Miracle-dz/UniFAR-FTUs huggingface dataset:
How personal beliefs determine adherence to standards of research ethics: an EFA and path analysis study

Purpose This study aims to identify causes of (un)ethical behaviour in research and how they influence adherence to research ethics. Design/methodology/approach The authors developed and tested a conceptual model that includes mediation and helps to understand the mechanism of adherence to ethical standards of research based on the “social judgment theory” (SJT). In Study 1, the authors conducted an exploratory study using the exploratory factor analysis technique to identify factors responsible for adherence to research ethics. In Study 2, the authors used SJT to provide support for establishing a relationship between key variables. Findings Two factors, “Proclivity to Egoism” and “Proclivity to Emotivism”, were identified based on the personal beliefs of researchers. These factors were found to play an important role in determining the tendency towards adherence to standards of research ethics (Belmont Report and COPE). SJT successfully explains the mechanism of adoption of ethical standards. Adherence to Belmont principles was seen to mediate relationship between factors identified and tendency to adhere to COPE. Originality/value Majorly, this study is unique as it establishes and guides to incorporate researchers’ point of view in formulating ethical standards and guidelines, apart, from various other important theoretical and societal implications.
Improving Pipeline Magnetic Flux Leakage (MFL) Detection Performance With Mixed Attention Mechanisms (AMs) and Deep Residual Shrinkage Networks (DRSNs)

Magnetic flux leakage (MFL) detection is one of the most commonly used nondestructive testing methods and plays a crucial role in ensuring pipeline safety during transportation. However, the identification of abnormal MFL signals still relies on manual interpretation, leading to issues such as missed detection and false alarms. In addition, MFL data acquisition is prone to noise interference. To address these challenges, this article proposes a method that integrates comprehensive transfer learning (TL), attention mechanisms [including self-attention encoder (SE), contextualized attention (CA), convolutional block attention module (CBAM), and efficient channel attention (ECA)], and deep residual shrinkage networks (DRSNs). This approach effectively improves the training efficiency and recognition accuracy of the model while successfully suppressing the high-noise interference in MFL images during data acquisition. Furthermore, this article combines the Grad-CAM++ algorithm to visualize the recognition logic within the model and achieve preliminary localization of MFL abnormal features. Experimental results demonstrate that attention mechanisms significantly enhance the model’s recognition performance, achieving a best accuracy of 99.7%. Moreover, under high-noise interference, DRSNs effectively enhance the model’s anti-interference capability, with the highest improvement reaching 11.4%.
Seasonal and long‐term changes in elemental concentrations and ratios of marine particulate organic matter

What is the temporal variability of the elemental stoichiometry of marine microbial communities across ocean regions? To answer this question, we present an analysis of environmental conditions, particulate organic carbon, nitrogen, and phosphorus concentrations and their ratios across 20 time series (3–25 years duration) representing estuarine, coastal, and open ocean environments. The majority of stations showed significant seasonal oscillations in particulate organic elemental concentrations and ratios. However, shorter‐term changes contributed most to overall variance in particulate organic matter concentrations and ratios. We found a correlation between the seasonal oscillations of environmental conditions and elemental ratios at many coastal but not open ocean and estuarine stations. C:N peaked near the seasonal temperature minimum and nutrient maximum, but some stations showed other seasonal links. C:N ratios declined with time over the respective observation periods at all open ocean and estuarine stations as well as at five coastal station but increased at the nine other coastal stations. C:P (but not N:P) declined slightly at Bermuda Atlantic Time‐series Study but showed large significant increases at Hawaii Ocean Time‐series and Arendal stations. The relationships between long‐term changes in environmental conditions and particulate organic matter concentrations or ratios were ambiguous, but interactions between changes in temperature and nutrient availability were important. Overall, our analysis demonstrates significant changes in elemental ratios at long‐term and seasonal time scales across regions, but the underlying mechanisms are currently unclear. Thus, we need to better understand the detailed mechanisms driving the elemental composition of marine microbial ecosystems in order to predict how oceans will respond to environmental changes.
Population Changes in Gharials ( Gavialis gangeticus ) Vary Spatially in Chitwan National Park, Nepal

