Miracle-dz/UniFAR-FTUs huggingface dataset:
Genotype-environment associations to reveal the molecular basis of environmental adaptation.

A fundamental goal in plant biology is to identify and understand the variation underlying plant adaptation to their environment. Climate change has given new urgency to this goal, as society aims to accelerate adaptation of ecologically important plant species, endangered plant species, and crops to hotter, less predictable climates. In the pre-genomic era, identifying adaptive alleles was painstaking work, leveraging genetics, molecular biology, physiology, and ecology. Now, the rise of genomics and new computational approaches may facilitate this research. Genotype-environment associations (GEA) use statistical associations between allele frequency and environment-of-origin to test the hypothesis that allelic variation at a given gene is adapted to local environments. Researchers may scan the genome for GEAs to generate hypotheses on adaptive genetic variants (environmental genome-wide association studies). Despite the rapid adoption of these methods, many important questions remain about the interpretation of GEA findings, which arise from fundamental unanswered questions on the genetic architecture of adaptation and limitations inherent to association-based analyses. We outline strategies to ground GEAs in the underlying hypotheses of genetic architecture and better test GEA-generated hypotheses using genetics and ecophysiology. We provide recommendations for new users who seek to learn about the molecular basis of adaptation. When combined with a rigorous hypothesis testing framework, GEAs may facilitate our understanding of the molecular basis of climate adaptation for plant improvement.
Can traditional teaching of Anatomy be replaced by alternative methods?

Purpose: There is murmur in the management of medical colleges that traditional teaching of Anatomy is in the process of being replaced by alternative method. Therefore, besides literature survey, a feedback survey has been carried out to seek the viewpoints of students and faculties, through a questionnaire, to compare their viewpoints regarding Anatomy teaching by traditional and alternative methods. Aim of the study is to assess whether traditional teaching of Anatomy can be replaced by alternative methods. Methods: A questionnaire having 17 questions, is designed to seek the feedback from medical students and faculties to assess the degree of need of traditional teaching of Anatomy in relation to comprehending medical subjects and for safe and successful clinical practice. The degree of need of traditional teaching of Anatomy is conceived such that if the mean responses of subjects fall within 9-17, it is most essential and cannot be replaced and if the responses lie within 0-8, it is not essential so can be replaced by alternative methods. The mean viewpoints have been computed and weighted mean is also calculated to compensate differential knowledge and experience of the subjects. Results: Statistical analyses of mean viewpoints and weighted mean viewpoints of 100% medical students and faculties have been found in the range of 10.7±3.3 to 14.5±1.9. The weighted mean of the total population has been computed to be 13.23. Conclusion: The teaching of Anatomy by traditional method is concluded most essential so it cannot be replaced by alternative method.
Approaching Exascale with the Weather Research and Forecasting Solar Model

We investigate the scalability and I/O performance of the Weather Research Forecasting (WRF) model on the PRACE Tier-0 systems SuperMUC-Haswell, Marconi KNL, and Marenostrum 4 within the PRACE 5th Implementation phase in cooperation with the Energy Oriented Centre of Excellence (EoCoE). We identify the bottlenecks which can impede WRF to run eﬃciently on pre-exascale and exascale machines. We report on the performance of both the computational kernels and I/O as captured using Scalasca/Score-P and extrae . From a series of strong scaling tests and benchmarks in which we vary the parallelization using diﬀerent MPI and OpenMP setups, we identify strategies to run eﬃciently on PRACE Tier-0 machines. The analysis is carried out for three schemes, namely the weather forecast scheme, the scheme based on WRFsolar, and the WRF-ﬁre scheme.
How to identify reconnecting current sheets in incompressible Hall MHD turbulence

