Miracle-dz/UniFAR-FTUs huggingface dataset:
Food Safety Issues in the Oltrepò Pavese Area: A SERS Sensing Perspective

Handly and easy-to-use optical instrumentation is very important for food safety monitoring, as it provides the possibility to assess law and health compliances at every stage of the food chain. In particular, the Surface-enhanced Raman Scattering (SERS) method appears highly promising because the intrinsic drawback of Raman spectroscopy, i.e., the natural weakness of the effect and, in turn, of the signal, is overcome thanks to the peculiar interaction between laser light and plasmonic excitations at the SERS substrate. This fact paved the way for the widespread use of SERS sensing not only for food safety but also for biomedicine, pharmaceutical process analysis, forensic science, cultural heritage and more. However, the current technological maturity of the SERS technique does not find a counterpart in the recognition of SERS as a routine method in compliance protocols. This is mainly due to the very scattered landscape of SERS substrates designed and tailored specifically for the targeted analyte. In fact, a very large variety of SERS substrates were proposed for molecular sensing in different environments and matrices. This review presents the advantages and perspectives of SERS sensing in food safety. The focus of the survey is limited to specific analytes of interest for producers, consumers and stakeholders in Oltrepò Pavese, a definite regional area that is located within the district of Pavia in the northern part of Italy. Our attention has been addressed to (i) glyphosate in rice fields, (ii) histamine in a world-famous local product (wine), (iii) tetracycline, an antibiotic often detected in waste sludges that can be dangerous, for instance in maize crops and (iv) Sudan dyes—used as adulterants—in the production of saffron and other spices, which represent niche crops for Oltrepò. The review aims to highlight the SERS performance for each analyte, with a discussion of the different methods used to prepare SERS substrates and the different reported limits of detection.
Mesenchymal Stem Cells in the Pathogenesis and Therapy of Autoimmune and Autoinflammatory Diseases

Mesenchymal stem cells (MSCs) modulate immune responses and maintain self-tolerance. Their trophic activities and regenerative properties make them potential immunosuppressants for treating autoimmune and autoinflammatory diseases. MSCs are drawn to sites of injury and inflammation where they can both reduce inflammation and contribute to tissue regeneration. An increased understanding of the role of MSCs in the development and progression of autoimmune disorders has revealed that MSCs are passive targets in the inflammatory process, becoming impaired by it and exhibiting loss of immunomodulatory activity. MSCs have been considered as potential novel cell therapies for severe autoimmune and autoinflammatory diseases, which at present have only disease modifying rather than curative treatment options. MSCs are emerging as potential therapies for severe autoimmune and autoinflammatory diseases. Clinical application of MSCs in rare cases of severe disease in which other existing treatment modalities have failed, have demonstrated potential use in treating multiple diseases, including rheumatoid arthritis, systemic lupus erythematosus, myocardial infarction, liver cirrhosis, spinal cord injury, multiple sclerosis, and COVID-19 pneumonia. This review explores the biological mechanisms behind the role of MSCs in autoimmune and autoinflammatory diseases. It also covers their immunomodulatory capabilities, potential therapeutic applications, and the challenges and risks associated with MSC therapy.
A Typology of Family Functioning at The Beginning of The COVID-19 Pandemic

Family functioning affects the physical and psychological health of individuals in the family. The more effortlessly a family performs its various functions, the better the mental health of its members. The purpose of this research is to analyze family issues and explore the elements that influence family functioning following the implementation of the Large Scale Social Restrictions (PSBB) policy. The research was conducted using an online survey method via Google form application. Data were collected from 18 provinces, with West Java having the highest percentage (54.8%), followed by DKI Jakarta (12.3%), Riau (7.1%), East Java (6.5%), and South Sumatra (6.0%). Data were processed using SPSS version 20, followed by descriptive and regression analysis. Based on the dimensions of family functioning, the results showed that more than 80 percent of the aspects of communication and affective responsiveness were in the low category. In comparison, more than 90 percent of responders rate their role and behavioral control as high. According to the functioning typology, as many as 64% of families have less functioning conditions, while 36% of families are still functioning well. According to the findings, the COVID-19 epidemic has also caused additional challenges for families, especially children (63.5%) and economic problems (49.5%). These findings are intended to provide useful information to the government and academia in strengthening family resilience during times of crisis.
Are Excessive Daytime Sleepiness and Lower Urinary Tract Symptoms the Triggering Link for Mental Imbalance? An Exploratory Post Hoc Analysis

