Miracle-dz/UniFAR-FTUs huggingface dataset:
SSR Analysis of Maternal and Paternal Lines Selected in the Don Region (Russia)

Evaluation of DNA polymorphisms of breeding material of sunflower from L.A. Zhdanov Don Experimental Station of oil Crops of V.S. Pustovoit All-Russian Research Institute of Oil Crops represented by 17 maternal (CMS) lines and 12 paternal (Rf) lines was conducted. There were identified 35 allelic variants of CMS lines and 42 allelic variants of Rf lines with use of 11 SSR markers. It is shown that the level of genetic diversity of microsatellite loci of CMS lines is 1.2 times lower than that of Rf lines. The average number of alleles per SSR locus for maternal lines also lowers than for paternal lines. In addition, CMS lines and Rf lines differ in the frequency of alleles of SSR loci. Thus, the discriminatory capacity of the studied marker system for identification of cultivated sunflower lines was quite high and is suitable for certification of the lines.
Fair task assignment in spatial crowdsourcing

With the pervasiveness of mobile devices, wireless broadband and sharing economy, spatial crowdsourcing is becoming part of our daily life. Existing studies on spatial crowdsourcing usually focus on enhancing the platform interests and customer experiences. In this work, however, we study the fair assignment of tasks to workers in spatial crowdsourcing. That is, we aim to assign tasks, considered as a resource in short supply, to individual spatial workers in a fair manner. In this paper, we first formally define an online bi-objective matching problem, namely the Fair and Effective Task Assignment (FETA) problem, with its special cases/variants of it to capture most typical spatial crowdsourcing scenarios. We propose corresponding solutions for each variant of FETA. Particularly, we show that the dynamic sequential variant, which is a generalization of an existing fairness scheduling problem, can be solved with an O(n) fairness cost bound (n is the total number of workers), and give an O(n/m) fairness cost bound for the m-sized general batch case (m is the minimum batch size). Finally, we evaluate the effectiveness and efficiency of our algorithm on both synthetic and real data sets.
Dipole Estimation from the Magnetic Field Gradient for RFID Tag Localization†

This paper presents a simple sensor and algorithm to estimate the position of a magnetic dipole for localization of an RF-ID tag. Acquisition of the tag position, in addition to the ID information, opens up various applications with location awareness. A key point of our method is the use of spatial gradients of the magnetic field, created by the RF-ID tag. First we show a deterministic algorithm to express the tag position, irrespective of its posture, in terms of the combination of the fields and their first order spatial derivatives. Then, we show a sensor unit that can measure the spatial gradients efficiently.
Genome-wide RNA-sequencing dataset reveals the prognostic value and potential molecular mechanisms of lncRNA in non-homologous end joining pathway 1 in early stage Pancreatic Ductal Adenocarcinoma

Objective: Our current study is to explore the prognostic value and molecular mechanisms underlying the role of lncRNA in non-homologous end joining pathway 1 (LINP1) in early stage pancreatic ductal adenocarcinoma (PDAC). Methods: Genome-wide RNA-seq datasets of 112 early stage PDAC patients were got from The Cancer Genome Atlas and analyzed using multiple online tools. Results: Overall survival in high LINP1 expression patients was shorter than those with low expression (high-LINP1 vs. low-LINP1=481 vs. 592 days, log-rank P=0.0432). The multivariate Cox proportional hazard regression model suggested that high-LINP1 patients had a markedly higher risk of death than low-LINP1 patients (adjusted P=0.004, hazard ratio=2.214, 95% confidence interval=1.283-3.820). Analysis of genome-wide co-expressed genes, screening of differentially expressed genes, and gene set enrichment analysis indicated that LINP1 may be involved in the regulation of cell proliferation-, cell adhesion- and cell cycle-related biological processes in PDAC. Six small-molecule compounds including STOCK1N-35874, fenofibrate, exisulind, NU-1025, vinburnine, and doxylamine were identified as potential LINP1-targeted drugs for the treatment of PDAC. Conclusions: Our study indicated that LINP1 may serve as a prognostic biomarker of early stage PDAC. Analysis of genome-wide datasets led to the elucidation of the underlying mechanisms and identified six potential targeted drugs for the treatment of early PDAC.
CONCEPTUAL DESIGN OF A HIGH AVERAGE CURRENT SRF GUN

