Miracle-dz/UniFAR-FTUs huggingface dataset:
Development and Field Application of an Automated Pipe Jacking Friction Resistance Identification and Warning System in Construction

Minimizing frictional resistance is crucial for ensuring the safety and smooth progress of pipe jacking construction. However, due to the unpredictability of geological conditions, it is difficult to grasp the frictional resistance during construction, which poses challenges to safe and smooth construction. In order to reduce the frictional resistance during the process of pipe jacking, an automated pipe jacking friction resistance identification and warning system is thus innovatively proposed. This system uses jacking resistance sensors to identify resistance during the jacking process. When the jacking resistance exceeds a certain threshold, the system will send alerts, which could prompt construction workers to adjust the rheological slurry ratio according to the on-site soil conditions. This system includes the following major components: (1) an analysis of primary factors influencing pipe frictional resistance and a model for resistance calculation, (2) the examination of forces exerted on disturbed soil during pipe jacking construction to determine the optimal placement of resistance sensors, (3) the design and operational principles for an automated resistance identification and warning system, and (4) the application of a slurry shield construction method for resistance reduction. The research has practical significance in providing a reference for developing intelligent pipe jacking and contributing to the improvement in construction safety levels.
Spatiotemporal Analysis of the Controlling Factors of Forest Cover Change in the Romanian Carpathian Mountains

Forest cover change is driven by complex processes that depend on political, conservation, and biophysical conditions. At present, mountain areas worldwide are undergoing intense forest cover change. Local-scale studies exist, but policy makers lack reliable and consistent information at the regional scale about long-term trends, controlling factors, and the success of existing policy measures. Long-term forest cover change data based on advanced image preprocessing procedures have recently become available. This study explores the potential of such data for a regional-scale analysis of forest cover change in mountain areas by analyzing forest cover change in the Romanian Carpathian Ecoregion (about 107,000 km2) between 1985 and 2010. It shows that (1) extrapolations from local to regional scale are inaccurate, (2) European forest protection policies have been unsuccessful, and (3) the Romanian Carpathians are greening due to land abandonment in remote areas.
A Review of the Role of Built Environment and Temperature in the Development of Childhood Obesity

The burden of obesity is rising globally and is studied widely, yet the evidence for the association of environmental factors (both built and natural) with childhood obesity remains inconsistent. A relation with temperature as a proxy for natural environmental factors for obesity has not been reviewed previously. The purpose of this review was to assimilate updated evidence on environmental factors of childhood obesity. Three databases, MEDLINE (Medical Literature Analysis and Retrieval System Online), Web of Science, and Cochrane, were searched for articles related to the effect of built environment and temperature on childhood obesity in 6-12-year-olds published in the last five years. Twelve studies were identified: four longitudinal and eight cross-sectional. The studies were appraised using the National Institute of Health Quality (NIH) Assessment Tool. A review of included studies showed that built environmental features like higher residential and population density, higher intersection density, more playgrounds, and all park features like the presence or availability of parks, high number of parks, proximity to parks, and an increased park land area, showed a protective association against childhood obesity while land use mix showed a promoting association for the development of childhood obesity. Inconclusive evidence was observed for other built environmental features. The search strategy did not retrieve any literature published in the past five years studying the association between temperature and the development of childhood obesity. Standardization of definitions of exposure and outcome measures is recommended. Further research studying the relationship between environmental temperature and the development of childhood obesity is recommended.
Neurodevelopmental outcome of low-risk moderate to late preterm infants at 18 months

