Miracle-dz/UniFAR-FTUs huggingface dataset:
Household composition and academic performance in the elementary level in Brazil

Children with divorced parents or children living in single-parent families are expected to achieve lower academic performance in standardized tests when compared to children living with two biological parents. Nevertheless, the mechanisms of those disparities remain poorly addressed in the Brazilian literature. We compared the performance of students in the 5th-grade at the elementary level using Saeb of 2017 for Mathematics and Portuguese. The main objective was to address the differences between students living with: mother and father; mother and social father; mother only or with aggregates; father and social mother; father only or with aggregates; and other arrangements. Children living with their mother and a social father or with both biological parents had higher performances. Nonetheless, differences became insignificant when controlled by school infrastructure and location, household´s socioeconomic status and household´s social interactions. The results highlight the need for public policies to strengthen school and family resources invested on academic learning to overcome the challenges imposed by the new family configurations on children´s achievement.
Capital social e qualidade de vida relacionada à saúde bucal de adultos do Sistema Único de Saúde

Objetivo: Avaliar a influência do capital social individual na qualidade de vida relacionada à saúde bucal (QVRSB) de adultos do Sistema Único de Saúde (SUS). Métodos: Este estudo transversal incluiu adultos adscritos às Estratégias da Saúde da Família (ESFs) de Santa Maria, RS. A coleta de dados foi realizada de novembro de 2019 a março de 2020 em quatro ESFs por examinadores calibrados e treinados. O capital social individual, avaliado pela participação em atividades voluntárias e a confiança em vizinhos e amigos, foi considerado o preditor do estudo. Características sociodemográficas, comportamentais e de saúde periodontal também foram coletadas. A QVRSB, considerada o desfecho, foi mensurada pelo questionário OHIP-14. Modelos de regressão de Poisson avaliaram a associação entre variáveis independentes e QVRSB. Resultados: Ao total, 80 adultos foram incluídos. Indivíduos do sexo feminino, da cor da pele não branca, com menor renda familiar mensal, fumantes, que visitaram o serviço odontológico a menos de um ano e que possuíam sangramento gengival apresentaram altos scores totais de OHIP-14 (P<0,05). A não participação em atividades voluntárias [razão de média (RR): 1,24; intervalo de confiança (IC) 95%: 1,03-1,50] e a ausência de confianca em vizinhos e amigos (RR: 1,24; IC 95%: 1,08-1,43) foram associadas a uma pior QVRSB dos adultos. Conclusão: A ausência de um capital social individual influenciou negativamente a QVRSB de adultos usuários do SUS.
Biocompatible Nanocomposites for Postoperative Adhesion: A State-of-the-Art Review

To reduce and prevent postsurgical adhesions, a variety of scientific approaches have been suggested and applied. This includes the use of advanced therapies like tissue-engineered (TE) biomaterials and scaffolds. Currently, biocompatible antiadhesive constructs play a pivotal role in managing postoperative adhesions and several biopolymer-based products, namely hyaluronic acid (HA) and polyethylene glycol (PEG), are available on the market in different forms (e.g., sprays, hydrogels). TE polymeric constructs are usually associated with critical limitations like poor biocompatibility and mechanical properties. Hence, biocompatible nanocomposites have emerged as an advanced therapy for postoperative adhesion treatment, with hydrogels and electrospun nanofibers among the most utilized antiadhesive nanocomposites for in vitro and in vivo experiments. Recent studies have revealed that nanocomposites can be engineered to generate smart three-dimensional (3D) scaffolds that can respond to different stimuli, such as pH changes. Additionally, nanocomposites can act as multifunctional materials for the prevention of adhesions and bacterial infections, as well as tissue healing acceleration. Still, more research is needed to reveal the clinical potential of nanocomposite constructs and the possible success of nanocomposite-based products in the biomedical market.
Precision Agriculture: The Effect of Variable Rate Fertilizer Application On Soil Test Values

