Miracle-dz/UniFAR-FTUs huggingface dataset:
Production of Gluten-Free Biscuits for Celiac Patients Using Yellow Corn Flour, Sweet Lupine and Sweet Potato Powders

Gluten-free corn biscuits were prepared from yellow corn flour and partially replaced by various levels (10, 20 and 30%) of sweet lupine and sweet potato powders. The proximate composition, minerals content, physical and sensory attributes of the prepared gluten-free biscuits was evaluated. The obtained data observed that, the water absorption and dough stability of yellow corn flour was gradually increased as the percentage of replacement with sweet lupine and sweet potato powders increased. On contrast, dough weakening was gradually decreased as the substitution level increased. Also, the blends of sweet potato and yellow corn flour had the most significant set-back values. On contrast, sweet lupine powder had the lower set-back values. The replacement of yellow corn flour with sweet lupine powder caused gradually increase in both of biscuits moisture, ash, protein, lipids, crude fibers and minerals levels as the level of replacement increased. Meanwhile, total carbohydrates content was gradually decreased as the level of replacement increased. Gradual increase in both of biscuits weight and spread ratio and gradual decrease in biscuits specific volume were observed by raising the proportion of replacement with sweet lupine and sweet potato powders in compare to control sample. Sensory results showed the levels of substitution with 20% sweet lupine and 10% sweet potato powders were the most preferable. Due to the lack of gluten, these studied biscuits can be suitable for celiac disease patients.
A Domain Generalization Network Exploiting Causal Representations and Non-Causal Representations for Three-Phase Converter Fault Diagnosis

Deep learning (DL) methods have attracted increasing attention and have shown competitive performance in power converter fault diagnosis. However, models trained by existing fault data cannot function well for converter systems with unknown parameters in unknown environments. In addition, obtaining the target data distribution in advance limits the application of transfer learning (TL) methods based on domain adaptation (DA) in real-time fault diagnosis. To address this challenge, this article proposes a domain generalization network exploiting causal representations and non-causal representations (DGNECN) for power converter fault diagnosis under unknown working conditions. First, structural causal models (SCMs) are introduced in converter fault diagnosis, and invariant causal representations with fault information are extracted by the causal factorization module based on a causal matching strategy. Subsequently, the domain-specific non-causal representations are captured by the domain classifier. Finally, the two representations are further purified by disentanglement within a unified framework while optimizing non-causal representations through meta-learning to achieve stable generalization to unknown working conditions. Extensive comparison and ablation experiments confirm the effectiveness and superiority of DGNECN in the domain generalization (DG) setting. DGNECN achieved an average accuracy of 97.38% even in unknown noise and frequency.
Antibacterial Properties of Manuka Honey and the Role of Methylglyoxal

The unique ecosystems of New Zealand have produced a diverse range of honey over the years, with Manuka honey being one of the most renowned. Produced by Western honeybees extracting nectar from Manuka flowers, this monofloral honey has become known for its distinct antibacterial and anti-inflammatory properties. Whilst antibacterial activity in other honey tend to stem from factors such as hydrogen peroxide content, high viscosity, osmotic effect, and acidic pH, the antibacterial activity of Manuka honey is mainly attributed to methylglyoxal (MGO), a dicarbonyl compound which is found in high concentrations in Manuka honey. This review paper will focus on the antibacterial properties of Manuka honey and the role that MGO plays. Understanding the specific chemical mechanisms that of attack on different strains of bacteria by Manuka honey and the role of MGO is crucial to potentially understanding how new drugs or medicines can combat antibacterial resistance to antibiotics.
Overview of Advanced Land Observing Satellite-2 (ALOS-2)

Advanced Land Observing Satellite-2 (ALOS-2) is a Japanese earth observation satellite operated over two years after the launch on May 24, 2014. The mission objective of ALOS-2 are disaster monitoring, environmental monitoring, land monitoring, and technology development. To achieve these missions, ALOS-2 carries the Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2) that has many improved performances compared to previous L-band SAR satellite in Japan. This paper introduces the ALOS-2 missions, specifications of the satellite and PALSAR-2, current operation status such as data acuisition and emergency observation, and examples of PALSAR-2 applications.
Allergy-associated biomarkers in early life identified by Omics techniques

