Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of Growth Performance, Meat Quality and Sensory Attributes of the Broiler Fed a Diet supplemented with Curry Leaves (Murraya koenigii)

An experiment was conducted to evaluate the growth performance and meat quality traits of broilers fed a diet supplemented with dry-ground curry leaves (Murraya koenigii). A total of 750 one-day-old broiler chicks (Cobbs 500) were arranged in the experiment with a completely randomized design and allotted to one of five treatments, with T1-Control and T2-T5 curry leaves powder levels (i.e., 0.3%, 0.6%, 0.9% and 1.2%, respectively). The initial body weights, final body weights and daily feed intake were measured over an experimental period of 32 days. At the conclusion of the experiment, the carcass weights and meat quality parameters were measured. The birds fed diets supplemented with curry leaves powder had a higher weight gain (P 0.05) in feed intake among the dietary treatments. Similarly, supplementation of curry leaves powder had no effect (P>0.05) on the proportions of the carcass, leg meat and drumstick. No differences were (P>0.05) observed in cooking loss or the pH of meat from broilers fed the curry leaves supplemented diet. However, curry leaf supplementation affected (P<0.05) the meat water holding capacity. A sensory evaluation showed higher levels of taste and tenderness in meat from broilers fed with curry leaves powder. In conclusion, our results suggested that curry leaves powder improved the growth performance of broilers, with a lower incidence of mortality and improvement of some meat qualities.
Arrhythmogenesis of Sports: Myth or Reality?

Regular exercise confers health benefits with cardiovascular mortality risk reduction through a variety of mechanisms. At a population level, evidence suggests that undertaking more exercise has greater benefits. In the modern era of sport, there has been an exponential rise in professional and amateur athletes participating in endurance events, with a progressively better understanding of the associated cardiac adaptations, collectively termed ‘athletes heart’. However, emerging data raise questions regarding the risk of potential harm from endurance exercise, with an increased risk of arrhythmia from adverse cardiac remodelling. Cross-sectional studies have demonstrated that athletes may exhibit a higher burden of AF, conduction tissue disease, ventricular arrhythmias, a cardiomyopathy-like phenotype and coronary artery disease. In an attempt to separate myth from reality, this review reports on the evidence supporting the notion of ‘too much exercise’, the purported mechanisms of exercise-induced cardiac arrhythmia and complex interplay with sporting discipline, demographics, genetics and acquired factors.
Revealing Influence of Meteorological Conditions on Air Quality Prediction Using Explainable Deep Learning

Meteorological conditions have a strong influence on air quality and can play an important role in air quality prediction. However, due to the “black-box” nature of deep learning, it is difficult to obtain trustworthy deep learning models when considering meteorological conditions in air quality prediction. To address the above problem, in this paper, we reveal the influence of meteorological conditions on air quality prediction by utilizing explainable deep learning. In this paper, (1) the source data from air pollutant datasets, including PM2.5, PM10, SO2 hourly concentration, and the meteorological condition datasets measuring the temperature, humidity, and atmospheric pressure are obtained; (2) the Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) models are established for air quality prediction in 4 conditions; (3) the SHapley Additive exPlanation (SHAP) method is employed to analyze the explainability of the air quality prediction models. We find that the prediction accuracy is not improved by considering only meteorological conditions. However, when combining meteorological conditions with other air pollutants, the prediction accuracy is higher than considering other air pollutants. In addition, the largest contribution to air quality prediction is atmospheric pressure, followed by humidity and temperature. The reason for the different accuracies of the prediction may because of the interaction between meteorological conditions and other air pollutants. The investigated results in this paper can help improve the prediction accuracy of air quality and achieve trusted air quality predictions.
Premature Deindustrialization Risk in Asian Latecomer Developing Economies

