Miracle-dz/UniFAR-FTUs huggingface dataset:
Suaeda australis and its associated rhizosphere microbiota: a comparison of the nutrient removal potential between different shrimp farm sediments in New Caledonia

Shrimp rearing generate organic waste that is trapped in the pond sediment. In excess, these wastes may impair aquaculture ecosystem and shrimps’ health. To promote the biological oxidation of accumulated organic waste, the pond is drained and dried at the end of each production cycle. However, this practice is not always conducive to maintaining microbial decomposition activities in sediments. Shrimp production in New Caledonia is no exception to this problem of pollution of pond bottoms. One promising way of treating this waste would be bioremediation, using a native halophyte plant and its microbiota. Thus, this study explored the nutrient removal potential of Suaeda australis and its microbiota on sediments from four shrimp farms. Suaeda australis was grown in an experimental greenhouse for 6 months. In order to mimic the drying out of the sediments, pots containing only sediments were left to dry in the open air without halophytes. An analysis of the chemical composition and active microbiota was carried out initially and after 6 months in the sediments of the halophyte cultures and in the dry sediments for each farm, respectively. In the initial state, the chemical parameters and the microbial diversity of the sediment varied considerably from one farm to another. Growing Suaeda australis reduced the nitrogen, phosphorus and sulfur content in all type of sediment. However, this reduction varied significantly from one sediment to another. The rhizosphere of Suaeda australis is mainly composed of micro-organisms belonging to the Alphaproteobacteria class. However, the families recruited from this class vary depending on the farm in question. Depending on the sediment, the variation in microbiota leads to different putative biochemical functions. For two of the farms, a similar reduction in nitrogen concentration was observed in both dry and cultivated sediments. This suggests that certain initial chemical characteristics of the sediments influence the nutrient removal efficiency of Suaeda australis. Our study therefore highlights the need to control the pH of sediments before cultivation or in dry sediments in order to ensure optimal microbial decomposition of organic waste and nutrient cycling.
A global model for present‐day atmospheric/soil CO2 consumption by chemical erosion of continental rocks (GEM‐CO2)

The flux of atmospheric/soil CO 2 consumed by chemical weathering of the continents ( F CO2 ) can be estimated from river fluxes of bicarbonates. Using published data for 232 small monolithologic watersheds, empirical relationships between F CO2 and runoff ( Q ) have been determined for the major rock types outcropping on the continents. For validation, the models fitted to these relationships are applied to the Garonne, Congo and Amazon river basins to calculate the average CO 2 consumption on these large river basins; the model results are close to previous estimates based on field measurements. The model (GEM-CO 2 : Global Erosion Model for CO 2 fluxes) is then applied at the global scale and allows the determination of latitudinal variations of the consumption of atmospheric/soil CO 2 by chemical erosion. The main results show that the consumption of CO 2 is mainly localized in the Northern hemisphere, because of large continental area with a high proportion of carbonate rocks, and in equatorial regions which are very humid. Finally, the mean annual CO 2 consumption for the whole continents amount to 0.26 Gt C y -1 , and 72% of this flux is removed in the Northern hemisphere. DOI: 10.1034/j.1600-0889.47. issue1.23. x
Communication-Efficient Decentralized Linear Precoding for Massive MU-MIMO Systems

Extremely large-scale (XL) massive multiple-input multiple-output (MIMO) antenna array is envisioned as a critical technology for future wireless communication systems. To effectively conduct precoding for XL massive MIMO antennas, a novel star decentralized baseband processing (DBP) paradigm has recently emerged. This new architecture distributively stores and processes the channel data of physically separated massive MIMO antenna segments using multiple decentralized units, which cooperate with a common central unit via fronthaul links. Although the star DBP architecture is promising, decentralized precoding schemes applicable to this framework have not yet been well investigated. In this article, we decentralize the classical eigen zero forcing (EZF) and weighted minimum mean square error (WMMSE) precoding schemes in the star DBP architecture. These decentralized algorithms yield identical performance with their centralized counterparts while requiring much lower fronthaul bandwidths. Moreover, to further improve fronthaul bandwidth efficiency, we propose two compression-then-communication based decentralized precoding schemes that have flexibly configurable compression ratios. Extensive numerical results are presented to verify the effectiveness of our solutions. Especially, our proposed compression-based decentralized WMMSE methods can achieve comparable performance with their non-compressed counterparts by requiring only a few percentages of the fronthaul bandwidth in low signal-to-noise-ratio regime.
Nano-Additive Manufacturing and Non-Destructive Testing of Nanocomposites

