Miracle-dz/UniFAR-FTUs huggingface dataset:
DNA Barcoding Identifies a Unique Haplotype of Nile Tilapia Oreochromis niloticus Thriving in Egyptian Freshwater and Brackish Water Lakes

Global shortage of freshwater is expected to reduce aquaculture activities that depend upon freshwaters. Mining the wild genetic resources of fish species can aid much the selection and development of new strains capable of withstanding unusual culturing conditions, such as tolerance to unusual salinities. Nile tilapia is a supreme international aquaculture species, with a limited degree of tolerance to brackish waters. In the current study, DNA barcoding for the Nile Tilapia Oreochromis niloticus , using the mitochondrial cytochrome oxidase subunit I gene, was carried out. Samples were collected from two locations at Manzala Lake in the North of Egypt (El-Serow, salinity 1‰; and Ashtoom El-Gamil, Salinity 20‰); and from Lake Nasser (salinity 1‰;) in the South of Egypt. Numbers, locations and phylogenetic interrelationships among these haplotypes were determined, appending to the comparison the world haplotypes available in GenBank database. The results indicated the main haplotype lineages in the area of study and the world. Also, a newly identified haplotype with natural tolerance to different salinities could be identified from both studied lakes. This can contribute much to the genetic enhancement of tilapia aquaculture using new parents with more capability to tolerate salinity differences, producing then pure or hybrid offsprings with further ameliorated salinity tolerance.
Coarse woody debris in forest regions of Russia

Les auteurs ont combine des donnees collectees dans le cadre de l'inventaire forestier regulier avec des mesures prises dans 1044 places-echantillons et les resultats d'un echantillonnage par densite de 922 arbres morts pour evaluer les stocks regionaux de debris ligneux grossiers dans sept regions forestieres d'importance en Russie. Les stocks de debris ligneux grossiers etaient en moyenne plus faibles (14-20 m 3 /ha ou 4,0-5,8 Mg/ha) dans la partie ouest de la Russie (les regions de Saint-Petersbourg, Centrale, de Khanty-Mansi et de Novosibirsk) que dans les regions de la Siberie orientale et de l'extreme Est (40-51 m 3 /ha ou 11,0-14,4 Mg/ha). La difference dans les stocks de debris ligneux grossiers etait particulierement importante entre les jeunes forets de deux regions occidentales (2,4 Mg/ha dans la region de Saint-Petersbourg et 3,4 Mg/ha dans la region Centrale) et celles des regions orientales (20,4-24,4 Mg/ha). Cette difference est associee aux principaux types de perturbations: la coupe a blanc dans l'ouest de la Russie et les perturbations naturelles dans l'est. L'analyse de variance des stocks de debris ligneux grossiers montre que la region, les especes dominantes, le groupe d'âge des forets, la classe de productivite et les interactions entre ces facteurs expliquent 87-88% de la variation totale et que les facteurs les plus importants sont le groupe d'âge et la region. Le fait que les stocks de debris ligneux grossiers soient plus faibles dans les regions ou la foret est sous amenagement intensif indique qu'une utilisation plus intensive de la foret dans plusieurs regions de la Russie risque d'entrainer une reduction des stocks regionaux de debris ligneux grossiers et de carbone.
Antioxidant Potential, Physico-chemical, and Sensory Attributes of Cookies Supplemented with Mosambi Peel Extract

ABSTRACT The core objective of the present investigation was to isolate and quantify antioxidants from mosambi (sweet orange) peel. In the proposed research, different solvents were used for the extraction of antioxidants from mosambi peel. Among these solvents, ethanol resulted in better antioxidant yield compared to aqueous extract. Ethanolic extract of mosambi peel showed higher total phenolic contents (19.3 ± 0.3 mg/g) as compared to aqueous extracts (18.2 ± 0.04 mg/g). Considering the safety health concern, aqueous extract of mosambi peel was incorporated in cookies at different concentrations of 1%, 2%, and 3%, and further subjected to physico-chemical and sensory attributes. Proximate composition (moisture, crude protein, crude fat, crude fiber, ash, and niitrogen-free extract (NFE) contents) of fortified cookies varied non-significantly. However, sensory evaluation rated aqueous extract of mosambi peel (2%) with better hedonic response. Mosambi peel antioxidants have a great potential to be used in various functional foods and the ability to improve storage stability.
Direct ink writing of highly bioactive glasses 1