Use of variable rate fertilizer spreaders (VRS) is available to farmers in many areas of Kentucky. For use of VRS, a soil fertility map must be prepared for the field to be spread which requires subdividing the field into subunits. Each subunit is then soil sampled separately. A common procedure in commercial use is to grid a field into 2.5 acre blocks and to take a composite sample of 6-8 cores along the perimeter of a circular radius of 60-80 ft from the center of each block. Each block receives a separate fertilizer recommendation based on results from the soil test. With this information, a VRS can be programmed to apply the recommended rate of fertilizer on-the-go to each specific block as it drives across the field. The objective is to direct the amount (or kind) of fertilizer to soil test variations which occur within the field. This approach assumes that the result from each soil sample of each block uniformly represents the soil test level for all the area within that block. It also assumes that the VRS applies fertilizer (amount and kind) uniformly across its swath width and along the pathway it is driven across each block. These assumptions may be questionable. We conducted a study to measure soil test levels within blocks of a field which had been soil tested on a grid, before fertilizer was applied and at harvest, 6 months later. The objective was to define soil test variability within blocks before and after VRS fertilization. This information should provide insight into the effectiveness of on-the-go VRS fertilizer
Cardiac output and the pharmacology of general anesthetics: a narrative review

The relationship between cardiac output and anesthetic drugs is important to anesthesiologists, since cardiac output determines the speed with which a drug infused into the bloodstream reaches its target and the intensity of the drug’s effect. But rather than focus on how anesthetic drugs affect cardiac output, this narrative review focuses on how changes in cardiac output affect the pharmacokinetics and pharmacodynamics of general anesthetics during the three phases of anesthesia. At induction, an increase in cardiac output shortens both the onset time of propofol for hypnosis and the neuromuscular blocking effect of rapid-acting neuromuscular blockers, favoring the conditions for rapid sequence intubation. During maintenance, changes in cardiac output are followed by opposite changes in the drug plasma concentration of anesthetic drugs. Thus, an increase in cardiac output followed by a decrease in the plasma concentration of the anesthetic could expose the patient to a real risk of intraoperative awakening, which can be avoided by increasing the dose of hypnotic drugs. At emergence, an increase in cardiac output secondary to an increase in pCO2 allows for a more rapid recovery from anesthesia. The pCO2 can be increased by adding CO2 to the respiratory circuit, lowering the ventilatory rate, or placing the patient on partial rebreathing. Finally, the reversal action of sugammadex for rocuronium-induced neuromuscular block can be shortened by increasing the cardiac output.
DeepMetaForge: A Deep Vision-Transformer Metadata-Fusion Network for Automatic Skin Lesion Classification

Skin cancer is a dangerous form of cancer that develops slowly in skin cells. Delays in diagnosing and treating these malignant skin conditions may have serious repercussions. Likewise, early skin cancer detection has been shown to improve treatment outcomes. This paper proposes DeepMetaForge, a deep-learning framework for skin cancer detection from metadata-accompanied images. The proposed framework utilizes BEiT, a vision transformer pre-trained as a masked image modeling task, as the image-encoding backbone. We further propose merging the encoded metadata with the derived visual characteristics while compressing the aggregate information simultaneously, simulating how photos with metadata are interpreted. The experiment results on four public datasets of dermoscopic and smartphone skin lesion images reveal that the best configuration of our proposed framework yields 87.1% macro-average F1 on average. The empirical scalability analysis further shows that the proposed framework can be implemented in a variety of machine-learning paradigms, including applications on low-resource devices and as services. The findings shed light on not only the possibility of implementing telemedicine solutions for skin cancer on a nationwide scale that could benefit those in need of quality healthcare but also open doors to many intelligent applications in medicine where images and metadata are collected together, such as disease detection from CT-scan images and patients’ expression recognition from facial images.
A Novel Sparse Image Reconstruction Based on Iteratively Reweighted Least Squares Using Diagonal Regularization

