Miracle-dz/UniFAR-FTUs huggingface dataset:
REVIEW SLEEP AND SLEEP DEPRIVATION TINJAUAN TIDUR DAN KURANG TIDUR

Sleep is a sedentary mental and physical condition. Sleep is necessary for emotional, physical, and cognitive well-being and accounts for approximately one-third of a person's life. Sleep happens in cycles in which the body alternates between two modes: REM sleep and non-REM sleep. Behavioural observation, physiological monitoring, or a mix of the two can be used for the assessment of sleep and wake. Current clinical recommendations for scoring PSGs describe three phases of progressively. The majority of hormones in plasma show strong 24-hour cycles, highlighting the significance of the circadian clock and sleep-related impacts on hormone release and/or metabolism. Lack of sufficient sleep for duration or quality might affect one's ability to function normally and maintain good health. The typical adult requires seven or more hours of sleep each night to be healthy. This report will inform the current state of the science of sleep and sleep deprivation.
Role of brand heritage in local and franchise restaurant service

Given the growth of franchise practices in the service industry, this study focuses on the impact of restaurant heritage in helping to create positive outcomes in company performance. In particular, this study examines the direct impact of brand heritage on customers’ perceived restaurant image and whether it produces positive attitudes and behavior. Due to limited studies on restaurant operation type, the proposed relationship is compared between franchise and local restaurants. Partial least squares structural equation modeling with SmartPLS 4.0 software was used to analyze 599 restaurant customers in the United States. The findings confirm that the perceived restaurant heritage affects the brand image for customers, leading to positive customer evaluations (i.e. satisfaction and trust). In addition, differing levels of customer satisfaction and trust are found to influence the behavioral intentions of customers (i.e. willingness to pay a premium and repurchase intentions). Last, a multigroup analysis showed that the effect of trust on customer behavior was significantly higher among franchise than local customers. In contrast, the effect of satisfaction on customer behavioral intentions was stronger among local than franchise customers. This study provides valuable insights for both local and franchise operators who need to manage their brands to create positive customer outcomes.
Dependability Evaluation of a Smart Poultry House: Addressing Availability Issues Through the Edge, Fog, and Cloud Computing

Internet of Things (IoT) applications equip rural producers with decision support tools and automated solutions that boost agribusiness productivity, quality, and profit. However, most poultry farmers still use conventional methods of operation in which human workers carry out all routines for monitoring and controlling their farms at the expense of greater productivity. One of these human activities is manual weighing, which can be replaced by nonintrusive methods such as computational vision applications that estimate live poultry's weight using video cameras. Since Internet of Things (IoT) devices may have low computing power limiting the ability to process the data locally, they can transfer it to a fog or cloud data center, where they are processed. This article aims to conduct a dependability study of a poultry house automated with a computer vision-based system for estimating poultry weight considering hierarchical models (e.g., Markov chain, reliability block diagram, and closed-form equation) to represent the whole system and obtain steady-state availability and annual downtime. In addition, our purpose is to consider and compare different architectural solutions, such as edge and fog computing-based solutions. The proposed solution verified that a cloud-based application with no redundancy has a downtime of 34.14% and 9.176% hours when considering a hot-standby redundancy strategy in the office node of a cloud solution.
Application of Geological Radar in Surveying the Completeness of Base Rock

With the application practice of geological radar in surveying the completeness of base rock as an example,the paper presents the abno rmal rule and feature appearing in the cross section of common developed Karst a rea through geological radar survey.It provides reference for the future applica tion of geological radar in surveying the completeness of base rock.
Relativity analysis for the false flame extinction and supervisory position of flame detector

This paper analyzed the main causes of false boiler flame extinction through theory analysis and the test of existing boiler,proposed the technology measures to clear the false deduction from flame detector by adjusting the supervisory position of flame detector and verified the feasibility and safety.The practical application indicates that regulating the detecting position is safe and reliable to avoid the false deduction effectively,reduce the amount of the combustion stabilizing oil and prevent the flame extinction resulted from the false deduction of flame detector and the flame protection system.
Risk and Prognosis of Thyroid Cancer in Patients with Graves’ Disease: An Umbrella Review

