Miracle-dz/UniFAR-FTUs huggingface dataset:
Histological Study on the Protective Effect of Endogenous Stem Cell Mobilization in Busulfan-Induced Testicular Injury in Albino Rats

Background: Testicular damage is one of the most hazardous effects of chemotherapy as it is frequently associated with oligozoospermia and azoospermia. Aim of the Work: This study aimed at evaluating the protective effect of hematopoietic stem cell mobilization by granulocyte colony-stimulating factor (G-CSF) in a rat model of busulfan-induced testicular injury. Materials and Methods: Twenty-four adult albino rats were divided into four groups: group I, the control, Group II: rats received two doses of busulfan (each 15 mg/kg) intraperitoneally (IP) with 14 days interval, Group III: rats received busulfan and left untreated, and Group IV received busulfan IP then G-CSF (70 μg/kg/day) subcutaneously for 5 consecutive days. Testicular sections were stained with H and E and immunohistochemically for CD34, proliferating cell nuclear antigen (PCNA) and caspase-3, and semithin sections were stained with toluidine blue. Results: Groups II and III showed loss of the normal histological architecture of the testis and spermatogenic cells, with increased apoptosis confirmed by significantly increased caspase-3 and significantly decreased PCNA immunoexpression. While Group IV revealed improved testicular histology, decreased apoptosis, and increased proliferative capacity of spermatogenic cells. This was confirmed by significantly decreased caspase-3 immunoexpression and increased PCNA immunoreaction. Conclusion: Mobilization of stem cells with G-CSF was found to improve the testicular histology following busulfan chemotherapy in albino rats.
A sport-specific wearable jump monitor for figure skating

Advancements in wearable technology have facilitated performance monitoring in a number of sports. Figure skating may also benefit from this technology, but the inherent movements present some unique challenges. The purpose of this study was to evaluate the feasibility of using an inertial measurement unit (IMU) to monitor three aspects of figure skating jumping performance: jump count, jump height, and rotation speed. Seven competitive figure skaters, outfitted with a waist-mounted IMU, performed a total of 59 isolated multi-revolution jumps and their competition routines, which consisted of 41 multi-revolution jumps along with spins, footwork, and other skills. The isolated jumps were used to develop a jump identification algorithm, which was tested on the competition routines. Four algorithms to estimate jump height from flight time were then evaluated using calibrated video as a gold standard. The identification algorithm counted 39 of the 41 program jumps correctly, with one false positive. Flight time and jump height errors under 7% and 15% respectively were found using a peak-to-peak scaling algorithm. Rotation speeds up to 1,500°/s were noted, with peak speeds occurring just over halfway between takeoff and landing. Overall, jump monitoring via IMUs may be an efficient aid for figure skaters training multi-revolution jumps.
A Randomized Controlled Trial on the Effectiveness of Family Group Conferencing in Child Welfare: Effectiveness, Moderators, and Level of FGC Completion

The present study examined the effectiveness of Family Group Conferencing (FGC) in child welfare. Effects were operationalized in terms of child safety (child maltreatment, supervision order, and out-of-home placement), number of professional services used, parental empowerment, and social support in a 1-, 3-, 6-, and 12-month follow-up. Furthermore, the influence of family characteristics and the level of FGC completion were examined. A total of 328 families were included, randomly assigned to an experimental group (n = 229) and a care as usual (CAU) group (n = 99). FGC was equally effective as CAU in improving child safety but resulted in more out-of-home placements. Furthermore, FGC resulted in a longer duration of child welfare involvement, a marginally higher number of professional services used, and increased parental empowerment and social support. Family characteristics did not moderate the results. Level of FGC completion was in general low. Higher levels of completion were related to a larger social network, a higher number of professional services used, and, marginally, less parental empowerment. In conclusion, although some beneficial results marginally support the use of FGC, it is the question whether these effects outweigh FGC costs, a longer duration of child welfare involvement and a higher number of professional services used.
Structured Pruning of Neural Networks With Budget-Aware Regularization