Abstract This study examines the risk of premature deindustrialization in latecomer developing countries in Asia, focusing on their manufacturing output ratio. Diverging from the literature that treats Asian economies as a group with comparative advantages in manufacturing, this empirical analysis adopts the latecomer index to demonstrate downward shifts in the latecomers’ manufacturing–income relationship, implying a premature deindustrialization risk. Furthermore, it shows that the risk is higher for manufacturing trade-deficit countries (compared with trade-surplus countries) and for South Asian countries (compared with Southeast Asian countries). Therefore, Asian economies should improve their logistics performance for greater global value chain participation to avoid premature deindustrialization.
Eco-Efficiency Assessment of Beijing-Tianjin-Hebei Urban Agglomeration Based on Emergy Analysis and Two-Layer System Dynamics

In the process of the economic development of the Beijing-Tianjin-Hebei urban agglomeration, ecological and environmental issues are still an important factor restricting high-quality development. The study of eco-efficiency is of great significance for coordinating the relationship between economy, resources and environment. This paper used a combinated method of two-layer system dynamics and emergy analysis to construct an emergy–system dynamics coupling model for eco-efficiency evaluation from the subsystems of resource flow, energy flow, currency flow and population flow of urban system, which is used to simulate and analyze the eco-efficiency of the Beijing-Tianjin-Hebei urban agglomeration. The results show that the overall eco-efficiency of the Beijing-Tianjin-Hebei urban agglomeration is not high, with an average value of 0.3786, and there is a trend of the value rising first and then falling from 2000 to 2035. The index values of emergy waste rate, contaminant emergy ratio, emergy output rate and environmental load rate after the decomposition of the eco-efficiency show that the high environmental pressure, the low re-use rate of pollutants and the low production efficiency of the system are important reasons for the low eco-efficiency in regional economic development. Finally, through scenario simulation, we propose that optimizing the economic structure, adjusting the population size and rationally arranging the fixed assets investment are conducive to improving the eco-efficiency of the Beijing-Tianjin-Hebei urban agglomeration.
The State of HSTS Deployment: A Survey and Common Pitfalls

HSTS (HTTP Strict Transport Security) has gained signicant browser and server adoption since reaching IETF proposed status. However, there are several important deployment challenges. A scan of top websites reveals that many HSTS sites have not properly congured the HSTS header, which still leaves them open to some attacks HSTS is meant to solve. We survey the current state of deployment and describe common mistakes and diculties with HSTS conguration. We conclude with approaches for properly deploying HSTS as eectively as possible.
An Accurate False Data Injection Attack (FDIA) Detection in Renewable-Rich Power Grids

An accurate state estimation (SE) considering increased uncertainty by the high penetration of renewable energy systems (RESs) is more and more important to enhance situational awareness, and the optimal and resilient operation of the renewable-rich power grids. However, it is anticipated that adversaries who plan to manipulate the target power grid will generate attacks that inject inaccurate data to the SE using the vulnerabilities of the devices and networks. Among potential attack types, false data injection attack (FDIA) is gaining popularity since this can bypass bad data detection (BDD) methods implemented in the SE systems. Although numerous FDIA detection methods have been recently proposed, the uncertainty of system configuration that arises by the continuously increasing penetration of RESs has been been given less consideration in the FDIA algorithms. To address this issue, this paper proposes a new FDIA detection scheme that is applicable to renewable energy-rich power grids. A deep learning framework is developed in particular by synergistically constructing a Bidirectional Long Short-Term Memory (Bi-LSTM) with modern smart grid characteristics. The developed framework is evaluated on the IEEE 14-bus system integrating several RESs by using several attack scenarios. A comparison of the numerical results shows that the proposed FDIA detection mechanism outperforms the existing deep learning-based approaches in a renewable energy-rich grid environment.
Electron Radiation Effects of Grain-Boundary Evolution on Polycrystalline Silicon in MEMS

