Miracle-dz/UniFAR-FTUs huggingface dataset:
Screening of horsegram accessions towards Pulse beetle, Callosobruchus chinensis (Linnaeus.) under laboratory condition

Screening studies of horsegram accessions towards pulse beetle, Callosobruchus chinensis under laboratory conditions were carried out at Regional Research Station, Paiyur during the year 2016 for a period of nine months. The results showed that the maximum number of eggs were laid in only two accessions viz., Poonamalli 2 (70.0 No.s) and in Hosur 3 (65.5 No. of eggs). The minimum number of eggs was laid in only one accession in case of KPT 20 Kr (10 eggs) which contributed for bruchid resistance. The maximum number of accessions (385 Nos) fall under the category of 10-20 eggs laid followed by 274 accessions with laid eggs of 20-30 Nos and seventy nine accessions with egg laying capability of 30-40 Nos per accession. Out of 760 accessions, fifty per cent of accessions contributed for resistance, 36.05 per cent for moderate resistance and 21.0 per cent towards moderate susceptible to susceptible nature to C. chinensis. The per cent loss studies due to bruchids showed that the per cent loss ranged from 0.0-15.46 and the highest 15.46 was reported in 12 accessions tested. The highest number of eggs laid (35.0 Nos) and 4.5 seed damage was reported in PYR 2 variety. The lowest number of eggs was laid in Paiyur Acc 15 (15.5 Nos) with six per cent of affected seeds. The per cent affected seeds were found to be highest in Paiyur Acc 3 with 20 per cent damage.
Chemical properties, antioxidant activities and in vitro fermentation profiles of some shrubs of North Western Tunisia

The main aims of this study were to analyze the chemical composition and total phenolic, and to evaluate the in vitro fermentation and antioxidant activities from some shrubs (Erica arborea, Myrtus communis, Arbutus unedo and Phillyrea latifolia). The determination of the chemical composition, total phenolic, flavonoid contents and the antioxidant activity were investigated by using in vitro methods. The in vitro gas production and ruminal parameters were determined in the presence of goat rumen juice. Total nitrogen content was significantly high with Myrtus communis (p less than 0.01). Total phenolic and flavonoid content vary by species and season (p less than 0.01). It can be concluded that all parameters were significantly affected by the seasonal period and the shrubs nature. Expect the OM that was similar regardless the seasonal period.
High Performance CNN Accelerators Based on Hardware and Algorithm Co-Optimization

Convolutional neural networks (CNNs) have been widely used in image classification and recognition due to their effectiveness; however, CNNs use a large volume of weight data that is difficult to store in on-chip memory of embedded designs. Pruning can compress the CNN model at a small accuracy loss; however, a pruned CNN model operates slower when implemented on a parallel architecture. In this paper, a hardware-oriented CNN compression strategy is proposed; a deep neural network (DNN) model is divided into “no-pruning layers (<inline-formula> <tex-math notation="LaTeX">$NP$ </tex-math></inline-formula>-layers)” and “pruning layers (<inline-formula> <tex-math notation="LaTeX">$P$ </tex-math></inline-formula>-layers)”. A <inline-formula> <tex-math notation="LaTeX">$NP$ </tex-math></inline-formula>-layer has a regular weights distribution for parallel computing and high performance. A <inline-formula> <tex-math notation="LaTeX">$P$ </tex-math></inline-formula>-layer is irregular due to pruning, but it generates a high compression ratio. Uniform and incremental quantization schemes are used to achieve a tradeoff between compression ratio and processing efficiency at a small loss in accuracy. A distributed convolutional architecture with several parallel finite impulse response (FIR) filters is further proposed for the regular model in the <inline-formula> <tex-math notation="LaTeX">$NP$ </tex-math></inline-formula>-layers. A shift-accumulator based processing element with an activation-driven data flow (ADF) is proposed for the irregular sparse model in the <inline-formula> <tex-math notation="LaTeX">$P$ </tex-math></inline-formula>-layers. Based on the proposed compression strategy and hardware architecture, a hardware/algorithm co-optimization (HACO) approach is proposed for implementing a <inline-formula> <tex-math notation="LaTeX">$NP-P$ </tex-math></inline-formula> hybrid compressed CNN model on FPGAs. For a hardware accelerator on a single FPGA chip without the use of off-chip memory, a <inline-formula> <tex-math notation="LaTeX">$27.5\times $ </tex-math></inline-formula> compression ratio is achieved with 0.44% top-5 accuracy loss for VGG-16. The implementation of the compressed VGG-16 model on a Xilinx VCU118 evaluation board processes 83.0 frames per second (FPS) for image applications, this is <inline-formula> <tex-math notation="LaTeX">$1.8\times $ </tex-math></inline-formula> superior than the state-of-the-art design found in the technical literature.
The role of DA1 in organ size control in Arabidopsis thaliana

