Miracle-dz/UniFAR-FTUs huggingface dataset:
Suicide Risk Screening and Assessment before and after the COVID-19 Pandemic in New Inmates

(1) Background: Suicide is the main cause of death in Italian prisons. The largest number of inmates who killed themselves was recorded during three years of the COVID-19 pandemic. This study aimed to explore psychosocial risk factors for suicide among inmates incarcerated before and after the onset of COVID-19. (2) Methods: At prison reception, inmates underwent clinical interviews and were assessed using the Blaauw Scale and Suicide Assessment Scale. Psychological distress, measured by the Symptom Checklist-90-R, was compared between inmates admitted before and after COVID-19. Regression analyses were run to examine psychosocial vulnerabilities associated with suicidal intent in newly incarcerated individuals at risk of suicide. (3) Results: Among the 2098 newly admitted inmates (93.7% male) aged 18 to 87 years (M = 39.93; SD = 12.04), 1347 met the criteria for suicide risk, and 98 exhibited high suicidal intent. Inmates who entered prison after the onset of COVID-19 were older and had fewer social relationships. They had a higher prevalence of recidivism and substance abuse, along with elevated levels of psychological distress. An increase in perceived loss of control, anergia, obsessive-compulsive symptoms, phobic anxiety, and paranoid ideation emerged as the factors most strongly associated with high suicidal intent. (4) Conclusions: These findings support the value of psychosocial screening in promptly identifying inmates at risk of suicide, enabling the implementation of targeted, multi-professional interventions. Future research should replicate these results, with a focus on longitudinal studies that monitor the same inmates throughout their incarceration period.
Analysis of Factors Influencing Academic Performance in Primary School National Examination in Tanzania: A Case of Kilosa District

This paper examined the factors influencing academic performance in primary schools in the Kilosa district, Mrogoro region in Tanzania. The study employed a qualitative research approach through a cross-sectional research design. About 106 participants were involved including five (5) head teachers (from five schools), one (1)district education officer, one (1)ward education officer, 30 primary school teachers, and 69 students from the five selected primary schools. Data were collected through interviews and focus group discussions. The collected data were qualitatively analyzed. The study shows that poor academic performance in primary schools in the Kilosa district was first, contributed by a learning environment characterized by the poor quality of school infrastructures, long distance to schools, few desks, and poor teachers' houses. The second was a lack of motivation and the last one was a lack of parental involvement. The findings of this study add to the body of literature on academic performance and learning environment. It also underlines the importance of creating favourable working conditions for both teachers and students that fosters high morale among workers and students. This study also broadens our understanding of the importance of government intervention as part of the strategies for improving teaching and learning environments to improve academic performance.
Overnight Index Swap Market-Based Measures of Monetary Policy Expectations

I assess the use of overnight indexed swap (OIS) rates as measures of monetary policy expectations. I find that one to twelve-month US OIS rates provide measures of investors’ interest rate expectations that are comparable to those from corresponding-horizon federal funds futures rates, which have regularly been used as financial market-based measures of US interest rate expectations. More generally, I find that one to 24-month US, euro-zone and Japanese OIS rates and one to 18-month UK OIS rates tend to accurately measure expectations of future short-term interest rates. Motivated by these results, researchers can look to OIS rates as globally comparable measures of monetary policy expectations.
Functional connectivity of the nucleus accumbens predicts clinical course in treated and non-responder adult ADHD

Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental condition that often persists into adulthood, contributing to a challenging trajectory characterised by increased rates of psychiatric comorbidity. Contrary to previous assumptions, the clinical course of ADHD in adulthood is characterised by dynamic changes influenced by stimulant treatment. To improve the precision of treatment, the identification of a predictive neuroimaging biomarker would be of great clinical importance. In this study, we explore the potential of seed-based functional connectivity (FC) as a predictive tool for assessing the clinical course of ADHD symptoms. We conducted a longitudinal follow-up study of 54 adult ADHD patients who underwent magnetic resonance imaging (MRI) using a 3 Tesla scanner. All patients received stimulant treatment during an initial run-in period. After an average of three years, only subjective responders continued treatment (n=34), while subjective non-responders discontinued medication (n=20). We reassessed patients after three years of treatment to 1) evaluate the prediction of individual outcome by baseline fMRI and 2) to investigate differences in prediction by baseline fMRI depending on long-term treatment vs. discontinuation. Our investigation focused on determining whether a relationship could be established between resting-state FC of the nucleus accumbens (NAc) and the trajectory of symptom development, as well as identifying possible differences in FC between individuals who had been on long-term stimulant treatment and those who had not used stimulants at the time of follow-up. In general, reduced FC between the NAc and the default mode network (DMN) was associated with initially higher symptom burden, whereas patterns of improvement correlated with reduced FC between the NAc and the salience network (SN). Comparatively, higher FC between the NAc and the SN was associated with better symptom outcomes in patients receiving long-term stimulant medication, whereas lower FC between the NAc and the SN was correlated with a more favourable prognosis in non-responders. Our prospective fMRI study suggests that functional connectivity between the dopaminergic reward circuitry and the SN, especially the insula, is predictive of better ADHD symptom outcomes. This work highlights the potential of dopaminergic functional connectivity as a prognostic factor in ADHD. While future research with larger samples and longer follow-up is warranted, our study highlights the role of the NAc in the prognosis of ADHD.
The Physiological Occlusion of the Central Canal May Be a Prerequisite for Syringomyelia Formation

Objective Syringomyelia is a common central nervous system disease characterized by the dilation of the central canal (CC). Regarding the pathogenesis of syringomyelia, cerebrospinal fluid (CSF) circulation obstruction in the subarachnoid space (SAS) of the spinal cord has been widely accepted. However, clinical and animal studies on obstructing the CSF in SAS failed to form syringomyelia, challenging the theory of SAS obstruction. The precise pathogenesis remains unknown. Methods We utilized an extradural compression rat model to investigate the pathogenesis underlying syringomyelia. Magnetic resonance imaging enabled detection of syringomyelia formation. To assess CSF flow within the SAS, Evans blue was infused into the cisterna magna. Histological analysis allowed morphological examination of the CC. Furthermore, CSF flow through the CC was traced using Ovalbumin Alexa-Flour 647 conjugate (OAF-647). Scanning electron microscopy (SEM) enabled visualization of ependymal cilia. Results The findings showed that the dura mater below the compression segment exhibited lighter coloration relative to the region above the compression, indicative of partial obstruction within the SAS. However, the degree of SAS occlusion did not significantly differ between syringomyelia (SM-Y group) and those without (SM-N group). Intriguingly, hematoxylin and eosin staining and CSF tracing revealed occlusion of the CC accompanied by reduced CSF flow in the SM-Y group compared to SM-N and control groups. SEM images uncovered impairment of ependymal cilia inside the syringomyelia. Conclusion CC occlusion may represent a physiological prerequisite for syringomyelia formation, while SAS obstruction serves to initiate disease onset. The impairment of ependymal cilia appears to facilitate progression of syringomyelia.
Deep causal speech enhancement and recognition using efficient long-short term memory Recurrent Neural Network

