Miracle-dz/UniFAR-FTUs huggingface dataset:
Assessment of Resource Potential and Feasibility Study of Standalone PV-Wind-Biogas Hybrid System for Rural Electrification

Ethiopian Electric Power Corporation utility company uses extension of grids and installation of diesel generators as an option for the electrification of rural villages. Despite the tremendous efforts exhibited during the past few years, there are still exceedingly many people without access to electricity services. Grid extension to rural areas is either financially not viable or practically not feasible as these locations are geographically isolated and have a very low power demand in the country. The use of diesel generators has also harmful effect on the environment in addition to their higher cost of fuel, maintenance and operation. Consequently, rural areas are dependent on local solutions for electricity supply. However, the Adama area has renewable energy resources, such as Wind, Solar and Biogas with the capability of providing the needed power demand without requiring the extension of the national grid. In this study, assessment of resource potential and feasibility study of PV-Wind-Biogas hybrid system with battery storage as a backup is studied to electrify the village in Adama rural area. Electric load estimation for the basic needs of the community are considered. The hybrid energy system optimized by HOMER is cost effective to electrifying the village.
STMF: A Sentiment Topic Matrix Factorization Model for Recommendation

Traditional recommender system model latent matrix factorization only use the ratings but ignore the information hidden in reviews text. In recent years, there have been some models based on latent matrix factorization exploiting reviews. Most of them use the topics in reviews because the topics in reviews can capture item features well. However, they missed the sentiment contained in reviews while the sentiment hidden in reviews reflects user preference. In this paper, we propose a novel matrix factorization model which simultaneously considers sentiment and topics involved in reviews and ratings as well. Experimental results on real datasets show that our model reached the performance of state of the art models, and our model has better interpretability especially in user preference.
Advance Publication by J-STAGE Journal of Reproduction and Development

17 We examined the effects of a single or 2.5-fold dose of dephereline [a gonadotropin-releasing hormone 18 (GnRH) analogue] as well as the drainage of the smaller follicle at the time of insemination on ovulation 19 in dairy cows with two follicles of pre-ovulatory size in the same ovary. The three study groups included 20 220 monovular cows (control), 110 non-drained cows with two follicles, and 110 cows with two 21 follicles, of which one was drained. In each group, cows treated with a single dose or 2.5-fold dose of 22 dephereline showed similar results following treatment. Ovulation failure of the non-drained follicle 23 occurred in 29.1% of the drained cows, whereas ovulation occurred in 96% of the non-drained and 24 control cows. Twin pregnancy was recorded in 19.4% of the pregnant non-drained cows with two 25 follicles. In conclusion, the increased dephereline dose did not improve the ovulation rate in any group. 26 Follicular drainage, however, prevented twin pregnancy in cows with two follicles, but also resulted in 27 an increase in the non-drained follicle’s rate of ovulation failure. 28 29
Dietary canthaxanthin reduces xanthophyll uptake and red coloration in adult red-legged partridges

ABSTRACT Carotenoids give color to conspicuous animal signals that are often the product of sexual selection. Knowledge of the mechanisms involved in carotenoid-based signaling is critical to understanding how these traits evolve. However, these mechanisms remain only partially understood. Carotenoids are usually viewed as scarce dietary antioxidants whose allocation to ornaments may trade off against health. This trade-off would ensure its reliability as a signal of individual quality. In the case of red (keto)carotenoids, the literature suggests that some species may show constraints in their uptake. Canthaxanthin is one of the most common ketocarotenoids in red ornaments of animals. It is often commercially used as a dietary supplement to obtain redder birds (e.g. poultry). We increased the dietary canthaxanthin levels in captive red-legged partridges (Alectoris rufa). This species shows red non-feathered parts mostly pigmented by another common ketocarotenoid: astaxanthin. We studied the impact on the uptake of carotenoids and vitamins and, finally, on coloration. We also tested the potential protective effect of canthaxanthin when exposing birds to a free radical generator (diquat). Canthaxanthin did not apparently protect birds from oxidative stress, but interfered with the absorption of yellow carotenoids (lutein and zeaxanthin). Zeaxanthin is a precursor of astaxanthin in enzymatic pathways, and their levels in tissues and eggs were lower in canthaxanthin-supplied birds. This led to lower astaxanthin levels in ornaments and paler coloration. As far as we know, this is the first report of a carotenoid supplementation decreasing animal coloration. The results have implications for understanding carotenoid-based signaling evolution, but also for improving husbandry/experimental procedures. Summary: High levels of red carotenoids (i.e. canthaxanthin) in the diet paradoxically lead to paler red coloration, which raises questions about potential constraints in the evolution of red carotenoid-based sexual signals.
Evaluation of Sutureless, Glueless, Flapless, Intrascleral Fixated Posterior Chamber Intraocular Lens in Children with Ectopia Lentis

