Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhancement of Thermal Efficiency in Gas-Fired Heaters Through a Novel Double-Walled Chimney Design: Experimental and CFD Analysis

: In the Middle East, gas-fired heaters are conventionally favored due to their reliability, cost-effectiveness, and minimal environmental impact. However, the challenges associated with traditional designs, such as low thermal efficiency, high fuel consumption, emissions of environmental pollutants, indoor gas leakage, moisture absorption, uneven heat distribution, and non-compliance with design standards, necessitate innovative solutions. A novel gas-fired heater design is thus presented in this investigation, incorporating a double-walled chimney equipped with an intermediate ejector, blades, and a mesh plate. These components were integrated to enhance the overall performance by optimizing airflow dynamics, thereby improving efficiency and ensuring uniform flame formation. An experimental heater model was constructed, and a series of controlled experiments, along with Computational fluid dynamics (CFD) modeling, were performed. The thermal efficiency was found to improve by an average of 10% compared to conventional models, elevating the efficiency from 75% to 85%. This increase was attributed to the preheating of the inlet air in the double chimney, proper air distribution within the combustion chamber through mesh plate application, and the reduction of excess air volume by controlling the air inlet. Enhanced safety was also observed in the proposed design, with no exchange of air with the room, thereby alleviating concerns related to indoor gas leakage and moisture absorption. A minor trade-off was noted with a 3 ppm increase in nitrogen oxides ( NO x ) emissions, an effect of reduced excess airflow to the combustion chamber; however, this was deemed acceptable in light of the substantial efficiency increase. Furthermore, the decreased natural gas consumption rendered the model economically attractive. Overall, the proposed gas-fired heater design offers significant potential for improving residential heating systems, addressing environmental issues, and maximizing energy savings, and is aligned with the global pursuit of energy-efficient and sustainable solutions.
Charge transport mechanism of high-resistive state in RRAM based on SiOx

Nonstoichiometric silicon oxide SiOx is a promising material for developing a new generation of high-speed, reliable flash memory based on the resistive effect. It is necessary to understand the electron transport mechanism of the high-resistive state in SiOx to develop a resistive memory element. At present, it is generally accepted that the charge transport of the high-resistive state in the Resistive Random Access Memory (RRAM) is described by the Frenkel effect. In our work, the charge transport of the high-resistive state in RRAM based on SiOx is analyzed with two contact-limited and five volume-limited charge transport models. It is established that the Schottky effect model, thermally assisted tunneling, the Frenkel model of Coulomb trap ionization, the Makram-Ebeid and Lannoo model of multiphonon isolated trap ionization, and the Nasyrov-Gritsenko model of phonon-assisted tunneling between traps, quantitatively, do not describe the charge transport of the high-resistive state in the RRAM based on SiOx. The Shklovskii-Efros percolation model gives a consistent explanation for the charge transport of the high-resistive state in the RRAM based on SiOx at temperatures above room temperature.Nonstoichiometric silicon oxide SiOx is a promising material for developing a new generation of high-speed, reliable flash memory based on the resistive effect. It is necessary to understand the electron transport mechanism of the high-resistive state in SiOx to develop a resistive memory element. At present, it is generally accepted that the charge transport of the high-resistive state in the Resistive Random Access Memory (RRAM) is described by the Frenkel effect. In our work, the charge transport of the high-resistive state in RRAM based on SiOx is analyzed with two contact-limited and five volume-limited charge transport models. It is established that the Schottky effect model, thermally assisted tunneling, the Frenkel model of Coulomb trap ionization, the Makram-Ebeid and Lannoo model of multiphonon isolated trap ionization, and the Nasyrov-Gritsenko model of phonon-assisted tunneling between traps, quantitatively, do not describe the charge transport of the high-resistive state in the RRAM based on .
Strategies for Obtaining Survey Responses from Extension Clients: Exploring the Role of E-Mail Requests

Extension professionals want to use the Web for conducting surveys, but studies show using the Web alone introduces significant bias. The study reported here compared strategies for obtaining responses that might minimize cost and bias. E-mail and postal invitations to the Web-hosted survey version were compared to the postal mail-only standard. The response rate was highest when using an e-mailed invitation, followed by the traditional mail-only mode and the postal invitation/Web-hosted mode. It appears the best strategy for minimizing the cost of collecting data and maximizing representativeness is to use e-mail invitations when available and postal mail for those without e-mail.
Correctness of belief propagation in Gaussian graphical models of arbitrary topology

