Miracle-dz/UniFAR-FTUs huggingface dataset:
Multi-Task Decouple Learning With Hierarchical Attentive Point Process

Sequential data mining is ubiquitous in various scenarios. Modeling event sequence and predicting event occurrence is of vital importance in sequential data mining, and Temporal Point Processes (TPP) are widely used in this area. Conventional TPP use objective functions as sum of classification loss for event type and regression loss for occurrence time, leading to practical limitations that conventional TPP is unable to predict the occurrence of each type of event and distinguish the dependency within and between different event types. To tackle these defects, we propose a Multi-task Decouple Learning (MTDL) framework to model TPP from a novel perspective of Multi-task Learning (MTL), i.e., predicting the next-step occurrence time for all event types using a weighted multi-task regression loss. We experiment with three state-of-the-arts, showing that the proposed MTDL framework can improve the performance of original TPP models. Moreover, we develop a Hierarchical Attentive Point Process (HAPP) to further exploit the potential of the proposed MTDL framework, using a hierarchical attention mechanism to capture the inner-sequence time dependency within the same type of events and the inter-sequence dependency between different types of events. Experiments on real-world business dataset and public datasets show the efficacy of the proposed method.
Lymphocyte to C-Reactive Protein Ratio as an Early Biomarker to Distinguish Sepsis from Pneumonia in Neonates

Background Neonatal sepsis is an acute and severe disease that seriously threatens the life and health of newborns. Neonates with pneumonia may also have unrecognized neonatal sepsis. Early diagnosis of neonatal sepsis is beneficial for early treatment. This study aimed to evaluate the clinical significance of the lymphocyte-to-C-reactive protein ratio (LCR) as an early biomarker to distinguish sepsis from pneumonia. Methods This retrospective study enrolled 1635 neonates with pneumonia from February 2016 to March 2022. Among them, 182 cases were diagnosed with sepsis based on the positive blood culture results. Clinical and laboratory data were extracted from the electronic medical records. LCR was calculated as the ratio of the total lymphocyte count (×109 cells/L) to the C-reactive protein level (mg/L). Binary logistic regression analysis was conducted to evaluate the clinical significance of LCR as an early biomarker in distinguishing sepsis from pneumonia. Receiver operating characteristic (ROC) analysis was performed to assess the diagnostic value of LPCR in sepsis cases. All statistical analyses were conducted using Statistical Product and Service Solutions, version 24.0. Results The neonates with pneumonia combined with sepsis had a lower LCR than that of the neonates with pneumonia. Further analysis showed that the prevalence of neonatal pneumonia combined with sepsis was significantly higher in the low-LCR group than in the high-LCR group (20.7% vs 5.5%, P < 001). Binary logistic regression revealed that LCR was an independent risk factor for identifying pneumonia combined with sepsis. The ROC curve analysis revealed that LCR had better power than the lymphocyte count and CRP level individually in diagnosing neonatal pneumonia combined with sepsis (0.72 vs 0.65 vs 0.66, P < 0.001), with 62% sensitivity and 72% specificity. Conclusion LCR can be a potential early biomarker in distinguishing neonates with sepsis from those with pneumonia.
The development of Frontex: integration through supranationalism

ThisarticleinterrogatesthedevelopmentoftheEuropeanBorderandCoastGuard(Frontex)anditsimplicationsfortheEU ’ s approach to border control coordination. Through the theoretical lens of the principal-agent model, it investigates information asymmetry and friction between stakeholders in the implementation of Frontex ’ s increased competence at the borders. The ﬁ ndings of this article show that the development of Frontex has led to growing incentives for the EU ’ s supranational institutions to steer the agency to pursue their individual objectives, creating new supranational elements in EU border management.
An Innovative Use of Propolis in the Production of Dipping Sauce Powder as a Functional Food to Mitigate Testicular Toxicity Induced by Cadmium Chloride: Technological and Biological Evidence

