Miracle-dz/UniFAR-FTUs huggingface dataset:
6. DEVELOPMENT OF A HIGH-QUALITY NATURAL GAMMA DATA SET FROM THE CEARA RISE: CRITICAL GROUNDWORK FOR CORE AND LOG DATA INTEGRATION 1

Natural gamma-ray emissions are potentially powerful indicators of terrigenous sediment composition. At the Ceara Rise, such data can provide insight to the evolution of terrigenous suxes from the South American continent during the late Neogene. Although log-derived natural gamma emissions data have relatively lower noise levels than core-derived data, they are limited by a vertical resolution on the order of 0.5 - 1 m. Conversely, natural gamma-ray emissions data collected from cored sediments during Leg 154, although noisier, have a depth resolution on the order of 10 cm. Thus, the core data provide both a strong complement to downhole measurements of natural gamma as well as higher vertical (depth) resolution. Combining the two measurements provides for reconstruction of variations in terrigenous sedimentation over the past 35 m.y. encompassing both orbital (~0.01 - ~0.1 m.y.) and tectonic (>0.1 m.y.) time scales. In this paper we present a method to obtain robust discretely sampled, core-derived natural gamma-ray data from multiple holes. A OstackedO data set derived from multiple holes has less noise (lower mean square error) at all natural gamma-ray emissions channels, and thus is superior to core-derived natural gamma data taken from a single APC/XCB hole. A comparison of the stacked core-derived natural gamma data to the logderived natural gamma data for a 12-m.y. -long Neogene sequence from Site 926 documents the general attenuation of logderived measurements relative to stacked core-derived measurements for most orbital-scale and tectonic-scale oscillations. This result suggests that high-quality core-derived measurements of natural gamma-ray emissions can, under the correct circumstances, provide superior resolution and reliability to log-derived measurements over a large range of time scales.
Webpage Validation by Visualizing Importance Area

Web designers should develop webpages that are easy to navigate and engage users. However, an aesthetic design does not guarantee usability. Users tend to avoid webpages with low usability, resulting in poor service and sales. One cause of inadequate usability is the difference between the intended content and what the users see on the webpage. On the other hand, visual saliency is the ease with which the human eye notices something. Visual saliency maps (VSMs) are used to recognize areas in an image where people pay attention. VSMs often represent the visual features of landscapes and human faces. Here, we propose a method to generate a webpage-specific VSM based on the layout. Our method computes and visualizes the visual salience level for each webpage element, allowing web designers to easily recognize webpage elements with a high visual prominence. An evaluation revealed that the quality of VSMs generated by our method is higher than those generated by existing methods. Moreover, the VSMs generated by our method are easier to recognize than those of existing methods.
A Two-Big-Leaf Model for Canopy Temperature, Photosynthesis, and Stomatal Conductance

The energy exchange, evapotranspiration, and carbon exchange by plant canopies depend on leaf stomatal control. The treatment of this control has been required by land components of climate and carbon models. Physiological models can be used to simulate the responses of stomatal conductance to changes in atmospheric and soil environments. Big-leaf models that treat a canopy as a single leaf tend to overestimate fluxes of CO 2 and water vapor. Models that differentiate between sunlit and shaded leaves largely overcome these problems. A one-layered, two-big-leaf submodel for photosynthesis, stomatal conductance, leaf temperature, and energy fluxes is presented in this paper. It includes 1) an improved two stream approximation model of radiation transfer of the canopy, with attention to singularities in its solution and with separate integrations of radiation absorption by sunlit and shaded fractions of canopy; 2) a photosynthesis‐stomatal conductance model for sunlit and shaded leaves separately, and for the simultaneous transfers of CO 2 and water vapor into and out of the leaf—leaf physiological properties (i.e., leaf nitrogen concentration, maximum potential electron transport rate, and hence photosynthetic capacity) vary throughout the plant canopy in response to the radiation‐weight time-mean profile of photosynthetically active radiation (PAR), and the soil water limitation is applied to both maximum rates of leaf carbon uptake by Rubisco and electron transport, and the model scales up from leaf to canopy separately for all sunlit and shaded leaves; 3) a well-built quasi-Newton‐Raphson method for simultaneous solution of temperatures of the sunlit and shaded leaves. The model was incorporated into the Common Land Model (CLM) and is denoted CLM 2L. It was driven with observational atmospheric forcing from two forest sites [Anglo-Brazilian Amazonian Climate Observation Study (ABRACOS) and Boreal Ecosystem‐Atmosphere Study (BOREAS)] for 2 yr of simulation. The simulated fluxes by CLM 2L were compared with the observations, and with the results by the CLM with a single bigleaf scheme (CLM 1L) and by the CLM with the assimilation‐stomatal conductance scheme of NCAR Land Surface Model (LSM). The results showed that CLM 2L was an improvement compared to the CLM 1L and the CLM for the test cases of tropical evergreen broadleaf land cover and coniferous boreal forest.
Together We Can Face On: Co-parenting and Parental Stress on Mothers During the Covid 19 Pandemic

