Miracle-dz/UniFAR-FTUs huggingface dataset:
Carbon Emission Disclosure: Kinerja Lingkungan, Carbon Performance Dan Board Diversity

Tujuan dari penelitian ini ialah untuk menguji bagaimana pengaruh dari kinerja lingkungan, carbon performance dan board diversity terhadap carbon emission disclosure. Populasi yang digunakan pada penelitian ini ialah perusahaan non-financial yang listing di Bursa Efek Indonesia pada tahun 2018-2020. Sampel yang diperoleh pada penelitian ini dilakukan dengan menggunakan metode purposive sampling dengan menghasilkan 92 sampel perusahaan. Pengujian hhipotesis yang dilakukan menggunakan analisis regresi linear berganda. Berdasarkan analisis regresi linear berganda serta uji t menunjukkan yakni kinerja lingkungan berpngearuh terhadap carbon emission disclosure, sedangkan pada variabel carbon performance, foreign diversity serta ukuran perusahaan tidak berpengaruh terhadap carbon emission disclosure. Kata Kunci: Carbon Emission Disclosure, Board Diversity, Carbon Performance, Kinerja Lingkungan
Conditional Events and Quantum Logic

This paper begins with an overview of quantum mechanics, and then recounts a relatively recent algebraic extension of the Boolean algebra of probabilistic events to “conditional events” (order pairs of events). The main point is to show that a so-called “superposition” of two (or more) quantum events (usually with mutually inconsistent initial conditions) can be represented in this algebra of conditional events and assigned a consistent conditional probability. There is no need to imagine that a quantum particle can simultaneously straddle two inconsistent possibilities.
Products marketing policy for small scale consumer products

The development and implementation of a product marketing policy is necessary in small scale industries to boost the sales of their products. Since the small unit does not have a strong marketing network to move their products a strong marketing management programme is highly required based on various marketing strategies and tactics. Even though the government policies are in favour for generating employment opportunities in village and farmer communities, utilising the locally available natural resources, the producers are not getting sustainable income due to lack of knowledge in marketing strategies. Most of the Government of India programmes, like, Department of Science and Technology ISTED (Innovation, Science, Technology and Entrepreneurship Development) project are running in progressive mode, but, the marketing aspects with respect to economic empowerment is poor. The need for establish a strong marketing policy for sustainable income generation for such small scale production units are highlighted in the present paper, in the light of various marketing strategies and marketing tactics.
Assessment of Land Use Land Cover and River Dynamics of Himalaya: Seti River Sub-Basin of Nepal

In rapidly growing areas, land use land cover (LULC) change is one of the most pre-eminent features of environmental changes produced by human-induced activities. LULC changes are critical issues and challenges for environmentally friendly and sustainable development. Understanding land-use and land-cover (LULC) changing patterns is critical for sustainable environmental management, particularly effective water management. This study was focused on the assessment of LULC and sinuosity of the Seti River sub-Basin over 28 years. Satellite imagery of Landsat series (MS, TM, and OLI) were classified using maximum likelihood classifier to create LULC maps for 1991, 2004 and 2019. The LULC change was assessed using change detection analysis and verified the result by confuse matrix. The results showed that forest cover is regaining its original status with the increasing rate of 1.31%. In the meantime, built-up areas are expanding with the rate of 2.62% while agricultural land has decreased with the rate of -1.89% per year and are more converted to built-up area. Trendofsinuosityindexfoundincreasing and varying in different sections of the river path indicated the complex response of changing characteristics of river flow, river mining and geomorphology of landscape. Based on research findings and descriptions from earlier works, river morphology is affected by both natural (topography, climate, precipitation), and anthropogenic (rapid urbanization, foreign labor migration, abandonment of cultivable land, community forest programs, development activities) factors.
The square kilometre array: challenges of distributed operations and big data rates