Simple Summary Graves’ disease (GD) is the most common cause of thyrotoxicosis due to autoimmune hyperthyroidism, especially in women. This umbrella review aimed to provide an evidence-based summary of epidemiological studies conducted on the association between GD and the risk of developing thyroid cancer risk and its prognosis. Strong evidence was found for thyroid cancer risk in GD patients and nodular thyroid disease and mortality risk from thyroid cancer in GD patients, particularly in Europe. However, the results of this umbrella review should be taken with caution; as the evidence comes mainly from retrospective studies, the potential concerns are selection and recall bias. Abstract Graves’ disease (GD) is an autoimmune disease considered the most common cause of hyperthyroidism. Some studies have investigated its relationship with the risk and prognosis of developing thyroid cancer. Considering that there is no consensus on the relationship between GD and thyroid cancer risk, this umbrella review aimed to summarize the epidemiologic evidence and evaluate its strength and validity on the associations of GD with thyroid cancer risk and its prognosis. This umbrella review was performed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We systematically searched PubMed and Scopus from January 2012 to December 2022. The strength of the epidemiological evidence was graded as high, moderate, or weak by the Measurement Tool to Assess Systematic Reviews (AMSTAR-2). “Strong” evidence was found for the risk of thyroid cancer in GD patients with thyroid nodular disease (OR: 5.30; 95% CI 2.43–12) and for the risk of mortality from thyroid cancer in these patients (OR 2.93, 95% CI 1.17–7.37, p = 0.02), particularly in Europe (OR 4.89; 95% CI 1.52–16). The results of this umbrella review should be interpreted with caution; as the evidence comes mostly from retrospective studies, potential concerns are selection and recall bias, and whether the empirically observed association reflects a causal relationship remains an open question.
Hybrid Nanocomposites of Tenoxicam: Layered Double Hydroxides (LDHs) vs. Hydroxyapatite (HAP) Inorganic Carriers

The search for effective systems to facilitate the release of poorly bioavailable drugs is a forefront topic for the pharmaceutical market. Materials constituted by inorganic matrices and drugs represent one of the latest research strategies in the development of new drug alternatives. Our aim was to obtain hybrid nanocomposites of Tenoxicam, an insoluble nonsteroidal anti-inflammatory drug, with both layered double hydroxides (LDHs) and hydroxyapatite (HAP). The physicochemical characterization on the base of X-ray powder diffraction, SEM/EDS, DSC and FT-IR measurements was useful to verify the possible hybrids formation. In both cases, the hybrids formed, but it seemed that the drug intercalation in LDH was low and, in fact, the hybrid was not effective in improving the pharmacokinetic properties of the drug alone. On the contrary, the HAP–Tenoxicam hybrid, compared to the drug alone and to a simple physical mixture, showed an excellent improvement in wettability and solubility and a very significant increase in the release rate in all the tested biorelevant fluids. It delivers the entire daily dose of 20 mg in about 10 min.
Novel Hybrid Inulin–Soy Protein Nanoparticles Simultaneously Loaded with (-)-Epicatechin and Quercetin and Their In Vitro Evaluation

(-)-Epicatechin and quercetin have attracted considerable attention for their potential therapeutic application in non-communicable chronic diseases. A novel hybrid inulin–soy protein nanoparticle formulation was simultaneously loaded with (-)-epicatechin and quercetin (NEQs) to improve the bioavailability of these flavonoids in the human body, and NEQs were synthesized by spray drying. After process optimization, the physicochemical and functional properties of NEQs were characterized including in vitro release, in vitro gastrointestinal digestion, and cell viability assays. Results showed that NEQs are an average size of 280.17 ± 13.42 nm and have a zeta potential of −18.267 ± 0.83 mV in the organic phase. Encapsulation efficiency of (-)-epicatechin and quercetin reached 97.04 ± 0.01 and 92.05 ± 1.95%, respectively. A 3.5% soy protein content conferred controlled release characteristics to the delivery system. Furthermore, NEQs presented inhibitory effects in Caco-2, but not in HepG-2 and HDFa cell lines. These results contribute to the design and fabrication of inulin–soy protein nanoparticles for improving the bioavailability of multiple bioactive compounds with beneficial properties.
The Shape of Inspiration: Exploring the Emotional Arcs and Self-Transcendent Elicitors Within Inspirational Movies

ABSTRACT Emotions have long been regarded as a central component of the entertainment media experience. The present study combines computational analysis and quantitative content analysis to analyze the emotional arcs of inspirational media content and associated elicitors of self-transcendent emotions in order to develop a more comprehensive understanding of inspirational media. Results demonstrate that inspirational movies can be characterized by a positive shift in sentiment at the end of the narrative and multiple shifts between relatively negative and relatively positive sentiment throughout the story. Furthermore, the “peaks” and “valleys” in the emotional arcs are associated with the presence of differing inspirational elicitors, and the presence of certain elicitors (such as kindness/moral goodness) within a scene predicted positive shifts in the emotional arcs in the scenes following the elicitor.
Prediction of Sea Surface Temperature by Combining Numerical and Neural Techniques

