Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards Understanding the Impact of Real-Time AI-Powered Educational Dashboards (RAED) on Providing Guidance to Instructors

The objectives of this ongoing research are to build RealTime AI-Powered Educational Dashboard (RAED) as a decision support tool for instructors, and to measure its impact on them while making decisions. Current developments in AI can be combined with the educational dashboards to make them AI-Powered. Thus, AI can help in providing recommendations based on the students’ performances. AIPowered educational dashboards can also assist instructors in tracking real-time student activities. In this ongoing research, our aim is to develop the AI component as well as improve the existing design component of the RAED. Further, we will conduct experiments to study its impact on instructors, and understand how much they trust RAED to guide them while making decisions. This paper elaborates on the ongoing research and future direction.
Optimal Portfolio Choice under Hidden Regime Switching Model

We investigate a portfolio optimization problem in a continuous-time Markov-modulated financial market. The unobservable mean return of a risky asset follows a continuous-time, two-state Markov chain whose states are interpreted as different states of market. Using results from filter theory, we reduce this problem to one with complete observation. We solve the problem by stochastic control methods and the optimal portfolio can be explicitly characterized by stochastic integrals. The Monte Carlo simulations are implemented to compute the optimal portfolio allocations. The results show that state uncertainty have a great influence on optimal portfolio choice. The parameter uncertainty prompts the investor to hedge against unanticipated changes in the state variables.
An investigation of pulmonary findings of Crimean-Congo haemorrhagic fever patients.

Survival of inoculants in grass silages may enable them to improve the quality of silages through enrichment with polyunsaturated fatty acids (PUFAs). The effects of 2 inoculants, Enterococcus faecium 2/3s (EF2/3s) and E. faecium 26/42 (EF26/42), on nutrient composition, fermentation parameters, and fatty acid content in grass silages during ensiling (111 days) of fresh grass (G) were examined under laboratory conditions. The G [285 g of dry matter (DM) kg-1] was ensiled in 36 polyethylene jars (1 L) divided into 3 × 12 sets per treatment and ensiled at 21 °C for 111 days. The 3 silage treatments used were: 1) grass without inoculant (GS, control), 2) grass inoculated by the strain EF2/3s (GS+EF2/3s), and 3) grass inoculated by the strain EF26/42 (GS+EF26/42). The inoculant strains were sufficiently established during ensiling and reached 4.62 log10 cfu g-1 for EF2/3s and 3.76 log10 cfu g-1 for EF26/42 on day 111 of ensiling. Crude protein contents were G > GS+EF2/3s > GS+EF26/42 > GS (129, 110, 109, and 100 g kg-1 of DM, respectively). The lactate-to-acetate ratios were GS < GS+EF26/42 < GS+EF2/3s (2.82, 4.20, and 4.70, respectively). Concentrations of a-linolenic acid and g-linolenic acid were highest in grass before ensiling (P < 0.001). Higher isomer C18:2 (9,11) content (P < 0.01) was detected in GS+EF2/3s and GS+EF26/42 than in GS. Nutritional manipulation associated with Enterococcus faecium EF2/3s and EF26/42 inoculation of GS resulted in better quality of silages based on lower lactate (GS+EF26/42) and a greater lactic-to-acetic acid ratio (GS+EF2/3s and GS+EF26/42). This might positively affect PUFAs and their isomers.
EPKF: Energy Efficient Communication Schemes Based on Kalman Filter for IoT

The Internet of Things (IoT) has been recognized as the next technological revolution. It faces two challenges: 1) how to achieve energy efficient communication for the battery constrained devices and 2) how to connect a very large number of devices to the Internet with low latency, high efficiency, and reliability. To address these problems, this paper proposes two methods based on Kalman filter (KF), termed as extensions of predicable KF (EPKF). They locally reduce the unnecessary transmission (access) of end devices to the network (Internet) utilizing the spatial and temporal correlations with low algorithmic overhead. Each transmitting device (TD) independently controls its transmission using the temporal correlation; and the receiving device (RD) exploits the spatial correlation among the TDs to further improve the reconstruction quality. The reconstruction problem in the RD is nonlinear. To reduce the computation complexity, an in-depth analysis of the local estimate error is conducted and the approximated linear solutions are thereupon obtained. They are fundamental methods applicable to any IoT monitored/controlled physical system that can be modeled as a linear state space representation. The pedestrian-position application is used as a case study to demonstrate the efficiency in the simulation. Remarkably, the EPKF methods using the linear combinations of the local estimates from multiple TDs reduce the transmission rate to 10%, while achieving the same reconstruction quality as using KF in the traditional manner.
Spatially Consistent Coarse-Mesh Discretization of the Low-Order Quasidiffusion Equations in 2D Geometry

