Miracle-dz/UniFAR-FTUs huggingface dataset:
Impact of Seminal Plasma Antioxidants on DNA Fragmentation and Lipid Peroxidation of Frozen–Thawed Horse Sperm

Cryopreservation is a stressful process for sperm, as it is associated with an increased production of reactive oxygen species (ROS). Elevated ROS levels, which create an imbalance with antioxidant capacity, may result in membrane lipid peroxidation (LPO), protein damage and DNA fragmentation. This study aimed to determine whether the membrane LPO and DNA fragmentation of frozen–thawed horse sperm relies upon antioxidant activity, including enzymes (superoxide dismutase (SOD), glutathione peroxidase (GPX), catalase (CAT) and paraoxonase type 1 (PON1)); non-enzymatic antioxidant capacity (Trolox-equivalent antioxidant capacity (TEAC), plasma ferric reducing antioxidant capacity (FRAP) and cupric reducing antioxidant capacity (CUPRAC)); and the oxidative stress index (OSI) of their seminal plasma (SP). Based on total motility and plasma membrane integrity (SYBR14+/PI−) after thawing, ejaculates were hierarchically (p < 0.001) clustered into two groups of good- (GFEs) and poor-(PFEs) freezability ejaculates. LPO and DNA fragmentation (global DNA breaks) were higher (p < 0.05) in the PFE group than in the GFE group, with LPO and DNA fragmentation (global DNA breaks) after thawing showing a positive relationship (p < 0.05) with SP OSI levels and ROS production. In addition, sperm motility and membrane integrity after thawing were negatively (p < 0.05) correlated with the activity levels of SP antioxidants (PON1 and TEAC). The present results indicate that LPO and DNA fragmentation in frozen–thawed horse sperm vary between ejaculates. These differences could result from variations in the activity of antioxidants (PON1 and TEAC) and the balance between the oxidant and antioxidant components present in the SP.
Cultural Heritage Information Retrieval: Past, Present, and Future Trends

The importance of knowledge organization and information retrieval techniques has been evident throughout human history, becoming even more crucial in the digital age. While computer systems and the web have facilitated information retrieval, challenges arose with the increasing volume of data. The introduction of Semantic Web technologies aimed to enhance precision and accuracy by converting the web into a structured data format. The Cultural Heritage (CH) community has been at the forefront of adopting Semantic Web practices to promote interoperability and shared understanding. In this study, we present a comprehensive conceptual framework that spans cultural heritage, information modeling, and information retrieval. Our model addresses early solutions in knowledge organization systems, highlighting the evolution from classification systems and controlled vocabularies to the significance of metadata schemas. We delve into the limitations of traditional knowledge organization systems and the necessity of formal ontologies, particularly in the cultural heritage domain. The comparative analysis of CRM vs. EDM, ontology-based metadata interoperability, and ontology technologies elucidate our contributions to the field. This paper outlines the process from the initial steps of adopting Semantic Web technologies in the CH domain to the latest developments in CH information retrieval. In this paper, we also reviewed intelligent applications and services developed in the CH domain after establishing semantic data models and Knowledge Organization Systems. Finally, challenges and possible future research directions are discussed. The findings revealed that GLAMs (Galleries, Libraries, Archives, and Museums) are excellent and comprehensive sources of CH information. The CH community has put in a lot of time and effort to develop data models and knowledge organization tools; now it’s time to use this valuable resource to construct smart applications that are still in their early phases. This could benefit the CH industry even more.
Does digitalization enhance the effects of lean production on social performance?

