Miracle-dz/UniFAR-FTUs huggingface dataset:
Optimization of Rice Distribution Network Based on Green Logistics Concept

SDGs or Sustainable Development Goals have become a global and national commitment. Greenhouse gases (GHG) are indicators of climate change which is one of the 17 SDG’s goals. In the national food logistics system with rice as a staple food, there are some regions with surplus production and other deficits. Hence, the distribution involved the transportation activities that need to be carried out. In transportation, the carbon footprints are generated from exhaust gases as residue from the fuel combustion process. The carbon footprint efficiency is one of the indicators in green logistics. Green logistics for decarbonization in the transportation sector for a better environment has to start massively. Indonesia is committed to implementing the green logistics concept in logistics distribution. In this case, the author determined the surplus area and the deficit one based on statistical data on the production and consumption of each city in Java. Furthermore, a distribution network model is designed that involves emission level as a parameter in determining the route on the network. In the design, the selected mode of freight transportation was limited to land transportation modes besides trains. The design makes environmental aspects a major consideration in the distribution as well as the shipping costs. Keywords: carbon footprint, emission factor, green logistics
Transformational Logistics within the Infantry Brigade Combat Team (IBCT): Solutions or Shell Game?

Abstract : This monograph examines the logistical transportation gap in the tactical segment of the U.S. Army distribution system of the Infantry Brigade Combat Team (IBCT) and provides recommendations for future capabilities and requirements necessary to reduce the current logistical transportation gap. The U.S. Army has struggled with logistical distribution at all levels since the Revolutionary War. This logistical distribution problem often leads to tactical pauses in an operation. The loss of capability or freedom of action due to logistics results from the inability to distribute supplies at the far end of the logistical supply chain, the last 1,000 yards. The Army historically has overcome logistical gaps by temporarily supplementing additional capabilities or resources to solve the immediate problem -- essentially playing a shell game. As the Army transforms to a campaign quality force with an expeditionary capability, these shell games will no longer enable the desired effectiveness of the Modular Force. The methodology of this monograph consists of establishing critical components of the distribution gap through a historical lens and following these components through the transition of doctrine from the current Legacy Force to the emerging Modular Force. The identified critical components of the logistical transportation gap are transportation platforms, labor forces, and materiel handling equipment. The evaluation of these transportation pillars against the desired capabilities of the Modular Force forms the basis of the solution set required to address the logistical transportation gap. This monograph finds the IBCT's logistical transportation gap to be expanding, not contracting, under the emergent design of the Modular Force's logistical distribution system. To reverse this expansion process and bridge the logistical transportation gap, the proposed solution set incorporates changes across the spectrum of doctrine, organization, training, materiel, and personnel.
Evaluation of offensive and defensive agility depending on the type of visual cue and personal decision-making styles in basketball

Background: The specific goal was to determine the level and differences in the performance of reactive agility (RA) depending on the type of visual stimulus and to identify the role of selected psychological patterns in the decision-making process. Method: 13 female basketball players (17.12 ± 1.09 years; mean BW 58.17 kg ± 7.68 kg; mean BH 1.73 ± 0.11, BMI 19.53 ± 3.86) playing top Slovak junior league. The diagnosis of specific game reactions was carried out using a Y-shaped reaction agility test. The stimulus for the action effect was a light direction indicator and a video sequence. Decision-making style was assessed using the Melbourne Decision Making Questionnaire (MDMQ). Results: The significance of the differences between offensive actions according to the type of stimulus was revealed by statistically significant differences between offensive reaction agility to a light stimulus and a stimulus with a contextual stimulus, and also in the case of defensive actions. Correlation analysis revealed significant correlations between offensive and defensive skills in the light stimulus, between the performance in offensive skills in the light stimulus, between the two types of defensive agility (light and video) and in the context stimulus, and a correlation between vigilance and both offensive activities was also found. Conclusion: The player's sensorimotor mechanisms are different depending on the type of stimulus, not on the type of actions, which leads to the conclusion that specific contextual information can lead to faster and more accurate decisions during the game 1:1 and improve the timing of action effects.
Human Capital is the Key to the Successful Competitiveness of Countries in the Asean