Background Of the 15 million preterm births that occur worldwide each year, approximately 80% occur between 32 and 36 + 6 weeks gestational age (GA) and are defined as moderate to late preterm (MLP) infants. This percentage substantiates a need for a better understanding of the neurodevelopmental outcome of this group Aim To describe neurodevelopmental outcome at 18 months in a cohort of healthy low-risk MLP infants admitted to the neonatal unit at birth and to compare the neurodevelopmental outcome to that of a healthy term-born infant group. Study design and method This single-centre observational study compared the neurodevelopmental outcome of healthy MLP infants to a group of healthy term control (TC) infants recruited during the same period using the Griffith's III assessment at 18 months. Results Seventy-five MLP infants and 92 TC infants were included. MLP infants scored significantly lower in the subscales: Eye-hand coordination (C), Personal, Social and Emotional Development (D), Gross Motor Development (E) and General Developmental (GD) (p < 0.001 for each) and Foundations of Learning (A), (p = 0.004) in comparison to the TC infant group with Cohen's d effect sizes ranging from 0.460 to 0.665. There was no statistically significant difference in mean scores achieved in subscale B: Language and Communication between groups (p = 0.107). Conclusion MLP infants are at risk of suboptimal neurodevelopmental outcomes. Greater surveillance of the neurodevelopmental trajectory of this group of at-risk preterm infants is required.
Illiteracy in the Arab Region: A Meta Study

There are many opinions as to the causes of illiteracy in the Arab region. The issue is debated and researched by both those from within and outside of the Arab region. This paper is a consideration of seventeen different studies and papers researching and expounding upon the causes of illiteracy. Four of these are distilled from the literature to provide what this author believes to be the four major reasons for illiteracy in the Arab region.
XXVIII.—On the Buried Forests and Peat Mosses of Scotland, and the Changes of Climate which they indicate

The following communication is an attempt to eliminate the geological history of our Scottish Peat Mosses. So much, however, has already been done in this matter, that the reconsideration of phenomena, for the most part well known, may appear almost a superfluous task. But, notwithstanding the essays of Walker, Rennie, Anderson, and others, in this department of geological inquiry, there is still probably much to be gathered from the same source, which shall greatly increase our knowledge of the condition of these latitudes in the ages that followed upon the close of the glacial epoch. At present, I mean to give only an outline of the subject, reserving for some future occasion a fuller statement of the facts on which the conclusions arrived at are based.
Virulence factors in carbapenem-resistant hypervirulent Klebsiella pneumoniae

Hypervirulence and carbapenem-resistant have emerged as two distinct evolutionary pathotypes of Klebsiella pneumoniae, with both reaching their epidemic success and posing a great threat to public health. However, as the boundaries separating these two pathotypes fade, we assist a worrisome convergence in certain high-risk clones, causing hospital outbreaks and challenging every therapeutic option available. To better understand the basic biology of these pathogens, this review aimed to describe the virulence factors and their distribution worldwide among carbapenem-resistant highly virulent or hypervirulent K. pneumoniae strains, as well as to understand the interplay of these virulence strains with the carbapenemase produced and the sequence type of such strains. As we witness a shift in healthcare settings where carbapenem-resistant highly virulent or hypervirulent K. pneumoniae are beginning to emerge and replace classical K. pneumoniae strains, a better understanding of these strains is urgently needed for immediate and appropriate response.
Early Reflections on a Collaborative Research Project About the Safety of Rainbow Ākonga on Te Pūkenga Campuses

This paper reports on the experiences of a research team designing and beginning to implement a research project exploring how safe and inclusive the various campuses of Te Pūkenga are for Rainbow ākonga (students). As Aotearoa New Zealand’s largest tertiary education provider, Te Pūkenga is bound and shaped by current anti-discrimination social policies. Under the 1993 Human Rights Act, discrimination based on gender was banned in Aotearoa. Same-sex marriage was legalised in 2013, and since 2021 people have been able to change their birth sex on official documents. In 2021, the Government also banned conversion therapy. However, despite these policies and as numerous national studies have documented, educational institutions remain hostile spaces for Rainbow ākonga. We aim to investigate ākonga and kaimahi (staff) experiences of inclusivity and discrimination across Te Pūkenga campuses. A research design was established, and we are in the process of collecting data. Because we have just begun the fieldwork at the time of this writing, we cannot discuss our findings to date. Instead, this article uses the feminist method of storytelling to explore the formation of a collaborative multi-site research team, the necessity of consulting with a Rainbow youth organisation when designing the survey, the research team’s duty of care to participants, the ethics process involved in conducting a multi-site organisational study and managing ‘teething problems’ when the online survey went live. This paper thus reports on our experiences of overcoming hurdles associated with a multi-site research project at a time of transition into one organisation, Te Pūkenga.
All-cause and immune checkpoint inhibitor–associated acute kidney injury in immune checkpoint inhibitor users: a meta-analysis of occurrence rate, risk factors and mortality