Propolis is a common natural ingredient used in food production, food packaging, and pharmaceutical products. Therefore, the aim of our study was to prepare dipping sauce powders as an innovative functional product with a regular and spicy taste from economical raw materials with high nutritional value. The developed products were fortified with propolis powder at 250, 500, and 750 mg/kg. All studied dipping sauces were subjected to a palatability test, a nutritional evaluation, and a microbiological assay performed during 6 months of storage. In addition, an in vivo study was designed to evaluate the efficacy of these products in preventing the testicular toxicity disorders induced by cadmium chloride (CdCl2) in albino rats. Based on the palatability test, the dipping sauces supplemented with propolis at 250 mg/kg and 500 mg/kg were preferred. Moreover, all samples were safe to consume within 6 months. Biological results showed that all investigated propolis-enriched dipping sauce samples caused an improvement in all CdCl2-induced testicular histopathological and biochemical changes, especially the spicy dipping sauce powder fortified with 500 mg/kg of propolis.
Predicting developmental language disorders using artificial intelligence and a speech data analysis tool

ABSTRACT Developmental Language Disorder (DLD) affects children’s comprehension and production of spoken language without any known biomedical condition. The importance of early identification of DLD is widely acknowledged. Several studies have explored DLD predictors to identify children needing further diagnostic investigation. Most of these measures might be problematic for young children and bilingual children. Based on literature reporting fragile rhythmic abilities in children with DLD, in our study, we followed a different approach. We explored how non-linguistic measures of rhythmic anticipation can be gathered by means of advanced information technology and used to identify children at risk of DLD. With this aim, we developed MARS, a web-based tool to collect such data in a playful way and to analyze them using Machine Learning. MARS engages children in rhythmic babbling exercises, records their vocal productions, and analyzes the recordings. We discuss the methodological rationale of MARS and its underlying technology, and we describe a preliminary study with N = 47 children with and without DLD. The analysis of the audio features of participants’ rhythmic vocal productions highlights different patterns in the two groups. This result, although preliminary, suggests that MARS could be a valuable tool for early DLD assessment.
Barriers and Facilitators to Delivering Inpatient Cardiac Rehabilitation: A Scoping Review

Objective The purpose of this scoping review was to summarize the literature on barriers and facilitators that influence the provision and uptake of inpatient cardiac rehabilitation (ICR). Methods A literature search was conducted using PsycINFO, MEDLINE, EMBASE, CINAHL and AgeLine. Studies were included if they were published in English after the year 2000 and focused on adults who were receiving some form of ICR (eg, exercise counselling and training, education for heart-healthy living). For studies meeting inclusion criteria, descriptive data on authors, year, study design, and intervention type were extracted. Results The literature search resulted in a total of 44,331 publications, of which 229 studies met inclusion criteria. ICR programs vary drastically and often focus on promoting physical exercises and patient education. Barriers and facilitators were categorized through patient, provider and system level factors. Individual characteristics and provider knowledge and efficacy were categorized as both barriers and facilitators to ICR delivery and uptake. Team functioning, lack of resources, program coordination, and inconsistencies in evaluation acted as key barriers to ICR delivery and uptake. Key facilitators that influence ICR implementation and engagement include accreditation and professional associations and patient and family-centred practices. Conclusion ICR programs can be highly effective at improving health outcomes for those living with CVDs. Our review identified several patient, provider, and system-level considerations that act as barriers and facilitators to ICR delivery and uptake. Future research should explore how to encourage health promotion knowledge amongst ICR staff and patients.
Chinese Personality Traits and Mental Health: A Meta-Analysis

This meta-analysis aimed to synthesize the evidence on the relationship between Chinese personality traits and mental health. Through literature search and screening, a total of 70 original articles and 72 independent samples with a total of 65,133 participants were included. The results showed that: (1) Chinese mental health was significantly correlated with three dimensions of personality: psychoticism, neuroticism, and extraversion (correlation coefficients were 0.234, 0.438, and −0.101, respectively); (2) each factor of mental health was significantly positively correlated with psychoticism and neuroticism; only the factor of interpersonal sensitivity was significantly negatively correlated with extraversion; (3) subject type has a significant moderating effect on the relationship between mental health and neuroticism and extraversion, but has no significant moderating effect on the relationship between mental health and psychoticism; (4) publication type does not play a moderating role in the relationship between mental health and the three personality dimensions. This meta-analysis confirmed that personality traits have a significant predictive effect on mental health in Chinese people. However, the relationship between personality and mental health varied considerably across dimensions and groups.
Comprehensive Evaluation and Transcriptome Analysis Reveal the Salt Tolerance Mechanism in Semi-Wild Cotton (Gossypium purpurascens)

