Miracle-dz/UniFAR-FTUs huggingface dataset:
Individual, Social and Institutional Vulnerabilities in the Premature Infant Care at Home

The prematurity carries some difficulties for families during the preterm infant hospitalization, as well as, after hospital discharge. In this context, is required a specific knowledge about the preterm biological characteristics, family’s life conditions, health care, and social context. This study aims to analyze parent’s experiences on daily home care for preterm infants focusing on individual, social and institutional vulnerabilities. Descriptive qualitative study was developed through the hermeneutic perspective approach, in South of Brazil with six families, who had babies discharged from Neonatal Intensive Care Unit. Non-structured interviews were recorded in the home visit with 12 participants (parents) and genogram and ecomap were applied. Emerged as core theme: Parents’ feelings related to preterm care at home and their interaction with health services. During the first month after discharge, parents were emotionally vulnerable. There is a lack of connection between parents and Primary Health Care, what increases institutional vulnerability. After discharge, parents have experienced an individual, social, and institutional vulnerability. To minimize their institutional vulnerability, the health services need to be organized in a network offering qualified follow-up. Applying the Health Policy to care for premature infant, consequently, reducing the individual vulnerability and recognize social vulnerabilities related to premature infant care.
An Investigation of a Multidimensional CNN Combined with an Attention Mechanism Model to Resolve Small-Sample Problems in Hyperspectral Image Classification

The convolutional neural network (CNN) method has been widely used in the classification of hyperspectral images (HSIs). However, the efficiency and accuracy of the HSI classification are inevitably degraded when small samples are available. This study proposes a multidimensional CNN model named MDAN, which is constructed with an attention mechanism, to achieve an ideal classification performance of CNN within the framework of few-shot learning. In this model, a three-dimensional (3D) convolutional layer is carried out for obtaining spatial–spectral features from the 3D volumetric data of HSI. Subsequently, the two-dimensional (2D) and one-dimensional (1D) convolutional layers further learn spatial and spectral features efficiently at an abstract level. Based on the most widely used convolutional block attention module (CBAM), this study investigates a convolutional block self-attention module (CBSM) to improve accuracy by changing the connection ways of attention blocks. The CBSM model is used with the 2D convolutional layer for better performance of HSI classification purposes. The MDAN model is applied for classification applications using HSI, and its performance is evaluated by comparing the results with the support vector machine (SVM), 2D CNN, 3D CNN, 3D–2D–1D CNN, and CBAM. The findings of this study indicate that classification results from the MADN model show overall classification accuracies of 97.34%, 96.43%, and 92.23% for Salinas, WHU-Hi-HanChuan, and Pavia University datasets, respectively, when only 1% HSI data were used for training. The training and testing times of the MDAN model are close to those of the 3D–2D–1D CNN, which has the highest efficiency among all comparative CNN models. The attention model CBSM is introduced into MDAN, which achieves an overall accuracy of about 1% higher than that of the CBAM model. The performance of the two proposed methods is superior to the other models in terms of both efficiency and accuracy. The results show that the combination of multidimensional CNNs and attention mechanisms has the best ability for small-sample problems in HSI classification.
Standard/Handbook for Multipactor Breakdown Prevention in Spacecraft Components

Abstract : This document is intended to serve as a standard and handbook for the prevention of multipactor and ionization breakdown in spacecraft components and systems. The document provides minimum requirements for risk definition, system analysis, and component analysis and test. Supporting documentation describes proper design, analysis, and test guidelines while also providing the requirements for defining the proper system engineering to identify RF breakdown risks within susceptible components. The document framework is based on defining worst-case parameters as general inputs to analysis or test criteria for all components within the RF system. Using hardware-specific values, these worst-case parameters are defined separately from margin requirements. With properly defined worst-case conditions, the document addresses required margins for analysis and test for multiple devices categories. Subsequent sections provide minimum verification requirements to demonstrate the margin recommendations for both analysis and test. Applicability of different analysis and test methods to the device class categories is provided, with special cases and considerations. Multiple appendices based on state-of-the-art industry best practices are also provided as guidelines to aid manufacturers and contractors. Typical approaches including examples for both design and test are provided. A reference geometry is described along with corresponding analysis and test data. This information can be used as a benchmark standard, such that component vendors and manufacturers can have a standard example for RF breakdown.
The Biosynthesis and Transport of Ophiobolins in Aspergillus ustus 094102

