Miracle-dz/UniFAR-FTUs huggingface dataset:
EFFECT OF WATER STRESS ON LEAF CHLOROPHYLL CONTENT (CHL-A, B & TOTAL CHLOROPHYLL) OF POTATO CULTIVARS

Four potato cultivars namely Kufri Chipsona-1, Kufri Pukhraj, Kufri Lauvkar and Desiree were investigated under water stress conditions with respect to three growth stages viz. tuber initiation (T2), tuber enlargement (T3) and tuber maturation stage (T4). In present study chlorophyll-a, chlorophyll-b and total chlorophyll content per gram fresh weight was found to be higher under water stress in comparison with that of well-waterd control. Chlorophyll-a content increased significantly due to water stress treatments at different growth stages against well watered control (T1). Maximum chlorophyll ‘a’, ‘b’ and total chlorophyll content were recorded under water stress treatment at tuber enlargement stage (T3) whereas minimum observed when water stress was imposed at tuber maturation stage (T4). Among four cultivars evaluated Kufri Pukhraj recorded maximum chlorophyll ‘a’, chlorophyll ‘b’ and total chlorophyll contents.
Optimizing Markov Random Field Inference via Event-Driven Gibbs Sampling for GPUs

A Markov Random Field (MRF) is a graphical model for representing a wide range of applications in statistical machine learning [4]. MRF encodes the conditional dependence among random variables (RVs). One approach to solving problems represented by MRF is using probabilistic algorithms, e.g., Gibbs sampling [2]. These methods go through all RVs in the MRF model and update them iteratively, until converged to the ﬁnal result. This process relies on sampling from probability distributions, which is often computationally intensive.
To Err.Is Human: Characterizing the Threat of Unintended URLs in Social Media

—To make their services more user friendly, online social media platforms automatically identify text that corresponds to URLs and render it as clickable links. In this paper, we show that the techniques used by such services to recognize URLs are often too permissive and can result in unintended URLs being displayed in social network messages. Among others, we show that popular platforms (such as Twitter) will render text as a clickable URL if a user forgets a space after a full stop at the end of a sentence, and the ﬁrst word of the next sentence happens to be a valid Top Level Domain. Attackers can take advantage of these unintended URLs by registering the corresponding domains and exposing millions of Twitter users to arbitrary malicious content. To characterize the threat that unintended URLs pose to social media users, we perform a large-scale study of unintended URLs in tweets over a period of 7 months. By designing a classiﬁer capable of differentiating between intended and unintended URLs posted in tweets, we ﬁnd more than 26K unintended URLs posted by accounts with tens of millions of followers. As part of our study, we also register 45 unintended domains and quantify the trafﬁc that attackers can get by merely registering the right domains at the right time. Finally, due to the severity of our ﬁndings, we propose a lightweight browser extension which can, on the ﬂy, analyze the tweets that users compose and alert them of potentially unintended URLs and raise a warning, allowing users to ﬁx their mistake before the tweet is posted.
Hospital Equipment Management System for a Poor Resource Setting

Hospital equipment management plays a vital role in ensuring of good healthcare service in the region or country which indicates the need of properly managed hospital equipment in healthcare setting. Healthcare staff including doctors, nurses or other supporting staff cannot perform well to provide good health, without having properly managed hospital equipment. Delivery of poor quality health service may be resulted with the absence of well-developed hospital equipment management system which can leads to disability or death sometimes. Development of hospital equipment management system using Japanese 5S total quality management tool was propose with this paper. Although this is simple and cheaper method, can achieve dramatically significant change to healthcare system.
TOURISM QUALITATIVE FORECASTING SCENARIO BUILDING THROUGH THE DELPHI TECHNIQUE