Despite the sizes of organs and organisms being a key defining feature, very little is known about how the final sizes of organs is determined. Recent progress has highlighted the important role of the DA1 peptidase as a negative regulator of organ size in Arabidopsis thaliana. Previous studies have proposed that DA1, and the E3 ligase BIG BROTHER (a protein known to regulate DA1 activity), work synergistically to regulate the duration of cell proliferation. In the prulresent study, we take a multidisciplinary approach to further our understanding of the biological activities of DA1 and BB. Protoplast transient expression analyses were used to explore potential new substrates for DA1 peptidase activity, and to work towards identifying a conserved target site for DA1mediated cleavage. Using confocal microscopy and bespoke segmentation software, I embarked on a global analysis of leaf cellular phenotypes in the da1-1, bb, and da1-1bb mutants throughout early development. This allowed a holistic comparison to wild type of parameters such as total cell number, and cell area, density, and circularity. In addition, scanning electron microscopy was used to examine cells in mature leaves of wild type, and da1-1, bb, and da1-1bb mutants, revealing novel insights into the control of final organ size in these mutants relative to wild type. Finally, innovative live cell imaging has, for the first time, allowed cell divisions to be observed in plants carrying the da1-1, bb, and da1-1bb mutations. My observations and interpretation establish new insights into how DA1 and BB control growth by controlling the arrest of cell proliferation, and the population-level rate of cell proliferation. The approaches I have developed show the promise of quantitative cell imaging for understanding organ growth, and establish a framework for precisely comparing the effects of different mutations on organ growth.
International financial reporting standards (IFRSs) adoption in Africa: Abibliometric analysis

Abstract Countries in Africa have since joined their counterparts in other regions of the world in adopting IFRSs with over 30 countries either requiring or permitting its use for its companies. This study contributes to academic literature as it presents a bibliometric analysis on the state of IFRS research in Africa. The analysis involves 73 published articles listed on Scopus database between 2005 and 2018. Key findings in the study indicate that the first research document on Scopus database on IFRS in Africa was in 2005, despite its early adoption since 1993 in Zimbabwe. There is a continued upward growth in the volume of publications and citations over the years. The year of first IFRSs adoption is not associated with the volume of publication. Top five leaders in the volume of publication on IFRSs include Tunisia and Egypt, these countries are yet to adopt IFRSs. The dominant subject areas on IFRSs research are Business, Management & Accounting, Economics, Econometrics & Finance and Social Sciences. Only 21 authors and 18 institutions out of over 600 institutions in Africa contribute more than one publication to IFRS research. These institutions and authors are all in six African countries (South Africa, Nigeria, Tunisia, Egypt, Uganda and Ghana). Recommendations from the result include the need for higher visibility of research on IFRS. Approximately 87% of the publications are non-open access and the need for more academic conference on IFRS as conference proceedings accounts for only 11%.
Knowledge Tracing Within Single Programming Practice Using Problem-Solving Process Data

