Miracle-dz/UniFAR-FTUs huggingface dataset:
ASSESSMENT OF REMOTE SENSING ON DEFORESTATION OF ECONOMIC TREE SPECIES IN WUDIL, KANO STATE, NIGERIA

A remote sensing strategy was investigated to evaluate how temperature and rainfall affect the deforestation of economically important tree species in Wudil, Kano Nigeria. The research was carried out in Wudil. To assess the vulnerability of the study area to desertification and the abundance of economic tree species. Landsat satellite products (Landsat 5, 7, 8. were used as the sources of remote sensing imageries. These products were sourced for intervals of ten years, from 1986 to 1999, 2006 to 2016, and 2020. Standardized temperature anomaly and precipitation index from 1986 to 2020 were analyzed using primary and secondary data obtained for information on temperature and rainfall, a hundred questionnaires were used to analyze how much anthropogenic activity has contributed to desertification in the area by looking at their socioeconomic activities, roads, and infrastructural development. To determine the quantity, distribution, growth, and yield of all the species, a transect of one square kilometer was surveyed using regional techniques in each of the four cardinal directions. Principal component analysis revealed that the activity variables and activity observations for 1999, 2006, 2016, and 2016 were all negative, while the years 1986 and 2020 were positive. Increased trends in temperature and decreasing trends in rainfall are evident using the Mann-Kendall analysis, with P-values of 0.0 and 0.003, respectively, which are smaller than the alpha value of 0.05. The main causes of drought and desertification vulnerability according to the findings include variations in the characteristics of rainfall, human activities, and overgrazing. More tree-planting initiatives should be encouraged, ideally making them an annual event in the study region.
Design and Analysis of Charge Pumping Circuit for Low Power Charge Pump Based Phase Locked Loop Organization

In general the Charge pumping (CP) circuit is one of the major power consuming modules in charge pumping based Phase locked loop (CP-PLL) architecture. CP circuit transforms the voltage fluctuation in the Phase and Frequency detection circuit into equivalent current signal and supports in sustaining a steady control signal to retain the frequency of Voltage control oscillator (VCO). In this article a new CP circuit is proposed by using C2MOS logic. To construct the topology of anticipated circuit, the power saving practices such as lessening the counts of total MOS device usage and path splitting approaches are integrated, which leads to falling of switching and short circuit power dissipation correspondingly. The proposed CP model is executed in DSCH - MICROWIND tool and assessed by simulating the model at 0. 12µm - 6 Metal model CMOS technology. The system level simulation indicates that the anticipated design attains power saving from 59% to 79% with minimum layout area occupation.
Méthode des moments de probabilité pondérés. Application à la loi de Jenkinson

Cet article a pour objectif de presenter une methode, relativement nouvelle, d'estimation des parametres d'une distribution de probabilite : la methode des moments de probabilite ponderes, introduite par Greenwood et al. (1979). La facilite de mise en œuvre, la robustesse et l'efficacite de cette methode ont retenu notre attention. Nous faisons une synthese des etudes menees sur l'application de cette methode a l'estimation des parametres de la loi de Jenkinson (Generalized Extreme Value distribution - GEV).
Polish Adaptation and Psychometric Validation of the PREM-C9 Questionnaire for Patients with Chronic Obstructive Pulmonary Disease

Introduction: Chronic obstructive pulmonary disease (COPD) is a common, preventable, and treatable disease. The first PREM (patient-reported outcome measure)-type questionnaire that has been dedicated to assess the experience of care in COPD is the PREM-C9. Aim: The aim of this study was to create a Polish version of the PREM-C9 and determine its psychometric characteristics. Methods: The validation procedure involved forward and back translation. We included 42 patients with COPD. The psychometric properties were assessed using Cronbach’s alpha, Bartlett’s test, the Kaiser–Meyer–Olkin test, and Spearman’s correlation coefficient. The validity of the questionnaire was assessed using a principal component analysis for the extracted principal components. The validity of the factor analysis was demonstrated using Bartlett’s sphericity test and the Kaiser–Meyer–Olkin (KMO) test. A factor analysis was performed using the Oblimin and Varimax rotation. The reliability of the questionnaire was assessed using Cronbach’s alpha. Results: The Polish version of the analyzed questionnaire met all the validation criteria: face, translation, psychometric, functional, and reconstruction equivalence. Spearman’s correlation results between the Polish PREM-C9 and CAT were as follows: rho = 0.44, p = 0.003539; HADS-Anxiety: rho = 0.370864, p = 0.015612; and HADS-Depression: rho = 0.387405, p = 0.011253. Conclusions: The developed Polish PREM-C9 questionnaire is a reliable and valid tool that assesses Polish COPD patients’ experiences of their disease and the care they receive.
Long‐term trends in precipitation and temperature across the Caribbean