In the present work, the recent advancements in additive manufacturing (AM) techniques for fabricating nanocomposite parts with complex shaped structures are explained, along with defect non-destructive testing (NDT) methods. A brief overview of the AM processes for nanocomposites is presented, grouped by the type of feedstock used in each technology. This work also reviews the defects in nanocomposites that can affect the quality of the final product. Additionally, a detailed description of X-CT, ultrasonic phased array technology, and infrared thermography is provided, highlighting their potential application in non-destructive inspection of nanocomposites in the future. Lastly, it concludes by offering recommendations for the development of NDT methods specifically tailored for nanocomposites, emphasizing the need to utilize NDT methods for optimizing nano-additive manufacturing process parameters, developing new NDT techniques, and enhancing the resolution of existing NDT methods.
De las nuevas religiosidades urbanas : La Divina Revelación Alfa y Omega : Cristo vivió en Lima

La investigacion que presentamos a continuacion se ubica en el ambito que se conoce como "Antropologia de la Religion". Se trata del estudio de un grupo religioso de origen peruano, al que se le conoce como "La Hermandad del Cordero de Dios" o "La Divina Revelacion Alfa y Omega". Este es pues nuestro Objeto de Estudio.
Influence of Latrine Proximity and Type on Tubewell Water Quality and Diarrheal Disease in Bangladesh

Diarrheal diseases are endemic in Bangladesh, where sanitation is poor, and untreated drinking water extracted from shallow (<43 m) tubewells could partially contribute to disease propagation. This study measures the effects of local population–environment context on tubewell water quality and diarrheal disease incidence. The study site includes six villages in Matlab, Bangladesh, with approximately 12,000 residents. Study data include monthly Escherichia coli concentrations for 100 wells, monthly diarrheal events for all children under five, and a detailed water and sanitation infrastructure database created through a submeter accuracy Global Positioning System survey. We developed sanitation metrics to measure the relationship between tubewell water fecal contamination and estimates of human fecal loadings at varying scales. The relationship between childhood diarrhea and E. coli in drinking water was measured for households that obtained drinking water from survey wells. Results show that tubewells surrounded by unsanitary latrines, latrine-polluted ponds, and higher population densities were more frequently contaminated with fecal coliforms. The analysis also showed that poor sanitation infrastructure might affect childhood diarrheal disease via tubewell contamination. Our findings shed light on the importance of integrating population and environment data to identify circumstances in which shallow well water quality is compromised and children are put at risk of contracting diarrheal diseases. Sanitation interventions should highlight the spatial separation of latrines and drinking water wells to limit contamination.
Rates and Processes of Marsh Shoreline Erosion in Rehoboth Bay, Delaware, U.S.A.

