Miracle-dz/UniFAR-FTUs huggingface dataset:
Enabling security for the Industrial Internet of Things using deep learning, blockchain, and coalitions

In a wireless Industrial Internet of Things (IIoT) network, enforcing security is a challenge due to the large number of devices forming the network and their limited computation capabilities. Furthermore, different security attacks require specifically tailored security protocols to prevent their occurrence. As an alternative to these conventional centralized security protocols, the application of Blockchain (BC) and Deep learning (DL) for securing IIoT networks hold great potential. BC facilitates security by being an immutable record of the changes happening in a network. Coalition Formation theory aids decentralization and promotes energy efficiency. And to enforce a state‐of‐the‐art attack detection technique, Deep learning provides an adaptive and reliable platform. Thus, in this paper, a security framework that facilitates generalized security for the IIoT network using BC and Coalition Formation theory is proposed. Additionally, we promote a sophisticated deep learning‐based classification algorithm to efficiently classify malicious and benign devices in IIoT scenarios. In the proposed model, connection links can only be established if the details of the connection are mined on the BC by the “sender” device. Therefore, we propose a Proof of Reliance algorithm that dynamically increases the computational difficulty to prevent malicious devices from attacking the network. Through simulations, it is experimentally proven that malicious devices can never attack the network when the proposed framework is employed for IIoT security.
Characterising fitness landscapes of protein evolution by next-generation sequencing

A protein’s amino acid sequence determines its structural, chemical and physical properties, yet how sequence variation influences protein function is still incompletely understood. Protein fitness landscapes powerfully describe the sequence-function relationship by dividing sequence space into functional hills and valleys. This representation is often invoked yet lacks experimental evidence; the immense vastness of possible sequence space makes comprehensive high-quality datasets difficult to obtain. Laboratory directed evolution has focused on optimal utilisation of substitution libraries, however examination of functional innovation in Nature shows that short insertions and deletions (InDels) also play a key role. Beyond rare targeted studies of specific InDels, high-throughput data on fitness landscape for mutations other than substitutions are lacking entirely. In my PhD, I worked towards experimentally describing the fitness landscapes of InDels and substitutions in three systems: GFP, phosphotriesterase (PTE) and the kinase MKK1 docking domain. Towards this goal, I established two experimental assays (GFP, PTE) for deep mutational scanning and a new software toolkit, InDelScanner, for interpreting resulting data that contain InDels. With GFP, I sorted the deletions and substitution libraries into three activity fractions using FACS, then deep sequenced them with Illumina MiSeq to obtain a pilot dataset. The comparison of deletion effects between different lengths of deletions (-3, -6 and -9 bp) indicates that deletions are partially tolerated in eGFP, with tolerance improved for short deletions and in the stabilised starting point GFP8. Further interpretation of data was complicated by limited resolution in the sequencing dataset stemming from poor FACS separation, so I optimised the conditions for better sorting resolution using the mKate2 fluorescent protein as an expression reporter. In the second iteration of the activity sorting I additionally included UMIs in the plasmid design to improve the utilisation of NGS capacity. In the case of PTE, I performed proof-of-concept experiments for microfluidic droplet sorting in an integrated device with an in-line incubation line and a fluorescent sorting design. In parallel, testing of solubility and activity of random InDel variants showed that functional
Making the Unsustainable Sustainable: How Swedish Secondary School Teachers Deal with Sustainable Development in Their Teaching

The aim of this article is to investigate how Swedish teachers manage the uncertainty and complexity associated with sustainable development (SD) as a field of knowledge, in relation to the requirements in the school curriculum. Underlying the whole concept of sustainable development is the vision that there is a possible solution to the ecological, economic and social problems created by humans. However, it is not so clear what this solution actually means in practice. The article builds on an analysis of transcribed individual and group interviews with 40 teachers at Swedish lower and upper secondary schools, related to the topic of sustainable development as a field of knowledge. A thematic analysis was carried out by identifying four broad themes, including dominating discourses. The results indicate that there is a lack of vision among the teachers for a future sustainable society, while at the same time, it seems to be taboo to talk about what an unsustainable society might mean in the long run. Presentations of the problems and knowledge of what causes them must always be combined with instructions on how problems can be solved and how pupils can influence their own future and help create sustainable development. The starting point for such a solution-oriented approach to SD is based on an assumption that individual behaviour is essential to achieving sustainable development and thus that individual responsibility is crucial. This focus leads to individual consumer choices, behaviours and lifestyles at the heart of teaching, while progressive, alternative visions and critical perspectives are downplayed.
Linguistic recycling and its relationship to academic conflict