This study considers long‐term precipitation and temperature variability across the Caribbean using two gridded data sets (CRU TS 3.21 and GPCCv5). We look at trends across four different regions (Northern, Eastern, Southern and Western), for three different seasons (May to July, August to October and November to April) and for three different periods (1901–2012, 1951–2012 and 1979–2012). There are no century‐long trends in precipitation in either data set, although all regions (with the exception of the Northern Caribbean) show decade‐long periods of wetter or drier conditions. The most significant of these is for the Southern Caribbean region which was wetter than the 1961–1990 average from 1940 to 1956 and then drier from 1957 to 1965. Temperature in contrast shows statistically significant warming everywhere for the periods 1901–2012, 1951–2012 and for over half the area during 1979–2012. Data availability is a limiting issue over much of the region and we also discuss the reliability of the series we use in the context of what is known to be available in the CRU TS 3.21 data set. More station data have been collected but have either not been fully digitized yet or not made freely available both within and beyond the region.
Use of Behavioural Pain Scale in assessing pain during physical therapy procedures in sedated, mechanically ventilated patients in ICU: A cross-sectional observational study

Background: Critically ill patients who are sedated and mechanically ventilated, experience significant pain during physical therapy procedures but cannot communicate effectively due to sedation. Identification and evaluation of pain with validated behavioral observation tools in patients unable to self-report pain improve quality of care by administration of appropriate analgesia or sedation during routine physical therapy care of ventilated patients. Aims and Objectives: This study aimed to assess pain in sedated, mechanically ventilated patients using the Behavioural Pain Scale (BPS) during physical therapy procedures like body positioning and tracheal suctioning. Materials and Methods: Following ethical approval, 50 adult patients, sedated and mechanically ventilated, admitted in the ICUs in a tertiary care teaching hospital were assessed for pain severity using BPS during routine physical therapy procedures. Patients ≥18 years of age, both male and female, with Glasgow Coma Scale of (GCS) < 10, were included in the study. Patients with Ramsay Sedation Scale (RSS) of 3, 4, and 5, mechanically ventilated for at least 48 hours, who were unable to verbalize, patients who were undergoing routine physical therapy that included body positioning and tracheal suctioning for removal of secretion were included. Patients below 18 years of age, able to verbalize pain, and GCS score of ≤ 3, were excluded from the study. Conclusion: BPS is recommended for better pain evaluation during physical therapy procedures in sedated, mechanically ventilated adult patients in the ICU.
Machine Learnig based Number Plate Recognition in Roadways

The main goal of the study is to find the vehicles that are uninsured and do not have valid fitness certificates with the help of the image processing technique. Vehicles violating traffic rules must be charged with fines. Manual recognition of the vehicle is challenging. The technology is based on automatic recognition of the license plate recognition using image processing, character segmentation, and recognition technology. In this work, image acquisition comes first. The haar cascade approach will be used to position the license plate after the vehicle's image has been identified. The license plate is then cropped, and optical character recognition extracts the character from the plate on the cropped image. The number extracted from the number plate will be checked with the violators data list. If the number exists in that data list some amount of fine will be generated. The details of the fined vehicle will be stored in the database and a message will be sent by push bullet app to the respective officers. This system can be used in many different countries based on their country-specific standard or fonts.
Extreme Precipitation Events in the Western United States Related to Tropical Forcing

Abstract Three-day accumulations of precipitation for 2.5° long × 2.0° lat areas along the west coast of the United States are used to rank precipitation events. Extreme precipitation events (those above the 90th percentile) occur at all phases of the El Nino–Southern Oscillation (ENSO) cycle, but the largest fraction of these events (for the West Coast as a whole) occur during neutral winters just prior to the onset of El Nino. In the tropical Pacific these winters are characterized by enhanced activity on intraseasonal (roughly 20–60 day) timescales and by relatively small sea surface temperature anomalies compared to ENSO winters. For these winters, lagged composites are used to document a coherent relationship between the location of extreme precipitation events along the West Coast and the location of enhanced tropical convection on intraseasonal timescales. The evolution of the atmospheric circulation patterns associated with the extreme precipitation events is described and a physical mechanism rel.
A Review of Artificial Intelligence-Based Gait Evaluation and Rehabilitation in Parkinson’s Disease