Graphical models, such as Bayesian networks and Markov random elds represent statistical dependencies of variables by a graph. Local \belief propagation" rules of the sort proposed by Pearl [20] are guaranteed to converge to the correct posterior probabilities in singly connected graphs. Recently good performance has been obtained by using these same rules on graphs with loops, a method known as \loopy belief propagation". Perhaps the most dramatic instance is the near Shannon-limit performance of \Turbo codes", whose decoding algorithm is equivalent to loopy propagation. Except for the case of graphs with a single loop, there has been little theoretical understanding of loopy propagation. Here we analyze belief propagation in networks with arbitrary topologies when the nodes in the graph describe jointly Gaussian random variables. We give an analytical formula relating the true posterior probabilities with those calculated using loopy propagation. We give su cient conditions for convergence and show that when belief propagation converges it gives the correct posterior means for all graph topologies, not just networks with a single loop. The related \max-product" algorithm nds the maximumposterior probability estimate for singly connected networks. We show that, even for non-Gaussian probability distributions, the xed points of the max-product algorithm in loopy networks are at least local maxima of the posterior probability. These results motivate using the powerful belief propagation algorithm in a broader class of networks, and help clarify the empirical performance results. Sumbitted to Neural Computation. Preliminary version appeared in Proc. NIPS 99
Gene expression Causality and pathway search in microarray time series experiment

Motivation: Interaction among time series can be explored in many ways. All the approach has the usual problem of low power and high dimensional model. Here we attempted to build a causality network among a set of time series. The causality has been established by Granger causality, and then constructing the pathway has been implemented by finding the Minimal Spanning Tree within each connected component of the inferred network. False discovery rate measurement has been used to identify the most significant causalities. Results: Simulation shows good convergence and accuracy of the algorithm. Robustness of the procedure has been demonstrated by applying the algorithm in a non-stationary time series setup. Application of the algorithm in a real dataset identified many causa-lities, with some overlap with previously known ones. Assembled network of the genes reveals features of the network that are common wisdom about naturally occurring networks.
Restoring savannas and tropical herbaceous ecosystems

When people think of savannas, they think of the vast African landscapes where elephants, wildebeest, giraffes or lions used to roam. With the seasons, the vegetation tall grasses more or less scattered with trees and shrubs changes from green to yellow. These herbaceous ecosystems cover about 20% of the earth's surface and are present throughout the world's tropical belt, in Africa of course, but also in America and Asia. Recurrent fires or herbivores, themselves controlled by predators, keep these environments open by limiting the presence of trees and shrubs. Due to the complexity of savanna vegetation dynamics, the impacts of climate change and land use on savannas are highly uncertain. In addition, savannas are already largely threatened by human activities: conversion of land for agriculture, urbanization, etc. They are also threatened by the massive planting of trees, often implemented within the framework of carbon compensation. The natural resilience of these ecosystems to human-induced degradation is low and restoration actions are often necessary, but remain an ongoing challenge.
Young People’S Attitudes Toward Mobile Phones in the Republic Of Macedonia

Abstract This study explores the mobile phones’ attitudes and usage habits of young people in the Republic of Macedonia. The data from the survey were subjected to exploratory factor analysis, cluster analysis and ANOV A. The factor analysis identified five different factors interpreted as: fashion/status, dependency, added value, safety/security and negatives. Cluster analysis produced two segments: involved mobile phones users and indifferent mobile phone users. The ANOVA test revealed differences in the mobile phone attitudes regarding years of mobile phone use, number of calls per day and the average duration of a call. The results provide useful implications for development of effective marketing strategies.
On Translations between ML Models for XAI Purposes

In this paper, the succinctness of various ML models is studied. To be more precise, the existence of polynomial-time and polynomial-space translations between representation languages for classifiers is investigated. The languages that are considered include decision trees, random forests, several types of boosted trees, binary neural networks, Boolean multilayer perceptrons, and various logical representations of binary classifiers. We provide a complete map indicating for every pair of languages C, C' whether or not a polynomial-time / polynomial-space translation exists from C to C'. We also explain how to take advantage of the resulting map for XAI purposes.
IguideME: Supporting Self-Regulated Learning and Academic Achievement with Personalized Peer-Comparison Feedback in Higher Education