Ophiobolins are a group of sesterterpenoids with a 5-8-5 tricyclic skeleton. They exhibit a significant cytotoxicity and present potential medicinal prospects. However, the biosynthesis and transport mechanisms of these valuable compounds have not been fully resolved. Herein, based on a transcriptome analysis, gene inactivation, heterologous expression and feeding experiments, we fully explain the biosynthesis pathway of ophiobolin K in Aspergillus ustus 094102, especially proved to be an unclustered oxidase OblCAu that catalyzes dehydrogenation at the site of C16 and C17 of both ophiobolin F and ophiobolin C. We also find that the intermediate ophiobolin C and final product ophiobolin K could be transported into a space between the cell wall and membrane by OblDAu to avoid the inhibiting of cell growth, which is proved by a fluorescence observation of the subcellular localization and cytotoxicity tests. This study completely resolves the biosynthesis mechanism of ophiobolins in strain A. ustus 094102. At the same time, it is revealed that the burden of strain growth caused by the excessive accumulation and toxicity of secondary metabolites is closely related to compartmentalized biosynthesis.
Deep Learning Architecture Reduction for fMRI Data

In recent years, deep learning models have demonstrated an inherently better ability to tackle non-linear classification tasks, due to advances in deep learning architectures. However, much remains to be achieved, especially in designing deep convolutional neural network (CNN) configurations. The number of hyper-parameters that need to be optimized to achieve accuracy in classification problems increases with every layer used, and the selection of kernels in each CNN layer has an impact on the overall CNN performance in the training stage, as well as in the classification process. When a popular classifier fails to perform acceptably in practical applications, it may be due to deficiencies in the algorithm and data processing. Thus, understanding the feature extraction process provides insights to help optimize pre-trained architectures, better generalize the models, and obtain the context of each layer’s features. In this work, we aim to improve feature extraction through the use of a texture amortization map (TAM). An algorithm was developed to obtain characteristics from the filters amortizing the filter’s effect depending on the texture of the neighboring pixels. From the initial algorithm, a novel geometric classification score (GCS) was developed, in order to obtain a measure that indicates the effect of one class on another in a classification problem, in terms of the complexity of the learnability in every layer of the deep learning architecture. For this, we assume that all the data transformations in the inner layers still belong to a Euclidean space. In this scenario, we can evaluate which layers provide the best transformations in a CNN, allowing us to reduce the weights of the deep learning architecture using the geometric hypothesis.
First report on Fusarium cerealis, identification and virulence as causal agents of crown rot on wheat in Algeria

Abstract In this study, FCR-symptomatic samples from the north-east of Algeria were collected. Macroscopic data and microscopic characteristics were used to identify the 23 isolates, which were then confirmed by molecular identification. NCBI GenBank assigned the accession number MW358286 to isolate FC14, which was identified as Fusarium cerealis. Under controlled conditions, two pathogenicity tests were performed on nine bread wheat cultivars (cv). The first one is an in vitro test in the growth chamber. The second one, in vivo test in the greenhouse. The results revealed that all cultivars were susceptible to FC14, and that F. cerealis reduced germination and coleoptile emergence rates significantly, with GI% and AUDPC values of 38.09% and 49.58% for cv. Boumerzoug, respectively. With cv. Bordj Mehis, F. cerealis decreased the RCL% and RCW% by 50.71% and 60.70%, respectively. The presence of F. cerealis species as an agent causing FCR was identified for the first time in Algeria.
Isolation, Characterization, and Molecular Detection of Porcine Sapelovirus