Abstract Reaching an understanding of how scholarly writers manage linguistic recycling remains a focus of many studies in applied linguistics, bibliometrics, and the sociology of science. The value apportioned to citations in research assessment protocols is one factor in this sustained interest, the challenges that managing intertextuality present for novice scholars, another. Applied linguists such as Harwood (2009) and Hyland and Jiang (2017) alongside sociologists of science have studied citation practices largely from the point of view of writers’ reasons for citing (see Erikson & Erlandson, 2014 for a review) or readers’ understanding of the function of the citation (e.g., Willett, 2013). Linguistic recycling as direct quotation of previously published research has received less attention from applied linguists, a notable exception being Petric’s (2012) examination of students’ quotation practices. Her study focuses on quoting writers’ intentions. We know less, however, about cited authors’ responses to quotations of their work. It is these responses that form the focus of our study. Taking our two most frequently cited publications, we compiled a corpus of direct quotations noting the quotation strategy and our responses to each instance of the reuse of our words. These responses ranged from pride and satisfaction through to annoyance at an instance of blatant misquotation. We then extended our corpus to include quotations from publications by three scholars who have played a role in debate around a key controversy in the English for research publication purposes (ERPP) literature. We presented these scholars with a representative sample of quotations of their publications related to the controversy and asked them to indicate which instances they regarded as unwarranted. Analysis of these authors’ responses provides insights into the relationship of direct quotation to the rhetorical management of academic conflict. We suggest possible parallels with the expression of discrepancy in other domains.
Implication of Data Mining and Machine Learning in Software Engineering Domain for Software Model, Quality and Defect Prediction

: Software metrics have a direct link with measurement in software engineering. Correct measurement is the prior condition in any engineering fields, and software engineering is not an exception, as the size and complexity of software increases, manual inspect becomes a harder task. Most Software Engineers worry about the quality of software, how to measure and enhance its quality. The overall objective of this study was to asses and analysis’s software metrics used to measure the software product. Developers have attempted to improve software quality by mining and analyzing software data. In any phase of software development life cycle (SDLC), while huge amount of data is produced, some design, security, or software problems may analyze software data helps to handle these problems and lead to more accurate and timely delivery of software projects. Various data mining and machine learning studies have been conducted to deal with software engineering tasks such as defect prediction, effort estimation, etc. This study shows the open issues and presents related solutions and recommendations in software engineering, applying data mining and machine learning techniques. Software quality is a field of study and practice that describes the desirable attributes of software products. The performance must be perfect without any defects. Software quality metrics are a subset of software metrics that f software defect prediction model helps in early detection of defects and contributes to their efficient removal and producing a quality software system based on several metrics. The main paper is to help developers identify defects based on existing software metrics using data mining techniques and thereby improve the software quality. In this paper, various classification are revisited which are employed for software defect prediction using software metrics in the literature.
Characterizing short-term light dynamics in forested headwater streams

Light controls local- and reach-scale primary production in forested headwater streams. In terrestrial ecosystems, short periods of elevated light beneath canopies (sunflecks) are instrumental in maintaining understory autotrophic production, but sunflecks are unexplored and uncharacterized in stream systems. We described short-term light dynamics in 4 forested headwater streams in the western Cascade Mountains of Oregon. We quantified the prevalence and characteristics of sunflecks, compared the timing of light exposure at stream sites to a sensor in full sun, and evaluated whether sunfleck characteristics differed between stream sections in old-growth vs second-growth forest. Sunflecks were common in streams. A minimum of 3 individual sunflecks/d occurred at each of 47 sensor locations. Short sunflecks were more common than long sunflecks, a result consistent with findings in terrestrial studies. However, streams had longer sunflecks than upland forests in this region, probably because canopy gaps are larger over stream channels than in the forest. In >½ of the 47 sensor locations, daily light distributions differed between in-stream and full-sun locations, revealing that canopies affect both the total light and the timing of light delivery to understory locations. The timing of peak stream temperature coincided better with light delivery by sunflecks than in full sun. Peak stream temperature was offset by ≥3 h from midday peak light in full sun, but beneath the forest canopy at the 4 surveyed streams, 26 to 60% of sunfleck events occurred within 2 h of peak stream temperature. These findings highlight the presence and potential importance to in-stream autotrophy of short-term light events (sunflecks) in forested streams. In a model simulation, a 1-h sunfleck increased stream primary production 5 to 17%, depending on the time of day that sunfleck occurred.
Predators enhance resilience of a saltmarsh foundation species to drought