Elevated salinity significantly threatens cotton growth, particularly during the germination and seedling stages. The utilization of primitive species of Gossypium hirsutum, specifically Gossypium purpurascens, has the potential to facilitate the restoration of genetic diversity that has been depleted due to selective breeding in modern cultivars. This investigation evaluated 45 G. purpurascens varieties and a salt-tolerant cotton variety based on 34 morphological, physiological, and biochemical indicators and comprehensive salt tolerance index values. This study effectively identified a total of 19 salt-tolerant and two salt-resistant varieties. Furthermore, transcriptome sequencing of a salt-tolerant genotype (Nayanmian-2; NY2) and a salt-sensitive genotype (Sanshagaopao-2; GP2) revealed 2776, 6680, 4660, and 4174 differentially expressed genes (DEGs) under 0.5, 3, 12, and 24 h of salt stress. Gene ontology enrichment analysis indicated that the DEGs exhibited significant enrichment in biological processes like metabolic (GO:0008152) and cellular (GO:0009987) processes. MAPK signaling, plant-pathogen interaction, starch and sucrose metabolism, plant hormone signaling, photosynthesis, and fatty acid metabolism were identified as key KEGG pathways involved in salinity stress. Among the DEGs, including NAC, MYB, WRKY, ERF, bHLH, and bZIP, transcription factors, receptor-like kinases, and carbohydrate-active enzymes were crucial in salinity tolerance. Weighted gene co-expression network analysis (WGCNA) unveiled associations of salt-tolerant genotypes with flavonoid metabolism, carbon metabolism, and MAPK signaling pathways. Identifying nine hub genes (MYB4, MYB105, MYB36, bZIP19, bZIP43, FRS2 SMARCAL1, BBX21, F-box) across various intervals offered insights into the transcriptional regulation mechanism of salt tolerance in G. purpurascens. This study lays the groundwork for understanding the important pathways and gene networks in response to salt stress, thereby providing a foundation for enhancing salt tolerance in upland cotton.
Toward Improving Short-Range Fog Prediction in Data-Denied Areas Using the Air Force Weather Agency Mesoscale Ensemble

Abstract : This work develops and tests the viability of a new framework for producing short-range (20 h) probabilistic fog predictions using post-processing of a 4-km, 10-member Weather Research and Forecasting (WRF) ensemble configured to closely match the Air Force Weather Agency Mesoscale Ensemble Forecast System. The raw WRF predictions produce excessive forecasts of zero cloud water, mainly caused by a negative relative humidity bias, which is largely traced to a warm overnight bias. Post-processing mitigates these systematic errors by leveraging traits of a joint parameter space in the predictions to modify individual ensemble members not predicting fog on their own. The method is generally most effective when the space is defined with a moisture parameter and a lowlevel stability parameter. Cross-validation shows the method adds significant overnight skill to predictions in valley and coastal regions compared to the raw WRF forecasts, with modest skill increases after sunrise. Post-processing does not improve the highly skillful raw WRF predictions at the mountain test sites. Since the framework addresses only systematic WRF deficiencies and identifies parameter pairs with a clear, non-site-specific physical mechanism of predictive usefulness, it is transferable without the need for recalibration, and therefore does not require any observational record to employ.
Bounded Confidence and Cohesion-Moderated Pressure: A General Model for the Large-Scale Dynamics of Ordered Opinion

