Miracle-dz/UniFAR-FTUs huggingface dataset:
PI3K regulates integrin-dependent processes in neutrophils by signalling through its effector ARAP3

ARAP3, a GTPase activating protein for Rho and Arf family GTPases, is one of many PI3K effectors. Here we investigate the regulatory input of PI3K upstream of ARAP3, by analysing neutrophils from an ARAP3 PH domain point mutation knock-in mouse (R302, 303A), in which ARAP3 is uncoupled from activation by PI3K. ARAP3 PH domain point mutant neutrophils are characterised by disturbed responses linked to stimulation by either integrin ligands or immobilised immune complexes. These cells exhibit increased β2 integrin inside-out signalling (binding affinity and avidity), and our work suggests the disturbed responses to immobilised immune complexes are secondary to this. In vitro, neutrophil chemotaxis is affected in the mutant. In vivo, ARAP3 PH domain point mutant bone marrow chimeras exhibit reduced neutrophil recruitment to the peritoneum on induction of sterile peritonitis and also reduced inflammation in a model for rheumatoid arthritis. The present work suggests a dramatic regulatory input of PI3K into the regulation of β2 integrin activity, and processes dependent on this, by signalling through its effector ARAP3.
Billboard prediction using listeners’ perspective and audio features from top music platforms

Music has been a form of entertainment for many years. The music industry is constantly putting forth effort to improve the quality of our music. It would be an interesting exercise to predict that the song makes it into top charts from a mathematical perspective. The proposed model in this paper predicts the success of a song based on its audio features and listeners perspective factors that will be of great help to music producers. Violating the features of the song to predict whether the song will be hit before it is released can greatly help producers to increase their profits and reduce the risks, they take in producing songs. The audio features can be processed using machine learning algorithms like Logistic Regression, Support Vector Machines, Random Forest, Naive Bayes Classifier and patterns may be identified in the processed data, which can finally be combined with listeners perspective features to effectively predict hit songs.
Chaining and the formation of spatial semantic categories in childhood

Children face the problem of extending a limited spatial lexicon to potentially infinite spatial situations. Previous work has examined how spatial semantic categories may be formed in child development, but it is unclear how children extend these categories to novel situations over the developmental time course. Drawing on cognitive linguistic theories of category extension, we present a framework that models the incremental extension of spatial relational words to novel situations through time. We describe a longitudinal dataset and computational analyses for investigating the extension of spatial word meanings in a developmental setting. Our preliminary results suggest that the formation of spatial categories takes place through an exemplar-based process of chaining, similar to the process underlying the growth of linguistic categories in history. Our work offers opportunities to explore the connection between ontogeny and phylogeny in the process of word meaning extension.
Algoritmo memético para el Problema del Particionado de Grafos en ejecuciones a largo plazo

El problema del Particionado de Grafos (gpp — Graph Partitioning Problem) es un problema NP-Dif́ıcil cuyo objetivo es particionar los nodos de un grafo en k conjuntos de forma que se minimice el número de aristas que unen vértices localizados en diferentes conjuntos, a la vez que se cumplen restricciones relativas al tamaño de los conjuntos. En los últimos años, el desarrollo de metaheuŕısticas poblacionales que incorporan un control expĺıcito de la diversidad ha permitido realizar avances significativos al tratar diversos problemas de optimización combinatoria como el problema de coloreado de grafos o el de asignación de frecuencias. A pesar de que el gpp es un problema clásico, el desarrollo de metaheuŕısticas poblacionales con control de diversidad para el gpp es un tema prácticamente inexplorado. Por ello, a partir de la hipótesis de que un algoritmo memético con gestión de diversidad ayudaŕıa a mejorar el estado del arte para el gpp, se desarrollaron nuevos algoritmos que efectivamente han permitido mejorar las soluciones encontradas hasta la fecha para una gran cantidad de casos. El trabajo presentado es un resumen de la tesis que ganó el Premio Mixbaal a la mejor tesis de licenciatura en matemáticas aplicadas, en la edición del año 2019. Este premio es otorgado por la Sociedad Mexicana de Computación Cient́ıfica y Sus Aplicaciones.
Forage particle size: it s implications on behavior, performance, health and welfare of dairy cows

