Miracle-dz/UniFAR-FTUs huggingface dataset:
Agro-Morphological Characterization of Kenyan Slender Leaf (Crotalaria brevidens and C. ochroleuca) Accessions

Slender leaf (Crotalaria spp) is among the indigenous and underutilized vegetables in Kenya whose production is limited to the Western and Coastal regions of the country. For a long time, this crop has been neglected in terms of research and genetic improvement. There is therefore scanty information on its morphological diversity and agronomic performance, hence the need for this study. Field experiments were carried out for two seasons in October to December 2018 and March to May 2019. The experiments were laid out in Randomized Complete Block Design with 29 accessions and replicated three times. Both qualitative and quantitative data were recorded from the accessions based on the Crotalaria descriptors. Quantitative data were subjected to analysis of variance using XLSTAT Version 2019, and accession means were separated using Student’s Newman Keuls test at 95% level of confidence. Both qualitative and quantitative data were subjected to multivariate cluster analysis, and a dendrogram was constructed using the unweighted pair-group method with arithmetic average. The principal component analysis was conducted to obtain information on the importance of the characters. Significant variation in agro-morphological traits was found within and between the two species. Cluster analysis grouped the accessions into seven major classes with a between-classes diversity of 75.13% and a within-classes diversity of 24.87%. This study sets the basis for genetic improvement of slender leaf in Kenya since the observed diversity can be exploited in selection for intraspecific and interspecific hybridization.
Isolation of bacteria from mobile phones before and after decontamination: Study carried out at King Abdulaziz University, Jeddah, Saudi Arabia

Different fomites which are in regular contact with humans can play an important role in the transmission of microorganisms. Mobile phones have become indispensable in all walks of life; nevertheless their potential role in transmission of infections is of great interest. A cross-sectional study was done (April to June, 2015) at King Abdulaziz University, Jeddah, Faculty of Medicine (female campus), in order to detect the prevalence of bacterial contamination of mobile phones by students and staff, to investigate the most frequent habits associated with the use of mobile phones and effective cleaning of mobile phones with 70% alcohol for decontamination. A total of 168 swabs from 84 mobile phones derived from 80 volunteers were sampled at random. At the same time during sampling, a self-administered questionnaire was developed. All 84 mobile phones sampled were contaminated with bacteria, before decontamination. Coagulase-negative staphylococci were isolated frequently (32.3%), followed by Staphylococcus aureus (18.1%), viridans streptococci (15.7%), Bacillus spp. (13.4%) and Corynebacterium spp. (11.8%). Gram-negative bacilli and other Gram-positive cocci were also isolated but at lower levels. Mobile phones belonging to students had the highest rates of contamination (65.35%), followed by doctors (47%) and administrators (8.67%). Whilst, the lowest rate of bacterial contamination (5.5%) was observed among laboratory technicians, McNemar's analysis indicated that decontamination with 70% alcohol significantly decreased the rate of contamination from 100 to 47.6% (P<0.000). This study shows that all mobile phones examined were heavily contaminated with bacteria and the use of 70% alcohol for decontamination was effective in reducing bacterial colonization on these devices. Educating users on hygiene practices while using either mobile phones or other fomites in daily life aspects can help to reduce cross-transmission with microorganisms. Key words: Medical campus, mobile phones, bacteria, decontaminations, hygiene, contamination, Saudi Arabia.
WHAT BANG FOR THE BUCK? EXPORT PROMOTION AND THE EXTENSIVE MARGIN OF TRADE

Export promotion agencies (EPAs) provide support to firms that are willing to expand their operations across borders. This paper assesses whether allocating larger amount of an EPA’s budget to new exporters effectively increases the number of exporters. We test this by combining information on EPA’s budget allocation with country level indicators of exporters’ performance in 27 countries. Our results confirm that allocating more support to new exporters raises the number of exporters. This result is led by budget allocated to small firms, while the number of exporters declines when more budget is allocated to large firms. Our findings reinforce the heterogeneous firms’ theory: trade costs affect firms differently, and smaller firms are the ones which could potentially benefit more from targeted support. EPAs can use these results to allocate their budget in a way that is most effective given their policy objectives. JEL Classification: F13, F14, O24
The modulated low-temperature structure of malayaite, CaSnOSiO4