The prevalence and severity of allergic diseases have increased over the last 30 years. Understanding the mechanisms responsible for these diseases is a major challenge in current allergology, as it is crucial for the transition towards precision medicine, which encompasses predictive, preventive, and personalized strategies. The urge to identify predictive biomarkers of allergy at early stages of life is crucial, especially in the context of major allergic diseases such as food allergy and atopic dermatitis. Identifying these biomarkers could enhance our understanding of the immature immune responses, improve allergy handling at early ages and pave the way for preventive and therapeutic approaches. This minireview aims to explore the relevance of three biomarker categories (proteome, microbiome, and metabolome) in early life. First, levels of some proteins emerge as potential indicators of mucosal health and metabolic status in certain allergic diseases. Second, bacterial taxonomy provides insight into the composition of the microbiota through high-throughput sequencing methods. Finally, metabolites, representing the end products of bacterial and host metabolic activity, serve as early indicators of changes in microbiota and host metabolism. This information could help to develop an extensive identification of biomarkers in AD and FA and their potential in translational personalized medicine in early life.
Impact of Organizational Culture and Values on Employee Engagement and Performance in Brazil

Purpose: The aim of the study was to investigate impact of organizational culture and values on employee engagement and performance in Brazil. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: In Brazil, aligning organizational culture with employee values boosts engagement and performance. Collaborative and inclusive cultures are highly valued, as are well-being and development opportunities. Cultural sensitivity and trust-building are vital in the diverse Brazilian workforce. Overall, aligning culture with values enhances engagement and performance in Brazil. Unique Contribution to Theory, Practice and Policy: Social exchange theory, expectancy theory & organizational support theory may be used to anchor future studies on impact of organizational culture and values on employee engagement and performance in Brazil. Implement leadership development programs that emphasize the role of leaders in shaping and modeling the desired organizational culture and values. Develop regulatory guidelines that encourage organizations to integrate corporate social responsibility (CSR) into their values and culture.
Occurrence, dietary exposure and risk assessment to aflatoxins in red pepper flakes from Southeast of Türkiye

Aflatoxins contamination of foods is a global issue that severely threatens human health. This study aimed to measure total aflatoxin (AF) (aflatoxin B1 (AFB1), aflatoxin B2 (AFB2), aflatoxin G1 (AFG1), and aflatoxin G2 (AFG2)) levels in red pepper flakes samples and to evaluate the potential dietary exposure and cancer risk to aflatoxin in the southeast of Türkiye. A total of 90 red pepper flake samples were collected from local markets Gaziantep, Şanlıurfa, and Hatay provinces, Türkiye. Total AF in red pepper flakes was determined by high-performance liquid chromatography with a fluorescence detector (HPLC-FLD). Then, the margin of exposure (MOE) and cancer risk were calculated. AFB1 and total AF were detected in red pepper flake samples at 98.89% and 100%, respectively. The number of red pepper flake samples exceeded the legislation limits for AFB1 was four, and there was only one sample for total AF. It was determined that AFB1 exposure could pose a risk to public health for Turkish adults (MOE < 10,000). Although AF exposure seems to be higher due to the high consumption of red pepper flakes in some regions of Türkiye, the risk of exposure and cancer may decrease because of complying with the recommendations of the dietary guidelines. The findings provide new insights into exposure to total AF by consuming red pepper flakes.
The Malaria Burden: A South African Perspective

