Miracle-dz/UniFAR-FTUs huggingface dataset:
Routine or Rare Activity? A Quantitative Assessment of Parliamentary Scrutiny in the European Semester

The European Semester is an EU procedure, designed to facilitate coordination between national and EU actors in planning and implementing economic and fiscal policies and contribute to sustained economic convergence and employment in the EU. Scholars have highlighted this procedure as a crucial area of EU politics for national parliaments since its introduction in 2011. However, national parliaments participate differently in the European Semester. This article investigates which factors (institutional, political, economic) are more likely to intensify parliamentary engagement at the national stage of the procedure, based on a comparative quantitative analysis of parliamentary scrutiny activities across 35 parliaments/chambers in the EU over the 2014–2017 period. The article offers new insights about prospects for greater parliamentary accountability in the European Semester in practice.
Potential of hydroponic barley in rabbit diets: effect on productive performance, nutrient digestibility, microbiological and physiological responses

DOI: 10.21608/svu.2021. 67695.1114 Received: March 13, 2021 Accepted: June 12, 2021 Published: August 10, 2021 *Corresponding Author: Ahmed A.A. abdel-Wareth E-mail: a.wareth@agr.svu. edu.eg Citation: Mohamed et al., Potential of Hydroponic Barley in Rabbit Diets: Effect on Productive Performance, Nutrient Digestibility, Microbiological and Physiological Responses. SVU-IJVS 2021, 4 (3): 12-23. Copyright: © Mohamed et al. This is an open access article distributed under the terms of the creative common attribution license, which permits unrestricted use, distribution and reproduction in any medium provided the original author and source are created. Competing interest: The authors have declared that no competing interest exists. Abstract
The Proximate Analysis, Phytochemical Screening, Antioxidant Activity and Mineral Composition of Momordica charantia and Ocimum gratissimum Leaf Powder

Aim: This study aims to evaluate and characterise the Momordica charantia and Ocimum gratissimum leaf powder. Methodology: The quantitative analyses for proximate, phytochemicals, minerals, and antioxidant activities of Momordica charantia and Ocimum gratissimum leaf powder were carried out using standard procedures. Results: The result of the proximate analysis showed that both plants contain an appreciable amount of moisture, ash, crude fibre, crude fat, crude protein and nitrogen-free extract content, with M. charantia leaf powder having higher moisture (5.49 ± 0.03%) content than O. gratissimum leaf powder (5.02 ± 0.01%) (P < 0.05). Ocimum gratissimum had higher crude fibre content (25.03 ± 0.25%) than M. charantia leaf powder (20.86 ± 0.12%) (P < 0.05). The protein, ash, crude fat and nitrogen-free extract contents were not significantly different (p> 0.05) between the two leaf powders. The phytochemical screening revealed the presence of tannin, flavonoid, phenol, alkaloids, saponin and phytate. Except for alkaloid content, M. charantia leaf powder had higher tannins (1.20±0.02 mg/g), flavonoids (225.64±14.61 mg/g), phenol (21.04±0.57 mg/g), saponins (57.36±0.08 mg/g) and phytate (7.79±0.25 mg/g) content compared to O. gratissimum leaf powder. The antioxidant activity of the plants showed that M. charantia leaf powder possessed higher DPPH scavenging free radical activity than that of O. gratissimum leaf powder. The mineral constituents revealed that both plants contain a significant amount of zinc, calcium, iron and phosphorus, with M. charantia leaf powder having higher zinc and calcium concentration than O. gratissimum leaf powder (p < 0.05). In conclusion, this study shows that the leaf of M. charantia and O. gratissimum plants are rich sources of nutrients and phytochemicals and can be used as natural feed additives in animal nutrition.
Phytochemical Constituents of Carrot (Daucus carota) Fruit Juice and its Hepatoprotective Property in CCl4-Induced Liver Cirrhotic Rats