Futures analyses and scenario-building exercises have received scant attention from scientific literature on the planning and management of tourist destinations. This article emphasizes the importance of a territorial foresight strategy and scenario building in the planning and management of tourist destinations, demonstrating how it is methodologically possible to combine the Delphi technique with a scenario-building exercise. The findings suggest that the knowledge provided by stakeholders operating within the tourism system can benefit the planning and management of tourist destinations.
The Call of the Wild: The Transformative Nature of Nature

Positive psychology is concerned with guiding individuals toward the good life. It does so by defining well-being and providing ways to both measure and increase it. Often this pursuit of well-being requires and results in transformation and growth. Although personal growth can occur in many different settings nature, specifically the wilderness, provides a compelling environment for just such transformational change. There are two distinct components to a wilderness experience: physical and psychological. Unique factors of the physical wilderness setting contribute to the profound psychological experiences that happen there. Through the lens of positive psychology, this paper will explore the transformative nature of nature. Awe, personal growth and transformation, self-efficacy, resilience, and optimism will be discussed. The author will draw liberally upon her own and other's wilderness adventure experience in order to illustrate the concepts presented. Suggestions for future research will be made.
Disclosure Regulation and Competitive Interactions: Evidence from the Oil and Gas Industry

We study the effects of mandatory disclosure on competitive interactions in the setting of oil and gas (O&G) reserve disclosures by North American public firms. We document that reserve disclosures inform competitors: when one firm announces larger increases in O&G reserves, competitors experience lower announcement returns and higher real investments. To sharpen identification, we analyze several sources of cross-sectional variation in these patterns, the degree of competition, and the sign and the source of reserves changes. We also exploit two plausibly exogenous shocks: the tightening of the O&G reserve disclosure rules and the introduction of fracking technology. Additional tests more directly focused on the presence of proprietary costs confirm that the mandated reserve disclosures result in a relative loss of competitive edge for announcing firms. Our collective evidence highlights important trade-offs in the market-wide effects of disclosure regulation.
BEM-BASED FINITE ELEMENT METHOD WITH PROSPECTS TO TIME DEPENDENT PROBLEMS

The requirement of flexible mesh handling gains more and more importance in the numerical treatment of boundary value problems. The recent BEM-based Finite Element Method is applicable on general polygonal and polyhedral meshes and yields conforming approximations, due to the implicit definition of trial functions in a Trefftzlike manner. These functions are treated by means of local Boundary Element Methods (BEM) in the computational realization. The method is reviewed and applied to a time dependent model problem, where the integration in time is performed with the help of a singly diagonally implicit Runge-Kutta scheme.
Practical Non-Interactive Searchable Encryption with Forward and Backward Privacy

—In Dynamic Symmetric Searchable Encryption (DSSE), forward privacy ensures that previous search queries cannot be associated with future updates, while backward privacy guarantees that subsequent search queries cannot be associated with deleted documents in the past. In this work, we propose a generic forward and backward-private DSSE scheme, which is, to the best of our knowledge, the ﬁrst practical and non-interactive Type-II backward-private DSSE scheme not relying on trusted execution environments. To this end, we ﬁrst introduce a new cryptographic primitive, named Symmetric Revocable Encryption (SRE), and propose a modular construction from some succinct cryptographic primitives. Then we present our DSSE scheme based on the proposed SRE, and instantiate it with lightweight symmetric primitives. At last, we implement our scheme and compare it with the most efﬁcient Type-II backward-private scheme to date (Demertzis et al. , NDSS 2020). In a typical network environment, our result shows that the search in our scheme outperforms it by 2 − 11 × under the same security notion.
PHENOTYPIC CHARACTERIZATION AND MOLECULAR IDENTIFI- CATION OF N2 FIXING SYMBIOTIC RHIZOBIA OF DICHROSTACHYS CINEREA FROM ARID AND SEMI-ARID SOILS OF RAJASTHAN, INDIA

