Miracle-dz/UniFAR-FTUs huggingface dataset:
Competencies and professional development needs of kindergarten teachers

The study identified the level of competencies and the extent of professional development needs of kindergarten teachers in the Sultan Kudarat Division, during the school year 2019 - 2020. The study employed a descriptive method. The study involved 54 kindergarten teachers in the division in accomplishing the 12-item self-assessment instrument. Data were analyzed using descriptive statistics. The results revealed that kindergarten teachers have a high level of competencies in content knowledge and pedagogy, learning environment and diversity of learners, curriculum and planning, and assessment and reporting. These indicate that they possess almost all of the competencies of efficient teachers. Results further revealed a very high extent of professional needs in content knowledge and pedagogy and the learning environment and diversity of learners, while they had a high extent of professional needs in the remaining domains. Since they reported very high priorities in content knowledge and pedagogy and the learning environment and diversity of learners, these areas would be the main considerations in the crafting of a professional development plan.
FATE OF ATMOSPHERIC DUST FROM MINING ACTIVITIES IN NEW CALEDONIA AND THE IMPACT ON THE NICKEL CONTENT OF LICHEN

Nickel mining in New Caledonia proceeds in open pit mining. Therefore, bare soil surfaces submitted to wind blow and mining operation (earthwork, excavating, transport, etc.) are a source of particulate matter. These phenomena produce essentially coarse metal rich dusts which undergo regional atmospheric transport. This study aims to determine how the mining activities can impact the environment and the population in conjunction with the presence of particles in the atmosphere via the wind transport. In this work, Koniambo (KNS) is the target mine, a new plant and mining site created in 2010 in the north of New Caledonia. Particle matter with diameter below 10 μm (PM10) was measured in three sites surrounding the KNS mine to follow the population exposition to particulate matter. Air mass trajectory modelling was carried out to identify the sources of high PM10 events (above 50 μg/m3) in these locations and to elaborate a density map of air mass trajectories. Five mines appeared to contribute more or less to rich PM10 air masses: KNS, Népoui, Poro, Kouaoua and Monéo. A density map of air mass trajectories originating from these mines showed areas where the lower atmosphere is potentially impacted by mining dust. As lichens are known for their air pollution bioindication properties, lichens were sampled in areas with high, medium and poor trajectory densities and their Ni and Ti content were analyzed. A positive correlation between Ni/Ti ratio and trajectory densities was observed. Air mass trajectory modelling is thus a good tool to predict the potential environmental impact of mining dust.
COGNITIVE SCIENCE BASED DESIGN OF SMART COACHING SCHEMA

A BSTRACT . Developments and advances of computers and technology has un-wrapped various novel opportunities in the arena of coaching, with key advancements emerging in the creation of Smart Coaching Schemas (SCS). The proposed framework presents a Smart Coaching Schema consisting the services offered by existing systems and an enhancement of these services by utilizing cognitive proﬁciency criteria of variety of users. Different cognitive aspects including prominence of assignment to the student, his/her level of enthusi-asm, level of attentiveness, intellectual promptness, and basic acquaintance level have been measured and used as a basis for designing Smart Coaching Schema. The proposed technique utilizes Naive Bayes classiﬁer categorize the students as Novice, Average and Excellent. This categorisation is useful to distinguish coaching settings of the proposed Smart Coaching System based on students’ cognitive proﬁciency. The combination of aforementioned cognitive proﬁciency criteria with the traditional SCS has brought up a novel design of Smart Coaching Systems.
Structure of the FindFish Knowledge Transfer Platform