Aim: This study evaluated the phytochemical constituents of Carrot fruit juice (CFJ) and its hepatoprotective property in CCl4-induced liver cirrhotic rats. Study Design: Sixty male rats of weight ranging from 150-180 g were completely randomized into six groups. All rats were administered 0.5 ml/kg CCl4 subcutaneously thrice weekly except groups 1, 2, 3, and 4 while rats in groups 3 and 6 and groups 4 and 5 orally received 2.5 and 5.0 ml/kg of CFJ on daily basis for 12 weeks. Results: The preliminary qualitative phytochemical screening of extract revealed the presence of alkaloids, flavonoids, cardiac glycosides, carbohydrate, saponin, phenolic compound and tannins. The extract treated groups significantly revealed an increase in liver cirrhotic emaciated body weight and reduction in the liver index, a reversal of liver marker enzymes activities, an increase in enzymic and non-enzymic antioxidants with a decrease in malondialdehyde level reduction in C-reactive protein, interleukin-6, alpha-fetoprotein, and carcinoembryonic antigen. Exposure of animal to CCl4 induces oxidative stress, increases the generation of reactive oxygen species and myeloperoxidase activity, and reduces cell viability but was reversed by the CFJ. Conclusion: The result showed that CFJ is a promising therapeutic option for treating liver failure.
Hierarchical Intelligent Real-Time Optimal Control for LLRF Using Time Series Machine Learning Methods and Transfer Learning

Machine learning (ML) is under study for Low-level RF (LLRF) control systems to keep the voltage and phase of superconducting radio-frequency (SRF) cavities stable within 0.01 degree in phase and 0.01% amplitude as constraints. Model predictive control (MPC) uses an optimization algorithm offline to minimize a cost function with constraints on the states and control input. The surrogate model optimally controls the cavities online. Time series deep ML structures including recurrent neural network (RNN) and long shortterm memory (LSTM) can model the control input of MPC and dynamics of LLRF as a surrogate model. When the predicted states diverge from the measured states more than a threshold at each time step, the states’ measurements from the cavity fine-tune the surrogate model with transfer learning (TL). MPC does the optimization offline again with the updated surrogate model, and transfer learning fine-tunes the surrogate model with the new data from the optimal control inputs. The surrogate model provides us with a computationally faster and accurate modeling of MPC and LLRF, which in turn results in a more stable control system.
Assessment of Environmental Impact and Economic Viability of Domestic Biogas Plant Technology in Bangladesh

The study investigated the distinct environmental impacts and economic viability of domestic biogas technology in the countryside of Bangladesh. The study was carried out by a survey through personal interviews with biogas users. Seventy households were selected purposively and interviews were conducted through semi-structured questionnaires. The study mainly highlighted the potential reduction of greenhouse gas (GHG) emission and economic benefits of biogas utilization which were evaluated considering the substitution of traditional biomass fuels, by saving Liquefied Petroleum Gas (LPG) and cost of chemical fertilizer, and carbon trading. The economic benefits are addressed using some well-known economic indicators like Net Present Value (NPV), Payback Period (PBP), and Benefit-Cost Ratio (BCR). The results of the study revealed that a small-scale household anaerobic cow dung biogas digester not only exhibited the potential to cut carbon emissions on average by about 7.8 tons of CO2 equivalents yearly, but it also demonstrated the economic feasibility of doing so as the value of NPV and BCR was positive. This study recommends that the government approach, awareness program, and continuous and proper performing of the biogas technology are needed to intensify the multiples environmental benefits of the technology.
Role of herbs for elevating immunity against SARS-CoV-2: a concise review

COVID-19 has emerged as a dreadful pandemic caused by the virus SARS-CoV-2. Though the number of patients recovering from infection is encouraging, sturdy cure is still being researched upon and the effective vaccines are yet to be rigidly resolute. COVID-19 has so far instigated a massive loss of lives globally and even the countries with the most advanced healthcare systems have come under its grasp. Health experts suggest in such case “Prevention is better than cure” which includes an appropriate daily lifestyle and a rugged immune system that could help mankind surmount this peril. This review highlights the importance of influential herbs and their medicinal significance. Biomedical articles were explored from PubMed, Google Scholar, Web of Science for the period of 2010-2021. Guidelines from the Ministry of Ayush (India) were also considered. The Ayurveda does not mention any cure for the novel coronavirus; however, it emphasizes the means of boosting one’s immunity. Accordingly, this article highlights some of the role of prevalent Ayurvedic herbs in promoting immunity for combating the novel coronavirus. The herbs in combination with drugs could be utilized for the sake of curtailing the side effects as well as the malefic repercussions of strong synthetic drugs used for treating COVID-19 patients, which would be a paramount leap in the field of Ayurveda as well as western-style medicine. However, the beneficial effects of these traditional medicines and their clinical trials remained to be known. We reviewed the latest updates on traditional medicines proposed for promoting immunity towards COVID-19.
SMT-Based Safety Verification of Data-Aware Processes under Ontologies (Preliminary Results)

