Miracle-dz/UniFAR-FTUs huggingface dataset:
Vertical DNA Sequences Compression Algorithm Based on Hexadecimal Representation

— The number of DNA sequences stored in databases is growing exponentially. Thus, decreasing the Data storage costs for the creation and the analysis of DNA sequences has become a necessity. Standard compression algorithms failed to get a good compression ratio. In this paper, we describe a LOSSLESS algorithm that compresses the DNA sequence in its equivalent in hexadecimal representation. In addition, by using a mathematical operation, it identifies the regions of similarity between two sequences.
Phytochemistry and Biological Activities of Leaves and Pulp Extracts from Ziziphus mauritiana (Lam.) Collected in Mali

Introduction: The objectives of this work consisted of a phytochemical study of the leaves and pulp of Ziziphus mauritiana Lam collected from the flooded and dried sites of Niono and Sévaré in Mali and to evaluate the biological activities of the extracts, i.e. the antiradical activity and hemolytic activity. Methods: Phytochemical analysis and biological activities were performed at the plant biochemistry and biotechnology laboratory of the FST / USTTB. The tannins and flavonoids were Original Research Article Keita et al.; JABB, 23(1): 1-10, 2020; Article no.JABB. 53585 2 extracted by maceration, dosed by spectrophotometry then analyzed by HPLC and their antiradical activity was evaluated by the DPPH method. The saponosides were extracted by decoction and their hemolytic activity was evaluated on beef blood. Results: Tannins and flavonoids were abundant in the leaves and the pulp but saponosides were absent in the pulp. Calcium ions, carbonate ions and chloride ions were abundant in the leaves and pulp of Zizyphus mauritiana Lam from the dried site of Niono and the flooded site of Sévaré. HPLC chromatograms showed two peaks of gallic acid in the tannins extracts. Catechical tannins and flavonoids of the flooded sites have a greater antiradical activity than those of the dried sites. However, their antiradical activity remains lower than that of ascorbic acid whose IC50 was measured at 30 μg. Leaf saponosides from the flooded site of Niono and the dried site of Sévaré showed hemolytic activity on red blood cells of beef. Conclusion: The leaves and pulps of Zizyphus mauritiana Lam were rich in phenolic compounds and have interesting antiradical activity. The saponosides extracted from the leaves showed hemolytic activity.
Trace element composition of size-fractionated suspended particulate matter samples from the Qatari Exclusive Economic Zone of the Arabian Gulf: the role of atmospheric dust

Abstract. We analyzed net-tow samples of natural assemblages of plankton, and associated particulate matter, from the Exclusive Economic Zone (EEZ) of Qatar in the Arabian Gulf. Size-fractionated suspended particles were collected using net tows with mesh sizes of 50 and 200 µm to examine the composition of small- and large-size plankton populations. Samples were collected in two different years (11 offshore sites in October 2012 and 6 nearshore sites in April 2014) to examine temporal and spatial variabilities. We calculated the excess metal concentrations by correcting the bulk composition for inputs from atmospheric dust using aluminum (Al) as a lithogenic tracer and the metal∕Al ratios for average Qatari dust. Atmospheric dust in Qatar is depleted in Al and enriched in calcium (Ca), in the form of calcium carbonate ( CaCO3 ), relative to the global average Upper Continental Crust (UCC). To evaluate the fate of this carbonate fraction when dust particles enter seawater, we leached a subset of dust samples using an acetic acid–hydroxylamine hydrochloride (HAc–HyHCl) procedure that should solubilize CaCO3 minerals and associated elements. As expected, we found that Ca was removed in Qatari dust; however, the concentrations (ppm) for most elements actually increased after leaching because the reduction in sample mass resulting from the removal of CaCO3 by the leach was more important than the loss of metals solubilized by the leach. Because surface seawater is supersaturated with respect to CaCO3 and acid-soluble Ca is abundant in the particulate matter, we only used unleached dust for the lithogenic correction. Statistical analysis showed that for many elements the excess concentrations were indistinguishable from zero. This suggested that the concentrations of these elements in net-tow plankton samples were mostly of lithogenic (dust) origin. These elements include Al, Fe, Cr, Co, Mn, Ni, Pb, and Li. For several other elements (Cd, Cu, Mo, Zn, and Ca) the excess concentrations present after lithogenic correction are most likely of biogenic/anthropogenic origin. The excess concentrations, relative to average dust, for most elements (except Cd) decreased with distance from the shore, which may be due to differences in biology, currents, proximity to the coast, or interannual processes.
Marine Organism Detection and Classification from Underwater Vision Based on the Deep CNN Method