Accurately tracing the state of learner knowledge contributes to providing high-quality intelligent support for computer-supported programming learning. However, knowledge tracing is difficult when learners have only had a few practice opportunities, which is often common in block-based programming. This article proposed two knowledge tracing models that can exploit the problem-solving process data generated by learners from a single programming task. A novel metric, the approaching index, was developed using the tree edit distance in abstract syntax trees to measure the similarities between the learners’ intermediate solutions and the optimal solution. The proposed method allows for each learner's programming path to be represented as a raw approaching index sequence (AISeq) or as a single variable (AIScore) by averaging the AISeq. A logistic regression model was first designed to predict the learners’ performances using their AIScore, the number of attempts, and their current performance. A second model, a recurrent neural network model, was also developed to directly use the AISeq and to make predictions. To verify the effectiveness of these models, a series of statistical analyses and experiments were conducted on two existing large-scale block-based programming datasets, the results from which revealed that the proposed models were competitive with four state-of-the-art models on multiple metrics, such as the precision-recall curve, accuracy, specificity, and Cohen's Kappa. Especially, the proposed models were found to be more robust than the compared models in predicting who would fail to complete the tasks.
Codon usage and amino acid identity are major determinants of mRNA stability in humans

mRNA degradation is a critical, yet poorly understood, aspect of gene expression. Previous studies demonstrate that codon content acts as a major determinant of mRNA stability in model organisms. In humans, the importance of open reading frame (ORF)-mediated regulation remains unclear. Here, we globally analyzed mRNA stability for both endogenous and human ORFeome collection mRNAs in human cells. Consistent with previous studies, we observed that synonymous codon usage impacts human mRNA decay. Unexpectedly, amino acid identity also acts as a driver of translation-dependent decay, meaning that primary protein sequence dictates overall mRNA levels and, consequently, protein abundance. Both codon usage and amino acid identity affect translational elongation rate to varying degrees in distinct organisms, with the net result being sensed by mRNA degradation machinery. In humans, interplay between ORF- and UTR-mediated control of mRNA stability may be critical to offset this fundamental relationship between protein sequence and mRNA abundance.
Evaluation of imputed genomic data in discrete traits using Random forest and Bayesian threshold methodsb

The objectives of this study were (1) to quantify imputation accuracy and to assess the factors affecting it; and (2) to evaluate the accuracy of threshold BayesA (TBA), Bayesian threshold LASSO (BTL) and random forest (RF) algorithms to analyze discrete traits. Genomic data were simulated to reflect variations in heritability (h 2 = 0.30 and 0.10), number of QTL (QTL = 81 and 810), number of SNP (10 K and 50 K) and linkage disequilibrium (LD=low and high) for 27 chromosomes. For real condition simulating, we randomly masked markers with 90% missing rate for each scenario; afterwards, hidden markers were imputed using FImpute software. In imputed genotypes, a wide range of accuracy was observed for RF (0.164-0.512) compared to TBA (0.283-0.469) and BTL (0.272-0.504). Comparing to original genotypes, using imputed genotypes decreased the average accuracy of genomic prediction about 0.0273 (range of 0.024 to 0.036). Comparing to Bayesian threshold, using RF was improved rapidly accuracy of genomic prediction with increase in the marker density. Despite the higher accuracy of BTL and TBA at different levels of LD and heritability, the increase in accuracy was greater for RF. Furthermore, the best method for prediction of genomic accuracy depends on genomic architecture of population.
High Gain and Wideband Metasurfaced Magnetoelectric Antenna for WiGig Applications

This communication presents a high gain wideband metasurfaced magnetoelectric dipole for wireless gigabit (WiGig) applications. The proposed antenna achieves wide bandwidth and low cross-polarization. In addition, peak gain is increased by employing a metasurface (MS) which is working as a partially reflective surface. The proposed idea is numerically and experimentally demonstrated. Full-wave analysis shows 10 dB impedance bandwidth of 53.47–80.26 GHz, corresponding to 40.5%, while the measured data achieve 39.3% with the frequency from 47.2 to 70.3 GHz. Meanwhile, the simulated and measured 3 dB gain bandwidth of the proposed antenna are 52.86–66.86 (23.3%) and 51.86–67 GHz (25.5%), respectively. Peak gain increased by 3.37–5.57 dB when including the MS; providing 11.9–13.65 dBi for 57–66 GHz, corresponding to the WiGig bandwidth.
Research into truck transmission torsion vibrations under longitudinal acceleration