Forage particle size has long been recognized as the key intricate factor determining ration contents of physically effective neutral detergent fibre, which in recent years has become the most important consideration in advanced dairy feed formulation for the rumen health, milk yield and welfare of the dairy cows. Fine chopping reduces particle size, resulting in reduced forage dry matter intake, lower retention period of digesta, decreased digestibility of fiber, inconsistent quality of ruminal mat, decreased milk yield, depression of milk fat, and health issues secondary to sub-acute ruminal acidosis. Similarly, excessive coarse forage particles may be lead to reduced total nutrient intake, poor digestibility of organic matter, reduced milk yield and quality, and compromised overall performance. The rumen is a constant fermentation vessel, containing vast amounts of hydrogen ions that can only be stabilized by a proper salivary buffer balance obtained through intake of sufficient effective neutral detergent fibre and its optimal duration. The overall impacts of particle size, however, depend on forage type, forage to concentrate ratio and, fermentability characteristics of the organic matter in the formulated ration. In general, 8-19 mm particle size irrespective of forage type measured on Penn State Particle Separator may be considered optimum for practical dairy feed formulation.
A Stricter Constraint Produces Outstanding Matching: Learning More Reliable Image Matching Using a Quadratic Hinge Triplet Loss Network *

A BSTRACT Image matching is widely used in many applications, such as visual-based localization and 3D reconstruction. Compared with traditional local features (e.g., SIFT) and outlier elimination methods (e.g., RANSAC), learning-based image matching methods (e.g., Hard-Net and OANet) show a promising performance under challenging environments and large-scale benchmarks. However, the existing learning-based methods suffer from noise in the training data and the existing loss function, e.g., hinge loss, does not work well in image matching networks. In this paper, we propose an end-to-end image matching method that with less training data to obtain a more accurate and robust performance. First, a novel data cleaning strategy is proposed to remove the noise in the training dataset. Second, we strengthen the matching constraints by proposing a novel quadratic hinge triplet (QHT) loss function to improve the network. Finally, we apply a stricter OANet for sample judgement to produce more outstanding matching. The proposed method shows the state-of-the-art performance when applied to the large-scale and challenging Phototourism dataset that also reported the 1st place in the CVPR 2020 Image Matching Challenges Workshop Track1 (un-limited keypoints and standard descriptors) using the reconstructed pose accuracy metric.
Building Subjective Opinions on Amateur Football Player 1 Step Kicks by Analyzing Ankle Biomechanics

Kicking is the fundamental skill in Football. 2 most common shots are Laces (In step) and Inside (Side foot). Key biomechanical features are Hip flexion, Knee extension, Backswing, Force on landing foot, Ball Contact and Follow through. In this experiment, a simple kick study with University football team regarding their technique upon Ball Contact is analyzed. “1-step” kicking analysis was done via video recording, importing into an application, plotting the motion of kick, and its velocities. An Inertial Measuring Unit sensor was placed on the front outer sole of the football boot to monitor the ankle rotations upon ball contact. The aim was to understand each player’s technique regarding their position profile and gameplay approach. Based on existing opinions on players, could technology analysis, with camera and sensor support observation assessment? A Decision matrix was created to rank each kicker against tracked features linking to selected biomechanics. After reviewing video and sensor data, 2 players showed differences compared to initial observed rank, with greater understanding of 1 player’s technique. Research Article
Curative Therapies for Hepatitis C Virus Infection in Patients with Kidney Disease

Abstract Through the discovery of direct-acting antiviral therapies over the last decade, hepatitis C virus (HCV) has been transformed from a highly morbid and potentially fatal chronic viral infection to a curable illness. HCV is common in patients with kidney disease, is a risk factor for progression of CKD, is associated with higher morbidity and mortality in patients receiving dialysis, and leads to worse allograft and patient outcomes in recipients of kidney transplants. Clinical trial and real-world data of direct-acting antivirals in patients with kidney disease demonstrate extremely high cure rates and favorable adverse event profiles. This review covers the transformative effects of curative HCV therapies on patients with kidney disease, including patients with CKD, ESKD, and those who have received a kidney transplant.
Void space containing crystalline Cu(I) phenanthroline complexes as molecular oxygen sensors