In this paper, we develop spatially consistent coarse-mesh discretization method for the 2D low-order quasidiffusion equations for the full-core calculations. The coarse-mesh solution generated by this method preserves a number of spatial polynomial moments of the fine-mesh transport solution over coarse cells. The proposed method reproduces accurately the complicated large-scale behavior of the transport solution within assemblies. To demonstrate accuracy of the developed method, we present numerical results of calculations of test problems that simulate interaction of MOX and uranium assemblies.
Hierarchical reinforcement learning in multiplayer Bomberman

Experiments have been conducted to compare winrates of an agent obtained with hierarchical reinforcement learning and flat reinforcement learning on the multiplayer mode of the videogame Bomberman. The performance between a single network, two networks and four networks have been compared. Four bombermen are placed together in an arena. This arena contains walls, which are always placed in the same location at the start of each game. Bombermen and some of these walls can be destroyed by exploding bombs. These bombs are placeable by the bombermen. Multilayer perceptrons are used to approximate the utility of each state-action pair used in Q-learning. The exploration strategies used are Error-Driven-epsilon, which is a variant on Diminishing epsilon-Greedy, and Max-Boltzmann. Each trial consisted of a hundred generations of 10,000 training games with 100 test games. A significant difference in results has been found with both exploration strategies. The winrate during the first twenty generations is higher for both the two networks and four networks experiments. After this, the winrate becomes lower in comparison to flat reinforcement learning.
Monitoring Polychlorodibenzo-P-Dioxins and Furans in Eggs and Feed in Egypt

A total of 150 samples (120 eggs , 17 plant origin feed, 9 Animal By-product and 3 feed Additives samples) were collected from different 36 farms in Egypt and analyzed for polychlorodibenzo-p-dioxins (PCDDs) and polychloro-dibenzo-furans (PCDFs) allowing more detailed discussions of different aspects of the relative importance of these individual congeners. The total PCDD/Fs WHO-TEQ levels in Eggs and feed were determining by High Resolution Gas Chromatography High Resolution Mass Spectrometer (HRGC-HRMS) ranged from 0.33:4.51 pg WHO-TEQ/g lipid weights in Eggs. The results of this study showed that the contribution of ∑ PCDDs is 31% and ∑ PCDFs is 69% in egg out of ∑PCDD/Fs. This study showed that the PCDD/Fs levels in eggs were almost below the Egyptian permissible limits for PCDD/Fs (3pg WHO-TEQ/g fat). The consumption of Egyptian people for eggs attained According to GEMS/Food World Health Organization (WHO) consumption rate of egg for the Middle Eastern people =14g/per/day which showed that the Estimated Daily Intake (EDI) of ∑PCDD/Fs of the Egyptian consumer is 0.38 (pg WHO-TEQ/kg b.w/day) lower than the WHO acceptable daily intake which is 1-4 pg WHO-TEQ/ kg b.w/day.
GLOBALISATION AND SUSTAINABLE SOCIO-ECONOMIC DEVELOPMENT: WHAT HOPE FOR MSMEs IN THE 21ST CENTURY NIGERIA?

