Miracle-dz/UniFAR-FTUs huggingface dataset:
A Damage Detection Approach in the Era of Industry 4.0 Using the Relationship between Circular Economy, Data Mining, and Artificial Intelligence

Over the last decades, the emergence of new technologies has inspired a paradigm shift for the fourth industrial revolution. For example, circular economy, data mining, and artificial intelligence (AI), which are multidisciplinary topics, have recently attracted industrial and academic interests. Sustainable structural health monitoring (SHM) also concerns the continuous structural assessment of civil, mechanical, aerospace, and industrial structures to upgrade conventional SHM systems. A damage detection approach inspired by the principles of data mining with the adoption of circular-economic thinking is proposed in this study. In addition, vibration characteristics of a composite bridge deck structure are employed as inputs of AI algorithms. Likewise, an artificial neural network (ANN) integrated with a genetic algorithm (GA) was also developed for detecting the damage. GA was applied to define the initial weights of the neural network. To aid the aim, a range of damage scenarios was generated and the achieved outcomes confirm the feasibility of the developed method in the fault diagnosis procedure. Several data mining techniques were also employed to compare the performance of the developed model. It is concluded that the ANN integrated with GA presents a relatively fitting capacity in the detection of damage severity.
Case Report: HAVCR2 mutation-associated Hemophagocytic lymphohistiocytosis

Germline HAVCR2 mutation has been reported to be associated with subcutaneous panniculitis-like T-cell lymphoma (SPTCL) leading to Hemophagocytic lymphohistiocytosis (HLH). Several studies have indicated that HAVCR2 mutation can cause HLH even in the absence of lymphoma, though the exact mechanism remains unclear. In this article, we reported five cases of HAVCR2 mutation-associated HLH. Our analysis revealed an elevated level of IL-1RA in the serum of these patients. Furthermore, we investigated the potential mechanisms underlying HLH associated with HAVCR2 mutation based on changes in cytokine levels. Our findings suggest that HAVCR2 mutation may represent a distinct genetic defect underlying HLH, differing from traditional primary HLH.
More Than Organic: Consumer Expectations of Sustainability and Quality. Evidences from a Qualitative Study in Italy

ABSTRACT Research shows that the search for healthier foods and concern for sustainability are driving the purchase of organic products. However, consumer expectations for quality attributes and sustainability often go beyond the parameters for organic certification, even after the latest revision (EU Regulation 2018/848). This article aims to explore Italian consumers’ expectations for attributes beyond the current organic certification and to highlight the importance of introducing an additional certification for this added value. Nine focus groups (59 participants) were conducted and analyzed with the Template Analysis approach using Atlas.ti 6.0. Participants expressed expectations beyond current organic certification: i) “for the consumer” (excellent product quality); ii) “for the people and the planet” (ethical aspects of production and distribution); iii) information about organic labels. The development of an “organic plus sustainability certification” seems important: it could allow consumers to make more conscious and ethical purchasing decisions in mature but still changing organic markets such as Italy.
Aerococcus viridans Phage Lysin AVPL Had Lytic Activity against Streptococcus suis in a Mouse Bacteremia Model

Streptococcus suis (S. suis) is a swine pathogen that can cause sepsis, meningitis, endocarditis, and other infectious diseases; it is also a zoonotic pathogen that has caused a global surge in fatal human infections. The widespread prevalence of multidrug-resistant S. suis strains and the decline in novel antibiotic candidates have necessitated the development of alternative antimicrobial agents. In this study, AVPL, the Aerococcus viridans (A. viridans) phage lysin, was found to exhibit efficient bactericidal activity and broad lytic activity against multiple serotypes of S. suis. A final concentration of 300 μg/mL AVPL reduced S. suis counts by 4–4.5 log10 within 1 h in vitro. Importantly, AVPL effectively inhibited 48 h S. suis biofilm formation and disrupted preformed biofilms. In a mouse model, 300 μg/mouse AVPL protected 100% of mice from infection following the administration of lethal doses of multidrug-resistant S. suis type 2 (SS2) strain SC19, reduced the bacterial load in different organs, and effectively alleviated inflammation and histopathological damage in infected mice. These data suggest that AVPL is a valuable candidate antimicrobial agent for treating S. suis infections.
Predictors of Phthalate Metabolites Exposure among Healthy Pregnant Women in the United States, 2010–2015

