Miracle-dz/UniFAR-FTUs huggingface dataset:
Beneficial effect of Hordeum vulgare extract against aluminum chloride induced neurotoxicity in Wistar rats

Hadj Fidah* Laboratory of Biotoxicology, Pharmacognosy and Biological Valorisation of plants (LBPVBP) Department of Biology, Faculty of Natural and Life Sciences, University of Dr Moulay TaharSaida-Algeria Kadda Hachem Laboratory of Biotoxicology, Pharmacognosy and Biological Valorisation of plants (LBPVBP) Department of Biology, Faculty of Natural and Life Sciences, University of Dr Moulay TaharSaida Algeria Djallal Eddine Adli Laboratory of Biotoxicology, Pharmacognosy and Biological Valorisation of plants (LBPVBP) Department of Biology, Faculty of Natural and Life Sciences, University of Dr Moulay TaharSaida-Algeria Mostapha Brahmi Laboratory of Biotoxicology, Pharmacognosy and Biological Valorisation of plants (LBPVBP) Department of Biology, Faculty of Natural and Life Sciences, University of Dr Moulay TaharSaida-Algeria Hemida Houari Institute of Veterinary Sciences, University of Tiaret, Algeria Khaled Kahloula Laboratory of Biotoxicology, Pharmacognosy and Biological Valorisation of plants (LBPVBP) Department of Biology, Faculty of Natural and Life Sciences, University of Dr Moulay TaharSaida-Algeria Miloud Slimani Laboratory of Biotoxicology, Pharmacognosy and Biological Valorisation of plants (LBPVBP) Department of Biology, Faculty of Natural and Life Sciences, University of Dr Moulay TaharSaida-Algeria
Consequences of abandoned Cu-Co mining in Northern Spain in surface watercourses

Prehistoric tools at the Texeo Mine indicate it is one of the oldest Asturian mining sites. The ore deposit was formed by metasomatic replacement related to fracture systems in Carboniferous limestones. The mineralization comprises major Cu-Co-Ni sulphides and arsenides, with minor concentration of precious metals. The mine site has been the most important source of Cu in the region since Roman times and nowadays, approximately 40,000 m of wastes from mine and metallurgical operations containing average concentrations of 9,263 mg.kg Cu, 1,100 mg.kg As, 549 mg.kg Co, and 840 mg.kg Ni are accumulated on site, posing a threat to the environment, due to the potential release of toxic elements. A sequential systematic sampling has been undertaken in wastes, soils and waters, to outline anthropogenic anomalies, which have been found especially for As and Cu in soils, whereas concentrations up to 5 mg.l Cu have been detected in surface water downstream the mine works. Computer based risk assessment for the site gives a carcinogenic risk associated to the presence of As in waters and soils, and a health index risk for long exposures mainly associated to the presence of high contents of Cu in soils.
Acoustic Control of Directed Assembly in Microfluidic Devices

A combined top-down/bottom-up microfluidic assembly system is demonstrated in which microspheres undergo directed assembly within microchannels. The approach is adapted from macroscale templated assembly by selective removal (TASR), in which high-frequency acoustic excitations drive selective assembly into shape- and size-matched wells patterned in a planar surface. A PDMS layer patterned with microchannels is bonded to a PDMS layer molded to define assembly wells. A suspension of 10 <inline-formula> <tex-math notation="LaTeX">$\mu \text{m}$ </tex-math></inline-formula> diameter polystyrene microspheres is flowed into the microchannels, and an external, high-frequency ultrasonic transducer circulates the microspheres within the channels and removes them from everywhere except the size-matched wells. Microspheres are successfully assembled in wells inside the microchannels with yields of up to 90%. Smaller channel dimensions reduce assembly yield in part because smaller internal channel volumes reduce the availability of microspheres relative to assembly wells. In addition, reducing channel width below about <inline-formula> <tex-math notation="LaTeX">$500~\mu \text{m}$ </tex-math></inline-formula> is shown to be an independent predictor of low assembly yields; this is attributed to the physics of acoustic streaming flow under the acoustic excitation. Assembly yield is largely independent of the location of the assembly wells within the microchannels, and selectivity is confirmed by low assembly yield of <inline-formula> <tex-math notation="LaTeX">$6~\mu \text{m}$ </tex-math></inline-formula> diameter microspheres into the larger wells. [2020-0072]
An Enhanced Artificial Ecosystem-Based Optimization for Optimal Allocation of Multiple Distributed Generations