PurposeThis study aims to investigate whether Industry 4.0 digital technologies can enhance the effects of lean production on social performance.Design/methodology/approachSurvey data collected from China’s manufacturing industry are used to test research hypotheses.FindingsThe results reveal that the three dimensions of lean production (internal, customer and supplier) have a significant positive effect on social performance and that digital technology advancement (DTA) positively moderates these relationships. DTA adds only a marginal contribution to social performance.Practical implicationsThis study addresses a new challenging question from manufacturing firms: how to integrate lean, technology and people? The empirical findings provide timely and insightful practical guidance for managers to better understand the role of digital transformation in the traditional lean context.Originality/valueWhile digitalization is known to complement lean production, this study shows digitalization also complements the effects of lean production on social performance.
HEALTH AND RELIGION RELATIONS IN NEW MEDIA : THE COMMODIFICATION OF RELIGION IN HEALTH PROMOTION DURING THE PANDEMIC ON @PROMKES_KALTENG

This study aims to analyze the commodification of religion in health promotion on the Instagram account @promkes_kalteng. Two aspects are the focus of the study in this research, namely the use of language and religious terms and the use of religious symbols. This study uses a qualitative method with a descriptive qualitative interactive media study approach. Data were obtained in two ways, namely observation and documentary studies. Specifically, the data obtained were analyzed using the Miles and Huberman model, namely data reduction, data verification, and conclusion. This study found two important points related to the commodification of religion in health promotion on the Instagram account @promkes_kalteng. First, three language or religious terms classifications are used in health promotion in the @promkes_kalteng account, related to the rituality, social, and health dimensions. The use of language or terms tends to legitimize the content of the message so that religious community groups can accept it. Second, the findings regarding using religious symbols in health promotion posts on the @promkes_kalteng account. The implications of these religious symbols are part of the tendency of the tool to transmit a message to strengthen the content of the message conveyed.
Advanced Data Processing of Pancreatic Cancer Data Integrating Ontologies and Machine Learning Techniques to Create Holistic Health Records

The modern healthcare landscape is overwhelmed by data derived from heterogeneous IoT data sources and Electronic Health Record (EHR) systems. Based on the advancements in data science and Machine Learning (ML), an improved ability to integrate and process the so-called primary and secondary data fosters the provision of real-time and personalized decisions. In that direction, an innovative mechanism for processing and integrating health-related data is introduced in this article. It describes the details of the mechanism and its internal subcomponents and workflows, together with the results from its utilization, validation, and evaluation in a real-world scenario. It also highlights the potential derived from the integration of primary and secondary data into Holistic Health Records (HHRs) and from the utilization of advanced ML-based and Semantic Web techniques to improve the quality, reliability, and interoperability of the examined data. The viability of this approach is evaluated through heterogeneous healthcare datasets pertaining to personalized risk identification and monitoring related to pancreatic cancer. The key outcomes and innovations of this mechanism are the introduction of the HHRs, which facilitate the capturing of all health determinants in a harmonized way, and a holistic data ingestion mechanism for advanced data processing and analysis.
A Bose-Einstein Condensate Achieved on a Persistent-supercurrent Atom Chip

A persistent-supercurrent atom chip is a quantum device designed with a view to transcending the limits of conventional technologies by employing some of the significant properties of quantum mechanics. We have applied this novel technique to achieve an atomic gas in a macroscopic quantum state in the vicinity of a solid-state surface. In this article, we review a technique for making an extremely stable Bose-Einstein condensate above a chip surface and describe our attempts to overcome several unpre-dicted problems introduced by superconductivity.
3D Time-Domain Airborne EM Inversion with Finite-Volume Method

We investigate an algorithm for 3D time-domain AEM inversion with the finite-volume and direct Gauss-Newton methods. We separate a spatially varying secondary field from the 1D background in time-domain, and constrain the calculation to be within the small volume of influence of airborne EM secondary source, resulting in more compact discretization. To demonstrate the validity and merits of 3D inversion, we first compare the results with 1D inversion on synthetic data for a horizontal conductor and a dipping plate, which shows that both methods can well recover the horizontal conductor, while only 3D inversion can offer good recovery for the dipping plate. We apply our 3D algorithm to invert GEOTEM data obtained over the Lisheen deposit in Ireland to map the sulphides at depth and obtain similar results to 1D inversion but with better data fitting, further showing the effectiveness of our 3D inversion algorithm.
Weakly Supervised Depth Estimation for 3D Imaging with Single Camera Fringe Projection Profilometry