Abstract As consumer awareness increases in Poland, fish consumption is on an upward trend. While new technologies permit meeting increasing demand, they significantly increase the pressure on fish supplies. As a result, many fish stocks are over-exploited, which threatens marine ecosystems. Declining fisheries, increasing fishing operating costs, and the necessity of making longer fishing expeditions at greater distances that often end with catches of fewer or less valuable fish mean that in some fisheries sectors are currently running at the margins of profit or at a loss. At the same time, the European Union’s fisheries policy aims to create more selective and sustainable fisheries, to implement limitations through fishing quotas, and to ban the recognition of discards. The aim is to ensure that individual fish species are protected while providing the European Union with stable, secure supplies of fresh fish. The FindFish Knowledge Transfer Platform project was launched to provide solutions for challenges facing commercial fisheries. Its purpose is to provide fishers with a knowledge transfer platform and a numerical forecasting system for the marine environment of the Gulf of Gdansk. By combining in-situ research, environmental data, fish catch data, and numerical calculations, this tool will improve the accuracy of targeted fishing while reducing by-catch. The system will provide more reliable data on fish stocks and facilitate more efficient resource management.
Dominant Rodent Species in Animal Production Farms at Sohag Governorate, Egypt

Rodents are known for their high reproductive potential, there are many interesting dynamics to various rodent populations that should be understood to better facilitate their management and to reduce damage. The population goes through an annual cycle that may include high and low densities, active and inactive periods, reproductive and non-reproductive periods, and dispersal periods. To avoid inclement periods, some species exhibit winter dormancy (hibernation), and some species have summer dormancy (estivation) during hot, dry periods. Some species exhibit multi-year cycles; for example, the rodents often reach population peaks (irruptions) every 3-5 years (Edge et al., 1995 and Wolff et al., 1997).
Isolation and molecular characterization of Campylobacter jejuni from chicken and human stool samples in Egypt

Campylobacteriosis is one of the most well-characterized bacterial foodborne infections worldwide that arises chiefly due to the consumption of poultry and poultry products (Wieczorek et al., 2012). The disease is caused by numerous species within the genus Campylobacter, but Campylobacter jejuni is the most commonly isolated species from established cases of human campylobacteriosis (Eurosurveillance Editorial Team, 2012).
The Adenosine System at the Crossroads of Intestinal Inflammation and Neoplasia

Adenosine is a purine nucleoside, resulting from the degradation of adenosine triphosphate (ATP). Under adverse conditions, including hypoxia, ischemia, inflammation, or cancer, the extracellular levels of adenosine increase significantly. Once released, adenosine activates cellular signaling pathways through the engagement of the four known G-protein-coupled receptors, adenosine A1 receptor subtype (A1), A2A, A2B, and A3. These receptors, expressed virtually on all immune cells, mitigate all aspects of immune/inflammatory responses. These immunosuppressive effects contribute to blunt the exuberant inflammatory responses, shielding cells, and tissues from an excessive immune response and immune-mediated damage. However, a prolonged persistence of increased adenosine concentrations can be deleterious, participating in the creation of an immunosuppressed niche, ideal for neoplasia onset and development. Based on this evidence, the present review has been conceived to provide a comprehensive and critical overview of the involvement of adenosine system in shaping the molecular mechanisms underlying the enteric chronic inflammation and in promoting the generation of an immunosuppressive niche useful for the colorectal tumorigenesis.
A New Species and New Records of the Genus Sarcophaga from Egypt, with a Key to the Known Egyptian Species (Diptera: Sarcophagidae)

The Sarcophaga spp. available whether through the field collections from different Egyptian localities and/or through the material preserved in the main Egyptian insect collections are keyed in the present study. One new species, S. mennae sp. n. , is described, and two new species records for Egypt, S. parkeri (Rohdendorf, 1937) and S. marshalli Parker, 1923 are discovered. A key to nine subgenera and 21 out of 27 species representing the genus Sarcophaga in Egypt is provided based primarily on male genitalia. Photographs and illustrations of treated species are included.
BOTNET DETECTION FROM DRIVE-BY DOWNLOADS

The advancement in Information Technology has brought about an advancement in the development and deployment of malware. Bot Malware have brought about immense compromise in computer security. Various ways for the deployment of such bots have been devised by attackers and they are becoming stealthier and more evasive by the day. Detecting such bots has proven to be difficult even though there are various detection techniques. In this work, a packet capturing and analysis technique for detecting host-based bots on their characteristics and behavior is proposed. The system captures network traffic first, to establish normal traffic, then already captured botnet traffic was used to test the system. The system filters out HTTP packets and analyses these packets to further filter out botnet traffic from normal internet traffic. The system was able to detect malicious packets with a False Positive Rate of 0.2 and accuracy of 99.91%.
Antioxidant activity and content of selected antioxidant compounds in grain of different oat cultivars