In the context of veriﬁcation of data-aware processes, a formal approach based on satisﬁability modulo theories (SMT) has been considered to verify parameterised safety properties of so-called artifact-centric systems . This approach requires a combination of model-theoretic notions and algorithmic techniques based on backward reachability . We introduce here a variant of one of the most investigated models in this spectrum, namely simple artifact systems ( SASs ), where, instead of managing a database, we operate over a description logic (DL) ontology expressed in (a slight extension of) RDFS. This DL, enjoying suitable model-theoretic properties, allows us to deﬁne DL-based SASs to which backward reachability can still be applied, leading to decidability in PSpace of the corresponding safety problems.
Anthropometric indices as novel markers of risk in type 2 diabetes mellitus (T2DM) among Nigerian adults in Zamfara State

Body mass index (BMI) has traditionally been used as an indicator of body size measure and composition. Although, other measures of adiposity of the abdomen such as waist circumference (WC), waist-hip ratio (WHR), neck circumference (NC) have been suggested as being superior to BMI in predicting disease outcome. This study was designed to compare different anthropometric variables in term of their ability to predict type 2 diabetes mellitus (T2DM). This was a case-control study in 240 participants involving 120 verified T2DM cases and 120 non-diabetics as control. Age, gender and anthropometric data were collected from each participant. Logistic regression models were used with areas under the receiver operating characteristic (AROC) curve to compare the variables predictive statistics. The AROC of WHR to identify T2DM patients was 0.678 (P<0.05), with sensitivity 62.5% of and specificity of 60.8%. The AROC for average arm circumference (AAC) model is 0.649 with sensitivity of 55.8% followed by BMI model (AROC 0.635) and WC model (AROC 0.600) (P<0.05). Hip circumference (HC) (AROC 0.508) and NC (AROC 0.492) models were not significant predictors of T2DM. Subjects of ≥60 years, AAC value ≥32.6 cm, BMI value ≥ 30 kg/m2, and WHR value ≥ 0.93 were at significantly (P<0.05) higher odds of developing T2DM than lower subjects with lower values. There were no significant differences (P>0.05) in the mean HC and NC values between the diabetic and non-diabetic subjects. The non-diabetic subjects have significantly (P>0.05) higher mean height value than the diabetic subjects. Measures of generalized and central obesity were significantly associated with increased risk of developing T2DM. This study revealed that WHR can predict type 2 diabetes mellitus risk more accurately than other anthropometric measures and can thus be helpful in predicting patients with future occurrence of diabetes and providing necessary interventions
Preliminary Study on Water Quality and Heteropterans Diversity in a Semi-Urban Stream (Central Region of Cameroon)

A study was conducted in the Konglo stream for six months to make an inventory of aquatic heteroptera, following a monthly sampling frequency. Some hydrological and physicochemical parameters such as water width, current velocity, and water flow, water temperature and pH, electrical conductivity, dissolved oxygen, total hardness, phosphates, nitrates, and ammonia were measured according to standard methods. For an inventory of the heteropterans, the multihabitat approach was used during sampling, but only heteropterans representing 3.15 % of total abundance are considered in this study. The hydrological variables were different in each station. The water width and flow were increased from upstream to downstream. The results showed that pH, total hardness, nitrites, phosphates, and ammonia values ​​were weak and no significant differences were observed. Among physicochemical variables, only dissolved oxygen and electrical conductivity were different between upstream and downstream. The conductivity increased from upstream to downstream while the dissolved oxygen was very low downstream. 62 individuals were collected and counted belonging to 11 taxa, the most abundant being Ranatra linearis. The other taxa such as Anisops sp. , Aphelocheirus aestivalis, Gerris sp. , Gerridae Nd. , Hydrometra sp. , Ilyocoris cimicoides, Naucoris sp. , Nepa sp. , Notonectidae Nd. , and Velia sp. were poorly represented. High abundance was recorded at the upstream (38 individuals), but the taxonomic richness (3 taxa) and diversity (0.24 bits/ind) remain low, unlike the stations located downstream (7 taxa and 1.82 bits/ind).
Prediction breast cancer risk: Performance analysis data mining techniques

