Miracle-dz/UniFAR-FTUs huggingface dataset:
The state of polymorphism of genes affecting the meat quality in micropopulations of meat simmentals

A comparative study of the biological characteristics of the heifers Bredy meat type of two populations located in Russia and Kazakhstan was carried out to determine the state of genes associated with the meat quality in the genotypeCAPN1, GDF5, TG5, BGL. In genotyping, we used the real-time PCR method using oligonucleotide primers (Gen Bank), for each primer individually in the corresponding sequences. Studies for improve breeding by innovative methods revealed the frequencies of genotypes and alleles for marker genes CAPN1, TG5, BGL and GDF5, which are related to meat quality indicators, a certain displacement in the genotypes of the compared populations of the Bredy meat type of Kazakhstan and Russia according to the CAPN1 gene (χ2 = 8.52) and the TG5 gene (χ2 = 4.73). The genotyping result of animals from LLC “Breeding plant Bredy” were analyzed from the point of view of attributing carriers of different genotypes to the offspring of bulls-producers Fakir, Kust and Chizhik, in order to determine the producer giving offspring with predictably high nutritional and biotechnological properties of beef. A comparison of the carriers of the identified genotypes of the studied genes by the characteristics used in the evaluation of young animals by their own productivity did not give significant results, however, showed trends by which scientific research can be directed. An assessment of the bulls-producers of the successors of the different line of meat simmentals on the quality of heifers – daughters showed that the largest comprehensive index was set for the bull-producer Bush 39046 – 102.7, which was recognized as an improver. The assignment of all, without exception, heifers of different groups, evaluated bulls-producers, to the highest class elite-record, indicates the value of all the studied genotypes.
High perturbations of Choquard equations with critical reaction and variable growth

This paper deals with the mathematical analysis of solutions for a new class of Choquard equations. The main features of the problem studied in this paper are the following: (i) the equation is driven by a differential operator with variable exponent; (ii) the Choquard term contains a nonstandard potential with double variable growth; and (iii) the lack of compactness of the reaction, which is generated by a critical nonlinearity. The main result establishes the existence of infinitely many solutions in the case of high perturbations of the source term. The proof combines variational and analytic methods, including the Hardy-Littlewood-Sobolev inequality for variable exponents and the concentration-compactness principle for problems with variable growth.
Inequality of Opportunity and Degree of Human Development: Evidence from Tunisia

There are many socio-economic factors beyond the individual control that can affect human development indicators. In this setting, this paper aims to examine the effects and evolution of unequal opportunities on the distribution of human development indicators embodied by monetary well-being (consumption) and education in Tunisia for the period 2005-2010. We used parametric and non-parametric approach in addition to Dissimilarity-Index and Shapley’s Decomposition to identify most important factors explaining inequality of chances in Tunisia. We found that Father’s education, residence area, and connection to drinking water appears to be the most important background variables affecting well-being profile. However, child’s sex appears to be the most important determinant of the accessibility to education. Inequality of opportunity in consumption and education persists and tends to increase over time which is undesirable for the country. As an economic implication of our results, policy makers must make appropriate policies to reduce intergenerational transmission of parental background and sex discrimination and to overcome traps of inequality for future generations
Three Logistic Predictive Models for the Prediction of Mortality and Major Pulmonary Complications after Cardiac Surgery