The crystal structure of malayaite, CaSnOSiO4, at T = 20 K has been refined, based on the presence of satellite reflections with a modulation vector of 0.26b*. The structural modulation is attributed to a soft optic phonon, dominated by motion of the Ca atoms.
Identification of Dominant Factors Influencing Non-engineering Students of Politeknik Negeri Padang Intentions as Entrepreneur

: To be an advance nation, it takes 14% of one country citizen as entrepreneur, while curently, Indonesia only has 3,1% entrepreneur of its citizen. Therefore, the government promotes entrepreneurial program for students especially those in higher education. Through this research, the factors that might influencing students of Politeknik Negeri Padang, especially non-engineering students, intention as entrepreneur is identified. By distributing questionnaires which developed based on planned behavior theory, data was collected and processed by utilizing structured equational model. It resulted that there are variables that positively influencing intention as entrepreneurial attitude, and others, subjective norms and behavior control are not confirmed.
Improving SAR Automatic Target Recognition Models With Transfer Learning From Simulated Data

Data-driven classification algorithms have proved to do well for automatic target recognition (ATR) in synthetic aperture radar (SAR) data. Collecting data sets suitable for these algorithms is a challenge in itself as it is difficult and expensive. Due to the lack of labeled data sets with real SAR images of sufficient size, simulated data play a big role in SAR ATR development, but the transferability of knowledge learned on simulated data to real data remains to be studied further. In this letter, we show the first study of Transfer Learning between a simulated data set and a set of real SAR images. The simulated data set is obtained by adding a simulated object radar reflectivity to a terrain model of individual point scatters, prior to focusing. Our results show that a Convolutional Neural Network (Convnet) pretrained on simulated data has a great advantage over a Convnet trained only on real data, especially when real data are sparse. The advantages of pretraining the models on simulated data show both in terms of faster convergence during the training phase and on the end accuracy when benchmarked on the Moving and Stationary Target Acquisition and Recognition data set. These results encourage SAR ATR development to continue the improvement of simulated data sets of greater size and complex scenarios in order to build robust algorithms for real life SAR ATR applications.
Review of snapshot spectral imaging technologies

Abstract. Within the field of spectral imaging, the vast majority of instruments used are scanning devices. Recently, several snapshot spectral imaging systems have become commercially available, providing new functionality for users and opening up the field to a wide array of new applications. A comprehensive survey of the available snapshot technologies is provided, and an attempt has been made to show how the new capabilities of snapshot approaches can be fully utilized.
Evaluation of fluorescence polarization assay for the diagnosis of brucellosis in cattle and buffaloes in India

Fluorescence polarization assay (FPA) was evaluated for serological diagnosis of brucellosis in cattle and buffaloes. Sera samples from 1397 cattle, comprising 120 indirect ELISA (iELISA) positive and 1277 iELISA negative; and 937 from buffaloes (88 iELISA positive and 849 iELISA negative) were tested by Rose Bengal test (RBT) and FPA in parallel. Receiver operating characteristic (ROC) curve was used for evaluation of FPA, using iELISA as gold standard to determine the cut-off offering the highest performance index (PI) and to compare its performance with RBT. In cattle, sensitivity (Sn) and specificity (Sp) of FPA were 46.7% and 96.6% respectively at a cut-off of 75 millipolarization (mP) in relation to iELISA, while Sn and Sp of RBT were 35.8% and 99.6% respectively. In buffaloes, Sn of FPA was 47.7% and Sp was 96.7% at a cut-off of 77.1 mP, whereas Sn and Sp of RBT were 44.3% and 99.2% respectively in relation to iELISA. McNemar’s chi-square test for independent data (with Yates’ correction) revealed that there was no significant difference in the proportion of positive samples between the FPA and RBT in cattle and buffaloes. Results indicated that FPA is as efficient as RBT for diagnosis of brucellosis. FPA may be preferred over RBT because of its characteristic of cut-off adjustments useful in different epidemiological situations and its potential application in field. However, further study with large number of known positive samples would be required for endorsement of FPA as a routine diagnostic test under the field condition.
Transcriptome Analysis Reveals the Negative Effect of 16 T High Static Magnetic Field on Osteoclastogenesis of RAW264.7 Cells

