Miracle-dz/UniFAR-FTUs huggingface dataset:
Factors Influencing Participation In Agricultural Land Preservation Programs

We analyze the factors influencing participation in Maryland's farmland preservation programs using data from a survey of agricultural landowners and spatial data on individual parcels. Factors influencing participation included distance from a major city, proximity to preserved parcels, length of family ownership, whether a child plan to continue farming and share of income from farming.
HEART DISEASE DIAGNOSIS WITH TREE STRUCTURAL NAÏVE BAYES

Among the world population, the Disease of Heart is one of the biggest mortality and morbidity causes. This disease's precise prediction and early detection might decline rate of mortality rate certainly. Learning machines are utilized to consider several problems in the science of information. In Fortune, one of efficient methods for classification is naïve bayes (NB) is because of the ability of it for learning inherent features of data. Although, generally such method groups data with just one single that makes this less efficient relatively in several classes for big classification issue. In the article, we present the tree structural naïve bayes (Tree-NB) that classifies big classification in small classifications with utilizing structure of tree. The particular classifier is adjusted after division for every small classification. By several classifiers that are employed, Tree-NB is able to complement each other in performance of classification as well as one classifier issue is solved. As all several classifiers are end-to-end frameworks, automatically Tree-NB is able to learn nonlinear relationship among output and input data with no extraction of feature. For verifying our model validity, we compare modern methods with Tree-NB by utilizing dataset of UCI. Experimental results illustrate that Tree-NB is able to obtain the higher performance in less time of training. Average Tree-NB accuracy is 1.19 % higher than the other modern methods also it possesses higher average recall and precision
Graph IRs for Impure Higher-Order Languages: Making Aggressive Optimizations Affordable with Precise Effect Dependencies

Graph-based intermediate representations (IRs) are widely used for powerful compiler optimizations, either interprocedurally in pure functional languages, or intraprocedurally in imperative languages. Yet so far, no suitable graph IR exists for aggressive global optimizations in languages with both effects and higher-order functions: aliasing and indirect control transfers make it difficult to maintain sufficiently granular dependency information for optimizations to be effective. To close this long-standing gap, we propose a novel typed graph IR combining a notion of reachability types with an expressive effect system to compute precise and granular effect dependencies at an affordable cost while supporting local reasoning and separate compilation. Our high-level graph IR imposes lexical structure to represent structured control flow and nesting, enabling aggressive and yet inexpensive code motion and other optimizations for impure higher-order programs. We formalize the new graph IR based on a λ-calculus with a reachability type-and-effect system along with a specification of various optimizations. We present performance case studies for tensor loop fusion, CUDA kernel fusion, symbolic execution of LLVM IR, and SQL query compilation in the Scala LMS compiler framework using the new graph IR. We observe significant speedups of up to 21x.
Spotting Cyber Breaches in IoT Devices

In the ever-growing realm of the Internet of Things (IoT), ensuring the security of interconnected devices is of paramount importance. This paper discusses the process of spotting cyber breaches in IoT devices, a significant concern that needs urgent attention due to the susceptibility of these devices to hacking and other cyber threats. With billions of IoT devices worldwide, the detection and prevention of cybersecurity breaches are critical for maintaining the integrity and functionality of networks and systems. In this paper, we showcase the outcomes achieved by employing the LightGBM technique for a cyberattack prediction challenge, which was a part of the FedCSIS 2023 conference.
The Impact of Implementing Emergency Curriculum on Students' Creativity during
 Covid-19 Pandemic Learning