Seabed fishing depends on humans in common, for instance, the sea cucumber, sea urchin, and scallop fishing, which is always a very dangerous task. Considering the underwater complex environment conditions such as low temperature, dim vision, and high pressure, collecting the marine products using underwater robots is commonly regarded as a feasible solution. The key technique of the underwater robot development is to detect and locate the main target from underwater vision. This research is based on the deep convolutional neural network (CNN) to realize the target recognition from underwater vision. The RPN (Region Proposal Network) is used to optimize the feature extraction capability. Deep learning dataset is prepared using an underwater video obtained from a sea cucumber fishing ROV (Remote Operated Vehicle). The inspiration of the network structure and the improvements come from the Faster RCNN and Hypernet method, and for the underwater dataset, the method proposed in this paper shows a good performance of recall and object detection accuracy. The detection runs with a speed of 17 fps on a GPU, which is applicable to be used for real-time processing.
Understanding Academic Engagement and Context Through Multimodal Data

The Internet has penetrated the life of adolescents and become a new space for learning, socializing and entertainment. Physical exercise and sleep remain crucial for the development of adolescents. However, the influence of these critical contextual factors on learning and life is insufficiently explored, partially due to the difficulty of measuring these factors. To bridge the gap, a semi-automated Day Reconstruction Method was proposed which leverages 24-hour multimodal data collected by smart wristband (Fitbit Versa), paired mobile phone (Red Mi 6), and time management application (RescueTime). A pilot study was conducted to verify the feasibility of this proposed method and is reported in this paper. As academic engagement among adolescents is widely concerned by stakeholders, this pilot study also explores the relationship between the aforementioned contextual factors and academic engagement. With some interesting patterns, revealed, this study contributes to furthering our understanding of how context shapes adolescents’ academic engagement using a more objective and nonintrusive method.
An Exploratory Study of Social Media Analysis for Rare Diseases Using Machine Learning Algorithms: A Case Study of Trigeminal Neuralgia

Rare diseases, affecting approximately 30 million Americans, are often poorly understood by clinicians due to lack of familiarity with the disease and proper research. Patients with rare diseases are often unfavorably treated, especially those with extremely painful chronic orofacial rare disorders. In the absence of structured knowledge, such patients often choose social media to seek help from peers within patient-oriented social media communities thereby generating tremendous amounts of unstructured data daily. We investigate whether we can organize this unstructured data using machine learning to help members of rare communities find relevant information more efficiently in real-time. We chose Trigeminal Neuralgia (TN), an extremely painful rare disorder, as our case study and collected 20,000 social media TN posts. We categorized TN posts into Twitter (very short), and Facebook (short, medium, long) datasets based on message length and performed three clustering experiments. Results revealed GSDMM outperformed both K-means and Spherical K-means in clustering Facebook especially for short messages in terms of speed. For long messages, MDS reduction outperformed the PCA when both were used with K-means and Spherical K-means. Our study demonstrated the need for further topic modeling to utilize among high level clusters based on semantic analysis of posts within each cluster.
Evaluating 'Prefer not to say' Around Sensitive Disclosures