Using high Reynolds number simulations of two‐dimensional Hall magnetohydrodynamics (HMHD) turbulence, a statistical association between magnetic discontinuities and magnetic reconnection is demonstrated. We find that sets of discontinuities, identified using the normalized partial variance of vector increments (PVI method), strongly depend on threshold in PVI statistic that is used as an identifying condition and on the strength of the Hall term. The analysis confirms that the Hall term plays an important role in turbulence and it affects the methods employed for detection of reconnecting current sheets. In particular, we found the following: (1) Among all the discontinuities detected by the PVI method, the reconnecting ones are on average thinner. (2) A reduction in size of all discontinuities and of reconnecting current sheets is observed as the threshold θ grows. (3) The average width of the reconnecting current sheets decreases as the strength of the Hall term grows and the ion inertial scale di increases with respect to the dissipative scale.
BIOINFORMATICS Identifying functional miRNA–mRNA regulatory modules with correspondence latent dirichlet allocation

Motivation: MicroRNAs (miRNAs) are small non-coding RNAs that cause mRNA degradation and translational inhibition. They are important regulators of development and cellular homeostasis through their control of diverse processes. Recently, great efforts have been made to elucidate their regulatory mechanism, but the functions of most miRNAs and their precise regulatory mechanisms remain elusive. With more and more matched expression proﬁles of miRNAs and mRNAs having been made available, it is of great interest to utilize both expression proﬁles to discover the functional regulatory networks of miRNAs and their target mRNAs for potential biological processes that they may participate in. Results: We present a probabilistic graphical model to discover functional miRNA regulatory modules at potential biological levels by integrating heterogeneous datasets, including expression proﬁles of miRNAs and mRNAs, with or without the prior target binding information. We applied this model to a mouse mammary dataset. It effectively captured several biological process speciﬁc modules involving miRNAs and their target mRNAs. Furthermore, without using prior target binding information, the identiﬁed miRNAs and mRNAs in each module show a large proportion of overlap with predicted miRNA target relationships, suggesting that expression proﬁles are crucial for both target identiﬁcation and discovery of regulatory modules. Supplementary information: Supplementary data are available at Bioinformatics online.
Determining the Extremes of the Cellular NAD(H) Level by Using an Escherichia coli NAD (cid:1) -Auxotrophic Mutant (cid:1)

NAD (NAD (cid:1) ) and its reduced form (NADH) are omnipresent cofactors in biological systems. However, it is difﬁcult to determine the extremes of the cellular NAD(H) level in live cells because the NAD (cid:1) level is tightly controlled by a biosynthesis regulation mechanism. Here, we developed a strategy to determine the extreme NAD(H) levels in Escherichia coli cells that were genetically engineered to be NAD (cid:1) auxotrophic. First, we expressed the ntt4 gene encoding the NAD(H) transporter in the E. coli mutant YJE001, which had a deletion of the nadC gene responsible for NAD (cid:1) de novo biosynthesis, and we showed NTT4 conferred on the mutant strain better growth in the presence of exogenous NAD (cid:1) . We then constructed the NAD (cid:1) -auxotrophic mutant YJE003 by disrupting the essential gene nadE , which is responsible for the last step of NAD (cid:1) biosynthesis in cells harboring the ntt4 gene. The minimal NAD (cid:1) level was determined
Bi-State Frequency Selective Surfaces Made of Intertwined Slot Arrays C

— Novel arrangements of active frequency selective surfaces (AFSSs) with integrated voltage control wiring are proposed for bi-state (transparency/reflectance) operation at specified frequencies. The AFSSs are comprised of passive arrays of intertwined patterns of slots in a conductor screen and an active dipole array with pin diodes placed either on the same or opposite sides of a thin dielectric substrate. Simulation and measurement results show that such AFSSs exhibit good isolation (~ 15 dB) between the translucency and reflection states at normal incidence that slightly decreases at oblique incidence. The proposed AFSSs maintain the high angular and polarisation stability over broad fractional bandwidths (FBWs) inherent to the constituent periodic arrays of intertwined conductor patterns with substantially subwavelength unit cells. The merits of these AFSS arrangements also include resilience to parasitic effects of real switches, whose insertion loss in the on -state only enhances the AFSS on / off isolation. Such AFSSs are essential elements for reconfiguring and controlling the electromagnetic architecture of buildings.
Fatigue of double-network hydrogels The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters

: The discovery of tough hydrogels of many chemical compositions, and their emerging applications in medicine, clothing, and engineering, has raised a fundamental question: How do hydrogels behave under many cycles of stretch? This paper initiates the study of the fatigue behavior of the classic PAMPS/PAAM double network hydrogels discovered by Gong and her co-workers (Advanced Materials 15, 1155, 2003). We reproduce the hydrogels, and prepare samples of two types, with or without a crack cut before the test. When an uncut sample is subject to cyclic stretches, internal damage accumulates over thousands of cycles until a steady state is reached. When a cut sample is subject to cyclic stretches, the crack extends cycle by cycle if the amplitude of stretch is above a certain value. A threshold of energy release rate exists, below which the crack remains stationary as the sample is cycled. We find a threshold around 400 J/m 2 for hydrogels containing PAAM networks of a low density of crosslinkers, and around 200 J/m 2 for hydrogels containing PAAM networks of a high density of crosslinkers. The experimental findings are compared to the Lake-Thomas model adapted to the double-network hydrogels.
A Novel Reduced Representation Methodology for Provenance Data

— Learning structure and concepts in provenance data have created a need for monitoring scientific workflow systems. Provenance data is capable of expanding quickly due to the catch level of granularity, which can be quite high. This study examines complex structural information based provenance representations, such as Network Overview and Social Network Analysis. Further examination includes whether such reduced provenance representation approaches achieve clustering effective for understanding the hidden structures within the execution traces of scientific workflows. The study applies clustering on a scientific dataset from a weather forecast to determine its usefulness, compares the proposed provenance representations against prior studies on reduced provenance representation, and analyzes the quality of clustering on different types of reduced provenance representations. The results show that, compared to prior studies on representation, the Social Network Analysis based representation is more capable of completing data mining tasks like clustering while maintaining more reduced provenance feature space.
CO 2 -induced ocean acidification increases anxiety in Rockfish via alteration of GABA A receptor functioning

The average surface pH of the ocean is dropping at a rapid rate due to the dissolution of anthropogenic CO 2 , raising concerns for marine life. Additionally, some coastal areas periodically experience upwelling of CO 2 -enriched water with reduced pH. Previous research has demonstrated ocean acidification (OA)-induced changes in behavioural and sensory systems including olfaction, which is due to altered function of neural gamma-aminobutyric acid type A (GABA A ) receptors. Here, we used a camera-based tracking soft-ware system to examine whether OA-dependent changes in GABA A receptors affect anxiety in juvenile Californian rockfish ( Sebastes diploproa ). Anxiety was estimated using behavioural tests that measure light/dark preference (scoto-taxis) and proximity to an object. After one week in OA conditions projected for the next century in the Californiashore (1125 + 100 m atm, pH 7.75), anxiety was significantly increased relative to controls (483 + 40 m atm CO 2 , pH 8.1). The GABA A -receptor agonist muscimol, but not the antagonist gabazine, caused a significant increase in anxiety consistent with altered Cl 2 flux in OA-exposed fish. OA-exposed fish remained more anxious even after 7 days back in control seawater; however, they resumed their normal behaviour by day 12. These results show that OA could severely alter rockfish behaviour; however, this effect is reversible.
System Modeling and Faults Diagnosis of a Five Hydraulic Tank