The study evaluated the influence of globalisation on sustainable socioeconomic development within the context of micro, small and medium-scale enterprises (MSMEs) in the contemporary Nigerian society. The central thrust of the study was to assess the influence of Harvard Research and Publications International December 31, 2019 Vol. 11 No. 2 ISSN: 0081 – 3998 JOURNAL OF AFRICAN SUSTAINABLE DEVELOPMENT INTRODUCTION The contribution of micro, small and medium-scale enterprises (MSMEs) to national development as experienced in many countries of the world, mostly the ‘Asian tigers’ such as China, Malaysia, Indonesia and India among others, shows that entrepreneurship contributes substantially to national development, most especially in this contemporary regime of globalisation, trade liberalisation and deregulated market economy. The experiences of those countries certainly serve as an impetus to a developing economy, such as Nigeria, where poverty level is on a very high side. The incidence of poverty in Nigeria, where over 70 per cent of the total population is being classified as poor is highly worrisome (Aremo & Aiyegbusi, 2011 as cited in Ojapinwa, 2014). The rate of poverty in
Effective Forum Curation via Multi-task Learning

Despite several advantages of online education, lack of eﬀec-tive student-instructor interaction, especially when students need timely help, poses signiﬁcant pedagogical challenges. Motivated by this, we address the problems of automatically identifying posts that express confusion or urgency from Massive Open Online Course (MOOC) forums. To this end, we ﬁrst investigate the extent to which the tasks of confusion detection and urgency detection are correlated so as to explore the possibility of utilizing a multitasking set-up. We then propose two LSTM-based multitask learning frameworks to leverage shared information and transfer knowledge across these related tasks. Our experiments demonstrate that the approaches improve over single-task models. Our best-performing model is especially useful in identifying posts that express both confusion and urgency, which can be of particular relevance for forum curation.
Predicting Student Dropout by Mining Advisor Notes

More Americans are attending college than ever before but almost half of them do not complete college. Thus, early detection of students at risk of dropping out of college is of paramount importance. This study describes a novel attempt at using notes made by student advisors to predict student dropout. We use a Natural Language Processing (NLP) technique called sentiment analysis to analyze unstructured textual data to extract the positive or negative sentiment contained in the advisor’s notes. We then use the sentiment extracted from the notes as features to train a random forest model to predict student dropout. We achieve 73% accuracy in predicting student dropout. Thus, our study demonstrates the value of unstructured data held in institutional databases for identifying at-risk students.
A-PRIORI EVALUATION OF THE POLLUTION ERROR FOR FINITE ELEMENT ACOUSTIC PROBLEMS

This paper examines the a-priori assignment of polynomial order in the p-version of the FEM for the efficient simulation of time-harmonic acoustic problems. An error indicator is proposed, which accounts not only for the local interpolation error, but also for the accumulation of phase errors (i.e. the so-called pollution effect). The finite element mesh is traversed using a variant of the breadth first search, a strategy developed for graph numbering. The local phase error is computed from a dispersion analysis performed on a one-dimensional element of equivalent size. The proposed method is verified on several academic Helmholtz problems including non-uniform meshes.
Reconfigurable Pipelined Control Systems

Editor’s notes: As sensor data processing, e.g., from video cameras, is becoming more compute intensive, it is also introducing higher sensor-to-actuator delays. This article studies cross-layer schemes that co-design a controller together with sensor data processing in a pipelined fashion on multicore embedded processors. –Samarjit Chakraborty, University of North Carolina at Chapel Hill
The Djibouti francolin and juniper forest in Djibouti: the need for both ecosystem and species-specific conservation

Abstract The majority of Galliformes are ground dwelling, many live in forests, and c. 25% are on the IUCN Red List. The Djibouti francolin Francolinus ochropectus is a Critically Endangered galliform endemic to only two areas of relict Juniperus procera forest in Djibouti. This study assessed population status and habitat condition in the species' stronghold in the Forêt du Day during the post-breeding season. Line transect distance sampling was used to survey the francolin, recording visual encounters and calls. Canopy and understorey vegetation were sampled across the study area at 150-m intervals using 400-m2 quadrats. Interviews were conducted in all adjacent villages to obtain information about francolin sightings, forest use and capacity for community-based conservation. Distance was used to generate francolin population density estimates. A geographical information system and generalized linear modelling were used to determine predictors of francolin presence and juniper condition. The Distance model estimated francolin density to be 38–94 km-2. Within the Forêt du Day this is equivalent to a population of 285–705 individuals. The presence of juveniles in the samples suggests that the effective population size may be lower and therefore, although this is the first estimate of Djibouti francolin density using standard survey methodology, it should be interpreted cautiously. Juniper condition in the Forêt du Day is poor. The healthiest forest is 50% dead. Francolins are more abundant where tree cover is high. This cover now mostly consists of Buxus hildebrandtii, which appears to have mostly replaced the original juniper. In areas of high tree cover, grazing intensity is significantly negatively correlated with francolin presence. Anthropogenic influences on juniper health and francolin decline are mediated through the large number of cows grazing in the forest. We recommend an ecosystem approach to conservation of the forest, with additional species-specific protection measures for the francolin and juniper.
Caspar SUMOylation regulates Drosophila lifespan

