Miracle-dz/UniFAR-FTUs huggingface dataset:
Laboratory and Field Performance of the Biosand Point of Use Water Filtration System in the Artibonite Valley, Haiti

9 Introduction 10 Methods 12 Results 15 Discussion 19 Conclusions and Recommendations 24 III. Long-term Field Performance of the Biosand Filter the Artibonite Valley near Deschapelles, Haiti 26 Abstract 26 Introduction 26 Methods 28 Results 32 Discussion 37 Conclusions 4126 Introduction 26 Methods 28 Results 32 Discussion 37 Conclusions 41
Adaptive Teaching for Cross-Domain Crowd Counting

The main challenge of Unsupervised Domain Adaptation (UDA) crowd counting is the large domain gap between a synthetic domain with annotations (source) and a real-world domain of interest without annotations (target). Previous mainstream UDA crowd counting methods either employ feature alignment or a semi-supervised learning paradigm via pseudo-labels. We for the first time combine both of their advantages and propose an Adversarial Mean Teacher (AMT) framework. On the one hand, we optimize the student model with domain adversarial learning. On the other hand, we feed perturbed target images to the teacher model to generate pseudo-labels. Furthermore, to improve the quality of the pseudo-labels, we propose an Adaptive Teaching (AT) module, consisting of pseudo-label refinement and credible pseudo-label selection. Concretely, we first generate two candidate pseudo-labels from the prediction of the teacher model and obtain a refined pseudo-label by mixing them at the pixel-level. Moreover, we introduce an auxiliary task of foreground-background classification to assist credible region selection and only activate supervision signals on those regions. Extensive experiments on four real-world crowd counting benchmarks demonstrate the effectiveness of our method namely Cross-Domain Adaptive Teacher (CDAT).
Auto-Points: Automatic Learning for Point Cloud Analysis With Neural Architecture Search

Pure point-based neural networks have recently shown tremendous promise for point cloud tasks, including 3D object classification, 3D object part segmentation, 3D semantic segmentation, and 3D object detection. Nevertheless, it is a laborious process to construct a network for each task due to the artificial parameters and hyperparameters involved, e.g., the depths and widths of the network and the number of sampled points at each stage. In this work, we propose Auto-Points, a novel one-shot search framework that automatically seeks the optimal architecture configuration for point cloud tasks. Technically, we introduce a set abstraction mixer (SAM) layer that is capable of scaling up flexibly along the depth and width of the network. Each SAM layer consists of numerous child candidates, which simplifies architecture search and enables us to discover the optimum design for each point cloud task pursuant to resource constraint from an enormous search space. To fully optimize the child candidates, we develop a weight-entwinement neural architecture search (NAS) technique that entwines the weights of different candidates in the same layer during supernet training such that all candidates can be extremely optimized. Benefiting from the proposed techniques, the trained supernet allows the searched subnets to be exceptionally well-optimized without further retraining or finetuning. In particular, the searched models deliver superior performances on multiple extensively employed benchmarks, 93.9% overall accuracy (OA) on ModelNet40, 89.1% OA on ScanObjectNN, 87.1% instance average IoU on ShapeNetPart, 69.1% mIoU on S3DIS, 70.4% mAP@0.25 on ScanNet V2, and 64.4% mAP@0.25 on SUN RGB-D.
The role of benthic macroalgae in sediment-water nutrient cycling in the Swan-Canning estuarine system, Western Australia