Article type: Research Introduction: Early detection breast cancer Causes it most curable cancer in among other types of cancer, early detection and accurate examination for breast cancer ensures an extended survival rate of the patients. Risk factors are an important parameter in breast cancer has an important effect on breast cancer. Data mining techniques have a growing reputation in the medical field because of high predictive capability and useful classification. These methods can help practitioners to develop tools that allow detecting the early stages of breast cancer.
Unusual thermal resistance of spores of mesophilic fungi

Thermophilic fungi are well-known for their ability to grow at high temperatures of 50–60oC. However, our previous research demonstrated the exceptional thermal resistant capability of the spores of some mesophilic fungi. These fungi, isolated from leaf litters of forests that experience frequent ground fires, were resistant to dry heat at 100–115oC. To determine whether these high thermal resistant spores are unique to fungi in flammable forests, we screened leaf endophytes of trees of a mangrove forest that rarely experience ground fire due to its inundated forest floor. Of the 129 endophyte isolates tested, the spores (conidia/ascospores) of 27 and 13 isolates survived an exposure to dry heat at 100oC for 2 hrs and 4 hrs respectively. The ascospores of Chaetomium globosum isolated from the leaves of Rhizophora stylosa survived an exposure to 100oC for 10 h. Presence of melanin synthesis inhibitor reduced the thermal resistance in this fungus suggesting that melanin plays a role in the thermal protection.
Optimized Extraction, Microencapsulation, and Stability of Anthocyanins

1Postgraduate College, Campus Cordoba. Postgraduate in Sustainable Agrifood Innovation, Km 348 carretera Córdoba-Veracruz, 94946, Amatlán de los Reyes, Veracruz, Mexico 2National Institute of Forestry, Agriculture and Livestock Research, Experimetal Field Centro Altos de Jalisco, Km 8 carretera Tepatitlán-Lagos de Moreno, Tepatitlán de Morelos, CP 47600 Jalisco, Mexico 3Center for Research and Advanced Studies of the National Polytechnic Institute, Campus Querétaro, Libramiento Norponiente No. 2000, Fraccionamiento Real de Juriquilla, CP 76230 Santiago de Querétaro, Querétaro, Mexico 4Technological Institute of Tlajomulco, Jalisco, Agri-Food processes pilot plant, Km 10 carr. A San Miguel, Cuyutlán, Tlajomulco de Zúñiga, CP 45640 Jalisco, Mexico
Diversity of non-symbiotic nitrogen-fixing bacteria and their potential in andisols affected by the eruption of Mount Sinabung, North Sumatra, Indonesia

Abstract. Sembiribg M, Sabrina T. 2021. Diversity of non-symbiotic nitrogen-fixing bacteria and their potential in andisols affected by the eruption of Mount Sinabung, North Sumatra, Indonesia. Biodiversitas 22: 3539-3544. Nitrogen is the main macro-nutrient that is very important for plant growth. Nitrogen is absorbed by plants in the form of NO3-or NH4+ ions from the soil. The andisols affected by the eruption of Mount Sinabung alter the chemical, physical and biological characteristics of the soil. As a result, the population of beneficial microbes in the soil decreased, so soil fertility also decreased. The aim of this research is to determine the diversity of nitrogen-fixing microbes in andisol soil affected by the Mt. Sinabung eruption. The soil samples used in this research were collected from andisols affected by the eruption of Mount Sinabung. The isolation of non-symbiotic nitrogen-fixing bacteria was carried out using a nitrogen-free Jensen medium. The results showed that five non symbiotic N-fixing bacteria can increase the N content in andisols affected by Mount Sinabung eruption. Enterobacter cloacae can increase soil N by 111.76% as compared to without microbial application.
RECOGNITION OF BUMBLEBEE SPECIES BY THEIR BUZZING SOUND