11 Direct ink writing (DIW) or Robocasting, is an additive manufacturing technique that offers the 12 opportunity to create patient specific bioactive glass scaffolds and high strength scaffolds for bone 13 repair. The original 45S5 Bioglass® composition crystallises during sintering and until now, robocast 14 glass scaffolds contained at least 51.9 mol% SiO2 or B2O3 to maintain their amorphous structure. 15 Here, ICIE16 and PSrBG compositions, containing < 50 mol% SiO2, giving silicate network connectivity 16 close to that of 45S5, were robocast and compared to 13-93 composition. Results showed Pluronic F17 127 can be used as a universal binder regardless of glass reactivity and that particle size distribution 18 affected the ink “printability”. Scaffolds with interconnects of 150 μm (41-43% porosity) had 19 compressive strengths of 32-48 MPa, depending on the glass composition. Robocast scaffolds from 20 these highly reactive bioactive glasses promise greatly improved bone regeneration rates compared 21 with existing bioactive glass scaffolds. 22
Molecular and Phylogenetic Status of Coenurus cerebralis Infecting Sheep from Dakahlia Province, Egypt

| The limited genetic data as well as the economic and zoonotic importance of the genus Taenia, interestingly T. multiceps, from Egypt drew our attention to study the molecular characters and the phylogenetic position of this parasite species from sheep. Brains from 80 apparently healthy sheep slaughtered at Mansoura abattoir, Dakahlia province, Egypt, were incised and palpated for the presence of Coenurus cerebralis cysts. DNA was extracted from each cyst and amplified by PCR using two mitochondrial genes, the cytochrome oxidase (CO1) and the NADH dehydrogenase (ND1). Sequences were aligned with those published on GenBank and subjected to the phylogenetic analysis. C. cerebralis cysts were found in 3 (3.7%) out of the examined sheep and the three isolates were identical in their sequences. There were 99% identity between our isolates and those from Turkish (KT217594) and Iranian ( JQ710587) sheep at the level of CO1 gene which confirmed by the phylogenetic analysis. Both CO1 and ND1 phenograms evidenced the existence of genetic variants within T. multiceps from variable hosts within different geographical regions. Our results supposed the conspecificity between the sheep and goat isolates, and the potential existence of a quasi-species in T. multiceps isolates from cattle. Such data could help in the epidemiological studies and implementation of control regimens against this economically important parasite.
Slant Removal Technique for Historical Document Images

Slanted text has been demonstrated to be a salient feature of handwriting. Its estimation is a necessary preprocessing task in many document image processing systems in order to improve the required training. This paper describes and evaluates a new technique for removing the slant from historical document pages that avoids the segmentation procedure into text lines and words. The proposed technique first relies on slant angle detection from an accurate selection of fragments. Then, a slant removal technique is applied. However, the presented slant removal technique may be combined with any other slant detection algorithm. Experimental results are provided for four document image databases: two historical document databases, the TrigraphSlant database (the only database dedicated to slant removal), and a printed database in order to check the precision of the proposed technique.
Geographical Analysis of Lung Cancer Mortality Rate and PM2.5 Using Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth

