Miracle-dz/UniFAR-FTUs huggingface dataset:
UPCYCLING AS A BUSINESS STRATEGY IN TEXTILE AND CLOTHING INDUSTRY CLUSTERS

Industrialization made consumerism an integral part of the economy, and the preoccupation with sustainable development has been debated within organizations, which seek ways to contribute to the future of the planet, aiming to minimize social and environmental impacts. In textile and clothing industry clusters, one way to minimize the environmental impact is the incorporation of Circular Economy, and upcycling can be highlighted among its practices. Under this assumption, this study aims to analyze the final customer's opinion on the incorporation of upcycling as a sustainable business strategy aimed at textile and clothing industry clusters, contributing with subsidies to the elaboration of strategies and actions for the incorporation of this practice in network companies. It is a quantitative study which utilizes a survey via online questionnaire and multivariate statistical analysis. Among the main results, it can be highlighted that the customer's frequency of practicing upcycling is correlated to their intention, to the conditions that prevent them to adhere and to the opinion of people who are considered important. It is inferred that there are many impeding conditions to the individual incorporation of the practice, and therefore there is opportunity for growth to companies, especially small businesses of the textile and clothing industry that operate in clusters, in which not only the economic and social values are involved, but also opportunities for inclusion of environmental value, considering the growth of the sustainability-focused market.
Getting a Grip on Normativity: A Phenomenological Response to Maslow’s Call for a “Humanistic Biology”

Maslow suggests that a study of “superior” human specimen might have the potential to identify biological traits that distinguish flourishing individuals from those who are languishing. Maslow’s recommendation is open to criticisms. First, his method is circular. Second, the thrust of Maslow’s project has a eugenic ring to it. However, while Maslow’s eugenic vision should be sidelined, his call for an understanding of normativity and the need to overcome the fact-value dichotomy in psychology and neuroscience are well-considered recommendations. A phenomenological approach to normativity presents a more authentically humanistic approach to consideration of normativity. Husserl’s concept of optimal givenness and Merleau-Ponty’s notion of maximum grip illustrate that normativity is a quality that can be identified at a pre-predicative, implicit level of operative intentionality. Based on an examination of the notions of optimal givenness and maximum grip, the article further suggests that, within the context of interpersonal relations, agapic love can be understood to operate as a normative and regulative idea for ethical relations. Since this form of intentionality instantiates itself into perceptual and motor habits, normative ethical relations may be subject to investigation within neuroscience, to the extent that it maintains an ongoing dialogue with phenomenology.
ADAPTASI SKALA PROSOCIALNESS FOR ADULT VERSI BAHASA INDONESIA

This study adapts and analyzes the psychometric properties of Prosocialness for Adults developed by Caprara in Indonesian with a sample of university students. The adaptation of this measuring instrument goes through several stages, starting from translation, back translation, testing the reliability coefficient, and collecting validity evidence in the form of content-based testing and internal structure testing using confirmatory factor analysis (CFA). This study involved a sample of students in Bandung and Cimahi, as many as 273 students. The results showed that the Indonesian version of PSA Scale was declared reliable (alpha Cronbach = 0.841) and met the goodness of fit index criteria. Indonesian version of the PSA Scale measuring instrument has good psychometric properties, so it can be used for research or assessment purposes that measure degree prosocial in adolescent samples. This study suggests that the Indonesian version of the PSA Scale can be developed by adding a wider variety of samples, a larger sample size, and trying to relate to other variables to increase criterion validity
Advancing Forest Monitoring and Assessment Through Immersive Virtual Reality

