Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of some enzymes and probiotic mixture on milk production, components and some blood traits in Awassi ewes

Al-Shaar, N. M. , Al-Juwari, M. F. , Saadi, A. M. & Almallah, O. D. (2023). Impact of some enzymes and probiotic mixture on milk production, components and some blood traits in Awassi ewes. Bulg. J. Agric. Sci., 29 (6), 1137–1142 The study was conducted in the animals’ field of the Department of Animal Production / College of Agriculture and For - estry/University of Mosul, to clarify the impact of adding a mixture of enzymes Amylase, Protease and Cellulose with the probiotic in different proportions on milk production and its components in Awassi ewes. The study was carried out by using 12 ewes by using cross over design, the ewes were divided into three groups and fed periodically on the experimental feed at three periods, and each period took up 17 days (15 days’ adaptation period and two days for the collection of milk and blood samples). The ewes in all treatments were fed on standard feed formed of barley, wheat bran, soybeans and wheat straw, with a 1.5 kg/ewe per day of feed, without addition in first treatment (control), or with adding 2g from enzymes mixture and probiotic per ewe per day in the second treatment, while adding 4g of mixture enzymes and probiotic per ewe per day in third treatment. The results showed an improvement in milk production by 10% and 7%, when adding a mixture of enzymes and probiotics in the second and third treatments compared to the control, while the addition was not affected on milk components of protein, fat, lactose and solid non-fat. The results of blood measurements pointed out a significant increase (p ≤ 0.05) in the concentration of the total protein and globulin in second treatment 7.75 and 3.51 g/dl, respectively, compared to the control treatment 6.95 and 2.7 g/100 ml, respectively, while triglycerides decreased significantly (p ≤ 0.05) in second treatment, 38.44 mg/dl as com - pared to the third treatment 43.91 mg/dl. In general, the addition of the enzymes mixture and probiotic improved the production of milk and blood immune proteins in Awassi ewes.
IDENTITIES INVOLVING SUM OF DIVISORS, INTEGER PARTITIONS AND COMPOSITIONS

A bstract . In this paper we show some identities come from the q -identities of Euler, Jacobi, Gauss and Rogers-Ramanujan. Some of these identities relating the function sum of divisor of a positive integer n and the number of integer partitions of n . One of the most intriguing result found here is given by the next equation, for n > 0.
Early-Stage Pine Wilt Disease Detection via Multi-Feature Fusion in UAV Imagery

Pine wilt disease (PWD) is a highly contagious and devastating forest disease. The timely detection of pine trees infected with PWD in the early stage is of great significance to effectively control the spread of PWD and protect forest resources. However, in the spatial domain, the features of early-stage PWD are not distinctly evident, leading to numerous missed detections and false positives when directly using spatial-domain images. However, we found that frequency domain information can more clearly express the characteristics of early-stage PWD. In this paper, we propose a detection method based on deep learning for early-stage PWD by comprehensively utilizing the features in the frequency domain and the spatial domain. An attention mechanism is introduced to further enhance the frequency domain features. Employing two deformable convolutions to fuse the features in both domains, we aim to fully capture semantic and spatial information. To substantiate the proposed method, this study employs UAVs to capture images of early-stage pine trees infected with PWD at Dahuofang Experimental Forest in Fushun, Liaoning Province. A dataset of early infected pine trees affected by PWD is curated to facilitate future research on the detection of early-stage infestations in pine trees. The results on the early-stage PWD dataset indicate that, compared to Faster R-CNN, DETR and YOLOv5, the best-performing method improves the average precision (AP) by 17.7%, 6.2% and 6.0%, and the F1 scores by 14.6%, 3.9% and 5.0%, respectively. The study provides technical support for early-stage PWD tree counting and localization in the field in forest areas and lays the foundation for the early control of pine wood nematode disease.
Processus hydriques dans des écosystèmes forestiers