Fringe projection profilometry (FPP) is widely used for high-accuracy 3D imaging. However, employing multiple sets of fringe patterns ensures 3D reconstruction accuracy while inevitably constraining the measurement speed. Conventional dual-frequency FPP reduces the number of fringe patterns for one reconstruction to six or fewer, but the highest period-number of fringe patterns generally is limited because of phase errors. Deep learning makes depth estimation from fringe images possible. Inspired by unsupervised monocular depth estimation, this paper proposes a novel, weakly supervised method of depth estimation for single-camera FPP. The trained network can estimate the depth from three frames of 64-period fringe images. The proposed method is more efficient in terms of fringe pattern efficiency by at least 50% compared to conventional FPP. The experimental results show that the method achieves competitive accuracy compared to the supervised method and is significantly superior to the conventional dual-frequency methods.
Estimation of instantaneous peak flows from maximum mean daily flows using the HBV hydrological model

The record length and quality of instantaneous peak flows (IPFs) have a great influence on flood design, but these high resolution flow data are not always available. The primary aim of this study is to compare different strategies to derive frequency distributions of IPFs using the Hydrologiska Byråns Vattenbalansavdelning (HBV) hydrologic model. The model is operated on a daily and an hourly time step for 18 catchments in the Aller‐Leine basin, Germany. Subsequently, general extreme value (GEV) distributions are fitted to the simulated annual series of daily and hourly extreme flows. The resulting maximum mean daily flow (MDF) quantiles from daily simulations are transferred into IPF quantiles using a multiple regression model, which enables a direct comparison with the simulated hourly quantiles. As long climate records with a high temporal resolution are not available, the hourly simulations require a disaggregation of the daily rainfall. Additionally, two calibrations strategies are applied: (1) a calibration on flow statistics; (2) a calibration on hydrographs.
L1−2 minimization for exact and stable seismic attenuation compensation

S U M M A R Y Frequency-dependent amplitude absorption and phase velocity dispersion are typically linked by the causality-imposed Kramers–Kronig relations, which inevitably degrade the quality of seismic data. Seismic attenuation compensation is an important processing approach for enhancing signal resolution and fidelity, which can be performed on either pre-stack or post-stack data so as to mitigate amplitude absorption and phase dispersion effects resulting from intrinsic anelasticity of subsurface media. Inversion-based compensation with L1 norm constraint, enlightened by the sparsity of the reflectivity series, enjoys better stability over traditional inverse Q filtering. However, constrained L1 minimization serving as the convex relaxation of the literal L0 sparsity count may not give the sparsest solution when the kernel matrix is severely ill conditioned. Recently, non-convex metric for compressed sensing has attracted considerable research interest. In this paper, we propose a nearly unbiased approximation of the vector sparsity, denoted as L1−2 minimization, for exact and stable seismic attenuation compensation. Non-convex penalty function of L1−2 norm can be decomposed into two convex subproblems via difference of convex algorithm, each subproblem can be solved efficiently by alternating direction method of multipliers. The superior performance of the proposed compensation scheme based on L1−2 metric over conventional L1 penalty is further demonstrated by both synthetic and field examples.
Identification and validation of prognostic and immunotherapeutic responses in esophageal squamous carcinoma based on hypoxia phenotype-related genes