Optimal allocation of distributed generations (DGs) is vital to the proper operation of the distribution systems, which leads to power loss minimization and acceptable voltage regulation. In this paper, an Enhanced Artificial Ecosystem-based Optimization (EAEO) algorithm is proposed and used to solve the optimization problem of DG allocations to minimize the power loss in distribution systems. In the suggested algorithm, the search space is reduced using operator G and sine-cosine function. The G-operator affects the balance between explorative and exploitative phases. At the same time, it gradually decreases during the iterative process in order to converge to the optimal global solutions. On the other hand, the sine-cosine function creates different and random solutions. The EAEO algorithm is applied for solving the standard 33-bus 69-bus, and 119-bus distribution systems with the aim of minimizing the total power losses. Multiple DG units operating at various power factors, including unity-, fixed-, and optimal-power factors, are considered. Both single and multiple objectives are considered to minimize the total voltage deviation (TVD), maximize the system stability, and reduce the total power losses. The obtained results are compared with those obtained by the AEO and other algorithms. The results demonstrate a significant reduction of total power losses and improvement of the voltage profile of the network, especially for the DGs operating at their optimal power factors. Comparisons show the dominance of the proposed EAEO algorithm against other analytical, metaheuristic, or hybrid algorithms. Moreover, the EAEO outperforms the original AEO algorithm with a faster convergence speed and better system performance.
Closed-Form Training-Based Blind Estimation of Frequency Offset for QAM Signals with Unknown Power and Signal-to-Noise Ratio

A method is proposed for blind estimation of the frequency offset for signals with quadrature amplitude modulation. The method allows to obtain the result in a closed form, it is a modified version of the Luise and Reggiannini method for harmonic signal frequency estimation. The main modification is the introduction of a two-dimensional weighting function that depends on the magnitudes of two signal samples. Optimization of this weighting function is carried out by training in batch mode on the simulated sequences of signal samples. Normalization of input signal power and the use of training sequences with various signal-to-noise ratios allow to adapt weighting function to varying reception conditions. The results of computer simulation confirmed the efficiency of the proposed method and showed the advantage of a two-dimensional weighting function over one-dimensional versions.
Total and Available Micronutrient Status in Soils of Derived Savanna Ecology of Oyo State, Nigeria

The potentially available and total micronutrient status in soils of derived savanna ecology of Oyo State, Nigeria were assessed and compared with standard critical values in soils. Soil samples were collected from a land measuring 285m 2 on a line transect with the aid of a stainless soil auger. The sampling depths were 0 -15 cm, 15 – 30 cm, 30 – 45 cm and 45 – 60 cm respectively. The Physico-chemical properties and micronutrient content of the soil were determined using standard methods. The mobility factor of the micronutrients revealed the following trends Zn > Fe > Mn > Cu. In all, the concentration of Mn was relatively constant irrespective of the soil depth. This study revealed that the micronutrients (Fe, Mn, Zn, and Cu) were adequate and well supplied in the soils of the area, and therefore, deficiencies of the elements are quite unlikely. Generally, the soils contained Fe, Mn, Zn, and Cu above the critical level for crop production. The application of organic matter would help to improve the overall fertility of the soil. Activities that hastens up mineralization of organic materials should be minimized in managing soil health for optimum nutrient availability. Soil testing is recommended before fertilizer use to prevent nutrient imbalance or toxicity. Original Research Article Oviasogie and Okoro; IRJPAC, 21(9): 17-26, 2020; Article no.IRJPAC. 57196 18
Clinical, Morphological and Immunophenotypical Findings in Acute Leukemia: A Study from a Tertiary Care Hospital

