Miracle-dz/UniFAR-FTUs huggingface dataset:
Prevalence and Determinants of Hypothyroidism in Patients on Routine Hemodialysis in Somalia: A Cross-Sectional Study

Introduction In recent decades, the relationship between thyroid and kidney disease has drawn considerable attention. We aim to assess the prevalence and the determinants of hypothyroidism in hemodialysis patients in Somalia. Materials and Methods This is a cross-sectional study which was conducted in the hemodialysis unit of Mogadishu Somalia Turkish Training and Research Hospital, between June 1 and July, 31 2022. A total of 301 patients who are routinely going to hemodialysis were included in the study. Demographic data including age, gender, and data regarding hemodialysis were extracted from hospital information system (HIS). All participants had their thyroid function test measured before hemodialysis sessions. Results A total of 301 patients were examined. Their ages ranged from 40 to 66 years, with the median age being 54 (IQR= 40–66). Males were 167 (55.5%) compared to females 134 (44.5%). Hypertension was the most common comorbidity among the patients with 137 (45.5%). Diabetic kidney disease was the most common cause of renal failure in 138 patients (45.84%) followed by hypertensive kidney disease 100 (33.22%). The prevalence rate of hypothyroidism in hemodialysis patients in our study was 28%. In hypothyroidism patients 57.8% had subclinical hypothyroidism and 42.2% had overt hypothyroidism. 70.8% of our patients were in euthyroid status. Subclinical hypothyroidism was commonly seen in patients with diabetes, hypertension, and heart disease. We found that increasing age, decreased albumin level were related to higher risk of subclinical hypothyroidism. We also found that increasing creatinine levels were associated with lower risk of overt hypothyroidism. Conclusion The prevalence rate of hypothyroidism in hemodialysis patients was 28%, with 57.8% showing subclinical hypothyroidism and 42.2% overt hypothyroidism. Increased age and low albumin level was associated with the prevalence of subclinical hypothyroidism in hemodialysis patients. Also low creatinine level was observed in overt hypothyroidism patients.
A New Look at the Israeli Cloud Seeding Experiments

Abstract Two statistical experiments, carried out in Israel, appeared for a time to have provided a unique demonstration of the ability of cloud seeding to increase rainfall. In this paper the authors examine the possibility that both experiments were compromised by type I statistical errors (i.e., “lucky draws” or false positives). It is concluded that in the first Israeli experiment a type I statistical error produced the appearance of statistically significant effects of artificial seeding on rainfall 1) in the buffer zone and the center target area, 2) in the coastal region of Israel, a few kilometers downwind of the seeding, and 3) in portions of Lebanon, Syria, and Jordan. Analysis of the second Israeli experiment using the original crossover design produced a null result. However, when the two target areas were evaluated separately, naturally heavier rainfall over a wide region on days when the north target area was seeded produced the appearance of increases in rainfall due to seeding in the north.
Necessary and sufficient condition for absolute stability of neural networks

The main result in this paper is that for a neural circuit of the Hopfield type with a symmetric connection matrix T, the negative semidefiniteness of T is a necessary and sufficient condition for Absolute Stability. The most significant theoretical implication is that the class of neural circuits with a negative semidefinite T is the largest class of circuits that can be employed for embedding and solving optimization problems without the risk of spurious responses. >
Heat transfer over an exponentially stretching continuous surface with suction

Similary solutions of the laminar boundary layer equations describing heat and flow in a quiescent fluid driven by an exponentially stretching surface subject to suction are examined numerically. The direction and amount of heat flow were found to be dependent on the magnitude of " γ " (parameter of temperature) for the same Prandtl number. Nusselt number increases with increasing " γ " and the Prandtl number. The effect of decreasing suction parameter is found to be significant particularly for the Prandtl number.
CORRIGENDA: LOW-DIMENSIONAL REPRESENTATIONS OF QUASI-SIMPLE GROUPS

This paper contains corrections to the tables of low-dimensional representations of quasi-simple groups published in the paper, ‘Lowdimensional representations of quasi-simple groups’, LMS Journal of Computation and Mathematics4 (2001) 22‐63. In our paper ‘Low-dimensional representations of quasi-simple groups’ , we determine all the absolutely irreducible representations of quasi-simple groups of dimension at most 250, excluding those of groups of Lie type in their defining characteristic. Martin Liebeck has kindly pointed out to us three omissions in our tables: the 12- and 13dimensional representations of the group L3.3/, and the 248-dimensional representations of L4.5/ in characteristic 2. When checking our arguments and calculations we realized that in fact all the representations of L3.3/ were missing, as well as the representations of L4.5/ of dimension exceeding 247. The absolutely irreducible representations of L 3.3/ can be found in the modular Atlas [7]. This leads to the first part of Table 1 below.
A note on robust pole assignment for periodic systems