The Square Kilometre Array (SKA) is an ambitious project to build the world's largest radio observatory: a low frequency (50 { 350 MHz) array in Western Australia, and a mid-frequency (0.35 { 15 GHz) array in South Africa. The SKA's Global Headquarters will be at the Jodrell Bank Observatory in the UK. Once in steady-state operations, the SKA will have one of the largest data rates of any research infrastructure in the world. One key challenge for SKA is to manage its digital data they are passed from receptors in the field, through several stages of processing before being delivered. In addition, a global network of SKA Regional Centres (SRCs) is planned, where advanced data products will be generated and processed for analysis, collaboration, publication and preservation. This paper will describe the operational concept for the SKA and the challenges faced by its distributed operational model. The paper provides an update on the current work leading to the development of a collaborative network of SRCs around the world.
Cerebral Oxygenation Responses to Standing in Young Patients with Vasovagal Syncope

Vasovagal syncope (VVS) is common in young adults and is attributed to cerebral hypoperfusion. However, during active stand (AS) testing, only peripheral and not cerebral hemodynamic responses are measured. We sought to determine whether cerebral oxygenation responses to an AS test were altered in young VVS patients when compared to the young healthy controls. A sample of young healthy adults and consecutive VVS patients attending a Falls and Syncope unit was recruited. Continuous beat-to-beat blood pressure (BP), heart rate, near-infrared spectroscopy (NIRS)-derived tissue saturation index (TSI), and changes in concentration of oxygenated/deoxygenated Δ[O2Hb]/Δ[HHb] hemoglobin were measured. BP and NIRS-derived features included nadir, peak, overshoot, trough, recovery rate, normalized recovery rate, and steady-state. Multivariate linear regression was used to adjust for confounders and BP. In total, 13 controls and 27 VVS patients were recruited. While no significant differences were observed in the TSI and Δ[O2Hb], there was a significantly smaller Δ[HHb] peak-to-trough and faster Δ[HHb] recovery rate in VVS patients, independent of BP. A higher BP steady-state was observed in patients but did not remain significant after multiple comparison correction. Young VVS patients demonstrated a similar cerebral circulatory response with signs of altered peripheral circulation with respect to the controls, potentially due to a hyper-reactive autonomic nervous system. This study sets the grounds for future investigations to understand the role of cerebral regulation during standing in VVS.
Facilitators and inhibitors of Agile methods adoption: Practitioners view

This study provides empirical evidence to the body of knowledge in Agile methods adoption in small, medium, and large organizations in the global context. This research explores facilitators and inhibitors of Agile methods adoption in software development organizations. A survey was conducted among Agile professionals to gather survey data from 52 software organizations in seven countries across the world. This study found many facilitators of Agile adoption to be significant such as customers’ dominant issues, encouragement, project champion, highly competent team, use of tools, etc. Similarly a correlation analysis revealed multiple inhibitors as significant: absence of a full set of right Agile practices, absence of customer presence, absence of tracking mechanisms during Agile progress, and failure to determine the role of the client. The present study identifies that an Agile team with high expertise and competence leads to higher quality in software, customer satisfaction along with return on investment (ROI) while a small Agile team increases ease in handling changing requirements, customer satisfaction, reduced delivery time, and increased ROI. Frequent delivery accelerates better control over work, adds to software quality, customer satisfaction, and in shortening delivery time along with increase ROI. It has also been observed that providing essential features early leads to increase in software quality and customer satisfaction. This study confirms that active customer focus leads to better control over work. Further, absence of customer decreases dealing with changing requirements, and customer satisfaction while absence of progress tracking lowers customer satisfaction.
Desempenho de Canceladores de Interferência Paralelo Multiestágio com Decisores Hard e Soft