BackgroundAcute leukemias comprise a heterogeneous group of diseases characterized by rapid and uncontrolled clonal expansion of progenitor cells of the hematopoietic system. Immunophenotyping helps subclassify acute leukemias into subgroups with prognostic implications.Materials and MethodsThis descriptive observational cross-sectional study was performed on 80 newly diagnosed cases of acute leukemia in children up to 18 years of age from August 2012 to Febuary 2014.The immunophenotypic analysis was performed by Beckman Coulter Flow cytometer using monoclonal antibodies against various cell surface / cytoplasmic antigens.ResultsOut of 80 cases, 68 cases had acute lymphocytic leukemia (ALL) and 12 cases had acute myelocytic leukemia (AML). In this study, 68 cases of ALL could be categorized into 53 cases of B-ALL, 13 of T-ALL, and 2 cases of Bi-phenotypic acute leukemia (BAL). Twelve cases of AML comprised of 7 cases of AML with minimal differentiation; 2 of AML with cases of AML with maturation, and 3 cases of acute myelomonocytic leukemia. Hepatosplenomegaly was seen in the majority of cases in both ALL and AML. Most cases had a total leucocyte count between 10,000 and 50,000/µl and platelets <100,000/µl. Hemoglobin levels were < 7.5 g/dl in the majority of them. CD19 and CD79a were 100 % sensitive for B ALL, while cCD3 was 100% sensitive for T-ALL. MPO was positive in all cases of AML.ConclusionImmunophenotyping must be done in all AL cases as it helps in risk-stratification and follow up of patients for evaluating minimal residual disease.
EURASIAN JOURNAL OF BUSINESS AND MANAGEMENT

Purpose of this paper is to value the role of the human capital in the profitability production within the Italian Mutual Bank (Bcc); to achieve this, we provide for the carrying out of an analysis on a sample of 209 of the above-mentioned banks using the Pulic’s VAIC TM methodology (1998), in a five-year period of time (2006-2010). Obviously, we will use what the specialized literature gives us, which offers interesting and in-depth hints about the intellectual capital, but only referred to the listed medium-large banks; as far as we know there are no analysis and assessments over the local banks which, apart from their dimension, have a more and more nerve role in the financing of the real economy. The results of our analysis show clearly how the human capital has a meaningful role on the banks’ profitability, especially those which let the active presence in the territory be a setting value of their own business mission. At a territorial level, the Bcc of the South show steadier marginal effects than their sister companies of the North. In a historical period characterized by evident phenomena of credit crunch put into action by the great banks on the real economy, the banks’ local model and centrality of the human capital which characterize them still represents a value on which set up the sustain and the revival of the economy in the territory.
Trailing Behavior in Prairie Rattlesnakes (Crotalus viridis)

Six rattlesnakes (Crotalus v. viridis) were observed in four experimental conditions designed to assess ability to follow odoriferous mouse trails. If snakes had not struck mice just prior to being exposed to the trails, then no trailing behavior was observed, whereas trails were followed with precision if the snakes struck mice prior to the tests. Striking led to pronounced elevations in rate of tongue flicking, and the magnitude of this effect did not depend upon presence vs absence of mouse trails in the post-strike environment. However, when a trail was present, the high rate of tongue flicking facilitated locating the trail and following it to the mouse carcass positioned at its end. Once a trail was located, the snake confined its head to within 2 cm of the odoriferous cues, and 75% of the tongue flicks were directed to the trail.
Piezoelectricity in Sr doped thick films of hydroxyapatite

The current study reports the synthesis, characterization and tape casting of strontium substituted into the calcium sublattice of hydroxyapatite in range of (0–100 mol%). The XRD powder data reveals that a primary HAp phase as well as secondary Ca3(PO4)2 (β-TCP) phase coexist. Our analysis shows that Sr+2 preferentially occupies the HAp lattice sites rather than β-TCP. Developed free-standing tapes of HAp offer unique possibility of custom designed solutions for biomedical applications by controlling shape size and tuned electrical properties. We report piezoelectricity in Sr doped hydroxyapatites thick films, the piezoelectric coefficient is an order of magnitude higher than what has been previously obtained in PLD deposited hydroxyapatite films [15]. The piezoelectricity shows slight improvement with the Sr doping. Despite low piezoelectric coefficient, the generated voltage is of the order of mV which is high enough to have physiological relevance since the resting potential of the cells lie between 60–90 mV. Further improvements in the material design and poling could pave way to understand the role of electricity in bone growth and to use piezoelectric energy harvesting to tune spinal and neuro stimulators.
Development of e-textile sewn together with embroidered fabric having motion-sensing function using piezoelectric braided cord for embroidery