In this note a robust pole assignment algorithm is proposed for linear periodic discrete-time systems with time-varying dimensions of the state and/or input spaces. The algorithm deduces a periodic state feedback law by the minimization of the condition numbers of the eigenvector matrices of the closed-loop system. Numerical examples are provided to show the performances of the algorithm.
X-rays from the magnetic white dwarf PG 1658 + 441

X-ray emission has been detected from PG 1658 + 441, a hot, isolated, magnetic white dwarf. The source was first detected in an Einstein IPC observation and was later identified in an Exosat channel multiplier array observation. Both imaging observations were motivated by an attempt to find the optical counterpart to the HEAO 1 soft X-ray source H1659 + 44. Spectral analysis, however, indicates that H1659 + 44 and PG 1658 + 441 are unrelated. The broad-band spectrum of this DA white dwarf can be explained as emission from a homogeneous, high-gravity, pure hydrogen atmosphere with a temperature near 28,000 K. The observations of PG 1658 + 441 support the suggestion that a correlation exists between temperature and helium abundance in white dwarf atmospheres.
An Investigation of Teachers’ Perceptions of School Competitiveness and Organizational Work Environment in a Rural Area

Abstract School choice is expected to generate competition and thereby lead to organizational improvements. Using teachers’ original survey responses, this study uses the market culture within the competing values framework and finds substantial variation in how rural schoolteachers perceive competitive pressure and school climate. When we restricted our analysis to teachers from low-income schools, the relationship between competition and work environment is amplified for some organizational climate variables. Findings, which suggest that higher levels of perceived competition are associated with somewhat higher morale and stronger organizational cultures, are important for school leaders and policymakers.
Breaking Barriers in Eye Treatment: Polymeric Nano-Based Drug-Delivery System for Anterior Segment Diseases and Glaucoma

The eye has anatomical structures that function as robust static and dynamic barriers, limiting the penetration, residence time, and bioavailability of medications administered topically. The development of polymeric nano-based drug-delivery systems (DDS) could be the solution to these challenges: it can pass through ocular barriers, offering higher bioavailability of administered drugs to targeted tissues that are otherwise inaccessible; it can stay in ocular tissues for longer periods of time, requiring fewer drug administrations; and it can be made up of polymers that are biodegradable and nano-sized, minimizing the undesirable effects of the administered molecules. Therefore, therapeutic innovations in polymeric nano-based DDS have been widely explored for ophthalmic drug-delivery applications. In this review, we will give a comprehensive overview of polymeric nano-based drug-delivery systems (DDS) used in the treatment of ocular diseases. We will then examine the current therapeutic challenges of various ocular diseases and analyze how different types of biopolymers can potentially enhance our therapeutic options. A literature review of the preclinical and clinical studies published between 2017 and 2022 was conducted. Thanks to the advances in polymer science, the ocular DDS has rapidly evolved, showing great promise to help clinicians better manage patients.
Complete chloroplast and mitochondrial genomes of Ditrichum rhynchostegium Kindb. (Ditrichaceae, Bryophyta)

Abstract The moss family Pottiaceae is one of the most diverse lineages of the subclass Dicranidae (haplolepideous mosses). Nevertheless, the phylogenetic relationships of Pottiaceae with other Dicranidae families remain unclear. To better understand the ancestral genomic structure and evolution of the Pottiaceae, herein, we present the chloroplast and mitochondrial genomes of Ditrichum rhynchostegium (Ditrichaceae, Bryophyta). The chloroplast genome is 124,628 bp long and displayed a circular structure composed of a large single-copy region, a small single-copy region, and a pair of inverted repeats. It has 118 genes, including 82 protein-coding genes, 32 tRNA genes, and four rRNA genes. The mitochondrial genome is 106,246 bp long and has a circular structure. It contains 67 genes, including 40 protein-coding genes, 24 tRNA genes, and three rRNA genes. Phylogenetic trees based on the coding sequences strongly support the sister relationship of D. rhynchostegium with all Pottiaceous accessions, and the dextrosely arranged operculum cells suggest its affinity for Pottiaceae. This study also demonstrates that long-read sequencing employing the Nanopore platform facilitates the repair of unassembled or misassembled organellar genomic regions.
Comparison of Probabilistic Statistical Forecast and Trend Adjustment Methods for North American Seasonal Temperatures

AbstractThe three multivariate statistical methods of canonical correlation analysis, maximum covariance analysis, and redundancy analysis are compared with respect to their probabilistic accuracy for seasonal forecasts of gridded North American temperatures. Derivation of forecast error covariance matrices for the methods allows a probabilistic formulation for the forecasts, assuming Gaussian predictive distributions. The three methods perform similarly with respect to probabilistic forecast accuracy as reflected by the ranked probability score, although maximum covariance analysis may be preferred because of its slightly better forecast skill and calibration. In each case the forecast accuracy for North American seasonal temperatures compares favorably to results from previously published studies. In addition, two alternative approaches are compared for alleviating the cold biases in the forecasts that derive from ongoing climate warming. Adding lagging 15-yr means to forecast temperature anomalies impr.
A comparative experimental study of geocell and geogrid-reinforced highway base layers under repeated loads