— Gharials, large crocodilians found only in South Asia, are widely seen as a flagship species for river conservation in Nepal, especially in Chitwan National Park, where a headstart program has supplemented the population since 1981. The population has shown signs of recovery only in the last decade, so continued monitoring of population trends is vital for conservation. We conducted annual winter population surveys for gharial in Chitwan between 2017 and 2022, during which we also characterized riverbank substrate availability and basking preferences. We documented potential threats to the species in Chitwan throughout the year. Overall, we counted an increasing number of Gharials in Chitwan; however mixed-effects modelling of Gharial encounter rate showed that increasing encounters rates are not evenly distributed throughout available habitat, with some river stretches having stable or decreasing trends. Encounter rates on the Rapti River increased in all transects, compared to more variable results on the Narayani River, likely attributable to higher levels of human disturbance and the impact of captivity on habitat selection. Fewer Gharials were seen in transects with high levels of disturbance due to sand mining and
Crystal Structure Control of the Energetics of Chemical Doping in Rub-Aligned P3HT Films

: Semiconducting polymers have received increased attention in recent years as low-cost, electrically conductive layers. To show reasonable electrical conductivity, however, semiconducting polymers must be doped, a process that requires oxidation or reduction of the conjugated backbone and structural rearrangement to accommodate a charge-balancing counterion into the polymer network. Here, we aim to understand how this structural rearrangement contributes to the energetics of doping. We utilize the fact that rub-aligned poly(3-hexylthiophene-2,5-diyl) (P3HT) films contain two polymorphs, one with a crystal structure that is less dense than the structure observed in unaligned films and the other with a more compact, denser structure. The two structures are dominantly face-on and edge-on with respect to the substrate, respectively, so their diffraction is well separated in q -space and thus doping induced structural changes can be monitored separately for each population. When films are doped with 2,3,5,6-tetrafluoro-7,7,8,8-tetracyanoquinodimethane (F 4 TCNQ), the less-dense face-on oriented P3HT polymorph undergoes doping induced structural change more easily than the denser edge-on oriented polymorph. This finding suggests that rearrangement of the polymer crystal structure to accommodate the dopant counterion is a significant energetic term in the doping process and that doping of semiconducting polymers can be facilitated by designing new polymers where dopant counterions can be accommodated in the polymer lattice with reduced structural change.
Surface damage detection for concrete bridges using single-stage convolutional neural networks

Detecting surface damages is vital for keeping concrete bridges structurally healthy and reliable. Currently, most of imagebased detection techniques are based on handcrafted low-level features which make them less applicable to actual images taken under varying environmental conditions. Recent rapid advancement in convolution neural network has enabled the development of deep learning-based visual inspection techniques for detecting multiple structural damages without needing manually-crafted features. However, most deep learning-based techniques are built on two-stage, proposal-driven detectors using less complex image data, which is not promising for practical applications and integration within intelligent autonomous inspection systems. In this study, a faster, simpler single-stage detector is proposed based on the real time object detection technique, You Only Look Once (YOLOv3) for detecting multiple surface damages of concrete bridges. A large field inspection images dataset of bridge damage is used for training and testing of YOLOv3. The original YOLOv3 is further improved by introducing a novel transfer learning method, batch renormalization and focal loss. The results show that the improved YOLOv3 has a detection accuracy of up to 80% and its performance is about 13% better than the original YOLOv3.
Decoupled Model Predictive Control for Path Following on Complex Surfaces

—The present letter proposes a predictive path following control (PPFC) that controls 5 degrees of freedom (DoFs) of the end-effector while the remaining (decoupled) translational DoF should be controlled by an external controller. This PPFC is particularly useful for the path following on surfaces with geometric uncertainties such that the external controller can be independently designed to manage the interaction between the tool and the surface. Therefore, the proposed strategy turns out to be a versatile control scheme that can be integrated with external controllers designed for applications such as robotic surface finishing, welding and 3D printing on complex surfaces. The corresponding optimal control problem (OCP) considers mainly the positioning and orientation errors, tangential velocity and control input amplitudes. The proposed PPFC is validated experimentally in the context of robotic 3D bio-printing. A 7-DoF redundant manipulator equipped with a distance sensor is used to handle a print head through the desired print path. The distance measurements are used by an external controller to correct the printed layer height. The obtained accuracy is consistent with the repeatability of the used manipulator and computation time is compatible with high frequency controllers.
A Flexible and Stretchable MXene/Waterborne Polyurethane Composite-Coated Fiber Strain Sensor for Wearable Motion and Healthcare Monitoring