Objective: This research aims to look at competitiveness in the Asean region. Knowing the factors driving competitiveness then mapping the strength of competitiveness based on the driving factors for each country in ASEAN. So you will know which countries with high competitiveness are influenced by what factors. The results will be an illustration for other countries in ASEAN to improve these factors with the aim of increasing competitiveness. Method: The method used to determine the factors driving competitiveness is to use panel data regression with the Stata application. Then group them using main factor analysis with SPSS so that country categories are found based on the factors driving their competitiveness. The data used are 12 indicators forming independent and dependent variables. Obtained from various relevant sources. In a period of 10 years, namely 2010 to 2019. Results: The results of multivariate linear regression showed that both simultaneously and partially Human Capital Development (HCD), Human Capital - High Education (HCH), Research and Technology Development (RTD), and Social Capital – Unemployment (SCU) had a significant influence on Competitiveness. HCD has the greatest influence on competitiveness. This research can provide an illustration for each country in ASEAN that the driving factors of competitiveness needed to achieve high competitiveness are HCD and HCH because of their large influence in the regression model. Countries with very strong competitiveness also have very strong HCD and HCH factors and vice versa. This can be a consideration for each country in making policies related to increasing national competitiveness. Because high competitiveness indicates a high level of population welfare.
Molluscan assemblages in a highly variable setting in littoral bottoms of the Lower Pleistocene of Rhodes (Greece).

Στην eργασία αυτή μeλeτήθηκe η πλούσια και καλά διατηρημένη πανίδα μαλακίων που πeριέχeται σe αμμώδeς στρώμα ρηχών θαλάσσιων αποθέσeων του Κατωτέρου Πλeιστοκαίνου της νήσου Ρόδου. Πιστοποιήθηκαν 4 διαφορeτικές συγκeντρώσeις μαλακίων γeιτονικών πeριβαλλόντων καθώς και οι οικολογικές τους φωλeές οι οποίeς καθορίζονται από την πλeυρική μeταβολή του τύπου του υποστρώματος. Αναγνωρίστηκαν αντιπρόσωποι μαλακίων σκληρού υποστρώματος έως και αμμώδους βυθού της παράκτιας ζώνης. Προσδιορίστηκαν 55 eίδη μαλακίων eκ των οποίων 29 eίδη γαστeρόποδων. Πιστοποιήθηκe η παρουσία της Ervilia castanea και της αντιπροσωπeυτικής φάσης της στο Κατώτeρο Πλeιστόκαινο της Eλλάδας για πρώτη φορά.
A dynamic nomogram for predicting 28-day mortality in septic shock: a Chinese retrospective cohort study

Background Septic shock is a severe life-threatening disease, and the mortality of septic shock in China was approximately 37.3% that lacks prognostic prediction model. This study aimed to develop and validate a prediction model to predict 28-day mortality for Chinese patients with septic shock. Methods This retrospective cohort study enrolled patients from Intensive Care Unit (ICU) of the Second Affiliated Hospital, School of Medicine, Zhejiang University between December 2020 and September 2021. We collected patients’ clinical data: demographic data and physical condition data on admission, laboratory data on admission and treatment method. Patients were randomly divided into training and testing sets in a ratio of 7:3. Univariate logistic regression was adopted to screen for potential predictors, and stepwise regression was further used to screen for predictors in the training set. Prediction model was constructed based on these predictors. A dynamic nomogram was performed based on the results of prediction model. Using receiver operator characteristic (ROC) curve to assess predicting performance of dynamic nomogram, which were compared with Sepsis Organ Failure Assessment (SOFA) and Acute Physiology and Chronic Health Evaluation II (APACHE II) systems. Results A total of 304 patients with septic shock were included, with a 28-day mortality of 25.66%. Systolic blood pressure, cerebrovascular disease, Na, oxygenation index (PaO2/FiO2), prothrombin time, glucocorticoids, and hemodialysis were identified as predictors for 28-day mortality in septic shock patients, which were combined to construct the predictive model. A dynamic nomogram (https://zhijunxu.shinyapps.io/DynNomapp/) was developed. The dynamic nomogram model showed a good discrimination with area under the ROC curve of 0.829 in the training set and 0.825 in the testing set. Additionally, the study suggested that the dynamic nomogram has a good predictive value than SOFA and APACHE II. Conclusion The dynamic nomogram for predicting 28-day mortality in Chinese patients with septic shock may help physicians to assess patient survival and optimize personalized treatment strategies for septic shock.
Metabolic-associated fatty liver disease: a selective review of pathogenesis, diagnostic approaches, and therapeutic strategies