The goal of our work is to help people to automatically identify the species and worker/queen type of bumblebee based on their recorded buzzing. Many recent studies of insect and bird classification based on their sound have been published, but there is no thorough study that deals with the complex nature of buzzing sound characteristic of bumblebees. In this paper, a database of recorded buzzings of eleven species were preprocessed and segmented into a series of sound samples. Then we applied J48, MLP and SVM supervised classification algorithms on some predetermined sets of feature vectors. For five species the recognition rate was above 80% and for other six species it was above 60%. At the end we consider how to further improve the results.
Perturbation of the mucosa-associated anaerobic gut microbiota in streptozotocin-induced diabetic rats

Our aim was to map the gut region-specific diﬀerences of the mucosa-associated microbiome distribution in a streptozotocin-induced diabetic rat model. Tissue samples from the duodenum, ileum and colon were collected 10 weeks after the onset of hyperglycaemia to analyse the mucosa-associated microbiota using next-generation DNA sequencing. Striking diﬀerences were observed in the mucosa-associated microbiota of the duodenum between diabetic and control rats. A significant invasion of the aerobic genus Mycoplasma was apparent in diabetes, and the abundance of the anaerobic phylum Firmicutes decreased massively. It is noteworthy that insulin treatment eliminated the Mycoplasma invasion in the duodenum and apparently restored the anaerobic environment in the mucosa. In the ileum the abundance of the phylum Firmicutes increased in the diabetic samples. Although the proportion of the phylum Proteobacteria decreased moderately, its composition changed significantly, and insulin treatment induced only minor alterations. In the diabetic samples of colon, the abundance of the phylum Firmicutes decreased slightly, the relative number of the bacteria in the phylum Bacteroidetes increased strongly as compared to the control values, and after insulin treatment this increase was more significant. Chronic hyperglycaemia has the most prominent eﬀect on the mucosa-associated microbiota in the duodenum.
The Effects of Current Account Deficits on Economic Growth: Evidence from Kenya

The study examines the effects of current account deficits on economic growth. It also evaluates the direction of causality between the current account deficits and economic growth. These have in the recent past been analyzed in developed and developing economies. In contributing to this ongoing debate, the study applied unit root tests, cointegration analysis, a dynamic vector error correction model and Toda-Yamamoto Granger-causality representation using annual time series data for Kenya from 1980 to 2016. There is evidence that in the long run, current account deficit has significant positive effect on economic growth in Kenya. The evidence suggests a bidirectional causality running from current account deficit to economic growth with feedback effects. The study underscores the need for the authorities to utilize current account deficits to strictly finance public investment to foster gross fixed capital formation, for shared prosperity in Kenya. The evidence underscores the need for more country specific studies in sub-Saharan Africa.
From Verbal English to Visual English—A Semiotic Turn

As its general aim, this paper calls for a semiotic turn or a paradigm shift from concentration on verbal English to interaction between visual and verbal English in English Studies. Specially, within a theoretical framework of multimodal social semiotics, the present paper illustrates what visual English is, examines how it represents and communicates meaning as a semiotic resource system, and identifies some characteristic features of visual English through an itemised, theoretically informed analysis of five advertisements as embodiments of visual
Drug-Drug Interaction Mining and Interaction Terms Extraction using Deep Learning: A Word-level Attention Bi-Directional LSTM

Detection of Drug-Drug Interactions (DDIs) is critical for patient medication safety. Knowledge about drug interactions may not only prevent serious adverse drug events, but also control unnecessary health costs. The amount of biomedical literature related to drug interactions is increasing every year while the publicly available database for guiding medication treatment is consistently outdated due to the lack of automated DDIs extraction systems. In this paper, we propose a novel automated DDIs extraction method based on a word-level attention bi-direction LSTM neural network architecture (which is a special kind of Recurrent Neural Networks and used to solve long-term dependency problems). Our proposed framework requires minimal effort for manual feature engineering with good results for detecting DDIs from biomedical documents. The proposed method is able to extract interaction terms from sentences which contain DDIs via the word-level attention mechanism. The experimental results show that our method achieves better performance when compared with the existing state-of-the-art baselines for the multi-class DDIs detection problem.