Abstract. The recent influx of remote and proximal sensing data provides new opportunities to understand environmental processes. A potential application of these datasets is to facilitate forestry operations. However, forest management decision-making through sensing techniques faces many challenges, partly due to the involvement of stakeholders with different knowledge levels and objectives. We present a virtual reality application developed for forest monitoring and assessment to address some of these challenges. First, a workflow for visualizing different sources of environmental sensing data is introduced to reconstruct digitally forest and terrain characteristics. Then, the VR experience is introduced in which users can observe, manipulate, and measure LiDAR-derived forest and tree models in immersive virtual environments. Finally, a heuristic expert evaluation to assess the overall user experience and the usability of individual application features is reported. We also gathered open-ended responses from domain experts to reflect on the potential and actual uses of the application in forest-related practices.
Perceived Use Cases, Barriers, and Requirements for a Smart Health-Tracking Toilet Seat: Qualitative Focus Group Study

Background Smart bathroom technology offers unrivaled opportunities for the automated measurement of a range of biomarkers and other data. Unfortunately, efforts in this area are mostly driven by a technology push rather than market pull approach, which decreases the chances of successful adoption. As yet, little is known about the use cases, barriers, and desires that potential users of smart bathrooms perceive. Objective This study aimed to investigate how participants from the general population experience using a smart sensor-equipped toilet seat installed in their home. The study contributes to answering the following questions: What use cases do citizens see for this innovation? and What are the limitations and barriers to its everyday use that they see, including concerns regarding privacy, the lack of fit with everyday practices, and unmet expectations for user experience? Methods Overall, 31 participants from 30 households participated in a study consisting of 3 (partially overlapping) stages: sensitizing, in which participants filled out questionnaires to trigger their thoughts about smart bathroom use and personal health; provotyping, in which participants received a gentle provocation in the form of a smart toilet seat, which they used for 2 weeks; and discussion, in which participants took part in a web-based focus group session to discuss their experiences. Results Participants mostly found the everyday use of the toilet, including installation and dismantling when necessary, to be relatively easy and free of complications. Where complications occurred, participants mentioned issues related to the design of the prototype, technology, or mismatches with normal practices in using toilets and hygiene. A broad range of use cases were mentioned, ranging from signaling potentially detrimental health conditions or exacerbations of existing conditions to documenting physical data to measuring biomarkers to inform a diagnosis and behavioral change. Participants differed greatly in whether they let others use, or even know about, the seat. Ownership and control over their own data were essential for most participants. Conclusions This study showed that participants felt that a smart toilet seat could be acceptable and effective, as long as it fits everyday practices concerning toilet use and hygiene. The range of potential uses for a smart toilet seat is broad, as long as privacy and control over disclosure and data are warranted.
A new magnet design for future Kibble balances

We propose a new permanent magnet system for Kibble balance experiments, which combines advantages of the magnet designs invented by the National Physical Laboratory (NPL) and by the Bureau International des Poids et Mesures (BIPM). The goal of the proposed magnet system is to minimize the coil-current effect and to optimize the shielding at the same time. In the proposed design, a permanent magnet system with two gaps, each housing a coil, is employed to minimize the coil current effect, by reducing the linear coil-current dependence reported for the single air gap design by at least one order of magnitude. Both air gaps of the magnet are completely surrounded by high-permeability material, and hence the coils are shielded from outside magnetic fields and no magnetic field leaks outside of the magnet system. An example of the new magnet system is given and the analysis shows that the magnetic field in the air gap can be optimized to meet the requirement to be used in Kibble balances.
Influence of approximation range of the hologram transmission spectrum on the inverse problem solution

Transmission spectra of holographic sensors based on the Denisyuk holograms with silver nanograins embedded in the polymer matrix are investigated. It is necessary for the determination of the operation mode and of optical parameters of the sensors. The spectra have a narrow Bragg dip against a background decreasing with decreasing the wavelength. Three parameters of this dip determine the operating mode of the sensor. To calculate them, it is necessary to know 3 background parameters. All the parameters are calculated from fitting curves based on the formula proposed earlier which approximates the experimental spectrum quite well. It turns out that the spectral interval chosen for fitting is important and a solution exists not over any interval. When it exists, the parameters of the dip (the main goal of our work) are determined with a good accuracy. As for the optical parameters of the background, those associated with light scattering and with absorption seem to be strongly related. Changing the fitting interval leads to a correlated change of the values of parameters, sometimes considerably. Nevertheless, the fitting function approximates the experimental spectrum quite well and the accuracy of determining the Bragg dip is high.
Extensions of pseudo-Perron-Frobenius splitting related to generalized inverse AT,S(2)