Background Metabolic associated fatty liver disease (MAFLD) is a novel terminology introduced in 2020 to provide a more accurate description of fatty liver disease associated with metabolic dysfunction. It replaces the outdated term nonalcoholic fatty liver disease (NAFLD) and aims to improve diagnostic criteria and tailored treatment strategies for the disease. NAFLD, the most prevalent liver disease in western industrialized nations, has been steadily increasing in prevalence and is associated with serious complications such as cirrhosis and hepatocellular carcinoma. It is also linked to insulin resistance syndrome and cardiovascular diseases. However, current studies on NAFLD have limitations in meeting necessary histological endpoints. Objective This literature review aims to consolidate recent knowledge and discoveries concerning MAFLD, integrating the diverse aspects of the disease. Specifically, it focuses on analyzing the diagnostic criteria for MAFLD, differentiating it from NAFLD and alcoholic fatty liver disease (AFLD), and exploring the epidemiology, clinical manifestations, pathogenesis, and management approaches associated with MAFLD. The review also explores the associations between MAFLD and other conditions. It discusses the heightened mortality risk associated with MAFLD and its link to chronic kidney disease (CKD), showing that MAFLD exhibits enhanced diagnostic accuracy for identifying patients with CKD compared to NAFLD. The association between MAFLD and incident/prevalent CKD is supported by cohort studies and meta-analyses. Conclusion This literature review highlights the importance of MAFLD as a distinct terminology for fatty liver disease associated with metabolic dysfunction. The review provides insights into the diagnostic criteria, associations with CKD, and management approaches for MAFLD. Further research is needed to develop more accurate diagnostic tools for advanced fibrosis in MAFLD and to explore the underlying mechanisms linking MAFLD with other conditions. This review serves as a valuable resource for researchers and healthcare professionals seeking a comprehensive understanding of MAFLD.
Daily Profit Analysis In Profit Management For Street Vendors In Pringapus Village, Pringapus District, Semarang District

This study aims to determine the daily profit management of street vendors in Pringapus Village, Pringapus District, Semarang Regency and to find out the obstacles faced in analyzing daily earnings in profit management for street vendors in Pringapus Village, Pringapus District, Semarang Regency.The research method used in this study is a qualitative research method by conducting interviews, observations and literature studies.The results obtained in this study are the average profit earned by street vendors in Pringapus village is 155 thousand. Then the street vendors in Pringapus village manage their profits by using them as daily necessities and most street vendors in Pringapus village have not mastered how to analyze profits properly and correctly due to education and age factors
Optrode-Assisted Multiparametric Near-Infrared Spectroscopy for the Analysis of Liquids

We demonstrate a sensing scheme for liquid analytes that integrates multiple optical fiber sensors in a near-infrared spectrometer. With a simple optofluidic method, a broadband radiation is encoded in a time-domain interferogram and distributed to different sensing units that interrogate the sample simultaneously; the spectral readout of each unit is extracted from its output signal by a Fourier transform routine. The proposed method allows performing a multiparametric analysis of liquid samples in a compact setup where the radiation source, measurement units, and spectral readout are all integrated in a robust telecom optical fiber. An experimental validation is provided by combining a plasmonic nanostructured fiber probe and a transmission cuvette in the setup and demonstrating the simultaneous measurement of the absorption spectrum and the refractive index of water–methanol solutions.
The effects of selected bio-active feed additives on NIle tilapia (Oreochromis niloticus) production and health