The marsh shoreline in western Rehoboth Bay, Delaware, is rapidly eroding due to wave attack. A 30-90 cm vertical scarp characterizes the shoreline and exposes the present-day rootmat and the underlying mud unit. Using an Electronic Total Station surveying instrument, marsh erosion rates were determined for six 10-meter shoreline sections. Over a three-year period, averaged erosion rates ranged from 14 cm/yr to 43 cm/yr. Three styles of shoreline erosion were observed. (1) Cleft and neck formation-V-shaped notches are cut into an initially "straight" shoreline. Between adjacent clefts, marsh necks, up to three meters in length, occur creating an undulatory shoreline geometry. (2) Neck cut-off-marsh necks can be cut off from the marsh creating a small marsh "stack. " (3) Undercutting with rootmat toppling-wave action erodes the lower mud unit faster than the overlying rootmat creating an overhang that eventually topples into the bay. At a decimeter scale, shoreline geometry is due to successive changes in erosional style. In contrast, the geometry of a fringing marsh shoreline over several hundred meters is likely controlled by antecedent topography and not by lateral variations in erosion rates. Rates of erosion are correlated with wave power. The wave power potentially impinging on nine selected marsh shoreline sites was calculated using wind, bathymetric, and fetch data. Erosion rates for each site were plotted against estimated wave powers producing a regression equation that allows erosion rates to be predicted. As wave power increases, the rate of erosion increases.
Circulating donor-derived cell-free DNA as a marker for rejection after lung transplantation

Objective Recently, circulating donor-derive cell free DNA (dd-cfDNA) has gained growing attention in the field of solid organ transplantation. The aim of the study was to analyze circulating dd-cfDNA levels in graft rejection, ACR and AMR separately for each rejection type compared with non-rejection, and assessed the diagnostic potential of dd-cfDNA levels in predicting graft rejection after lung transplantation. Methods A systematic search for relevant articles was conducted on Medline, Web of Science, China National Knowledge Infrastructure (CNKI), and Wanfang databases without restriction of languages. The search date ended on June 1, 2023. STATA software was used to analyze the difference between graft rejection, ACR, AMR and stable controls, and evaluate the diagnostic performance of circulating dd-cfDNA in detecting graft rejection. Results The results indicated that circulating dd-cfDNA levels in graft rejection, ACR, and AMR were significantly higher than non-rejection (graft rejection: SMD=1.78, 95% CI: 1.31-2.25, I2 = 88.6%, P< 0.001; ACR: SMD=1.03, 95% CI: 0.47-1.59, I2 = 89.0%, P < 0.001; AMR: SMD= 1.78, 95% CI: 1.20-2.35, I2 = 89.8%, P < 0.001). Circulating dd-cfDNA levels distinguished graft rejection from non-rejection with a pooled sensitivity of 0.87 (95% CI: 0.80-0.92) and a pooled specificity of 0.82 (95% CI: 0.76-0.86). The corresponding SROC yield an AUROC of 0.90 (95% CI: 0.87-0.93). Conclusion Circulating dd-cfDNA could be used as a non-invasive biomarker to distinguish the patients with graft rejection from normal stable controls. Systematic Review Registration https://www.crd. york.ac. uk/prospero/, identifier CRD42023440467.
Perceptual Low-Rank Learning and Geometry-Preserving Feature Selection for Categorizing High-Resolution Aerial Photos

Recognizing the multiple categories of an high-resolution (HR) aerial photos is an indispensable technique in geoscience and remote sensing. In this work, a perceptual low-rank algorithm combined with a geometry-preserving feature selection (FS) is proposed for categorizing HR aerial photos. In practice, the theory of human visual perception indicates that for each scenery, the background non-salient regions are highly correlated, whereas the foreground visually/semantically salient regions are almost uncorrelated. Motivated by this, we design a novel low-rank algorithm that seeks a sparse set of foreground visually/semantically salient image patches. These patches are sequentially linked into a so- called GSP (path reflecting gaze movement) to mimick human vision system. Afterward, a geometry-preserving FS algorithm is proposed to select highly discriminative features from the aforementioned gaze features, wherein a classifier can be trained simultaneously. Comprehensive experimental validation on our Internet-scale image set have shown its superiority.
Research Opportunities in Microservices Quality Assessment: A Systematic Literature Review