We have shown that crystals of a number of emissive copper compounds of the form [Cu(NN)2]X (X = BF4−, tfpb−) (where NN = 1,10-phenanthroline (phen), 2,9-dimethyl-1,10-phenanthroline (dmp), 2,9-dimethyl-4,7-diphenyl-1,10-phenanthroline (bdmp), 2,9-diisopropyl-1,10-phenanthroline (dipp), 2,9-ditert-butyl-1,10-phenanthroline (dbp); tfpb− = tetrakis(bis-3,5-trifluoromethylphenylborate) are oxygen sensors, if they contain void space. All of the tfpb− salts were found to be oxygen sensors reinforcing the idea that bulky counterions can produce void space and obviate the need for a support material in solid-state photoluminescent oxygen sensors. The reponse time for the X = tfpb− and NN = dipp complex was measured to be fast (280 ms (95% of final value)). The first solid-state quantum yields and lifetimes are reported for the [Cu(NN)2]X systems and are found to be approximately 10 times larger than those observed in solution-state measurements. The linear Stern−Volmer plots with highly reproducible Ksv constant.
Operation and control of micro sources in Island mode of a Microgrid

In the country like India where population is increasing at a rapid rate the electrical power demand has become a great problem. Unfortunately the conventional energy resources are limited, cause greenhouse emissions and are expected to increase in costs due to an increase in the demand. Recently, the new concept of MicroGrid has been emerging on distribution network for integration of micro generation in low voltage network and to increase the reliability of supply. A microgrid is a cluster of micro generators, loads, storage devices, control devices and a low voltage distribution network functioning in a coordinated manner. The microgrid can operate in two different modes: interconnected or emergency. In first mode the microgrid is connected with the conventional low voltage distribution network for importing or exporting electricity. In emergency mode the microgrid is isolated (islanded) with the help of control devices from the distribution network and uses local micro-generators, changing from power control to frequency control. Most of the micro sources installed in a microgrid cannot be connected directly to the electrical network therefore; power electronics interfaces (dc/ac or ac/dc/ac) are required. Thus, the inverter control is also a challenge for smooth and reliable operation of a smart microgrid. This paper describes microgrid operation in various modes and various control strategies adopted. © 2014 Elixir All rights reserved. ARTICLE INF O Articl e h istory: Received: 17 June 2014; Received in revised form: 19 November 2014; Accepted: 29 November 2014;
Deep Stacked Patch Auto-Encoder Based Organ Classification For Surgical Data Science Applications

A deep learning based robust classiﬁcation is presented using Deep SPAE (Stacked Patch Auto-Encoder) optimized using Black-Widow Optimization (BWO) algorithm in anatomical structures which is commonly called as Deep SPAE_BWO. Initially, pre-processing is done using GIF (Guided Image Filter) eliminates the noise and preserves the sharp edges. Next normalization using Min_Max method makes changes in the range of pixel values. Then, the image structures which possess similar characteristics are grouped with Modified C-Mean (MC-M) clustering. Feature Extraction is done using Entropy based Local Binary Pattern (ELBP), Grey Level Co-occurrence Matrix (GLCM) and Grey Level Run Length Matrix (GLRLM) to extract the optimal features. The tissues may be incompletely visible and may look different across images. So, Deep SPAE_BWObased classification is used to classify the anatomical structures followed by automatic confidence estimation named Gini-co-efﬁcient (GC). Finally, an automatic image tagging (IT) approach is presented to label the classified images as Liver, Gallbladder and Fat Tissues. This work is implemented in PYTHON tool. The classification performance is evaluated in terms of precision, specificity, accuracy, sensitivity, NPV (Negative Predictive Value) and F1-score.
Biogeochemistry of Mediterranean Wetlands: A Review about the Effects of Water-Level Fluctuations on Phosphorus Cycling and Greenhouse Gas Emissions