Background and Objectives: Pulmonary complications are a leading cause of morbidity after cardiac surgery. The aim of this study was to develop models to predict postoperative lung dysfunction and mortality. Materials and Methods: This was a single-center, observational, retrospective study. We retrospectively analyzed the data of 11,285 adult patients who underwent all types of cardiac surgery from 2003 to 2015. We developed logistic predictive models for in-hospital mortality, postoperative pulmonary complications occurring in the intensive care unit, and postoperative non-invasive mechanical ventilation when clinically indicated. Results: In the “preoperative model” predictors for mortality were advanced age (p < 0.001), New York Heart Association (NYHA) class (p < 0.001) and emergent surgery (p = 0.036); predictors for non-invasive mechanical ventilation were advanced age (p < 0.001), low ejection fraction (p = 0.023), higher body mass index (p < 0.001) and preoperative renal failure (p = 0.043); predictors for postoperative pulmonary complications were preoperative chronic obstructive pulmonary disease (p = 0.007), preoperative kidney injury (p < 0.001) and NYHA class (p = 0.033). In the “surgery model” predictors for mortality were intraoperative inotropes (p = 0.003) and intraoperative intra-aortic balloon pump (p < 0.001), which also predicted the incidence of postoperative pulmonary complications. There were no specific variables in the surgery model predicting the use of non-invasive mechanical ventilation. In the “intensive care unit model”, predictors for mortality were postoperative kidney injury (p < 0.001), tracheostomy (p < 0.001), inotropes (p = 0.029) and PaO2/FiO2 ratio at discharge (p = 0.028); predictors for non-invasive mechanical ventilation were kidney injury (p < 0.001), inotropes (p < 0.001), blood transfusions (p < 0.001) and PaO2/FiO2 ratio at the discharge (p < 0.001). Conclusions: In this retrospective study, we identified the preoperative, intraoperative and postoperative characteristics associated with mortality and complications following cardiac surgery.
VMShield: Memory Introspection-Based Malware Detection to Secure Cloud-Based Services Against Stealthy Attacks

With the rapid evolution of the industrial Internet, cloud service has emerged as a next-generation industrial standard that has the potential to revolutionize and transform the enterprise industry. In recent years, numerous enterprises have acknowledged the benefits of cloud-based service models. However, the security issues are a major concern, such as stealthy malware attacks against virtual domains. In this article, we propose an introspection based security approach, called VMShield for securing virtual domains in a cloud based service platform, which is designed to detect malware in cloud infrastructure. VMShield performs virtual memory introspection from the hypervisor (trusted-domain) to collect the run-time behavior of processes, making it impossible for the malware to evade the security tool. The use of introspection makes the proposed approach a better choice over traditional static and dynamic state-of-the-art techniques which fail to detect stealthy attacks. The VMShield extracts the system call features using Bag of n-gram approach and selects important features using the meta-heuristic algorithm, binary particle swarm optimization. Random Forest (RF) classifier is used to classify the monitored programs into benign and malign processes, making it capable of detecting the variants of malware thus, an advantage over the typical signature-matching approach. The University of New Mexico (UNM) Dataset and Bare cloud Dataset (University of California) has been used for the demonstration and validation of VMShield. The results prove that VMShield achieves a higher attack detection rate and reduced storage compared to previously proposed techniques.
The Predictive Value of Osteocalcin, Granulin, Cathepsin K and Some Other Biomarkers in Women with Premature Ovarian Failure

Background: Premature ovarian failure (POF), often and misleadingly referred to as ‘premature menopause’,is defined as a loss of ovarian activity before the age of 40 years and is characterized by irregular or absentperiods and reduced fertility. Symptoms include those associated with the natural menopause (night sweatsand vaginal dryness), and with the long-term adverse effects of estrogen deficiency (osteoporosis andcardiovascular disease): the latter is believed to explain the shorter life expectancy associated with POF.Aim: To determinethe predictive value of serum osteocalcin(OC), granulin(GRN), cathepsin k (CTK),vitamin D, parathyroid hormones (PTH), calcium and phosphrus as biomarkers for POF.Method: Sixty (60) women with idiopathic POF with thirty (30) women as control groups were included inthe study. Baseline investigation in all subjects included serum Osteocalcin(OC), granulin(GRN), cathepsink (CTK), vitamin D, parathyroid hormones (PTH), calcium and phosphrus levels were estimated using theappropriate assays for each.Results: The mean serum levels of Osteocalcin, Ganulin,Parathyroid hormones,vitamin D and phosphorus,were significantly higher in women with POF,when compared to healthy controls (P=<0.05). However, meanserum levels of cathepsin k and calcium in POF group were non significant differences,when compared tohealthy controls.Conclusion: Osteocalcin and granulin serum levels may be used as new biomarker for the diagnosis ofpremature ovarian failure.
Predicting golf ball launch characteristics using iron clubhead presentation variables and the influence of mishits