—The growth in the development of microservices has sparked interest in evaluating their quality. This study seeks to determine the key criteria and challenges in evaluating microservices to drive research and optimize processes. The systematic review of the literature presented in this research identified that the most commonly used evaluation criteria are performance, scalability, security, cohesion, coupling, and granularity. Although evaluation tools exist, they mainly measure performance aspects such as latency and resource consumption. Challenges were identified in security, granularity, throughput, monitoring, organizational strategy, orchestration, choreography, scalability, decomposition, and monolith refactoring. In addition, research opportunities in empirical studies, analysis of quality trade-offs, and broadening of relevant perspectives and tools are noted. Challenges in the interrelation of quality attributes, metrics and patterns, automatic evaluation, architectural decisions and technical debt, domain-based design, testing, monitoring, and performance modeling are also highlighted. Challenges in orchestration, communication management and consistency between microservices, independent evolution, and scalability are also mentioned. Therefore, it is critical to address these particular challenges in microservices and to continue research to improve the understanding and practices related to quality.
Comparison of recurrent neural network and long-short term memory technique in predicting mortality rate in Malaysia

The Disease Control Division, Ministry of Health states that mortality data are a crucial tool for examining a community's health. Several studies have been conducted on developing a predictive model to predict the mortality rate but most of them are applying the standard machine learning models. Hence, this study is conducted with its main objective to develop the Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) models in predicting the general mortality rate in Malaysia and compare the predicted mortality rates between data with and without post-pandemic statistics. The death rate was investigated using the 2022 Revision of World Population Prospects, the twenty-seventh edition of official United Nations population estimates and projections issued by the Population Division of the United Nations Secretariat's Department of Economic and Social Affairs. A Z-test was employed to investigate if the 2021 and 2022 mortality rates bring any significant difference to the predicted mortality rates. The findings confirm the superiority of the LSTM model in accurately predicting mortality rates compared to RNN with the inclusion of post-pandemic data did not significantly affect the model's predictions. Overall, this study contributes to the understanding of Malaysian mortality rates and provides a foundation for future investigations in this field. The accuracy in predicting the future mortality rates, particularly in pandemic scenarios, remains challenging and requires further research.
Characteristics of the pulmonary microbiota in patients with mild and severe pulmonary infection

Background Lung infection is a global health problem associated with high morbidity and mortality and increasing rates of hospitalization. The correlation between pulmonary microecology and infection severity remains unclear. Therefore, the purpose of this study was to investigate the differences in lung microecology and potential biomarkers in patients with mild and severe pulmonary infection. Method Patients with pulmonary infection or suspected infection were divided into the mild group (140 cases) and the severe group (80 cases) according to pneomonia severity index (PSI) scores. Here, we used metagenomic next-generation sequencing (mNGS) to detect DNA mainly from bronchoalveolar lavage fluid (BALF) collected from patients to analyze changes in the lung microbiome of patients with different disease severity. Result We used the mNGS to analyze the pulmonary microecological composition in patients with pulmonary infection. The results of alpha diversity and beta diversity analysis showed that the microbial composition between mild and severe groups was similar on the whole. The dominant bacteria were Acinetobacter, Bacillus, Mycobacterium, Staphylococcus, and Prevotella, among others. Linear discriminant analysis effect size (LEfSe) results showed that there were significant differences in virus composition between the mild and severe patients, especially Simplexvirus and Cytomegalovirus, which were prominent in the severe group. The random forest model screened 14 kinds of pulmonary infection-related pathogens including Corynebacterium, Mycobacterium, Streptococcus, Klebsiella, and Acinetobacter. In addition, it was found that Rothia was negatively correlated with Acinetobacter, Mycobacterium, Bacillus, Enterococcus, and Klebsiella in the mild group through co-occurrence network, while no significant correlation was found in the severe group. Conclusion Here, we describe the composition and diversity of the pulmonary microbiome in patients with pulmonary infection. A significant increase in viral replication was found in the severe group, as well as a significant difference in microbial interactions between patients with mild and severe lung infections, particularly the association between the common pathogenic bacteria and Rothia. This suggests that both pathogen co-viral infection and microbial interactions may influence the course of disease. Of course, more research is needed to further explore the specific mechanisms by which microbial interactions influence disease severity.
Assessing Resilience to Sleep Loss Among the Italian Population: A 13-Item Model of the Iowa Resistance to Sleeplessness Test (iREST)