The Covid-19 pandemic has changed the worldwide education system; one of which is demanding schools to implement Emergency Curriculum in online learning. According to the results of a quick survey of learning from homes conducted in 34 provinces in Indonesia, there are 97.6% of schools that have applied online learning with a total of respondents of 988 principals on each education rank from elementary school to high school or vocational school. This sudden change of education system brings both positive and negative impacts for students, teachers and schools. Besides, it also affects students' creativity during the teaching-learning process. This study aims to describe the impact of Emergency Curriculum implementation on students' creativity in learning drama appreciation at a vocational school during the Covid-19 pandemic period. Other than finding the positive and negative impact of implementing Emergency Curriculum, this study also shows students' creativity during online learning. This study is descriptive qualitative analyzing the impact of implementing Emergency Curriculum on students' creativity during the Covid-19 pandemic learning. Primary data is taken directly from data sources through interviews directly as well as using digital media, and observations against research informants including teachers, principals, vice principle of curriculum affairs, and students of SMKN 1 Karanganyar class Multimedia I. Secondary data is data obtained from the results of the skill scoring of making a role-play script, and various other sources such as archive documents, and other reading sources. Those collected data were then analyzed by using interactive analysis techniques validated by using data triangulation, theory, method and researcher. The findings in the study were to figure out the impact of implementing Emergency Curriculum on students' creativity during the Covid-19 pandemic learning. This was evidenced by the data of the students' assignment results along with the reality happened when research was conducted. On its implementation, this study resulted in new perspectives about the real differences between positive and negative impacts of implementing Emergency Curriculum and how it affects students' creativity during the Covid-19 pandemic learning.
Motor control and skill acquisition in pediatric physical therapy: an enactive proposal

Theories of motor control and skill acquisition strongly influence and guide various fields of clinical practice. In last decades, changes in theoretical frameworks related to the conceptualization of brain plasticity, functional structures within the child, and environment have led to a revision of therapy approaches progressing from therapist-driven to child-initiated approaches. Even though theoretical frameworks and clinical practice are closely linked to the child’s body, the profession has paid less attention to theories concerning the body’s role and status in interpersonal relationships when fostering motor control and skill acquisition in children. In this theoretical paper we discuss the theoretical frameworks of motor control and skill acquisition that currently guide clinical practice. Through highlighting valuable contributions of these theories, we explore theoretical and practical benefits pediatric physical therapy can acquire by taking an enactive approach as a means to bring the child as a subject into focus. We rely on enactive concepts of embodiment, autonomy, and participatory sense-making in our exploration to provide an extended understanding of motor control and skill acquisition shaping our beliefs about what counts in therapeutic encounters in pediatric physical therapy.
Determinantes de la desigualdad en la Comunidad Andina: evidencia desde un panel VAR bayesiano

Este artículo analiza los determinantes de la desigualdad de ingresos en los países de la Comunidad Andina considerando los efectos de la inversión extranjera directa, el capital humano, el desempleo y la producción por medio de un modelo panel VAR bayesiano. Se halla que: i) la inversión extranjera directa tiene un efecto negativo en la desigualdad de ingresos en Bolivia, lo que es consistente con la teoría neoclásica del comercio, y uno positivo en Perú, el país más minero dentro de la muestra; ii) la respuesta de la desigualdad ante shocks en el capital humano es positiva en la mayoría de casos, lo que podría significar que la educación amplifica la brecha existente; iii) el impacto del desempleo sobre la desigualdad es positivo en Colombia, el país con menor informalidad, negativo en Perú y no significativo en Bolivia y Ecuador, donde la pérdida del empleo formal no necesariamente afecta los ingresos porque existe la alternativa del empleo informal; iv) el efecto de la producción sobre la desigualdad es positivo en Bolivia y Colombia, pero negativo en Ecuador y Perú.
Opuntia ficus indica fruit alleviates the cerebellar neurotoxicity induced by monosodium glutamate and aspartame in female rats and their pups