—In the information age, numerous data needs to be transferred from one point to another. The bigger the amount of the data, the more the consumption in computation and memory. Due to a limitation of the existing resource, the compression of the data and the reconstruction of the compressed data receive much attention in several research areas. A sparse signal reconstruction problem is considered in this work. The signal can be captured into a vector whose elements can be zeros. Iteratively Reweighted Least Squares (IRLS) is a technique that is designed for extracting the signal vector from the available observation data. In this paper, a new algorithm based on the iteratively reweighted least squares using diagonal regularization method are proposed for sparse image reconstruction. The explicit solution of the IRLS optimization problem is derived and then an alternative IRLS algorithm based on the available solution is proposed. Since the matrix inverse in the iterative computation can be subject to ill condition, a diagonal regularization is proposed to overcome such a problem. Numerical simulation is conducted to illustrate the performance of the new IRLS with the comparison to the former IRLS algorithm. Numerical results indicate that the new IRLS method provides lower signal recovery error than the conventional IRLS approach at the expense of more complexity in terms of more computational time.
Investigating the Point of View of Project Management Practitioners on Technical Debt - A Study on Stack Exchange

Context: Technical debt (TD) can bring short-term benefits to software projects, but its presence is associated with issues such as decreasing product quality. Recent literature has proposed various approaches for identifying and managing TD, but most of them focus on the software developers’ point of view. Little is known about how project management practitioners perceive and manage TD items. Goal: This work aims to investigate how project management practitioners discuss and experience TD. Method: To achieve this goal, our work mines, curates, and selects a total of 108 TD-related discussions on the Stack Exchange Project Management (SEPM) Q&A site. These discussions amount to 547 posts and 882 text comments on the subject. We analyze this data set quantitatively and qualitatively, using open coding to derive TD types, indicators, and management practices. Results: We identified 74 indicators used for recognizing debt items and 126 TD management practices. The types of debt most discussed at SEPM are process and people debts. This contradicts studies done with developers where code and design debts are most discussed. Conclusion: The perspective considered by project management practitioners to analyze the TD phenomenon is different from the one considered by other roles in the software development process. Our work organizes the identified TD indicators and management practices into a Sankey diagram, which may assist TD management practitioners and serve as guidance for future research on the subject.
Design and Implementation of Convolutional Neural Network Model for Melanoma Classification

The automated detection of melanomas out of dermo-scopic skins sample remains a particularly issue of subject. But, these problems can be remedied by deploying deep learning technique like a tools of mechanic visions. This would allow for more accurate image analysis. This research proposes the use of an automatic mechanism of melanoma grouper that depends on a (DCNN) deep convolutional neural network. The goal of this classifier is to accurately differentiate between benign and malignant forms of melanoma. The structure of the DCNN was deliberately built by arranging a number of substrates which were accountable so as to collect lower-level to higher-level information from skin photos form of specific manner. This arrangement was done in order to produce the structure. Choosing a large number of filters and the sizes of those filters, using deep learning layers that are suitable, determining the network’s depth, and tweaking hyperparameters are other key variables in the creation of a DCNN. In order to efficiently diagnose melanoma skin cancer, the primary objective is to propose a DCNN that is both lightweight and less difficult in comparison to other cutting-edge methods. For the purpose of this inquiry, which involved analyzing numerous cancer samples, dermoscopic images were obtained via the utilization of the datastores made available by the International Skin Imaging Collaboration (ISIC 2020). In order to evaluate the model, we looked at its accuracy, precision, recall, and specificity, as well as its F1 score. On the ISIC datasets from 2020, suggested DCNN grouper attained precision of about 90.42%,81.41% and 88.23% respectively. This demonstrates high performance in contrast to the performance of other cutting-edge networks. As a result, the proposed technique can provide a less difficult and more cutting-edge infrastructure pertaining to automatic identification of melanoma, speeding procedures in diagnosing it, hence increasing the likelihood of successfully saving a life.
Application of the Principles of the Generalized Spectral-Analytical Approach for Image Processing of RTM Diagnostics Thermograms