Due to the development of social media, the mechanisms underlying consensus and chaos in opinion dynamics have become open questions and have been extensively researched in disciplines such as sociology, statistical physics, and nonlinear mathematics. In this regard, our paper establishes a general model of opinion evolution based on micro-mechanisms such as bounded confidence, out-group pressure, and in-group cohesion. Several core conclusions are derived through theorems and simulation results in the model: (1) assimilation and high reachability in social networks lead to global consensus; (2) assimilation and low reachability result in local consensus; (3) exclusion and high reachability cause chaos; and (4) a strong “cocoon room effect” can sustain the existence of local consensus. These conclusions collectively form the “ideal synchronization theory”, which also includes findings related to convergence rates, consensus bifurcation, and other exploratory conclusions. Additionally, to address questions about consensus and chaos, we develop a series of mathematical and statistical methods, including the “energy decrease method”, the “cross-d search method”, and the statistical test method for the dynamical models, contributing to a broader understanding of stochastic dynamics.
In-Loco Optical Spectroscopy through a Multiple Digital Lock-In on a Linear Charge-Coupled Device (CCD) Array

Accurate and reliable measurements of optical properties are crucial for a wide range of industrial and commercial applications. However, external illumination fluctuations can often make these measurements challenging to obtain. This work proposes a new technique based on digital lock-in processing that enables the use of CCD spectrometers in optical spectroscopy applications, even in uncontrolled lighting conditions. This approach leverages digital lock-in processing, performed on each pixel of the spectrometer’s CCD simultaneously, to mitigate the impact of external optical interferences. The effectiveness of this method is demonstrated by testing and recovering the spectrum of a yellow LED subjected to other light sources in outdoor conditions, corresponding to a Signal-to-Noise Ratio of −70.45 dB. Additionally, it was possible to demonstrate the method’s applicability for the spectroscopic analysis of gold nanoparticles in outdoor conditions. These results suggest that the proposed technique can be helpful for a wide range of optical measurement techniques, even in challenging lighting conditions.
Elevation and volume changes on the Harding Icefield, Alaska

Abstract Airborne surface elevation profiles of the Harding Ice field, south-central Alaska, were made in 1991 and 1996. Thirteen glaciers were profiled, along with the tipper region of the icefield. The profiles were compared to U.S. Geological Survey topographie maps made in the 1950s, to obtain elevation and volume changes. Comparison of the changes for the different glaciers shows no significant correlation between volume change and the type of glacier or characteristics such as location, aspect, size, slope or terminus changes. Estimated total volume change tor this ~43 year period is about -34 km3, which corresponds to an area-average elevation change of-21 m. The estimated error in this elevation change of 5 m is mainly due to errors in the maps at higher elevations. Our measurements provide an accurate baseline against which future determinations of volume change can be made.
Penerapan Algoritma K-Means dan Analisisnya untuk Menentukan Kebijakan Strategis Penyelesaian Studi Mahasiswa

Pertambahan jumlah mahasiswa yang menyelesaikan studi setiap tahun pada suatu program studi telah menghasilkan banyak tumpukan data dan tentunya menimbulkan sebuah pertanyaan besar, yaitu “pengetahuan apa yang dapat dihasilkan dari tumpukan data tersebut? ”. Menjawab pertanyaan besar tersebut peneliti mencoba untuk menerapkan suatu teknik data mining yang merupakan sebuah tahapan dalam Knowledge Discovery in Database (KDD). Usaha meningkatkan kualitas mahasiswa yang dilakukan oleh prodi PTIK UIN Bukittinggi menghadapi beberapa kendala, diantaranya yaitu secara umum tugas akhir mahasiswa dirasakan mengalami penurunan jika dibandingkan dengan beberapa tahun sebelumnya. Selain itu, prodi belum mensosialisasikan kepada dosen dan mahasiswa tentang judul penelitian tugas akhir mahasiswa dan juga roadmap atau arah penelitian ke depan. Masalah lainnya yaitu terdapat mahasiswa yang mengajukan judul penelitian tugas akhir namun kurang sesuai dengan empat domain skill pada prodi PTIK. Metodologi pengembangan data mining yang digunakan dalam penelitian ini adalah CRIPS-DM merupakan singkatan dari Cross-Industry Standart Process for Data Mining. Hasil dari penerapan data mining metode clustering dengan algoritma K-Means yang diterapkan dalam penelitian ini memperoleh tiga buah cluster atau kelompok dengan beberapa analisis setiap cluster. Analisis dari setiap cluster menghasilkan rekomendasi untuk program studi dalam mengambil kebijakan strategis terhadap mahasiswa yang sedang dalam penyelesaian studi pada prodi PTIK UIN Bukittinggi.
Methods and Applications of 3D Ground Crop Analysis Using LiDAR Technology: A Survey