Fiber-based flexible sensors have promising application potential in human motion and healthcare monitoring, owing to their merits of being lightweight, flexible, and easy to process. Now, high-performance elastic fiber-based strain sensors with high sensitivity, a large working range, and excellent durability are in great demand. Herein, we have easily and quickly prepared a highly sensitive and durable fiber-based strain sensor by dip coating a highly stretchable polyurethane (PU) elastic fiber in an MXene/waterborne polyurethane (WPU) dispersion solution. Benefiting from the electrostatic repulsion force between the negatively charged WPU and MXene sheets in the mixed solution, very homogeneous and stable MXene/WPU dispersion was successfully obtained, and the interconnected conducting networks were correspondingly formed in a coated MXene/WPU shell layer, which makes the as-prepared strain sensor exhibit a gauge factor of over 960, a large sensing range of over 90%, and a detection limit as low as 0.5% strain. As elastic fiber and mixed solution have the same polymer constitute, and tight bonding of the MXene/WPU conductive composite on PU fibers was achieved, enabling the as-prepared strain sensor to endure over 2500 stretching–releasing cycles and thus show good durability. Full-scale human motion detection was also performed by the strain sensor, and a body posture monitoring, analysis, and correction prototype system were developed via embedding the fiber-based strain sensors into sweaters, strongly indicating great application prospects in exercise, sports, and healthcare.
20 Years of MIMO Radar

The 20th anniversary of multiple-input–multiple-output (MIMO) radar was commemorated in 2023. Introduced to the radar community 21 years prior, MIMO radar was not an entirely novel concept for researchers, particularly in the realm of MIMO communication during the late 1990s. Originating from communication theories, MIMO concepts were later applied to radar, gaining significant attraction after the publication of influential articles in 2007 and 2008. Presently, MIMO radar remains a prominent research area, evidenced by numerous conference papers, journal publications, and patent acquisitions each year. Anticipated is the sustained growth of interest in MIMO radar, extending into new domains. This study utilizes data from IEEE Xplore and Scopus databases to analyze the history, present state, and future trajectory of MIMO radar.
Channel competition in tidal flats

The aim of the paper is to investigate the stability of a series of channels draining a tidal flat with respect to a perturbation of their depths. The conceptual model is relatively simple and consists of two elements: the channels, schematized as one-dimensional elements connected to an external basin whose level oscillates in time, and the tidal flat delimited by them, which exchanges and temporarily stores the discharge entering and leaving the tidal system through the mouths of the channels. We use the tidal average of the absolute value of the discharge as the relevant agent for the erosion process. Since any variation in the depth of a channel reflects in a local perturbation of discharge and energy slope, maintaining the total discharge, the bottom shear stress in the other channels varies accordingly and hence determines erosion or deposition. If we assume that all the channels have the same energy slope, the system turns out to be always unstable, namely deepening of one channel invariably induces deposition in the other channels. Thus, in order to reproduce a more realistic behavior, we consider the simple system consisting of two channels with the same initial geometrical characteristics and we try to establish a relationship between the variation of their depths and that of the area drained by each channel: the above relationship crucially depends on the asymmetric propagation of the tidal wave within the channels. According to the above watershed delimitation in the flat we then compute the partition of flow discharge within the channels and hence the bottom stresses. Model results suggest that stability is mainly controlled by the lateral distance between the channels, such that the system keeps stable provided this distance falls above a threshold value.
Modelling the Spatial and Temporal Resolution of a Sensor Observation

This paper looks at possible ways of modelling the spatial and temporal resolution of a sensor observation. A receptor-centric definition of spatial and temporal support is proposed, and it is suggested that spatial resolution can be equated with the spatial support of the observer, while temporal resolution can be estimated using the temporal support of the observer. A formal specification in the functional language Haskell helps to test the consistency of the ideas proposed.
Motivational and personality factors in sports coaches' non-formal education

This review summarizes the available literature on the non-formal education of sports coaches. Considering the complexity of the sports coaches' job, it is recognized that formal education alone is not sufficient, and non-formal education within this field may need to be mandatory. Earlier studies suggested that motivation and personality could be crucial predictors of the willingness to continuously learn. The most promising motivational theory in the context of education is the self-determination theory, which emphasizes that even controlled, external motivation could be internalized. Furthermore, some personality traits (e.g., curiosity, conscientiousness) are associated with non-formal education and should, therefore, be fostered even in those individuals who did not autonomously decide to enroll in a program. This review also identified a clear lack of studies investigating the motivational and personality determinants of non-formal education in sports coaches, and future studies should aim to fill this gap.
Patient Experiences When Preparing for Discharge Home after Patient Experiences When Preparing for Discharge Home after Total Knee Replacement Total Knee Replacement