Malaria is a deadly disease caused by protozoan pathogens of the Plasmodium parasite. Transmission to humans occurs through the bite of an infected female Anopheles mosquito. According to the World Health Organization (WHO), an estimated 247 million cases of malaria were recorded worldwide in 2021, with approximately 619 000 malaria deaths. The initial signs of malaria can be mild and challenging to diagnose due to the signs and symptoms being similar to those of other illnesses. The malaria burden remains largely concentrated in the WHO sub-Saharan African region and has been recognised as a significant contributor to morbidity and mortality. This review aims to contribute to the existing knowledge on malaria in South Africa, a region within sub-Saharan Africa, focusing on the epidemiology and life cycle of the malaria parasite as well as diagnostic approaches for detecting malaria. In addition, nonpharmacological and pharmacological interventions for treating and preventing malaria infections will also be discussed herein. While there has been a significant reduction in the global burden of this disease, malaria remains a public health issue in South Africa. As such, the implementation of effective preventative measures and strategies, early diagnosis, and appropriate treatment regimens are crucial to reducing the malaria burden in South Africa.
Green technology vs environmental sustainability in india– an overview

Various technologies are being invented and used by Human Civilization which supports day to day activities. The adoption of technology is limited and has adverse effects on environment and human civilization. Therefore, scope exists for application of new technologies which are more eco and environmental friendly for supporting day to day activities of the present lifestyle. However, new technologies are more efficient and environment friendly due to increased awareness and recent development in research areas of energy management. These technologies are characterized as green or clean technology. Green technologies involve: energy efficiency, recycling, safety and health concerns, renewable resources, and many more. With the increased efforts in the direction of globalization across the globe also increased the level of competition among various companies in various domains of work and in between governments for the sake of development. The fact that the globalization has taken the world to new heights of development and it has also increased the pace of development in many developing countries especially, India and China. For the sake of globalization and development we are continuously exploiting our mother nature, the environment. People concerned with environment and ecology suggests that if this rate of exploitation continues then the day is not so far when earth and its environment will be not suitable for sustainable life. That’s where the term green technology comes into lime light which uses technology in such a way that in one end development which is a result of globalization continues and on the other end the level of negative environmental impact is reduced to its minimum level. This paper will critically review literature on current environmental sustainability practices and the role of green technologies in sustainable development. This paper also reviews various green technologies from view point of adaptability and implementation issues for modern living towards sustainable environment.
Giant Tophaceous Gout: The Importance of Therapeutic Compliance

Gout is a metabolic disease resulting from the deposition of monosodium urate crystals in joints, tissues, and organs. Nowadays, the treatment of hyperuricemia is easily accessible and widespread and mainly consists of xanthine oxidase inhibitors and uricosurics. In refractory and advanced cases of gout, amputation surgery may be required. The authors present the case of an 85-year-old man who is non-compliant with hypouricemic medication, has exuberant gout, and has refused amputation surgery several times. The patient went to the emergency department with a triad of acute kidney injuries, acute gout, and poorly controlled pain. Cases of tophaceus gout such as the one presented are very rare nowadays.
Diving Deep With BotLab-DS1: A Novel Ground Truth-Empowered Botnet Dataset

Cyberspace faces unparalleled threats due to the rapid rise in botnet attacks and their profound repercussions. Utilizing AI-assisted systems emerges as a potent solution for detecting and neutralizing such attacks. Existing research on botnet attack detection revolves around dataset creation, amplifying the detection methods’ efficacy and precision via sophisticated machine learning models, and a behaviour-centric analysis. A discerning review of current datasets reveals their limitations: the obsolescence of some datasets, their limited relevance to certain attack types, and an imperative lack of ground truth. Addressing these gaps, we introduce a ground truth, the BotLab-DS1 dataset, featuring 5,279 real-world active botnet samples spanning 12 botnet families and 3,000 benign instances. This paper’s core is threefold; initially, we delineate a thorough review of existing datasets and their inherent shortcomings. Subsequently, we unfold a holistic data creation strategy and leverage advanced feature engineering methods on static, behavioural, and network-centric attributes. Finally, the research involves training diverse machine learning algorithms using the BotLab-DS1 dataset for enhanced botnet detection. Our empirical findings underline that BotLab-DS1, when paired with the random forest algorithm, attains 98.6% accuracy and 99.0% precision. In contrast, gradient boosting trails closely, registering 96.34% accuracy and 96.0% precision. We believe our study will pioneer new pathways for dataset formulation and algorithmic scrutiny, enriching the research landscape and backing the global initiative to thwart botnet incursions effectively.
The Effect of Arctic Sea Ice Loss on the Hadley Circulation