Pruning methods have shown to be effective at reducing the size of deep neural networks while keeping accuracy almost intact. Among the most effective methods are those that prune a network while training it with a sparsity prior loss and learnable dropout parameters. A shortcoming of these approaches however is that neither the size nor the inference speed of the pruned network can be controlled directly; yet this is a key feature for targeting deployment of CNNs on low-power hardware. To overcome this, we introduce a budgeted regularized pruning framework for deep CNNs. Our approach naturally fits into traditional neural network training as it consists of a learnable masking layer, a novel budget-aware objective function, and the use of knowledge distillation. We also provide insights on how to prune a residual network and how this can lead to new architectures. Experimental results reveal that CNNs pruned with our method are more accurate and less compute-hungry than state-of-the-art methods. Also, our approach is more effective at preventing accuracy collapse in case of severe pruning; this allows pruning factors of up to 16x without significant accuracy drop.
BRDF Estimation of Complex Materials with Nested Learning

The estimation of the optical properties of a material from RGB-images is an important but extremely ill-posed problem in Computer Graphics. While recent works have successfully approached this problem even from just a single photograph, significant simplifications of the material model are assumed, limiting the usability of such methods. The detection of complex material properties such as anisotropy or Fresnel effect remains an unsolved challenge. We propose a novel method that predicts the model parameters of an artist-friendly, physically-based BRDF, from only two low-resolution shots of the material. Thanks to a novel combination of deep neural networks in a nested architecture, we are able to handle the ambiguities given by the non-orthogonality and non-convexity of the parameter space. To train the network, we generate a novel dataset of physically-based synthetic images. We prove that our model can recover new properties like anisotropy, index of refraction and a second reflectance color, for materials that have tinted specular reflections or whose albedo changes at glancing angles.
Image Classification at Supercomputer Scale

Deep learning is extremely computationally intensive, and hardware vendors have responded by building faster accelerators in large clusters. Training deep learning models at petaFLOPS scale requires overcoming both algorithmic and systems software challenges. In this paper, we discuss three systems-related optimizations: (1) distributed batch normalization to control per-replica batch sizes, (2) input pipeline optimizations to sustain model throughput, and (3) 2-D torus all-reduce to speed up gradient summation. We combine these optimizations to train ResNet-50 on ImageNet to 76.3% accuracy in 2.2 minutes on a 1024-chip TPU v3 Pod with a training throughput of over 1.05 million images/second and no accuracy drop.
Efficient Keyword Spotting Using Dilated Convolutions and Gating

We explore the application of end-to-end stateless temporal modeling to small-footprint keyword spotting as opposed to recurrent networks that model long-term temporal dependencies using internal states. We propose a model inspired by the recent success of dilated convolutions in sequence modeling applications, allowing to train deeper architectures in resource-constrained configurations. Gated activations and residual connections are also added, following a similar configuration to WaveNet. In addition, we apply a custom target labeling that back-propagates loss from specific frames of interest, therefore yielding higher accuracy and only requiring to detect the end of the keyword. Our experimental results show that our model outperforms a max-pooling loss trained recurrent neural network using LSTM cells, with a significant decrease in false rejection rate. The underlying dataset – "Hey Snips" utterances recorded by over 2.2K different speakers – has been made publicly available to establish an open reference for wake-word detection.
Diagnostic Accuracy Of Plain X-Ray Lateral Neck In The Diagnosis Of Cervical Esophageal Foreign Bodies Keeping Oesophagoscopy As Gold Standard.

