Miracle-dz/UniFAR-FTUs huggingface dataset:
Trend of Sediment Yield in the Coarser Sediment-producing Area in the Middle Yellow River Basin in the Period 1997-2007 and the Formative Cause

Based on hydrometric and precipitation data,a study has been made on the temperal variation in the drainage area between Hekouzhen and Longmen in the Yellow River basin. It has been found that the trend of sediment yield changed from increasing in the period 1986-1996 to decreasing in the period 1997-2007. During the period 1986-1996,the mean annual sediment yield was 5.08×108 t,but it decreased to 2.338×108 t for the period 1997-2007,decreased by 54.1%. As an overall tendency,the annual sediment yield in the Heliuzhen-Longmen area decreased,but there were some secondary trends. The annual sediment yield decreased to a minimum appeared in 1986,then increased to a maximum in 1996,followed by a decrease. For the period 1998-2006,the squared correlation coefficient r2 between annual sediment yield and annual precipitation was as low as 0.017,indicating that the variation in sediment yield is not dependent on the variation in precipitation. This means that human activity has greatly changed the "normal" relationship between sediment yield and precipitation,and become the dominant control for sediment yield. After 1997,the relationship between annual sediment yield and annual runoff has also been totally changed. Since 1970,the sediment reduction rate (defined as the ratio of sediment reduction by soil and water conservation measures to the sediment yield in the supposed condition of unchanged precipitation) shows a complicated variation. It is increased to a maximum,then decreased to a minimum,followed by an increase. The contribution of human activity to the reduction in sediment yield showed an increasing trend. In the period 1998-2006,it was 65%,and the contribution of precipitation was only 35%. The marked decrease in sediment yield after 1997 can be explained by the enhanced soil and water conservation measures,the large-scale implementation of "replacing cultivated land by forestation" ,building of large number of check-dams for sediment trapping,putting the practice of "closing hillsides to facilitate affrestation" in large area,and large-scale transferring of surplus rural labors.
SOME SYSTEMATIC ERRORS IN AAM AND OAM DATA

Atmospheric Angular Momentum (AAM) and Ocean Angular Momentum (OAM) func- tions excite significant parts of the length of day (LOD) and polar motion variations and provide strong disturbances over the broad band of frequencies with periods from several days to years. The time series of AAM and OAM contain some systematic biases of the mean values for some periods due to unevenly spaced distribution of some observational stations in time. These biases are determined by analyses of the significant linear trends, longer than five years, in the integrated AAM and OAM functions. After estimated biases are removed from the AAM and OAM data, the resulting time series have good consis- tency in relation to the oscillations with periods from several days to five years. Their application yields a more precise estimation of the periodic terms of the Earth orientation parameters within this band.
The collaborative construction of knowledge through online forums and blogging in an EFL undergraduate class

In the educational field, the World Wide Web can be used as a medium of communication, as an information delivery system as well as an interactive space to provide novel opportunities for students' engagement in learning tasks. The present study attempts to explore the latter through interpretive, qualitative research. It examines how the use of blogging and the electronic forum contributes to the development of collaborative tasks and the application of critical thinking skills in an English Language II class at the Faculty of Languages of the National University of Córdoba (UNC), which offers programmes in EFL Teacher Training, Translation and Research. The teacher-researcher, two raters, one of whom was also the external observer, and 24 Spanish-speaking undergraduate students participated in this study. The data collection instruments included a pre-study and a post-study questionnaire, the text generated in the students' group forums and blogs. The findings led to the development of a taxonomy of online L2 collaborative contributions in the group debate forums, and to a threefold classification of the patterns of application of critical thinking skills and collaboration in the blog entries. Although the implications of this study relate to a specific group of students in a particular educational setting, the results suggest that the electronic forum and group blogging can facilitate collaboration and the application of higher order thinking and that the students perceived these Web-based activities as relevant to their L2 learning.
Using fuzzy and machine learning iterative optimized models to generate the flood susceptibility maps: case study of Prahova River basin, Romania