Background: Both lower urinary tract symptoms (LUTS) and excessive daytime sleepiness (EDS) could negatively impair the patients’ quality of life, increasing the sensitivity to psychological distress that results in mental health disorders. The relationships of both urinary and respiratory domains with psychological distress in obstructive sleep apnea patients is still underestimated. Methods: This study was a post hoc analysis of a web-based Italian survey, which included 1998 participants. Three hierarchical multiple linear regression analyses with psychological distress as dependent variable were performed on the study of 1988 participants enrolled in the final analysis. Cohen’s f2 was used for the assessment of the effect size. Results: From the hierarchical multiple linear regression analyses, it emerged that the final statistical model (including sociodemographic characteristics, comorbidities, perceived urinary function, and excessive daytime sleepiness) for all dimensions accounted for 16.7% of the variance in psychological distress, with a medium effect size (f2 = 0.15). Conclusions: People reported psychological distress was impaired by the presence of LUTS and EDS. Specifically, our study showed that higher levels of distress were scored especially in young women exhibiting urinary symptoms and with high values of daytime sleepiness.
The Design of a 1–6 GHz Broadband Double-Balanced Mixer

This brief proposes a 1–6 GHz broadband double-balanced mixer. On the basis of the standard Marchand balun mixer, two techniques to enhance the performance of the mixer are proposed. Firstly, by loading capacitors, the amplitude and phase imbalance of the balun at high frequencies are improved, thereby expanding the relative bandwidth of the mixer by 0.1. Secondly, by cascading a first-order LC filter at the intermediate-frequency (IF) port, the leakage of radio frequency (RF) and local oscillator (LO) signals at the IF port is reduced by approximately 8 dB and 7 dB, respectively. This brief analyzes the various parameters that affect balun indicators and designs a broadband balun with a double-layer spiral line structure. As a result of these technologies, a 1–6 GHz double-balanced mixer is realized. The chip area is 1.13 mm × 0.95 mm, and the isolation between the IF port and the RF port is 34 dB and yields 13.5 dBm input power at 1 dB compression point (IP1 dB). The chip is fabricated via the GaAs pHEMT process.
Relationship Between Spatial Price Transmission And Geographical Distance In Brazil

The price transmission between markets is often interpreted as providing insights into the market’s infrastructure efficiency and transaction costs. Thus, finding a possible explanation for the degree of integration has become an issue of special interest. Recent researchers have pointed out the distance between markets as one of the possible factors. However, the distance is closely related with other elements, such as road quality and the proximity to an export point, which affect transport costs, opportunity costs and thus the integration. Therefore, what the most important factor is when determining the relationship among markets remains unclear. The cointegration framework, OLS and principal component regressions are applied in order to investigate the influence of geographical distance on the cointegration relationship between Brazil`s rice markets. In response to changes of the agricultural policies during the period of investigation, the presence of multiple structural breaks in the long run equation is allowed. The results point out a weak, negative and significant relation between distance and the elasticity of cointegration. Moreover, the region in which the market is located and a better access to export points are the main variables which defined the strength of the price transmission.
Effect of Different Host Plants on Life Type Characteristics of Three Spider Mite Pests (Acari: Prostigmata: Tetranychidae)

