Miracle-dz/UniFAR-FTUs huggingface dataset:
Stereo: Assignment and Scheduling in MPSoC Under Process Variation by Combining Stochastic and Decomposition Approaches

Aggressive scaling in integrated circuits creates new challenges such as an increase in power density, temperature, and especially process variation in designing Multiprocessor Systems-on-Chip (MPSoC). While most of the previous works attempt to mitigate the process variation effects at the system level, the eventual design still suffers from the variability of frequency and leakage power. In this paper, we propose a method called Stereo that combines stochastic and decomposition to solve task assignment and scheduling under process variation in MPSoCs. In our previous work, we formulated a Mixed Integer Linear Programming (MILP) problem for variation-aware task assignment and scheduling to optimize energy consumption while meeting the real-time constraints. To capture the stochastic behavior of process variation, we employed a chance-constrained programming technique to turn the problem into a corresponding stochastic optimization that can be solved by typical ILP solvers. However, it had a scalability problem. To address this issue, in this work, we leverage a Logic-based Benders Decomposition (LBD) approach to improve the running time for finding an optimal solution of assignments and schedulings under process variation phenomenon). We carried out extensive experiments using Embedded System Synthesis Benchmarks Suite (E3S). The experimental results of the Stereo method evince considerable improvements compared to the baseline method in terms of performance-yield and run-time. The Stereo-based MILP method ameliorates performance-yield up to 2× and run-time by 532×. Moreover, for manifold applications, the Stereo-based LBD method archives 3.47×-91.49× run-time improvement compared to the Stereo-based MILP approach and is capable of assigning and scheduling of more than 50 tasks on 9 processors.
Clinical Data Analysis for Prediction of Cardiovascular Disease Using Machine Learning Techniques

Cardiovascular disease is difficult to detect due to several risk factors, including high blood pressure, cholesterol, and an abnormal pulse rate. Accurate decision-making and optimal treatment are required to address cardiac risk. As machine learning technology advances, the healthcare industry's clinical practice is likely to change. As a result, researchers and clinicians must recognize the importance of machine learning techniques. The main objective of this research is to recommend a machine learning-based cardiovascular disease prediction system that is highly accurate. In contrast, modern machine learning algorithms such as REP Tree, M5P Tree, Random Tree, Linear Regression, Naive Bayes, J48, and JRIP are used to classify popular cardiovascular datasets. The proposed CDPS's performance was evaluated using a variety of metrics to identify the best suitable machine learning model. When it came to predicting cardiovascular disease patients, the Random Tree model performed admirably, with the highest accuracy of 100%, the lowest MAE of 0.0011, the lowest RMSE of 0.0231, and the fastest prediction time of 0.01 seconds.
Sex Hormones, Growth Hormone, and the Cornea

The growth and maintenance of nearly every tissue in the body is influenced by systemic hormones during embryonic development through puberty and into adulthood. Of the ~130 different hormones expressed in the human body, steroid hormones and peptide hormones are highly abundant in circulation and are known to regulate anabolic processes and wound healing in a tissue-dependent manner. Of interest, differential levels of sex hormones have been associated with ocular pathologies, including dry eye disease and keratoconus. In this review, we discuss key studies that have revealed a role for androgens and estrogens in the cornea with focus on ocular surface homeostasis, wound healing, and stromal thickness. We also review studies of human growth hormone and insulin growth factor-1 in influencing ocular growth and epithelial regeneration. While it is unclear if endogenous hormones contribute to differential corneal wound healing in common animal models, the abundance of evidence suggests that systemic hormone levels, as a function of age, should be considered as an experimental variable in studies of corneal health and disease.
Capacity Optimization of HV Distribution Lines Based on Load Supply Capability Analysis

To reasonably choose current-carrying capacities of HV distribution lines to implement refined planning and intensive construction to select benefiting conductors to reduce invest and increase utilization of supplying equipment,a method to optimize capacity of HV distribution line based on load supply capability analysis is proposed. Firstly,the concepts of power supplying route matrix and operation/wheeling mode vector of main transformer are defined to describe the information of the wireframe of HV distribution network; then based on the analysis of load supply capability of distribution network the minimized demand on capacity of HV distribution line,which makes the load supplying capability of distribution network reaching its limit,is taken as the objective and the constraints are determined through the analysis on normal operation of HV distribution wireframe and N? 1 contingency as well as the analysis on operation/wheeling mode and the loop closing of wheeling mode,and then a mathematical model is formed; finally,a modified genetic algorithm is presented and used to solve the proposed optimization model. The effectiveness and practicality of the proposed method are verified by the calculation of a certain urban distribution network.
Los Sistemas de Información Tecnológica como herramienta para la competitividad empresarial en las MiPyMES