A mother becomes a figure who has a central role in the family, one of which is in terms of parenting. However, when carrying out the role of parenting, it is not always easy. Difficult conditions and situations will be encountered and allow stress to arise. The situation difficulty coupled with the occurrence of the covid-19 pandemic causes all activities to be carried out at home and adds to the work to become children's learning companions and to take care of family needs. The condition can make the mother feel pressure for the demands faced, causing stress. Looking at this, the researchers assessed a thing that can affect the stress of mothers when raising children (parental stress) is the involvement of partners in parenting (co-parenting). This study aims to prove, namely how the effect of co-parenting on parental stress in mothers, especially during the covid-19 pandemic. In the process, this study involved 62 mothers as research respondents by providing research questionnaires. The research questionnaire consisted of a co-parenting scale and a parental stress scale. The results of data analysis obtained by simple regression analysis showed that there was an effect of co-parenting on parental stress in mothers during the covid-19 pandemic (p < 0.05). The output are that the role of partners in working together to care for and care for children can reduce the stress felt by mothers.
How Do Work Discipline, Compensation And Competence Influence Employee Productivity?

Islamic banks require employee productivity, where employee productivity indicates the continuity of bank business productivity. This research aims to analyze the extent to which work discipline, compensation, and competence impact employee productivity. The research uses a quantitative approach with primary data in the form of a questionnaire. The data analysis technique uses partial least squares structural equation statistical modelling, and data processing is carried out using SmartPLS 3.0 software. The population of this study was all employees of Bank Muamalat, Yogyakarta’s main branch office (MBO), totalling 65 people. The research sample consisted of 65 employees selected using a saturated sampling procedure. The research results show a positive and statistically significant impact between work discipline and employee productivity. However, the results of this study did not identify a significant impact between compensation and competency on employee productivity. The results of this research can complement existing theories and can be used as material for consideration and information for Bank Muamalat Yogyakarta’s MBO in making decisions to increase employee productivity.
Detection of Big Five personality traits in Twitter user's profiles based on textual posts

Personalidade descreve o comportamento das pessoas e pode influenciar suas escolhas e tomadas de decisão. Uma das métricas mais consolidadas para traços de personalidade é o Big Five. Poucos trabalhos foram produzidos para detecção dos mesmos a partir de textos em português compartilhados em redes sociais. O objetivo do presente trabalho consiste na construção de um conjunto de dados com tweets em português rotulados com o traço de personalidade dominante e verificar o seu potencial de uso em modelos de aprendizado de máquina clássicos. No experimento realizado, os algoritmos de aprendizado de máquina apresentaram desempenho superior com a inclusão da técnica SMOTE e o melhor resultado foi Regressão Logística com TF-IDF unigram.
A Polyamidoamine-Based Electrochemical Aptasensor for Sensitive Detection of Ochratoxin A