In golf, it is well understood that the interaction between the clubhead and ball determines the initial ball launch conditions. Specific knowledge regarding these relationships for iron clubs, particularly when clubhead and turf interactions are considered, would be both novel and of benefit to practitioners. Linear regression analysis was used to determine relationships between selected clubhead presentation and shot outcome variables for a sample of 1127 ‘5-iron’ shots hit from natural turf by 96 golfers. As expected, clubhead speed was the most significant predictor of ball speed, with obliquity of impact and eccentricity of the impact location making smaller, yet statistically significant contributions. Marginally ‘fat’ strikes, whereby the leading edge of the clubhead was only slightly beneath the ground at impact, appeared to have a lesser effect than expected in terms of ball speed. Effective loft was found to be the strongest predictor of vertical launch angle, whilst clubhead speed and spin loft had the greatest influence in the model for predicting total spin; inclusion of ‘thin’ strikes (i.e. those struck with the leading edge) appeared to create a non-linear element to these models and consequently overestimated the influence of vertical impact location in both cases. These findings suggest that determination of impact location, particularly for instances whereby ball contact is not wholly on the club face, is critical in research concerning irons. Overall, this study makes an original contribution to the understanding of 5-iron shot outcomes based on clubhead presentation characteristics.
Microwave-assisted, facile route to 1H-pyrazolo[3,4-b]quinolines

Aromatic aldehydes have been reported to react with 5-anilinopyrazoles in the presence of ZnCl2 to give the corresponding benzylidenopyrazoles. In this paper evidence is given that the corresponding products are, in fact, 1Hpyrazolo[3,4-b]quinolines. This observation opens a novel route to these compounds. They show a blue emission in the solid state and, therefore, they are useful blue luminophores for electroluminescent devices. The synthetic procedure reported in the literature was significantly modified and improved by application of microwave heating. In our modified synthesis the reaction time was reduced from the usual 5 to 8 h to 5 to 7 min and the reaction products were formed without contamination.
Nurse’s Knowledge and Accuracy in Using Comfort Scale

More than 30% of critical patients have significant pain while resting and more than 50% of patients experience significant pain during the routine care process. Pain is difficult to measure and treat in patients with reduced awareness because direct reports from patients are important in the assessment. Assessment of pain in patients with decreased consciousness can use the Comfort Scale. This research is to describe nurse’s knowledge in pain assessment in patient using comfort scale in Muhammadiyah Hospital. This study uses a descriptive method with a survey approach. The sample in this study were 84 nurses taken in total sampling. Instrument in the form of a questionnaire sheet. Data was analyzed using descriptive analysis. Most of the nurses at PKU Muhammadiyah Sruweng Hospital were 30 years old (79.8%), female sex (79.8%), Diploma education (88.1%), and length of employment 5 years (73.8%). Knowledge of nurses in pain assessment in patients using comfort scale in Muhammadiyah Hospital was in a sufficient category (66.7%). Pain assessment uses a comfort scale in patients in Muhammadiyah Hospital in the inappropriate category (77.4%). Nurses' knowledge in pain assessment in sufficient categories while pain assessment uses comfort scale in inappropriate categories. Future research can be further developed by examining other factors that influence the use of comfort scale gauges.
Hamiltonian‐driven adaptive dynamic programming for mixed H2/H∞ performance using sum‐of‐squares