As people's offline and online lives become increasingly entwined, the sensitivity of personal information disclosed online is increasing. Disclosures often occur through structured disclosure fields (e.g., drop-down lists). Prior research suggests these fields may limit privacy, with non-disclosing users being presumed to be hiding undesirable information. We investigated this around HIV status disclosure in online dating apps used by men who have sex with men. Our online study asked participants (N=183) to rate profiles where HIV status was either disclosed or undisclosed. We tested three designs for displaying undisclosed fields. Visibility of undisclosed fields had a significant effect on the way profiles were rated, and other profile information (e.g., ethnicity) could affect inferences that develop around undisclosed information. Our research highlights complexities around designing for non-disclosure and questions the voluntary nature of these fields. Further work is outlined to ensure disclosure control is appropriately implemented around online sensitive information disclosures.
WHO EMRO | Molecular epidemiology and evolution of A(H1N1)pdm09 and H3N2 viruses in Jordan, 2011−2013 PDF version

Understanding the genetic evolution of A(H1N1)pdm09 and H3N2 viruses can help better select strains to be included in the annual influenza vaccine. There is little information on their evolution in Jordan so this study investigated the genetic and antigenic variability of A(H1N1)pdm09 and H3N2 viruses in Jordan by performing phylogenetic and genetic analyses of the HA and NA genes of A(H1N1)pdm09 and H3N2 viruses between 2011 and 2013. The full HA and NA genes of 16 H1N1-positive samples obtained in our study and 21 published HA sequences and 20 published NA sequences from Jordanian viruses that were available on online gene databases were analysed. For H3N2, we generated 20 HA and 19 NA sequences and included 19 published HA and NA sequences each in the analysis. Jordanian H1N1 viruses had mutations that are characteristic of antigenic group 6 while H3N2 virus mutations belonged to group 3. No markers of resistance to oseltamivir were detected. The individual mutations are described in detail.
Classiﬁcation of 3D Shapes with Convolutional Neural Networks

This project explores how to apply convolutional neural networks to efﬁciently classify 3D shapes. Using 3D shapes from the ShapeNet project [1], they are ﬁrst centered, rescaled and resampled to occupancy voxel grids of dimension 30 x 30 x 30. We implement 3D convolutional neural networks operating directly on these three dimensional volumes, as well as 2D convolutional networks operating on a learned embedded from the 3D model. Results from both methods are state-of-the-art compared to existing, published methods.
Modeling of the Market-Manufacturing System Relationship

In order to progress in the present-day complex and unpredictable environment, the company must feature abilities of quick response and favorably reposition itself on the market. Acquisition and preservation of this capacity is the most difficult step for companies as it involves many endogenous and exogenous factors and the process is continuous, dynamic and hardly predictable. The paper goal is a new approach of the manufacturing systems market assembly, with a view to finding the quantities that characterizes it, the laws that govern it, the relationships that describe it, and on this basis, to design a competitive management system of the assembly as a whole. The approach is general, but the application is focused on the manufacture of mechanical products, in small and medium series, always taking into account the dynamics of the interaction factors such as capital, market and system.
IIU: Specialized Architecture for Inverted Index Search

Inverted index serves as a fundamental data structure for efficient search across various applications such as full-text search engine, document analytics and other information retrieval systems. The storage requirement and query load for these structures have been growing at a rapid rate. Thus, an ideal indexing system should maintain a small index size with a low query processing time. Previous works have mainly focused on using CPUs and GPUs to exploit query parallelism while utilizing state-of-the-art compression schemes to fit the index in memory. However, scaling parallelism to maximally utilize memory bandwidth on these architectures is still challenging. In this work, we present IIU, a novel inverted index processing unit, to optimize the query performance while maintaining a low memory overhead for index storage. To this end, we co-design the indexing scheme and hardware accelerator so that the accelerator can process highly compressed inverted index at a high throughput. In addition, IIU provides flexible interconnects between modules to take advantage of both intra- and inter-query parallelism. Our evaluation using a cycle-level simulator demonstrates that IIU provides an average of 13.8\times× query latency reduction and 5.4\times× throughput improvement across different query types, while reducing the average energy consumption by 18.6\times×, compared to Apache Lucene, a production-grade full-text search framework.
Sustainability of cooperation in dynamic games played over event trees when players have asymmetric beliefs