This paper presents experimental results of laboratory model tests of geosynthetic reinforced highway base layers subjected to repeated loads. The potential benefit of geocell and geogrid, when used in the base layer as a reinforcement material, was examined and assessed by performance indicators including total, permanent (plastic), and elastic (resilient) deformation, traffic benefit ratio (TBR), rut depth reduction (RDR), percentage of elastic deformation, and resilient modulus (MR ). In the light of the results of this study, geocell and geogrid-reinforced bases outperform the unreinforced base in terms of elastic and permanent deformations. Further experimental results reveal that although the thickness of the base layer was decreased to a rate of 33%, geocell and geogrid enable a considerable reduction in the rut depth at an approximate rate of 21% and 13%, respectively. Moreover, when the thickness of the base layer remains constant, about 48% to 43% reduction in the rut depth was provided by geocell and geogrid reinforcement.
Association and prediction of red blood cell distribution width to albumin ratio in all-cause mortality of acute kidney injury in critically ill patients

Aim The progression of acute kidney injury (AKI) might be associated with systemic inflammation. Our study aims to explore the association and predictive value of the red blood cell distribution width (RDW) to human serum albumin (ALB) ratio (RDW/ALB ratio), an inflammation-related indicator, in the risk of all-cause mortality and renal replacement therapy (RRT) in AKI patients admitted in intensive care units (ICU). Methods A retrospective cohort study was designed, and data were extracted from the Medical Information Mart for Intensive Care III (MIMIC-III). The primary outcome was the risk of all-cause mortality (1-month, 3-month, and 12-month), and the secondary outcome was the risk of RRT. The association between the RDW/ALB ratio and the risk of all-cause mortality and RRT was assessed using the Cox regression analysis, with results shown as hazard ratio (HR) and 95% confidence intervals (CIs). The relationship between the RDW/ALB ratio and crude probability of all-cause mortality or RRT was assessed using restricted cubic splines (RCS). The concordance index (C-index) was used to assess the discrimination of the prediction model. Results A total of 13,856 patients were included in our study. In the fully adjusted Cox regression model, we found that a high RDW/ALB ratio was associated with an increased risk of 1-month, 3-month, and 12-month all-cause mortality and RRT (all p < 0.05). Moreover, RCS curves showed the linear relationship between the RDW/ALB ratio and the probability of all-cause mortality and RRT, and the probability was elevated with the increase of the ratio. In addition, the RDW/ALB ratio showed a good predictive performance in the risk of 1-month all-cause mortality, 3-month all-cause mortality, 12-month all-cause mortality, and RRT, with a C-index of 0.728 (95%CI: 0.719–0.737), 0.728 (95%CI: 0.721–0.735), 0.719 (95%CI: 0.713–0.725), and 0.883 (95%CI: 0.876–0.890), respectively. Conclusion The RDW/ALB ratio performed well to predict the risk of all-cause mortality and RRT in critically ill patients with AKI, indicating that this combined inflammatory indicator might be effective in clinical practice.
IoT-Enabled WBAN and Machine Learning for Speech Emotion Recognition in Patients

Internet of things (IoT)-enabled wireless body area network (WBAN) is an emerging technology that combines medical devices, wireless devices, and non-medical devices for healthcare management applications. Speech emotion recognition (SER) is an active research field in the healthcare domain and machine learning. It is a technique that can be used to automatically identify speakers’ emotions from their speech. However, the SER system, especially in the healthcare domain, is confronted with a few challenges. For example, low prediction accuracy, high computational complexity, delay in real-time prediction, and how to identify appropriate features from speech. Motivated by these research gaps, we proposed an emotion-aware IoT-enabled WBAN system within the healthcare framework where data processing and long-range data transmissions are performed by an edge AI system for real-time prediction of patients’ speech emotions as well as to capture the changes in emotions before and after treatment. Additionally, we investigated the effectiveness of different machine learning and deep learning algorithms in terms of performance classification, feature extraction methods, and normalization methods. We developed a hybrid deep learning model, i.e., convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM), and a regularized CNN model. We combined the models with different optimization strategies and regularization techniques to improve the prediction accuracy, reduce generalization error, and reduce the computational complexity of the neural networks in terms of their computational time, power, and space. Different experiments were performed to check the efficiency and effectiveness of the proposed machine learning and deep learning algorithms. The proposed models are compared with a related existing model for evaluation and validation using standard performance metrics such as prediction accuracy, precision, recall, F1 score, confusion matrix, and the differences between the actual and predicted values. The experimental results proved that one of the proposed models outperformed the existing model with an accuracy of about 98%.
How Rare Are Argonautoidea Octopuses in the Mediterranean? New Data from Stranding Events, Stomach Contents and Genetics