This paper highlights the results of a research on hydric processes in different forest systems to evaluate the effectiveness on soil conservation. Reafforestations of pine (P. laricio Poir.) and oak coppices (Q. pubescens Willd. and Q. frainetto Ten.) where chosen because they are representative of conditions throughout the Mediterranean area. The interception, which is a function of the forest cover, is a significant factor in the hydrological balance and represents a variable fraction of the occurent rainfall while the stemflow represents a small fraction of the precipitation. In the pine stands rainfall did not cause any runoff This was both because of the crown interception and the infiltration in the soil. It was, moreover, possible to confirm that the reduction of density did not substantially modify the hydrological balance.
Local intraseasonal air–sea relationship over the North Indian Ocean and western North Pacific during the spring-to-summer transition

Abstract This study investigates the local air–sea relationship associated with the two dominant intraseasonal oscillation (ISO) components during the spring-to-summer transition and compares their properties using multiple air–sea variables in the period 1998–2013. The amplitude of percentage variance in SST in periods of 10–20 and 30–60 days are comparable, but the locations of the maxima differ. A strong percentage variance in the 10–20-day SST is evident in the equatorial western Pacific, whereas for the 30–60-day SST the strongest ratio occurs in the North Indian Ocean (NIO), South China Sea (SCS), and North Pacific. Over the NIO, SCS, and Philippine Sea, there are significant correlations between SST and precipitation for both 10–20-day and 30–60-day ISOs. In contrast, the correlations between SST and surface heat fluxes cover a broader region and have larger coefficients. Thus, the atmospheric variables and surface heat fluxes show larger variations within the higher frequency band. However, the amplitude of the correlation coefficients between SST and surface heat fluxes, and SST and rainfall, is greater in the lower frequency band. The corresponding time lags for the different variables reveal that a strong local air–sea interaction is indicated over the NIO, SCS, and western North Pacific, from April to June in both timescales; however, the strength of the air–sea relationship depends on the region and variable.
Original Research “Someone You Love” Documentary: Using Narratives in Entertainment Media to increase HPV vaccination in Georgia

Background: Although HPV is the most common sexually transmitted disease in the United States, vaccination rates are still lagging among adolescents and young adults. Entertainment-education is a popular strategy for incorporating educational messages into entertainment media. With popular shows on television now integrating health messages into their narrative, there are more opportunities to influence knowledge, attitude and health behaviors. Objective: To (a) determine the effectiveness of the HPV narrative included in the “Someone You love” documentary on HPV risk perception, vaccine self-efficacy and behavioral intention for HPV vaccine uptake on college students and (b) assess the immediate impact of the documentary on HPV vaccine initiation. Methods: A dependent samples t-test was conducted to determine if differences in the scale scores for each variable existed between pre and post viewing. Scale items were measured on a 7-point Likert scale and summed for analyses. Results: Students (n=126) participated in four screenings. Participants were mostly female (76.5%), freshman (40%), Caucasian (48.3%), heterosexual (81.5%) and sexually active (74.3%). The results showed a positive and significant effect from pre-and post-test scores on Risk Perception 7.150, t (119) = 14.502, p. Discussion: While the documentary shares light on the impact of HPV transmission and its deadly impact, no formal research study has been done to measure its overall impact on behavior change. After watching the documentary in our study, gains pre to posttest scores indicate that overall students in our study felt more at risk for HPV, were confident in their ability to seek out and receive the vaccine and they had a greater intention to start the HPV vaccination series.
How good was the fossil record? Clues from the Californian Pleistocene

The living members of 113 families of bivalves and gastropods of the Californian Province include 698 species living at shelf depths, of which 538 or 77% are known as Pleistocene fossils from the same region; another 113 fossil species are extralimital, and 98 are extinct. Living species not found as fossils are chiefly rare today, and/or minute, fragile, and/or from deeper shelf habitats. Sampling of the Pleistocene record has been biased towards shallow-water assemblages. Fragile and minute forms are probably underrepresented in the record. Rare forms, however, are still appearing as new studies are conducted, and many rare species are yet to be discovered. At least 85% of durably skeletonized living species may have been captured in the record. It is probable that most durably skeletonized invertebrate species were represented in lithostratigraphic units throughout the Phanerozoic, but that this record is lost owing to erosion, burial, and destruction of skeletons in situ. The bulk of the marine invertebrate fossil record does not represent a series of unusual skeletal accumulations, but rather the preserved remnants of an excellent original record formed through ordinary though episodic processes.
MAAL: Multimodality-Aware Autoencoder-based Affordance Learning for 3D Articulated Objects