Exposure to particulate matter with an aerodynamic diameter of less than 2.5 μm (PM2.5) may increase risk of lung cancer. The repetitive and broad-area coverage of satellites may allow atmospheric remote sensing to offer a unique opportunity to monitor air quality and help fill air pollution data gaps that hinder efforts to study air pollution and protect public health. This geographical study explores if there is an association between PM2.5 and lung cancer mortality rate in the conterminous USA. Lung cancer (ICD-10 codes C34- C34) death count and population at risk by county were extracted for the period from 2001 to 2010 from the U.S. CDC WONDER online database. The 2001-2010 Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth dataset was used to calculate a 10 year average PM2.5 pollution. Exploratory spatial data analyses, spatial regression (a spatial lag and a spatial error model), and spatially extended Bayesian Monte Carlo Markov Chain simulation found that there is a significant positive association between lung cancer mortality rate and PM2.5. The association would justify the need of further toxicological investigation of the biological mechanism of the adverse effect of the PM2.5 pollution on lung cancer. The Global Annual Average PM2.5 Grids from MODIS and MISR Aerosol Optical Depth dataset provides a continuous surface of concentrations of PM2.5 and is a useful data source for environmental health research.
Off-Topic Recommendations

In order to make useful recommendations, the product and the person using the product need to focus on the same task. However, when working with a product, people may explore new product features or change their mind about what they want to do. Such behavior can confuse recommendation agents, unless people and their products communicate about the shift of focus. This paper contributes to the design of recommendation agents that offer off-topic suggestions and consistently handle focus shifting. The paper describes key issues in the design of recommendations under focus shifting, and the three possible dialogue strategies for handling focus shifts. The results of an initial study on one of the strategies indicate trends in how people combine use of off-topic recommendations with focused action in the rest of the product interface. Study results also inform a model of focus shifting behavior, presenting a baseline for future research on the design of off-topic recommendations.
Behavioural Modification and Classroom Management Skills as Protective Factors against Mental Health Problems in Teachers: A Synthesis of Research

Teaching schoolchildren is almost uniformly regarded as a particularly stressful occupation characterized by a range of mental health hazards. Consequently, clinical psychological research and practice has made intense efforts towards proliferating understanding, treatment and prevention of teacher burnout. Compared to other parameters, lack of classroom control is a major source of mental health problems in secondary school teachers. While the available literature on the relationship between classroom management and teacher burnout is intriguing, there is a need for a summary of the available findings. To encourage the progression of this research and the development of mental health intervention for teachers, the present review seeks to synthesize the relevant literature. As previous findings indicate, behaviour modification and classroom management skills enable teachers to prevent and modify student misbehavior and therefore contribute to both stress reduction and self-efficacy. Teachers without sufficient resources such as classroom management and behaviour modification skills are particularly vulnerable to experience stress when exposed to prolonged discipline problems. In an attempt to compensate their skill deficit, they are inclined to draw on punitive and coersive practices that exacerbate student misbehavior and maladaptive selfefficacy beliefs. Teachers might then experience severe emotional strain that again occupies information processing resources and impedes successful classroom management; the mental health risks originate from an escalating and self-perpetuating cycle of skill deficit, student misbehavior and ineffective control strategies. A threshold model is forwarded to account for the specific vulnerability towards mental health problems conferred by skill deficits. Overall, burnout interventions should address classroom management deficits and equip teachers with behavior modification skills.
Hit Song Prediction Based on Early Adopter Data and Audio Features

Billions of USD are invested in new artists and songs by the music industry every year. This research provides a new strategy for assessing the hit potential of songs, which can help record companies support their investment decisions. A number of models were developed that use both audio data, and a novel feature based on social media listening behaviour. The results show that models based on early adopter behaviour perform well when predicting top 20 dance hits.
Maintaining computer-based information systems using text-based intelligent systems techniques

In order to incorporate up-to-date quantitative and qualitative information, Computer-Based Information Systems (CBIS) must be able to extract data from unstructured, textual formats such as newspapers and magazines. The process of updating information in a CBIS currently requires large amounts of human effort analyzing and converting data from such sources into formats which information systems can work with. This paper suggests some meth­ ods by which the data needs of a CBIS can be handled semi-automatically (Employing both computers and humans) using text-based intelligent systems (TBIS) techniques
A Comparison of Different Feature Sets for Age-Based Classification of Short Texts