Existen pocos programas de gestión de informática en el sector veterinario, que solo una minoría saben usar en su trabajo diario. Sin la utilización de los sistemas de información tecnológica, el funcionamiento, el desempeño y la competitividad empresarial se verían afectados. El objetivo de la presente investigación es determinar si el uso de los sistemas de información tecnológica en el sector de las MiPyMES de servicios veterinarios en México, tienen un efecto en la competitividad empresarial, proponiendo un modelo teórico que sustenten el objetivo de la presente investigación.
Design of a Functional Pea Protein Matrix for Fermented Plant-Based Cheese

The production of a fermented plant-based cheese requires understanding the behavior of the selected raw material prior to fermentation. Raw material processing affects physicochemical properties of plant protein ingredients, and it determines their ability to form fermentation-induced protein gels. Moreover, the addition of oil also influences structure formation and therefore affects gel firmness. This study focuses on identifying and characterizing an optimal pea protein matrix suitable for fermentation-induced plant-based cheese. Stability and gel formation were investigated in pea protein matrices. Pea protein isolate (PPI) emulsions with 10% protein and 0, 5, 10, 15, and 20% olive oil levels were produced and further fermented with a starter culture suitable for plant matrices. Emulsion stability was evaluated through particle size, ζ-potential, and back-scattered light changes over 7 h. Gel hardness and oscillation measurements of the fermented gels were taken after 1 and 7 days of storage under refrigeration. The water-holding capacity of the gels was measured after 7 days of storage and their microstructure was visualized with confocal microscopy. Results indicate that all PPI emulsions were physically stable after 7 h. Indeed, ζ-potential did not change significantly over time in PPI emulsions, a bimodal particle size distribution was observed in all samples, and no significant variation was observed after 7 h in any of the samples. Fermentation time oscillated between 5.5 and 7 h in all samples. Higher oil content led to weaker gels and lower elastic modulus and no significant changes in gel hardness were observed over 7 days of storage under refrigeration in closed containers. Water-holding capacity increased in samples with higher olive oil content. Based on our results, an optimal pea protein matrix for fermentation-induced pea protein gels can be produced with 10% protein content and 10% olive oil levels without compromising gel hardness.
Genomic features underlie the co-option of SVA transposons as cis-regulatory elements in human pluripotent stem cells

Domestication of transposable elements (TEs) into functional cis-regulatory elements is a widespread phenomenon. However, the mechanisms behind why some TEs are co-opted as functional enhancers while others are not are underappreciated. SINE-VNTR-Alus (SVAs) are the youngest group of transposons in the human genome, where ∼3,700 copies are annotated, nearly half of which are human-specific. Many studies indicate that SVAs are among the most frequently co-opted TEs in human gene regulation, but the mechanisms underlying such processes have not yet been thoroughly investigated. Here, we leveraged CRISPR-interference (CRISPRi), computational and functional genomics to elucidate the genomic features that underlie SVA domestication into human stem-cell gene regulation. We found that ∼750 SVAs are co-opted as functional cis-regulatory elements in human induced pluripotent stem cells. These SVAs are significantly closer to genes and harbor more transcription factor binding sites than non-co-opted SVAs. We show that a long DNA motif composed of flanking YY1/2 and OCT4 binding sites is enriched in the co-opted SVAs and that these two transcription factors bind consecutively on the TE sequence. We used CRISPRi to epigenetically repress active SVAs in stem cell-like NCCIT cells. Epigenetic perturbation of active SVAs strongly attenuated YY1/OCT4 binding and influenced neighboring gene expression. Ultimately, SVA repression resulted in ∼3,000 differentially expressed genes, 131 of which were the nearest gene to an annotated SVA. In summary, we demonstrated that SVAs modulate human gene expression, and uncovered that location and sequence composition contribute to SVA domestication into gene regulatory networks.
When a Pandemic Enters the Game: The Initial and Prolonged Impact of the COVID-19 Pandemic on Live-Stream Broadcasters on Twitch

The global COVID-19 pandemic has accelerated the popularity of video games and online-gaming platforms. However, little research is devoted to understanding how the pandemic has affected gamers, especially live-stream broadcasters. Therefore, our study aimed to evaluate the impact the COVID-19 pandemic has had on established streamers on Twitch. By using a longitudinal time-series design and focusing on a large sample (N = 23,019) of broadcasters, we were able to determine the initial as well as prolonged effects of the pandemic on their streaming behavior. Our results suggest that the pandemic was a”game changer” for the target group, especially in regard to their choice of game settings and their focus on non-gaming content. Relating the data obtained from the target group of established streamers to the general platform data, we discuss the pandemic-related platform dynamics. © 2022 IEEE Computer Society. All rights reserved.
A Framework for Incorporating Serious Games into Learning Object Repositories through Experiential Learning