: In modern process industry such as chemical and petrochemical plants, it is important to detect and isolate faults, while the plant is running. This paper investigates a robust unknown input observer (UIO) used for detection and isolation of faults. The impact of disturbances and uncertainty may create difficulties at the decision stage of diagnosis (false alarm); this has resulted to use UIO. Five tank system can be used as a good prototype of many industrial applications in process industry. The main contribution is to construct modeling of this system subject to unknown inputs and results from unknown input observer theory. Two actuator faults are considered, residuals are generated using this kind of observer. The faults will be isolated by using a bank of UIOs in the framework of the Dedicated Observer Scheme (DOS). Simulations results are given to show the effectiveness of the proposed method.
Accident Analysis and Prevention

The objective of an accident-mapping algorithm is to snap trafﬁc accidents onto the correct road segments. Assigning accidents onto the correct segments facilitate to robustly carry out some key analyses in accident research including the identiﬁcation of accident hot-spots, network-level risk mapping and segment-level accident risk modelling. Existing risk mapping algorithms have some severe limitations: (i) they are not easily ‘transferable’ as the algorithms are speciﬁc to given accident datasets; (ii) they do not perform well in all road-network environments such as in areas of dense road network; and (iii) the methods used do not perform well in addressing inaccuracies inherent in and type of road environment. The purpose of this paper is to develop a new accident mapping algorithm based on the common variables observed in most accident databases (e.g. road name and type, direction of vehicle movement before the accident and recorded accident location). The challenges here are to: (i) develop a method that takes into account uncertainties inherent to the recorded trafﬁc accident data and the underlying digital road network data, (ii) accurately determine the type and proportion of inaccuracies, and (iii) develop a robust algorithm that can be adapted for any accident set and road network of varying complexity. In order to overcome these challenges, a distance based pattern-matching approach is used to identify the correct road segment. This is based on vectors containing feature values that are common in the accident data and the network data. Since each feature does not contribute equally towards the identiﬁcation of the correct road segments, an ANN approach using the single-layer perceptron is used to assist in “learning” the relative importance of each feature in the distance calculation and hence the correct link identiﬁcation. The performance of the developed algorithm was evaluated based on a reference accident dataset from the UK conﬁrming that the accuracy is much better than other methods.
NON-FARM INCOME DIVERSIFICATION AND POVERTY REDUCTION IN NIGERIA: A PROPENSITY-SCORE MATCHING ANALYSIS

In this paper, we investigate the impact of non-farm employment (disaggregated by wage- and self-employment) on household income and poverty. Using a propensity score matching model, we evaluate the differences in outcomes between households who participate in the non-farm employment and those who do not. The results from the study show that non-farm wage-employed households in rural Nigeria have a significantly higher income than self-employed households. Second, we show that non-farm wage-employment impacts more on household welfare than non-farm self-employment. Third, we show that the benefits to non-farm wage-employment are much higher among the non-poor than among the poor.
Towards a better understanding of the impact of economic disruptions on the Moroccan economy: An input-output network analysis

Input-Output tables are often used to understand the interactions between different industries. In this paper we want to extract a clear view of the Moroccan economy, with the objective to identify some of its structural features and to understand the impact of some disruptions such as those due to natural hazard, that can affect these interactions between the different sectors and regions and so the global economy.
The Concepts Underlying Structure Coefficients, Communality, and Factor Scores in the Exploratory Factor Analytic Case.

This paper illustra_es the transformation of a raw data matrix into a matrix of associations, and then into a factor matrix. In the procesS of extracting two factors from heuristic data, the nature of structure coefficients is explored, the derivation and utility of factor scores are discussed, and the concept of communality is related to the multiple coelation coefficient. Although factor analysis has several possible uses, an important, application is the service the procedures provide to summarizing scientific data, thus enabling empirical relationships to be more easily conceptualized (Gorsuch, 1974, pi 2). The analysis evaluates a data matrix defined by two dimensions and can be visualized as a rectangular table _ith the columns defining one set of entities (such as variables, people ) or occasions of measurement) and the rows defining a group of replicates -ver which those entities are measured. According to Horst (1965, p. 17), tta primary concern of factor analysis with such a table of numbers is to determine whether the table may be simplified in some way". The original dati matrix may contain random or unreliable information in addition to relevant or systematic info -ation (p. 469). A simplif cation of the matrix, it is expected, will help to disentangle complex interrelationships so that they may be more easily understood as they exist in . eal life (Rummel, 1970, pp. 3-4). Factor analysis "distill the info ation in the ,variables such that the data are more meaningful' Several values derived through factor analytic procedures allow the researcher to examine different aspects of the relationships among the variables of a study. The present paper discusses the concepts underlying these indices. Specifically, this paper focuses upon ucture coefficients factor scores, and commLna ity coefficients. '
Patterns of Widal test Results among Patients Suspected to Have Typhoid Fever Attending Bsuth Makurdi Nigeria