The aim of current study is to compare two feature sets for age-based classification of short texts as about 100 words pe r author. Besides widely used n-grams text readability features are proposed as a n alternative. By readability features we mean different relative ratios of text lements as characters per word, words per sentence, etc. Support Vector Machi nes, Logistic Regression, and Bayesian algorithms were used to build models. W e found that with 4-year age gap between age groups readability features wer e mo e effective for classification than n-grams. With 2-year age gap there wa s no significant difference in classification results between two feature sets. In both cases combined feature set yield to highest f-scores. Model generated Simple Logistic regression and combined feature set yield to f-score 0.9.
An initial study of educational game applications supporting the STEM education in K-12 systems

This study develops a novel model focusing on educational game development based on active learning paradigm. The model is designed as a collaborative endeavor involving college constituencies and K-12 stakeholders in the effort to promote adoption of educational game applications supporting the STEM curriculum in K-12 systems. Preliminary evidence from pilot experiments suggest that college students found real-world game development activities stimulating and worthwhile while K-12 administrators and teachers became interested in game development collaboration. Based on this initial success, an educational game laboratory model is proposed. The model explains the roles played by different actors in the collaborative effort. It also outlines a set of expected outcomes for an ensuing experiment. Finally, the model specifies potential evaluation schemes. The results obtained from the experiment would present further evidence concerning the effectiveness of educational games. In particular, the study could potentially provide insights and directions for game developers in the areas of technical features, content selection and delivery methods.
Investigation of global optimum seeking methods in water resources problems

Optimization has become a valuable tool in most of hydroinformatics applications. Given that these problems are intrinsically nonlinear and multimodal, they do not exist deterministic optimization methods that can locate the globally optimal solution. During the last two decades, probabilistic schemes have been developed for solving global optimization problems. These methods use a combination of random and deterministic steps, without generally requiring restrictive conditions on the nature of the objective function.
A comparison of machine learning algorithms for automatic classification of neurons by their morphology

Classification of neurons has been a studied topic in neuroscience for several years and with the increase of data, new methods are encouraged to help with the classification. This study compares different machine learning algorithms to see which are better suited for classification of large data sets of morphological reconstructions in multidimensional feature space. Ten algorithms were compared on a data set of over 10 000 samples of mice neurons. Further, each classifiers ability to classify each available cell type were also investigated. The results show that Random Forest had the best overall mean accuracy followed by Multi-layer Perceptron with 83% and 78% respectively. However, observing the classification of individual cell types all the algorithms varied in accuracy and Random Forest was not considered the best. In conclusion, machine learning algorithms are a viable source when classifying neurons but more research needs to be performed to reach the higher accuracy results.
Food Powder Classification Using a Portable Visible-Near-Infrared Spectrometer

Visible-near-infrared (VIS-NIR) spectroscopy is a fast and non-destructive method for analyzing materials. However, most commercial VIS-NIR spectrometers are inappropriate for use in various locations such as in homes or offices because of their size and cost. In this paper, we classified eight food powders using a portable VIS-NIR spectrometer with a wavelength range of 450–1,000 nm. We developed three machine learning models using the spectral data for the eight food powders. The proposed three machine learning models (random forest, k-nearest neighbors, and support vector machine) achieved an accuracy of 87%, 98%, and 100%, respectively. Our experimental results showed that the support vector machine model is the most suitable for classifying non-linear spectral data. We demonstrated the potential of material analysis using a portable VIS-NIR spectrometer.
Modeling the Impact of User Awareness on Immunization Strategies

Despite the efforts to design better antivirus software, malware continue to spread and cause enormous damages. Effect of immunizing computer systems as the most effective control policy for preventing such infections is two-fold. On one hand, it increases the global immunity of the network by providing indirect protection for unimmunized systems. On the other hand, raising the awareness of users from the possibility of infection can trigger behavioral changes by which users take measures to reduce their systems’ susceptibility using the antivirus software. Here, we propose the Behavior-Immunity model that allows measurement of vaccination effect based on the indirect protective effect of immunization strategies. It also provides a mean to utilize human behavioral changes to enhance the effectiveness of immunization strategies. In this work, we focus on the word of mouth as the source of user awareness and show that immunization schema can appropriately utilized the behavioral changes to practice better results. We also present a methodology for network immunization which is provably close to the optimal solution. Extensive computational experiments on some synthetic and real-world networks revealed that this strategy offers a significant improvement over well-studied targeted immunization method based on degree centrality.
Modality Preferences of Different User Groups