Inferring affordance for 3D articulated objects is a challenging and practical problem. It is a primary problem for applying robots to real-world scenarios. The exploration can be summarized as figuring out where to act and how to act. Correspondingly, the task mainly requires producing actionability scores, action proposals, and success likelihood scores according to the given 3D object information and robotic information. Current works usually directly process multi-modal inputs with early fusion and apply critic networks to produce scores, which leads to insufficient multi-modal learning ability and inefficiently iterative training in multiple stages. This paper proposes a novel Multimodality-Aware Autoencoder-based affordance Learning (MAAL) for the 3D object affordance problem. It is an efficient pipeline, trained in one go, and only requires a few positive samples in training data. More importantly, MAAL contains a MultiModal Energized Encoder (MME) for better multi-modal learning. It comprehensively models all multi-modal inputs from 3D objects and robotic actions. Jointly considering information from multiple modalities, the encoder further learns interactions between robots and objects. MME empowers the better multi-modal learning ability for understanding object affordance. Experimental results and visualizations, based on a large-scale dataset PartNet-Mobility, show the effectiveness of MAAL in learning multi-modal data and solving the 3D articulated object affordance problem.
A Scalable JPEG Encoder on a Many-Core Array

JPEG is a widely-used image compression algorithm. A 31-core JPEG encoder and a scalable family of JPEG encoders were developed for a fine-grain many-core processor array and are measured on the 32 nm KiloCore chip. These implementations are compared against JPEG implementations on three high-level-language-programmable chip platforms: an Nvidia A100 GPU with an Intel Platinum 8168 (nvJPEG), a TI C66x embedded processor, and an Intel i9-9900 processor (libjpeg-turbo). In addition, an HDL-configurable Xilinx Zynq-7000 FPGA (VISENGI) was compared. All results are scaled to 32nm CMOS, and throughput per area, energy per megapixel encoded, and the comprehensive energy × delay metrics are compared. The KiloCore designs achieve the lowest chip area and the highest normalized throughput per chip area. Among the chips that are programmable by a high-level programming language, the KiloCore achieves up to 4.33×, 31.4×, and 46.4× lower energy dissipation and up to 4.81×, 7,845×, and 14,510× lower energy × delay than the TI, Intel, and Nvidia respectively.
The Correlation between Polymorphism of β Fibrinogen Gene -455 G/A and Serum Fibrinogen Level with The Severity of Coronary Artery Stenosis In Coronary Artery Disease Patient

Background: Now a days coronary artery disease (CAD) becomes major cause of death. One among 7 deaths in America caused by CAD. CAD is an atherosclerosis process, which progresively develops into plaque that will lead to stenosis of coronary artery lumen. Several studies found that high serum fibrinogen level is an independent and significant to the severity of artery coronary stenosis. Serum fibrinogen level determined by genetic factor. Polymorphism of fibrinogen gene β -455 G/A seem plays an important role in plasma fibrinogen level. Although some studies showed a significant correlation between polymorphism and cardiovascular diseases, but some other studies report inversely. Aim. To evaluate the correlation between the polymorphism of fibrinogen gene β -455 G/A and serum fibrinogen level with the severity of artery coronary stenosis. Method: This is an analytic correlative study with prospective approach without comparison. Coronary angiography was performed in catheterization labor in the department of internal medicine, while DNA analysis and PCR done in the department of microbiology in General Hospital dr Muhammad Husin Palembang- Indonesioa, since July 2015 until Agustus 2016. Samples are CAD patient who undergo for coronary angiography and fulfield the criterias. The severity of stenosis in coronary artery determined by Gensini score. This study included 31 patient. Results. Among 31 CAD patients, this study found severe stenosis of coronary artery in 17 patients (53,1%), moderate in 5 patients (15,6%) and mild in 10 patients (31,2%). Genetic analysis showed that serum fibrinogen level was controlled by polymorphism of fibrinogen gene β -455 G/A, concecutively by genotipe AA in 15 patients (48,4%), genotipe GA in 12 patient (38,7%) and by genotipe GG in 4 patients (12,9%). Chi Square test showed a significant correlation between polymorphism gene fibrinogen β -455 G/A and serum fibrinogen level (p=0,039). Spearman’s rho test found no significant correlation between serum fibrinogen level and severity of coronary artery stenosis based on Gensini score (r=0,142; p=0,447). And also this study found no significant correlation between polymorphism gene fibrinogen β -455 G/A with the severity of stenosis in coronary artery (p=0,512). Conclusion. Although this study succeded to prove that serum fibrinogen level was determined by polymorphism fibrinogen gene β -455 G/A, but there are no significant correlations between polymorphism fibrinogen gene β -455 G/A and serum fibrinogen level with severity of coronary artery stenosis in CAD patients. This study suggest to study other candidate gene to look for other cardiac risk beside this fibrinogen. Bangladesh Journal of Medical Science Vol.18(2) 2019 p.379-384
Characterization of viscerofugal neurons in human colon by retrograde tracing and multi-layer immunohistochemistry