Abstract We in this paper define the outer-Perron-Frobenius splitting, which is an extension of the pseudo- Perron-Frobenius splitting defined in [A.N. Sushama, K. Premakumari, K.C. Sivakumar, Extensions of Perron-Frobenius splittings and relationships with nonnegative Moore-Penrose inverse, Linear and Multilinear Algebra 63 (2015) 1-11]. We present some criteria for the convergence of the outer-Perron-Frobenius splitting. The findings of this paper generalize some known results in the literatures.
Improving Knowledge Distillation with Supporting Adversarial Samples

Many recent works on knowledge distillation have provided ways to transfer the knowledge of a trained network for improving the learning process of a new one, but finding a good technique for knowledge distillation is still an open problem. In this paper, we provide a new perspective based on a decision boundary, which is one of the most important component of a classifier. The generalization performance of a classifier is closely related to the adequacy of its decision boundary, so a good classifier bears a good decision boundary. Therefore, transferring information closely related to the decision boundary can be a good attempt for knowledge distillation. To realize this goal, we utilize an adversarial attack to discover samples supporting a decision boundary. Based on this idea, to transfer more accurate information about the decision boundary, the proposed algorithm trains a student classifier based on the adversarial samples supporting the decision boundary. Experiments show that the proposed method indeed improves knowledge distillation and achieves the state-of-the-arts performance.
PREDICTING ENTREPRENEURIAL INTENTIONS THROUGH AUTONOMY, RELATEDNESS, AND COMPETENCY: A STUDY AMONG STATE UNDERGRADUATE STUDENTS IN SRI LANKA

The purpose of this study is to assess the impact of autonomy, relatedness, ands competency on social entrepreneurial intention among state undergraduate students in Sri Lanka. The Self-determination Theory was tested in the context of state undergraduate students in Sri Lanka. Exogenous variables studied included Autonomy, Relatedness, and competency. The instrument used in the research was developed using validated items from past literature. Data for this quantitative study were collected from undergraduate students from nine state universities in Sri Lanka. Structural equation modeling was used to see the insights from the valid data using IBM’s SPSS 25 and AMOS 22. Results of the confirmatory factor analysis and subsequent evaluation of the structural model revealed a positive relationship between Social Entrepreneurial Intention and Relatedness and, social entrepreneurial Intention and Autonomy. However, the results did not support the relationships between social entrepreneurial intention and competency and the moderating effect of gender on competency and Social Entrepreneurial Intention.limited research has been carried out relating to Social Entrepreneurial Intention in the Sri Lankan context. The lack of research has not assisted in addressing the state university graduate unemployment which been a major socio-politico-economic problem in Sri La. Social entrepreneurship can be proposed as a viable career option. This research will shed light on the antecedent factors that affect social entrepreneurial intention and assist policymakers in developing appropriate strategies for promoting Social entrepreneurship among undergraduates.
Monotonicity and sharp inequalities related to gamma function

In this paper, we investigate the monotonicity pattern of the function x → lnΓ(x+1) ln (x2 +a)− ln (x+a) on (0,1) for a 1 and resolve an open problem. From which we prove that the double inequality ( x2 +a x+a )(1−γ)(a+1) < Γ(x+1) < ( x2 +b x+b )(1−γ)(b+1) holds for x∈ (0,1) if and only if 0 < a (1− γ)/(2γ −1) and b (π2 −6γ) / (18−12γ −π2) , while the double inequality ( x2 +a x+a )γa < Γ(x+1) < ( x2 +b x+b )γb holds for x ∈ (0,1) if and only if a (1− γ)/(2γ −1) and 0 < b 6γ/(π2 − 12γ) , where γ = 0.577 . denotes Euler-Mascheroni’s constant. These greatly improve some existing results.
Investigation of DC and RF characteristics of spacer layer thickness engineered recessed gate and field‐plated III‐nitride nano‐HEMT on β‐Ga2O3 substrate