Resumo - Analisa-se o desempenho dos canceladores de interfe-rência paralelo (PIC) multiestágio com dispositivo de decisão hard (PIC–HD) e soft (PIC–SD) do tipo linear ilimitado e tangente hiper-bólica. Para cada um destes canceladores foram obtidos desempen-hos via simulação Monte Carlo (MCS) considerando cancelamento total e parcial em canal AWGN e com desvanecimento Rayleigh. As simulações Monte Carlo mostraram que entre os canceladores de interferência paralelo multiestágio com diversos dispositivos de decisão analisados, o PIC–SD com decisor Tanh e cancelamento parcial resulta no melhor desempenho, tanto em canal AWGN co-mo em Rayleigh Plano, sendo que em canal estático observa-se uma acentuada melhoria de desempenho em relação ao PIC–HD e PIC– SD Linear ilimitado.
bHLH transcription factor family identification, phylogeny, and its response to abiotic stress in Chenopodium quinoa

The second-largest transcription factor superfamily in plants is that of the basic helix-loop-helix (bHLH) family, which plays an important complex physiological role in plant growth, tissue development, and environmental adaptation. Systematic research on the Chenopodium quinoa bHLH family will enable a better understanding of this species. Herein, authors used a variety of bioinformatics methods and quantitative Real-Time Polymerase Chain Reaction (qRT-PCR) to explore the evolution and function of the 218 CqbHLH genes identified. A total of 218 CqbHLH transcription factor genes were identified in the whole genome, located on 18 chromosomes. A phylogenetic tree was constructed using the CqbHLH and AtbHLH proteins to determine their homology, and the members were divided into 20 subgroups and one unclustered gene. Authors also analyzed 218 CqbHLH genes, conservative motifs, chromosome diffusion, and gene replication. The author constructed one Neighbor-Joining (NJ) tree and a collinearity analysis map of the bHLH family in C. quinoa and six other plant species to study the evolutionary relationship and homology among multiple species. In addition, the expression levels of 20 CqbHLH members from different subgroups in various tissues, different fruit developmental stages, and six abiotic stresses were analyzed. Authors identified 218 CqbHLH genes and studied their biological functions, providing a basis for better understanding and further studying the bHLH family in quinoa.
The improvement of wavefront cellular learning automata for task scheduling in fog computing

The rapid advancement of the “Internet of Things” (IoT) devices has led to the emergence of different types of IoT applications that need immediate response and low delay to operate. The emergence of fog computing has provided a proper platform to process fast-emerging IoT applications. Nevertheless, to name the disadvantages of fog computing devices, it can be said that they are typically distributed, dynamic, and resource-limited. Therefore, it seems a substantial challenge to schedule fog computational resources effectively to perform heterogeneous and delay-sensitive IoT tasks. The problem of scheduling tasks aimed at minimizing the energy consumption of fog nodes is formulated in this article, while meeting the requirements of the quality of service (QoS) of IoT tasks, including response time. Minimizing the deadline time and balancing the network load are also considered in the mathematical model. In the next stage, a new algorithm is introduced based on a wavefront cellular learning automata (WCLA) called the wavefront cellular learning automata improved by genetic algorithm (WCLA + GA). WCLA + GA is indeed a modified version of WCLA that has been improved using the genetic algorithm. In this version, the WCLA reinforcement signal is regulated by a genetic algorithm that accelerates the automata convergence rate. WCLA + GA is then utilized to schedule fog tasks. Simulating the proposed method followed by comparing it with other methods demonstrates that WCLA + GA performs task scheduling significantly better in terms of response time, energy consumption, and percentage of tasks that meet their deadline.
Programa de prevención de la obesidad a través del uso de una aplicación móvil. Protocolo de intervención (Obesity prevention program through the use of a mobile application. Intervention protocol)