Background and Aims Viscerofugal neurons (VFNs) have cell bodies in the myenteric plexus and axons that project to sympathetic prevertebral ganglia. In animals they activate sympathetic motility reflexes and may modulate glucose metabolism and feeding. We used rapid retrograde tracing from colonic nerves to identify VFNs in human colon for the first time, using ex vivo preparations with multi-layer immunohistochemistry. Methods Colonic nerves were identified in isolated preparations of human colon and set up for axonal tracing with biotinamide. After fixation, labeled VFN cell bodies were subjected to multiplexed immunohistochemistry for 12 established nerve cell body markers. Results Biotinamide tracing filled 903 viscerofugal nerve cell bodies (n = 23), most of which (85%) had axons projecting orally before entering colonic nerves. Morphologically, 97% of VFNs were uni-axonal. Of 215 VFNs studied in detail, 89% expressed ChAT, 13% NOS, 13% calbindin, 9% enkephalin, 7% substance P and 0 of 123 VFNs expressed CART. Few VFNs contained calretinin, VIP, 5HT, CGRP, or NPY. VFNs were often surrounded by dense baskets of axonal varicosities, probably reflecting patterns of connectivity; VAChT+ (cholinergic), SP+ and ENK+ varicosities were most abundant around them. Human VFNs were diverse; showing 27 combinations of immunohistochemical markers, 4 morphological types and a wide range of cell body sizes. However, 69% showed chemical coding, axonal projections, soma-dendritic morphology and connectivity similar to enteric excitatory motor neurons. Conclusion Viscerofugal neurons are present in human colon and show very diverse combinations of features. High proportions express ChAT, consistent with cholinergic synaptic outputs onto postganglionic sympathetic neurons in prevertebral ganglia.
An AI Architecture for Power MOS Rds-on-Driven Lifetime Estimation

The components lifetime estimation is one of the main challenge in all engineering process specially in power electronics. The problem involves several domains of interest and is particularly felt, because, the estimation of the residual life with an acceptable degree of confidence, allows to carry out preventive measures in order to avoid the consequences of the malfunction and failure of the device at the end of its life. Considering a Power MOS, the distinctive element for understanding the end of life of this component can be obtained by observing the $Rds_{on}$ curve during its life. The $Rds_{on}$ curve works in an operating range during the correct life cycle, this curve exceeds a certain threshold when the device begins to have the first signs of degradation. The proposed method allows to evaluate the variation of the $Rds_{on}$ by making predictions for understand when the device may stop working well. The method is based on a deep learning model trained with a dataset containing the cycle of life of several Power MOS. The pipeline is based on Artificial Intelligence techniques with regularization of the Jacobian of the gradient, designed to compensate for the inevitable measurement and conversion noises present in the system based on ST MCU. The experiments concern predictions of the $Rds_{on}$ at 10, 15 and 20 steps and allow to obtain a good degree of accuracy for predicting the $\mathbf{RDS}_{-}\mathbf{on}$ at least 20 samples before. This allows to guarantee a preventive intervention when the prediction exceed the threshold considered for the correct operating range. The proposed pipeline allows to robustly characterize the threshold voltage of the device by means of a simple acquisition of voltages and currents at power-on, being able to monitor the evolution of this voltage over time and each time the device is used. The obtained results and the cross-validation performances are very promising and allow us to state that the proposed method is really robust.
Six Leads Are All You Need for Efficient Cardiac Analysis