Phthalate use and the concentrations of their metabolites in humans vary by geographic region, race, ethnicity, sex, product use and other factors. Exposure during pregnancy may be associated with detrimental reproductive and developmental outcomes. No studies have evaluated the predictors of exposure to a wide range of phthalate metabolites in a large, diverse population. We examined the determinants of phthalate metabolites in a cohort of racially/ethnically diverse nulliparous pregnant women. We report on urinary metabolites of nine parent phthalates or replacement compounds—Butyl benzyl phthalate (BBzP), Diisobutyl phthalate (DiBP), Diethyl phthalate (DEP), Diisononyl phthalate (DiNP), D-n-octyl phthalate (DnOP), Di-2-ethylhexyl terephthalate (DEHTP), Di-n/i-butyl phthalate (DnBP), Di-isononyl phthalate (DiNP) and Di-(2-ethylhexyl) phthalate (DEHP) from urine collected up to three times from 953 women enrolled in the Nulliparous Mothers To Be Study. Phthalate metabolites were adjusted for specific gravity. Generalized estimating equations (GEEs) were used to identify the predictors of each metabolite. Overall predictors include age, race and ethnicity, education, BMI and clinical site of care. Women who were Non-Hispanic Black, Hispanic or Asian, obese or had lower levels of education had higher concentrations of selected metabolites. These findings indicate exposure patterns that require policies to reduce exposure in specific subgroups.
Prognostic Impact of the UMIPIC Program in the Follow Up in Patients with Heart Failure and Cardiorenal Syndrome

Background: Individuals suffering from heart failure (HF) and cardiorenal syndrome (CRS) represent a special group of patients considering their age, multiple health issues, and treatment challenges. These factors make them more susceptible to frequent hospital stays and a higher mortality rate. UMIPIC is a multidisciplinary care model program for patients with heart failure follow up provided by internists and nurses who are experts in this entity. Our study delved into the effectiveness of this specialized care program (UMIPIC) in mitigating these risks for HF and CRS patients. Methods: We analyzed the medical records of 3255 patients diagnosed with HF and CRS types 2 and 4, sourced from the RICA registry. These patients were divided into two distinct groups: those enrolled in the UMIPIC program (1205 patients) and those under standard care (2050 patients). Using propensity score matching, we ensured that both groups were comparable. The study focused on tracking hospital admissions and mortality rates for one year after an HF-related hospital stay. Results: Patients in the UMIPIC group experienced fewer hospital readmissions due to HF compared to their counterparts (20% vs. 32%; Hazard Ratio [HR] = 0.48; 95% Confidence Interval [95% CI]: 0.40–0.57; p < 0.001). They also showed a lower mortality rate (24% vs. 36%; HR = 0.64; 95% CI: 0.54–0.75; p < 0.001). Furthermore, the UMIPIC group had fewer total hospital admissions (36% vs. 47%; HR = 0.58; 95% CI: 0.51–0.66; p < 0.001). Conclusions: The UMIPIC program, centered on holistic and ongoing care, effectively reduces both hospital admissions and mortality rates for HF and CRS patients after a one-year follow-up period.
Hydrogeochemistry of coal mine drainage and other ferruginous waters in north Derbyshire and south Yorkshire, UK

Abstract Fifteen coal mine drainage waters from the Millstone Grit and Coal Measures of Derbyshire and Yorkshire have been compared hydrochemically with other iron-rich waters from spoil tips, natural springs and lead mine soughs in the area. The coal mine waters typically contained several tens of mg/l iron, with a range from 0.1 to 101 mg/l, and sulphate from 60 to over 1000 mg/l. The waters are undersaturated with respect to siderite. There is a strong linear correlation between iron and sulphate indicating that pyrite weathering is the dominant source of these parameters, although iron appears to be preferentially removed by precipitation or adsorption within the mines. The pH values of coal mine water are typically c. 6, although one water has a pH of 3.6, contains some 17 mg/l aluminium and lacks the saturation relative to gibbsite and kaolinite present in the other waters. The coal mine waters may be net acidic or net alkaline: there is some evidence to suggest that the former are typically derived from unsaturated, underdrained (i.e. drained from underneath the workings) shallow workings and the latter from saturated, overflowing workings. The spoil tip waters are neutral to alkaline and saline. A possible explanation for this is the leaching of residual pore-water brines from the deep (several hundred metres) mined strata. The spoil tip leachates are poor in iron, which may be retained as iron hydroxides, sulphates or even siderite within the spoil.
Evaluation of Cyber Insecurities of the Cyber Physical System Supply Chains Using α-Discounting MCDM