Long short-term memory (LSTM) has been effectively used to represent sequential data in recent years. However, LSTM still struggles with capturing the long-term temporal dependencies. In this paper, we propose an hourglass-shaped LSTM that is able to capture long-term temporal correlations by reducing the feature resolutions without data loss. We have used skip connections in non-adjacent layers to avoid gradient decay. In addition, an attention process is incorporated into skip connections to emphasize the essential spectral features and spectral regions. The proposed LSTM model is applied to speech enhancement and recognition applications. The proposed LSTM model uses no future information, resulting in a causal system suitable for real-time processing. The combined spectral feature sets are used to train the LSTM model for improved performance. Using the proposed model, the ideal ratio mask (IRM) is estimated as a training objective. The experimental evaluations using short-time objective intelligibility (STOI) and perceptual evaluation of speech quality (PESQ) have demonstrated that the proposed model with robust feature representation obtained higher speech intelligibility and perceptual quality. With the TIMIT, LibriSpeech, and VoiceBank datasets, the proposed model improved STOI by 16.21%, 16.41%, and 18.33% over noisy speech, whereas PESQ is improved by 31.1%, 32.9%, and 32%. In seen and unseen noisy situations, the proposed model outperformed existing deep neural networks (DNNs), including baseline LSTM, feedforward neural network (FDNN), convolutional neural network (CNN), and generative adversarial network (GAN). With the Kaldi toolkit for automated speech recognition (ASR), the proposed model significantly reduced the word error rates (WERs) and reached an average WER of 15.13% in noisy backgrounds.
Pressure-induced tuning of physical properties in high-throughput metal halide MSn2Br5 (M = K, Cs) perovskites for optoelectronic applications

The physical properties of the ferromagnetic oxide perovskites MSn2Br5 (M = K, Cs) were thoroughly examined using the GGA + PBE formalism of density functional theory. The investigation includes a comprehensive characterization of these materials under hydrostatic pressures ranging up to 25 GPa. Our work represents the first theoretical framework for exploring the behavior of MSn2Br5 (M = K, Cs) under pressure, providing valuable insights into their properties. To ensure the thermodynamic and mechanical stability of the studied compounds, we justified their stability through the analysis of formation energy and Born stability criteria. Furthermore, we conducted a thorough examination of the mechanical features of MSn2Br5 (M = K, Cs) based on various parameters, such as elastic constants, elastic moduli, the Kleinman parameter, the machinability index, and the Vickers hardness. Pugh's ratio and Poisson's ratio data show a ductile behavior for both compounds under stress. Moreover, our analysis of the refractive index suggests that both materials hold significant potential as candidates for ultrahigh-density optical data storage devices, particularly when subjected to appropriate laser irradiation. This finding opens up exciting possibilities for utilizing MSn2Br5 (M = K, Cs) in advanced optical technologies.
Where do diaspores come from? Reverse wind modelling unveils plant colonization trajectories

In alpine habitats, wind is the predominant dispersal vector of diaspores (seeds and spores). The wind flow field in mountain areas depends on the interaction of wind with topography which creates very complex patterns for both wind directions and speeds. Most alpine species utilize wind transport for diaspore dispersal, and more than 90% are anemochorous. The transport of diaspores is to date considered a forward (ahead in time) problem, i.e. from actual diaspore locations to future ones. I argue here that, using appropriate reverse mathematical modelling, the problem can be reversed: starting from actual locations of plants and diaspores, one can evince the trajectories that led to actual positions. So doing, one can reconstruct the trajectories followed by plant species to reach actual niches. A particular application of this approach is the individuation of corridors followed by exotic plant species. The ad-hoc software Wind-Lab has been realized which incorporates both forward and backward wind modelling. The model described here might be of importance in geobotany, climatic ecology and plant conservation biology.
High-altitude adaptation is accompanied by strong signatures of purifying selection in the mitochondrial genomes of three Andean waterfowl

Evidence from a variety of organisms points to convergent evolution on the mitochondria associated with a physiological response to oxygen deprivation or temperature stress, including mechanisms for high-altitude adaptation. Here, we examine whether demography and/or selection explains standing mitogenome nucleotide diversity in high-altitude adapted populations of three Andean waterfowl species: yellow-billed pintail (Anas georgica), speckled teal (Anas flavirostris), and cinnamon teal (Spatula cyanoptera). We compared a total of 60 mitogenomes from each of these three duck species (n = 20 per species) across low and high altitudes and tested whether part(s) or all of the mitogenome exhibited expected signatures of purifying selection within the high-altitude populations of these species. Historical effective population sizes (Ne) were inferred to be similar between high- and low-altitude populations of each species, suggesting that selection rather than genetic drift best explains the reduced genetic variation found in mitochondrial genes of high-altitude populations compared to low-altitude populations of the same species. Specifically, we provide evidence that establishment of these three Andean waterfowl species in the high-altitude environment, coincided at least in part with a persistent pattern of negative purifying selection acting on oxidative phosphorylation (OXPHOS) function of the mitochondria. Our results further reveal that the extent of gene-specific purifying selection has been greatest in the speckled teal, the species with the longest history of high-altitude occupancy.
Proposal for the precise definition of mean values of gravity field quantities