Electrocardiography (ECG) serves as a noninvasive method of monitoring the electrical activity of the heart by employing electrodes attached to the skin. These electrodes detect the minuscule electrical signals generated by the heart’s activity. A conventional ECG, known as a 12-lead ECG, necessitates the positioning of 12 electrodes across the body to yield a detailed perspective of the heart’s electrical function. Our study introduces an innovative approach to real-time ECG signal classification, using a maximum of six leads, with the aim of reducing the time and resources dedicated to data acquisition and signal processing without compromising accuracy. We introduce a technique for grouping leads and assess the performance of the classification of ECG signals on various leads. Our findings indicate that implementing lead-wise grouping with up to six leads results in a 93.67% reduction in sampling time, a 50% decrease in data size on the acquisition device, and an 84.72% cut in signal processing time, all while experiencing a minimal accuracy decrease of 0.08%. The efficacy of the proposed lead grouping has been assessed through the Kafka real-time platform.
Development of nepheline syenites in rift zones - information from three rift complexes

Occurrences of nepheline syenite in the Gardar and Oslo rift systems in South Greenland and Southeast Norway, respectively, are compared with occurrences of phonolite in the Mont-Dore volcano, the French Massif Central. Intermediate igneous rocks predominate in the two last-named provinces, where nepheline syenite and phonolite are of subordinate importance. MontDore may illustrate surface conditions at the time of formation of the Oslo province. The Gardar province shows a predominance of basaltic lavas and felsic intrusions including large complexes of nepheline syenite. The Gardar and Oslo nepheline syenites are spatially associated with augite syenite (larvikite), the Mont-Dore phonolites with corresponding trachyandesite/trachyte. These rocks appear to have developed from mantle-derived basic magmas in deep magma chambers with little crustal contamination. The early stages in the evolution from augite syenite to nepheline syenite and from trachyandesite to phonolite are characterized by decreasing contents of REE and weak or positive Eu anomalies, the more evolved stages by increasing contents of REE and by distinct negative Eu anomalies.
VR and Sensors in Alleviating Loneliness

This research proposes a novel combination of behavioural-tracking sensors and immersive virtual reality in alleviating chronic loneliness. Various limitations have been identified in current approaches, prompting more advanced techniques that efficiently target loneliness at an individual patient level. An affective intelligence approach has been proposed to maximise cognitive behavioural therapy outcomes in treatment, combining technology that is successful in related work.
Beyond Scores: A Novel Method for Predicting Student Performance Based on Rank and Positional Embedding

Predicting student performance based on continuous assessment scores is an important task in educational data mining (EDM). The task aims to provide personalized feedback and intervention for students at risk of failing the course or dropping out. In this paper, we examine the limitations of using raw scores as input features for predicting student outcomes, as raw scores can be biased and sensitive to the variation of assignment difficulty. We propose a novel approach that uses rank instead of score as the input feature for predicting student performance. Rank is a relative measure that reflects the performance of a student compared to other students in the same course or cohort, which can reduce bias caused by different score distributions and assignment difficulties, and capture the relative position and improvement of each student. In this paper, we use the idea of positional embedding to encode rank into a dense representation for prediction models. Positional encoding assigns a vector representation to each rank based on its ordinal position in a sequence. We apply positional encoding to various recurrent neural network (RNN) models and other machine learning models, such as logistic regression and support vector machines. We compare their performance on public datasets of student assessment scores. Our results show that using rank with positional encoding can significantly improve the prediction accuracy and reliability of RNN models and their variants.