Aim This paper aims at evaluating refractive outcome and complication profile of sutureless, glueless, flapless, intrascleral fixation of intraocular lens (SFIOL) in pediatric population. Methods This retrospective study included patients ≤18 years of age who underwent SFIOL for ectopia lentis. Details obtained included preoperative uncorrected visual acuity (UCVA), cycloplegic refraction, and best-corrected visual acuity (BCVA); intraoperative complications; and postoperative UCVA, cycloplegic refraction, and BCVA and complications. Results Median pre- and postoperative UCVA was logMAR 1.78 (Snellen 20/1200) and logMAR 0.30 (Snellen 20/40), respectively, (p < 0.001). Median pre- and postoperative BCVA was logMAR 0.24 (Snellen 20/34) and logMAR 0.18 (Snellen 20/30), respectively. UCVA ≥20/60 was attained in 90% of eyes. BCVA ≥20/30 was attained in 85.0% of eyes. Most common early postoperative complications were hyphaema (10%), transient vitreous hemorrhage (2.5%), and ocular hypotony (2.5%). None of these developed any long-term sequelae. Only one case of subluxation of IOL was seen. No case of late endophthalmitis or retinal detachment was seen. Conclusion Since refractive error induced is minimal, the procedure is suitable for IOL implantation in children, who are noncompliant with spectacles. The complication profile is similar to that reported in adults.
Statistical Challenges in the Analyses of Bone Mineral Density in Pediatric Populations

Assessing bone mineral density (BMD) by dual-energy x-ray absorptiometry (DXA) is standard in clinical practice with good precision and reproducibility. One way to analyze BMD data is through the Z -score where a subject’s BMD is standardized against some reference population. This article highlights several potential problems in the calculation of the Z -score: (1) reference data are manufacturer dependent; (2) a transformation is recommended to reduce the skewness often seen in BMD data, however a transformation parameter is only available in some references using the Hologic manufacturer; (3) some reference data may be obsolete, as they were done under older scan models; (4) reference data are recommended to be interpolated to the subject’s age, and linear interpolation is questionable; (5) reference data do not exist for all age groups; (6) reference data depend on the race of the subjects, and not all races are representative; and (7) reference data are limited to certain body composition. Given the limitation in the BMD Z -scores, other clinical symptoms (eg, bone fractures) or laboratory findings (eg, bone biomarkers) should be assessed in conjunction with the BMD Z -score to evaluate a subject’s bone health.
Unsupervised Sense-Aware Hypernymy Extraction

In this paper, we show how unsupervised sense representations can be used to improve hypernymy extraction. We present a method for extracting disambiguated hypernymy relationships that propagates hypernyms to sets of synonyms (synsets), constructs embeddings for these sets, and establishes sense-aware relationships between matching synsets. Evaluation on two gold standard datasets for English and Russian shows that the method successfully recognizes hypernymy relationships that cannot be found with standard Hearst patterns and Wiktionary datasets for the respective languages.
REOH: Using Probabilistic Network for Runtime Energy Optimization of Heterogeneous Systems

Significant efforts have been devoted to choosing the best configuration of a computing system to run an application energy efficiently. However, available tuning approaches mainly focus on homogeneous systems and are inextensible for heterogeneous systems which include several components (e.g., CPU s, G PU s) with different architectures. This study proposes a holistic tuning approach called REOH using probabilistic network to predict the most energy-efficient configuration (i.e., which platform and its setting) of a heterogeneous system for running a given application. Based on the computation and communication patterns from Berkeley dwarfs, we conduct experiments to devise the training set including 7074 data samples covering varying application patterns and characteristics. Validating the REOH approach on heterogeneous systems including CPUs and GPUs shows that the energy consumption by the REOH approach is close to the optimal energy consumption by the Brute Force approach while saving 17 % of sampling runs compared to the previous (homogeneous) approach using probabilistic network. Based on the REOH approach, we develop an open-source energy-optimizing runtime framework for selecting an energy efficient configuration of a heterogeneous system for a given application at runtime.
Matching Recommendations Based on Siamese Network and Metric Learning

Clothing matching is always making customers in trouble because it is both time-consuming and challenging. To solve the issue of “What outfit matches this piece of shirt? ”, recommendation tasks have attracted attentions from scholars. Most existing recommendation systems focus on the similarity between items or user's interest in items. A few studies pay attention to matching recommendations which are based on the visual features of items. Identifying and understanding relationships between items is the base of the matching recommendation tasks. A distance between items can be defined to measure the relationships. Therefore, we explore a novel recommendation framework to integrate visual features with category features based on Siamese architecture and metric learning. The distance between items can be learnt in target space (matching space) rather than in the input space (original space). In the matching space, the matching items are close to each other while the mismatching items are far away. Compared with the baselines, our methods show great superiority which demonstrates that the matching space defined in our framework is more suitable for learning the matching relationship between items. The results also show that training in both visual features and category features performs better than that of training in only one of them. The method can be even better if giving more negative samples for an item.
Sodium Channel–Dependent and –Independent Mechanisms Underlying Axonal Afterdepolarization at Mouse Hippocampal Mossy Fibers