ABSTRACT Background Immune checkpoint inhibitors (ICIs) have been associated with acute kidney injury (AKI). However, the occurrence rate of ICI-related AKI has not been systematically examined. Additionally, exposure to proton pump inhibitors (PPIs) and non-steroidal anti-inflammatory drugs (NSAIDs) were considered as risk factors for AKI, but with inconclusive results in ICI-related AKI. Our aim was to analyse the occurrence rate of all-cause AKI and ICI-related AKI and the occurrence rates of severe AKI and dialysis-requiring AKI, and to determine whether exposure to PPIs and NSAIDs poses a risk for all-cause and ICI-related AKI. Methods This study population was adult ICI recipients. A systematic review was conducted by searching MEDLINE, Embase and PubMed through October 2023. We included prospective trials and observational studies that reported any of the following outcomes: the occurrence rate of all-cause or ICI-related AKI, the relationship between PPI or NSAID exposure and AKI development or the mortality rate in the AKI or non-AKI group. Proportional meta-analysis and pairwise meta-analysis were performed. The evidence certainty was assessed using the Grading of Recommendations Assessment, Development and Evaluation framework. Results A total of 120 studies comprising 46 417 patients were included. The occurrence rates of all-cause AKI were 7.4% (14.6% from retrospective studies and 1.2% from prospective clinical trials). The occurrence rate of ICI-related AKI was 3.2%. The use of PPIs was associated with an odds ratio (OR) of 1.77 [95% confidence interval (CI) 1.43–2.18] for all-cause AKI and an OR of 2.42 (95% CI 1.96–2.97) for ICI-related AKI. The use of NSAIDs was associated with an OR of 1.77 (95% CI 1.10–2.83) for all-cause AKI and an OR of 2.57 (95% CI 1.68–3.93) for ICI-related AKI. Conclusions Our analysis revealed that approximately 1 in 13 adult ICI recipients may experience all-cause AKI, while 1 in 33 adult ICI recipients may experience ICI-related AKI. Exposure to PPIs and NSAIDs was associated with an increased OR risk for AKI in the current meta-analysis.
Decision Making in Killer Robots Is Not Bias Free

ABSTRACT Autonomous weapons are systems that, once activated, can identify, select and engage targets by themselves. Scharre (2018. Army of None: Autonomous Weapons and the Future of War. New York: Norton) has given a definition of autonomy based on three dimensions: the automatized tasks, the relationship with the human user and the sophistication of the machine’s decision-making process. Based on this definition of autonomy, this article provides an overview of systematic biases that may occur in each of these three dimensions. Before the deployment of autonomous systems in war it is important to know how various biases can affect the functioning of the machines and how these biases can be compensated for.
Model of soybean NDVI change based on time series.

Abstract: Normalized Difference Vegetation Index (NDVI) has been found to have good correlations with many physical properties of soybean surfaces. Due to the factors of air temperature, humidity, solar radiation, soil moisture, etc., NDVI of soybean varies dynamically in a day. The establishment of the soybean NDVI prediction model at different times in a day can effectively modify this variation. The soybean NDVI values are continuously monitored in hours during soybean seeding, flowering & podding and maturating stages by way of Green Seeker. Results show that the trend of NDVI change every day in the three stages is taken on as a reverse parabola. The NDVI value reaches to the maximum at 8 am or 9 am and decreases to its minimum at 2 pm before a moderate rise. A model for intraday and long-term NDVI change for soybean is built. The test of the model with independent data indicates that the precision meets the demands, with the root mean square error (RMSE) of each day being 3.95, 5.45 and 2.86 for the seeding stage, the bean podding stage and the maturation period, respectively. The prediction RMSEs of the soybean NDVI model for soybeans of the three stages for the fifth day are 5.75, 2.65 and 5.51, respectively and the prediction RMSEs for the sixth day are 9.74, 2.82 and 14.04, respectively according to the data from the first four days. Keywords: model, NDVI, monitoring time, time series, atmospheric radiation, soybean DOI: 10.3965/j.ijabe. 20140705.007 Citation: Zhang Z T, Lan Y, Wu P T, Han W T. Model of soybean NDVI change based on time series. Int J Agric & Biol Eng, 2014; 7(5): 64－70.
Retrieving Tiger Habitats: Conserving Wildlife Geospatially