Monosodium glutamate (MSG) has a long history of use enhancer to flavor food but modern scientific research has shown that it has very serious damage to the different organs of the body, especially the nervous system. Aspartame (ASP) is one of the most widely used artificial sweeteners in the world. ASP was assured to induce many hazardous effects on the structure and functions of the brain. Opuntia ficus indica fruit as a source of natural liquid sweetener cactus fruit juice laden with total phenolic, total flavonoids, vitamin C, vitamin E, and β-carotene can safeguard the body against oxidative stress and minimize cataract risk in diabetes patients. This work aims to evaluate the possible ameliorative role of fruit juice of O. ficus indica against MSG and ASP-induced cerebellar toxicity in female rats and their fetuses. For this study, 36 pregnant females were used in this study and randomly divided into six groups on the fourth day of gestation: control, Opuntia group, MSG group, ASP group, MSG plus O. ficus indica group, and ASP plus O. ficus indica group. The experiment extended from the fourth day of pregnancy till the end of weaning. At the end of the experiment, the mother’s rats and their pups were dissected for collection of blood and removal of the cerebellum for estimation of biochemical and histopathological changes. The obtained results revealed pronounced histopathological signs in the cerebellar cortex of MSG, and ASP-treated dams and their pups. These signs included disorganized cerebellar layers, pyknotic Purkinje and granular cells, and scattered vacuoles. The immunohistochemical results revealed strong expression for GFAP and P53 protein while weak expression for Bcl-2 in the cerebellar cortex of MSG and ASP groups compared with control. Additionally, the obtained biochemical analysis shows a significant increase in the levels of caspase-3 and IL-1 in the cerebellar tissue while a significant decrease in the levels of serum insulin and IGF-1 compared with control. Co-supplementation of O. ficus indica fruit juice with MSG or ASP successfully alleviated the deleterious histopathological, immunohistochemical, and biochemical changes induced by MSG and ASP.
Crow Way: An Optimization Technique for generating the Weight and Bias in Deep CNN

Fine-tuning Convolutional Neural Networks (CNNs) weights and biases are essential for solving difficult machine learning problems. We provide a hybrid optimizations strategy that combines the benefits of Crowd Search (CSA) and Brainstorm Optimization (BSO). CSA-BSO optimizes CNNs. CSA-BSO optimizes CNN weights. Our fitness measures determine each crow's location and speed throughout the CSA phase. The BSO phase mixes optimal replies with random ones to create new solutions. The best new ideas move on. After a certain number of iterations, we alternate between the CSA and BSO phases and pick the best solution as the CNN's final state. We design and test the CSA-BSO approach on many CNN architectures and datasets. Experimentally, the hybrid algorithm outperforms CSA and BSO in convergence time and solution quality. CSA and BSO collaborate to efficiently employ feasible regions and investigate a bigger search field, boosting optimizations. Stable and adaptable, CSA-BSO supports many CNN architectures and data formats. This study's main contribution is the CSA-BSO, a unique hybrid optimizations approach for convolutional neural network weight and bias optimizations. It beats CSA and BSO. The recommended strategy improves CNN picture classification, object recognition, and NLP.
Activated protein C in epilepsy pathophysiology

Epilepsy is one of the most common neurologic disorders that is characterized by recurrent seizures, and depending on the type of seizure, it could lead to a severe outcome. Epilepsy’s mechanism of development is not fully understood yet, but some of the common features of the disease are blood-brain barrier disruption, microglia activation, and neuroinflammation. Those are also targets of activated protein C (APC). In fact, by downregulating thrombin, known as a pro-inflammatory, APC acts as an anti-inflammatory. APC is also an anti-apoptotic protein, instance by blocking p53-mediated apoptosis. APC’s neuroprotective effect could prevent blood-brain barrier dysfunction by acting on endothelial cells. Furthermore, through the downregulation of proapoptotic, and proinflammatory genes, APC’s neuroprotection could reduce the effect or prevent epilepsy pathogenesis. APC’s activity acts on blood-brain barrier disruption, inflammation, and apoptosis and causes neurogenesis, all hallmarks that could potentially treat or prevent epilepsy. Here we review both Activated Protein C and epilepsy mechanism, function, and the possible association between them.
ONLAY VERSUS RIVES-STOPPA TECHNIQUES IN THE TREATMENT OF INCISIONAL HERNIAS