Up to a 100 mA 10 MeV continuous wave electron injector may be required to deliver high brightness electron bunches for future light sources. One of the possible solutions would be the use of Superconducting RF (SRF) cavities due to the high RF power and vacuum requirements. The development of a suitable acceleration scheme has been identified, including the design of the RF Cavities. In this paper, the injector design and performance as well as the associated challenges are presented.
Molecular characterization of Votho pigs from Nagaland using microsatellite markers

This study details genetic diversity of Votho pig population using a set of 21 microsatellite markers recommended by Food and Agriculture Organization of United Nations (FAO) for Swine. All the studied loci were highly informative. The number of observed alleles (Na) detected ranged from 2 to 10, with an overall mean of 5.59±0.598. In total 122 alleles were observed across the investigated loci. The effective number of alleles (Ne) ranged from 1.054 to 5.075 with a mean of 3.02±0.284. The Polymorphic Information Content (PIC) value ranged from 0.0499 to 0.7750 with the overall mean of 0.53±0.250. The overall means for observed (Ho) and expected (He) heterozygosities were 0.38±0.060 and 0.57±0.055 respectively. The within breed inbreeding estimate indicated heterozygosity shortage of 0.273. The Hardy-Weinberg equilibrium (HWE) test revealed that 14 out of 21 loci deviated from equilibrium. Shannon’s information index (I), was sufficiently high with a mean of 1.17±0.124. The bottleneck analysis revealed that population has not undergone any recent reduction.
Flood Mapping and Analysis using Sentinel Application Platform ( SNAP )-A Case Study of Kerala

In August 2018, harsh flooding affected the Kerala state due to heavy rainfall during the Monsoon season. According to the media reports these were the worst floods since 1924 which have affected one sixth of population of Kerala. Flood inundation mapping and analysis was carried by using Sentinel-1 data. For the analysis of the temporal and spatial dynamics of the disaster we use Sentinel 1 Synthetic Aperture Radar (SAR) data due to its systematic frequent acquisition. A dataset of pre-event and postevent Sentinel -1 image within the two data set i.e. 29-52018 and 27-82018 are selected for the temporal analysis. In this study, preprocessing steps are performed using SNAP tool and s1tbx tools. Sentinel Application Platform (SNAP) software is used for these pre-processes that are Radiometric Calibration, Terrain Correction and Speckle filter. Three approaches were used to extract water bodies of Kerala flood.
Optimization of Large-Scale Structures using Hybrid Genetic Algorithms

With the recent progress in computational technology, distributed or parallel computing on multiprocessor computers provided an opportunity to obtain optimal solutions with gradient-based algorithms for large-scale structures subjected to the actual design codes. Also, effective use of high performance computers, or the exploitation of parallelism achieved in parallel or distributed implementations, can greatly increase the feasibility of computationally intensive iterative algorithms such as GA and SA. Especially, GAs use a set of population for candidate designs to find an optimum solution. Therefore the number of iteration and analysis is increased as population increases. The performance of GAs depends on the selection of optimization parameters since the proper parameter setting guarantees a stable and rapid convergence. Therefore the parameter must be set properly before applying to a problem. In this paper, parallel and distributed hybrid genetic algorithms are proposed to avoid the cumbersome process related to the parameter setting and to reduce convergence time with small size of population. To demonstrate the performance, the algorithms are implemented on high-performance computers such as IBM Regatta P690 system and a cluster of personal computers.
PRODUCTIVITY AND PHYSICO CHEMICAL QUALITY OF YELLOW PASSION UNDER DIFFERENT NITROGEN SOURCES THROUGH FERTIGATION