Porcine sapelovirus (PSV) is an important emerging pathogen associated with a wide variety of diseases in swine, including acute diarrhoea, respiratory distress, skin lesions, severe neurological disorders, and reproductive failure. Although PSV is widespread, serological assays for field-based epidemiological studies are not yet available. Here, four PSV strains were recovered from diarrheic piglets, and electron microscopy revealed virus particles with a diameter of ~32 nm. Analysis of the entire genome sequence revealed that the genomes of PSV isolates ranged 7569–7572 nucleotides in length. Phylogenetic analysis showed that the isolated viruses were classified together with strains from China. Additionally, monoclonal antibodies for the recombinant PSV-VP1 protein were developed to specifically detect PSV infection in cells, and we demonstrated that isolated PSVs could only replicate in cells of porcine origin. Using recombinant PSV-VP1 protein as the coating antigen, we developed an indirect ELISA for the first time for the detection of PSV antibodies in serum. A total of 516 swine serum samples were tested, and PSV positive rate was 79.3%. The virus isolates, monoclonal antibodies and indirect ELISA developed would be useful for further understanding the pathophysiology of PSV, developing new diagnostic assays, and investigating the epidemiology of the PSV.
Medicinal Cannabis for the Treatment of Chronic Refractory Pain: An Investigation of the Adverse Event Profile and Health-Related Quality of Life Impact of an Oral Formulation

Introduction: Medicinal cannabis is prescribed in Australia for patients with chronic refractory pain conditions. However, measures of safety and effectiveness of different cannabinoids are lacking. We designed an observational study to capture effectiveness, adverse events (AEs), and health-related quality of life (HRQoL) measures in patients prescribed an oral medicinal cannabis formulation at Cannabis Access Clinics through the Cannabis Access Clinics Observational study (CACOS). Objectives: We aimed to evaluate effectiveness, reported AEs, and change in patient-reported outcomes in individuals prescribed a cannabinoid oil formulation for management of chronic pain. Methods: A cross-sectional analysis was conducted on patients prescribed an oil formulation of Δ9-tetrahydrocannabinol and cannabidiol for pain symptoms of at least 3-month duration. Clinician-reported AEs were organized by system, organ, class, and frequency. Analysis of patient-reported responses to a questionnaire was conducted using published minimal clinically important differences to determine meaningful change in HRQoL over time. Results: More than half (n = 91/151, 60.3%) of the participants experienced at least one AE during the observation period (mean 133 ± 116 days). No serious AEs were reported. Patient-reported pain impact scores were significantly reduced across the cohort (p = 0.034), and pain intensity scores verged on significance (p = 0.053). The majority of patients saw meaningful improvements in sleep (49.3%) and fatigue (35.6%). Conclusion: This analysis presents real-world data collected as part of standard of care. More than one-third of patients benefited from oral medicinal cannabis, which is impactful given the refractory nature of their pain. Amelioration of the impact of pain confirms continued prescribing of this formulation and validates our observational methodology as a tool to determine the therapeutic potency of medicinal cannabinoids.
Stock Portfolio Optimization Using a Combined Approach of Relative Robust Risk Parity

Risk parity is perceived as one of the stock portfolio selection models that have received a lot of attention since the US financial crisis in 2008. The philosophy of this model is to allocate the same amount of portfolio risk between the constituent assets. In the present study, the combined portfolio selection model of relative robust risk parity is introduced, which uses the worst-case scenario approach on the covariance matrix parameter appearing in the robust risk model in portfolio robustness. According to historical data, several scenarios are considered for the covariance matrix. The objective function value of the hybrid model for each portfolio (feasible point) is the worst result (with most volatility) among the set of scenarios. Finally, the model selects a portfolio for which the worst possible result has the least relative volatility. The research portfolio consists of 8 industries from Tehran Stock Exchange in the period 88 Iranian Journal of Finance, 2021, Vol. 5, No. 4 (Mirmohammadi, S.) 2011 to 2020. This portfolio has a higher Sharpe ratio than conventional models of mean-variance and weight parity, and is more resilient to market declines than the two models and produces less loss. Therefore, risk-averse investors are advised to use this stock portfolio selection model as a cover to face severe market declines.
Genetic Epidemiological Studies of Diabetes Mellitus in Hospital Population of District Bahawalpur