Abstract In this work, the vulnerability to flooding in the Prahova River basin was calculated and analyzed using advanced methods and techniques. Thus, 2 hybrid models represented by Iterative Classifier Optimizer – Multiclass Alternating Decision Tree – Certainty Factor (ICO-LADT-CF) and Fuzzy-Analytical Hierarchy Process – Certainty Factor (FAHP-CF) were generated, which had as input data the values of 10 flood predictors and a number of 158 points where historical floods occurred. In the first step, the Certainty Factor values were calculated, which were then used in the Fuzzy-Analytical Hierarchy Process and Multiclass Alternating Decision Tree models. It should be mentioned that the Multiclass Alternating Decision Tree model was optimized with the help of the Iterative Classifier Optimizer. In the case of both ensemble models the slope angle was the most important flood conditioning factor. Moreover, according to Certainty Factor modelling the 8 classes/categories achieved the maximum value of 1. Next, the susceptibility to floods on the surface of the study area was derived. On average, about 20% of the study area has areas with high and medium susceptibility to flash floods. After evaluating the quality of the models through Receiver Operating Characteristics (ROC) Curve, the following results emerged: Success Rate for Flood Potential Index (FPI) Iterative Classifier Optimizer – Multiclass Alternating Decision Tree – Certainty Factor (ICO-LADT-CF) (Area Under Curve = 0.985) and Flood Potential Index (FPI) Fuzzy-Analytical Hierarchy Process – Certainty Factor (FAHP-CF) (Area Under Curve = 0.967); Prediction Rate for Flood Potential Index (FPI) Iterative Classifier Optimizer – Multiclass Alternating Decision Tree – Certainty Factor (ICO-LADT-CF) (Area Under Curve = 0.952) and Flood Potential Index Fuzzy-Analytical Hierarchy Process – Certainty Factor (FAHP-CF) (Area Under Curve = 0.913). At the same time, the accuracies of the models were: Training dataset − 0.943 (Iterative Classifier Optimizer – Multiclass Alternating Decision Tree – Certainty Factor) and 0.931 (Fuzzy-Analytical Hierarchy Process – Certainty Factor); Validating dataset − 0.935 (Iterative Classifier Optimizer – Multiclass Alternating Decision Tree – Certainty Factor) and 0.926 (Fuzzy-Analytical Hierarchy Process – Certainty Factor). As main conclusion, it can be mentioned that the 2 ensemble models outperform the previous machine learning models applied on the same study area before.
Support of space techniques for groundwater exploration in Lebanon.

Lebanon is known by the availability in water resources whether on surface or among the existing rock for-mations. However, the status-quo does not reflect this availability due to a number of physical factors, as well as the mismanagement of these resources. Hence, the per capita has been reduced by about 50% in the last three decades. There are sixteen exposed rock formations in Lebanon, two of them are major aquifers and they are characterized by highly fractured and karstified carbonate rocks. Recently, challenges for groundwater in Lebanon have been developed. These are the: overexploitation, climate change and the acute geologic setting, which led to decline in rainfall rate, and thus exacerbated water demand. The existing chal-lenges resulted with a number of problems in ground water resources management, namely: quality deterio-ration, impact on springs and groundwater behavior, loss of groundwater o the sea, saltwater intrusion and exacerbated by the lack of data and mismanagement in water sector. In this respect, new technologies can be utilized as a helpful instrument in managing groundwater resources to treat the unfavorable situation. Space techniques and GIS have been recently raised in several topics on water resources management, including, mainly exploration and monitoring. They proved to be capable to extract hydrogeologic information and thus to manipulate this information in creditable approaches of analysis. This study introduced the present status on the Lebanese groundwater resources and the existing challenges and problems. Thus, it extends an appli-cation from Lebanon on the used new approaches for exploring groundwater.
A Comparative Study on Main Content Extraction Algorithms for Right to Left Languages

: With the daily increase of published information on the Web, extracting the web page's main content has become an important issue. Since 2010, in addition to the English Language, the contents with the right to left languages such as Arabic or Persian are also increasing. In this paper, we compared the three famous main content extraction algorithms published in the last decade, Boilerpipe, DANAg, and Web-AM, to find the best algorithm considering evaluation measures and performance. The ArticleExtractor algorithm of the Boilerpipe approach was scored as the most accurate algorithm, with the highest average score of F1 measure of 0.951. On the contrary, the DANAg algorithm was selected with the best performance, being able to process more than 21 megabytes per second. Considering the accuracy and the effectiveness of the main content extraction projects, one of the two Boilerpipe or DANAg algorithms can be used.
Vegetation Index greenness global data set White Paper for NASA ESDR/CDR (April 2006)

Vegetation Indices (VI) are optical measures of vegetation canopy ‘greenness’, a direct measure of photosynthetic potential resulting from the composite property of total leaf chlorophyll, leaf area, canopy cover, and structure. VI’s are widely used as proxies in estimating canopy state variables (leaf area index, fraction of absorbed photosynthetically-active radiation, chlorophyll content, vegetation fraction) and canopy biophysical processes (photosynthesis, transpiration, net primary production). The Vegetation Index ESDR/CDR includes the Normalized Difference Vegetation Index (NDVI) and an Enhanced Vegetation Index (EVI) at coarse (~5-8km) and moderate (~250m -1km) resolutions to effectively characterize ecosystem states and processes for long-term climate change and near real-time operational applications.
Non-Parallel Training Approach for Emotional Voice Conversion Using CycleGAN