Simple Summary Some spider mite species are economically important agricultural pests, attacking both annual and perennial host plants. They usually produce silken threads of varying densities on the surface of the leaves of inhabiting plants to perform various biological/behavioral activities. In the present study, field-collected leaf samples and laboratory-infested leaves were used to evaluate the effect of different plants on the web-associated behavioral characteristics (life type) of three spider mite species, namely, Tetranychus urticae, Eutetranychus orientalis, and Eutetranychus palmatus. Both annual and perennial plants for T. urticae and only perennial plants for E. orientalis and E. palmatus were used. Two spider mites, E. orientalis and E. palmatus, showed persistence in life type characteristics on different plant species. In contrast, some behavioral characteristics of T. urticae varied by changing the host plants. Although T. urticae showed variations in some behavioral characteristics, it did not change its life type, which shows its high adaptability to utilizing the host plant resources. The variations observed in the life type characteristics of T. urticae could be helpful in applied pest management. Abstract The present study evaluated the host plant effect on life type characteristics of three important spider mite pest species, Tetranychus urticae Koch, Eutetranychus orientalis (Klein), and E. palmatus Attiah (Acari: Prostigmata: Tetranychidae), based on both field and laboratory observations. The polyphagous species, T. urticae with complicated web (CW-u) life type, occupying unstable habitats, showed variations in the sites for quiescence (SQ), sites for oviposition (SO), sites for defecation (SD), and webbing density (WD) on different annual/perennial host plants. The SQ, SO, and SD of T. urticae were observed either on the leaf, web threads, or trichomes. Tetranychus urticae constructed the lowest WD on tomato plants and the highest WD on maize/mulberry plants. Two spider mite species of the genus Eutetranychus Banks, the polyphagous E. orientalis and the oligophagous E. palmatus, inhabit stable host plants, depicted in the little web (LW-j) life types with persistency in all characteristics on different plants. It is concluded that polyphagous spider mites have restricted their life types, showing their high adaptability to utilize the resources of different host plants for survival with slight variation in some important life type characteristics.
Speaker-Aware Interactive Graph Attention Network for Emotion Recognition in Conversation

Recently, Emotion Recognition in Conversation (ERC) has attracted much attention and has become a hot topic in the field of natural language processing. Conversation is conducted in chronological order; current utterance is more likely influenced by nearby utterances. At the same time, speaker dependency also plays a core role in the conversation dynamic. The combined effect of the sequence-aware information and the speaker-aware information makes the emotion’s dynamic change. However, past works used simple information fusion methods to model the two kinds of information but ignored their interactive influence. Thus, we propose a novel method entitled SIGAT (Speaker-aware Interactive Graph Attention Network) to solve the problem. The core module is a mutual interactive module in which a dual-connection (self-connection and interact-connection) graph attention network is constructed. The advantage of SIGAT is modeling the speaker-aware and sequence-aware information in a unified graph and updating them simultaneously. In this way, we model the interactive influence of them and obtain the final representations, which have richer contextual clues. Experimental results on the four public datasets demonstrate that SIGAT outperforms the state-of-the-art models.
A Fast and Reliable Approach for COVID-19 Detection from CT-Scan Images

Background: COVID-19 is a highly contagious respiratory disease with multiple mutant variants, an asymptotic nature in patients, and with potential to stay undetected in common tests, which makes it deadlier, more transmissible, and harder to detect. Regardless of variants, the COVID-19 infection shows several observable anomalies in the computed tomography (CT) scans of the lungs, even in the early stages of infection. A quick and reliable way of detecting COVID-19 is essential to manage the growing transmission of COVID-19 and save lives. Objective: This study focuses on developing a deep learning model that can be used as an auxiliary decision system to detect COVID-19 from chest CT-scan images quickly and effectively. Methods: In this research, we propose a MobileNet-based transfer learning model to detect COVID-19 in CT-scan images. To test the performance of our proposed model, we collect three publicly available COVID-19 CT-scan datasets and prepare another dataset by combining the collected datasets. We also implement a mobile application using the model trained on the combined dataset, which can be used as an auxiliary decision system for COVID-19 screening in real life. Results: Our proposed model achieves a promising accuracy of 96.14% on the combined dataset and accuracy of 98.75%, 98.54%, and 97.84% respectively in detecting COVID-19 samples on the collected datasets. It also outperforms other transfer learning models while having lower memory consumption, ensuring the best performance in both normal and low-powered, resource-constrained devices. Conclusion: We believe, the promising performance of our proposed method will facilitate its use as an auxiliary decision system to detect COVID-19 patients quickly and reliably. This will allow authorities to take immediate measures to limit COVID-19 transmission to prevent further casualties as well as accelerate the screening for COVID-19 while reducing the workload of medical personnel. Keywords: Auxiliary Decision System, COVID-19, CT Scan, Deep Learning, MobileNet, Transfer Learning
Hydrologic drought characteristics of selected basins in various climate zones of Lebanon