Figure 1: Generation and characterization of a caspK551R transgenic fly by CRISPR/Cas9 genome editing. (A) Casp is a negative regulator of IMD/NFkB signaling. Casp negatively regulates DREDD activity. DREDD is the protease responsible for cleavage/maturation of Relish (Rel), in response to IMD signaling and leads to the subsequent release of its N-terminal fragment Rel68, which travels to the nucleus to activate transcription. (B) Domain structure of Casp. Casp is orthologous to mammalian Fas associated factor 1 (FAF1) and contains an N-terminal Ubiquitin interaction domain (UBA), a ubiquitin-like (UAS) self-association domain and a C-terminal Ubiquitin regulatory domain (UBX). UBA domains are known to interact with Ubiquitin (Ub) and polyUb-chains (connected circles) while UBX binds specifically to the Transitional-ER-ATPase 94 (TER94; also known as valsolin containing protein -VCP or p97), which is member of the degradative Ub-proteasomal recycling system (Tresse et al., 2010). The site of Casp SUMOylation (K551) (Handu et. al., 2015) is marked in red on the figure. Double-headed arrows indicate non-covalent interactions between Casp and other proteins (C) Generation of putative lines for screening. 350 0-3 hour old embryos expressing Act5c-Cas9 along with the gRNA were injected with a 100 bp donor single-stranded oligonucleotide (ssODN). Adult males (n=123, one male per vial) that developed from these embryos were crossed to IInd chromosome balancer females as a first step to stabilize putative mutant lines. Next, individual single parent crosses were set up to generate homozygous lines that were used to screen for mutants. (D) Screening for the caspK551R mutant. PCR primers were designed to amplify 566 bp region spanning the site of mutation within the casp locus. A unique BssHII restriction site was engineered in the ssODN, allowing the successful genomic integration to be identified by a simple restriction digest. Representative PCRs from 225 lines confirm that two lines, 7A and 17C incorporated the ssODN by homologous recombination. Animals where the wildtype genome was retained (6C, 17B, 7B & 18A) were resistant to BssHII digestion and could be used as CRISPR controls. 8/2/2020 Open Access For the two positives lines 7A and 17C, two digestion bands of 350 bp and 216 bp were obtained (Arrows, lanes 8 & 10), confirming successful genome editing. This was further confirmed by DNA sequencing of the casp genomic region. (E) Survival plot for caspK551R transgenic lines for both uninfected and infected. The homozygous caspK551R mutant lines show a shortened lifespan. This lifespan is further shortened when animals are infected with gram-negative E. coli. The data were analyzed using Log-rank test of trend (F) Tabulation of median lifespan for Casp SUMO mutants along with all relevant controls. Values for the Median lifespan extracted from survival data were plotted using GraphPad 8.
Mitochondrial DNA variation among populations of Oedura reticulata (Gekkonidae) in remnant vegetation: implications for metapopulation structure and population decline