A study was carried out to obtain a rapid assessment of nutritional quality of diets supplemented with exogenous digestive enzymes using an in vitro digestion technique. The in vitro digestion technique consisted of 2-step digestion at 28 °C. Step 1 a 4 h digestion of the experimental diets with pepsin at pH 2.5. Step 2 – a 14 h digestion with porcine pancreatin at pH 7.5. The undigested materials (residues) were recovered by centrifugation, oven dried at 105 °C and analysed for chemical composition. The digestion coefficients (DCs), digestible nutrients (DNs) and total digestible nutrients (TDNs) were calculated. DCs of dry matter and energy are higher (P < 0.05) in phytase and carbohydrase supplemented diets compared to that of a control and protease supplemented diets. DC of crude protein was highest (P < 0.05) in phytase supplemented diet and least (P < 0.05) in protease supplemented diet. However, the DC of lipid was highest (P < 0.05) in the protease supplemented diet. The DC of ash was significantly higher (P < 0.05) in the phytase supplemented diet than in the remaining three experimental diets. The DCs translated to DNs of the experimental diets in a similar trend. The TDNs of the three enzyme supplemented diets (P < 0.05) were higher than TDN of the control diet. Going by the DCs and TDNs, the exogenous digestive enzymes seem to ________________________________________________________________ Chapter 3 69 show potential for use in aquafeed and thus should be tested in vivo with the appropriate
Validation of preparedness and willingness on early detection of autism spectrum disorder among healthcare providers in Jordan

In recent years, there have been significant advancements in the field of early detection and intervention for children with developmental and behavioural disorders, with significant in the context of Autism Spectrum Disorder (ASD). It highlights the advantages of early detection, such as reduced long-term costs and positive effects on a child's development. However, it also acknowledges the prevalent barriers to early ASD diagnosis and intervention. This study aims to develop and validate questionnaires on Preparedness and Willingness in early ASD detection among Al-Mafraq City, Jordan, healthcare providers. The research in the Al-Mafraq region of Jordan employed a cross-sectional research design. The study first involved the development of a questionnaire, which underwent rigorous content validation by a panel of experts well-versed in ASD. Face validity was assessed utilizing the Face Validity Index (FVI). A random sample of 130 healthcare providers from one hospital answered the draft questionnaires online for the EFA analysis recommended. It resulted in satisfactory items' factor loadings (r>0.60) and internal reliability (Cronbach's alpha >0.8). Followed by CFA from a random sample of another 202 healthcare providers from another hospital and healthcare centres in Al-Mafraq showed that the instrument effectively met the validation criteria, demonstrating its reliability and validity in assessing healthcare providers' Preparedness and Willingness for early ASD detection. Notably, the participants in the study exhibit differing degrees of Preparedness and Willingness. In conclusion, the study underscores the critical standing of developing a comprehensive instrument to evaluate the limitations associated with early ASD detection among healthcare providers.
Monitoring of distortions and interferences in ASK-modulated currents of railway signaling systems

The problem considered in the work concerns the automation of the monitoring of ACK signals, which are widely used in railway signaling systems, namely in track circuits, due to the simplicity of their generation. Due to the low interference immunity of ACK signals under the influence of traction current and other electromagnetic sources at the railways, malfunctions can occur in the operation of train control systems. To prevent possible failures in the operation of track circuits, measurements of the signal parameters on generators and receivers of track circuits are periodically carried out. Such measurements are mainly made manually, therefore they are expensive and do not provide the necessary accuracy of the results. The problem of automating the control of signals in track circuits is related to the correct choice of characteristic features of signal distortions in order to identify excessive distortions that can lead to failures in the operation of track circuits. The article discusses methods for analyzing the signal current in the time and frequency domains to detect signal distortions. It is shown that in addition to the current measurements of the rms voltage of signals in track circuits, it is necessary to monitoring the voltage levels in the pulses and pauses of the signals, as well as the spectral composition of the signals.
An Improved Long Short-Term Memory Algorithm for Cardiovascular Disease Prediction