AbstractThe prediction of sea surface temperature (SST) in real-time or online mode has applications in planning marine operations and forecasting climate. This paper demonstrates how SST measurements can be combined with numerical estimations with the help of neural networks and how reliable site-specific forecasts can be made accordingly. Additionally, this work demonstrates the skill of a special wavelet neural network in this task. The study was conducted at six different locations in the Indian Ocean and over three time scales (daily, weekly, and monthly). At every time step, the difference between the numerical estimation and the SST measurement was evaluated, an error time series was formed, and errors over future time steps were forecasted. The time series forecasting was affected through neural networks. The predicted errors were added to the numerical estimation, and SST predictions were made over five time steps in the future. The performance of this procedure was assessed through various error.
A comprehensive review on papaya seed oil extraction and recent applications in food industry

The study has been carried out to explore papaya seed oil extraction techniques which are the new source of edible oil in the food industry. Given the global trend towards the utilisation of solid waste and agricultural leftovers, oil extraction could give economic value to a large number of seeds that are generally wasted. In conventional extraction technology there are many shortcomings, like high consumption of energy, more consumption of harmful chemicals. These have forced the food and chemical industries to find new separation "green" techniques which typically use less solvent and energy, such as microwave extraction, supercritical fluid extraction, ultrasound extraction, ultrafiltration, flash distillation, the controlled pressure drop process and subcritical water extraction. Separation under extreme or non-classical conditions is currently a dynamically developing area in applied research and industry. The bioactive compounds present in papaya seeds make its essential oil a promising food for therapeutic benefits. There are traditional and non-traditional methods for extracting oil from papaya seeds. Traditional extraction methods such as soxhlet extraction and solvent extraction as well as non-traditional extraction methods such as enzyme-assisted, ultrasound-assisted, microwave-assisted, and supercritical fluid extractions have been studied. Plants are used to extract vegetable oils, which are then employed in a variety of industrial and food products. This review summarizes the methods and technologies that can be used for the efficient extraction of papaya seed oil, along with its nutritional importance and applications in the food sector.
Understanding the Role of Social Media Content in Brand Loyalty: A Meta-Analysis of User-Generated Content Versus Firm-Generated Content

The enormous growth of social media has increased interest in this platform among marketers and marketing academics. However, the previous literature has not provided a clear consensus regarding the influence of social media content on consumers’ brand loyalty. The meta-analysis presented in this article integrates results from 223 independent samples, with a total of 97,709 respondents. The study synthesizes previous research to develop a conceptual framework around the dimensions of brand loyalty (cognitive, affective, and conative loyalty), user-generated and firm-generated social media content attributes, and the moderating effects of contextual characteristics and control variables. Selected content attributes (information quality, information credibility, information usefulness, positive emotions, interactivity, and self-congruity) emerged as triggers in social media for dimensions of brand loyalty. Specifically, the authors show that the impact of the attributes on the brand loyalty dimension is stronger for firm-generated content than for user-generated content for most of the relationships. The results indicate that these effects are dependent on contextual characteristics (e.g., low involvement vs. high involvement, hedonic vs. utilitarian, nondurable vs. durable, Human Development Index, and social media platform). The contributions to theory and managerial implications of these findings are discussed, and future research directions are developed.
Fibromyalgia – etiology, diagnosis and treatment including perioperative management in patients with fibromyalgia

Fibromyalgia (FM) is considered a multifactorial disorder/syndrome with not fully understood etiology. Chronic generalized pain is the main symptom. A broad spectrum of factors is proposed to explain the etiology. Its multifactorial nature is inherently associated with challenges in diagnosis and therapy. Various evidence of etiology has been evaluated with the aim of establishing a novel therapeutic approach. The main issue in the diagnosis and management is to focus on the evaluation of strict diagnostic criteria to minimize under- and overdiagnosis. Fibromyalgia is a challenge for perioperative management because of the increased risk of possible complications and poorer outcomes, including postoperative pain chronification. The authors have proposed an up-to-date evaluation of perioperative management considering the current guidelines. Multimodal analgesia combined with tailored perioperative care is the most appropriate assessment. Interdisciplinary research with special interest in pain management, including perioperative medicine, seems to be the main theme for the future.
Infrared Small Target Detection Algorithm Using an Augmented Intensity and Density-Based Clustering