The total antioxidant activity (TAA), total contents of polyphenols (TPC), phenolic acids (TPA) and tocols (TTC) were determined in the grain of 5 oat cultivars of Czech origin grown under organic and conventional cropping systems in two-year experiments (2018 and 2019). The TPC ranged from 772.9 mg/kg DM (dry matter) (hulled oat cv. Seldon) to 890.6 mg/kg (naked oat cv. Patrik); the TPA from 261.6 mg/kg (cv. Seldon) to 479.0 mg/kg (cv. Patrik); the TTC from 110.9 mg/kg (hulled oat cv. Korok) to 126.5 mg/kg (cv. Seldon). The TAA ranged from 427.1 mg/kg (cv. Korok) to 474.9 mg/kg (cv. Seldon). Besides the effect of the cultivar, the TAA and antioxidant contents were significantly affected also by year (weather conditions); higher values were observed in the drier and warmer the year 2019. The effect of the cropping system was statistically insignificant.
Effect of the Preparation Method on the Physicochemical Properties and the CO Oxidation Performance of Nanostructured CeO2/TiO2 Oxides

Ceria-based mixed oxides have been widely studied in catalysis due to their unique surface and redox properties, with implications in numerous energy- and environmental-related applications. In this regard, the rational design of ceria-based composites by means of advanced synthetic routes has gained particular attention. In the present work, ceria–titania composites were synthesized by four different methods (precipitation, hydrothermal in one and two steps, Stöber) and their effect on the physicochemical characteristics and the CO oxidation performance was investigated. A thorough characterization study, including N2 adsorption-desorption, X-ray diffraction (XRD), scanning electron microscopy with energy dispersive X-ray spectroscopy (SEM/EDS), transmission electron microscopy (TEM) and H2 temperature-programmed reduction (H2-TPR) was performed. Ceria–titania samples prepared by the Stöber method, exhibited the optimum CO oxidation performance, followed by samples prepared by the hydrothermal method in one step, whereas the precipitation method led to almost inactive oxides. CeO2/TiO2 samples synthesized by the Stöber method display a rod-like morphology of ceria nanoparticles with a uniform distribution of TiO2, leading to enhanced reducibility and oxygen storage capacity (OSC). A linear relationship was disclosed among the catalytic performance of the samples prepared by different methods and the abundance of reducible oxygen species.
Molecular Phylogeny of Coprophanaeus (Megaphanaeus) d’Olsoufieff, 1924 (Coleoptera: Scarabaeidae: Scarabaeinae) and the position of C. bellicosus

Coprophanaeus ( Megaphanaeus ) d’Olsoufieff, 1924 has four valid species: C. lancifer (Linne, 1767), C. ensifer (Germar, 1821), C. bonariensis (Gory, 1844) and C. bellicosus (Olivier, 1789). However, authors disagree about the placement of C. bellicosus . Thus, our aims were (I) to test if Megaphanaeus is a monophyletic group and (II) verify to which subgenus C. bellicosus belongs. We sequenced three mitochondrial and one nuclear marker for ten Phanaeini species: COI (672bp), COI-II (1326bp), 16S (527bp) and 28S (994bp). For fifteen species we sequenced two markers, COI (681pb) and 16S (532pb). Both matrices were analyzed under three methods of phylogenetic inference: Maximum Parsimony, Maximum Likelihood, and Bayesian Inference. Megaphanaeus is here considered monophyletic including C. bellicosus as sister-group to ( C. bonariensis ( C. lancifer + C. ensifer )). All analyses recovered the non-monophyly of both C. lancifer and C. ensifer , because of a population of C. lancifer grouped with C. ensifer specimens.
Assessing the impact of plant genetic diversity in shaping the microbial community structure of Vitis vinifera phyllosphere in the Mediterranean