The development of a modern motor vehicle is aimed at improving the performance in the fi eld of dynamics (both lon-gitudinal and lateral), economy, safety and ergonomic characteristics. Special attention is paid to passenger comfort. Torsional oscillations in transmission cause longitudinal vibrations of the vehicle, depending on inertial parameters, as well as on stiffness and damping of the transmission. Taking into account the complexity of the problem, it is esti-mated that it is useful to analyse the impact of the transmission design parameters on the longitudinal (fore and aft) vibrations of freight motor vehicle. For this purpose, the dynamic simulation method was used, and the analysis of the infl uence of certain constructive parameters on the longitudinal oscillations of the vehicle was performed using the sensitivity function.
Adaptive Repetitive Learning Control of PMSM Servo Systems with Bounded Nonparametric Uncertainties: Theory and Experiments

In this article, an adaptive repetitive learning control (ARLC) scheme is proposed for permanent magnet synchronous motor (PMSM) servo systems with bounded nonparametric uncertainties, which are divided into two separated parts. The periodically nonparametric part is involved in an unknown desired control input, and a fully saturated repetitive learning law with a continuous switching function is developed to ensure that the estimate of the unknown desired control input is continuous and confined with a prespecified region. The nonperiodically nonparametric part is transformed into the parametric form and compensated by designing the adaptive updating laws, such that a prior knowledge on the bounds of uncertainties is not required in the controller design. With the proposed ARLC scheme, a high steady-state tracking accuracy is guaranteed, and comparative experiments are provided to demonstrate the effectiveness and superiority of the proposed method.
Service-Oriented Fair Resource Allocation and Auction for Civil Aircrafts Augmented Space-Air-Ground Integrated Networks

In this paper, we present a civil aircrafts augmented space-air-ground integrated networks (CAA-SAGIN) architecture, where each mobile user can access multiple platforms simultaneously. With the target of ensuring fairness, we put forward the fair optimization strategies including resource allocation and resource auction. In the resource allocation, we formulate a service-oriented fair (SOF) resource allocation problem in order to minimize the difference between the allocated and required data rate. After introducing convex-relaxation and logarithmic approximation, the joint optimal solutions of subchannel and power allocation can be obtained by SOF iteration algorithm. Aiming at managing the terrestrial network overload, we present a user update mechanism. After applying SOF resource allocation for selected original users in sky access platforms, we propose a resource auction scheme so as to maximize the utility for both sides. First, we decompose the original problem into several subproblems and transform them into their lower bound by first-order approximation. Then, we can obtain the joint optimal solution with an alternating descent iterative method. From simulation results, we can find that CAA-SAGIN can bring great benefits to traditional terrestrial networks. In addition, the proposed resource allocation and auction schemes are significant in terms of telecommunication and economic parameters.
Where Do I Stand? Assessing Researchers' Beliefs About Their Relative Productivity

In 2017 the Italian government established the Fund to Finance Basic Research Activities – FFABR – with the purpose of assigning a 3,000 euros research grant to the most productive applicants among eligible assistant and associate professors. We show that, rather surprisingly, many low-productivity researchers applied to the program while many high-productivity ones did not. Our evidence from both a simple structural model of program participation estimated on registry data and a survey of the eligible population suggests that high-productivity researchers under-estimate their own position in the productivity distribution relative to the assignment threshold, while the opposite holds for low-productivity ones.
PRODUCTION CONSTRAINTS AND FARMERS’ CULTIVAR PREFERENCE CRITERIA OF CULTIVATED YAMS (DIOSCOREA CAYENENSIS - D. ROTUNDATA COMPLEX) IN TOGO