In this work, a field plated recessed gate III‐nitride HEMT on β‐Ga2O3 substrate is proposed using AlN spacer between AlGaN and GaN layers. The two‐dimensional electron gas (2DEG) transport characteristics, input/output, and RF characteristics of the proposed HEMT with AlN spacer layer of different thickness (1, 2, 3, 4, and 5 nm) are numerically simulated and compared with HEMT without spacer layer. The 2DEG, which is created at the junction of AlGaN/GaN, plays a crucial role in the operation of GaN HEMTs. With the help of AlN as spacer layer between AlGaN and GaN, an augmented 2DEG concentration is accomplished owing to its large conduction band offset, high polarization effect, and higher barrier. Additionally, the inclusion of AlN spacer layer shifts the 2DEG density away from interface, resulting minimized interface scattering which results into greater mobility. The HEMT exhibited a mobility of 1261 cm2/Vs, threshold voltage of −0.45 V, drain current of 1.12 A/mm, breakdown voltage of 149 V, and excellent RF characteristics, that is, cut‐off frequency (maximum oscillation frequency) of 384 GHz (546 GHz) using 2‐nm AlN spacer layer. The proposed III‐nitride HEMT on β‐Ga2O3 substrate with 2‐nm AlN spacer can be used for RF/microwave and high‐power nanoelectronics applications.
Monte Carlo and DFT calculations on the corrosion inhibition efficiency of some benzimide molecules

Calculations using density functional theory (DFT) and Monte Carlo methods were performed on 2-methylbenzimidazole, 2-mercaptobenzimidazole, 2-aminobenzimidazole, benzotriazole, and benzimidazole to determine their corrosion inhibition efficiency. The molecular structure was optimized geometrically using DFT calculations at the B3LYP/6– 311 G++(d,p) and b2plypd3/aug-cc-pvdz basis set level in protonated and non-protonated species in gas and water. In this study, HOMO, LUMO, bandgap, ionization energy, electronegativity, hardness, softness, electrophilicity and nucleophilicity, electron transfer, back donation energy and condensed Fukui indices are used to assess a molecule's local reactivity. Theoretical investigations can precisely establish the geometrical dimensions of a molecule and correctly explain the quantum properties of inhibitors. The mechanism of interaction between inhibitors and metal surfaces in a specified molecule is studied using molecular dynamics. The benzimidazole functional groups absorbed energy linearly on metal surfaces, with quantum characteristics determined using density functional theory and an ab initio technique. Importantly, the findings of this conceptual model are consistent with the corrosion inhibition efficiency of earlier experimental investigations.
Refining the Klobuchar Ionospheric Model with Spherical Cap Harmonic Model for GNSS Positioning

Ionospheric delay is one of the major error sources in GNSS (Global Navigation Satellite System) positioning. For single frequency system, it is very important to effectively correct the ionospheric delay and so-called Klobuchar’s ionospheric model has been widely used due to its well known properties such as computational simplicity. The Klobuchar model is one of the global ionospheric models, and it can correct about 50% RMS ionospheric errors[1]. On the other hand, there are some models that can achieve better accuracy than the Klobuchar model, the SCHA (Spherical Cap Harmonics Analysis) model is one of such models. By the SCHA model, it has been reported that the ionospheric delays can be well modeled in the regional area such as the sky over Japan[2]. However, comparing with the Klobuchar model, the SCHA model needs more number of parameters and computational burden. Therefore, in this paper, a method to generate the parameters of the Klobuchar model from the SCHA model is proposed. By this method, the regional ionospheric model that is not only simple and easy operational like the Klobuchar model but also regionally accurate like the SCHA model is obtained.
Persistent and Recurrent Primary Hyperparathyroidism: Intraoperative Supplemental Methods, Basic Principles of Surgery, and Other Treatment Options