: The focus of this research is proposing a nonparallel emotional voice conversion for Egyptian Arabic speech. This method aims to change emotion-related features of a speech signal without changing its lexical content or speaker identity. We relied on the assumption that any speech signal can be divided into content and style code and the conversion between different emotion domains is done by combining the target style code with the content code of the input speech signal. We evaluated the model using an Egyptian Arabic dataset covering two emotion domains and the conversion results were successful depending on a survey conducted on random people. Our purpose is to produce a state-of-the-art pre-trained model as it will be an unprecedented model in the Egyptian Arabic language as far as we are concerned.
FPGA-Based Extended Control Set Model Predictive Current Control with a Simplified Search Strategy for Permanent Magnet Synchronous Motor

The conventional finite control set model predictive current control (FCS-MPCC) suffers from suboptimal steady-state performance, primarily due to the limited selection of only eight basic voltage vectors in each control cycle. To overcome this limitation, the proposed extended control set MPCC (ECS-MPCC) utilizes an control set consisting of 818 selectable vectors, enabling a more refined voltage output and achieving a deadbeat response for current control by minimizing the cost function. To mitigate the computational burden resulting from the substantial increase in voltage vectors, a simplified search strategy is devised, which can be extended to other multi-objective cost functions. Remarkably, based on the inherent parallelism of the algorithm, the ECS-MPCC is implemented on an FPGA, further reducing the overall control time of the current loop to an impressive 0.61 μs. Through simulation and experimental tests on a laboratory PMSM driver, the effectiveness of the proposed ECS-MPCC strategy is validated. The experimental results demonstrate a significant reduction of 79% in the total harmonic distortion of phase currents compared to the conventional FCS-MPCC approach. This improvement underscores the superiority of the ECS-MPCC in enhancing the performance of PMSM drives, thereby illustrating its potential for practical implementation in real-world applications.
Comparative Analysis of miRNA and EMT Markers in Metastatic Colorectal Cancer

Abstract Colorectal cancer (CRC) is the fourth most commonly diagnosed malignant condition in the world. Micro RNAs (miRNAs) as well as epithelial to mesenchymal transition (EMT) play an important role in the pathogenesis of CRC. We performed a comparative analysis of the expression of selected miRNA genes and EMT markers in bioptic samples from patients (n = 45) with primary CRC or metastatic (m)CRC to the regional lymph node using reverse transcription-quantitative PCR and IHC staining. Results: Out of all miRNA analyzed, the miR-17 expression was most significantly different and associated with lower risk of CRC spread to the lymph node. In addition, significant relationships were found between the tumor side localization and several miRNAs expressions (miR-9, miR-29b, miR-19a, miR-19b, miR-21, miR-106a, miR-20a and miR-17). In addition, of the examined EMT markers, only VEGFA expression correlated with tumor progression (tumor grade G2). In the examined set of patient samples and their matched healthy tissue, several specific molecular markers (miRNAs associated with EMT and tumor progression) were identified with a promising prognostic potential. Their further examination in larger patient cohorts is planned to validate the present data.
Discovery and engineering of ribosomally synthesized and post-translationally modified peptide (RiPP) natural products

Ribosomally synthesized and post-translationally modified peptides (RiPPs) represent a diverse superfamily of natural products with immense potential for drug development. This review provides a concise overview of the recent advances in the discovery of RiPP natural products, focusing on rational strategies such as bioactivity guided screening, enzyme or precursor-based genome mining, and biosynthetic engineering. The challenges associated with activating silent biosynthetic gene clusters and the development of elaborate catalytic systems are also discussed. The logical frameworks emerging from these research studies offer valuable insights into RiPP biosynthesis and engineering, paving the way for broader pharmaceutic applications of these peptide natural products.
Factors Impacting Retention of Aged Care Workers: A Systematic Review

Retention of care support workers in residential aged care facilities and home-based, domiciliary aged care is a global challenge, with rapid turnover, low job satisfaction, and poorly defined career pathways. A mixed-methods systematic review of the workforce literature was conducted to understand the factors that attract and retain care staff across the aged care workforce. The search yielded 49 studies. Three studies tested education and training interventions with the aim of boosting workforce retention and the remaining 46 studies explored opinions and experiences of care workers in 20 quantitative, four mixed-methods and 22 qualitative studies. A range of factors impacted retention of aged care staff. Two broad themes emerged from the analysis: individual and organisational factors facilitating retention. Individual factors related to personal satisfaction with the role, positive relationships with other staff, families, and residents, and a cooperative workplace culture. Organisational factors included opportunities for on-the-job training and career development, appropriate wages, policies to prevent workplace injuries, and job stability. Understaffing was often cited as a factor associated with turnover, together with heavy workloads, stress, and low job satisfaction. With global concerns about the safety and quality of aged care services, this study presents the data associated with best practice for retaining aged care workers.
Implementasi Metode K-Means Clustering Untuk Menentukan Persediaan Barang Pada Toko SS BabyShop