Small tree form legume Dichrostachys cinerea is widely spread in western and southern states of India, but its N2 fixing root nodule symbionts are not known so far. Here we report phenotypic and genotypic characterization of its rhizobia including their molecular identification. To trap its rhizobia seeds were grown in soils collected from eight sampling sites from arid and semi-arid regions of Rajasthan. Total twenty rhizobia were isolated which included both fast-growing mucilaginous EPS producing strains and gummy slow-growing strains. Six strains were phenotypically characterized of which the fast-growing rhizobia tolerated up to 1% NaCl and 48°C temperature, grew at pH range 6-11 and were acid producers. While the slowgrowing rhizobia survived up to 0.5% NaCl, 48°C, pH range 5-11 and produced alkali. Fast-growing strains were resistant to antibiotic Erythromycin (E15) while slow-growing were resistant to Tetracycline (TE30) and Ciprofloxacin (CIP5). Xylose and dextrose sugars were utilized by all tested strains. RPO1 primer based DNA fingerprinting of fourteen strains indicated significant genetic diversity among the D. cinerea rhizobia forming seven individual RAPD genotypes and three groups. 16S rRNA gene sequencing of five strains revealed that the fast-growing strains belonged to species of Ensifer and the slowgrowing strains were identified as species of Bradyrhizobium. This suggests that D. cinerea is nodulated by both slowgrowing (Bradyrhizobium) and fast-growing (Ensifer) alpha-rhizobia. Such phenotypically and genetically diverse rhizobia obtained from the arid environments of Rajasthan need further evaluation to screen them for their ability to nodulate other host plants for their potential use in agroforestry, reforestation and agriculture establishment programs specifically in desert regions to improve soil and plant health.
A Microservice Decomposition Method Through Using Distributed Representation of Source Code

This research proposed a novel decomposition method for refactoring monolithic applications into microservices applications using a neural network model (code2vec) for creating code embeddings from the monolithic application source code. As a Result, semantically similar code embeddings are clustered through a hierarchical clustering algorithm to produce microservices candidates to resemble the domain model more efficiently. The quality characteristics of the results were measured using two metrics for measuring cohesion. These metrics were Cohesion at Message Level (CHM) and Cohesion at Domain Level (CHD). Also, four applications were used as test cases with different sizes ranging from small to big applications. The proposed method showed promising results in terms of cohesion when compared to other decomposition methods. The proposed method scored better scores in 5 out of 8 tests compared to other methods. Also, averaged CHD and CHM results were 0.52 and 0.76, respectively, for the proposed method, better results when compared to the other methods.
Physical profile of junior and senior amateur boxers

© JPES. Purpose: The purpose of this study was to profile the physiological characteristics of amateur boxers using a battery of tests designed to assess the physiological and physical demands required for performance. Fifteen junior amateur (age 14.9 ± 2.0 years; stature 164 ± 12 cm; body mass 50.9 ± 11.3 kg) and sixteen senior amateur boxers (n = 16; age 20.5 ± 4.0 years; stature 174 ± 9 cm; body mass 65.2 ± 10.7 kg) provided informed consent to participate in the study. Body composition, squat jump (SJ), countermovement jump (CMJ), 5-and 10 m sprint (5SP/10SP), press up (PU), right and left medicine-ball single-arm throws (MBR, MBL), repeated sprint test (RST) and Yo-Yo intermittent recovery test level 1 (YY) were performed. The likelihood (% chance) of between-group differences were assessed using a magnitude based approach, standardised-difference score (Cohen’s d) and 90% confidence intervals [CI]. Linear regression (r) was used to examine the association between variables. Results: Senior boxers outperformed (79 to 99% chance) junior counterparts in PU, YY, CMJ, SJ, 10SP, MBL and MBR tests (d ≥ 0.50 [-0.34 to 1.61]). There were very large (r 0.70) correlations between fat free mass, upper-and lower body lean mass and medicine ball throw distance. There were large correlations (r 0.50 to 0.69) between medicine ball throw distance and CMJ, SJ, PU, 5SP and 10SP. Conclusions: A simple and time-effective test battery was able to differentiate performance between junior and amateur boxers. These assessments could be useful when profiling junior and senior amateur boxers.
Classical Machine Learning Methods in Economics Research: Macro and Micro Level Examples