Restriction fragment length polymorphism (RFLP) analysis of mitochondrial DNA was used to examine the regional population structure of a species of gecko (Oedura reticulata) in vegetation remnants within the Western Australian wheatbelt. The species exhibited considerable polymorphism within and between populations with 22 haplotypes recognized among 12 populations. Phylogenetic analysis of haplotypes and clustering of nucleotide divergence among populations demonstrated little regional structure within the species with several haplotypes present in all three regions surveyed. This contrasted markedly with variation in haplotype frequency among populations which showed a high degree of independence between populations indicating that current levels of maternal gene flow are low and that the populations are too small to prevent genetic drift. This conclusion is supported by generally lower numbers of haplotypes in remnant populations than in nearby nature reserves. These findings, combined with demographic data from a previous study, suggest that post‐fragmentation populations of O. reticulata are unable to form a metapopulation structure in the habitat that remains and that stochastic extinction forces alone will be sufficient to severely reduce the regional distribution of this species. This study demonstrates that mtDNA is a useful tool for detecting contemporary population phenomena and can provide qualitative information of practical importance to wildlife managers.
Elliptic curves over finite fields with Fibonacci numbers of points

For a prime power q and an elliptic curve E over Fq having q + 1− a points, where a ∈ [−2√q, 2√q] let {#Em}m≥1 be the sequence of numbers whose mth term is the number of points of E over Fqm . In this paper, we determine all instances when #({#Em}m≥1 ∩ {Fn}n≥1) ≥ 2, where {Fn}n≥1 is the sequence of Fibonacci numbers. That is, we determine all six–tuples (a, q,m1,m2, n1, n2) such that #E = q + 1− a, #Em1 = Fn1 and #Em2 = Fn2 .
Image Super-Resolution Via a Convolutional Neural Network

Super-resolution is the task of constructing a higher-resolution image from a lower-resolution image. While this task has traditionally been approached with non-neural methods such as bilinear and bicubic upsampling, neural networks offer an opportunity for signiﬁcant improvements. We implement a Super-Resolution Convolutional Neural Network (SRCNN), as proposed by Dong et al. [2] and demonstrate improvements over the bicubic upsampling baseline test peak signal-to-noise ratio (PSNR) of 23.226 dB with a test PSNR of 26.442 dB
Numerical Simulation on Subcooled Pool Boiling

In this paper, the numerical simulations based on the MARS (Multi-interface Advection and Reconstruction Solver) with a phase-change model including the bubble growth and the condensation processes are performed. As the results, it was found that the numerical results for both bubble growth and condensation rates were very slow compared with the experimental results and the existing analytical model. In order to solve this discrepancy, the original model is improved by introducing the following models based on the quasi-thermal equilibrium state: (1) the improved phase-change model including the large density change between water and vapor; (2) a relaxation time model derived by considering the unsteady heat conduction. Resulting from the numerical simulation with the present improved model, the numerical results in both bubble growth and condensation processes show in good agreement with the experimental results and the existing analytical model.
An interactive tool for yarn strength prediction using support vector regression

Cotton, popularly known as White Gold has been an important commercial crop of National significance due to the immense influence of its rural economy. Transfer of technology to identify the quality of fibre is gaining importance. The physical characteristics of cotton such as fiber length, length distribution, trash value, color grade, strength, shape, tenacity, density, moisture absorption, dimensional stability, resistance, thermal reaction, count, etc., contributes to determine the quality of cotton and in turn yarn strength. In this paper yarn strength prediction has been modeled using regression. Support Vector regression, the supervised machine learning technique has been employed for predicting the yarn strength. The trained model was evaluated based on mean squared error and correlation coefficient and was found that the prediction accuracy of SVR based model, the intelligence reasoning method is higher compared with the traditional statistical regression, the least square regression model.
Persistent Mode MgB $_{2}$ Short Windings

Feasibility of industrial production of MgB2 cables and magnets has been established, thus leading to MRI systems realization. Apart from continuing the development in performances of both cable and magnet, a further important step consists in applying superconductive junctions to windings, to obtain a better field stability. In 2006 a technique to obtain some tens of Ampere in persistent mode operation in a joined MgB2 cable was found. Since then, short windings were repetitively built to test the progress of the performances of the junctions. Among them, a single junction, five meter long windings with a diameter of 260 millimeter were put in persistent mode (i. e. with total resistance less than 10-14 Ohm) with 300 Ampere circulating at 20 Kelvin, self-field; also windings with two junctions and about one meter long with the same diameter were put in persistent mode with 200 Ampere circulating at 20 Kelvin, self-field.