One of the most robust responses of the climate system to future greenhouse gas emissions is the melting of Arctic sea ice. It is thus essential to elucidate its impacts on other components of the climate system. Here we focus on the response of the annual mean Hadley cell (HC) to Arctic sea ice loss using a hierarchy of model configurations: atmosphere only, atmosphere coupled to a slab ocean, and atmosphere coupled to a full‐physics ocean. In response to Arctic sea ice loss, as projected by the end of the 21st century, the HC shows negligible changes in the absence of ocean‐atmosphere coupling. In contrast, by warming the Northern Hemisphere thermodynamic coupling weakens the HC and expands it northward. However, dynamic coupling acts to cool the Northern Hemisphere which cancels most of this weakening and narrows the HC, thus opposing its projected expansion in response to increasing greenhouse gases.
Optimizing multi-objective task scheduling in fog computing with GA-PSO algorithm for big data application

As the volume and velocity of Big Data continue to grow, traditional cloud computing approaches struggle to meet the demands of real-time processing and low latency. Fog computing, with its distributed network of edge devices, emerges as a compelling solution. However, efficient task scheduling in fog computing remains a challenge due to its inherently multi-objective nature, balancing factors like execution time, response time, and resource utilization. This paper proposes a hybrid Genetic Algorithm (GA)-Particle Swarm Optimization (PSO) algorithm to optimize multi-objective task scheduling in fog computing environments. The hybrid approach combines the strengths of GA and PSO, achieving effective exploration and exploitation of the search space, leading to improved performance compared to traditional single-algorithm approaches. The proposed hybrid algorithm results improved the execution time by 85.68% when compared with GA algorithm, by 84% when compared with Hybrid PWOA and by 51.03% when compared with PSO algorithm as well as it improved the response time by 67.28% when compared with GA algorithm, by 54.24% when compared with Hybrid PWOA and by 75.40% when compared with PSO algorithm as well as it improved the completion time by 68.69% when compared with GA algorithm, by 98.91% when compared with Hybrid PWOA and by 75.90% when compared with PSO algorithm when various tasks inputs are given. The proposed hybrid algorithm results also improved the execution time by 84.87% when compared with GA algorithm, by 88.64% when compared with Hybrid PWOA and by 85.07% when compared with PSO algorithm it improved the response time by 65.92% when compared with GA algorithm, by 80.51% when compared with Hybrid PWOA and by 85.26% when compared with PSO algorithm as well as it improved the completion time by 67.60% when compared with GA algorithm, by 81.34% when compared with Hybrid PWOA and by 85.23% when compared with PSO algorithm when various fog nodes are given.
Stiffness Control of Laminar Jammers With Fused Layers: A Discrete Approach

Laminar jamming, a technique in soft robotics for regulating structural rigidity, traditionally relies on vacuum pressure activation. Recent studies are exploring discrete jamming methods for enhanced portability in soft actuators. This letter investigates stiffness control in a fused laminar structure whose layers are made of 400 grit sandpaper bonded with 75 gsm printer copy paper, and the structure is discretely jammed using custom 3D-printed mini pressure clamps. It presents the concept, design, fabrication, and characterization of the fused jammer. Findings show that increasing separation among laminar layers reduces the structure's rigidity during bending. The study also explores the impact of discrete pressure's location and coverage area on stiffness, revealing that applying pressure closer to the fixed end of the jammer maximizes stiffness. The fabricated fused jammer achieves significantly higher stiffness, up to five times that of a traditional homogeneous jammer made solely of printer paper.
Quantitative and Qualitative Evaluation of Reinforcement Learning Policies for Autonomous Vehicles