In infrared search and tracking (IRST) systems, small target detection is challenging because IR imaging lacks feature information and has a low signal-to-noise ratio. The recently studied small IR target detection methods have achieved high detection performance without considering execution time. We propose a fast and robust single-frame IR small target detection algorithm while maintaining excellent detection performance. The augmented infrared intensity map based on the standard deviation speeds up small target detection and improves detection accuracy. Density-based clustering helps to detect the shape of objects and makes it easy to identify centroid points. By incorporating these two approaches, the proposed method has a novel approach to the small target detection algorithm. We have self-built 300 images with various scenes and experimented with comparing other methods. Experimental results demonstrate that the proposed method is suitable for real-time detection and effective even when the target size is as small as 2 pixels.
Clustering of eruptive events from high precision strain signals recorded during the 2020-2022 lava fountains at Etna volcano (Italy)

Explosive eruption events have been clustered by machine learning techniques applied on strain signal recorded by high-precision borehole strainmeters. We focus on the extraordinary intense and frequent eruptive activity at Etna in the period December 2020 – February 2022 when more than 60 lava fountains occurred. We apply the k-means algorithm on the associated strain variations which are representative of the eruptive dynamics. A novel procedure was developed to ensure a high-quality clustering process and obtain robust results. The analysis identified four distinct groups of strain variations 10 which characterize the events in terms of amplitude, and duration and time derivative of the signal. The temporal distribution of the clusters provides useful insights into the evolution of the volcano activity and reveals transitions in the eruptive style.
Fermented Whey Ewe’s Milk-Based Fruit Smoothies: Bio-Recycling and Enrichment of Phenolic Compounds and Improvement of Protein Digestibility and Antioxidant Activity

This study aimed to recycle whey milk by-products (protein source) in fruit smoothies (phenolic compounds source) through started-assisted fermentation and delivering sustainable and healthy food formulations capable of providing nutrients that are unavailable due to an unbalanced diet or incorrect eating habits. Five lactic acid bacteria strains were selected as best starters for smoothie production based on the complementarity of pro-technological (kinetics of growth and acidification) traits, exopolysaccharides and phenolics release, and antioxidant activity enhancement. Compared to raw whey milk-based fruit smoothies (Raw_WFS), fermentation led to distinct profiles of sugars (glucose, fructose, mannitol, and sucrose), organic acids (lactic acid and acetic acid), ascorbic acid, phenolic compounds (gallic acid, 3-hydroxybenzoic acid, chlorogenic acid, hydrocaffeic acid, quercetin, epicatechin, procyanidin B2, and ellagic acid) and especially anthocyanins (cyanidin, delphinidin, malvidin, peonidin, petunidin 3-glucoside). Protein and phenolics interaction enhanced the release of anthocyanins, notably under the action of Lactiplantibacillus plantarum. The same bacterial strains outperformed other species in terms of protein digestibility and quality. With variations among starters culture, bio-converted metabolites were most likely responsible for the increase antioxidant scavenging capacity (DPPH, ABTS, and lipid peroxidation) and the modifications in organoleptic properties (aroma and flavor).
Linear Zero-Knowledgde. A Note on Efficient Zero-Knowledge Proofs and Arguments

We present a zero-knowledge proof system [19] for any NP language L, which allows showing that x in L with error probability less than 2^−k using communication corresponding to O(|x|^c) + k bit commitments, where c is a constant depending only on L. The proof can be based on any bit commitment scheme with a particular set of properties. We suggest an efficient implementation based on factoring. We also present a 4-move perfect zero-knowledge interactive argument for any NP-language L. On input x in L, the communication complexity is O(|x|^c) max(k; l) bits, where l is the security parameter for the prover. Again, the protocol can be based on any bit commitment scheme with a particular set of properties. We suggest efficient implementations based on discrete logarithms or factoring. We present an application of our techniques to multiparty computations, allowing for example t committed oblivious transfers with error probability 2^−k to be done simultaneously using O(t+k) commitments. Results for general computations follow from this. As a function of the security parameters, our protocols have the smallest known asymptotic communication complexity among general proofs or arguments for NP. Moreover, the constants involved are small enough for the protocols to be practical in a realistic situation: both protocols are based on a Boolean formula Phi containing and- , or- and not-operators which verifies an NP-witness of membership in L. Let n be the number of times this formula reads an input variable. Then the communication complexity of the protocols when using our concrete commitment schemes can be more precisely stated as at most 4n + k + 1 commitments for the interactive proof and at most 5nl +5l bits for the argument (assuming k the number of commitments required for the proof is linear in n. Both protocols are also proofs of knowledge of an NP-witness of membership in the language involved.