We built a time-consistent cooperative solution for the class of dynamic games played over event trees in the context where the structure of the tree is given, but the players have different beliefs about the transition probabilities between nodes. Our three-step approach is as follows. First, we consider three alternative methods for aggregating the players probability distributions, and assume that the players agree to adopt one of them if they decide to cooperate. Second, we determine the Nash bargaining outcomes for the whole duration of the game. Finally, to insure sustainability of cooperation throughout the whole duration of the game, we propose two time-consistent decompositions over nodes of each player’s cooperative share, namely, a proportion-consistent and a node-consistent allocation. We illustrate our results with a simple Cournot oligopoly with capacity constraints.
A new SDN-based framework for wireless local area networks

Nowadays wireless networks are becoming important in personal and public communication andgrowing very rapidly. Similarly, Software De ned Network (SDN) is an emerging approach to over-come challenges of traditional networks. In this paper, a new SDN-based framework is proposedto ne-grained control of 802.11 Wireless LANs. This work describes the bene ts of programmableAccess Points. The proposed framework is evaluated on a prototype. We show that this architectureallows us to react to application needs, adjust network con guration for a priority application, detectnetwork problems, and improve the user experience of the network. Our architecture relies on theIEEE 802.11 standard, and exploits it to collect information from the stations.
Religiosity, the Use of Online Media, and the Youths’ Prosocial Behavior in Aceh

This study aims to look at the effect of religiosity and the use of online media on the youths’ prosocial behavior in Aceh. This study involved 12 state secondary schools in the province of Aceh by using a non-proportionate sampling technique of 402 students’ participants. Research data were collected using three scales, (1) religiosity using SPPIM-R from Azma (2006), (2) using online media, and (3) prosocial behavior using PTM-R from Carlo (2011). Data were analyzed by using multiple regression analysis and t-test. The results of this study showed a significant positive relationship between religiosity (r = .556; p <.00) and social media (r = .361; p <.00) with student prosocial behavior. It also demonstrates a significant influence between the main variables and student demographics on prosocial behavior (R2 = 0.528; p <0.00). The conclusion of the study shows that the variable of religiosity and the use of online media can influence prosocial behavior variables (52.8%). Respondents of this study developed the average-level of religiosity, whereas women were more religious using other languages. While the average level of prosocial online media use is medium, the female student group is the more frequent users of online media compared to their male counterparts. However, respondents in this study had an averagely medium level of prosocial behavior too, the male student group was more prosocial compared to the female students.
A TWO-STEP CLUSTER MODEL OF THE EMOTIONAL INTELLIGENCE AND LEADERSHIP STYLE PREFERENCES OF FOUR-STAR HOTEL EMPLOYEES

Purpose- The main objective of this study is to determine the leadership style preferences of four-star hotel employees based on their emotional intelligence (EI) profiles and demographics. Design/methodology- Data were collected from a sample of 190 four-star hotel employees. Descriptive statistics were used in identifying the level of employees' emotional intelligence and the leadership styles preferred in the sampled hotels. Further, two-step cluster analysis was used in clustering the respondents based on their level of emotional intelligence and their leaders’ leadership styles/demographic profiles. Findings- Two clusters emerged: low EI cluster of employees (44.21% of study sample) and high EI cluster of employees (57.79% of study sample). The low EI cluster is predominantly single, male, having 1–3 years of working experience and educational level less than high school; the high EI cluster are mostly married, female, with 4–6 years of working experience and have diplomas. However, employees from both clusters expressed preference for transformational leadership. Originality/value- The study extends prior research that identified employees’ EI, preferred leadership styles from employees’ perception and developed an EI model for evaluating hotel employees. The result could be used in soft-skills training need determination in hotel industry.
Topoisomerase IB: a relaxing enzyme for stressed DNA