Diabetes is considered a disease that is characterized by high glucose levels in the blood. Diabetes has become a global epidemic disease which is most common in developing countries. The aims are to provide an estimate of diabetes prevalence in the hospital population of district Bahawalpur. The study was carried out on 1000 Diabetic patients, Data was collected by a well-designed Questionnaire. In the statistical analysis, the percentage (%), Standard Error (S.E), mean (M), and Chi-Square tests were used. Out of 1000 Diabetic patients, 39.6% (396) were females and 60.4% (604) were males. The mean age was 51.57 ± 0.50 years in females and for the males, it was 47.99 ± 0.53. A greater number of patients belonged to the urban areas with 70.5% (705/1000) and Minimum belonged to Rural areas with 29.5% (295/1000). BMI recorded in the maximum range of 23-26.9 with 39.9% (399/1000) of the patients while it is recorded minimum the range of ≥27 with 10.1% (101/1000). By family history, much of the diabetic patients belonged to the consanguinity group with 35.7% (357/1000), while it was minimum in the out of cast 7.8 (78/1000). Type II Diabetes mellitus was more common with 64.2% (642/1000) and less common with 35.8% (358/1000). A more fetal onset of Diabetes occurs in the patients with Diabetic family history.
Fertilización biológica del cultivo de maíz* Biological fertilization of maize

By the growing demand for agricultural products and increased costs of chemical fertilizers, associated to pollution that this may cause to the environment, it is necessary to develop other sustainable alternatives for agricultural production. Biofertilizacion could mitigate these problems, and in turn increase crop yields. The aim of this study was to evaluate the effect of the application of biological fertilizers derived from seaweed applied to the soil and foliage on forage maize (Zea mays L.). The response variables were: relative chlorophyll content, electron transport rate, plant height, stem diameter and dry weight of the plant. The research was conducted during the summer-fall cycle 2011 in Torreon, Coahuila, Mexico. Two treatments were evaluated. With and without biological fertilizers; the fertilizers derived from seaweed extracts were: 1 L ha -1 compound Algaenzims MR and 0.5 L ha -1 AlZincB MR . The experimental design was completely random. Each treatment was replicated 10 times. Plants receiving biological fertilization showed higher values (p≤ 0.05) for relative chlorophyll content (32.4%) and electron transport rate (17.8%), which resulted in an increase (p≤ 0.05) in plant height ( 17.3%), stem diameter (10.5%) and plant dry weight (14.8%) compared to plants without application of biological fertilizers.
SYMBIOTIC VS COMMENSAL NETWORKING: THE CASE OF TEXTILE SMEs IN CHINA AND RUSSIA

e purpose of this research is to contribute to the literature addressing t he characteristics of small and medium enterprises (SMEs) based on the sample drawn "om two emerging economies - China and Russia. e study investigates the intensity and typology of n etworking activities that SMEs are involved in. e research contributes to the $eld by empirically inve stigating , testing , and pu%ing into a uni$ed "amework the measurement tools required for identifying symbiotic and commensal types of SMEs' networking interactions. It also provides an insight into a%itudinal, managerial, cul- tural, and environmental factors that condition these two types of networking and in&uence SMEs' willingness to globalize their operations and thus make their networks international. e overriding "amework of the study can be stated as developing , validating and testing the symbiotic networking concept relatively to the international business studies. In this way, the study contributes to overcoming the criticism that network theory is not predictive by nature and is not testable.
Plastic clays suitable for pipe manufacture in Wellington city