In this article, the mixed H2/H∞ performance optimization is first formulated as a nonzero‐sum game, of which the sufficient condition guaranteeing the existence of the Nash equilibrium is derived using the Hamilton–Jacobi (HJ) theory. Then, Hamiltonian‐driven inequalities are presented to evaluate the H2 and H∞ performances. Using this Hamiltonian‐inequality driven approach, the coupled HJ equations arising from finding the Nash equilibrium are relaxed to the HJ inequality constraints. A novel mixed policy iteration (PI) algorithm is developed that uses sum‐of‐squares (SOS) program in policy evaluation step, and consists of an H2 performance improvement step and an H∞ performance guarantee step. This constrained‐driven approach allows us to present a PI algorithm that takes into account both robustness and performance objectives. Finally, a numerical simulation is carried out to highlight the efficacy of the proposed framework.
The influence of cavitation processing on biotechnological aspects of feed application

The problem using production waste rationally is a fundamental one for our country. Waste agro-industrial complex is characterized by a high content of carbohydrates, proteins and fat, which makes them indispensable when balancing rations. In this regard, the method is about obtaining fodder product on the basis of cellulose-containing wastes enriched with zeolite powder. The method is based on ultrasonic treatment of joint products (bran) and the mineral zeolite. The efficiency of the use of the product lies in poultry feeding.
URLLC-Oriented Joint Power Control and Resource Allocation in UAV-Assisted Networks

Recently, ultrareliable and low-latency communication (URLLC) has attracted a significant interest for mission-critical applications in future wireless communication systems. Achieving strict requirements of latency and reliability for URLLC with a fixed infrastructure is challenging, and unmanned aerial vehicles (UAVs) have been deemed as promising enablers to handle this issue due to its salient attributes, such as high maneuverability, flexible deployment, and high probability of line-of-sight links. This article investigates a novel UAV-assisted URLLC service system, where the blocklength of channel codes is finite in Internet-of-Things (IoT) networks. Considering the limited energy of IoT devices, the average uplink transmit power of the IoT devices are minimized by jointly optimizing the device scheduling and association, power control and resource allocation, as well as UAV deployment. The formulated problem is a mixed-integer nonconvex optimization problem because of the finite blocklength regime. To tackle the problem, we derive the approximation of the achievable rate and propose an effective iteration algorithm by applying the block coordinate descent (BCD) and Lagrange dual decomposition techniques. Furthermore, the convergence of our proposed algorithm is analyzed and illustrated. The minimum average transmit power of IoT devices is calculated with a different resource allocation scheme. Simulation results demonstrate that our proposed iterative algorithm can obtain a performance gain of 15%–20% in terms of the average transmit power for URLLC. Moreover, compared with the average bandwidth allocation scheme, our proposed algorithm can get a stable minimum as the total bandwidth increases.
Effect of Estrus Induction on Blood Biochemical and Mineral Profiles and Fertility Rate in Retained Fetal Membranes Affected and Normally Calved Riverine Buffaloes

Background: Calving to conception interval is abnormally extended by the occurrence of retained fetal membranes (RFM) by altering the blood biochemical and mineral milieu in cows. Hence this experiment was conducted in RFM affected and normally calved (NC) buffaloes by inducing estrus with CIDR plus PGF2α protocol to study the blood biochemical and mineral profiles and to correlate them with fertility rate. Methods: Buffaloes (n=64) at 45-60 days postpartum including 32 treated for RFM and 32 NC from field were equally divided into groups I and II and groups III and IV, respectively. Buffaloes of groups I and III were initially dewormed and administered 35-50 g mineral mixture daily orally for 15 days in the concentrate feed. Then, buffaloes of all the groups were treated with CIDR plus PGF2α. After CIDR removal, all the buffaloes were artificially inseminated twice at 48 and 72 hrs. Blood was collected during different stages of treatment from all the buffaloes to assess the blood biochemical and mineral status. The animals returned to estrus following FTAI were again inseminated during subsequent estrus. Pregnancy diagnosis was done at 60 days post-AI and conception rates for induced estrus and overall of two cycles were calculated.Result: In all the groups, blood glucose, total protein, triglycerides, cholesterol and phosphorus levels increased from the time of selection to 10 days post-AI. There was an altered calcium phosphorus ratio in RFM affected buffaloes (1:1) at the time of selection. CIDR plus PGF2α protocol influenced the blood biochemical constituents and brought the calcium and phosphorus ratio as 2:1 and improved the fertility in riverine buffaloes. The overall conception rate was 62.50, 37.50, 87.50 and 75.00 per cent, in group I, II, III and IV buffaloes, respectively.
Emotion Detection for Conversations Based on Reinforcement Learning Framework