BACKGROUND Detection of foreign body oesophagus has always been a challenge for the otolaryngologists. Among different investigations available X -ray is valuable for detection of foreign bodies as it is readily available, inexpensive and easy to operate. However, this still remains to be decided that how accurate it is? The objective of the study is to determine the diagnostic accuracy of plain X ray lateral neck in the diagnosis of foreign bodies in cervical oesophagus keeping esophagoscopy as the gold standard. METHODS This descriptive study was conducted at department of ENT, Ayub Medical Institute (AMI) Abbottabad, from Mar to Sep 2016. A total of 290 patients were included in this study and all the patients had X-ray lateral view of neck, followed by oesophagoscopy (gold standard). Diagnostic accuracy of plain X-ray lateral view of neck was detected by determining sensitivity, specificity and accuracy. RESULTS The sensitivity, specificity and accuracy of plain X-ray lateral view of neck was 91.7%, 80%, and 89.7%, respectively. CONCLUSIONS X-Ray lateral view of neck is a reliable investigation and should be advised among all the patients with history of foreign body ingestion.
Shared Adversity Increases Team Creativity Through Fostering Supportive Interaction

In the current era, building more innovative teams is key to organizational success, yet there is little consensus on how best to achieve this. Common wisdom suggests that positive reinforcement through shared positive rewards builds social support within teams, and in turn facilitates innovation. Research on basic group processes, cultural rituals, and the evolution of pro-group behavior has, however, revealed that sharing adverse experiences is an alternative path to promoting group bonding. Here, we examined whether sharing an adverse experience not only builds social support within teams, but also in turn enhances creativity within novel teams. Drawing on behavioral observation of an experimental group interaction we find evidence that sharing an adverse (vs. non-adverse) experience leads to increased supportive interactions between team members and this in turn boosts creativity within a novel team. These effects were robust across different indicators of creativity: objective measures of creativity, third party ratings of the creativity of group products, and participants' own perceptions of group creativity. Our findings offer a new perspective from which to understand how best to boost innovation and creative output within teams.
Toward an Understanding of Trust Repair in Human-Robot Interaction

Gone are the days of robots solely operating in isolation, without direct interaction with people. Rather, robots are increasingly being deployed in environments and roles that require complex social interaction with humans. The implementation of human-robot teams continues to increase as technology develops in tandem with the state of human-robot interaction (HRI) research. Trust, a major component of human interaction, is an important facet of HRI. However, the ideas of trust repair and trust violations are understudied in the HRI literature. Trust repair is the activity of rebuilding trust after one party breaks the trust of another. These trust breaks are referred to as trust violations. Just as with humans, trust violations with robots are inevitable; as a result, a clear understanding of the process of HRI trust repair must be developed in order to ensure that a human-robot team can continue to perform well after a trust violation. Previous research on human-automation trust and human-human trust can serve as starting places for exploring trust repair in HRI. Although existing models of human-automation and human-human trust are helpful, they do not account for some of the complexities of building and maintaining trust in unique relationships between humans and robots. The purpose of this article is to provide a foundation for exploring human-robot trust repair by drawing upon prior work in the human-robot, human-automation, and human-human trust literature, concluding with recommendations for advancing this body of work.
Upper Normal Serum Creatinine Concentrations as a Predictor for Chronic Kidney Disease: Analysis of 14 Years’ Korean Genome and Epidemiology Study (KoGES)

Both serum creatinine (sCr) and estimated glomerular filtration rate (eGFR) have been used to assess kidney function in public health check-ups. However, when the sCr is within the normal levels but the eGFR is <60 mL/min/1.73 m2, a dilemma arises, as the patients might progress to chronic kidney disease (CKD) after several years. We aimed to evaluate the association between normal sCr and the risk of incident CKD in the general population. For this, 9445 subjects from the Korean Genome and Epidemiology Study, with normal sCr and eGFR of >60 mL/min/1.73 m2 were analyzed. The subjects were classified into quartiles based on sCr levels. The primary outcome was the development of eGFR <60 mL/min/1.73 m2 on two consecutive measures. During a mean follow-up of 8.4 ± 4.3 years, 779 (8.2%) subjects developed eGFR <60 mL/min/1.73 m2. The incidence of the development of eGFR <60 mL/min/1.73 m2 was higher in the higher quartiles than in the lowest quartile. In multivariable Cox analysis, the highest quartile was associated with an increased risk for the development of eGFR <60 mL/min/1.73 m2 (hazard ratio (HR), 4.71; 95% confidence interval (CI), 3.29–6.74 in females; HR, 12.77; 95% CI, 7.69–21.23 in males). In the receiver operating characteristic curve analysis, adding sCr to the traditional risk factors for CKD improved the accuracy of predicting the development of eGFR <60 mL/min/1.73 m2 (area under the curve, 0.83 vs. 0.80 in females and 0.85 vs. 0.78 in males), and the cutoff value of sCr was 0.75 mg/dL and 0.78 mg/dL in females and males. Cautious interpretation is necessary when sCr is within the normal range, considering that the upper normal range of sCr has a higher risk of CKD development.
Two decades with omalizumab: what we still have to learn