Breast cancer is one of the most common cancer illnesses in the world. Nowadays microwave diagnostics has great effect on early detection of breast cancer. In comparing with mammography this form of diagnosis has higher contrast that increases the effectiveness of early cancer detection in preclinical phase. Examination data obtained by microwave diagnosis represent a temperature map, where all temperature changes are traces. The most dangerous rapidly growing tumors reduce the heat generated, that can be observed on the temperature map. Analysis of such thermal images is an urgent task for early diagnosis of neoplasms. In this article, we propose an algorithm for processing thermal images based on a generalized spectral-analytical method. Gauss-Hermite functions are used as basis functions. The efficiency of the algorithm is tested on test thermal images, which are simplified images of the breast with different tumor diameters on the several stages of pathology development. The main results of processing are presented, as well as a conclusion about the prospects of the approach used.
Safety and Survival Outcomes of Liver Resection following Triple Combination Conversion Therapy for Initially Unresectable Hepatocellular Carcinoma

Simple Summary This study aimed to investigate the safety and long-term survival outcomes of salvage liver resection in patients with initially unresectable hepatocellular carcinoma (HCC) who had undergone triple combination conversion therapy (TACE/HAIC + TKIs + ICIs). While hepatectomy following conversion therapy exhibited elevated incidence rates of intra-abdominal bleeding, biliary leakage, post-hepatectomy liver failure, and Clavien–Dindo grade IIIa complications compared to pure hepatectomy, their safety profiles remained acceptable when appropriate medical interventions were administered. Patients with initially unresectable HCC, who successfully underwent conversion resection, demonstrated comparable overall survival (OS) and recurrence-free survival (RFS) to patients with initially resectable HCC. Abstract Triple combination conversion therapy, involving transcatheter arterial chemoembolization (TACE) or hepatic arterial infusion chemotherapy (HAIC) combined with tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs), has shown an encouraging objective response rate (ORR) and successful conversion surgery rate in initially unresectable hepatocellular carcinoma (HCC). However, the safety and long-term survival outcomes of subsequent liver resection after successful conversion still remain to be validated. From February 2019 to February 2023, 726 patients were enrolled in this retrospective study (75 patients received hepatectomy after conversion therapy [CLR group], and 651 patients underwent pure hepatectomy [LR group]). Propensity score matching (PSM) was used to balance the preoperative baseline characteristics. After PSM, 68 patients in the CLR group and 124 patients in the LR group were analyzed, and all the matching variables were well-balanced. Compared with the LR group, the CLR group experienced longer Pringle maneuver time, longer operation time, and longer hospital stays. In addition, the CLR group had significantly higher incidence rates of intra-abdominal bleeding, biliary leakage, post-hepatectomy liver failure (PHLF), and Clavien–Dindo grade IIIa complications than the LR group. There were no significant statistical differences in overall survival (OS) (hazard ratio [HR] 0.724; 95% confidence interval [CI] 0.356–1.474; p = 0.374) and recurrence-free survival (RFS) (HR 1.249; 95% CI 0.807–1.934; p = 0.374) between the two groups. Liver resection following triple combination conversion therapy in initially unresectable HCC may achieve favorable survival outcomes with manageable safety profiles; presenting as a promising treatment option for initially unresectable HCC.
Disentanglement of Surface and Confinement Effects for Diene Metathesis in Mesoporous Confinement

We study the effects of a planar interface and confinement on a generic catalytically activated ring-closing polymerization reaction near an unstructured catalyst. For this, we employ a coarse-grained polymer model using grand-canonical molecular dynamics simulations with a Monte Carlo reaction scheme. Inspired by recent experiments in the group of M. Buchmeiser that demonstrated an increase in ring-closing selectivity under confinement, we show that both the interface effects, i.e., placing the catalyst near a planar wall, and the confinement effects, i.e., locating the catalyst within a pore, lead to an increase of selectivity. We furthermore demonstrate that curvature effects for cylindrical mesopores (2 nm < d < 12.3 nm) influence the distribution of the chain ends, leading to a further increase in selectivity. This leads us to speculate that specially corrugated surfaces might also help to enhance catalytically activated polymerization processes.
Multi‐Instruments Observation of Ionospheric‐Thermospheric Dynamic Coupling Over Mohe (53.5°N, 122.3°E) During the April 2023 Geomagnetic Storm