In this article, we propose a novel reinforcement learning network that keeps track of the gradual emotional changes from every utterance throughout the conversation and uses this information for each utterance’s emotion detection. Concretely, we first establish an agent and, then, utilize sliding windows to extract the accumulated emotional information before the current utterance. We define the concatenation of accumulated emotional information and the contextual information as the state of the reinforcement learning framework. The action of the established agent is formulated as the emotional label of the current utterance. On this basis, we formulate the progressive emotional interaction process throughout the conversation as a sequential decision problem and solve it with the reinforcement learning framework. Detailed evaluations on the published multimodal MELD dataset demonstrate the effectiveness of our approach.
Development of Decision Support Software for Deep Learning-Based Automated Retinal Disease Screening Using Relatively Limited Fundus Photograph Data

Purpose—This study was conducted to develop an automated detection algorithm for screening fundus abnormalities, including age-related macular degeneration (AMD), diabetic retinopathy (DR), epiretinal membrane (ERM), retinal vascular occlusion (RVO), and suspected glaucoma among health screening program participants. Methods—The development dataset consisted of 43,221 retinal fundus photographs (from 25,564 participants, mean age 53.38 ± 10.97 years, female 39.0%) from a health screening program and patients of the Kangbuk Samsung Hospital Ophthalmology Department from 2006 to 2017. We evaluated our screening algorithm on independent validation datasets. Five separate one-versus-rest (OVR) classification algorithms based on deep convolutional neural networks (CNNs) were trained to detect AMD, ERM, DR, RVO, and suspected glaucoma. The ground truth for both development and validation datasets was graded at least two times by three ophthalmologists. The area under the receiver operating characteristic curve (AUC), sensitivity, and specificity were calculated for each disease, as well as their macro-averages. Results—For the internal validation dataset, the average sensitivity was 0.9098 (95% confidence interval (CI), 0.8660–0.9536), the average specificity was 0.9079 (95% CI, 0.8576–0.9582), and the overall accuracy was 0.9092 (95% CI, 0.8769–0.9415). For the external validation dataset consisting of 1698 images, the average of the AUCs was 0.9025 (95% CI, 0.8671–0.9379). Conclusions—Our algorithm had high sensitivity and specificity for detecting major fundus abnormalities. Our study will facilitate expansion of the applications of deep learning-based computer-aided diagnostic decision support tools in actual clinical settings. Further research is needed to improved generalization for this algorithm.
Modelization of the Personal Learning Environment in the Moroccan Higher Education

Any research focusing on the teaching-learning process must focus on the learner, by mobilizing the various devices to facilitate and optimize learning. In this context, we introduce the integration of educational technologies into a personal learning environment (PLE). The PLE has significant potential for learning; namely self-construction and self-management of knowledge. According to Attwel (2007b), the development and improvement of PLE will lead to drastic changes in the way we use educational technology, as well as in the organization and ethics of education. With the present contribution, we try to modelize the PLE of students within institutions of higher education in Morocco. Based on data from a questionnaire put online using google forms, we have found that digital devices are ubiquitous in the daily lives of learners, but their practices are limited to distracting uses, and that the institutional framework remains more basic to manage their learning. The purpose of this study is to develop learning autonomy and to improve the way of using technologies through our student’s conception of the PLE.