Optimizing traffic dynamics in an evolving transportation landscape is crucial, particularly in scenarios where autonomous vehicles (AVs) with varying levels of autonomy coexist with human-driven cars. This paper presents a novel approach to optimizing choices of AVs using Proximal Policy Optimization (PPO), a reinforcement learning algorithm. We learned a policy to minimize traffic jams (i.e., minimize the time to cross the scenario) and to minimize pollution in a roundabout in Milan, Italy. Through empirical analysis, we demonstrate that our approach can reduce time and pollution levels. Furthermore, we qualitatively evaluate the learned policy using a cutting-edge cockpit to assess its performance in near-real-world conditions. To gauge the practicality and acceptability of the policy, we conducted evaluations with human participants using the simulator, focusing on a range of metrics like traffic smoothness and safety perception. In general, our findings show that human-driven vehicles benefit from optimizing AVs dynamics. Also, participants in the study highlighted that the scenario with 80% AVs is perceived as safer than the scenario with 20%. The same result is obtained for traffic smoothness perception
Summary and final report on pyrite, magnetite and hematite mineral geochemistry, South Australia

Sulfide and oxide trace element geochemical analyses have been conducted on more than 290 drill core samples from 39 drillholes across South Australia, as part of a collaborative project between Centre for Ore Deposit and Exploration Science (CODES), University of Tasmania, and the Geological Survey of South Australia. The project aim was to analyse the mineral chemistry of pyrite, hematite and magnetite across a range of deposit styles in SA, and determine whether the technique could be used to provide insights into, and vector within, the various mineral systems. Pyrite analyses showed discernible trends for individual mineralisation types. For example, pyrite which forms in an IOCG-type environment typically contains Co>>Ni, with varying amounts of As, Te, Ag, and Au. Cobalt, Ni, and As are exclusively lattice-bound, whereas Te, Ag, and Au are commonly hosted as inclusions of Au-Ag telluride phases or electrum (AuAg alloy). Hematite and magnetite analyses from different magmatic-hydrothermal systems have revealed that these elements preferentially concentrate a large range of lithophile elements, including the REE’s, with rare to minor incorporation of select chalcophile and siderophile elements (e.g. Co, Ni, As, Zn, Pb, Bi, and Ag). Pyrite and hematite studies on IOCG-style magmatic-hydrothermal mineralisation have been particularly encouraging in the Intercept Hill area, ~90 km south of Olympic Dam. This area, which is very close to Emmie Bluff, contains IOCG-style hematite-magnetite-matrix granite-metasedimentary breccia bodies, together with pyrite-chalcopyrite mineralisation. Pyrite in these zones at Intercept Hill contain high levels (i.e. >>1 ppm) of Au dissolved in the pyrite structure, a feature which is not typical of IOCG-style sulfide mineralisation. Furthermore, the Au content of pyrite varies between drillholes, with the highest amount located near the presumed centre of mineralisation. Pyrite geochemistry thus appears to be a useful vector toward high-grade Au mineralisation at Intercept Hill. Hematite geochemistry also changes with location at Intercept Hill, though the reasons for this variation are not well-constrained. For instance, hematite mineralisation in drillhole IHAD-3 is characterised by fine-grained, colloform hematite crystals in a silicified metasedimentary host rock (possibly a carbonate horizon), with only trace associated sulfides. This style of hematite mineralisation is highly enriched in Mn (average 2 wt %), and is also intergrown with manganite (Mn3O4) which is carrying 1 wt % Cu in solid solution. In contrast, hematite from IHAD-2 and IHAD-5 is coarse-grained (i.e. specularite) and is typically associated with locally abundant pyrite and chalcopyrite. This type of hematite is much lower in Mn (~1000 ppm) and is intergrown with and replaces magnetite, not manganite. The results of this study underscore the value of using mineral trace element geochemistry to elucidate mineral paragenesis and provide proximity indices in magmatic-hydrothermal environments across South Australia and elsewhere.