This study documented the macroalgal assemblages of the Swan-Canning Estuarine System (SCES) over a two year period, and the influences of several environmental parameters on the assemblages. In addition, the impacts of unattached macroalgal accumulations on benthic nutrient fluxes and microbial communities were investigated. Benthic macroalgal assemblages and physico-chemical regimes were monitored in the SCES, to determine temporal and spatial changes in macroalgal communities and the influence of environmental factors in these changes. Physico-chemical regimes demonstrated strong seasonal changes, which revolved around the onset and cessation of freshwater flows in winter (May to September). In the months after freshwater flows, strong spatial variability n physico-chemical profiles was observed. However, by summer the system was essentially marine. Macroalgal biomass and species richness was lowest in winter. Species number was maximal during periods of greatest hydrological variability in the estuary (spring and autumn). It may be inferred from results of statistical analyses that substrate type (i.e. hard/soft) and waterflow were the most influential factors over temporal and spatial distribution of macroalgal species in the SCES. These factors were reflected by the patchiness of macroalgal distribution in the system attached macroalgal species distributed unevenly according to availability of limited hard substrate and presence/absence of unattached macroalgal species corresponding to seasonal fres hwater flows. One species, Graci/aria comosa, dominated macroalgal biomass and was the most widespread species and commonly occurred as extensive, unattached accumulations. As G. comosa was the most abundant unattached macroalga, accumulations of this sp ecies were investigated to determine the characteristics and behaviour of accumulations in the Swan-Canning Estuarine System. Accumulations were characterised by seasonally measuring height and biomass of accumulations in three regions of the estuarine sy stem over one year. The height of accumulations was generally between 5 and 25cm, regardless of water depth, location, or season. Biomass was highly variable, but generally between 100
Uveal Melanoma Metastasis to the Thyroid

Background Around 1.2 to 3.1% of thyroid malignancies are due to metastasis. Among them, cutaneous malignant melanomas constitute 4% of malignancy metastasized to the thyroid. Uveal melanoma is uncommon, and its metastasis to the thyroid has only rarely been reported. Hereby, we describe an unusual case of uveal melanoma metastasized to the thyroid and discuss the concept of correct diagnosis. Case Report. During a routine ophthalmological examination, an 86-year-old Caucasian female was found to have retinal detachment secondary to choroidal melanoma. She was treated with gamma knife which resulted in reduction of tumor size. Three months later, she was noted to have a goiter on physical examination. Follow-up thyroid ultrasonography demonstrated numerous vascularized nodules in both lobes. The fine needle aspiration (FNA) of the left dominant nodule was indeterminate the first time and nondiagnostic the second time. FNA of the right dominant nodule was nondiagnostic twice but showed malignant cells the third time. Subsequent immunohistochemistry staining of the FNA sample from the right thyroid nodule confirmed a profile consistent with malignant melanoma. Conclusion It should be kept in mind that a thyroid nodule detected in a patient with a diagnosis of uveal melanoma can be metastasis and that uveal melanoma diagnosis should be taken into account for the examination of the thyroid tumors of these patients. It is important to employ immunohistochemical staining FNA examination of the patient with such tumors for markers associated with a patient's known malignancy to facilitate diagnosis.
Distribution constraining for combating mode collapse in generative adversarial networks

Abstract. Image synthesis is a critical technique in the image processing field. Recently, generative adversarial networks (GANs) have played a significant role in synthesis tasks. However, the issue of mode collapse remains a major challenge in GANs, which limits their potential applications. We propose a method to address the mode collapse problem. Our approach focuses on minimizing the divergence between the distributions of real and generated features, thereby reducing the learning pressure on the discriminator. An advantage of our method is that it does not require prior knowledge or manual design. Additionally, it can be easily incorporated into state-of-the-art frameworks across various domains. Experimental results demonstrate the effectiveness and competitive performance of our proposed method.
Digital Transformation and Green Development Research: Microscopic Evidence from China’s Listed Construction Companies