Visual Abstract Action potentials propagating along axons are often followed by prolonged afterdepolarization (ADP) lasting for several tens of milliseconds. Axonal ADP is thought to be an important factor in modulating the fidelity of spike propagation during repetitive firings. However, the mechanism as well as the functional significance of axonal ADP remain unclear, partly due to inaccessibility to small structures of axon for direct electrophysiological recordings. Here, we examined the ionic and electrical mechanisms underlying axonal ADP using whole-bouton recording from mossy fiber terminals in mice hippocampal slices. ADP following axonal action potentials was strongly enhanced by focal application of veratridine, an inhibitor of Na+ channel inactivation. In contrast, tetrodotoxin (TTX) partly suppressed ADP, suggesting that a Na+ channel–dependent component is involved in axonal ADP. The remaining TTX-resistant Na+ channel–independent component represents slow capacitive discharge reflecting the shape and electrical properties of the axonal membrane. We also addressed the functional impact of axonal ADP on presynaptic function. In paired-pulse stimuli, we found that axonal ADP minimally affected the peak height of subsequent action potentials, although the rising phase of action potentials was slightly slowed, possibly due to steady-state inactivation of Na+ channels by prolonged depolarization. Voltage clamp analysis of Ca2+ current elicited by action potential waveform commands revealed that axonal ADP assists short-term facilitation of Ca2+ entry into the presynaptic terminals. Taken together, these data show that axonal ADP maintains reliable firing during repetitive stimuli and plays important roles in the fine-tuning of short-term plasticity of transmitter release by modulating Ca2+ entry into presynaptic terminals.
Working memory for self-initiated and provided spatial configurations

During a typical day, people temporarily memorise information provided to them. However, they memorise as often information they actively choose themselves. Although prevalent in everyday behaviour, this aspect of working memory (WM), we term self-initiated WM, has been largely unexplored. In this study, we used a modified spatial span task in which participants constructed the spatial sequences they maintained in memory. The results of three experiments demonstrated that participants planned and constructed structured spatial sequences by minimising the distances between successive locations and by selecting sequences with fewer path crossings. The sequences were initiated most often on the top left side. Memory accuracy was enhanced when participants memorised self-initiated spatial sequences, even when the self-initiated and provided sequences were matched for structure. When asked to construct spatial sequences for a hypothetical competitor in a memory contest, participants constructed complex sequences with longer paths and more path crossings, suggesting that these sequence parameters were under their control. The tendency to initiate the spatial sequences on the top left side remained. Overall, the results suggest that self-initiated WM can benefit from explicit metacognitive knowledge of the ideal structure of memory representations and also demonstrate that self-initiation benefits memory beyond structure.
Multi-Vehicle Trajectories Generation for Vehicle-to-Vehicle Encounters

Generating multi-vehicle trajectories analogous to these in real world can provide reliable and versatile testing scenarios for autonomous vehicle. This paper presents an unsupervised learning framework to achieve this. First, we implement variational autoencoder (VAE) to extract interpretable and controllable representatives of vehicle encounter trajectory. Through sampling from the distribution of these representatives, we are able to generate new meaningful driving encounters with a developed Multi-Vehicle Trajectory Generator (MTG). A new metric is also proposed to comprehensively analyze and compare disentangled models. It can reveal the robustness of models and the dependence among latent codes, thus providing guidance for practical application to improve system performance. Experimental results demonstrate that our proposed MTG outperforms infoGAN and vanilla VAE in terms of disentangled ability and traffic awareness. These generations can provide abundant and controllable driving scenarios, thus providing testbeds and algorithm design insights for autonomous vehicle development.
Gender Differences in Outcomes Following a Pain-Free, Home-Based Exercise Program for Claudication