The dwindling tiger populations and their habitats globally due to natural and anthropogenic causes seems to be a strong deterent for their in situ conservation. Once inhabited by tigers, Sariska Wildlife Reserve, India was not included as one of the 42 ‘source sites’ for tigers, due to the absence of tigers during 2004-05 on the account of commercial poaching. However, Sariska has the potential for sustaining tiger population for being a suitable habitat for them. Geospatial approach for tiger habitat suitability in Sariska has been utilized integrating with Multi-criteria Decision Analysis (MCDA) and fuzzy Analytic Hiearchy Process (AHP) Narrow Trapezoidal techniques for getting better insights into conservation of tigers in spatially determining suitable sites for their habitats and conservation and enumerating the area covered. Habitat suitability index (HSI) is calculated to be 0.882 ± 0.06, based on which a habitat suitability index map for tiger is generated. Results showed an area of 616.77 km 2 accounting to 52.1% of the total area under study to be extremely suitable for tiger habitat and relocation. This can help for planning management strategies for the conservation of tigers and hence Sariska could find a respectable place among the ‘source sites’ for tigers.
Testing the Influence of Metakaolinite and Zeolite on the Adhesion of BFRP and GFRP Bars to Concrete

Today’s sustainable development policy in Europe, which is driven by concerns about the greenhouse effect and environmental protection, mandates a reduction in CO2 emissions into the atmosphere. The cement industry and steel mills that produce reinforcing bars are among the largest and most emissions-intensive sectors emitting CO2 into the atmosphere. This article analyzes the possibility of achieving significant reductions in CO2 emissions by using basalt bars (BFRP) and glass bars (GFRP) in concrete structures, and—in the case of concrete—by using cement with the addition of metakaolinite and zeolite. There is a lack of literature reports on whether modifying concrete with the additions of metakaolinite and zeolite as substitutes for part of the cement affects the adhesion of FRP bars to concrete. It can be assumed, however, that improving the microstructure of concrete also improves the contact zone between the bar and the concrete. The aim of this research is to fill the aforementioned gap in the literature data by determining how the presence of metakaolinite and zeolite affects the adhesion of reinforcing bars to concrete and testing selected properties of hardened concrete. The test samples were prepared following the appropriate beam test procedure. The obtained results made it possible to perform a comparative analysis of reference samples and those with metakaolinite and zeolite additions. The research showed that introducing active pozzolanic additives in the form of metakaolinite and zeolite into concrete improved adhesion stress values by approximately 20% for glass GFRP bars and 15% for basalt BFRP bars, especially in the destruction phase.
A New Fractional-Order Virtual Inertia Support Based on Battery Energy Storage for Enhancing Microgrid Frequency Stability