The construction industry is in urgent need to transition away from its rough development and management practices. It is essential to embrace a sustainable development path to enhance core competitiveness, promote resource intensification, and prioritize environmental friendliness. The digital transformation uses information and data as the key elements to promote the transformation of traditional industries to become more intelligent and green. This ushers in new opportunities for transformation in the construction industry, marking a significant turning point for its evolution. This paper explores the impact of digital transformation on the green development of construction companies and its inner mechanism. Based on the panel data of the listed companies in China’s construction industry from 2015 to 2021, the two-way fixed effect, mediating effect, moderating effect, and threshold effect models are used to test the relationship between them. The results indicate that digital transformation significantly promotes the green development of construction companies. Additionally, this result still holds after robustness and endogeneity tests. This effect is more significant in state-owned, larger companies situated in regions with weaker digital economy development. In addition, the intensity of regional environmental regulations strengthens the impact of digital transformation on green development. However, it has a threshold effect. In the test of mediating effect, it has been found that green innovation and corporate human capital structure can serve as mediators. In the general trend of digital change, the drive towards the sustainable development of construction companies offers micro-empirical evidence that the digital economy empowers green development in China.
A novel validation approach shows new, solid reasons why vertical jump height should not be used to predict leg power

Jump height continues to be widely used to predict power in humans. Individual progress is often monitored on the basis of estimated power, but prediction equations are based on group data. The objective of the study was to show that vertical jump performance (VJP) and mechanical power are poorly associated, particularly within individuals. Two experiments are presented. First, 52 physically active male college students performed five maximal vertical jumps each. Second, three young male participants performed 50 maximal jumps each. Participants rested for 1 minute between jumps. VJP was calculated from kinematic data as peak body center of mass (BCOM) minus standing BCOM; peak power (PEAKPWR) was calculated from the vertical ground reaction force registered by a force plate, and average power (MEANPWR) during propulsion from the change in potential energy of BCOM. Regression analyses were performed using standardized VJP scores as the predictor variable and standardized power scores as the resulting variables, expecting an identity function of y = x (intercept = 0, slope = 1) and R2 = 1. In experiment 1, the model for zPEAKPWR R2 = 0.9707 (p < 0.0001) but slope (0.3452) ≠ 1 (p < 0.0001). The model for zMEANPWR R2 = 0.9239 (p < 0.0001); nevertheless, slope (0.4257) ≠ 1 (p < 0.0001). In experiment 2, all individual models for zPEAKPWR and zMEANPWR resulted in poor associations (R2 ≤ 0.21) and slopes ≠ 1 (p≤0.001). In conclusion, regression analysis for individuals, and even for groups, confirms that VJP is a poor predictor of mechanical power.
Direct medical cost of COVID-19 in children hospitalized at a tertiary referral healthcare center in Mexico City

Introduction Despite the end of the COVID-19 pandemic being declared by the WHO, the economic consequences are far from over. One of these implications was the cost of inpatient care for health institutions. To date, some studies have examined the economic burden of COVID-19 in the adult population but only a few have focused on child populations. Objective To estimate the direct medical costs of COVID-19, focusing on children in Mexico. Method Data about resources consumed during hospital stays were extracted from the medical records of patients hospitalized at a Mexican tertiary healthcare institution. Other sources of information were the unit prices of inputs and the salaries of health personnel. A micro-costing methodology was used to obtain cost results by age group over different hospital areas. Data analysis was performed with descriptive statistics and regression models to evaluate the predictors of total cost. Results One hundred and ten medical records were reviewed of which 57.3% corresponded to male patients and the mean age was 7.2 years old. The estimated average cost per patient was US$5,943 (95% CI: US$4,249–7,637). When the costs of the three clinical areas were summed, only the 5–10 years old group showed a maximum cost of US$14,000. The regression analysis revealed the following factors as significant: sex, age, staying at an emergency room, having a positive bacterial culture, and having comorbidities. Discussion The cost results were somewhat similar to those reported in children from the USA, but only regarding low severity COVID-19 cases. However, comparability between these types of studies should be done with caution due to the huge differences between the healthcare systems of countries. The study cost results may help public decision-makers in budget planning and as inputs for future cost-effectiveness studies about interventions regarding COVID-19.
Structure de l'écoulement diphasique gaz-liquide dans les échangeurs à plaques corruguées