La obesidad infantil se está convirtiendo en un problema grave de salud, por lo que es necesario el diseño de programas escolares que den solución a esta situación. Así, el objetivo de este trabajo es diseñar una intervención preventiva de la obesidad infantil en escolares de primaria, centrada en la educación nutricional y el aumento de la actividad física (AF), a través del uso de las nuevas tecnologías como elemento motivador. La muestra está formada por 80 estudiantes del tercer ciclo de Educación Primaria, 38 chicos y 42 chicas de edades comprendidas entre 10 y 13 años. Para el desarrollo del programa de fomento de la AF y de la alimentación saludable, los participantes se dividen en dos grupos que llevan a cabo el mismo programa, pero un grupo además utiliza la aplicación móvil (app) «Class Dojo» como refuerzo del mismo. De esta forma esperamos mejorar el conocimiento sobre alimentación saludable y el nivel de AF de los escolares y que esto en el futuro pueda tener un impacto significativo sobre su índice de masa corporal (IMC). Palabras clave: Intervención, obesidad infantil, alimentación, actividad física, nuevas tecnologías, educación primaria. Abstract. Childhood obesity is becoming a serious health problem, so it is necessary to design school programs that provide a solution to this situation. Therefore, the objective of this work is to design a preventive intervention for childhood obesity in primary school children, focused on nutritional education and increased physical activity (PA), using new technologies as a motivating element. The sample is made up of 80 students from the third cycle of Primary Education, 38 boys and 42 girls between the ages of 10 and 13. For the development of the program to promote PA and healthy eating, the participants are divided into two groups that carry out the same program, but one group also uses the "Class Dojo" mobile app (app) to reinforce it. Consequently, we hope to improve the nutrition knowledge and the PA level of schoolchildren and that this in the future can have a significant impact on their body mass index (BMI). Keywords: Intervention, childhood obesity, nutrition, physical activity, new technologies, primary education.
Flow-induced vibration analysis of a vehicle's front side window glass

This study analyses the flow-induced vibration of a car's front side window glass. The following working steps were carried out: experimental modal analysis to yield the dynamic characteristics of the system; wind tunnel experiments and corresponding numerical simulations with a computational fluid dynamics (CFD) code to acquire the pressure field including the fluctuations on the side glass; and a MATLAB implementation of the vibration velocity response calculated with the Corcos model and Mellen elliptical model. The MATLAB model calculates the averaged vibration velocity response by means of the pressure loading from the wind tunnel test or from the CFD simulations as well as by means of the result of the experimental modal analysis. The hereby calculated vibration response of the side glass has been validated by the results of laser Doppler vibrometer measurements in the wind tunnel. Through parameter study with the MATLAB algorithm, it was found that flow convective velocity with U c = 0.6*U, flow decay rates with α x = 0.1 and α z = 0.77 could be considered as the suitable values for the structure vibration velocity response calculation in this type of flow with a low Mach number.
A comparison principle for solutions to the Ricci flow

Barrier principles are a basic tool in the study of geometric flows. For example, if we have two solutions to the mean curvature flow with the property that one is contained in the other initially, then the maximum principle guarantees that this remains so for all subsequent times. It is a natural question whether there is a similar barrier principle for the Ricci flow. More specifically, if gt is a family of metrics evolving by Ricci flow, we want to find conditions that ensure that the evolving metrics gt stay above some family of comparison metrics. This is a non-trivial problem: indeed, while the mean curvature flow for hypersurfaces comes down to a scalar equation, the Ricci flow is a weakly parabolic system. The following is the main result of this note: Let Mm, Nn be smooth manifolds and consider families (gt)t∈[0,T ) and (ht)t∈[0,T ) on M and N . We assume that gt evolves by the Ricci flow ∂tgt = −2Ricgt and that the family ht satisfies the following condition: For every point p ∈ N and every two unit vectors u, v ⊂ TpN we have
Effects of Dried Blueberry Pomace and Pineapple Pomace on Growth Performance and Meat Quality of Broiler Chickens