Paper reviews the classical methods of machine learning (supervised and unsupervised learning),gives examples of the application of different methods and discusses approaches that will be useful for empiricaleconomics research (on data from Ukrainian firms, banks and official state statistics). The different sectors ofeconomics are investigated: the multiple linear regression is used on macrolevel for macro production functionof Ukraine specification; logistic regression is used in bank sector for credit risk management with the scoringmodel; k-means, hierarchic clustering and DBSCAN are used in regional level for regions of Ukraine groupingbased on competitiveness; principal component analysis is used for firm’s financial stability analysis. All modelsshowed adequate simulation results according to the quality criteria of the models. So, the possibility ofclassic machine learning methods application for investigations of the processes and objects on different levelsof economics (micro, mezzo and macro) is demonstrated in the article.
Test Case Quality: Issues and Limitations in Agile Software Development

In the Agile software development environment, continuous changes in user requirements lead to an increase in the importance of a testing process to demonstrate a quality product. As test case is a cornerstone of the testing process, it is important to emphasize the high-quality construction of the test cases. Hence, testing process should be adequately planned and evaluating the quality of test cases can help to explain some important issues associated with software testing. However, findings from literature and the critical analysis of empirical studies revealed that less academic research has investigated the test case quality in Agile software development process. Therefore, with a specific reference to scrum methodology, the purpose of this paper is to identify the problems of test case quality in Agile software development by reviewing the existing work concerning testing quality in Agile. This paper has made a useful contribution by illustrating and clarifying the shortcomings of test case quality in agile projects and pointing out the factors that help to improve it.
High-affinity tamoxifen analogues retain extensive positional disorder when bound to calmodulin

Abstract Using a combination of NMR and fluorescence measurements, we have investigated the structure and dynamics of the complexes formed between calcium-loaded calmodulin (CaM) and the potent breast cancer inhibitor idoxifene, a derivative of tamoxifen. High-affinity binding ( Kd∼300 nM) saturates with a 2:1 idoxifene:CaM complex. The complex is an ensemble where each idoxifene molecule is predominantly in the vicinity of one of the two hydrophobic patches of CaM but, in contrast with the lower-affinity antagonists TFP, J-8, and W-7, does not substantially occupy the hydrophobic pocket. At least four idoxifene orientations per domain of CaM are necessary to satisfy the intermolecular nuclear Overhauser effect (NOE) restraints, and this requires that the idoxifene molecules switch rapidly between positions. The CaM molecule is predominantly in the form where the N and C-terminal domains are in close proximity, allowing for the idoxifene molecules to contact both domains simultaneously. Hence, the 2:1 idoxifene:CaM complex illustrates how high-affinity binding occurs without the loss of extensive positional dynamics.
Regge Trajectories of Meson Excitations in the Pseudo-scalar and Vector Channels: Exploring the Dyson-Schwinger – Bethe-Salpeter Approach