Reoperative parathyroid surgery is challenging even for experienced surgeons. Cure rates are lower than primary surgery. Good anatomical and embryological knowledge is important. Preoperatively, a comprehensive surgical strategy should be planned. Pre-operative imaging modalities should be used extensively to find the overlooked gland to have a possibility to perform focused parathyroid surgery to avoid possible complications. One of the important developments is the new ancillary methods to find overlooked parathyroid glands. Orthotopic and possible ectopic locations should be known well by the surgeon to increase the surgical success rate. Reoperative parathyroid surgery needs a distinctive approach compared to primary parathyroid surgery. Basic principles include the selection of the incision and route for entering the thyroid region, use of ancillary methods, and intraoperative nerve monitoring and also require a meticulous dissection. Obtaining a surgical cure is difficult and high surgical caution is needed. Post-operative complication rates are higher compared to primary parathyroid surgery. Other treatment methods and medical treatment options may be evaluated in a patient who cannot undergo surgery.
Adoptation of Extended Metaheuristics Considering Risk-Allocated Portfolio Optimization

- In recent times, the soft computing criterion is competent for tackling practical ambiguities involving numerous techniques, specifically neural networks, approaches to fuzzy logic, and evolutionary computational techniques. Various soft computational-based metaheuristics for minimization of risk governing portfolio optimization by using Particle Swarm Optimization, Differential Evolution and Genetic Algorithm approach focusing on optimization of CVaR (Conditional Value at Risk) measures within various market situations established on diverse objectives and constraints have been discussed within this article. The territory of portfolio optimization is meant for the selection of the range of diversified assets present in a portfolio, thus constructing a portfolio which can be best by considering some stated principles. In the modern era, multiobjective optimization procedures have proven important within the area of business intelligence, measuring the market risk–return paradigm. VaR (Value at Risk), being a prevailing technique in ascertaining downside risk within a portfolio, has been elucidated as pth percentage of returns on a specified portfolio to plan any horizon. Another vigorous technique remains the Conditional Value at Risk to determine the labeled risk entity in a portfolio within unstable market circumstances. The suggested techniques have also proved beneficial in the selection of various financial instruments in comparison to their VaR counterparts. The obtained results depict a promising outlet for determining excellent portfolio return s.
Implementation of a PSO Based Improved Localization Algorithm for Wireless Sensor Networks

ABSTRACT Wireless sensor networks (WSNs) are broadly employed in lots of applications. WSN is comprised of spatially dispersed sovereign devices enabled with sensors to examine some physical phenomenon. The node localization, which is to be responsive of nodes’ location in the system, is a crucial component of numerous WSN functions and applications. Various localization algorithms have been proposed to precisely locate nodes in WSNs. The localization algorithms are normally categorized into range-based and range-free schemes based on range measurements. The range-based methods use exact computation measure (distance or time) among nodes in the network. So range-based methods need some additional hardware for such computation, thus expensive to be used in practice. Because of hardware constraints of sensor network devices, range-free methods are considered cost efficient alternatives. Though, these methods normally contain higher localization error in comparison with range-based methods. DV-Hop is an usual range-free method that use hop-based evaluation. In this article, we have modified DV-Hop method and applied a meta-heuristic (PSO) technique to overcome the positioning error. The algorithm has been implemented in MATLAB R2015a for the validation of results. The performance of implemented algorithm has been analyzed in terms of localization error, error variance, accuracy, and coverage. The results of modified algorithm confirm that our algorithm decreases the localization error and improved the localization accuracy as compared to DV-Hop and improved DV-Hop (IDV-Hop) algorithms.