We have developed a new type of piezoelectric poly-/-lactic acid (PLLA) braided cord that can be embroidered (piezoelectric PLLA embroidery) as a motion-sensing material for a new type of wearable sensor. We then examined the motion-sensing function of the piezoelectric PLLA embroidery in response to different types of movement. On the basis of the experimental results, we produced e-textiles embroidered with the piezoelectric PLLA braided cord as materials for a new wearable sensor. These e-textiles with piezoelectric PLLA embroidery, which are flexible, feel soft and are similar to high-quality fabrics, can sense complex human motion without using a complex computer system.
Improving the Efficiency of Deep Learning Methods in Remote Sensing Data Analysis: Geosystem Approach

The article proposes a solution for the problem of high-resolution remote sensing data classification by applying deep learning methods and algorithms in conditions of labeled data scarcity. The problem can be solved within the geosystem approach, through the analysis of the genetic uniformity of spatially adjacent entities of different scale and hierarchical level. Advantages of the proposed GeoSystemNet model rest on a large number of freedom degrees, admitting flexible configuration of the model contingent upon the task at hand. Testing GeoSystemNet for classification of EuroSAT dataset, algorithmically augmented after the geosystem approach, demonstrated the possibility to improve the classification precision in conditions of labeled data accuracy by 9% and to obtain the classification precision with a larger volume of training data (by 2%) which is slightly inferior in comparison with other deep models. The article also shows that synthesis of the geosystem approach with deep learning capabilities allows us to optimize the diagnostics of exogeodynamic processes, owing to the calculation of landscape differentiation regularities. Application of the presented approach enabled us to improve the accuracy in detecting landslides at the testing site “Mordovia” by 5% in comparison with the classical approach of using deep models for remote sensing data analysis. The authors advocate that application of the geosystem approach to improve the efficiency of remote sensing data classification through methods, proposed in the article, requires an individual project-based approach to source data augmentation.
Prevalence of subclinical mastitis in cattle in and around Bikaner district of Rajasthan

Lactating cows (n=100) were examined for subclinical mastitis (SCM) by California Mastitis Test (CMT) and cultural examination during the period from December, 2018 to December, 2019. On the basis of CMT; the prevalence of SCM was 42% and 24.50% on animal and quarter basis and on the basis of cultural examination; the prevalence was 51% and 29.75% on animal and quarter basis, respectively. Highest prevalence of SCM was observed in right hind quarter (45%) followed by left hind quarter (30%), right fore quarter (23%) and left fore quarter (21%). Maximum numbers of cows (72.22%) were affected with SCM in Vth parity, followed by 64.00, 63.63, 58.33, 31.57 and 13.33% in IVth, VIth, IIIrd, IInd and Ist parity, respectively.
The role of the interaction between the FKBP5 gene and stressful life events in the pathophysiology of schizophrenia: A narrative review

Stressful life events have been associated with increased risk for development of schizophrenia and play a pivotal role in its psychopathology. Genes related to stress response, such as FKBP5 gene associated with hypothalamic–pituitary–adrenal (HPA) axis, modulate brain response to childhood trauma and determine individual susceptibility for development and course of psychosis. It this review we provide an overview of FKBP5 gene role in human neurophysiology, its association with HPA axis and its role in stress response system in animals and humans. Moreover, we took a closer look on the studies showing the interaction between FKBP5 gene and stressful life events in the pathophysiology of schizophrenia. We explain how interactions between trauma and FKBP5 gene polymorphisms contribute to development of the disease, severity of psychotic symptoms and cognitive disturbances. We also discuss epigenetic modifications that may contribute to altered HPA axis reactivity to stress entailing higher risk for development of psychosis. Considering the pivotal role of FKBP5 gene in physiopathology of schizophrenia we discuss a possible use of new therapeutic agents that may influence HPA axis activity related to the FKBP5 protein especially in individuals exposed to early trauma.
A Systematic Assessment of Embedded Neural Networks for Object Detection