The state and variations of the Ionosphere‐Thermosphere (I‐T) system are strongly influenced by dynamical processes, with these effects being amplified during intense space environment disturbances such as geomagnetic storms, producing multi‐scale disturbance features in the I‐T system. The redistribution of energy and momentum through the dynamical processes is currently not well understood. Unfortunately, the dearth of thermospheric observations has yielded limited studies capable of monitoring and analyzing the I‐T dynamical coupling during storms using co‐located measurements. This work examines the responses of the I‐T system during the April 2023 geomagnetic storm based on high‐resolution continuous I‐T system observations at Mohe observatory, a middle latitude station. Both large‐scale features and short‐period oscillations were identified in multiple key parameters of the I‐T system. Similar disturbed patterns in thermospheric winds occurred during the main and recovery phases of the geomagnetic storm. However, the oscillation features in many parameters of the I‐T system are only observed during the main phase. The results of concurrent I‐T system observations unveil the oscillation features of thermospheric winds, temperatures, the ionospheric F2 peak height, electron density, and total electron content. These findings reveal the important influence of wind divergence on thermospheric temperature disturbances and its modulatory effect on ionospheric disturbances.
Geochronology of upper cretaceous and tertiary igneous rocks from the Slavonija-Srijem depression (Southern Pannonian Basin) and their basic petrological features

The paper presents geological and petrological data of igneous rocks sampled in 12 deep wells from the Slavonija-Srijem Depression. Four groups of igneous rocks can be distinguished: (1) Upper Cretaceous ophiolitic basic rocks; (2) Senonian bimodal basalts and rhyolites; (3) Late Oligocene-Early Miocene trachydacites, and (4) Badenian basalts and metabasalts. The rocks of the first two groups make up the basement of the Pannonian Basin and the rocks of the last two groups are included in its Tertiary cover. For each chronostratigraphic group of igneous rocks K-Ar ages and basic petrological data are presented. All these igneous rocks are correlated with corresponding igneous rocks from the Southern Pannonian Basin and the northernmost Dinarides.
Early Echocardiographic Findings of Pulmonary Hypertension-specific Therapy in Children

Objective: Echocardiography is a very useful tool for the diagnosis and evaluation of pulmonary hypertension (PH). This study was planned to investigate whether echocardiographic (ECHO) data of patients with PH are effective in the follow-up and course of treatment. Methods: A retrospective analysis of the data from 26 PH patients was performed. Analyses were performed on the data of the patients, including their demographics and ECHO findings. The ECHO measurements of the patients were labeled as 0 (beginning of the PH specific therapy), 1 (on the 15th day of the therapy), 2 (one month after the previous echocardiogram). Results: The left ventricle ejection fraction (EF) (p=0.05) and fractional shortening (FS) (p=0.038) values in ECHO2 were significantly higher than those in ECHO1. Aortic velocity-time integral1 (VTI1) was significantly higher than aortic VTI0 (p=0.001; p<0.01), and tricuspid annular plane systolic excursion2 (TAPSE2) was significantly higher than TAPSE0 (p=0.046). Moreover, right ventricular ejection time1 (RVET1) was significantly higher than RVET0 (p=0.034), and left ventricular ejection time1 (LVET1) was significantly higher than LVET0 (p=0.003). Conclusions: This study provides information on ECHO parameters that improve during the initial stages of therapy. Based on the results of our study, even at the beginning of treatment, there were increases in right and left ventricular filling, EF, and FS. Clinical deterioration of PH can be detected early/before the clinical status of the patient worsens with detailed examinations using echocardiography.