From its availability for clinical use nearly two decades ago for severe asthma, omalizumab has gained strong evidence of efficacy and safety in the treatment of severe asthma not controlled by standard-of-care therapy. It has been acknowledged by Global Initiative on Asthma guidelines as add-on therapy against severe uncontrolled asthma. Thanks to controlled trials supporting its efficacy, omalizumab has also been licensed for the treatment of chronic spontaneous urticaria. The optimal duration of treatment in either disease has not been established. Despite its high price, omalizumab appears to be cost-effective in severe uncontrolled asthma as well as in chronic urticaria. The literature suggests a wide range of applications for omalizumab in various disorders regardless of allergic or non-allergic pathophysiology.
Proximal Arterio Venous Fistula Creation - A Gold Standard In Chronic Renal Failure Patients With Multiple Comorbidities.

BACKGROUND Patients with end stage renal disease need an accurate and effective vascular access for haemodialysis. This study was conducted to postulate a hypothesis that proximal arterio venous fistula (AVF) creation should be a gold standard in Chronic Renal Failure (CRF) patients with multiple co morbidities. METHODS A total of 230 patients reporting to Vascular Surgery Clinic in Combined Military Hospital Lahore and Peshawar from January 2014 to January 2016 for AVF creation, were included and equally divided into two groups by random draw method. Distal AVF created in Group A and proximal AVFs at elbow in Group B. The data regarding age, gender, atherosclerotic risk factors, body mass index (BMI) was recorded. The groups were compared for functional maturation of AVF and their patency at 6 and 12 months. RESULTS Mean age was 30±SD 6.5 years (31±SD 5.1 in Group A, 30±SD 6.9 in Group B) with a male to female ratio of 5.4:1. In terms of age (p-value 0.529), gender (p-value 0.716), diabetes (p-value 0.682), hypertension (p-value 0.659) and BMI; there was no difference between two groups. 85.2% (n=98) AVFs matured in Group B as compared to 44.3% (n=51) AVFs in Group A (pvalue= 0.0045). Furthermore, statistically significant differences between the two groups were found in terms of patency rates at 6 and 12 months (73.9% and 66% in Group B: 26.9% and 16.5% in Group A; p-value 0.0039 and 0.0007 respectively). CONCLUSIONS Proximal AVF creation in CRF patients with multiple co morbidities should be the gold standard as a primary procedure in terms of better long term primary patency.
An evolutionary methodology for estimating blood glucose levels from interstitial glucose measurements and their derivatives

The patients suffering from diabetes are subjected to several serious medical risks that can lead also to fatal consequences. To enhance the quality of life of these patients there is the necessity to devise an artificial pancreas able to inject an insulin bolus when needed. This paper presents a genetic-programming based algorithm to extrapolate a regression model able to estimate the blood glucose (BG) level through interstitial glucose (IG) measurements and their derivatives. This algorithm represents a possible step in building the fundamental element of such an artificial pancreas, namely a new evolutionary computation-based metodology to derive a mathematical relationship between BG and IG. The proposed evolutionary automatic procedure is evaluated on a real-world database made up of both BG and IG measurements of people suffering from Type 1 diabetes. The discovered model is validated through a comparison with other techniques during the experimental phase.
Proteolytically released Lasso/teneurin-2 induces axonal attraction by interacting with latrophilin-1 on axonal growth cones