Recently, supply chains (SCs) are applying information technology to enable data sharing among suppliers, instant access to information, and complete tracking of products. With more cybersecurity risks present, such as theft of information, service interruptions, and financial resources risks, the vulnerability of systems is increased. The management of supply chain cybersecurity, which encompasses information systems, software, and infrastructure, is the emphasis of the supply chain's safety measure. There are several serious danger that attack supply chain systems. Most SC Cybersecurity procedures are used to reduce the threats posed by vulnerabilities to those processes. Researchers have mostly concentrated on supply chain-related cyber physical system (CPS) issues. This study makes attempts to classify and evaluate the cybersecurity insecurities of supply chains. In addition, this work provides an update of the analytic hierarchy process (AHP) method called α-discounting multi-criteria decision-making (α-D MCDM), which enables a more uniform assessment of supply chain cyber insecurities. This paper suggests using the α-D MCDM in various ways to address various supply chain evaluation problems.
Composition, interaction networks, and nitrogen metabolism patterns of bacterioplankton communities in a grassland type Lake: a case of Hulun Lake, China

The composition of bacterial communities in freshwater ecosystems is influenced by numerous factors including environmental conditions and biological interactions. In grassland inland closed lakes, factors affecting lake ecosystems are either exogenous or endogenous, contributing to the formation of distinct habitats in the surface and bottom waters of the bacterial communities. However, the extent to which environmental factors selectively shape the bacterial communities in aquatic systems remains unclear. Therefore, we sampled the surface, middle, and bottom waters at 13 sampling points in each layer. High-throughput sequencing techniques were employed to examine the spatial heterogeneity of the bacterial community structure during summer in Hulun Lake, the largest grassland-type lake in Inner Mongolia, China, to determine the microbial community dynamics and symbiosis patterns under different habitat conditions. Our results revealed a decrease in the diversity and heterogeneity of the bacterioplankton community, influenced by changes in the environment from exogenous inputs to endogenous releases. Furthermore, this alteration in community structure was concomitant with enhanced co-occurrences among microorganisms in the bottom water layers. This finding suggests that endogenous release promotes heightened symbiotic interactions, thereby facilitating the development of more complex modular structures. Symbiotic networks in different layers were differentiated by key species, with the ecological clustering modules of these species demonstrating dissimilar environmental preferences. The microbial communities were highly habitat-specific, mimicking responses to total nitrogen (TN) in the surface layer, pH in the middle layer, and chemical oxygen demand (COD) in the bottom layer. Bacterioplankton functions were assessed using Tax4Fun, indicating exogenous inputs and endogenous release increased the relative abundance of genes with nitrogen-fixing and nitrification potential nitrogen metabolism functions in surface and bottom waters, respectively. With Planctomycetota and Proteobacteria phyla as potential key groups for regulating nitrogen metabolic processes, Proteobacteria may facilitate the depletion of nitrate in surface and bottom waters, while the close contact of surface waters with the atmosphere accelerated Planctomycetota-dominated nitrogen fixation into the lake. Our findings contribute to the understanding of vertical microbial diversity and its network patterns in grassland type lakes, underscoring the potential role of environmental factors (exogenous inputs and endogenous releases) in bacterioplankton community formation.
The Impact of Type D Personality Traits on Quality of Life, Sleep, Anxiety, and Depression in Fibromyalgia Patients: A Comparative Study with Healthy Controls