DNA topoisomerase I enzymes relieve the torsional strain in DNA; they are essential for fundamental molecular processes such as DNA replication, transcription, recombination, and chromosome condensation; and act by cleaving and then religating DNA strands. Over the past few decades, scientists have focused on the DNA topoisomerases biological functions and established a unique role of Type I DNA topoisomerases in regulating gene expression and DNA chromosome condensation. Moreover, the human enzyme is being investigated as a target for cancer chemotherapy. The active site tyrosine is responsible for initiating two transesterification reactions to cleave and then religate the DNA backbone, allowing the release of superhelical tension. The different steps of the catalytic mechanism are affected by various inhibitors; some of them prevent the interaction between the enzyme and the DNA while others act as poisons, leading to TopI-DNA lesions, breakage of DNA, and eventually cellular death. In this review, our goal is to provide an overview of mechanism of human topoisomerase IB action together with the different types of inhibitors and their effect on the enzyme functionality.
University of Dundee A Systematic Review of Theoretical Foundations for Pedagogical Strategies to Promote Positive Behavior

This study analysed the theoretical foundations utilised by past empirical research in order to understand the pedagogical strategies used in schools for promoting positive behaviour. The analyses also include how pedagogical theories underpinned past research on positive behaviour enhancement. Samples for this study were academic papers obtained from four main databases: the Australian Education Index, British Education Index, ERIC (Educational Research Information Centre) and Scopus. By using a systematic review technique, a total number of 143 papers were found to be relevant for further analysis. Results revealed that four theoretical models dominate the studies examined, namely Applied Behavioural Analysis, Social Capital theory, Culturally Responsive Classroom Management, and Ecological Systems theory. This study recommends understanding of those theories is important in designing modules for positive behaviour enhancement in schools.
Optimization of surface determination to improve the accuracy of detecting unfused powder in AM Aluminium component

Additive manufacturing (AM) is quickly being recognized as a core technology for producing complex and customized components, so the need for well understood non-destructive testing is more urgent than ever. The mechanical properties of cast components are well studied and non-destructive testing is well established by various methods like XCT and ultrasound. On the other hand, there are big challenges for NDT with regard to additive manufactured components as the pores are different in nature from those found in cast alternatives. In additive manufactured components, the pores could be hollow, filled with partially fused powder or unfused powder. Furthermore, porosity could be due lack of fusion of un-melted powder (low laser energy) or balling up effect (too high laser energy). There is also the possibility of unfused powder within the internal architecture of complex components. In such cases XCT becomes an essential detection tool.
Investigation of a bacterial pathogen isolated from farmed Ompok pabda

Studies were conducted to isolate and identify a pathogen collected from the hemorrhagic ulcer offarmed Ompok pabda and to determine the pathogenic potentiality as well as antibiotic susceptibility of therecovered isolate. Infected fish were collected from a local fish farm located at Ishwarganj underMymensingh district, Bangladesh. The bacterial isolate was identified by using Hi Assorted™ BiochemicalTest kit and further investigated to determine the antibiotic susceptibilities. To determine the virulence, achallenge model was performed using the experimental bacterium, Ar-9 by intramuscular injection of O.pabda. A total of 50 healthy experimental fish (2.3±0.44 g) were used in another challenge test by usingsingle intramuscular injection with a pre-fixed dose (107 CFU/ fish) to find out the therapeutic effects ofvarious available antibiotics. The results demonstrated that the collected isolate was Gram-negative rodshaped bacterium exhibiting non-wrinkled, smooth and slightly yellowish colony on TSA from 8 to 42⁰C. Biochemical identification revealed that causative bacterium (Ar-9) was Aeromonas sp. that showed variablesusceptibilities against different antibiotics but marked resistance to ampicillin. Ar-9 was found virulent (LD50= 2.2× 106.0) to O. pabda. Moreover, experiment on the therapeutic effects against the infectivity of Ar-9revealed that CFCIN have successfully recovered 100% of challenged fish followed by O. T. C. power,Tylovet and ATIVET. Thus, the present study revealed a virulent and ampicillin resistant pathogenicbacterium which may be harmful in pabda culture in Bangladesh.