SS BABYSHOP merupakan salah satu toko usaha yang bergerak di bidang penjualan pakaian dan keperluan sehari hari di jambi, menentukan stok yang dilakukan secara manual dan tidak akurat akan menyebabkan biaya simpan yang tinggi, karena bisa terjadi kekosongan atau kelebihan produk tertentu. Hal ini tentu akan sangat merugikan semua pelaku usaha seperti halnya pada toko SS BABYSHOP. Penelitian ini bertujuan untuk mengelompokkan produk yang di jual pada toko SS BABYSHOP menjadi 5 cluster guna untuk mengetahui item barang apa saja yang terjual dengan jumlah paling banyak, terjual dengan jumlah banyak, terjual dengan jumlah sedang, terjual dengan jumlah sedikit, dan terjual dengan jumlah paling sedikit, sehingga untuk stok yang akan disediakan berdasarkan kelompok item barang pada cluster masing-masing yang telah ditentukan. Metode yang digunakan pada penelitian ini adalah K-Means Clustering mencari partisi yang optimal dari data dengan meminimalkan kritea jumlah kesalahan kuadrat dengan prosedur iterasi yang optimal. Variabel yang digunakan adalah jumlah transaksi,jumlah stok dan rata-rata penjualan.
The Flow Regimes Associated with Hydraulic Fractured Horizontal Wells in Shale Formations

The Flow Regimes Associated with Hydraulically Fractured Horizontal Wells in Shale Formations Saba J. Raeisi Shale gas in the United States went from a practically invisible resource to massive reserves that challenge the largest conventional gas accumulations in the world. Shale gas success is directly the result of economically managed deployment of petroleum technology, namely horizontal wells . Horizontal drilling and multi-stage stimulation technologies are driving the successful development of shale plays. The production performance of hydraulically fractured horizontal wells in naturally fractured ultra-low permeability shale formations is not well established since the interaction among the hydraulic fractures, natural fracture system, and the shale matrix leads to a complex production mechanism that has not been fully investigated. Modeling and simulation of shale gas reservoir is challenging due to the complex nature of the reservoir, the strong heterogeneous and anisotropic characteristics of the system, different reservoir behavior, multiple gas-storage mechanisms and unique attributes that control the production. The objective of this study was to understand the impact of hydraulic fracture on the flow behavior of the horizontal wells completed in ultralow permeability shale formations such as Marcellus Shale. A synthetic numerical model was developed using a commercial reservoir simulator (Eclipse) with different realizations to identify the impact of number of hydraulic fractures and gas desorption on the flow regime. Diagnostic plots were used to identify the flow regimes. The diagnostic plots were also used to investigate the impact of hydraulic fractures and shale characteristics on the duration of the flow periods. The most dominant flow regimes included the “Early Linear Flow” and “Compounded Linear Flow. ” The detail investigation of the flow regimes revealed that as the number of hydraulic fracture increased, the duration of the “Early Linear Flow” became longer while the duration of the “Compounded Linear Flow” became shorter. Furthermore as the fracture half-length was reduced, the “Early Linear Flow” became shorter and the “Compounded Linear Flow became longer. Also as the fissure permeability increased, the linear flow diminished.
MOLECULAR PHYLOGENY STUDY OF SCHISMATOGLOTTIS FROM DIFFERENT REGIONS IN SABAH USING INTERNAL TRANSCRIBED SPACER REGION

The Schismatoglottideae tribe, primarily in Borneo, is notably diverse within the Araceae family. It encompasses various rainforest herbs, adapting to terrestrial, lithophytic, and rheophytic habitats. The Schismatoglottis genus, with over 175 species, mostly exclusive to Borneo due to geological preferences, stands out. A study aimed to understand genetic relationships among Schismatoglottis species from Kadamaian-Kinabalu Park, Kionsom Recreational Area, Imbak Canyon Conservation Area, Mensalong Forest Reserve, Danum Valley Conservation Area, Tawau Hills Park, and Mantailang Crocker Range Park. The Internal Transcribed Spacer (ITS) regions of twelve Schismatoglottis species were sequenced. Genomic DNA was extracted from dried-silica-gel leaf tissue using a commercial kit (Promega, USA). ITS region lengths ranged from 528 bp to 708 bp. BLAST analysis accurately identified species within the Schismatoglottis genus (95% to 98% similarity). Phylogenetic analysis revealed a highly supported sister clade, uniting Schismatoglottis porpax species from Mensalong and Kionsom, despite differing elevational habitats. This pioneering study delves into Schismatoglottis phylogenetics, particularly in Sabah, with seven of the twelve species showing potential for new species classification, pending further research.