ABSTRACT BACKGROUND: In the surgical correction of large incisional hernias, the use of a prosthesis is essential in most cases regardless of the technique chosen. The preference is for the polypropylene prosthesis. AIMS: To compare the onlay and Rives-Stoppa techniques in the correction of incisional hernias, their immediate results, complications, advantages, and disadvantages. METHODS: Two groups of patients with incisional hernias were analyzed, submitted to the onlay (19 patients) and Rives-Stoppa (17 patients) techniques, and that used polypropylene prostheses. General epidemiological variables, perioperative data variables, and postoperative complications were assessed. RESULTS: The patients’ epidemiologic profile was similar between both groups. The majority were women (58.4%), with a mean age of 65.5 years and a previous mean body mass index of 41.5 kg/m². The Rives-Stoppa technique was employed in most patients (52.7%). Those submitted to the onlay technique had longer abdominal drainage time and longer hospital stay, as well as a higher incidence of seromas and surgical wound infection. CONCLUSIONS: The incisional herniorrhaphy technique with the placement of a pre-peritoneal polypropylene mesh by the Rives-Stoppa technique was superior to the onlay due to lower rates of drain use, hospital stay, and postoperative complications.
Implementing smoking cessation in routine primary care—a qualitative study

Background The use of digital tools has been proposed as a solution to some of the challenges of providing preventative services in primary care. Although there is a general acceptance among patients to use digital self-help tools to quit smoking, and healthcare organizations are increasingly urged to incorporate these tools in clinical practice, it is unclear how and for whom these innovations can be incorporated into clinical practice. Objectives To explore health care professionals' perceptions about smoking cessation practice in routine primary care and the use of digital tools in this work. Methods A qualitative study with nine in-depth telephone interviews with health care professionals working in primary care in Sweden. Convenience sampling and snowball technique was used as recruitment strategy. Informants included registered, district and auxiliary nurses as well as behavioral therapists. All informants were female, between 43 and 57 years old and experience of working with smoking cessation in primary care and possibility to recommend digital interventions to smokers. Results Informants described smoking cessation practice in primary care as (i) identifying smoking patients, (ii) pursuing standardized routines for smoking cessation practice and (iii) keeping smoking cessation practice on the agenda. Digital tools were described by informants to be used in different ways: (i) replicating practice, (ii) complementing practice and (iii) enabling access to health care practitioners. Finally, the analysis showed that patients' expectations and behaviors contributed to how and when smoking cessation practice was conducted, including the use of digital tools. Conclusions Implementing smoking cessation practice in primary care in Sweden encompass continuous work of reaching smoking patients, building buy-in among peers and keeping tobacco on the practice agenda. Digital interventions are used to replicate, complement and enabling access to care. The findings suggest that poor continuity of staff and negative attitudes towards preventative work may challenge smoking cessation practice. However, societal changes in the awareness of the health risks of tobacco use including shifting social norms regarding the acceptance of smoking may contribute to a normalization of speaking about smoking in primary care practice. Increased knowledge is needed on how, and for whom digital tools can be incorporated in clinical practice.
Factors for Effective Communication of IT Costs and IT Business Value

Nowadays, organizations must invest strategically in information technology (IT) and choose the right digital initiatives to maximize their benefit. Nevertheless, Chief Information Officers still struggle to communicate IT costs and demonstrate the business value of IT. The goal of this paper is to support their effective communication. In focus groups, we analyzed how different stakeholders perceive IT costs and the business value of IT as the basis of communication. We identified 16 success factors to establish effective communication. Hence, this paper enables a better understanding of the perception and the operationalization of effective communication.
Evaluation of the performance of trading companies in Serbia using the FF-WASPAS and WASPAS methods