Sensitive detection of ochratoxin A (OTA) is significant and essential because OTA may pose risks to human and animal health. Here, we developed an electrochemical aptasensor for OTA analysis using polyamidoamine (PAMAM) dendrimers as a signal amplifier. As a carrier, PAMAM has numerous primary amino groups that can be coupled with thiolated complementary strand DNA (cDNA), allowing it to recognize aptamers bound to the surface of horseradish peroxidase (HRP)-modified gold nanoparticles (AuNPs), thereby improving the sensitivity of the aptasensor. When monitoring the positive samples, OTA was captured by the aptamer fixed on the HRP-conjugated AuNP surface by specific recognition, after which the formed OTA-aptamer conjugates were detached from the electrode surface, ultimately decreasing the electrochemical signal monitored by differential pulse voltammetry. The novel aptasensor achieved a broad linear detection range from 5 to 105 ng L−1 with a low detection limit of 0.31 ng L−1. The proposed aptasensor was successfully applied for OTA analysis in red wine, with recovery rates ranging from 94.15 to 106%. Furthermore, the aptasensor also exhibited good specificity and storage stability. Therefore, the devised aptasensor represents a sensitive, practical and reliable tool for monitoring OTA in agricultural products, which can also be adapted to other mycotoxins.
The Effect of Weather Induced Internal Migration on Local Labor Markets: Evidence from Sub-Saharan Africa. ∗

Relying on census data collected in 2002 in Senegal and Uganda, we estimate the impact of weather induced internal migration on the probability for non migrants living in the destination regions to be employed. Our results show that a 10 percentage point increase in the weather induced net in-migration rate decreases this probability by 2.5 percentage points. A sensitivity analysis shows that this negative effect is not uniform across rural-urban status, gender, age and education. More precisely, weather induced net in-migration rate has a negative effect only on the employment status of non migrants living in rural areas (it has no effect on those living in urban areas). Moreover, this negative effect is stronger for female, for younger and for less educated individuals.
Novel Nanotherapeutic Systems Based on PEGylated Squalene Micelles for Enhanced In Vitro Activity of Methotrexate and Cytarabine

Nanomedicine has garnered significant attention due to the advantages it offers in the treatment of cancer-related disorders, some of the deadliest diseases affecting human lives. Conventional medication formulations often encounter issues of instability or insolubility in biological environments, resulting in low bioavailability. Nanocarriers play a crucial role in transporting and safeguarding drugs at specific sites of action, enabling gradual release under particular conditions. This study focuses on methotrexate (MTx) and cytarabine (Cyt), essential antitumoral drugs, loaded into PEGylated squalene micellar structures to enhance therapeutic effectiveness and minimize drawbacks. The micelles were prepared using ultrasound-assisted methods in both water and phosphate buffer saline solutions. Evaluation of drug-loaded micelles encompassed parameters such as particle size, colloidal stability, surface charge, morphology, encapsulation efficiency, drug loading capacity, and in vitro release profiles under simulated physiological and tumoral conditions. In vitro cell inhibition studies conducted on MCF-7 and HeLa cell lines demonstrated higher antitumoral activity for the drug-encapsulated micelles compared to free drugs. The encapsulation effectively addressed the burst effect, providing sustained release for at least 48 h while enhancing the drug’s protection under physiological conditions.
Automation of Legal Precedents Retrieval: Findings from a Literature Review

Judges frequently rely their reasoning on precedents. Courts must preserve uniformity in decisions while, depending on the legal system, previous cases compel rulings. The search for methods to accurately identify similar previous cases is not new and has been a vital input, for example, to case-based reasoning (CBR) methodologies. This literature review offers a comprehensive analysis of the advancements in automating the identification of legal precedents, primarily focusing on the paradigm shift from manual knowledge engineering to the incorporation of Artificial Intelligence (AI) technologies such as natural language processing (NLP) and machine learning (ML). While multiple approaches harnessing NLP and ML show promise, none has emerged as definitively superior, and further validation through statistically significant samples and expert-provided ground truth is imperative. Additionally, this review employs text-mining techniques to streamline the survey process, providing an accurate and holistic view of the current research landscape. By delineating extant research gaps and suggesting avenues for future exploration, this review serves as both a summation and a call for more targeted, empirical investigations.
Security-Reliability Analysis in CR-NOMA IoT Network Under I/Q Imbalance