Purpose The present study aimed to validate the Italian version of the Iowa Resistance to Sleeplessness Test (iREST), a 16-item self-report assessing resilience to sleep debt in the affective, cognitive, and somatic domains. Participants and Methods We examined its factor structure, assessed internal consistency and criterion validity, and established test-retest reliability on 768 Italian native speakers (65.8% of women) with a mean age of 25.98 years old. Results Confirmatory factor analysis (CFA) revealed a new 13-item structure for the Italian iREST (iREST-13), demonstrating more satisfactory goodness-of-fit values, and exhibiting good internal consistency (Cronbach’s α ranging from 0.73 to 0.89), relative to the 16-item original version. Results supported the iREST convergent validity, showing significant independence from established measures of sleep; low correlations with conceptually unrelated measures supported divergent validity, indicating that the iREST effectively measures resistance to sleeplessness without confounding with other constructs. Lastly, test-retest reliability was evaluated by administering the iREST to the same sample with a 2-week interval: the significant correlations supported its temporal stability. Conclusion Further studies are needed to evaluate the applicability of the iREST in diverse populations and explore its relationship with objective sleep measures. Nevertheless, the Italian iREST provides a valuable tool for assessing resistance to sleep loss, offering insights into individual differences in resilience. Additionally, the iREST can assist in identifying individuals who require interventions to enhance resilience to sleep debt, as well as help clinicians evaluate the impact of chronic sleep disruption and deliver targeted interventions.
Three‐dimensional modeling of a magnetic reversal boundary from inversion of deep‐tow measurements

A near-bottom magnetic survey was conducted over the Brunhes/Matuyama reversal boundary near the East Pacific Rise crest at 21° N. Magnetic measurements were made on a level plane approximately 200 m above the sea floor using the Marine Physical Laboratory's deep-tow vehicle, with precise transponder navigation. Track density was high both parallel and perpendicular to the magnetic lineations in order to study fine scale deviations from two-dimensionality. The magnetic field on a gridded map was inverted to obtain the crustal magnetization distribution (including the effects of topography) by extension of the Fourier technique of Parker and Huestis [1974]. Linearity of sources parallel to the spreading center was not assumed, nor was upward continuation necessary in this treatment. We found that the polarity transition boundary is extremely straight and sharp and is very close to two-dimensional even on a scale of hundreds of meters. Deviations from two-dimensionality, however, occur within the magnetized blocks away from the transition zone. The polarity transition width is narrow, only 1000 m to 1400 m throughout the study area. This suggests a zone of crustal emplacement which is only 600–1000 m wide at the spreading center, which is in excellent agreement with geologic observations in the area. Comparisons are made with a two-dimensional treatment of the same data from profiles (i.e., assuming linearity of sources). These studies also document a long-wavelength (≈ 60 km) sinuosity in the trend of the magnetic anomalies. This sinuosity is the result of offsets of the spreading center which are not transform faults but which involve a component of strike slip motion subparallel to the spreading center.
Evaluation and optimization of hospital system in Chinese provinces: does mortality matter?

During the production process of goods and services, sometimes undesirable outputs are difficult to avoid. However, this aspect is often ignored. Hospitals produce patient care, but undesirable outputs do arise. The novelty of this paper is to introduce the mortality as an undesirable output into the derivation of the public hospital efficiency measure. Similar to the production of economic goods and pollution where the latter increase along with the former, our description of mortality in hospital is considered as weakly disposable. Based on an extension model of Kuosmanen (2005), we evaluate the public hospital efficiency with and without incorporating mortality under four scenarios. We apply this model to measure public hospital efficiency in Chinese provinces. The results indicate that no matter whether one considers undesirable outputs within the objective functions, it has a significant impact on benchmarking once the mortality is included to define the production technology.