The magnetic field is the most common element in the universe, and high static magnetic field (HiSMF) has been reported to act as an inhibited factor for osteoclasts differentiation. Although many studies have indicated the negative role of HiSMF on osteoclastogenesis of RANKL-induced RAW264.7 cells, the molecular mechanism is still elusive. In this study, the HiSMF-retarded cycle and weakened differentiation of RAW264.7 cells was identified. Through RNA-seq analysis, RANKL-induced RAW264.7 cells under HiSMF were analysed, and a total number of 197 differentially expressed genes (DEGs) were discovered. Gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis indicated that regulators of cell cycle and cell division such as Bub1b, Rbl1, Ube2c, Kif11, and Nusap1 were highly expressed, and CtsK, the marker gene of osteoclastogenesis was downregulated in HiSMF group. In addition, pathways related to DNA replication, cell cycle, and metabolic pathways were significantly inhibited in the HiSMF group compared to the Control group. Collectively, this study describes the negative changes occurring throughout osteoclastogenesis under 16 T HiSMF treatment from the morphological and molecular perspectives. Our study provides information that may be utilized in improving magnetotherapy on bone disease.
The Discriminative Efficacy of Retinal Characteristics on Two Traditional Chinese Syndromes in Association with Ischemic Stroke

We aimed to investigate the efficacy of an objective method using AI-based retinal characteristic analysis to automatically differentiate between two traditional Chinese syndromes that are associated with ischemic stroke. Inpatient clinical and retinal data were retrospectively retrieved from the archive of our hospital. Patients diagnosed with cerebral infarction in the department of acupuncture and moxibustion between 2014 and 2018 were examined. Of these, the patients with Qi deficiency blood stasis syndrome (QDBS) and phlegm stasis in channels (PSIC) syndrome were selected. Those without retinal photos were excluded. To measure and analyze the patients' retinal vessel characteristics, we applied a patented AI-assisted automated retinal image analysis system developed by the Chinese University of Hong Kong. The demographic, clinical, and retinal information was compared between the QDBS and PSIC patients. The t-test and chi-squared test were used to analyze continuous data and categorical data, respectively. All the selected clinical information and retinal vessel measures were used to develop different discriminative models for QDBS and PSIC using logistic regression. Discriminative efficacy and model performances were evaluated by plotting a receiver operating characteristic curve. As compared to QDBS, the PSIC patients had a lower incidence of insomnia problems (46% versus 29% respectively, p=0.023) and a higher tortuosity index (0.45 ± 0.07 versus 0.47 ± 0.07, p=0.027). Moreover, the area under the curve of the logistic model showed that its discriminative efficacy based on both retinal and clinical characteristics was 86.7%, which was better than the model that employed retinal or clinical characteristics individually. Thus, the discriminative model using AI-assisted retinal characteristic analysis showed statistically significantly better performance in QDBS and PSIC syndrome differentiation among stroke patients. Therefore, we concluded that retinal characteristics added value to the clinical differentiation between QDBS and PSIC.
A study assessing the comparative molecular toxicities of heavy metals to multiple strains of Daphnia magna