Simple Summary Pomace, which is produced by fresh fruit after juice pressing, is rich in protein, crude fiber, vitamins, polyphenols, and so on. Making full use of pomace as feed in the breeding industry can reduce the need for many feed ingredients. Therefore, this study evaluated the effects of adding 3% blueberry pomace and pineapple pomace to the diet of broiler chickens on their growth performance and the quality of their meat. The results show that adding dried pomace to broiler chickens’ diets did not reduce growth performance or meat quality. This study provides a new approach and a reference for the development and utilization of broiler feed ingredients. Abstract The purpose of this study was to investigate the effects of dried blueberry pomace (BP) and pineapple pomace (PP) on the growth performance and meat quality of broiler chickens. A total of 240 1-day-old Ross 308 broiler chickens were randomly divided into 3 groups, with 10 replicates per treatment group and 8 birds per replicate (4 males and 4 females). The three groups were the control (CON) group, the 3% BP group, and 3% PP group. The entire trial period lasted 42 days. The results show that the average daily feed intake, average daily gain, and feed-to-gain ratio of the BP group and the PP group were not significantly different from those in the CON group (p > 0.05). Adding BP to the diet significantly reduced the proportion of liver and giblets (p < 0.05). Adding PP to the diet significantly reduced the proportion of liver, while the proportion of gizzard significantly increased (p < 0.05). The pH24h and L* of breast muscles were significantly lower in the PP group than in the CON group (p < 0.05). The water-holding capacity of the leg muscles in the BP group and the PP group was significantly lower than that in the CON group (p < 0.05). The crude protein content of breast muscle and the ether extract content of leg muscle in the BP group were significantly lower than those in the CON group (p < 0.05). In conclusion, the addition of 3% BP and PP to broiler chickens’ diets had no adverse effects on growth performance or meat quality.
Automatic internal crack detection from a sequence of infrared images with a triple-threshold Canny edge detector

Visual inspection and assessment of the condition of metal structures are essential for safety. Pulse thermography produces visible infrared images, which have been widely applied to detect and characterize defects in structures and materials. When active thermography, a non-destructive testing tool, is applied, the necessity of considerable manual checking can be avoided. However, detecting an internal crack with active thermography remains difficult, since it is usually invisible in the collected sequence of infrared images, which makes the automatic detection of internal cracks even harder. In addition, the detection of an internal crack can be hindered by a complicated inspection environment. With the purpose of putting forward a robust and automatic visual inspection method, a computer vision-based thresholding method is proposed. In this paper, the image signals are a sequence of infrared images collected from the experimental setup with a thermal camera and two flash lamps as stimulus. The contrast of pixels in each frame is enhanced by the Canny operator and then reconstructed by a triple-threshold system. Two features, mean value in the time domain and maximal amplitude in the frequency domain, are extracted from the reconstructed signal to help distinguish the crack pixels from others. Finally, a binary image indicating the location of the internal crack is generated by a K-means clustering method. The proposed procedure has been applied to an iron pipe, which contains two internal cracks and surface abrasion. Some improvements have been made for the computer vision-based automatic crack detection methods. In the future, the proposed method can be applied to realize the automatic detection of internal cracks from many infrared images for the industry.
Machine learning based priors for Bayesian inversion in MR imaging

The Bayesian approach allows the incorporation of informative prior knowledge to effectively enable and improve the solution of inverse problems. Obtaining prior information in probabilistic terms is, however, a challenging task. Recently, machine learning has been applied for the training of generative models to facilitate the translation of historically or otherwise available data to a prior distribution. In this work, we apply this methodology to undersampled magnetic resonance imaging. In particular, we employ an autoencoder as part of a generative model to statistically regularise and solve the high-dimensional inverse problem using Bayesian inversion. Comparison with a classical Gaussian Markov random field prior is performed and numerical examples highlight the possible advantages of data-driven priors.
Gaussian comparison and anti-concentration inequalities for norms of Gaussian random elements

We derive the bounds on the Kolmogorov distance between probabilities of two Gaussian elements to hit a ball in a Hilbert space. The key property of these bounds is that they are dimensional-free and depend on the nuclear (Schatten-one) norm of the difference between the covariance operators of the elements. We are also interested in the anti-concentration bound for a squared norm of a non-centered Gaussian element in a Hilbert space. All bounds are sharp and cannot be improved in general. We provide a list of motivation examples and applications for the derived results as well.