A mathematical definition of a mean value is the mean of values of a function or of a functional applied on a function, f R R n :Ω⊆ → The mean must be taken over a continous or discrete, bounded subset of Ω . The subset must have dimension less than or equal to n, which for the gravity field are 4 for time dependent quantities and otherwise 3. See for example Heiskanen and Moritz (1967, eq. (7-76)).
SUSTAINABLE DEVELOPMENT THROUGH THE ISLAMIC INSURANCE SYSTEM IN SUDAN

Several Islamic insurance and solidarity companies have been established since 1979; first in Sudan and later in Saudi Arabia, and then in various other Islamic countries. There are currently about 200 companies of Islamic insurance in all parts of the world, spreading over the Islamic world. This number indicates that the Islamic insurance industry has begun to prove and improve itself that is a strong competitor to traditional insurance industry.This paper evaluates and analyses the challenges on several issues related to Islamic insurance in Sudan for the period 1979-2011. This paper also covers semistructured interviewed at the preliminary in order to address the research questions, and hypotheses of this research. A planned questionnaire to find out the sustainability and challenges facing Islamic insurance in Sudan has been set. Smart PLS has been used to evaluate and analyze the result of sustainability in Sudan. A brief content analysis of Islamic insurance systems for sustainability was discussed to examine its challenges for research in the future. This research found that the link between Sudanese customers perception and his satisfaction with using Islamic model as in Sudan. This paper concludes with a discussion on the significant light of sustainable development in Islamic insurance industry in Sudan and Muslim countriesneeds to propagate the research and publication in the areas of Islamic economics and Islamic management.
Mapping inland water carbon content with Landsat 8 data

ABSTRACT Landsat 8 is the first Earth observation satellite with sufficient radiometric and spatial resolution to allow global mapping of lake CDOM and DOC (coloured dissolved organic matter and dissolved organic carbon, respectively) content. Landsat 8 is a multispectral sensor however, the number of potentially usable band ratios, or more sophisticated indices, is limited. In order to test the suitability of the ratio most commonly used in lake carbon content mapping, the green–red band ratio, we carried out fieldwork in Estonian and Brazilian lakes. Several atmospheric correction methods were also tested in order to use image data where the image-to-image variability due to illumination conditions would be minimal. None of the four atmospheric correction methods tested, produced reflectance spectra that matched well with in situ measured reflectance. Nevertheless, the green–red band ratio calculated from the reflectance data was in correlation with measured CDOM values. In situ data show that there is a strong correlation between CDOM and DOC concentrations in Estonian and Brazilian lakes. Thus, mapping the global CDOM and DOC content from Landsat 8 is plausible but more data from different parts of the world are needed before decisions can be made about the accuracy of such global estimation.
Dynamic Soil Properties and Site Coefficients for Aseismic Building Design in Some Typical Soil Deposits of the Marche Region, Italy