A specimen observed with a transmission electron microscope (TEM) was processed by focused ion beam (FIB) from a surface-micromachined polycrystalline silicon MEMS structure. Electron irradiation and in situ observation were performed on a selected grain boundary in the specimen. The grain boundary was observed and located by using lattice-oriented selective TEM photography. An evolution progress of amorphization of small silicon grain within the grain boundary and recrystallization of amorphous silicon were observed. A silicon grain turned into several smaller bar grains within the grain boundary. The mechanism of grain-boundary evolution inducing a change of conductivity of polycrystalline silicon has been revealed. The conductivity of polycrystalline silicon influenced by electron irradiation could be attributed to the change of grain boundary.
Revisión transdiciplinaria en intervenciones para cuidadores informales de pacientes con trastorno neurocognitivo mayor

a phenomenon is starting to constitute a public health problem. In response to this, multiple intervention strategies have emerged, aimed at reducing the discom-fort that care represents, but these have been developed in an isolated and fragmented way by the disciplines involved in the well-being of this population group. This article aims to review the intervention programs for care givers of patients with Alzheimer’s produced in the areas of psychology, phonoaudiology and physiotherapy, projecting an analysis from a transdisciplinary perspective using documen tary research. Specialized databases were used: Psychology and Behavioral Sciences Collec -tion, Scopus, Pubmed, Publindex, Lilacs, SciELO, EBSCO, ENFISPO, PEDro, ASHA, using the search for keywords through the PICO strategy which allows the selection of the best scientific evidence of health programs, between the months of January to June 2017. The descriptors used in Spanish and English were “family caregivers”, “primary caregiver”, “pain”, “physical impact”, “low back pain”, “physiotherapy”. A total of 317 articles were obtained, in Spanish, English and French, of which 30 were selected after an in-depth review. Among them, psychopedagogical and psychotherapeutic intervention programs with different application models were found. It is concluded that, despite the methodological differences of the programs, there will always be a positive change in the experience of care; it is also suggested to design transdisciplinary proposals in response to the specific needs of the informal caregiver.
Advances in Research on Antiviral Activities of Sulfated Polysaccharides from Seaweeds

In recent years, various viral diseases have suddenly erupted, resulting in widespread infection and death. A variety of biological activities from marine natural products have gradually attracted the attention of people. Seaweeds have a wide range of sources, huge output, and high economic benefits. This is very promising in the pharmaceutical industry. In particular, sulfated polysaccharides derived from seaweeds, considered a potential source of bioactive compounds for drug development, have shown antiviral activity against a broad spectrum of viruses, mainly including common DNA viruses and RNA viruses. In addition, sulfated polysaccharides can also improve the body’s immunity. This review focuses on recent advances in antiviral research on the sulfated polysaccharides from seaweeds, including carrageenan, galactan, fucoidan, alginate, ulvan, p-KG03, naviculan, and calcium spirulan. We hope that this review will provide new ideas for the development of COVID-19 therapeutics and vaccines.
Comparison of Wideband Channel Sounding Techniques

This paper compares time-domain and frequency-domain wideband channel sound- ing techniques by using measurement results. These techniques are compared based on the re- ceived power, the multipath resolution, and the RMS delay spread. Similar conclusions can be drawn for both sounding techniques for the measurement environment. In general, both sounding techniques have their own advantages and constrains; the choice of sounding technique heavily depends on the experiment environment.
Can the Eight Hop Test Be Measured with Sensors? A Systematic Review

Rehabilitation aims to increase the independence and physical function after injury, surgery, or other trauma, so that patients can recover to their previous ability as much as possible. To be able to measure the degree of recovery and impact of the treatment, various functional performance tests are used. The Eight Hop Test is a hop exercise that is directly linked to the rehabilitation of people suffering from tendon and ligament injuries on the lower limb. This paper presents a systematic review on the use of sensors for measuring functional movements during the execution of the Eight Hop Test, focusing primarily on the use of sensors, related diseases, and different methods implemented. Firstly, an automated search was performed on the publication databases: PubMed, Springer, ACM, IEEE Xplore, MDPI, and Elsevier. Secondly, the publications related to the Eight-Hop Test and sensors were filtered according to several search criteria and 15 papers were finally selected to be analyzed in detail. Our analysis found that the Eight Hop Test measurements can be performed with motion, force, and imaging sensors.
Knowledge management toolkit enhancement for a professional services firm