Light Detection and Ranging (LiDAR) technology is positioning itself as one of the most effective non-destructive methods to collect accurate information on ground crop fields, as the analysis of the three-dimensional models that can be generated with it allows for quickly measuring several key parameters (such as yield estimations, aboveground biomass, vegetation indexes estimation, perform plant phenotyping, and automatic control of agriculture robots or machinery, among others). In this survey, we systematically analyze 53 research papers published between 2005 and 2022 that involve significant use of the LiDAR technology applied to the three-dimensional analysis of ground crops. Different dimensions are identified for classifying the surveyed papers (including application areas, crop species under study, LiDAR scanner technologies, mounting platform technologies, and the use of additional instrumentation and software tools). From our survey, we draw relevant conclusions about the use of LiDAR technologies, such as identifying a hierarchy of different scanning platforms and their frequency of use as well as establishing the trade-off between the economic costs of deploying LiDAR and the agronomically relevant information that effectively can be acquired. We also conclude that none of the approaches under analysis tackles the problem associated with working with multiple species with the same setup and configuration, which shows the need for instrument calibration and algorithmic fine tuning for an effective application of this technology.
Translation and Validation of the Swedish Version of the Tilburg Frailty Indicator

The Tilburg Frailty Indicator (TFI) is a questionnaire with 15 questions designed for screening for frailty in community-dwelling older people. TFI has a multidimensional approach to frailty, including physical, psychological, and social dimensions. The aim of this study was to translate TFI into Swedish and study its psychometric properties in community-dwelling older people with multimorbidity. A cross-sectional study of individuals 75 years and older, with ≥3 diagnoses of the ICD-10 and ≥3 visits to the Emergency Department in the past 18 months. International guidelines for back-translation were followed. Psychometric properties of the TFI were examined by determining the reliability (inter-item correlations, internal consistency, test–retest) and validity (concurrent, construct, structural). A total of 315 participants (57.8% women) were included, and the mean age was 83.3 years. The reliability coefficient KR-20 was 0.69 for the total sum. A total of 39 individuals were re-tested, and the weighted kappa was 0.7. TFI correlated moderately with other frailty measures. The individual items correlated with alternative measures mostly as expected. In the confirmatory factor analysis (CFA), a three-factor model fitted the data better than a one-factor model. We found evidence for adequate reliability and validity of the Swedish TFI and potential for improvements.
Deep and Surface Circulation in the Northwest Indian Ocean from Argo, Surface Drifter, Satellite, and In Situ Profiling Current Observations

Deep and Surface Circulation in the Northwest Indian Ocean from Argo, Surface Drifter, Satellite and In Situ Profiling Current Observations. (August 2011) Sarah A. Stryker, B.S., The State University of New York at Fredonia Chair of Advisory Committee: Dr. Steven F. DiMarco The physical oceanography in the northwest Indian Ocean is largely controlled by the seasonal monsoon. The seasonal variability in circulation is complex. Many studies have investigated processes in the Persian (Arabian) Gulf and Arabian Sea, but little is understood about the Sea of Oman. This thesis incorporated observations from Argo floats, surface drifters and satellite imagery to study the deep and surface circulation in the northwest Indian Ocean. An assessment of four independent moorings located in the Sea of Oman and Arabian Sea, as well as a model skill comparison of the Simple Ocean Data Assimilation (SODA) model, contributed to understanding the dynamics in this region. Spatial patterns of surface current velocity produced from surface drifter data from 1995-2009 agreed with previously known surface currents. The Somali Current, East Arabian Current, Equatorial Current, Northeast/Southwest Monsoon Current, Great Whirl and Ras al Hadd Jet were all identified. During the Southwest Monsoon, flow direction was to the east and southeast in the Arabian Sea. The Somali Current flowed northeast along the Somali Coast extending to the East Arabian Current along the Oman