A presynaptic adhesion G-protein-coupled receptor, latrophilin-1, and a postsynaptic transmembrane protein, Lasso/teneurin-2, are implicated in trans-synaptic interaction that contributes to synapse formation. Surprisingly, during neuronal development, a substantial proportion of Lasso is released into the intercellular space by regulated proteolysis, potentially precluding its function in synaptogenesis. We found that released Lasso binds to cell-surface latrophilin-1 on axonal growth cones. Using microfluidic devices to create stable gradients of soluble Lasso, we show that it induces axonal attraction, without increasing neurite outgrowth. Using latrophilin-1 knockout in mice, we demonstrate that latrophilin-1 is required for this effect. After binding latrophilin-1, Lasso causes downstream signaling, which leads to an increase in cytosolic calcium and enhanced exocytosis, processes that are known to mediate growth cone steering. These findings reveal a novel mechanism of axonal pathfinding, whereby latrophilin-1 and Lasso mediate both short-range interaction that supports synaptogenesis, and long-range signaling that induces axonal attraction.
Deficits in Behavioral Functions of Intact Barrel Cortex Following Lesions of Homotopic Contralateral Cortex

Focal unilateral injuries to the somatosensory whisker barrel cortex have been shown cause long-lasting deficits in the activity and experience-dependent plasticity of neurons in the intact contralateral barrel cortex. However, the long-term effect of these deficits on behavioral functions of the intact contralesional cortex is not clear. In this study, we used the “Gap-crossing task” a barrel cortex-dependent, whisker-sensitive, tactile behavior to test the hypothesis that unilateral lesions of the somatosensory cortex would affect behavioral functions of the intact somatosensory cortex and degrade the execution of a bilaterally learnt behavior. Adult rats were trained to perform the Gap-crossing task using whiskers on both sides of the face. The barrel cortex was then lesioned unilaterally by subpial aspiration. As observed in other studies, when rats used whiskers that directly projected to the lesioned hemisphere the performance of Gap-crossing was drastically compromised, perhaps due to direct effect of lesion. Significant and persistent deficits were present when the lesioned rats performed Gap-crossing task using whiskers that projected to the intact cortex. The deficits were specific to performance of the task at the highest levels of sensitivity. Comparable deficits were seen when normal, bilaterally trained, rats performed the Gap-crossing task with only the whiskers on one side of the face or when they used only two rows of whiskers (D row and E row) intact on both side of the face. These findings indicate that the prolonged impairment in execution of the learnt task by rats with unilateral lesions of somatosensory cortex could be because sensory inputs from one set of whiskers to the intact cortex is insufficient to provide adequate sensory information at higher thresholds of detection. Our data suggest that optimal performance of somatosensory behavior requires dynamic activity-driven interhemispheric interactions from the entire somatosensory inputs between homotopic areas of the cerebral cortex. These results imply that focal unilateral cortical injuries, including those in humans, are likely to have widespread bilateral effects on information processing including in intact areas of the cortex.
Effectiveness of Surface Electromyography in Pattern Classification for Upper Limb Amputees

This study was undertaken to explore 18 time domain (TD) and time-frequency domain (TFD) feature configurations to determine the most discriminative feature sets for classification. Features were extracted from the surface electromyography (sEMG) signal of 17 hand and wrist movements and used to perform a series of classification trials with the random forest classifier. Movement datasets for 11 intact subjects and 9 amputees from the NinaPro online database repository were used. The aim was to identify any optimum configurations that combined features from both domains and whether there was consistency across subject type for any standout features. This work built on our previous research to incorporate the TFD, using a Discrete Wavelet Transform with a Daubechies wavelet. Findings report configurations containing the same features combined from both domains perform best across subject type (TD: root mean square (RMS), waveform length, and slope sign changes; TFD: RMS, standard deviation, and energy). These mixed-domain configurations can yield optimal performance (intact subjects: 90.98%; amputee subjects: 75.16%), but with only limited improvement on single-domain configurations. This suggests there is limited scope in attempting to build a single absolute feature configuration and more focus should be put on enhancing the classification methodology for adaptivity and robustness under actual operating conditions.