Disturbances are increasing in size and frequency with climate change, facilitating species that opportunistically exploit areas where habitat‐forming foundation species have been removed. Although it is well‐recognized that consumers, disease and weedy space‐holders can affect foundation species’ resistance to and recovery from disturbance, how predators influence their resilience is less clear. In salt marshareas de‐vegetated by drought and intensive snail Littoraria irrorata grazing (hereafter, ‘die‐offs’), we monitored bird use and experimentally manipulated bird and nekton access to the vegetated borders of die‐off mudflats across periods of both vegetation die‐off and regrowth to explore how these predators mediate the resilience of cordgrass Spartina alterniflora, the foundation species that structures US Atlantic coast salt marshes. Surveys revealed that birds, especially probers that agitate soils, forage year‐round for invertebrates in die‐off mudflats in our study area but not in adjacent vegetated areas. During periods of die‐off, cordgrass borders accessible to bird and nekton predators retreated >3‐times slower and snail densities were halved, relative to predator exclusion cages. In predator‐accessible plots, slower border retreat corresponded to greater snail infection by a bird host‐dependent trematode parasite. During recovery, cordgrass borders revegetated more quickly, and snail densities declined faster over time in unmanipulated controls relative to predator exclusions. Synthesis. These findings suggest that birds, through their transmission of parasites to snails, appear to act synergistically with snail‐consuming nekton to slow cordgrass loss after drought‐snail disturbances. Predator access also corresponds to faster cordgrass recovery as environmental conditions improve, although the mechanisms behind this need further investigation. Thus, predators that opportunistically forage within disturbances have the potential to suppress consumer impacts through multiple mechanisms, including consumption and disease transmission, thereby bolstering foundation species’ resilience and modulating whole ecosystem responses to climate change.
Thermal, Photometric and Radiometric Properties of Multi-Color LEDs Situated on the Common PCB

This paper presents the results of experimental investigations illustrating the influence of the spectra of the light emitted by power LEDs on their thermal, photometric and radiometric parameters. The investigations were performed for six diodes emitting white or monochromatic light of different spectra. Each of these diodes was produced by the same manufacturer, mounted in the same package and the tested devices were soldered to the common PCB. In the paper, the manner and set-ups making possible measurements of self and transfer transient thermal impedances, illuminance and the surface power density of the light emitted by the tested devices are described. Selected results of measurements are shown and discussed. These results prove that the spectra of the emitted light influence self-transient thermal impedances of the considered devices and transfer transient thermal impedances between some pairs of these devices. Additionally, it is proved that thermal couplings between the tested diodes strongly influence their junction temperature and the surface power density of the emitted radiation.
Practical guide for curve fitting in x-ray photoelectron spectroscopy

The use of peak fitting to extract information from x-ray photoelectron spectroscopy (XPS) data is of growing use and importance. Due to increased instrument accessibility and reliability, the use of XPS instrumentation has significantly increased around the world. However, the increased use has not been matched by the expertise of the new users, and the erroneous application of curve fitting has contributed to ambiguity and confusion in parts of the literature. This guide discusses the physics and chemistry involved in generating XPS spectra, describes good practices for peak fitting, and provides examples of appropriate use along with tools for avoiding mistakes.
Growth Response of Wheat (Triticum aestivum) Callus to Imazapyr and in Vitro Selection for Resistance

Intact wheat plants and wheat calli responded similarly to varying concentrations of imazapyr. Fifty percent growth inhibition of wheat callus occurred with 0.05 μM imazapyr after 70 d. As imazapyr concentration increased from 0 to 10 μM, the free isoleucine, leucine, and valine decreased from 160 to 35, 260 to 49, and 310 to 59 pmol mg−1, respectively. Resistant calli, which had relative growth rates exceeding a calculated upper prediction interval, were obtained by in vitro selection at 2 and 5 μM imazapyr. Resistant calli growing on 2 μM imazapyr had free isoleucine, leucine, and valine concentrations intermediate to the control and susceptible callus.
Elucidating The Influence Of Transformational Leadership On Job Performance: A Metabus-Enabled Meta-Analysis