Object detection is arguably one of the most important and complex tasks to enable the advent of next-generation autonomous systems. Recent advancements in deep learning techniques allowed a significant improvement in detection accuracy and latency of modern neural networks, allowing their adoption in automotive, avionics and industrial embedded systems, where performances are required to meet size, weight and power constraints.Multiple benchmarks and surveys exist to compare state-of-the-art detection networks, profiling important metrics, like precision, latency and power efficiency on Commercial-off-the-Shelf (COTS) embedded platforms. However, we observed a fundamental lack of fairness in the existing comparisons, with a number of implicit assumptions that may significantly bias the metrics of interest. This includes using heterogeneous settings for the input size, training dataset, threshold confidences, and, most importantly, platform-specific optimizations, that are especially important when assessing latency and energy-related values. The lack of uniform comparisons is mainly due to the significant effort required to re-implement network models, whenever openly available, on the specific platforms, to properly configure the available acceleration engines for optimizing performance, and to re-train the model using a homogeneous dataset.This paper aims at filling this gap, providing a comprehensive and fair comparison of the best-in-class Convolution Neural Networks (CNNs) for real-time embedded systems, detailing the effort made to achieve an unbiased characterization on cutting-edge system-on-chips. Multi-dimensional trade-offs are explored for achieving a proper configuration of the available programmable accelerators for neural inference, adopting the best available software libraries. To stimulate the adoption of fair benchmarking assessments, the framework is released to the public in an open source repository.
Seroprevalence of chikungunya fever in a tertiary care hospital in North Karnataka

Introduction: Chikungunya disease is caused by Chikungunya virus, an Alpha virus under the family Togaviridae, transmitted through the vector Aedes spp. mosquitoes. The sudden onset of very high fever along with rash and severe arthralgia are the main symptoms. It’s a major public health problem similar to other arboviral diseases like Dengue and Japanese B encephalitis infections. Materials and Methods: A cross sectional study was conducted at a tertiary care hospital in north Karnataka. Serum samples of 555 suspected cases of Chikungunya fever were tested for Chikungunya IgM antibodies by ELISA (from NIV, Pune) over a period of 4 years, from January 2013 to December 2016. Results: Of the 555 serum samples tested, 128 (23.06%) were positive for Chikungunya IgM antibodies. The most affected age group was 21 to 30 years 35 (27.34%), followed by 31 to 40 years 26(20.31%). Male to female ratio was 1:1.56. Of the seropositive cases, all the cases presented with the history of fever and joint pain. The maximum number of cases were seen during the monsoon i.e. June 32 (25%), followed by the post monsoon period September 26 (20.31%). ) Conclusions: The seroprevelance of Chikungunya cases in the present study is 23.06% with high prevalence in the monsoon and post monsoon months affecting the productive age group of the population. This reiterates the fact that Chikungunya continues to be a major health concern in our setting and indicates the need for appropriate strategies to reduce the severity of disease.
Prediction of COVID-19 Using Genetic Deep Learning Convolutional Neural Network (GDCNN)

Rapid spread of Coronavirus disease COVID-19 leads to severe pneumonia and it is estimated to create a high impact on the healthcare system. An urgent need for early diagnosis is required for precise treatment, which in turn reduces the pressure in the health care system. Some of the standard image diagnosis available is Computed Tomography (CT) scan and Chest X-Ray (CXR). Even though a CT scan is considered a gold standard in diagnosis, CXR is most widely used due to widespread, faster, and cheaper. This study aims to provide a solution for identifying pneumonia due to COVID-19 and healthy lungs (normal person) using CXR images. One of the remarkable methods used for extracting a high dimensional feature from medical images is the Deep learning method. In this research, the state-of-the-art techniques used is Genetic Deep Learning Convolutional Neural Network (GDCNN). It is trained from the scratch for extracting features for classifying them between COVID-19 and normal images. A dataset consisting of more than 5000 CXR image samples is used for classifying pneumonia, normal and other pneumonia diseases. Training a GDCNN from scratch proves that, the proposed method performs better compared to other transfer learning techniques. Classification accuracy of 98.84%, the precision of 93%, the sensitivity of 100%, and specificity of 97.0% in COVID-19 prediction is achieved. Top classification accuracy obtained in this research reveals the best nominal rate in the identification of COVID-19 disease prediction in an unbalanced environment. The novel model proposed for classification proves to be better than the existing models such as ReseNet18, ReseNet50, Squeezenet, DenseNet-121, and Visual Geometry Group (VGG16).