This paper presents a controllable analysis framework for evaluating the reliability and security of underlay cognitive radio networks (CRs) relying on non-orthogonal multiple access (NOMA). In such systems, a secondary base station (BS) transmits confidential information to multiple secondary users uniformly distributed in the presence of a nearby located external eavesdropper. Moreover, transmit power constraints are introduced to limit the interference to the primary imposed by cognitive base stations. As an effective approach of multiple input single output (MISO) systems, the transmit antenna selection (TAS) is selected in the BS to improve the secrecy performance of the primary networks. Furthermore, we first consider the impact of quadrature-phase imbalance (IQI) to characterize the secure performance of the considered network in practice. Then, the degraded performance is evaluated in terms of outage probability (OP), intercept probability (IP), and effective secrecy throughput (EST) of two NOMA users. The optimal EST can be achieved through simulations while the results of OP and IP provide guidelines in the design of IQI-aware CR-NOMA systems. Finally, the trade-off between OP and IP with transmit signal-to-noise ratio (SNR) at the BS is investigated for reflecting the security characteristic. Finally, the trade-off between OP and IP with transmit signal-to-noise ratio (SNR) at the BS is studied for displaying the security characteristic. Numerical results show that increasing the number of transmit antennas at the BS and other main parameters improves performance. Moreover, when the system parameters are reasonably set, the secondary NOMA user in CR-NOMA can be reached secure requirements regardless of the controlled IQI.
Data stream clustering using complex networks

O agrupamento em fluxo de dados é uma tarefa de aprendizado de máquina crucial para vários sistemas que geram dados de maneira contínua e carecem de analisá-los ininterruptamente. Através de recursos oferecidos pela plataforma MOA (Massive Online Analysis), a proposta desta pesquisa consiste em aplicar modelos de aprendizado baseados em redes complexas na fase offline do CluStream, na qual micro-grupos são agrupados através do algoritmo kMeans. Para os experimentos desse projeto, foram consideradas três bases de dados e várias medidas de desempenho específicas ao problema. Os resultados mostraram que o uso de redes complexas apresenta desempenho competitivo, chegando a superar o método tradicional k-Means em diversos cenários.
Risk and preventing of COVID-19 grounded aircraft-value, risks and resilience: an ongoing debate

ABSTRACT Design/methodology/approach This paper used pervious related to aviation literatures to summarise and viewpoint the current aviation environment and conduct the risks, value, and resilience of grounded aircraft-value in the post-pandemic era. Purpose Throughout 2020 to date, this major event, known as SARS CoV-2, has had a decisive impact on global air transport. Since the outbreak began, passenger travel has declined due to infection risks and new laws and travel restrictions. Dependent Surveillance-Despite the recent recovery in demand from the airline industry, risks posed by new models remain a concern for many airlines. From the data of Broadcasting (ADS-B) is helpful for preliminary observation and judgment of the value level of a certain type of aircraft. Findings This paper not only focuses on the aviation environment, but discusses aviation highlights such as international perspectives, domestic (i.e. Taiwan) perspectives, and several issues between industry and academic perspectives. Research limitations/implications The next phase of research needed in this area is a closer assessment of the value of aircraft in the development of global networks, which could have important policy implications for aircraft manufacturers and the aviation industry. Originality/value This paper provides a contemplative perspective about the aviation industry.
$\alpha$-Fair Resource Allocation for Downlink Multiuser Short Packet Communications

Short packet communications are promising techniques to satisfy the stringent latency requirements of delay sensitive applications. Existing works on short packet communications considered either sum throughput maximization or max-min throughput maximization, which correspond to zero fairness and absolute fairness among devices, respectively. Different from that, this paper adopts the <inline-formula><tex-math notation="LaTeX">$\alpha$</tex-math></inline-formula>-fairness metric, which offers a controllable fairness, and investigates the resource allocation problem in a downlink multiuser short packet communication system to maximize the sum <inline-formula><tex-math notation="LaTeX">$\alpha$</tex-math></inline-formula>-fair utility by optimizing the bandwidth unit allocation, power allocation and decoding error probability. A suboptimal solution is derived based on the block coordinate descent method and the successive convex approximation method. The effectiveness of the proposed solution in achieving flexible tradeoff between fairness and sum throughput is demonstrated by simulation results.
Comparative secretomic and proteomic analysis reveal multiple defensive strategies developed by Vibrio cholerae against the heavy metal (Cd2+, Ni2+, Pb2+, and Zn2+) stresses