Personalized feedback is important for the learning process, but it is time consuming and particularly problematic in large-scale courses. While automatic feedback may help for self-regulated learning, not all forms of feedback are effective. Social comparison offers powerful feedback but is often loosely designed. We propose that intertwining meaningful feedback with well-designed peer comparison using a learning analytics dashboard provides a solution. Third-year bachelor students were randomly assigned to have access to the learning analytics dashboard IguideME (treatment, n=31) or no access (control, n=31). Dashboard users were asked to indicate their desired grade, which was used to construct peer-comparison groups. Personalized peer-comparison feedback was provided via the dashboard. The effects were studied using quantitative and qualitative data, including the Motivated Strategies for Learning Questionnaire (MSLQ) and the Achievement Goal Questionnaire (AGQ). Compared to the control group, the treatment group achieved higher scores for the MSLQ components “metacognitive self-regulation” and “peer learning,” and for the AGQ component “other-approach” (do better than others). The treatment group performed better on reading assignments and achieved higher grades for high-level Bloom exam questions. These data support the hypothesis that personalized peer-comparison feedback can be used to improve self-regulated learning and academic achievement.
The Relationship between Entrepreneurial Competencies, Competitive Intelligence, and Innovative Performance among SMEs from an Emerging Country

Competitive intelligence is vital to an organisation because it emphasises on understanding and measuring an organisation's competitive environment and the unstructured information that influence an organisation's strategic decision making. In fact, it also assists in creation of ideas and innovation. Yet, research on competitive intelligence practice among entrepreneurs is quite scanty. There is a need to investigate if entrepreneurial competencies and innovative performance is influenced by competitive intelligence. Thus, this study aims to analyse the relationship between entrepreneurial competencies, innovative performance and if competitive intelligence is the missing link among the entrepreneurs within the Malaysian SME context.
Plant Essential Oils as Biopesticides: Applications, Mechanisms, Innovations, and Constraints

The advent of the “Green Revolution” was a great success in significantly increasing crop productivity. However, it involved high ecological costs in terms of excessive use of synthetic agrochemicals, raising concerns about agricultural sustainability. Indiscriminate use of synthetic pesticides resulted in environmental degradation, the development of pest resistance, and possible dangers to a variety of nontarget species (including plants, animals, and humans). Thus, a sustainable approach necessitates the exploration of viable ecofriendly alternatives. Plant-based biopesticides are attracting considerable attention in this context due to their target specificity, ecofriendliness, biodegradability, and safety for humans and other life forms. Among all the relevant biopesticides, plant essential oils (PEOs) or their active components are being widely explored against weeds, pests, and microorganisms. This review aims to collate the information related to the expansion and advancement in research and technology on the applications of PEOs as biopesticides. An insight into the mechanism of action of PEO-based bioherbicides, bioinsecticides, and biofungicides is also provided. With the aid of bibliometric analysis, it was found that ~75% of the documents on PEOs having biopesticidal potential were published in the last five years, with an annual growth rate of 20.51% and a citation per document of 20.91. Research on the biopesticidal properties of PEOs is receiving adequate attention from European (Italy and Spain), Asian (China, India, Iran, and Saudi Arabia), and American (Argentina, Brazil, and the United States of America) nations. Despite the increasing biopesticidal applications of PEOs and their widespread acceptance by governments, they face many challenges due to their inherent nature (lipophilicity and high volatility), production costs, and manufacturing constraints. To overcome these limitations, the incorporation of emerging innovations like the nanoencapsulation of PEOs, bioinformatics, and RNA-Seq in biopesticide development has been proposed. With these novel technological interventions, PEO-based biopesticides have the potential to be used for sustainable pest management in the future.
A Digital Power Amplifier With Built-In AM–PM Compensation and a Single-Transformer Output Network

This article presents a digital power amplifier (DPA) with a built-in AM–PM compensation technique and a compact single-transformer footprint. The AM–PM distortion behavior of the current-mode/voltage-mode power amplifiers (PAs) is detailed and an AM–PM compensation technique for both modes is introduced. The proposed design utilizes one current-mode DPA as the main path PA and a class-G PA voltage-mode digital PA as the auxiliary path PA, combined through a single-transformer footprint. It provides enhanced linearity through built-in adaptive biasing and hybrid current-/voltage-mode Doherty-based power combining. As a proof of concept, a 1.2–2.4-GHz wideband DPA is implemented in the Globalfoundries 45-nm CMOS SOI process. The measurements show a 37.6% peak drain efficiency (DE) at 1.4 GHz, and 21.8-dBm saturated output power (Psat) and $1.2\times /1.4\times $ power back-off (PBO) efficiency enhancement, compared to the ideal class-B at 3 dB/6 dB PBO at 1.2 GHz. This proposed digital PA supports 20-MSym/s 64-QAM modulation at 14.8-dBm average output power and 22.8% average PA DE while maintaining error vector magnitude (EVM) lower than −23 dB without any phase predistortion. To the best of our knowledge, this is the first demonstration of hybrid current–voltage-mode Doherty power combining on a single-footprint transformer over a broad bandwidth (BW).
VOLMAP: a Large Scale Benchmark for Volume Mappings to Simple Base Domains