River basins in Lebanon recently have experienced increasing droughts, which has prompted this study to characterize drought temporally and spatially. The study describes and analyzes hydrologic and precipitation conditions in seven river basins, representing most flow directions in various climatic zones. The characteristics of hydrologic and rainfall drought were discussed and analyzed, depending on available data from five climatic zones and fourteen hydrometric stations distributed in the river, allowing for a detailed analysis of drought. The Standardized Precipitation Index ( SPI ) and the Streamflow Drought Index ( SDI ) were calculated at 6-month intervals (first and second 6-months) using the DRINC program. The hydrologic and rainfall drought characteristics maps generated in the GIS platform may help to identify the degree of drought in the study areas. The investigation was carried out by examining the strength of relationships between SDI and SPI using bivariate correlation analysis. The significance of the correlation coefficient is used in this study to decide whether linear relationships between the SPI and SDI occurred in the first and second six months. Calculating the correlation coefficient for these variables based on hydrologic and rainfall data reveals an inconsistent correlation over different periods.
Multi-scale models of whole cells: progress and challenges

Whole-cell modeling is “the ultimate goal” of computational systems biology and “a grand challenge for 21st century” (Tomita, Trends in Biotechnology, 2001, 19(6), 205–10). These complex, highly detailed models account for the activity of every molecule in a cell and serve as comprehensive knowledgebases for the modeled system. Their scope and utility far surpass those of other systems models. In fact, whole-cell models (WCMs) are an amalgam of several types of “system” models. The models are simulated using a hybrid modeling method where the appropriate mathematical methods for each biological process are used to simulate their behavior. Given the complexity of the models, the process of developing and curating these models is labor-intensive and to date only a handful of these models have been developed. While whole-cell models provide valuable and novel biological insights, and to date have identified some novel biological phenomena, their most important contribution has been to highlight the discrepancy between available data and observations that are used for the parametrization and validation of complex biological models. Another realization has been that current whole-cell modeling simulators are slow and to run models that mimic more complex (e.g., multi-cellular) biosystems, those need to be executed in an accelerated fashion on high-performance computing platforms. In this manuscript, we review the progress of whole-cell modeling to date and discuss some of the ways that they can be improved.
Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package, version 2: assessing aerosols, clouds, and aerosol–cloud interactions via field campaign and long-term observations