Despite of the apparent simplicity of the Lagrangian where Quantum Chromodynamics (QCD) is based upon, it encodes an enormous richness of phenomena, most of them related to the non-perturbative regime. While lattice QCD allows for an access to many facets of the hadron spectra, the so called XYZ states pose still a challenge [1]. Apart the quantitatively adequate description of low-lying hadron states in various flavor channels, the higher excitations call also for a description and confrontation with experimentally well established facts. It is known for a long time that mesons of a given flavor composition can be grouped on radial Regge trajectories according to M n = M 2 0 +nμ , where Mn stands for the mass (energy) labeled by the radial quantum number n = 0, 1, 2, · · · , M0 denotes the ground state mass of a respective trajectory and μ = 1.25 GeV [2] or 1.35 GeV [3] is a universal slope parameter (cf. [3, 4] for a recent account and [5–8] for the discussion of the experimental data base). More generally, Ref. [9] advocates an ordering according to M n,J = â(n+ J) + ĉ, where J stands for the angular momentum and â and ĉ are appropriate constants, see also [10]. Often, a grouping according to M J = M (0) + β̂J is considered prototypically for a linear orbital Regge trajectory. While being a phenomenological ordering scheme, the arrangement of hadron states on Regge trajectories should emerge from QCD, ideally directly without approximations or based on certain symmetries or as result of suitable models. In fact, the relativistic quark model [11, 12] delivers such linear trajectories. Also holographic models based on the AdS/CFT correspondence (cf. [6, 13]) cope with Regge trajectories [14], or even use them as input for constraining the dilaton dynamics for further investigations [15–17]. Moreover, functional formulations of QCD such as combined Dyson-Schwinger (DS) and Bethe-Salpeter (BS) equations address the issue of recovering Regge trajectories [18, 19] with appropriate interactions
Development and Validation of the Suicide Behaviours Questionnaire – Autism Spectrum Conditions in Autistic, Possibly Autistic and Non-Autistic Adults.

Background: Autistic people and those with high autistic traits are at high risk of experiencing suicidality. Yet, there are no suicidality assessment tools developed or validated for these groups.Methods: A widely used and validated suicidality assessment tool developed for the general population (SBQ-R), was adapted using feedback from autistic adults. The adapted tool was refined through 9 interviews, and an online survey with 251 autistic adults, to establish clarity and relevance of the items. Subsequently, 308 autistic, 113 possibly autistic, and 268 non-autistic adults completed the adapted tool online, alongside self-report measures of autistic traits (AQ), camouflaging autistic traits (CAT-Q), depression (PHQ-9), anxiety (ASA-A), thwarted belongingness and perceived burdensomeness (INQ-15), lifetime non-suicidal self-injury, and the original version of the suicidality assessment tool (SBQ-R). Analyses explored the appropriateness and measurement properties of the adapted tool between the groups.Results: There was evidence in support of content validity, structural validity, internal consistency, convergent and divergent validity, test retest validity, sensitivity and specificity (for distinguishing those with or without lifetime experience of suicide attempt), and hypothesis testing of the adapted tool (SBQ-ASC) in each group. The structure of the SBQ-ASC was equivalent between autistic and possibly autistic adults, regardless of gender, or use of visual aids to help quantify abstract rating scales.Limitations: The samples involved in the development and validation of the adapted tool were largely female, and largely diagnosed as autistic in adulthood, which is not representative of the wider autistic population. The SBQ-ASC has been developed for use in research and is not recommended to assess risk of future suicide attempts and/or self-harm.Conclusions: The SBQ-ASC is a brief self-report suicidality assessment tool, developed and validated with and for autistic adults, without co-occurring intellectual disability. The SBQ-ASC is appropriate for use in research to identify suicidal thoughts and behaviours in autistic and possibly autistic people, and model associations with risk and protective factors.
MuTent: Dynamic Android Intent Protection with Ownership-Based Key Distribution and Security Contracts

Intents are the plain-text based message object used for ICC by the Android framework. Hence the framework essentially lacks an inbuilt security mechanism to protect the visibility, accessibility, and integrity of Intent’s data that facilitates adversaries to intercept or manipulate the data. In this work, we investigate the Intent protection mechanism and propose a security-enhanced Intent library μTent that allows Android apps to securely exchange sensitive data during ICC. Differently from the existing mechanism, μTent provides accessibility and visibility of Intent data by validating the receiver’s capability and provides integrity by using encryption and the Arc security contract code. Especially, ICC is initiated by exchanging μTent and follows a novel ownership-based key distribution model, that restricts the malware apps without permission from deciphering data. Through the evaluation, we show that μTent can improve the security for popular Android apps with minimal performance overheads, demonstrated using