The study aimed to investigate the clinical significance of the interaction between hypoxia and the immune system in esophageal squamous cell carcinoma (ESCC) microenvironment. A comprehensive evaluation of 13 hypoxia phenotype-related genes (HPRs) was conducted using data from TCGA-ESCC and two GEO cohorts. Three distinct HPRclusters were identified, and the HPRscore was established as an independent prognostic factor (p = 0.001), with higher scores indicating poorer prognosis. The HPRscore was validated in various immunotherapy cohorts, demonstrating its efficacy in evaluating immunotherapy and chemotherapy outcomes. Additionally, phenome-wide association study (PheWAS) analysis showed that PKP1 had no significant correlation with other traits at the gene level. PKP1 was identified as a potential prognostic marker for ESCC, with upregulated expression observed in ESCC patients. In vitro experiments showed that the knockdown of PKP1 inhibited ESCC cell proliferation and migration. These findings suggest that the novel HPRscore and PKP1 may serve as prognostic tools and therapeutic targets for ESCC patients.
Timeseries partitioning of ecosystem respiration components in seasonal, non-tropical forests; comparing literature derived coefficients with evaluation at two contrasting UK forest sites

Understanding carbon flows within ecosystems is key to quantifying the impacts of land-use change in the climate. However, while the net exchange of CO2 between the ecosystem and atmosphere indicates global warming potentials, partitioning into individual flux components is needed to understand sinks and sources, residence times, and sensitivities to land-use impacts. Scaling from research site to region requires modelling evaluated against in situ measurements, but there is often a mismatch between outputs of process models (e.g., soil heterotrophic respiration (Rh)) and site-measured parameters (e.g., total soil surface respiration (Rs) or whole ecosystem respiration (Re)). This study took a literature review approach to determine fractional coefficients for estimating Rh from Re or Rs and considered whether these fractions differed across a year in seasonal forests, where relative contributions of root respiration might be expected to vary between growing and dormant seasons. Compiled timeseries data were grouped by forest type (broadleaf, needleleaf, and mixed), and coefficients for a fraction of each component (Rs or Re) that Rh represented were calculated using two approaches, namely a simple annual mean value over all months and individual monthly means. These coefficients were then used to estimate Rh separately from higher-level fluxes (Re from eddy covariance and Rs from soil chambers), measured concurrently at two UK forest sites, and compared to Rh estimated from the same datasets using previously published generic coefficients as well as to concurrently measured Rh and Re.Both approaches resulted in much closer convergence of the two separate estimates of Rh (derived from Re or Rs) than previously published coefficients, particularly for Rh/Re coefficients that had previously been measured under peatland blanket bog rather than forest.This result suggests that land cover is an important factor in determining the relative contribution of heterotrophic respiration to higher-level fluxes and that the coefficients used would ideally be derived from studies on similar ecosystems.
The impact of the COVID-19 pandemic exposure on the corporate cash policy of Vietnam-listed enterprises

The purpose of this study was to assess the impact of the COVID-19 epidemic on the daily stock returns of 177 businesses listed on the Vietnam Stock Exchange during the period spanning from the second quarter of 2020 to the first quarter of 2023. Next, we proceed to evaluate the influence of COVID-19 exposure on the cash holding ratio of these enterprises. We used research methods for panel data, such as the fixed effects method and the system GMM method. Our findings demonstrate that the exposure of enterprises to the COVID-19 pandemic has a discernible and statistically significant adverse effect on their financial reserves. When conducting research on the transmission channel of COVID-19 exposure to cash holding policies, we found that this impact persists in firms through financial frictions. Based on the findings, we have put forth several policy implications for businesses to formulate cash management policies in anticipation of future pandemics of a similar nature.
Assessing nighttime lights for mapping the urban areas of 50 cities across the globe

Nighttime data from the Defense Meteorological Satellite Program Operational Linescan System have been widely used to map urban/built-up areas (hereafter referred to as “built-up area”), but to date there has not been a geographically comprehensive evaluation of the effectiveness of using nighttime lights data to map urban areas. We created accurate, convenient, and scalable grid cells based on Defense Meteorological Satellite Program/Operational Linescan System nighttime light pixels. We then calculated the density of Landsat-derived built-up areas within each grid cell. We explored the relationship between Defense Meteorological Satellite Program/Operational Linescan System nighttime lights data and the density of built-up areas to assess the utility of nighttime lights for mapping urban areas in 50 cities across the globe. We found that the brightness of nighttime lights was only in moderate agreement with the density of built-up areas; moreover, correlations between nighttime lights and Landsat-derived built-up areas were weak. Even in relatively sparsely populated urban regions (where the density of the built-up area is less than 20%), the highest correlation coefficient (R2) was only 0.4. Furthermore, nighttime lights showed lighted areas that extended beyond the area of large cities, and nighttime lights reduced the area of small cities. The results suggest that it is difficult to use the regression model to calibrate the Defense Meteorological Satellite Program/Operational Linescan System nighttime lights to fit urban built up areas.
Systematics, palaeoecology and taphonomy of Turonian oysters from the northern Gabon Coastal Basin