Fifty (50) villages randomly selected throughout agroecological zones in Togo were surveyed, using participatory approach, to identify and prioritize factors that affect production and farmers' varietal preference criteria of Guinea yam (Dioscorea cayenensis-D. rotundata complex). A total of nineteen (19) constraints of varying importance across agro-ecological zones were identified among which the most important were insects' damages on both leaves and tubers, nematodes attack on tubers, drought, soil poverty and wilting. For the majority (78.94%) of the constraints, the use of tolerant cultivars remains the most sustainable, economically profitable and environment preservative solution. Farmers' cultivar preference criteria identified are many (24 in total). Among them, high productivity, good quality of pounded yam, resistance to drought and adaptability to all types of soils are the most important. A perfect match is noted between enumerated constraints and identified preference criteria. The knowledge of farmers' selection criteria is of capital importance for breeders and also extension services for eventual yam cultivar exchange between agroecological zones in Togo.
Functional microbial stimulation for oil recovery enhancement based on microbial community analysis

Abstract This study stimulated functional microbial adaptation to the extreme environment of the Luliang oilfield reservoir and assessed the impact of indigenous microbial enhanced oil recovery treatment on the microbial community and oil recovery. By high-resolution pyro-sequencing, Acinetobacter, Pseudomonas, Sphingomonas, Thauera, Arcobacter and Hyphomonas were regarded as suitable candidates and a customised nutrient mixture was selected to activate the target microbes. The interfacial tension of crude oil and water decreased from 29.76 mN m−1 to 0.65 mN m−1 and the emulsion stability index increased from 5% to 92% after customised nutrient culture. The oil biodegradation experiments after the cultivation exhibited positive effects in degrading aromatics, resins and asphaltenes fractions and improving the mobility. Six target genera were activated markedly after 96 h of incubation. The oil recovery was enhanced from 51.2% to 60.7% using fermentation broth injection. Thus, injecting a customised nutrient mixture with injection brine into the stratum to stimulate functional microbes has the potential to enhance oil recovery in the Luliang oilfield.
Online Spatiotemporal Popularity Learning via Variational Bayes for Cooperative Caching

Herein, we focus on an end-to-end design of a proactive cooperative caching strategy for a multi-cell network. The design is challenging as it involves two interrelated problems: the ability to predict future content popularity and to meet network operation characteristics. To this end, we first formulate a cooperative content caching in order to optimize the aggregated network cost for delivering contents to users. An efficient proactive caching policy requires an accurate prediction of time-varying content popularity. Content popularity has temporal and spatial dependencies and therefore, we develop a probabilistic dynamical model for content popularity prediction by exploiting its spatiotemporal correlations. To achieve an accurate tracking and prediction of content popularity evolution, the proposed dynamical model is non-linear and incorporates non-Gaussian distributions. We use Variational Bayes (VB) approach for estimating the model parameters. The VB provides mathematical tractability. We then develop an online VB method that works with streaming data where content request arrives sequentially. Using extensive simulations study on a real-world dataset, we show that our online VB based dynamical model provides improved performance compared to conventional content caching policies.
Inferring wildlife poaching in Southeast Asia with multispecies dynamic occupancy models

Determining the ‘space race’ between sympatric species is crucial to understand the effects of interspecific interactions on the extinction risk of species threatened by poachers, predators, pathogens, and invasive competitors. Dynamic two-species occupancy models provide a flexible framework to decompose complex species interaction patterns while accounting for imperfect detection. In particular, these models can describe poachers-wildlife interactions by considering the occupancy, the extinction and colonisation probabilities of wildlife conditional on the presence or absence of poachers and vice versa. We apply our model to a case study on wildlife poaching in the Eastern plains of Cambodia. We used co-occurrence data extracted from the database of the SMART partnership to study the distribution dynamics between poachers and six ungulate species regarded as main prey of tigers. We used 4 years of survey data reporting the locations of ranger patrols on the detection of snares with visual detections or presence signs of the ungulates. Our results showed that a substantial proportion of the sites occupied by ungulate species went extinct over the years of the study while the proportion of sites colonised by poachers increased. We also showed, for the first time, that spatio-temporal heterogeneity in the patrolling effort explains a great deal of the variation in the detection of poachers and ungulates. Our approach provides practitioners with a flexible and robust tool to assess conservation status of species and extinction risk of wildlife populations. It can assist managers in better evaluating, learning and adapting the patrolling strategies of rangers.