Considerable quantities of plastic clays, probably halloysite rich and thought to be suitable for earthenware pipe manufacture, are present in many parts of the lower altitude, low-gradient areas around the city of Wellington. From the foundations of the City Council parking building on Wellington Terrace and the adjacent property, it appears likely that several thousands of yards of plastic clays have been removed and dumped. This valuable natural resource, now in short supply, should be used. Methods of use that could prove of benefit to both the builder and the pipe manufacturer are suggested.
Epidemiology of diagnosed cluster headache in Norway

Background: Cluster headache (CH) is one of the most painful conditions in humans and there is limited epidemiological data on this debilitating condition. Objectives: To describe the epidemiology of CH in Norway Methods: We conducted a nationwide study to investigate the prevalence, incidence, and comorbidity of CH in Norway between January 1 2008 and December 31 2016. Treatment and outcome data from the Norwegian patient registry and the Norwegian prescription database were linked on an individual basis. Results: Among 3,892,260 individuals ≥18 years old of age, we identified a total of 1891 patients with CH. The prevalence of CH was 48.6 per 100,000, and the male-to-female ratio was 1.47. The estimated incidence of CH was 3.0 per 100,000/year. Among patients with CH, increased age and sex adjusted odds ratios ([OR], all with p-values <0.0001, were observed for medication-induced headache (OR 50.7, 95% CI 36.7–69.9), migraine (OR 25.2, 95% CI 22.5–28.3), chronic posttraumatic headache (OR 22.2, 95% CI 12.8–38.45), history of cranial trauma (OR 1.9, 95% CI 1.5–2.4), somatoform disorders (OR 4.2, 95% CI 3.0–5.8), suicide attempt (OR 3.9, 95% CI 2.6–5.8), personality disorder (OR 3.6, 95% CI 2.6–4.9), bipolar disorder (OR 3.6, 95% CI 2.8–4.8), peptic ulcer (OR 2.8, 95% CI 2.3–3.3), depression (OR 2.8, 95% CI 2.4–3.1), substance abuse (OR 2.6, 95% CI 2.0–3.3), and cerebrovascular disease (OR 2.4, 95% CI 1.8–3.1). Use of opioid analgesics during the study period was more common among patients with CH compared to others (81% vs. 22%, sex and age adjusted OR 23.4, 95% CI 20.8–26.2, p < 0.0001).
Analysis of the Competitive Weekly Microcycle in Elite Soccer: Comparison of Workload Behavior in Absolute and Relative Terms

Abstract Guerrero-Calderón, B, Fradua, L, Morcillo, JA, and Castillo-Rodríguez, A. Analysis of the competitive weekly-microcycle in elite soccer: comparison of workload behavior in absolute and relative terms. J Strength Cond Res 37(2): 343–350, 2023—This study aimed to analyze the locomotion activity of elite-level soccer players throughout the weekly microcycle by playing position, and compare the training-load (TL) behavior in relation to match-play in absolute and relative (meters or events per minute) terms. Training and match data were collected from 30 professional soccer players belonging to a Spanish First Division team during the 2015/2016 season using global positioning technology (152 training sessions and 38 matches). Overall, the results showed a decrease of TL metrics when competition approached (p < 0.05). However, a progressive decrease was not found for all metrics. Two-way analysis of variance test revealed that workload was affected by the interaction between microcycle-day and season period showing medium or large effect size (ηp2 > 0.15) for all positions and metrics. Considering the TL in relation to the match-load, opposite load behavior was found in absolute and relative terms by position; whereas, central-defenders, external-defenders, and forwards covered 21, 25 and 26% more absolute medium-speed running distance (MSRD), respectively; central-defenders covered 14% (8.6–13.4 m·min−1), external-defenders 10% (7.5–13.9 m·min−1), and forwards 7% (8.4–15.7 m·min−1) more relative-MSRD 4 days before match than match-day. The accelerations-metric also showed higher relative values 4, 3, and 2 days before the match. Because the objective of the training is to prepare players to withstand the competition demands, analyzing the position-specific TL concerning to match demands represents an advantageous strategy for training periodization. In addition, this study highlights the importance of taking into account the time spent of developing the different efforts to properly define the position-specific physical demands.