Background: Professional services firms utilise knowledge management tools, for example, IBM and Oracle solutions and toolkits, in their day-to-day client-facing operations. The effectiveness of toolkits must be evaluated to establish their actual value.Objectives: This article evaluates the current toolkit used by the South African client-facing professionals of a global multinational corporation.Method: Pragmatism philosophy was used because of the various perspectives needed to interpret the data. Data were collected from 30 participants who adhered to sample eligibility criteria. An interview was used to collect data to help determine which tools worked well and what had to be improved on.Results: The most value-adding tool was the Experience Tool, whereas the Collaboration Tool ranked the least valuable. The Collaboration Tool showed the most potential to increase its value. The results gave a clear indication of areas of improvement that will enable a professional services firm to strategically position its knowledge management toolkit towards adding value for client engagements.Conclusion: The study contributes towards evaluating the knowledge management toolkit, analysing areas of improvement, and recommending components such as machine learning, online collaboration and other activities that would enhance the knowledge management toolkit.
Population, Productivity, and Sustainable Consumption

How does the sustainable level of consumption depend on productivity growth and the size and growth rate of the population? What is the effect of uncertainty over these growth rates? I address these questions using a model in which productivity and population growth are stochastic, and social welfare allows for human lives to have (positive or negative) intrinsic value. I show how the maximum sustainable consumption-wealth ratio depends on expected rates of productivity and population growth, the volatility of those growth rates, and the extent to which welfare depends directly on the size of the population. For plausible parameter values, the sustainable consumption-wealth ratio is well below the optimal ratio that maximizes welfare. This raises a question: Given its cost, should sustainability be a social objective? size. They show how these two types of the They ﬁnd that does and the ratio lies on
Establishment of a Cell Model for Dynamic Monitoring of Intracellular Calcium Concentration and High-Throughput Screening of P2Y2 Regulators

P2Y receptors are G-protein-coupled receptors (GPCRs) for extracellular nucleotides. The P2Y2 receptor subtype is expressed in a variety of cell types and plays an important role in physiological and pathophysiological processes such as inflammatory responses and neuropathic pain. Based on this, the P2Y2 has been identified as an important drug target. The specificity of current P2Y2 receptor modulators is relatively poor, and currently, specific and efficient P2Y2 receptor modulators and efficient screening strategies are lacking. In this study, a cell model based on calcium-activated chloride channels (CaCCs) was established that can detect changes in intracellular calcium concentrations and can be used to high-throughput screen for P2Y2 receptor-specific regulators. This screening strategy is suitable for screening of most G-protein-coupled receptor regulators that mediate increases in intracellular calcium signals. The cell model consists of three components that include the endogenously expressed P2Y2 receptor protein, the exogenously expressed calcium-activated chloride channel Anoctamin-1 (Ano1), and a yellow fluorescent protein mutant expressed within the cell that is highly sensitive to iodine ions. This model will allow for high-throughput screening of GPCR regulators that mediate increased intracellular calcium signaling using the calcium-activated transport of iodide ions by Ano1. We verified the ability of the model to detect intracellular calcium ion concentration using fluorescence quenching kinetic experiments by applying existing P2Y2 agonists and inhibitors to validate the screening function of the model, and we also evaluated the performance of the model in the context of high-throughput screening studies. The experimental results revealed that the model could sensitively detect intracellular calcium ion concentration changes and that the model was accurate in regard to detecting P2Y2 modulators. The resultant value of the Z-factor was 0.69, thus indicating that the model possesses good sensitivity and specificity.
Ammonium and Phosphate Recovery from Biogas Slurry: Multivariate Statistical Analysis Approach