A learning environment Galore seamlessly combining serious games with generative learning objects based on an experiential learning model is described. The learning object repository in Galore allows domain experts to elucidate knowledge concepts using parameterized learning objects in diverse formats such as text, visuals, interactive widgets, as well as embedded gamelets to provide a learning experience customized to student learning preferences. Reﬂective observation and abstract conceptualization zones are explicitly modeled to support the exploratory phases of the experiential learning model. The metadata associated with the knowledge components in the environment are used to develop algorithms that automatically retrieve and synthesize lesson plans for students to achieve a speciﬁed set of learning objectives. We illustrate Galore through a case study for secure quantum internet protocols using Python Jupyter notebooks. A total of 28 notebooks and 16 gamelets using Galore cover the foundations of secure quantum internet protocols.
Perspectiva teórica entre la Inteligencia Emocional y la Resiliencia

La situación actual derivada del Covid-19 de la pandemia y que afecta a nivel mundial, ha generado cambios de alto impacto en las organizaciones. Este estudio tiene como objetivo analizar los conceptos de inteligencia emocional y la resiliencia, desde los conceptos de diferentes autores. Se examinaron 18 artículos de revistas internacionales y se analizaron desde consideraciones de factores de protección y factores de riesgo encontrándose congruencia entre ambos conceptos. Los resultados confirman dependencia de la inteligencia emocional para llegar a la habilidad de la resiliencia sin embargo el afrontamiento a situaciones adversas solo la resiliencia lo considera al 100%. Y la inteligencia emocional en un 56%. Se concluye que se debe seguir investigando la relación de ambos conceptos.
Stronger Arctic amplification from ozone-depleting substances than from carbon dioxide

Arctic amplification (AA)—the greater warming of the Arctic near-surface temperature relative to its global mean value—is a prominent feature of the climate response to increasing greenhouse gases. Recent work has revealed the importance of ozone-depleting substances (ODS) in contributing to Arctic warming and sea-ice loss. Here, using ensembles of climate model integrations, we expand on that work and directly contrast Arctic warming from ODS to that from carbon dioxide (CO2), over the 1955–2005 period when ODS loading peaked. We find that the Arctic warming and sea-ice loss from ODS are slightly more than half (52%–59%) those from CO2. We further show that the strength of AA for ODS is 1.44 times larger than that for CO2, and that this mainly stems from more positive Planck, albedo, lapse-rate, and cloud feedbacks. Our results suggest that AA would be considerably stronger than presently observed had the Montreal Protocol not been signed.
Playing to be influencers: A comparative study on Spanish and Colombian young people on Instagram

This paper explores and describes how Colombian and Spanish young people present themselves on Instagram according to the social game and the symbolic capital that they infer as normative from influencers. The methodology used combines the focus group technique (seven groups) with a content analysis of the profiles of the informants (N = 651). In total, 53 first-year creative industries university students participated. The results show that the work developed by the influencers has given rise to an aspirational narrative genre that young people tend to emulate according to the Instagram habitus in order to be recognised as leading players. Their self-presentation has three main features: a) a preference for showing ‘in-classifying’ practices such as leisure and tastes for freedom; b) the predominance of a specific type of profile and gestures that avoids self-production markers and aspires towards a global audience; and c) the normalisation of self-promotional discourse. Most informants experience Instagram as a game in which they compete to accumulate visibility conceived as relational validation, although in the case of Colombian informants there is a more professional outlook towards the platform. Finally, for all of them, Instagram constitutes a serious game, and many of them admit to feeling too exposed. As a result, they have implemented self-surveillance practices, such as consulting with peers before posting photographs, using secondary accounts and deleting posts.
Let the Cat out of the Bag: Popular Android IoT Apps under Security Scrutiny

The impact that IoT technologies have on our everyday life is indisputable. Wearables, smart appliances, lighting, security controls, and others make our life simpler and more comfortable. For the sake of easy monitoring and administration, such devices are typically accompanied by smartphone apps, which are becoming increasingly popular, and sometimes are even required to operate the device. Nevertheless, the use of such apps may indirectly magnify the attack surface of the IoT device itself and expose the end-user to security and privacy breaches. Therefore, a key question arises: do these apps curtail their functionality to the minimum needed, and additionally, are they secure against known vulnerabilities and flaws? In seek of concrete answers to the aforesaid question, this work scrutinizes more than forty chart-topping Android official apps belonging to six diverse mainstream categories of IoT devices. We attentively analyse each app statically, and almost half of them dynamically, after pairing them with real-life IoT devices. The results collected span several axes, namely sensitive permissions, misconfigurations, weaknesses, vulnerabilities, and other issues, including trackers, manifest data, shared software, and more. The short answer to the posed question is that the majority of such apps still remain susceptible to a range of security and privacy issues, which in turn, and at least to a significant degree, reflects the general proclivity in this ecosystem.
FROM TRADITIONAL TO DIGITAL ASSET MANAGEMENT OF NETWORK COMPONENTS