Over the past three decades, transformational leadership has emerged as a significant antecedent of employee performance across a wide variety of contexts. Prior research has employed meta-analysis to confirm the effect of transformational leadership on job performance. While researchers and practitioners in the field of industrial and organizational psychology have relied heavily on meta-analyses, however, this approach are time consuming and also becoming increasingly difficult to obtain effect sizes as the amount of available research grows exponentially. To address this concern, we utilized metaBUS, a cloud-based research synthesis platform to identify studies conducted between 1980 and 2017. In particular, the search yielded 58031 studies with 713 effect sizes, which were used to replicate and confirm extant studies linking transformational leadership to different facets of job performance. As expected, the meta-analysis confirmed the positive relationship between transformational leadership and job performance. The practical implications and suggestions for future research have been discussed. 2357-1330 © 2020 Published by European Publisher.
El uso y la importancia de las redes sociales en el sector hotelero desde la perspectiva de los responsables de su gestión

When it started to become apparent how much social networks affect business, many organizations began to take them into account in the development of their management. The use of social networks is especially relevant in tourism companies since they largely depend on the opinion and experience of the client. Thus, this study seeks to gain a knowledge about the use and importance of social networks in the hotel sector through qualitative research based on interviews with the social network managers of ten hotel establishments. The theoretical framework has been taken into account to obtain the different categories and elaborate the research questions. Subsequently, through a content analysis using the Nvivo 11 software, subcategories with common characteristics were inductively obtained and divided into units of analysis by coding the data, thus facilitating the interpretation of the information. In the results, the social network managers interviewed stressed the importance of social media in the hotel sector to interact and interact with users. Therefore, they consider it essential to set their own goals for this area and to develop strategies depending on the social networks in which they intervene. The most prominent advantages identified are visibility, the ease of accessing information and the possibility of having a better communication, relationship and interaction with users.
Evaluation of yield of safflower (Carthamus tinctorius L.) genotypes under semi-arid conditions

Abstract To identify appropriate genotypes for breeding varieties suitable for semi-arid areas, yield components, as well as morphophonological traits of 127 safflower genotypes, were assessed at the Seed and Plant Improvement Institute, Iran. Cluster analysis revealed four distinct groups. The largest group (third cluster) includes 48 genotypes with characteristics such as mostly yellow-coloured flowers, mostly thorny with few thistle genotypes, relatively early-flowering, relatively high number of heads and grains per plant, highest 1000-grain weight with the highest grain yields. In contrast, the smallest group (second cluster) contains 13 genotypes with characteristics such as yellow florets, semi-dwarf, thorny, moderately late-flowering, low number of heads per plant and number of grains per head, low 1000-grain weight, and low grain yield. Principal component analysis results showed that the three components accounted for 29.5, 15.9 and 11.1% of the total variation, respectively. Graphic representation of the biplots based on the first and second principal components showed that the experimental genotypes were classified into four groups. The results also indicated that stem diameter, the number of branches, heads per plant and grains per head had the highest correlation with the first component, and grain yield, flower colour, flowering initiation and plant height had the highest correlation with the second component. These traits can be considered as an appropriate index for the selection of elite safflower genotypes for breeding varieties suited to cultivation in semi-arid conditions.
PEI-SiO2 composite membranes with high thermal stability: Synthesis by self-assembled in situ growth and application in lithium-ion batteries

To improve the safety of lithium-ion batteries (LIBs), a polyether amide–silica (PEI-SiO2) composite membrane was developed by the in situ hydrolysis of tetraethylorthosilicate (TEOS) and its subsequent self-assembly on the surface of PEI fibers. Because of the presence of the SiO2 shell, the PEI-SiO2 composite membrane exhibited good thermal stability at high temperatures. The composite membrane did not change its color and size after heating at 200°C for 1 h as well as exhibited excellent flame retardancy. Moreover, the membrane maintained its high porosity even after the introduction of shell layers. The electrolyte is completely absorbed in the membrane within 0.5 s. The electrolyte uptake was up to 625%, and the ionic conductivity was up to 1.9 mS/cm at room temperature. Compared to the polyolefin membrane and the pure PEI membrane, the PEI-SiO2 composite membrane showed higher electrochemical stability, with an electrochemical window of up to 5.5 V. The battery assembled with the composite membrane showed excellent cycle stability, and the capacity retention rate was as high as 98.6% after 50 cycles. The LIBs based on the PEI-SiO2 composite membrane exhibited safe operation and high electrochemical performance, thus highlighting the applicability of the composite membrane in high-power batteries.