Abstract Background: Peripheral artery disease (PAD) is a common cardiovascular pathology that affects mobility. In previous research, supervised exercise, a recommended treatment for claudication, was less effective in women. This study retrospectively investigated whether functional outcomes exhibit sex differences following a pain-free, home-based exercise program for PAD patients. Materials and Methods: Patients with PAD and claudication enrolled to a structured home-based program from 2003 to 2016 were studied. The program was prescribed at the hospital and based on two daily 10-minute pain-free walking sessions at progressively increasing speed. Outcome measures, which were assessed at baseline and discharge, were pain threshold speed (PTS) and maximal (Smax) during a treadmill test and pain-free walking distance (PFWD) and total distance walked in 6 minutes (6MWD). The ankle-brachial index (ABI), program duration, and patient adherence were determined. Results: A total of 1007 patients (women; n = 264; 26%) were enrolled. At baseline, compared to men, women exhibited similar ABI values but lower PTS and PFWD values (p < 0.001). At discharge, with similar adherence (score 3/4 ± 1 each) in both groups, superimposable improvements were observed for PTS (0.8 ± 0.8 km/h each), Smax (0.4 ± 0.5 km/h each), PFWD (women 95 ± 100; men 86 ± 104), 6MWD (women 32 ± 65; men 35 ± 58), and ABI (women 0.07 ± 0.12; men 0.06 ± 0.11) without between-group differences (confirmed after propensity analysis). Conclusion: A personalized, structured pain-free exercise program for PAD patients performed inside the home for a few minutes a day was equally effective in both sexes. Programs favoring adherence and functional outcomes in women should be tested in prospective studies.
Review of vaccination in pregnancy to prevent pertussis in early infancy

&NA; Maternal pertussis vaccination has been introduced in several countries to protect infants from birth until routine infant vaccination takes place. This review assesses existing evidence on the effectiveness and safety of immunization in pregnancy. The search was finalized in April 2017 and was based on searches using several databases. The selection criteria included any experimental or observational study reporting on the immunogenicity, effectiveness or safety of vaccination with a pertussis‐containing vaccine in pregnant women and their infants. Following de‐duplication and exclusions, we identified 8395 studies, which were reduced to 46 for inclusion. The overall risk of bias was low, with the exception of some early studies and pharmacovigilance safety data. The evidence demonstrates efficient transplacental transfer of maternal antibodies in infants whose mothers were vaccinated with Tdap or Tdap/IPV in pregnancy, with good evidence that this protects against disease in young infants. Safety studies covering more than 150 000 women vaccinated mostly in the late second or third trimesters are generally consistent and provide reassurance of no significant increased risk of recognized maternal conditions or of adverse events (including congenital anomalies) in infants born to vaccinated women. The clinical significance of reduced seroconversion to pertussis following routine immunization is not yet clear, but no increased risk of pertussis in infants whose mothers were vaccinated in pregnancy was found following primary immunizations in North American and English studies. Most post‐booster studies suggest that any blunting effect is short‐lived and that longer‐term protection in infants from active immunization is not compromised.
Multiscale network dynamics between heart rate and locomotor activity are altered in schizophrenia

Objective: Changes in heart rate (HR) and locomotor activity reflect changes in autonomic physiology, behavior, and mood. These systems may involve interrelated neural circuits that are altered in psychiatric illness, yet their interactions are poorly understood. We hypothesized interactions between HR and locomotor activity could be used to discriminate patients with schizophrenia from controls, and would be less able to discriminate non-psychiatric patients from controls. Approach: HR and locomotor activity were recorded via wearable patches in 16 patients with schizophrenia and 19 healthy controls. Measures of signal complexity and interactions were calculated over multiple time scales, including sample entropy, mutual information, and transfer entropy. A support vector machine was trained on these features to discriminate patients from controls. Additionally, time series were converted into a network with nodes comprised of HR and locomotor activity states, and edges representing state transitions. Graph properties were used as features. Leave-one-out cross validation was performed. To compare against non-psychiatric illness, the same approach was repeated in 41 patients with atrial fibrillation (AFib) and 53 controls. Main results: Network features enabled perfect discrimination of schizophrenia patients from controls with an areas under the receiver operating characteristic curve (AUC) of 1.00 for training and test data. Other bivariate measures of interaction achieved lower AUCs (train 0.98, test 0.96), and univariate measures of complexity achieved the lowest performance. Conversely, interaction features did not improve discrimination of AFib patients from controls beyond univariate approaches. Significance: Interactions between HR and locomotor activity enabled perfect discrimination of subjects with schizophrenia from controls, but these features were less performant in a non-psychiatric illness. This is the first quantitative evaluation of interactions between physiology and behavior in patients with psychiatric illness.
CEREALS - Cost-Effective REgion-based Active Learning for Semantic Segmentation

State of the art methods for semantic image segmentation are trained in a supervised fashion using a large corpus of fully labeled training images. However, gathering such a corpus is expensive, due to human annotation effort, in contrast to gathering unlabeled data. We propose an active learning-based strategy, called CEREALS, in which a human only has to hand-label a few, automatically selected, regions within an unlabeled image corpus. This minimizes human annotation effort while maximizing the performance of a semantic image segmentation method. The automatic selection procedure is achieved by: a) using a suitable information measure combined with an estimate about human annotation effort, which is inferred from a learned cost model, and b) exploiting the spatial coherency of an image. The performance of CEREALS is demonstrated on Cityscapes, where we are able to reduce the annotation effort to 17%, while keeping 95% of the mean Intersection over Union (mIoU) of a model that was trained with the fully annotated training set of Cityscapes.