Nitrogen is the most required and limiting nutrient in the yellow passion through irrigation water provides more rational and efficient use of fertilizers. T assessing productive and qualitative parameters of yellow passion doses of nitrogen through fertigation in Vale do Gurgueia June 2013 to August 2014 in the city randomized and arranged in a 2 x 5 factorial scheme, with four replicates. Treatments were consisted of combined two nitrogen sources (urea and ammonium sulfate) and five nitrogen levels (100, 200, 300, 400 and 500 kg ha The fertigation, occurred during the crop cycle, was weekly performed. Yield was evaluated per plant, productivity and mean weight of fruit. In pulp, pH, pulp percentage were evaluated. Increased ratios of N, ammonium sulfate source, cause reduction in fruit pulp percentage of the yellow passion quality within ranges established by normative instruction of MAPA. To urea source, it is recommended 227.87 kg ha ammonium sulfate, for a productivity of 14.92 t ha
A Computational Understanding of Classical (Co)Recursion

Recursion and induction are mature, well-understood topics in programming. Yet their duals, corecursion and coinduction, are still exotic and underdeveloped programming features. We aim to put them on equal footing by giving a foundation for corecursion based on computation, analogous to the original computational foundation of recursion. At the lower level, we show how the connection between the two can be strengthened through their implementation details in an abstract machine. At the higher level, we develop a syntactic equational theory for inductive and coinductive reasoning based on control flow. We also observe the impact of evaluation strategy: call-by-name has efficient recursion and strong coinductive reasoning, but call-by-value has efficient corecursion and strong inductive reasoning.
Supporting smallholders’ decision making: managing trade-offs and synergies for sustainable agricultural intensification

ABSTRACT Meeting multiple, often competing objectives when seeking to sustainably intensify their agricultural operations is a constant challenge for smallholder farmers in Sub-Saharan Africa. Trade-offs between social, economic and environmental goals at different time and spatial scales need to be reconciled, making best use of scarce resources. This study explored how different types of farm households in Northwest Ghana, Eastern Burkina Faso and Central Malawi make choices about resource allocation and farming strategies, and how they manage the trade-offs encountered. It used both quantitative (questionnaire survey) and qualitative (household case studies) methods to identify trade-offs experienced by farmers and to analyse trade-off management strategies used by them. The 10 main trade-offs identified across the 3 countries occurred across sustainability domains, across time, across spatial scales, across types of farmers or a combination of these. Famers were disincentivized from prioritizing long-term sustainability in their farming operation by resource constraints to meet multiple farming and livelihood objectives, mainstream agricultural policies encouraging short-term productivity gains and adoption-focused interventions, which disregard the diversity of farming households.
Psychological aspects of outbreaks scale (PAOS): A validation study

Aim: The aim of this study was set to develop a measurement tool to understand adults’ attitudes towards pandemic and to provide evidence of its validity and reliability Material and Method: Items developed from a pool of 59 items were applied to 798 adults The exploratory factor analysis was made on the data collected, and the size of the measurement tool with factor extraction techniques was analyzed using SPSS and R statistical environment In an iterative analysis of principal components, items that did not meet predefined criteria were removed and the 16-item final version of the Psychological Aspects of Outbreaks Scale was obtained The final four-factor solution obtained with principal component analysis was also confirmed by the Exploratory Graph Analysis and Parallel Analysis The second data collection was carried out by distributing the measurement tool to a group of 62 adults Data were used to analyze the criterion validity and test-retest reliability of the measurement tool Results: The following names were given to the dimensions: fear of harm, considerations on precautions, intolerance of uncertainty, appreciation PAOS’s significant relationships with other relevant constructs such as health anxiety, intolerance of uncertainty, and health cognitions supported criterion-related validity support its criterion-based validity PAOS items had adequate level of internal consistency (α = 77) and test-retest reliability (r = 76) Discussion: The Psychological Aspects of Outbreak Scale (PAOS) was a valid and reliable tool for evaluating people’s behavior, beliefs, and attitudes during the COVID-19 period
Intelligent Threat Response