Microgrids have a low inertia constant due to the high penetration of renewable energy sources and the limited penetration of conventional generation with rotating mass. This makes microgrids more susceptible to frequency stability challenges. Virtual inertia control (VIC) is one of the most effective approaches to improving microgrid frequency stability. Therefore, this study proposes a new model to precisely mimic inertia power based on an energy storage system (ESS) that supports low-inertia power systems. The developed VIC model considers the effect of both the DC-DC converter and the DC-AC inverter on the power of the ESS used. This allows for more precise and accurate modeling of the VIC compared to conventional models. Moreover, this study proposes a fractional-order derivative control for the proposed VIC model to provide greater flexibility in dealing with different perturbations that occur in the system. Furthermore, the effectiveness of the proposed fractional-order VIC (FOVIC) is verified through an islanded microgrid that includes heterogeneous sources: a small thermal power plant, wind and solar power plants, and ESSs. The simulation results performed using MATLAB software indicate that the proposed VIC scheme provides fast stabilization times and slight deviations in system frequency compared to the conventional VIC schemes. The proposed VIC outperforms the conventional load frequency control by about 80% and the conventional VIC model by about 45% in tackling load/RESs fluctuations and system uncertainty. Additionally, the studied microgrid with the proposed FOVIC scheme is noticeably more stable and responds faster than that designed with integer-order derivative control. Thus, the proposed FOVIC scheme gives better performance for frequency stability of low-inertia power systems compared to conventional VIC schemes used in the literature.
Radiomics and Clinicopathological Characteristics for Predicting Lymph Node Metastasis in Testicular Cancer

Simple Summary Testicular germ cell tumours (TGCTs) are the most common type of solid cancer in men under the age of 40. Of metastases from TGCTs, 95% involve the ipsilateral retroperitoneal lymph nodes. For early-stage TGCTs, the optimal treatment remains controversial, with options including surveillance, chemotherapy or lymph node surgery after orchiectomy. However, the accurate prediction of retroperitoneal lymph node metastasis is crucial to avoid unnecessary treatment and health complications in this group of young patients, highlighting the importance of precise follow-up care. In this study, we developed and validated predictive machine learning models integrating radiomics and clinical features for individual preoperative prediction of lymph node metastases in early TGCTs. Abstract Accurate prediction of lymph node metastasis (LNM) in patients with testicular cancer is highly relevant for treatment decision-making and prognostic evaluation. Our study aimed to develop and validate clinical radiomics models for individual preoperative prediction of LNM in patients with testicular cancer. We enrolled 91 patients with clinicopathologically confirmed early-stage testicular cancer, with disease confined to the testes. We included five significant clinical risk factors (age, preoperative serum tumour markers AFP and B-HCG, histotype and BMI) to build the clinical model. After segmenting 273 retroperitoneal lymph nodes, we then combined the clinical risk factors and lymph node radiomics features to establish combined predictive models using Random Forest (RF), Light Gradient Boosting Machine (LGBM), Support Vector Machine Classifier (SVC), and K-Nearest Neighbours (KNN). Model performance was assessed by the area under the receiver operating characteristic (ROC) curve (AUC). Finally, the decision curve analysis (DCA) was used to evaluate the clinical usefulness. The Random Forest combined clinical lymph node radiomics model with the highest AUC of 0.95 (±0.03 SD; 95% CI) was considered the candidate model with decision curve analysis, demonstrating its usefulness for preoperative prediction in the clinical setting. Our study has identified reliable and predictive machine learning techniques for predicting lymph node metastasis in early-stage testicular cancer. Identifying the most effective machine learning approaches for predictive analysis based on radiomics integrating clinical risk factors can expand the applicability of radiomics in precision oncology and cancer treatment.
User Acceptance of Online Examination System Using the Unified Theory of Acceptance and Use of Technology (UTAUT) Model

User acceptance is one of the factors that need to be considered in order to improve the quality of the online examination system. Therefore, an evaluation model is needed to measure online examination system user acceptance. The Unified Theory of Acceptance and Use of Technology (UTAUT) is one of the evaluation models used in this study. This study aims to determine the user acceptance of the web-based online examination system at Public VHS 4 Malang using the UTAUT factors. The UTAUT factors used are performance expectancy, effort expectancy, social influence, and facilitating conditions as exogenous latent variables, and behavioral intention as an endogenous latent variable. The respondents in this study were students in the 12th grade of 2022/2023 school year. The total number of students was 274. The data obtained were analyzed using the Partial Least Square (PLS) method using SmartPLS 3 software. In this study, performance expectancy, effort expectancy, and facilitating conditions have a positive and significant effect on behavioral intention, while social influence has a positive but insignificant effect on behavioral intention.