Cette etude a ete menee au LEMTA dans le cadre d'une action de recherche concertee CEA-CENG-GRETH-ECOTECH sur les echangeurs de chaleur a plaques. L’etat des connaissances sur la thermo hydraulique et l'hydrodynamique des ecoulements monophasiques (liquides newtoniens et complexes) permet maintenant de bien apprehender les problemes lies au dimensionnement de ces echangeurs. Pourtant maintenant largement employes dans des utilisations diphasiques, ces echangeurs n'ont pas fait l'objet d'etudes et de recherches approfondies a l'exception des echangeurs a plaques munis d'ailettes. Outre l'etablissement de cartes d'ecoulement, les objectifs de ce travail experimental sont d'expliquer les differents mecanismes de frottement parietal et donc d'echange lorsque le melange diphasique s'enrichit en gaz et subit des changements de regime (transition). Pour ce faire, les deux principales techniques de mesure mises en oeuvre sont la mesure du gradient parietal de vitesse par technique electrochimique (technique polarographique) et la mesure du taux de vide (sonde optique). Deux configurations, un ecoulement co-courant horizontal et un ecoulement co-courant vertical ascendant, ont ete etudiees avec deux geometries differentes (plaques a cannelures droites et plaques a chevrons croises).
Predictors of Length of Stay, Mortality and Rehospitalization in COPD Patients: A Retrospective Cohort Study

Chronic obstructive pulmonary disease (COPD) is a highly prevalent chronic lung disease that has a significant impact on individuals and healthcare systems worldwide. This study aimed to identify factors that predict the length of a hospital stay (LOHS), one-year mortality, and rehospitalization within 6 months in patients admitted for acute exacerbation of COPD (AECOPD). A retrospective cohort study was conducted using data from 170 patients admitted to a district general hospital in Switzerland between January 2019 and February 2020. Sociodemographic and health-related variables measured at admission were analyzed as potential predictors. Multivariable zero-truncated negative binomial and logistic regression analyses were performed to assess the risk factors for LOHS (primary endpoint), mortality, and rehospitalization. The results show that an indication for oxygen supplementation was the only significant predictor of LOHS. In the logistic regression analysis, older age, COPD severity stages GOLD III and IV, active cancer and arrhythmias were associated with higher mortality, whereas rehabilitation after discharge was associated with lower mortality. There were no significant associations regarding rehospitalization. This study identified routinely available predictors for LOHS and mortality, which may further advance our understanding of AECOPD and thereby improve patient management, discharge planning, and hospital costs. The protective effect of rehabilitation after hospitalization regarding lower mortality warrants further confirmation and may improve the comprehensive management of patients with AECOPD.
Chemometric Classification of Apple Cultivars Based on Physicochemical Properties: Raw Material Selection for Processing Applications

Apple cultivars exhibit significant diversity in fruit quality traits, creating distinct consumption scenarios. This study aimed to assess the physicochemical parameters and sensory attributes differences among fifteen apple cultivars and identify characteristic qualities suitable for various processed apple products using chemometric analysis. Relatively large differences were registered between cultivars for deflection, peel color, titratable acidity (TA), the ratio of total soluble solid to titratable acidity (TSS/TA), hardness, soluble sugar, and volatile organic compound contents. Sensory results showed significant differences existed among the preferences for different processed products. Based on the above results, all cultivars could be distinguished into three main clusters. Cluster I (i.e., Aziteke, Bakeai, Magic Flute, Royal Gala, Red General, Red Delicious, and Zhongqiuwang) demonstrated favorable appearance, high sensory scores, and rich aroma volatile compounds, making them suitable for direct consumption. Cluster II (i.e., Fuburuisi, Sinike, Honglu, and Huashuo) exhibited a higher sugar and acid content, making them suitable for apple juice production. Cluster III (i.e., Miqila, Honey Crisp, Shandong Fuji, and Yanfu 3) were more suitable for fresh-cut apples due to their good flavor and undesirable appearance. Several chemometric analyses effectively assessed differences among apple cultivars.
Eating Behavior and Factors of Metabolic Health in Primary Schoolchildren: A Cross-Sectional Study in Greek Children