This paper has, as a main objective, to go deep in the applications needed, at an ecosystem level, to have a proper inventory of traditional and digital assets taking inspiration from IEC TC57 as a reference architecture. In addition, the paper will also define the data exchange and services needed between the new electronic devices and the application installed in DSO premises to control and manage easily hundreds of deployed devices, mainly in secondary substations. This should be considered as the initial key step towards a digital twin of the electrical network. The final aim is having a holistic approach to the management of all the assets involved in the operation of the distribution network.
Adaptive Market Hypothesis and Time-varying Contrarian Effect: Evidence From Emerging Stock Markets of South Asia

This study contributes to the growing debate on the relation between varying stock market conditions and the profitability of stock market anomalies. We investigate the effect of changed market conditions on time-varying contrarian profitability in order to examine the presence of the Adaptive Market Hypothesis (AMH) in South Asian emerging stock markets. The empirical findings reveal that a strong contrarian effect holds in all the emerging markets. We also find the stock return opportunities vary over time based on contrarian portfolios. We show that contrarian returns strengthen during the down state of market, higher volatility and crises periods, particularly during the Asian financial crisis. Interestingly, the market state instead of market volatility is the primary predictor of contrarian payoffs, which contradicts the findings of developed markets. We argue that the linkage arises from structural and psychological differences in emerging markets that produce unique intuitions regarding stock market anomalies returns. The overall findings on the time-varying contrarian returns in this study provide partial support to AMH. Another significant outcome of this study implies that investors in South Asian emerging markets, like investors in the developed markets, could not adapt to evolving market conditions. Therefore, contrarian profits often exist, and persistent weak-form market inefficiencies prevail in these markets.
Generation of bright monomeric red fluorescent proteins via computational design of enhanced chromophore packing

Red fluorescent proteins (RFPs) have found widespread application in chemical and biological research due to their longer emission wavelengths. Here, we use computational protein design to increase the quantum yield and thereby brightness of a dim monomeric RFP (mRojoA, quantum yield = 0.02) by optimizing chromophore packing with aliphatic residues, which we hypothesized would reduce torsional motions causing non-radiative decay. Experimental characterization of the top 10 designed sequences yielded mSandy1 (λem = 609 nm, quantum yield = 0.26), a variant with equivalent brightness to mCherry, a widely used RFP. We next used directed evolution to further increase brightness, resulting in mSandy2 (λem = 606 nm, quantum yield = 0.35), the brightest Discosoma sp. derived monomeric RFP with an emission maximum above 600 nm reported to date. Crystallographic analysis of mSandy2 showed that the chromophore p-hydroxybenzylidene moiety is sandwiched between the side chains of Leu63 and Ile197, a structural motif that has not previously been observed in RFPs, and confirms that aliphatic packing leads to chromophore rigidification. Our results demonstrate that computational protein design can be used to generate bright monomeric RFPs, which can serve as templates for the evolution of novel far-red fluorescent proteins.
The Limits of Open Innovation: A Literature Review and Research Agenda

Open Innovation (OI) has become a popular method of value co-creation over the past two decades. While OI offers many benefits, it holds a high failure rate. Through a systematic literature review, this paper identifies 15 common limitations of OI that contribute to this high failure rate at three levels: organizational, operational
Species diversity, molecular phylogeny and ecological habits of Cyanosporus (Polyporales, Basidiomycota) with an emphasis on Chinese collections

﻿Abstract Cyanosporus is a genus widely distributed in Asia, Europe, North America, South America and Oceania. It grows on different angiosperm and gymnosperm trees and can cause brown rot of wood. Blue-tinted basidiomata of Cyanosporus makes it easy to distinguish from other genera, but the similar morphological characters make it difficult to identify species within the genus. Phylogeny and taxonomy of Cyanosporus were carried out based on worldwide samples with an emphasis on Chinese collections, and the species diversity of the genus is updated. Four new species, C.flavus, C.rigidus, C.subungulatus and C.tenuicontextus, are described based on the evidence of morphological characters, distribution areas, host trees and molecular phylogenetic analyses inferred from the internal transcribed spacer (ITS) regions, the large subunit of nuclear ribosomal RNA gene (nLSU), the small subunit of nuclear ribosomal RNA gene (nSSU), the small subunit of mitochondrial rRNA gene (mtSSU), the largest subunit of RNA polymerase II (RPB1), the second largest subunit of RNA polymerase II (RPB2), and the translation elongation factor 1-α gene (TEF). Our study expanded the number of Cyanosporus species to 35 around the world including 23 species from China. Detailed descriptions of the four new species and the geographical locations of the Cyanosporus species in China are provided.