Cardiovascular diseases, prevalent as leading health concerns, demand early diagnosis for effective risk prevention. Despite numerous diagnostic models, challenges persist in network configuration and performance degradation, impacting model accuracy. In response, this paper introduces the Optimally Configured and Improved Long Short-Term Memory (OCI-LSTM) model as a robust solution. Leveraging the Salp Swarm Algorithm, irrelevant features are systematically eliminated, and the Genetic Algorithm is employed to optimize the LSTM’s network configuration. Validation metrics, including the accuracy, sensitivity, specificity, and F1 score, affirm the model’s efficacy. Comparative analysis with a Deep Neural Network and Deep Belief Network establishes the OCI-LSTM’s superiority, showcasing a notable accuracy increase of 97.11%. These advancements position the OCI-LSTM as a promising model for accurate and efficient early diagnosis of cardiovascular diseases. Future research could explore real-world implementation and further refinement for seamless integration into clinical practice.
A Catalog of GNI-A1 Genes That Regulate Floret Fertility in a Diverse Bread Wheat Collection

Modifying inflorescence architecture improves grain number and grain weight in bread wheat (Triticum aestivum). Allelic variation in Grain Number Increase 1 (GNI-A1) genes, encoding a homeodomain leucine zipper class I transcription factor, influences grain number and yield. However, allelic information about GNI-A1 in diverse germplasms remains limited. Here, we investigated GNI-A1 alleles in a panel of 252 diverse bread wheat accessions (NBRP core collection and HRO breeder’s panel) by target resequencing. Cultivars carrying the reduced-function allele (105Y) were predominant in the NBRP panel, whereas the 105N functional allele was the major type in the HRO panel. Cultivars with the 105Y allele were distributed in Asian landraces but not in European genotypes. Association analysis demonstrated that floret fertility, together with grain size, were improved in cultivars in the NBRP core collection carrying the 105Y allele. These results imply that different alleles of GNI-A1 have been locally selected, with the 105Y allele selected in East Asia and the 105N allele selected in Europe.
Land surface temperature over global deserts: Means, variability, and trends

Land surface air temperature (LSAT) has been a widely used metric to study climate change. Weather observations of LSAT are the fundamental data for climate change studies and provide key evidence of global warming. However, there are very few meteorological observations over deserts due to their uninhabitable environment. This study fills this gap and provides independent evidence using satellite‐derived land surface temperatures (LSTs), benefiting from their global coverage. The frequency of clear sky from MODerate Resolution Imaging Spectroradiometer (MODIS) LST data over global deserts was found to be greater than 94% for the 2002–2015 period. Our results show that MODIS LST has a bias of 1.36°C compared to ground‐based observations collected at 31 U.S. Climate Reference Network (USCRN) stations, with a standard deviation of 1.83°C. After bias correction, MODIS LST was used to evaluate existing reanalyses, including ERA‐Interim, Japanese 55‐year Reanalysis (JRA‐55), Modern‐Era Retrospective Analysis for Research and Applications (MERRA), MERRA‐land, National Centers for Environmental Prediction (NCEP)‐R1, and NCEP‐R2. The reanalyses accurately reproduce the seasonal cycle and interannual variability of the LSTs, but their multiyear means and trends of LSTs exhibit large uncertainties. The multiyear averaged LST over global deserts is 23.5°C from MODIS and varies from 20.8°C to 24.5°C in different reanalyses. The MODIS LST over global deserts increased by 0.25°C/decade from 2002 to 2015, whereas the reanalyses estimated a trend varying from −0.14 to 0.10°C/decade. The underestimation of the LST trend by the reanalyses occurs for approximately 70% of the global deserts, likely due to the imperfect performance of the reanalyses in reproducing natural climate variability.