Childhood obesity has been associated with altered blood lipids and bad eating habits. In this cross-sectional study, we assessed cardiorespiratory fitness and metabolic health markers in regard to weight status and dietary habits in schoolchildren. In 134 children (6–11 years), we conducted: (1) Anthropometry, namely z-score BMI (z-BMI), waist-to-height ratio (WHtR), and body composition analysis. (2) Measurements of handgrip strength (HGS), resting metabolic rate (RMR) and VO2max. (3) Quantification of blood lipids and antioxidant vitamins A, E, C. (4) Eating breakfast assessment. About 35% of children were overweight/obese. The z-BMI positively correlated with WHtR (r = 0.637, p < 0.001), and adversely correlated with fat-free mass (r = −0.728, p < 0.001) and vitamin E (r = −0.286, p < 0.001). RMR and VO2max were greater in normal weight children compared to those with overweight/obesity (p < 0.001). HGS did not differ between these groups, but was negatively correlated with dyslipidemia as shown by TG/HDL-C ratio (r = −0.224, p = 0.037). According to regression analysis, eating breakfast routinely at home was positively associated with RMR and adversely associated with z-BMI. Hence, regular breakfast consumption at home may improve RMR in kids. Cardiorespiratory fitness and physical strength are key modulators of metabolic health in Greek children added to a social determinant of health i.e., eating breakfast at home.
Assessing the quality of sea surface temperature observations from drifting buoys and ships on a platform-by-platform basis

[1] This study investigates how the quality of sea surface temperature (SST) observations made by drifting buoys (drifters) and ships for 1996–2010 can be improved through retrospective quality control (QC) against a reference field. The observations used are a blend of delayed mode data taken from the International Comprehensive Ocean-Atmosphere Data Set (versions 2.0 and 2.5) and real time data obtained from the Global Telecommunication System. A comparison of drifter and ship measurements on a platform-by-platform basis to high-quality SST estimates from the Along track scanning radiometer Reprocessing for Climate (ARC) project reveals drifter observations are generally of good quality but frequently suffer from gross errors, whilst ship observations are generally of worse quality and show a diverse range of measurement errors. QC procedures are developed which similarly assess drifter and ship SST observations through comparison with the Met Office Operational SST and Sea Ice Analysis (OSTIA). These procedures make use of seasonal background error variance estimates now available for OSTIA. Drifter observations displaying some commonly observed gross errors are flagged and ship callsigns whose observations are deemed unreliable are blacklisted. Validation of the QC outcomes against ARC and Argo demonstrates that this retrospective QC improves the quality of drifter and ship observations, though some limitations are discussed.
Depth of response may predict clinical outcome in patients with recurrent/metastatic head and neck cancer treated with pembrolizumab-containing regimens

Background Pembrolizumab-containing regimens are standards of care for recurrent and metastatic head and neck squamous cell carcinoma (R/M HNSCC). The depth of response (DpR) predicts the survival of patients with several types of solid cancers; however, its association with the survival outcomes of patients with R/M HNSCC treated with pembrolizumab-containing regimens remains unclear. Methods This study included 66 patients with R/M HNSCC who received a pemblolizumab-containing regimen as a first-line therapy at Tohoku University Hospital, Sendai, Japan. The patients’ characteristics, combined positive score, baseline tumor size, tumor response, DpR, overall survival (OS), progression-free survival (PFS), PFS2, and adverse events were reviewed. The associations between DpR and survival outcomes were analyzed. Results The 1 year-OS and 1 year-PFS rates of pembrolizumab-containing regimens were 69.4% and 24.4%, respectively. The response rate was 28.8%. The mean and median values of tumor change from baseline were 5.1% and −9.0%. In the correlation analysis, a significant negative correlation was observed between tumor change rate from baseline and survival outcomes (OS: r= −0.41, p=0.0017; PFS: r=−0.49, p<0.001). In the multivariate analysis, DpR with tumor change of ≤−45 was associated with better OS and PFS. Conclusion DpR induced by pembrolizumab-containing regimens may be a predictive factor for OS and PFS in patients with R/M HNSCC.