Miracle-dz/UniFAR-FTUs huggingface dataset:
Distributed Event-Triggered Fixed-Time Leader–Follower Formation Tracking Control of Multiple Underwater Vehicles Based on an Adaptive Fixed-Time Observer

This paper focuses on the fixed-time leader–follower formation control of multiple underwater vehicles (MUVs) in the presence of external disturbances. First, an adaptive fixed-time disturbance observer (AFxDO) is developed to deal with unknown time-varying environmental disturbances. The developed AFxDO guarantees the fixed-time convergence property of the disturbance observation error and no prior information on the external disturbances or their derivatives is required. Then, with the aid of the developed AFxDO, a distributed event-triggered fixed-time backstepping controller was developed to achieve the leader–follower formation tracking control of MUVs. To solve the “explosion of complexity” problem inherent in the conventional backstepping, a nonlinear filter is introduced to obtain the derivative of the virtual control law. Furthermore, to reduce the communication burden, the event-triggered mechanism is integrated into the formation tracking controller. The stability analysis shows that the closed-loop MUV system is practical fixed-time stable. Finally, simulation results demonstrate the effectiveness of the proposed scheme.
Perceived usefulness and ease of using virtual reality during physiotherapy–A cross-sectional survey from physiotherapists perspective

Background: Virtual reality (VR) is a cutting-edge technology that consists of a sophisticated user-computer interface that allows for real-time visualization and interaction by using both visual and auditory sensorial channel. The implementation of inclusive innovation using VR in health services should be considered and hence, this study is conducted to investigate the perceived usefulness and ease of using VR during physiotherapy among Malaysian physiotherapists. Materials and methods: A cross-sectional a survey through social media, with an adapted questionnaire about the perceived usefulness and simplicity of adopting VR during physiotherapy is distributed to physiotherapists in Malaysia. In total, 102 physiotherapists participated in this study. Frequency and percentage are used to analyze the data of questionnaire items. Results: Overall 62% agree that using VR would enable to accomplish tasks more quickly, 63% finds it improve job performance, 57% believes that VR would increase my productivity. 59% enhance the effectiveness on the job. 64% easier to do my job, 61% VR useful in job. Regarding perceived ease of use 57% accepts learning to operate VR would be easy for me, 55% find it easy to get VR to do what physiotherapist want it to do, 53% agrees that interaction with VR would be clear and understandable, 54% agree that it is flexible to interact with, 54% agree to be become skillful using VR and lastly 55% agree it is easy to use. Conclusions: The majority of Malaysian physiotherapists find VR slightly useful for inclusive innovation in physiotherapy, improving work efficiency and performance. However, some remain neutral regarding its overall usefulness. They also find VR neither easy nor difficult to use in terms of inclusivity.
3D Printing of Layered Structures of Metal-Ionic Polymers: Recent Progress, Challenges and Opportunities

Layered Structures of Metal Ionic Polymers, or Ionic Polymer-Metal Composites (IPMCs) are formed by a membrane of an ionic electroactive materials flanked by two metal electrodes on both surfaces; they are devices able to change their shape upon application of an electrical external stimulus. This class of materials is used in various fields such as biomedicine, soft robotics, and sensor technology because of their favorable properties (light weight, biocompatibility, fast response to stimulus and good flexibility). With additive manufacturing, actuators can be customized and tailored to specific applications, allowing for the optimization of performance, size, and weight, thus reducing costs and time of fabrication and enhancing functionality and efficiency in various applications. In this review, we present an overview of the newest trend in using different 3D printing techniques to produce electrically responsive IPMC devices.
THE EFFECT OF PROFITABILITY, LEVERAGE AND PUBLIC SHARE OWNERSHIP ON CORPORATE SOCIAL RESPONSIBILITY DISCLOSURE WITH THE BOARD OF COMMISSIONERS AS A MODERATING VARIABLE IN MINING SECTOR COMPANIES LISTED ON THE INDONESIA STOCK EXCHANGE 2019–2021

This study aims to analyze the effect of profitability, leverage and public share ownership on corporate social responsibility disclosure with the board of commissioners as moderating variables in mining companies listed on the IDX in 2019-2021. The population in this study amounted to 31 mining companies. The sample selection method used purposive sampling technique. The type of data used is secondary data with data analysis techniques used, namely panel data regression analysis with multiple linear regression tests using Eviews software. The results show that Profitability has a positive and significant effect on Corporate Social Responsibility Disclosure, Leverage has a negative and significant effect on Corporate Social Responsibility Disclosure,
Improvement of Cognitive Function by Fermented Panax ginseng C.A. Meyer Berries Extracts in an AF64A-Induced Memory Deficit Model