—Software-defined networks decouple the control plane from the data plane, enabling researchers to evaluate protocols and network configurations through the centralized point of control, the controller. They provide easy management and automation, scalability, and flexibility in the traditional computer network. In spite of these advantages, software-defined networks fall prey to various denial-of-service attacks specific to network protocols and applications despite their simplicity. There is a need to implement intelligence in the controller as a countermeasure for not only the various types of denial-of-service attacks but also the increasing sophistication involved in them. In this paper, an intelligent threat-aware response system is proposed for defending against any attack by using reinforcement learning. Reinforcement learning can acquire intelligence for detection and reactive actions through experience with various attacks. This experience is obtained from interactions with the computer network through the controller. With the combination of reinforcement learning and the software-defined networking controller, the goal of the autonomous threat response system can be achieved.
Sketchy: Drawing Inspiration from the Crowd

In-person user studies show that designers draw inspiration by looking at their peers' work while sketching. To recreate this behavior in a virtual environment, we developed Sketchy, a web-based drawing application where users sketch in virtual rooms and use the "Peek'' functionality to gain ideas from their peers' sketches in real-time. To assess if "Peek'' supports individual creativity through finding inspiration, students from a Human-Computer Interaction class sketched user interface design tasks in two studies. Study 1 compares creativity measures with and without Peek between two groups of students, where self-reports reveal Peek increases satisfaction with their final sketch and better supports individual creativity. Study 2 took place in a large classroom, where 90 students, all with Peek enabled, completed different design tasks. Peeking led students to report an intention to change their sketch 18% of the time in Study 1 and 17% of the time in Study 2. Student designers were influenced by sketches that seem closer to completion, contain more details, and are carefully drawn. They were also about three times more likely to clear their canvas and start over if they found a sketch inspirational. Furthermore, sketches created by students with more sketching and design experience influence less experienced student designers. This work explores the directions and benefits of incorporating digital peeking to support individual creativity within a student designer's classroom experience to create more satisfactory final sketches.
Consolidation of C 5.0, Random Forest and Random Tree Crafts for Intrusion Detection System

: Our day to day activities e.g. ecommerce are influenced by Internet. The hazards from hackers have also expanded. According to view point of many researchers intrusion detection systems are the base of defense. There are many commercially available intrusion detection systems are principally signature-based. Known attacks are detected by these systems. These systems frequently renovate signature as well as rules. Unknown attacks are not detected by these systems. The use of anomaly base intrusion detection systems are the best solution. They are highly potent in recognizing not only known but also unknown attacks. Recognition of high false alarm rate is main problem with anomaly based intrusion detection systems. In our proposed system, we contribute explanation to increase attack detection rate while reducing high false alarm rate by combining various data mining techniques such as C 5.0, Random Forest and Random Tree.
Mathematical Modeling, Analysis, and Optimal Control of Corruption Dynamics

In this paper, a nonlinear deterministic model for the dynamics of corruption is proposed and analysed qualitatively using the stability theory of differential equations. The basic reproduction number with respect to the corruption-free equilibrium is obtained using next-generation matrix method. The conditions for local and global asymptotic stability of corruption-free and endemic equilibria are established. From the analysis using center manifold theory, the model exhibits forward bifurcation. Then, the model was extended by reformulating it as an optimal control problem, with the use of two time-dependent controls to assess the impact of corruption on human population, namely, campaigning about corruption through media and advertisement and exposing corrupted individuals to jail and giving punishment. By using Pontryagin’s maximum principle, necessary conditions for the optimal control of the transmission of corruption were derived. From the numerical simulation, it was found that the integrated control strategy must be taken to fight against corruption.
EXPERIMENTAL STUDY ON A CASCADED PCM STORAGE RECEIVER FOR PARABOLIC