The main goal of this research paper is to comprehensively analyze the performance of trading companies in Serbia and propose appropriate measures for future improvement. In the specific case study, DELHAIZE Serbia achieved a return on sales of 2.50%, a return on assets of 3.56% and a return on capital of 6.95% in 2021. On the other hand, LIDL Serbia achieved a return on sales of 5.77%, a return on assets of 6.66% and a return on capital of 12.55% in the same year. Thus, LIDL Serbia performed more successfully than DELHAIZE Serbia. In general, foreign retail chains demonstrate better performance than domestic ones. One reason for this is that they adopt newer business methods and have a higher degree of digitization of the entire business.
Tectonostratigraphy of the Southern Sivas Tertiary Basin (Central Turkey) and Comparison with Landsat MSS Imagery

The Sivas Basin is one of the most important sedimentary basins, in terms of tectonics and hydrocarbon potential, in the Central Anatolian region of Turkey. Its development is related mainly to the closure of the northern branch of the Neotethyan ocean, as well as to influences of the closure of the Inner Tauride ocean. This basin's complex history is related to several successive orogenic phases during the Cenozoic. Other interesting characteristics of this basin, as in the Central and Eastern Anatolian basins, are the tectonics and lithological features associated with the younger gypsum deposits. The study area comprises two distinct regions, namely the Savcun and Karacaoren areas. The primary stratigraphie relationships between Lutetian turbidites, Oligocene continental gypsum and detritics, and lower to middle Miocene continental deposits of the Savcun area have been elucidated. In this part of the study area, S-verging imbricated thrust systems, mainly located within the gypsum series, developed dur.
Optum: A Three-in-One Multimodal Tactile Sensor Based on Optical Fiber Knots for On-Orbit Service

The complex environment of outer space brings great challenges to on-orbit servicing tasks. Here, we report Optum: a frustum-shaped multimodal tactile sensor for a robot to recognize the surface features of a satellite. Based on optical fiber knots (OFNs), the Optum consists of three independent working modules that can measure pressure, hardness, and texture, respectively. Their sensing mechanisms are all based on the force-induced microbending loss of OFNs. A minimum resolution of 0.12 N is achieved for pressure sensing from 0–10 N, and a resolution ranging from 0.03–0.45 is recorded for hardness sensing from 1–30 in Shore A scale. For texture sensing, the sensor can measure wavelengths down to 300 µm. Installed on the end of a robotic arm, the Optum can touch the satellite by adjusting the posture of the arm to achieve a specific tactile sensing function. Free from electromagnetic interference, the Optum would be a valuable tool for on-orbit servicing tasks. As a pilot study, the Optum is implemented in a dual-arm space robot system for a solar panel unfolding task.
Evaluation of the skill and added value of a reanalysis‐driven regional simulation for Alpine temperature

To determine whether the use of regional climate models improves the representation of climate is a crucial topic in climate modelling. An improvement over coarser scale models is expected especially in areas with complex orography or along coastlines. However, some studies have shown no clear added value for regional climate models. In this study a high‐resolution regional climate simulation performed with REMO 5.0 (regional model) over the whole of Europe over the period 1958–1998 is analysed for 2‐m temperature over the European Alps and their surroundings called the Greater Alpine region (GAR). The simulation is driven by perfect boundary conditions at the lateral boundaries provided by the ERA40 reanalysis and spectral nudging of the large‐scale wind fields towards ERA40 values for the upper layers inside the model domain. The added value of the regional simulation (1/6° resolution) is analysed with respect to the driving reanalysis (1.125° resolution).
Contribution of satellite altimetry data in the geophysical investigation of the Red Sea Region, Egypt

Successful development of geodetic satellite missions has aroused new interest in determining global and regional gravity field based on satellite data. Satellite altimetry data enable direct determination of the geoid over sea regions.In Egypt, where land and marine geophysical data are inadequate because of rough topography and economic reasons, the use of satellite altimetry data is of special importance.The northern Red Sea region has been selected as a site for case study of the current research, after applying spectral analysis to reveal near-surface structure, the residual geoid of the studied region shows a good correlation with the known geologic features. Moreover, satellite-based gravity data enhance small-scale features and agrees well with land and marine gravity data. Thus, geoid undulation and satellite gravity data can be a complementary source of data to determine near-surface and deep structures.