In order to examine user group differences in modality preferences, participants of either gender and two age groups have been asked to rate their experience after interacting with a smart-home system offering unimodal and multimodal input possibilities (voice, free-hand gesture, smartphone touch screen). Effects for gender, but not for age (younger and older adults) have been found for modality preferences. Women prefer touch and voice over gesture for many scales assessed, whereas men do not show this pattern consistently. Instead, they prefer gesture over voice for hedonic quality scales. Comparable results are obtained for technological expertise assessed individually. This interrelation of gender and expertise could not be solved and is discussed along with consequences of the results obtained. Keywords-multimodal dialog system; evaluation; user factors.
From Paris Agreement to Action: Enhancing Climate Change Familiarity and Situation Awareness

The Paris Agreement was a monumental stride towards global climate change governance. It unlocked the climate change gridlock, introducing country-subjective commitments and a five-year review mechanism. To support the implementation of the Paris Agreement, we designed the Nzoia WeShareIt climate change game. Game sessions were conducted in June and July 2015, and 35 respondents completed a pre- and post-game situation awareness (SA) questionnaire and an in-game performance measurement system. The questionnaire uses a 10-dimensional situation awareness rating technique (SART). Subsequently, we conducted a factorial MANOVA (multivariate analysis of variance) to assess the interaction effects between familiarity, team, and gender. Results indicate an increase in situation awareness. However, policymakers' action was not contingent on the increased SA only, there was a significant interaction effect between familiarity and SA, to lead to climate change actions. Therefore, we recommend more emphasis on the role of familiarity in enhancing SA and, subsequently, supporting the implementation to the Paris five-year review country commitments. We also recommend the increased usage of symbols and capacity development of policymakers on connective capacity to enable them to span the climate change boundaries.
DISTRIBUIÇÃO DE SEMENTES DE SOJA COM TENOLOGIA RAMPFLOW NO DISCO HORIZONTAL

Uma tecnologia implantada nos discos horizontais sao os alveolos com furacao em formato conico e estriado, denominada rampflow. Esta inovacao propoe melhorar o alojamento das sementes nos alveolos e reduzir falhas e duplas. Sendo assim, objetivo deste trabalho foi avaliar a distribuicao longitudinal de sementes de soja utilizando disco horizontal com tecnologia rampflow e convencional. O experimento foi realizado no laboratorio de plantabilidade do grupo de plantio direto (GPD), da Faculdade de Ciencias Agronomicas – UNESP/Campus de Botucatu-SP. Os tratamentos utilizados para conducao do experimento foram: disco horizontal convencional e disco horizontal rampflow, ambos com diâmetro dos alveolos de 8 mm e anel liso. A distribuicao de sementes de soja utilizando disco horizontal com tecnologia rampflow proporciona menores indices de falhas e duplas, assim como maiores indices de aceitaveis e precisao na distribuicao das sementes.
A problem on completeness of exponentials

Let $\mu$ be a finite positive measure on the real line. For $a>0$ denote by $\EE_a$ the family of exponential functions $$\EE_a=\{e^{ist}| \ s\in[0,a]\}. $$ The exponential type of $\mu$ is the infimum of all numbers $a$ such that the finite linear combinations of the exponentials from $\EE_a$ are dense in $L^2(\mu)$. If the set of such $a$ is empty, the exponential type of $\mu$ is defined as infinity. The well-known type problem asks to find the exponential type of $\mu$ in terms of $\mu$. \ms\no In this note we present a solution to the type problem and discuss its relations with known results.