Parkinson's disease (PD) is a long-term degenerative disease of the central nervous system that affects both motor and non-motor functions. In most cases, symptoms develop gradually, with non-motor symptoms increasing in frequency as the condition progresses. Tremors, stiffness, slow movements, and difficulty walking are some of the early symptoms. There may be problems with cognition, behavior, sleep, and thinking. Dementia caused by PD becomes more common as the disease progresses. The development of PD is linked to certain sequences of motion that eventually contribute to diminished function. Patients with Parkinson's disease (PWPD) have a sluggish, scattered gait that is accompanied by intermittent freezing of gait (FOG), in which efficient heading briefly pauses. In individuals with severe PD, FOG is a neurological deficit that is related to falls and has an unfavorable impact on the patient's standard of living. Artificial intelligence (AI) and ambient intelligence (AmI) are inextricably linked as intelligence is the ability to gain new information and employ it in novel contexts. The ambience is what accompanies us, while artificial represents something developed by humans. Wearable technologies are being designed to recognize FOG and support patients in the beginning to walk again via periodic cueing. The article proposes a unique automated approach for action description that utilizes AI to carry out a non-intrusive, markerless evaluation in real-time and with full robotics. This computerized method accelerates detection and safeguards from human error. Despite significant improvements brought about by the advent of novel technologies, the available assessment platforms still fail to strike the ideal equilibrium among expenditure, diagnostic precision, velocity, and simplicity. The value of the recommended approach can be seen through a comparison of the gait parameters collected by each of the motion-tracking gadgets.
How Waterborne Disease Outbreaks Relate to Treatment Failures

Summary Persons working in jobs related to drinking water treatment need to be aware of the circumstances that can lead to waterborne outbreaks in the general population consuming tap water. Often such outbreaks are associated with not just one event but with the coincidence of a combination of problems, a single one of which might not have caused a disease outbreak. This case study reviews a number of outbreaks, demonstrating how the occurrence of two or more events or problems in the same time frame could have led to the persistence of pathogens through the treatment process and into the drinking water and thus caused the outbreak in question. Because treatment-related outbreaks tend to be associated with multiple causes, water treatment plant operation needs to be optimized at all times, especially during times of changing source water quality. In addition, those responsible for managing and operating water treatment plants need to be aware of conditions within the watershed or the recharge area of the aquifer serving as the source of water for the plant.
AVEN: a novel oncogenic biomarker with prognostic significance and implications of AVEN-associated immunophenotypes in lung adenocarcinoma

Introduction: AVEN, an apoptosis and caspase activation inhibitor, has been associated with adverse clinical outcomes and poor prognosis in Acute myeloid leukemia (AML). Targeting AVEN in AML improves apoptosis sensitivity and chemotherapy efficacy, making it a promising therapeutic target. However, AVEN’s role has not been studied in solid tumors. Therefore, our study investigated AVEN as a prognostic biomarker in a more comprehensive manner and developed an AVEN-derived prognostic model in Lung adenocarcinoma (LUAD). Method: Pan-cancer analysis was performed to examine AVEN expression in 33 cancer types obtained from the TCGA database. GEPIA analysis was used to determine the predictive value of AVEN in each cancer type with cancer-specific AVEN expression. Lung Adenocarcinomas (LUAD) patients were grouped into AVENhigh and AVENlow based on AVEN expression level. Differentially expressed genes (DEGs) and pathway enrichment analysis were performed to gain insight into the biological function of AVEN in LUAD. In addition, several deconvolution tools, including Timer, CIBERSORT, EPIC, xCell, Quanti-seq and MCP-counter were used to explore immune infiltration. AVEN-relevant prognostic genes were identified by Random Survival Forest analysis via univariate Cox regression. The AVEN-derived genomic model was established using a multivariate-Cox regression model and GEO datasets (GSE31210, GSE50081) were used to validate its prognostic effect. Results: AVEN expression was increased in several cancer types compared to normal tissue, but its impact on survival was only significant in LUAD in the TCGA cohort. High AVEN expression was significantly correlated with tumor progression and shorter life span in LUAD patients. Pathway analysis was performed with 838 genes associated with AVEN expression and several oncogenic pathways were altered such as the Cell cycle, VEGFA-VEGFR2 pathway, and epithelial-mesenchymal-transition pathway. Immune infiltration was also analyzed, and less infiltrated B cells was observed in AVENhigh patients. Furthermore, an AVEN-derived genomic model was established, demonstrating a reliable and improved prognostic value in TCGA and GEO databases. Conclusion: This study provided evidence that AVEN is accumulated in LUAD compared to adjacent tissue and is associated with poor survival, high tumor progression, and immune infiltration alteration. Moreover, the study introduced the AVEN-derived prognostic model as a promising prognosis tool for LUAD.
School Feeding Program Implementation and Students’ Discipline in Twelve Years Basic Education in Rwanda