Abstract Purpose:Purpose: Following total knee replacement (TKR), patients must prepare quickly for discharge to home via education and rehabilitation. Patient needs may not fully be met prior to discharge after TKR surgery. The purpose of this descriptive study using transcendental phenomenology methods was to understand patients’ experiences when preparing to return home after TKR surgery. Method:Method: Data was collected using semi-structured interviews that occurred 1 to 2 days prior to discharge in patients’ hospital rooms. Four participants were interviewed prior to discharge and interviews were transcribed verbatim for data analysis. Data analysis and data collection were concurrent, permitting subsequent interviews to be altered as needed based on results from previous participants. Thematic analysis of the interview transcriptions was conducted to identify significant meaning statements through a process of horizonalization. Significant statements were organized into shared themes among participants. Results:Results: Three themes emerged: being supported for discharge home; having confidence in self, family and health care staff; and persevering: overcoming obstacles. Participants overall felt prepared for their surgery and the post-operative phase. The following factors increased readiness for discharge: having prior positive experience with TKR through the experiences of others, attending pre-operative education, interacting with knowledgeable staff, and having the appropriate support at home. Some patients were unprepared for the amount of pain they experienced after surgery. Conclusions/Recommendations:Conclusions/Recommendations: Health care providers should educate patients about safety for the home environment, adaptive techniques for functional tasks, and when to resume normal activities at home. Other implications include encouraging patients to attend pre-operative education, addressing patients’ previous experiences with TKR, both positive and negative, as well as providing realistic information regarding pain after surgery.
Recombinant horse interleukin-4 and interleukin-10 induced a mixed inflammatory cytokine response in horse peripheral blood mononuclear cells

Background and Aim: Interleukin (IL)-4 and IL-10 activate plethora of immune cells and induce the humoral immune response. However, recombinant version of horse IL-4 and IL-10 has not been investigated to understand their immunomodulating activities. This study aimed to produce recombinant horse mature IL-4 and IL-10 in Escherichia coli. Immune-modulating activities of recombinant horse IL-4 and IL-10 were investigated in peripheral blood mononuclear cells (PBMCs). Materials and Methods: Equine PBMCs were stimulated with recombinant IL-4 and IL-10. A proliferation of PBMCs was measured by XTT assay and cytokines induction was measured by enzyme-linked immunosorbent assay and real-time polymerase chain reaction. Results: Sodium dodecyl sulfate-polyacrylamide gel electrophoresis analysis displayed a molecular weight of 15 kDa for IL-4 and 19 kDa for IL-10. Recombinant IL-4 and IL-10 significantly induced cell proliferation at 250 ng/ml. The results demonstrated that IL-4 enhanced expression of interferon-gamma (IFN-γ), IL-6, tumor necrosis factor-alpha (TNF-α), and IL-10, while recombinant horse IL-10 induced expression of IL-6, IFN-γ, and TNF-α. Conclusion: The present study demonstrated that biologically active horse IL-4 and IL-10 could be produced in E. coli.
Exploring Entrepreneurship Education in the Performing Arts: Perceptions of Nigerian Theatrepreneurs

Abstract: This study delves into the emerging field of entrepreneurship education in the performing arts, aiming to investigate current practices and evaluate the effectiveness of entrepreneurial endeavors within this domain. Focusing on Nigerian graduate and undergraduate prospective entrepreneurs, commonly referred to as theatrepreneurs, who pursue careers in drama, dancing, script writing, and other performing arts disciplines, the research utilizes qualitative methods. Forty purposefully selected respondents were interviewed, employing a mediated interview approach to identify theatrepreneurs' characteristics, motivations, and the significant challenges they encounter in their professional and entrepreneurial journeys. The findings demonstrate that participants opt for the performing arts primarily for personal career development rather than financial incentives. They highlight the benefits of talent development, confidence building, and professional growth. Nevertheless, the study identifies major obstacles such as time management, financial constraints, adaptation to the performing arts environment, unethical practices, and personal style, which significantly affect career development. Despite these challenges, respondents express optimism about the future of the profession. Based on the study's outcomes, it is recommended to introduce entrepreneurship education programs that nurture students' abilities to think creatively, reflectively, strategically, and analytically about their artistic practices. Such initiatives would further enhance professional career development within the performing arts industry.
Heart Disease Prediction Using Outlier Removal based Max Voting Ensemble Method

Heart disease has emerged as a serious health concern for many individuals due to its high death rate around the world. The routine clinical data analysis has a significant difficulty in the early diagnosis of cardiac disease. The identification of cardiac disease may benefit from the use of machine learning. To improve machine learning models, several studies have previously been conducted. The suggested study uses the maximum voting ensemble technique of classification to effectively identify heart disease. The suggested classifier is a more reliable and accurate approach. To identify and eliminate outliers, conduct Inter quartile range outlier removal and min-max normalization during preprocessing. Accuracy, Precision, Recall, and F1 Score are calculated and evaluated against various models. For the heart disease dataset collected from the Kaggle, the suggested max voting ensemble classifier has an accuracy of 99.22%.