Although Mediterranean wetlands are characterized by extreme natural water level fluctuations in response to irregular precipitation patterns, global climate change is expected to amplify this pattern by shortening precipitation seasons and increasing the incidence of summer droughts in this area. As a consequence, a part of the lake sediment will be exposed to air-drying in dry years when the water table becomes low. This periodic sediment exposure to dry/wet cycles will likely affect biogeochemical processes. Unexpectedly, to date, few studies are focused on assessing the effects of water level fluctuations on the biogeochemistry of these ecosystems. In this review, we investigate the potential impacts of water level fluctuations on phosphorus dynamics and on greenhouse gases emissions in Mediterranean wetlands. Major drivers of global change, and specially water level fluctuations, will lead to the degradation of water quality in Mediterranean wetlands by increasing the availability of phosphorus concentration in the water column upon rewetting of dry sediment. CO2 fluxes are likely to be enhanced during desiccation, while inundation is likely to decrease cumulative CO2 emissions, as well as N2O emissions, although increasing CH4 emissions. However, there exists a complete gap of knowledge about the net effect of water level fluctuations induced by global change on greenhouse gases emission. Accordingly, further research is needed to assess whether the periodic exposure to dry–wet cycles, considering the extent and frequency of the cycles, will amplify the role of these especial ecosystems as a source of these gases and thereby act as a feedback mechanism for global warming. To conclude, it is pertinent to consider that a better understanding about the effect of water level fluctuations on the biogeochemistry of Mediterranean wetlands will help to predict how other freshwater ecosystems will respond.
Influence of Species, Geographic Location, Seasonal Variation and Extraction Method on the Fucoidan Yield of the Brown Seaweeds of Gulf of Mannar, India

Special Issue 8, 2020 Indian Journal of Pharmaceutical Sciences 46 *Address for correspondence E-mail: yudelindl_1997@163.com This study aims to discuss the relationship between gastric perfusion and gastric mucosal injury induced by acute cerebrovascular disease in rats. Healthy adult male Wistar rats weighing 280-320 g are randomly divided into the following 4 groups: middle cerebral artery occlusion-reperfusion group, middle cerebral artery occlusion -sham group, gastric ischemia-reperfusion group and gastric ischemia-sham group, with 12 in each group. In gastric ischemia-reperfusion group, the similar changes occur to the mucous membrane of the rats, such as hyperaemia, edema, spotty or patchy hemorrhage and partial mucous exfoliation. There is no significant difference between middle cerebral artery occlusion-reperfusion group and gastric ischemia-reperfusion group in the number of gastrin cells and the expression of gas, but the number of gastrin cells and the expression of gas are significantly higher than those of their corresponding sham operation group, resulting in statistically significant difference. The gastric mucosal blood flow is significantly increased in the middle and high dose groups, which has significant difference compared with normal saline group (p<0.05). One of the important mechanisms of Calcitonin gene-related peptide protecting ischemic gastric mucosal injury is to increase gastric mucosal blood perfusion and improve microcirculation.
The challenges in control COVID-19 in Injibera, Awi Zone, Amhara Region, Ethiopia

Background: In the globe, on April 2021, 130 million coronavirus cases, around 2.8 million were deaths, 102 million were recovered and 105.2 million were closed cases of COVID-19 reported. On April 2021, the world population were 7.9 billion of which United Nations estimates were 1.65% COVID-19 cases included the Ethiopia in report. The main objective of the study was identify the challenges of in control COVID-19.Methods: The cross-sectional study design was used November to February 2021 in Injibera from Ethiopia. The total 385 respondents using simple random sampling were interviewed. The chi-square test of association and ordinal logistic regression was applied to identify the effect of predictor variables on challenges in control COVID-19.Results: Out of 385 respondents 277(71.95%) were high challenges in control COVID-19 in Injibera. There was a significant relationship with social media and challenges of in control virus (p-value = 0.047). The variables considered social media, housing status and influence were significant relationship with challenges of in control virus (p-value < 5%). Facebook users were the responsible causes of challenges in control COVID-19 (p-value = 0.023). The more social media followed, decreased the occurrence of challenges in control virus. In addition, a unit increase rented, the challenges in control virus decreased by 0.60 times (p-value = 0.009). Conclusion: Winning against the coronavirus together with world couldn’t be a marathon. COVID-19 couldn’t be won without collective global and local effort. It would also need serious thinking, discipline and war against the only virus. COVID-19 war needs in control, the globe should be faced free, coordination and discover scientific methods together.
The double-edged sword of 'best aspects' and 'needs improvement' in student experiences: A qualitative analysis