Livestock biogas slurry is an effluent containing nutrients such as ammonium and phosphate that are released by the industries. Therefore, recovery and reuse of ammonium and phosphorus is highly necessary. In recent years, many studies have been devoted to the use of different multivariate statistical analyses to investigate the interrelationship of one factor to another factor. The overall objective of this research study was to understand the significance of phosphate and ammonium recovery from biogas slurry using the multivariate statistical approach. This study was conducted using a range of salts that are commonly found in biogas slurry (ZnCl2, FeCl3, FeCl2, CuCl2, Na2CO3, and NaHCO3). Experiments with a biogas digester and aqueous solution were conducted at pH 9, with integration with NH4+, Mg2+, and PO43− molar ratios of 1.0, 1.2, and 1.8, respectively. The removal efficiency of ammonium and phosphate increased from 15.0% to 71.0% and 18.0% to 99.0%, respectively, by increasing the dose of respective ions K+, Zn2+, Fe3+, Fe2+, Cu2+, and CO32−. The elements were increased from 58.0 to 71.0 for HCO3−, with the concentration increasing from 30 mg L−1 to 240 mg L−1. Principal component, regression, path analysis, and Pearson correlation analyses were used to investigate the relationships of phosphate and ammonium recovery under different biochar, pyrolysis temperature, element concentration and removal efficiencies. Multivariate statistical analysis was also used to comprehensively evaluate the biochar and struvite effects on recovery of ammonium and phosphate from biogas slurry. The results showed that combined study of multivariate statistics suggested that all the indicators positively or negatively affected each other. Pearson correlation was insignificant in many ionic concentrations, as all were more than the significant 0.05. The study concluded that temperature, biochar type, and varying levels of components, such as K+, Zn2+, Fe3+, Fe2+, Cu2+, CO32−, and HCO3−, all had a substantial impact on P and NH4+ recovery. Temperature and varying amounts of metal salts enhanced the efficacy of ammonium and phosphate recovery. This research elucidated the methods by which biochar effectively reuses nitrogen and phosphate from biogas slurry, presenting a long-term agricultural solution.
Oficina Música Visual gerativa

A computação expande as possibilidades na criação de obras artísticas de música visual, com a intencionalidade da associação algorítmica entre elementos do som e elementos gráficos para geração de visualizações. No entanto, há dificuldades interdisciplinares na exploração destes artefatos, pois as pessoas interessadas na temática nem sempre encontram direcionamentos para construí-las. Sendo assim, essa oficina surge pela necessidade de proporcionar a experimentação dessas potencialidades tecnológicas e tem por objetivo estabelecer um ambiente de criação colaborativa durante o SBCM 2021, propondo experimentação de códigos que integram o processamento de som e processamento e síntese de imagem. Utilizaremos um processo de Design colaborativo, considerando os participantes como protagonistas de seus experimentos pelo mapeamento de suas expectativas e interesses, auxiliados por tutorias e esperando obter como resultado esboços e contribuições experimentais de música visual gerativa.
An Attack on Facial Soft-Biometric Privacy Enhancement

In the recent past, different researchers have proposed privacy-enhancing face recognition systems designed to conceal soft-biometric attributes at feature level. These works have reported impressive results, but generally did not consider specific attacks in their analysis of privacy protection. We introduce an attack on said schemes based on two observations: (1) highly similar facial representations usually originate from face images with similar soft-biometric attributes; (2) to achieve high recognition accuracy, robustness against intra-class variations within facial representations has to be retained in their privacy-enhanced versions. The presented attack only requires the privacy-enhancing algorithm as a black-box and a relatively small database of face images with annotated soft-biometric attributes. Firstly, an intercepted privacy-enhanced face representation is compared against the attacker’s database. Subsequently, the unknown attribute is inferred from the attributes associated with the highest obtained similarity scores. In the experiments, the attack is applied against two state-of-the-art approaches. The attack is shown to circumvent the privacy enhancement to a considerable degree and is able to correctly classify gender with an accuracy of up to approximately 90%. Future works on privacy-enhancing face recognition are encouraged to include the proposed attack in evaluations on the privacy protection.