bstract— Although in Central Italy seismicity is lly moderate and the maximum expected local Richter tudes are about 6-6.5, in the past many urban ents and villages have experienced, even during low ity earthquakes, very severe damage, which can be ted to the sharp topography or the presence of thick ts or the particular dynamic properties of the soils. fore, in order to provide new updated guidelines for c building design, great research effort has been aimed quantification of site responses in various Italian ical centres over the latest years. Moreover, since ode 8 (EC8) will be adopted within a short period in ies of the European Union, these studies have also aimed at controlling reliability of EC8 spectra for sites. This paper describes the research developed for fects evaluation at Offida, a historical centre in The e with important monuments and environmental ge. A specific program of seismological investigations, ting in measuring low amplitude earthquakes and tremors, and geotechnical testing, including boreholes, ic field and laboratory tests, was carried out. A y of methods were utilised and compared, considering nt earthquake scenarios and ground motions. The ed spectra were finally compared with those proposed rocode 8.
Longitudinal symptom profile of palliative care patients receiving a nurse-led end-of-life (PEACH) programme to support preference to die at home

Objectives Tailored models of home-based palliative care aimed to support death at home, should also ensure optimal symptom control. This study aimed to explore symptom occurrence and distress over time in Palliative Extended And Care at Home (PEACH) model of care recipients. Design This was a prospective cohort study. Setting and participants Participants were consecutive recipients of the PEACH rapid response nurse-led model of care in metropolitan Sydney (December 2013–January 2017) who were in the last weeks of life with a terminal or deteriorating phase of illness and had a preference to be cared or die at home. Outcome measures Deidentified data including sociodemographic and clinical characteristics, and symptom distress scores (Symptom Assessment Score) were collected at each clinical visit. Descriptive statistics and forward selection logistic regression analysis were used to explore influence of symptom distress levels on mode of separation ((1) died at home while still receiving a PEACH package, (2) admitted to a hospital or an inpatient palliative care unit or (3) discharged from the package (alive and no longer requiring PEACH)) across four symptom distress level categories. Results 1754 consecutive clients received a PEACH package (mean age 70 years, 55% male). 75.7% (n=1327) had a home death, 13.5% (n=237) were admitted and 10.8% (n=190) were still alive and residing at home when the package ceased. Mean symptom distress scores improved from baseline to final scores in the three groups (p<0.0001). The frequency of no symptom distress score (0) category was higher in the home death group. Higher scores for nausea, fatigue, insomnia and bowel problems were independent predictors of who was admitted. Conclusion Tailored home-based palliative care models to meet preference to die at home, achieve this while maintaining symptom control. A focus on particular symptoms may further optimise these models of care.
Prognostic value of longitudinal HbA1c variability in predicting the development of diabetic sensorimotor polyneuropathy among patients with type 2 diabetes mellitus: A prospective cohort observational study

ABSTRACT Aims/Introduction This prospective cohort study aims to identify the optimal measure of glycated hemoglobin (HbA1c) variability and to explore its relationship with the development of new diabetic sensorimotor polyneuropathy (DSPN) in individuals with type 2 diabetes mellitus, building upon previous cross‐sectional studies that highlighted a significant association between HbA1c visit‐to‐visit variability and DSPN. Materials and Methods In a prospective study, 321 participants diagnosed with type 2 diabetes mellitus underwent comprehensive clinical assessments, neurophysiologic studies, and laboratory evaluations at enrollment and follow‐up. Various indices, including HbA1c standard deviation (HbA1c SD), coefficient of variation (HbA1c CV), HbA1c change score (HbA1c HVS), and average real variability (HbA1c ARV), were employed to calculate the visit‐to‐visit variability HbA1c based on 3 month intervals. The investigation focused on examining the associations between these indices and the development of new DSPN. Results The average follow‐up duration was 16.9 ± 6.9 months. The Cox proportional hazards model identified age (P = 0.001), diabetes duration (P = 0.024), and HbA1C ARV (P = 0.031) as the sole factors associated with the development of new DSPN. Furthermore, the cumulative risk of developing DSPN over 1 year demonstrated a significant association with HbA1C ARV (P = 0.03, log‐rank test). Conclusions Apart from age and diabetes duration, HbA1c variability emerged as a robust predictor for the occurrence of new DSPN. Among the various measures of HbA1c variability evaluated, HbA1c ARV demonstrated the highest potential as a reliable indicator for anticipating the onset of new DSPN.