The freshwater crustacean Daphnia magna is used extensively in ecotoxicological testing throughout the world. In addition, acute toxicity tests using Daphnia are required during chemical risk assessment including under EU Registration, Evaluation, Authorisation and restriction of Chemicals (REACH). Multiple studies have reported variation in the response of different strains of Daphnia to toxicant exposure including heavy metals. In this thesis, 10 strains of Daphnia magna were obtained from international research institutions and the comparative molecular toxicities of the heavy metals cadmium and copper to these strains was investigated A standard measure of acute toxicity, the acute immobilisation test was performed, in addition to the use of mass spectrometry-based metabolomics in order to assess sensitivity and metabolic differences between these strains. Up to 12-fold differences in sensitivity between strains of Daphnia were observed. Considerable differences in the basal metabolism of these strains was also discovered and correlated with relative sensitivity of the strains to cadmium and copper. Together these findings show for the first time that strains of Daphnia magna are metabolically different in addition to identifying a significant limitation in the use of Daphnia in regulatory decision making: results from independent laboratories using different strains of Daphnia may not agree.
The Efficacy and Safety of Mesalamine and Probiotics in Mild-to-Moderate Ulcerative Colitis: A Systematic Review and Meta-Analysis

Objective To evaluate the efficacy and safety of mesalamine in conjunction with probiotics for ulcerative colitis. Methods Random controlled trials (RCTs) were searched in PubMed, EMBASE, Cochrane Library, China National Knowledge Infrastructure, Wanfang, and VIP (VIP Database for Chinese Technical Periodicals) from inception to October 2019. Methodological quality was assessed by the Cochrane Collaboration tool. The quality of evidence was rated by the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE). Data analysis was carried out in Review Manager 5.3. Results A total of fifteen studies met the criteria for inclusion. Thirteen studies reported the clinical efficacy, three studies provided data on the clinical symptom scores, two trials reported disease activity index, four studies evaluated endoscopic score, and twelve studies reported adverse events. For ulcerative colitis (UC), mesalamine and probiotics had better clinical efficacy than mesalamine alone (≤8 weeks: RR = 1.12, 95% CI: 1.07–1.18, P < 0.0001; >8 weeks: RR = 1.25, 95% CI: 1.11–1.41, P=0.0003). On the clinical symptom scores, disease activity index, and endoscopic score, UC patients receiving mesalamine and probiotics had significant difference than patients receiving mesalazine alone (MD = −2.02, 95% CI: −3.28 to −0.76, P=0.002; MD = −1.20, 95% CI: −1.76 to −0.65, P < 0.001; and MD = −0.42, 95% CI: −0.61 to −0.23, P < 0.0001, respectively). There was no statistically significant difference in adverse events between the two groups (RR = 0.88, 95% CI: 0.54 to 1.43, P=0.60). Conclusion Our meta-analysis results supported that mesalamine and probiotics were effective and safe in treating ulcerative colitis.
Critical Thinking in Health Sciences and How It Pertains to Sonography Education: A Review of the Literature

Objective: Critical thinking is an important skill that sonographers must develop beginning in educational programs and into professional practice. Critical thinking requires students to reflect on information, use judgment skills, and engage in higher levels of thinking, including analysis, interpretation, inference, evaluation, and explanation, to formulate reliable decisions. Methods: Current research related to critical thinking has focused on medicine, nursing, physical therapy, pharmacy, and dental programs, but there has been no description of assessing sonography students. The Dreyfus model has been used as a framework to describe acquired skills that reflects students’ progress from novice to expert clinicians. This model illustrates specific cognitive abilities that students develop as they advance in education. Results: This review of the literature describes critical thinking skills coupled with a framework to understand different levels of cognitive thinking, as well as how it can be assessed. Conclusion: To understand differences between undergraduate sonography students and experts, the Dreyfus model is an excellent model to recognize progression. It can be used with the Health Sciences Reasoning Test, which is a nationally recognized critical thinking examination that can ascertain different levels of health sciences students’ critical thinking skills.
Efficient empirical revenue maximization in single-parameter auction environments

