustained access to medical devices remains unachievable. The primary goal of this study was to identify what factors hinder access to medical devices through the perspectives of frontline public hospital staff in Ghana involved in the implementation of transnational funding initiatives. Methods: A case study was developed that involved an analysis of semi-structured interviews of 57 frontline technical, clinical and administrative public health care staff at 23 sites in Ghana between March and April 2017; a review of the national guidelines for donations; and images of abandoned medical devices. Results: Six key themes emerged, demonstrating how policy, collaboration, quality, lifetime operating costs, attitudes of health care workers and representational leadership influence access to medical devices. An in-depth assessment of these themes has led to the development of an enterprise-wide comprehensive acquisition and management framework for medical devices in the context of transnational funding initiatives. Conclusion: The findings in this study underscore the importance of incorporating frontline health care staff in developing solutions that are targeted at improving delivery of care. Sustained access to medical devices may be achieved in Ghana through the adoption of a rigorous and comprehensive approach to acquisition, management and technical leadership. Funders and public health policy makers may use the study’s findings to inform policy reform and to ensure that the efforts of transnational funders truly help to facilitate sustainable access to medical devices in Ghana.
Communication in Transactive Memory Systems: A Review and Multidimensional Network Perspective

The comprehensive review synthesizes 64 empirical studies on communication and transactive memory systems (TMS). The results reveal that (a) a TMS forms through communication about expertise; (b) as a TMS develops, communication to allocate information and coordinate retrieval increases, promoting information exchange; and (c) groups update their TMS through communicative learning. However, direct interpersonal communication is not necessary for TMS development or utilization. Nor do high-quality information-sharing processes always occur within developed TMS structures. For future research, we propose a multidimensional network approach to TMS that incorporates technologies, addresses member characteristics, considers multiple communication types, and situates groups in context.