ABSTRACT The aerial surface of the plant (phyllosphere) is the habitat of complex microbial communities and the structure of this microbiome may be dependent on plant genetic factors, local environment or interactions between them. In this study, we explored the microbial diversity present in the phyllosphere of a very diverse set of grapevine cultivars representing the three genetic pools of the species, grown on an experimental plot at Montpellier (French Mediterranean region). We assessed microbiome variation in the phyllosphere using amplicon sequencing of the 16S rRNA gene and of the internal transcribed spacer (ITS), according to the grapevine genetic pools or cultivars, and organs (i.e. leaves and grape berries). The observed microbiome was complex; out of 542 bacterial genera; Pseudomonas, Pantoea, Sphingomonas, and Acinetobacter were the most abundant and almost ubiquitously present across the samples, and out of 267 fungal genera; Aureobasidium, Alternaria, Mycosphaerella and Aspergillus were most represented. Our results illustrated that the microbial taxa were almost uniformly distributed among the genetic pools and only a few cultivar or genetic pool level differences were found, but a very clear differential taxa abundance was found between the leaf and berry samples. Some genus level associations were also observed with certain genetic pools.
Modelling and analysis of a novel mechanical‐variable‐flux IPM machine with rotatable magnetic poles

: In this study, a novel mechanical-variable-flux interior permanent magnet motor (MVF-IPMM) is presented, which employs rotatable magnetic poles and a mechanical flux-adjusting device placed on both sides of the rotor. The device can regulate the magnetic circuit by rotating magnetic poles and adjusting the angle of the magnetisation direction relative to the d axis. Consequently, the flux-weakening capability is enhanced. The configuration and additional mechanical devices of the MVF- IPMM are introduced, respectively. Then, the operation principle and flux-adjusting mechanism are deeply investigated by using analytical models, whose parameters are computed by automatic dynamic analysis of mechanical system and finite-element analysis. Based on the simulation results, an electromechanical model is established to predict the performance of the motor. In addition, the electromagnetic characteristics of the mechanical-variable-flux- and conventional interior permanent magnet machines are compared. Finally, the effectiveness of the design is successfully proven by experimenting with a prototype.
Human mobility in interest space and interactive random walk

Compared with the well-studied topic of human mobility in real geographic space, only a few studies focus on human mobility in virtual space, such as interests, knowledge, ideas, and so on. However, it relates to the issues like public opinion management, knowledge diffusion, and innovation. In this paper, we assume that the interests of a group of online users can span an Euclidean space which is called interest space, and the transfers of user interests can be modelled as Lévy Flight in the interest space. Considering the interaction between users, we assume that the random walkers are not independent but interacting with each other indirectly via the digital resources in the interest space. The proposed model in this paper successfully reproduced a set of scaling laws for describing the growth of attention flow networks of online communities, and obtaining similar ranges of users’ scaling exponents with empirical data. Further, we inferred parameters for describing the individual behaviours of the users according to the scaling laws of empirical attention flow network. Our model can not only provide theoretical understanding of human online behaviours but also has broad potential applications such as dissemination and public opinion management, online recommendation, etc.
Advancing Plant Phenology Causes an Increasing Trophic Mismatch in an Income Breeder Across a Wide Elevational Range

To avoid trophic mismatches, large herbivores should reschedule the breeding timing to keep in synchrony with the recent advance of plant phenology caused by climate change. To do so, individuals must track resources along two main non-exclusive axes: time (rescheduling the breeding timing) and space (i.e., shifting their range). While the vast majority of studies have focused on the study of speci ﬁ c populations inhabiting small and homogeneous environments, little is known about the response of species across large regions with highly heterogeneous topographies. Here, we studied roe deer ( Capreolus capreolus ), an income breeder that has demonstrated a lack of phenotypic plasticity on birth timing in a densely forested lowland area, and evaluated its ability to track resources along a wide elevational gradient (288 – 2366 m a.s.l.). We used data from 8986 parturition events collected in Switzerland during the period 1971 – 2015. We hypothesize that the mismatch between roe deer parturition dates and peak resource availability will increase over the study period. In addition, we expect this mismatch to be larger in low areas compared to higher elevation areas. Contrary to previous studies, we did ﬁ nd a consistent, but small, trend toward more advance parturition dates through time across all elevations. However, this rate of advance was less than that of the plant phenology indicators, resulting in an increasing mismatch at all elevations. Parturition dates changed on average at a rate between 7.5 times slower than the growing season start and 5 times slower than the ﬂ owering start. Thus, at the lowest elevations, parturition timing has already fallen outside the optimal time window for high-quality forage, while at high elevations, parturitions are still synchronized with the peak availability of quality forage. Our study emphasizes the need for large-scale study designs along climatic gradients to help understand the complex relationships that shape adaptation across environments. This would allow for better understanding of how populations will respond to the new environmental conditions imposed by climate change.
Sentiment Analysis on Corona Virus Pandemic Using Machine Learning Algorithm