Background Type D personality has been associated with adverse clinical outcomes and poor quality of life in many diseases. This study aimed to evaluate the effects of type D personality on pain, anxiety and depression, sleep quality, and quality of life in 50 patients with fibromyalgia syndrome. Material/Methods Fifty patients with fibromyalgia and 50 healthy controls were included in the study. Baseline and post-treatment evaluations encompassed a comprehensive battery of assessment tools: socio-demographic questionnaire, visual analog scale for pain, Beck Anxiety Inventory, Beck Depression Inventory, Fibromyalgia Impact Questionnaire, SF-36 Short Form Questionnaire, and Pittsburgh Sleep Quality Index. The effects of type D personality traits on clinical parameters were determined by evaluating the participants with the D-Type Personality Scale (DS-14). Results Twelve participants (24%) in the control group and 30 patients (60%) in the fibromyalgia group had type D personality traits, and the difference was significant (P<0.001). The Beck Anxiety Inventory and Beck Depression Inventory scores were significantly higher, and the SF-36 domains of vitality and mental health were significantly lower in fibromyalgia patients with type D personality (P=0.023, P=0.036, P=0.002, P>0.001). Conclusions This study draws attention to the high prevalence of type D personality in patients with fibromyalgia and demonstrates that this personality trait has a negative impact on patients’ clinical parameters.
δ11B as tracer of slab dehydration and mantle evolution in Western Anatolia Cenozoic Magmatism

Boron isotope data are presented for Cenozoic Western Anatolia rocks, which define two main associations: (i) calc‐alkaline, shoshonitic and ultra‐potassic rocks (Early to Middle Miocene); and (ii) Late Miocene–Quaternary intraplate alkali basalts. Boron data, together with Sr–Nd isotope and other trace elements, are consistent with a progressive dehydration of the slab, producing fluid phases gradually depleted in B (and 11B). These fluids were added to the supraslab mantle, triggering a partial melting that gave rise to orogenic magmatism. The stretching and tearing of the slab caused by the faster convergence of Greece over Africa with respect to Anatolia facilitated an interaction of the upwelling subslab asthenosphere with residual slab‐fluids during the Late Miocene followed by production of typical intraplate magmas during the Pleistocene–Holocene, whose relatively high δ11B (approximately −2‰) is considered representative of the local asthenosphere not affected by subduction contamination.
Associations between Host Genetic Variants and Subgingival Microbiota in Patients with the Metabolic Syndrome

Host genetic variants may affect oral biofilms, playing a role in the periodontitis–systemic disease axis. This is the first study to assess the associations between host genetic variants and subgingival microbiota in patients with metabolic syndrome (MetS); 103 patients with MetS underwent medical and periodontal examinations and had blood and subgingival plaque samples taken. DNA was extracted and processed, assessing a panel of selected single nucleotide polymorphisms (SNPs) first (hypothesis testing) and then expanding to a discovery phase. The subgingival plaque microbiome from these patients was profiled. Analysis of associations between host genetic and microbial factors was performed and stratified for periodontal diagnosis. Specific SNPs within RUNX2, CAMTA1 and VDR genes were associated with diversity metrics with no genome-wide associations detected for periodontitis severity or Mets components at p < 10−7. Severe periodontitis was associated with pathogenic genera and species. Some SNPs correlated with specific bacterial genera as well as with microbial taxa, notably VDR (rs12717991) with Streptococcus mutans and RUNX2 (rs3749863) with Porphyromonas gingivalis. In conclusion, variation in host genotypes may play a role in the dysregulated immune responses characterizing periodontitis and thus the oral microbiome, suggesting that systemic health-associated host traits further interact with oral health and the microbiome.
CONFLICT IN KEVIN KWAN'S NOVEL CRAZY RICH ASIANS