Widal agglutination test which is the main laboratory procedure for diagnosis of typhoid fever in our rural and urban settings has received cautious acceptability and often outright rejection in other places. This study was set up to ascertain suitability or otherwise of Widal test in the diagnosis of typhoid fever among hospital attendees with clinical diagnosis of typhoid fever. Three hundred and eighty-nine patients with clinical diagnosis of typhoid fever attending Benue State University Teaching Hospital (BSUTH) Makurdi between November 2016 and April 2017 were consecutively recruited into the study. Blood and stool samples were collected where Widal test and cultures were carried out on them respectively. Among the febrile patients 40.1% (n=156) and 59.9% (n=233) respectively had Widal agglutination tests titres of <1: 80 and ≥1: 80 while five (1.3%) of the patients grew Salmonella in stool. Analysis of the results showed the following: Sensitivity (O =73.8%, H = 25.3%); Specificity (O = 77.1%, H = 79.8%); Positive Predictive Value PPV (O = 13.7%, H = 5.0), and Negative Predictive Value NPV (O = 99.4%, H = 96.9%). Widal agglutination test alone has limited value in routine diagnosis of typhoid fever due to its poor positive predictive value and hence should not be used alone or at best with extreme caution to establish diagnosis of typhoid fever.
On the Reality of Causes: A Response to Ned Lebow

Qualitative & Multi-Method Research, Fall 2014 Eells, Ellery. 1991. Probabilistic Causality. Cambridge: Cambridge University Press. Kvart, Igal. 2004. “Causation: Probabilistic and Counterfactual Analyses. ” In Causation and Counterfactuals. John Collins, Ned Hall, and L.A. Paul, eds. (Cambridge, MA: MIT Press), 359–387. Lebow, Richard Ned. 2014. Constructing Cause in International Relations. Cambridge: Cambridge University Press. van Fraassen, Bas C. 1980. The Scientific Image. Oxford: Oxford University Press.
Licochalcone A Potently Inhibits Tumor Necrosis Factor (cid:1) Induced Nuclear Factor- (cid:2) B Activation through the Direct Inhibition of I (cid:2) B Kinase Complex Activation

Glycyrrhiza inflata has been used as a traditional medicine with anti-inflammatory activity; however, its mechanism has not been fully understood. Licochalcone A is a major and bioge- netically characteristic chalcone isolated from G. inflata . Here, we found that licochalcone A strongly inhibited tumor necrosis (TNF)- (cid:1) -induced nuclear localization, DNA binding activity, and the transcriptional activity of nuclear factor- (cid:2) B (NF- (cid:2) B). Whereas licochalcone A had no effect on the recruitment of receptor-interacting protein 1 and I (cid:2) B kinase (cid:3) (IKK (cid:3) ) to TNF receptor I by TNF- (cid:1) , it significantly inhibited TNF- (cid:1) -induced I (cid:2) B kinase complex (IKK) activation and inhibitor of nuclear fac- tor- (cid:2) B degradation. It is interesting that we found that the cysteine residue at position 179 of IKK (cid:3) is essential for licochalcone A-induced IKK inhibition, because licochalcone A failed to affect the kinase activity of the IKK (cid:3)