Corona virus outbreaks that occur in almost all countries in the world have an impact not only in the health sector, but also in other sectors such as tourism, finance, transportation, etc. This raises a variety of sentiments from the public with the emergence of corona virus as a trending topic on Twitter social media. Twitter was chosen by the public because it can disseminate information in real time and can see market reactions quickly. This research uses "tweet" data or public tweet related to "Corona Virus" to see how the sentiment polarity arises. Text mining techniques and three machine learning classification algorithms are used, including Naive Bayes, Support Vector Machine (SVM), K-Nearest Neighbor (K-NN) to build a tweet classification model of sentiments whether they have positive, negative, or neutral polarity. The highest test results are generated by the Support Vector Machine (SVM) algorithm with an accuracy value of 76.21%, a precision value of 78.04%, and a recall value of 71.42%. Keywords: Machine Learning, Corona Virus, Twitter, Sentiment Analysis.
VEGF in Renal Cell Carcinoma – A Mini Review

Angiogenesis is a very important process in the progression of the tumor growth. Vascular endothelial growth factor (VEGF) is a key factor in angiogenesis. The main function is vascular permeability, angiogenesis and endothelial cell growth. An inactivated or impaired tumor suppressor gene Von Hipple Lindaue(VHL) causes accumulation of hypoxia inducible factor (HIF-1A) and leads to increased production of VEGF. The more the expression of VEGF, the worse is the survival and recurrence in many malignancies like Renal Cell Carcinoma. VEGF-targeted therapy plays a major role in various carcinomas involving VEGF pathway for their cancerous growth.
Sound Event Detection Using Derivative Features in Deep Neural Networks

We propose using derivative features for sound event detection based on deep neural networks. As input to the networks, we used log-mel-filterbank and its first and second derivative features for each frame of the audio signal. Two deep neural networks were used to evaluate the effectiveness of these derivative features. Specifically, a convolutional recurrent neural network (CRNN) was constructed by combining a convolutional neural network and a recurrent neural networks (RNN) followed by a feed-forward neural network (FNN) acting as a classification layer. In addition, a mean-teacher model based on an attention CRNN was used. Both models had an average pooling layer at the output so that weakly labeled and unlabeled audio data may be used during model training. Under the various training conditions, depending on the neural network architecture and training set, the use of derivative features resulted in a consistent performance improvement by using the derivative features. Experiments on audio data from the Detection and Classification of Acoustic Scenes and Events 2018 and 2019 challenges indicated that a maximum relative improvement of 16.9% was obtained in terms of the F-score.
Suburbs and Urban Peripheries in a Global Perspective

Herbert Gans’ classic book, The Levittowners, has inspired generations of urban sociologists studying American suburbs, but it has also confined the field’s focus to studies of the local community. At the same time, however, outside the discipline of American urban sociology, an interdisciplinary field of global suburban studies has flourished. Global suburban studies address a wider range of topics that extends to infrastructural provision, governance, and popular resistance. By introducing the key debates in global suburban studies, this essay argues that it is time for American urban sociologists to broaden their analytical focus beyond community institutions and power relations, and that much can be gained by adopting an international and comparative perspective to learn about urban peripheries elsewhere in the world. A comparative vantage point can help U.S. sociologists better situate socio–spatial transformations in American suburbs among a world of cities (and suburbs), and mine new insights on topics involving poverty, segregation, and community life that have been at the center of suburban research in American sociology.