A flat surfaced solar receiver with integrated phase change material (PCM) in a cascaded manner is investigated to act as the short-term heat storage. The objective of this work is to store the heat energy effectively at the focal point using different melting point PCM. Three PCM dish receivers are attached in a series. The Scheffler reflector of 16 m 2 aperture area is used to concentrate the incident solar rays on the cascaded PCM receiver. The selected PCM are Xylitol, Erythritol and Galactitol. having melting points of 94°C, 118°C and 166°C respectively. The solar receiver is heated to a temperature of 250°C. The heat stored is determined based on the temperature measurements. The total heat stored in the solar receiver with PCM depends on the temperature of individual PCM and the thermal properties. The receiver material stores 30% of the heat and the PCM stores the remaining 70% of the incident energy on the receiver. Such cascaded PCM solar receiver is useful to store the heat at the focus of the dish reflector for the remote applications.
Tracking Footprints in a Swarm: Information-Theoretic and Spatial Centre of Influence Measures

Boids (bird-oids) is a widely used model to mimic the behaviour of birds. Shoids (sheep-oids) rely on the same boids rules with the addition of a repulsive force away from a sheepdog (a herding agent). Previous work assumed homogeneous shoids. Real-world observations of sheep show non-homogeneous responses to the presence of a herding agent. We present a portfolio of information-theoretic and spatial indicators to track the footprints of shoids with different parameters within the shoid flock. The portfolio is named the Centre of Influence to indicate that the aim is to identify the influential shoids with the highest impact on flock dynamics. We use both synthetic simulation-driven data and measurements collected from live sheep herding trials by an unmanned aerial vehicle (UAV) to validate the proposed measures. The resultant measures will allow us in our future research to design more efficient control strategies for the UAV, by polarising the attention of the machine learning algorithm on those shoids with influence footprints, to drive the flock to improve the herding of sheep.
Now You Hear Me, Later You Don’t: The Immediacy of Linguistic Computation and the Representation of Speech

What happens to an acoustic signal after it enters the mind of a listener? Previous work has demonstrated that listeners maintain intermediate representations over time. However, the internal structure of such representations—be they the acoustic-phonetic signal or more general information about the probability of possible categories—remains underspecified. We present two experiments using a novel speaker-adaptation paradigm aimed at uncovering the format of speech representations. We exposed adult listeners (N = 297) to a speaker whose utterances contained acoustically ambiguous information concerning phones (and thus words), and we manipulated the temporal availability of disambiguating cues via visually presented text (presented before or after each utterance). Results from a traditional phoneme-categorization task showed that listeners adapted to a modified acoustic distribution when disambiguating text was provided before but not after the audio. These results support the position that speech representations consist of activation over categories and are inconsistent with direct maintenance of the acoustic-phonetic signal.
Quantum Annealing for Solving a Nurse-physician Scheduling Problem in Covid-19 Clinics

Quantum annealing (QA) is a metaheuristic methodologythat has recently been used to analyze the performance of first generation adiabatic quantum processors, like the oneavailable from D-wave Systems, in solving combinatorial optimization problems. In this paper, we formulate QA representation of problems essential to mitigating the effects of the COVID-19 pandemic, namely, the Nurse Scheduling Problem (NSP), the Physician Scheduling Problem (PSP), and the Nurse-Physician Scheduling Problem (NPSP). The proposed objective functions for each problem are scripted to the Ising model and then transformed into thequadratic unconstrained binary optimization (QUBO)format. An optimal solutionis soughtfor a set of constraints, including thenumber ofnurses or physicians per shift andthe maximum number of shifts for each nurse or physician.After reducingtheproposed NSP, PSP, and NPSP QUBOs to a novel Ising type Hamiltonian, we obtain solutions from a classical (simulated) annealer,and then from the D-wave 2000Q forward and reverse annealer. Results from the reverse quantum annealer show a dramatic improvement in solution quality as compared to those from the classical annealer. We observe that the reverse annealing method gives us the most satisfactory output from among three heuristic processes used, for each scheduling problem.