Correspondences between geometric domains (mappings) are ubiquitous in computer graphics and engineering, both for a variety of downstream applications and as core building blocks for higher level algorithms. In particular, mapping a shape to a convex or star‐shaped domain with simple geometry is a fundamental module in existing pipelines for mesh generation, solid texturing, generation of shape correspondences, advanced manufacturing etc. For the case of surfaces, computing such a mapping with guarantees of injectivity is a solved problem. Conversely, robust algorithms for the generation of injective volume mappings to simple polytopes are yet to be found, making this a fundamental open problem in volume mesh processing. VOLMAP is a large scale benchmark aimed to support ongoing research in volume mapping algorithms. The dataset contains 4.7K tetrahedral meshes, whose boundary vertices are mapped to a variety of simple domains, either convex or star‐shaped. This data constitutes the input for candidate algorithms, which are then required to position interior vertices in the domain to obtain a volume map. Overall, this yields more than 22K alternative test cases. VOLMAP also comprises tools to process this data, analyze the resulting maps, and extend the dataset with new meshes, boundary maps and base domains. This article provides a brief overview of the field, discussing its importance and the lack of effective techniques. We then introduce both the dataset and its major features. An example of comparative analysis between two existing methods is also present.
Prediction of irregular wave runup

Abstract : A technique for predicting the runup distribution of wind-generated waves is presented which extends the traditional method of runup prediction for regular waves (constant period and height) presented in the Shore Protection Manual (SPM) (U.S. Army, Corps of Engineers, Coastal Engineering Research Center, 1975). The basic assumption is that runup has a Rayleigh distribution of the type commonly associated with wave heights. This technique appears conservative but reasonable for predicting extreme values of runup for design purposes. A method of correcting runup for slope roughness and porosity, which is easier to apply than the method presented in SPM, is also presented. Example problems are given using these techniques for both plain and composite slopes. (Author)
Improved awareness of physical activities is associated with a gain of fitness and a stable body weight in breast cancer patients during the first year of antineoplastic therapy: the BEGYN-1 study

Background Breast cancer is the most frequent cancer in women. Reduced physical activity and overweight are associated with poor prognosis. Breast cancer patients have a high risk to gain weight, lose muscle mass and reduce physical activity during therapy. Concepts are urgently needed to motivate patients to engage in physical activity. Methods 110 non-metastatic breast cancer patients were included in the prospective observational BEGYN-1 study. Physiological parameters and body composition were measured before the start of therapy and then quarterly for one year. Patients used a fitness tracker and documented their physical activity in a diary throughout the study. Results Although the patients were not offered any guided exercise, and despite the restrictions during the COVID-19 pandemic, they increased their physical activity (metabolic equivalent of task (MET) -minutes): p<0.001), physical fitness (decreasing resting heart rate: p=0.001) and did not gain weight (median - 0.4kg) over the course of the study. Conclusion Improved awareness of physical activity is associated with an increase in physical activity, fitness, and a stable weight during the first year of therapy in breast cancer patients. Counselling at diagnosis should motivate patients to engage in physical activity, wear a fitness tracker and document activities.
Extracts from "clinical evidence": hip fracture.

Competing interests: WG is coordinating editor of the Cochrane Musculoskeletal Injuries Group and has participated in several of the cited systematic reviews. If you are interested in being a contributor or peer reviewer for Clinical Evidence please visit the Clinical Evidence website (www.clinicalevidence.org) Clinical Evidence is published by BMJ Publishing Group. The fourth issue is available now, and Clinical Evidence will be updated and expanded every six months. Individual subscription rate, issues 4 and 5 £75/$140; institutional rate £160/$245. For more information including how to subscribe, please visit the Clinical Evidence website at www.clinicalevidence. org