ABSTRACT The systematic, paleoecology and taphonomy of the Turonian (Azilé Formation) oysters fauna from the geological section PK 12, South of Libreville - Gabon, are carried out. Twelve species from seven genera are described. Genera Curvostrea Vyalov, 1936 ; Gryphaeostrea Conrad, 1865 ; Gyrostrea Mirkamalov, 1963 ; Ilymatogyra Stenzel, 1971 ; Ostrea Linnaeus, 1758 ; Rhynchostreon Bayle, 1878 and all species are recorded herein for the time in Gabonese coastal basin. The assemblage is dominated by representatives of the genus Ostrea and can be regarded as parautochthonous. The oyster shells are thin and thick with medium to large size. The paleoecological study indicates a nearshore shallow marine environment with high energy, nutrient-rich and well oxygenated water column. Taphonomic observations show that shells of oyster are affected by disarticulation. Bioerosion, traces of predators and encrustation are scarcity or absence. Abrasion, breackage and high fragmentation of shell are generally lacking.
MetricSifter: Feature Reduction of Multivariate Time Series Data for Efficient Fault Localization in Cloud Applications

Automated fault localization in large-scale cloud-based applications is challenging because it involves mining multivariate time series data from large volumes of operational monitoring metrics. To improve localization accuracy, automated fault localization methods incorporate feature reduction to reduce the number of monitoring metrics unrelated to a failure. However, these methods have problems with inaccuracy, either from removing too many failure-related metrics or from retaining too few failure-unrelated metrics. In this paper, we present MetricSifter, a feature reduction framework designed to accurately identify anomalous metrics caused by faults. Our framework locates a failure time window with the highest density of fault-induced change point times across monitoring metrics with a focus on their temporal proximity. Experimental results indicate that MetricSifter achieves an accuracy of 0.981, which is significantly better than the selected baseline methods. Furthermore, experiments combining various reduction methods with various localization methods demonstrate that MetricSifter improves the recall and time efficiency over the baseline methods.
Characteristics of Ethiopia Air Chemistry and Its Meteorological Context

The concentration of trace gases and aerosols in Ethiopia is poorly characterized due to a limited history of surface measurements. Here, satellite measurements and model estimates of atmospheric composition are employed to understand space–time distributions in the period 2000–16. Methane (CH4) and carbon monoxide (CO) display high concentrations over the highlands and provide a focus for analysis of monthly and daily data. CH4 emissions from livestock peak at the beginning of the dry season, while CO from biomass burning rises at the end of the dry season. The seasonal cycle of dust, aerosol optical depth (AOD), and CO2 is inversely related with CH4, while CO closely follows sensible heat flux, thus linking drying and rural biomass burning. Stable easterly flow in the dry season accumulates local emissions, so near-surface concentrations of CO and CH4 are high then. The weather pattern underlying an episode of high nitrogen dioxide (NO2) concentrations was studied. In addition to a stable lapse rate and dry anticyclonic weather, midtropospheric subsidence was related to intrusion of the northern subtropical jet stream on 24–26 December 2010. The wind shadow was cast by the Rift Escarpment limited dispersion, particularly with the dry, stable weather conditions. A key outcome of this work is that CH4 concentrations over Ethiopia are high in global context and have increased >0.1 ppm from 2002 to 2016; hence, there is a need to improve livestock management and production efficiency.