Improving student experiences in higher education is of ongoing interest to colleges and universities across the globe. Non-university higher education institutions (NUHEIs) have outperformed universities in Australian national surveys on student experience. The present study examines qualitative responses of the Student Experience Survey within the context of Alphacrucis College (AC), a faith-based, private NUHEI to provide a contextualised understanding of NUHEIs as well as to explore reasons why NUHEIs outperform universities in most student experience categories. Content analysis revealed several themes in areas of ‘best experience’ and ‘needs improvement. ’ Results were examined across AQF levels and three study modes, namely online, blended, and on-campus. Findings are discussed in terms of the NUHEI student experience, lecturer training, lecturer performance indicators, and institutional infrastructure.
mmapx: uniform memory protection in a heterogeneous world

Modern Systems-on-Chip (SoCs) are networks of heterogeneous cores, intelligent devices, and memory, connected through multiple configurable address translation and protection units like IOMMUs and System MMUs. Modern OS kernels like Linux are based on traditional MMUs and have no clear abstractions to represent this complexity, mostly leaving IOMMU configuration to device drivers. This has led to a recent spate of serious bugs, and increasing concern over "cross-SoC" attacks on memory security. To address this, we propose a new kernel primitive, mmapx, based on a decoding net a rich and detailed representation of the memory addressing semantics of a complex SoC from the recent formal methods literature. mmapx provides a uniform facility for securely configuring all the address translation facilities in a system. mmapx leverages existing Unix facilities wherever possible: the file system for naming, discovery, and coarse-grained access control, and file descriptors for fine-grained authorization. We show how mmapx can eliminate bugs caused by device drivers programming IOMMUs directly, but also the detail captured by the underlying model has further benefits while incurring minimal overhead.
Exosomes derived from bone marrow mesenchymal stem cells promote angiogenesis via transfer of miR-21-5p after cerebral ischemia in mice

Background Mesenchymal stem cells (MSCs) transplantation is a potential clinical therapy for cerebral ischemia. The therapeutic effects of MSCs primarily depends on the paracrine action by releasing exosomes (Exos). Exosomes derived from bone marrow mesenchymal stem cells (BMSC-Exos) could modulate target cell functions by transferring microRNAs (miRs) cargo. In this study, we aimed to investigate whether BMSC-Exos could promote angiogenesis via transfer of miR-21-5p after cerebral ischemia. Methods BMSC-Exos were isolated from conditioned medium of BMSCs by differential ultracentrifugation, and confirmed by transmission electron microscopy, nanoparticle tracking analysis, and western blot analysis. In mice with middle cerebral artery occlusion (MCAO), the neurological function was evaluated by Zea Longa’s method, and the infarct volume and microvessel density were detected by TTC staining and vWF immunofluorescence staining, respectively. The proangiogenic effects of BMSC-Exos were assessed via proliferation, migration, and tube formation of human umbilical vein endothelial cells (HUVECs) in vitro assays. The miR-21-5p expression was detected by qRT-PCR. The expression levels of VEGF, VEGFR2, Ang-1, and Tie-2 were determined by western blot. Results BMSC-Exos significantly improved neurological function and reduced infract volume after cerebral ischemia. Moreover, BMSC-Exos significantly upregulated the microvessel density and the expression levels of proangiogenic proteins VEGF, VEGFR2, Ang-1 and Tie-2 in the ischemic boundary region. MiR-21-5p expression was also dramatically increased after cerebral ischemia. In vitro assays revealed that BMSC-Exos enhanced HUVECs functions including proliferation, migration and tube formation, as well as increasing the expression of VEGF and VEGFR2. However, these proangiogenic effects of BMSC-Exos on HUVECs were reversed by miR-21-5p inhibitor. Conclusion Our study indicated that BMSC-Exos could promote angiogenesis and neurological function recovery via transfer of miR-21-5p. Therefore, the application of miR-21-5p-loaded BMSC-Exos might be an attractive treatment strategy of cerebral ischemia.