Abstract. Poor representations of aerosols, clouds, and aerosol–cloud interactions (ACIs) in Earth system models (ESMs) have long been the largest uncertainties in predicting global climate change. Huge efforts have been made to improve the representation of these processes in ESMs, and the key to these efforts is the evaluation of ESM simulations with observations. Most well-established ESM diagnostics packages focus on the climatological features; however, they lack process-level understanding and representations of aerosols, clouds, and ACIs. In this study, we developed the Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package to facilitate the routine evaluation of aerosols, clouds, and ACIs simulated the Energy Exascale Earth System Model (E3SM) from the US Department of Energy (DOE). This paper documents its version 2 functionality (ESMAC Diags v2), which has substantial updates compared with version 1 (Tang et al., 2022a). The simulated aerosol and cloud properties have been extensively compared with in situ and remote-sensing measurements from aircraft, ship, surface, and satellite platforms in ESMAC Diags v2. It currently includes six field campaigns and two permanent sites covering four geographical regions: the eastern North Atlantic, the central US, the northeastern Pacific, and the Southern Ocean. These regions produce frequent liquid- or mixed-phase clouds, with extensive measurements available from the DOE Atmospheric Radiation Measurement user facility and other agencies. ESMAC Diags v2 generates various types of single-variable and multivariable diagnostics, including percentiles, histograms, joint histograms, and heatmaps, to evaluate the model representation of aerosols, clouds, and ACIs. Select examples highlighting the capabilities of ESMAC Diags are shown using E3SM version 2 (E3SMv2). In general, E3SMv2 can reasonably reproduce many observed aerosol and cloud properties, with biases in some variables such as aerosol particle and cloud droplet sizes and number concentrations. The coupling of aerosol and cloud number concentrations may be too strong in E3SMv2, possibly indicating a bias in processes that control aerosol activation. Furthermore, the liquid water path response to a perturbed cloud droplet number concentration behaves differently in E3SMv2 and observations, which warrants further study to improve the cloud microphysics parameterizations in E3SMv2.
Situated Personhood: Insights from Caregivers of Minimally Communicative Individuals

Abstract:For caregivers of minimally communicative individuals, providing support in the absence of clearly meaningful responses is ethically fraught. We conducted a secondary analysis of qualitative data from caregivers of individuals who are minimally communicative, including persons with advanced dementia and individuals in disorders of consciousness. Our analysis led to two central claims: (1) Personhood is a threshold concept that is situated, relational, and dynamic and (2) in circumstances in which personhood is difficult to judge, caregivers can "fill the gap" to reach the threshold through a repertoire of strategies. Because personhood is in part an attribution from others, a situational loss of personhood does not preclude restoration, nor does it eliminate moral status.
Preliminary analysis of the literature on the distribution of wild Musa species using MGIS and DIVA-GIS

The purpose of this work was to initiate a bibliography on wild Musa species and analyse the information (new species, distribution, ecogeographic data, etc.) related to them for integration into the Musa Germplasm Information System (MGIS). This database already contains over 5000 records of accessions held in 16 collections throughout the world. It contains passport data and complementary information such as photographs, morphological characteristics, geographical information. Since data from the literature have not been included in the MGIS database, this report will give a number of recommendations regarding the future entry of this kind of data and its transfer to DIVA-GIS. This software produces maps and can be used to show the geographical distribution of Musaceae in a country, a province and even a region, thus helping researchers decide where to organize future collecting missions. Finally the report will try to identify sources of interesting metadata (cultivation intensity, deforestation, soil degradation, etc.) that can be downloaded for the use with DIVA-GIS. (Author's abstract). [Le but de ce travail etait de commencer une bibliographie sur les especes sauvages de Musa et d'analyser l'information (especes nouvelles, distribution, donnees ecogeographiques, etc.) afin de pouvoir les integrer dans le Systeme d'information du materiel genetique de Musa (MGIS). Cette base de donnees contient deja plus de 5000 donnees sur des accessions maintenues dans 16 collections dans le monde entier. Elle contient des donnees de passeport et des informations complementaires comme des photographies, des caracteristiques morphologiques et des informations geographiques. Puisque des donnees bibliographiques n'ont pas ete incluses dans la base de donnees MGIS, ce rapport donnera un certain nombre de recommandations quant a l'entree future de cette sorte de donnees et son transfert dans DIVA-GIS. Ce logiciel fournit des cartes et peut etre utilise pour visualiser la distribution geographique des Musaceae dans un pays, une province et meme une region, aidant ainsi les chercheurs a savoir ou organiser des missions de collecte. Finalement le rapport tentera d'identifier les sources de metadonnees interessantes (intensite de culture, deforestation , degradation de sol, etc.) telechargeables avec DIVA-GIS. (Resume d'auteur). ]