The effective implementation of school feeding program plays a significant role in the promotion of students’ retention and disciple in general. The purpose of this study therefore, sought to determine the effect of school feeding program implementation on students’ discipline in twelve years basic education in Nyarugenge district in Rwanda. This study employed correlation research design. The target population of this study was 194 people corresponding to the sample size of 131respondents by using Solvin’s formula. Questionnaire and guided interview were used as data collection instruments. The findings revealed that the implementation of school feeding influences the students’ discipline at 64.9% as indicated by the R-Square. The findings also revealed that timely food provision, meal/snacks provision. Community participation and functional monitoring and evaluation system as well as school feeding management can improve students’ discipline. It was concluded that effective implementation of school feeding program influences students’ discipline somewhere between 49.2 percent and 78.2 percent. The study concludes that the implementation of the school feeding program has a significant positive impact on student discipline in the 12-year basic education system in Nyarugenge District, Rwanda. Teachers largely agree that the program has merits, from timely submission of assignments to community involvement in feeding initiatives. The study recommends that Ministry of Education in Rwanda should consider standardizing the school feeding program across all schools in the 12-year basic education system. In addition, it is crucial for educational planners to work in collaboration with school administrators to develop strategies that strengthen student discipline through the school feeding program. This may include training programs for school staff on how to effectively manage and monitor the feeding program, as well as creating channels for parents to be more involved, given their crucial role in the program's success. Daily oversight by school principals, as well as regular feedback mechanisms, should be put in place to ensure that the program is achieving its goals, both in terms of nutrition and student discipline.
Characteristic of Elite Male 800-m Runner’s Race Performance Based on Hybrid Computing Methods

The purpose of the study was to analyze the characteristics of elite men’s 800-m race performance, which help coaches to obtained the winning experience of 800-m race and prepare for athletes’ training more efficiently. Hybrid computing methods were applied to analyze athletes’ race performance. The study found that the competitive capability of elite athletes mainly include maximal speed running, speed endurance, and even pacing running. The maximal speed advance from 700–800 to 100–200-m sector, the velocity is also increase at the same time. The first peak speed (100–200 m) is higher than the second (500–600 m). Reduce the 0–400 m split times could be contributing to achieve personal best. 200–400 m is the even pacing phase which have the function of adjust physiological condition and preserve energy. The speed endurance was the most important factor to won the 800-m race. Place in permanent ranking and adopt the follow-running tactic can increase the odds to be medalist.
Research on Consumer Behavior Prediction Based on E-commerce Data Analysis

The user behavior log of e-commerce platform contains a wide range of data, which can be roughly divided into three types: user basic information, merchant information and user behavior information. Behavioral information includes clicks, favorites, shopping carts and purchases. Because of the asymmetry of online shopping information, the virtuality of trading environment, the incomplete perception of goods and the unsynchronization of trading process, consumers are faced with many uncertainties in the process of online shopping. According to the specific research problems, this paper applies the real consumer behavior data in the e-commerce data platform to build a model to predict consumer behavior. The consumer behavior sequence and other characteristics are analyzed by two machine learning methods respectively. First, the consumer behavior sequence based on time sequence is analyzed. Add the obtained probability value as a new feature to other feature sets as the input of NB (Naive Bayes) model, and train the model to get the probability of whether consumers will buy, and then get the final judgment result of the model. The results show that the fusion model has a balanced performance for consumer behavior sequences with different lengths, and its accuracy can be kept at around 0.9. The research on the problems raised in this paper can also be extended to other fields.
On the Use of FTAs: A Review of Research Methodologies

There has been much confusion, rather than debate, on the use of free trade agreements (FTAs). Unfortunately, a large part of the confusion is caused by the absence of consensus on the meaning of key terms such as the "utilization rate" and "usage rate" of FTAs, and the lack of knowledge on upward or downward biases from various information sources regarding the use of FTAs. Rather than making an original empirical contribution, this article reviews existing studies on the issue and attempts to identify the relevant methodologies for assessing the use of FTAs.
Extended Power Dynamic Range and Enhanced Power Conversion Efficiency of a Switched-Capacitor DC–DC Converter: A Tutorial

This tutorial brief presents a concise overview of integrated switched-capacitor (SC) DC-DC converter topologies for miniaturized energy harvesting (EH) IoT systems aiming for extended power dynamic range (PDR) and enhanced power conversion efficiency (PCE). This tutorial initiates by delving into the intricate SC conversion methodologies tailored for energy harvesting (EH) applications, including i) fine-grained conversion ratio (CR) tuning, ii) multiphase soft charging, and iii) clock frequency and amplitude scaling. Next, mathematical analysis is conducted along with an established model to correlate the prevailing dominant loss and its impact on the PCE and the PDR, aiming to provide designers with a guideline for different design parameter choices for the triode/subthreshold domain.