We present a polynomial-time algorithm that, given samples from the unknown valuation distribution of each bidder, learns an auction that approximately maximizes the auctioneer's revenue in a variety of single-parameter auction environments including matroid environments, position environments, and the public project environment. The valuation distributions may be arbitrary bounded distributions (in particular, they may be irregular, and may differ for the various bidders), thus resolving a problem left open by previous papers. The analysis uses basic tools, is performed in its entirety in value-space, and simplifies the analysis of previously known results for special cases. Furthermore, the analysis extends to certain single-parameter auction environments where precise revenue maximization is known to be intractable, such as knapsack environments.
CodeCarbonCopy

We present CodeCarbonCopy (CCC), a system for transferring code from a donor application into a recipient application. CCC starts with functionality identified by the developer to transfer into an insertion point (again identified by the developer) in the recipient. CCC uses paired executions of the donor and recipient on the same input file to obtain a translation between the data representation and name space of the recipient and the data representation and name space of the donor. It also implements a static analysis that identifies and removes irrelevant functionality useful in the donor but not in the recipient. We evaluate CCC on eight transfers between six applications. Our results show that CCC can successfully transfer donor functionality into recipient applications.
Better Safe than Sorry: Grappling with Failures of In-Memory Data Analytics Frameworks

Providing fault-tolerance is of major importance for data analytics frameworks such as Hadoop and Spark, which are typically deployed in large clusters that are known to experience high failures rates. Unexpected events such as compute node failures are in particular an important challenge for in-memory data analytics frameworks, as the widely adopted approach to deal with them is to recompute work already done. Recomputing lost work, however, requires allocation of extra resource to re-execute tasks, thus increasing the job runtimes. To address this problem, we design a checkpointing system called Panda that is tailored to the intrinsic characteristics of data analytics frameworks. In particular, Panda employs fine-grained checkpointing at the level of task outputs and dynamically identifies tasks that are worthwhile to be checkpointed rather than be recomputed. As has been abundantly shown, tasks of data analytics jobs may have very variable runtimes and output sizes. These properties form the basis of three checkpointing policies which we incorporate into Panda. We first empirically evaluate Panda on a multicluster system with single data analytics applications under space-correlated failures, and find that Panda is close to the performance of a fail-free execution in unmodified Spark for a large range of concurrent failures. Then we perform simulations of complete workloads, mimicking the size and operation of a Google cluster, and show that Panda provides significant improvements in the average job runtime for wide ranges of the failure rate and system load.
Classifying Code Comments in Java Mobile Applications

Developers adopt code comments for different reasons such as document source codes or change program flows. Due to a variety of use scenarios, code comments may impact on readability and maintainability. In this study, we investigate how developers of 5 open-source mobile applications use code comments to document their projects. Additionally, we evaluate the performance of two machine learning models to automatically classify code comments. Initial results show marginal differences between desktop and mobile applications.
New hardness results for routing on disjoint paths

In the classical Node-Disjoint Paths (NDP) problem, the input consists of an undirected n-vertex graph G, and a collection M={(s1,t1),…,(sk,tk)} of pairs of its vertices, called source-destination, or demand, pairs. The goal is to route the largest possible number of the demand pairs via node-disjoint paths. The best current approximation for the problem is achieved by a simple greedy algorithm, whose approximation factor is O(√n), while the best current negative result is an Ω(log1/2-δn)-hardness of approximation for any constant δ, under standard complexity assumptions. Even seemingly simple special cases of the problem are still poorly understood: when the input graph is a grid, the best current algorithm achieves an Õ(n1/4)-approximation, and when it is a general planar graph, the best current approximation ratio of an efficient algorithm is Õ(n9/19). The best currently known lower bound for both these versions of the problem is APX-hardness. In this paper we prove that NDP is 2Ω(√logn)-hard to approximate, unless all problems in NP have algorithms with running time nO(logn). Our result holds even when the underlying graph is a planar graph with maximum vertex degree 4, and all source vertices lie on the boundary of a single face (but the destination vertices may lie anywhere in the graph). We extend this result to the closely related Edge-Disjoint Paths problem, showing the same hardness of approximation ratio even for sub-cubic planar graphs with all sources lying on the boundary of a single face.