Vibrio cholerae is a common waterborne pathogen that can cause pandemic cholera in humans. The bacterium with heavy metal-tolerant phenotypes is frequently isolated from aquatic products, however, its tolerance mechanisms remain unclear. In this study, we investigated for the first time the response of such V. cholerae isolates (n = 3) toward the heavy metal (Cd2+, Ni2+, Pb2+, and Zn2+) stresses by comparative secretomic and proteomic analyses. The results showed that sublethal concentrations of the Pb2+ (200 μg/mL), Cd2+ (12.5 μg/mL), and Zn2+ (50 μg/mL) stresses for 2 h significantly decreased the bacterial cell membrane fluidity, but increased cell surface hydrophobicity and inner membrane permeability, whereas the Ni2+ (50 μg/mL) stress increased cell membrane fluidity (p < 0.05). The comparative secretomic and proteomic analysis revealed differentially expressed extracellular and intracellular proteins involved in common metabolic pathways in the V. cholerae isolates to reduce cytotoxicity of the heavy metal stresses, such as biosorption, transportation and effluxing, extracellular sequestration, and intracellular antioxidative defense. Meanwhile, different defensive strategies were also found in the V. cholerae isolates to cope with different heavy metal damage. Remarkably, a number of putative virulence and resistance-associated proteins were produced and/or secreted by the V. cholerae isolates under the heavy metal stresses, suggesting an increased health risk in the aquatic products.
Rekruttering til ASA-styrer etter innføring av kvoteringsregelen

Hovedspørsmålet som stilles i artikkelen, er om kvoteringsregelen har ført til at allmennaksjeselskapenes måte å rekruttere til styrer på er blitt endret. Er det slik at de nye kvinnene i ASA-styrene primært er rekruttert fordi de er familie og venner av eksisterende styremedlemmer? Eller er det kanskje slik at selskapene måtte ty til hodejegere og databaser for å komme i kontakt med et tilstrekkelig antall kompetente kvinner? Det ser ikke slik ut. Undersøkelsen viser at kvinner rekrutteres til ASA-styrer på samme måte som menn og på samme måte som før kvoteringsregelen ble innført, nemlig gjennom aksjonærenes, administrasjonens og valgkomitémedlemmenes egne profesjonelle sosiale nettverk.
Monthly variations of physical and chemical properties observed in Santos Bay and Santos Estuarine channel

Vertical profiles of physical (temperature and salinity) and chemical (ammonium, phosphate and silicate) properties were monthly obtained in seven oceanographic stations located in Santos Bay and in Santos channel, as part of a project which aims to determine the influence of the Santos estuarine system on the adjacent continental shelf. The fieldwork was carried out during the spring tides, from November/2004 until December/2005. Hydrographic measurements were made by a CTD and data were interpolated at 0.5 m depth intervals. Hydrographic structure was analyzed by the vertical profiles and T-S Diagram. Nutrients were sampled at surface, midwater and close to the bottom. The time-space variation of the average values obtained at each station was analyzed based on the hydrographic data. The channel waters represented an important source of nutrients to the bay. Whatever the hydrographic structure, these inputs occurs through the channel plume along the whole year, enhanced by rainfall events.
A Deep Learning Application for Psoriasis Detection

Nesse artigo é apresentado um estudo comparativo do desempenho de três modelos de Redes Neurais Convolucionais, ResNet50, Inception v3 e VGG19 para classificação de imagens de pele com lesões afetadas por psoríase. As imagens utilizadas para o treinamento e validação dos modelos foram obtidas em plataformas especializadas. Foram utilizadas várias técnicas para ajuste das métricas de avaliação das redes neurais. Os resultados encontrados sugerem o modelo Inception v3 como uma ferramenta valiosa para apoio ao diagnóstico de psoríase. Isso se deve ao seu desempenho satisfatório no que diz respeito à acurácia e F1-Score (97,5% ± 0,2).