The study aims to describe the kinds of conflict and also the factors causing conflict in Kevin Kwan's novel Crazy Rich Asians. It only focuses on kinds of conflict and factors causing conflict in selected characters of the novel. This study used a qualitative method. The data were analyzed descriptively. The data in this study were collected from the novel Crazy Rich Asians by Kevin Kwan. The data were taken by reading and marking words and phrases from the novel, which are related to the study. The data were analyzed from the novel based on the theory and statement of the problem to be analyzed. The results of the analysis obtained from this study have two conclusions. First, the types of conflicts in the novel Crazy Rich Asians, namely internal and external conflict are found in several characters in the novel. Second, the factors that may cause conflict in the novel Crazy Rich Asians are causative factors. These factors are differences between individuals, cultural differences, and differences in interests. The results of this study are expected to provide benefits, understanding, and knowledge in analyzing conflict in a literary work in the form of a novel. The results of this study are also expected to be used as a reference for further research.
The Protection of Land-based Wildlife under International Law

This article presents an overview of international wildlife protection law with the aim of presenting its breadth and the variety of approaches it takes which can be categorised as: protection by habitat; protection by species; protection through controlling trade; and protection as part of a wider ecosystem. The international law for the protection of wildlife presents a highly complex picture since (a) it relies on a variety of discreet approaches (or a combination thereof) (b) it applies to areas both within and beyond national jurisdiction (c) it applies also to areas such as Antarctica and international marine areas in which special international law regimes apply and (d) the subject of protection - animals - do not respect legally enforced territorial boundaries. In order to make it clearer, this article analyses the relevant law in the following manner: global treaties of general application; global treaties protecting habitats and/or species; and regional treaties. Other issues addressed include the use of scientific terminologies in a legal context and the relationship between wildlife conservation and animal welfare/rights. This analysis aims (a) to clarify the nature of the obligations placed on governments as Parties to these treaties (and the actions required for their implementation) and (b) to help us to identify the most effective strategies for the future development of national protective legislation and other measures. In view of the limited space available, the protection of land-based species is the focus of this article although, of course, the treaties described here apply also to the coastal and territorial waters of the Parties. ﻦﯿﺑ قﻮﻘﺣ ﺮﻈﻨﻣ زا ﻦﯿﻣز يور ﺶﺣو تﺎﯿﺣ زا ﺖﻇﺎﻔﺣ ﻞﻠﻤﻟا
Low-Cost EEG Multi-Subject Recording Platform for the Assessment of Students’ Attention and the Estimation of Academic Performance in Secondary School

The level of student attention in class greatly affects their academic performance. Teachers typically rely on visual inspection to react to students’ attention in time, but this subjective method leads to inconsistencies across classes. Online education exacerbates the issue as students can turn off cameras and microphones to keep their own privacy. To address this, we present a novel, low-cost EEG-based platform for assessing students’ attention and estimating their academic performance. In a study involving 34 secondary school students (aged 14 to 16), participants watched an academic video and answered evaluation questions while their EEG activity was recorded using a commercial headset. The results demonstrate a significant correlation (0.53, p-value = 0.003) between the power spectral density (PSD) of the EEG beta band (12–30 Hz) and students’ academic performance. Additionally, there was a notable difference in PSD-beta between high and low academic performers. These findings encourage the use of PSD-beta for the immediate and objective assessment of both the student attention and the subsequent academic performance. The platform offers valuable and objective feedback to teachers, enhancing the effectiveness of both face-to-face and online teaching and learning environments.
Contextual Set Selection Under Human Feedback With Model Misspecification

A common and efficient way to elicit human feed-back is to present users with a set of options, and record their relative preferences on the presented options. The contextual combinatorial ban-dits problem captures this setting algorithmically; however, it implicitly assumes an underlying consistent reward model for the options. The setting of human feedback (which e.g. may use different reviewers for different samples) means that there may not be any such model – it is misspecified . We first derive a lower-bound for our setting, and then show that model misspecification can lead to catastrophic failure of the C 2 UCB al-gorithm (which is otherwise near-optimal when there is no misspecification). We then propose two algorithms: the first algorithm (MC 2 UCB) requires knowledge of the level of misspecification ϵ (i.e., the absolute deviation from the closest well-specified model). The second algorithm is a general framework that extends to unknown ϵ . Our theoretical analysis shows that both algorithms achieve near-optimal regret. Further empirical evaluations, conducted both in a synthetic environment and a real-world application of movie recommendations, demonstrate the adaptability of our algorithm to various degrees of misspecifi-cation. This highlights the algorithm’s ability to effectively learn from human feedback, even with model misspecification.