Simple Summary This study reports the results of a multidisciplinary research on Mediterranean pelagic octopods belonging to the species Argonauta argo, Ocythoe tuberculata, Tremoctopus gracilis and Tremoctopus violaceus for the first time. The study area was the Strait of Messina and southern Tyrrhenian Sea. We used information from stranding events, accidental fishing catches and stomach contents of large predators (albacore, bluefin tuna, swordfish and Mediterranean spearfish). We analysed 47 fresh octopods, including exceptional records of rare males, and 330 individuals found in the stomachs of 800 predators. The analysis of genetic aspects was used to provide further details on the life and identity of these species. Abstract The present paper represents the first all-encompassing study on all Mediterranean holopelagic octopods belonging to Argonautoidea (Argonauta argo, Ocythoe tuberculata, Tremoctopus gracilis, Tremoctopus violaceus). Argonautoidea octopuses were collected by different sampling methods in the Strait of Messina and southern Tyrrhenian Sea. The aim of this paper was to improve knowledge, using information from different data sources, such as the study of stranded individuals or accidental caught specimens, as well as the analysis of stomach content of large pelagic fishes. Moreover, we investigated their taxonomic profile through the amplification of the mitochondrial cytochrome c oxidase subunit I (COI). Overall, 47 fresh holopelagic octopods were collected, including valuable records of rare males. Moreover, 330 Argonautoidea octopuses were found in the stomachs of 800 predators. The results provided evidence that these cephalopods are more abundant than thought in the past. The molecular approach supported the ecological results with interesting insights. The similarity-based identifications and tree-based methods indicated that three females could be identified as Tremoctopus violaceus in agreement with their morphological classifications. The sequences obtained from the two T. gracilis individuals were clustered with the sequences of Tremoctopus violaceus from the Gulf of Mexico and were differentiated from the sequences attributed to T. gracilis and T. robsoni. The study represents a valuable contribution to the genetic characterization of Mediterranean individuals of the genera Tremoctopus, Argonauta and Ocythoe.
Neural blind deconvolution with Poisson data

Blind Deconvolution problem is a challenging task in several scientific imaging domains, such as Microscopy, Medicine and Astronomy. The Point Spread Function inducing the blur effect on the acquired image can be solely approximately known, or just a mathematical model may be available. Blind deconvolution aims to reconstruct the image when only the recorded data is available. In the last years, among the standard variational approaches, Deep Learning techniques have gained interest thanks to their impressive performances. The Deep Image Prior framework has been employed for solving this task, giving rise to the so-called neural blind deconvolution (NBD), where the unknown blur and image are estimated via two different neural networks. In this paper, we consider microscopy images, where the predominant noise is of Poisson type, hence signal-dependent: this leads to consider the generalized Kullback–Leibler as loss function and to couple it with regularization terms on both the blur operator and on the image. Furthermore, we propose to modify the standard NBD formulation problem, by including for the blur kernel an upper bound which depends on the optical instrument. A numerical solution is obtained by an alternating Proximal Gradient Descent-Ascent procedure, which results in the Double Deep Image Prior for Poisson noise algorithm. We evaluate the proposed strategy on both synthetic and real-world images, achieving promising results and proving that the correct choice of the loss and regularization functions strongly depends on the application at hand.
An Investigation of Olfactory-Enhanced Video on EEG-Based Emotion Recognition

Collecting emotional physiological signals is significant in building affective Human-Computer Interactions (HCI). However, how to evoke subjects’ emotions efficiently in EEG-related emotional experiments is still a challenge. In this work, we developed a novel experimental paradigm that allows odors dynamically participate in different stages of video-evoked emotions, to investigate the efficiency of olfactory-enhanced videos in inducing subjects’ emotions; According to the period that the odors participated in, the stimuli were divided into four patterns, i.e., the olfactory-enhanced video in early/later stimulus periods (OVEP/OVLP), and the traditional videos in early/later stimulus periods (TVEP/TVLP). The differential entropy (DE) feature and four classifiers were employed to test the efficiency of emotion recognition. The best average accuracies of the OVEP, OVLP, TVEP, and TVLP were 50.54%, 51.49%, 40.22%, and 57.55%, respectively. The experimental results indicated that the OVEP significantly outperformed the TVEP on classification performance, while there was no significant difference between the OVLP and TVLP. Besides, olfactory-enhanced videos achieved higher efficiency in evoking negative emotions than traditional videos. Moreover, we found that the neural patterns in response to emotions under different stimulus methods were stable, and for Fp1, FP2, and F7, there existed significant differences in whether adopt the odors.