This study investigated the potential therapeutic properties of fermented ginseng berry extract (GBE) for Alzheimer’s disease (AD). Fermented GBE was examined for its ginsenoside content and physiological properties, which have been suggested to have neuroprotective effects and improve cognitive function. The results showed that fermented GBE contains high levels of major active ginsenosides and exhibits antioxidant and acetylcholinesterase inhibitory activities. Post-fermented GBE demonstrated therapeutic potential in AF64A-induced damaged neural stem cells and an animal model of AD. These findings suggest that fermented GBE may hold promise as a candidate for developing new therapeutic interventions for memory deficits and cognitive disorders associated with AD and other neurodegenerative conditions. However, further studies are needed to evaluate the safety, tolerability, and efficacy of fermented GBE in human subjects and to determine its clinical applications. In conclusion, our study provides evidence that fermented GBE has potential as a natural product for the prevention and treatment of AD. The high levels of active ginsenosides and antioxidant and acetylcholinesterase inhibitory activities of fermented GBE suggest that it may be a promising therapeutic agent for improving cognitive function and reducing neurodegeneration.
Anti-HBV Efficacy of Ficus Plant's Leaf Extract against the Most Dominant HBV Genotypes in the Nile Delta Region of Egypt

H EPATITIS B virus (HBV) infects millions of people worldwide annually, causing chronic liver diseases such as cirrhosis, fibrosis, and hepatocellular carcinoma. HBV has nine known genotypes (A, B, C, D, E, F, G, H, and I) and a tentative tenth genotype (J). Identifying HBV genotyping is crucial since different genotypes and sub-genotypes can influence treatment outcomes and responses to antiviral therapy. Therefore, we employed conventional polymerase chain reaction (PCR) to determine the HBV genotypes in three Egyptian governorates: Dakahlia (DK), Gharbia (GHR), and El-Sharkia (SHR). Specific primers for various HBV genotypes (A, B, C, D, E, and F) were used for this purpose. Out of 38 samples, three samples (7.8%) were found to have the D genotype, and four samples (10.5%) were identified as genotype C. The genotypes that were discovered underwent deep sequencing, which revealed two bands in the sequence results that were 99% identical to genotype D. The remaining bands could not be sequenced or gave unclear and incorrect sequence data. We evaluated the leaf extracts of three Ficus species ( F. mysorensis, F. deltoidei, and sycomorus ) as antiviral substances against HBV infection using an MTT assay. The results showed promising antiviral effects of these extracts, which could potentially aid in stopping the progression of HBV infection. Our findings indicate that conventional PCR with deep sequencing can accurately identify HBV genotypes, and Ficus plants may serve as an excellent supplement to standard treatment for HBV infections.
Facial expression transfer based on generative adversarial networks: a review

The fields of computer vision and special effects production often require editing and synthesis of facial expressions, such as transfer one person's expression to another's face. It is crucial to synthesize realistic facial expressions to ensure accurate expression of a person's feelings, however, because expressions are very subtle and subject to individual differences, facial expressions generated using methods such as 3D facial reconstruction and face morphing are difficult to guarantee sufficient facial details and the workload is huge, requiring a lot of time and effort. Facial expression transfer techniques can synthesize a large library of face expressions while ensuring human privacy, and provide data support for related face research problems. With the development of deep learning, generative adversarial networks provide a new solution for facial expression transfer. The currently available GANs are CGAN, StarGAN, G2-GAN, GC-GAN, geometric feature and attribute tagging driven GAN, Expr-GAN, TER-GAN, and StyleGAN. This paper focuses on the above methods of facial expression transfer based on generative adversarial networks, and discusses their respective features and advantages; summarizes the available facial expression transfer; finally, based on the problems of existing methods, research directions for future work are proposed.
Analysis of flavour mixing and CP violation in the strange-beauty meson system using LHCb data

This research analysed the avour mixing and CP violation in the B s meson system using LHCb data for the B s → D− s π and B s → D∓ s K± decays. The available data was ltered using the available detector reconstruction parameters, and tted with theoretical functions to extract fundamental parameters of nature. Mass plots for the B s and D ∓ s mesons were created, together with decay-time distributions, avour mixing and CP-asymmetry plots. ∆ms was found to be (17.732±0.042) ·1012s−1 and ∆Γs = (0.00±0.35) ·1012s−1, where the natural units ~ ≡ c ≡ 1. The obtained master equation parameters do not deviate signi cantly from 0, so no CP violation was observed. Further improvements could be the use of more sophisticated tting software, for example RooFit, and a more extensive background contribution modelling.
Assessment of the Variability of Human Exposure to Radiofrequency Electromagnetic Fields Arising from 5.9 GHz Vehicular Communication in Urban Environments

This paper assessed the variability of radiofrequency exposure among road users in urban settings due to vehicle-to-vehicle (V2V) communication operating at 5.9 GHz. The study evaluated the absorbed dose of radiofrequencies using whole-body specific absorption rate (SAR) in human models spanning different age groups, from children to adults. To overcome limitations of previous studies, we developed a novel hybrid procedure that combines deterministic and stochastic approaches, enabling assessment across multiple urban layouts. Real urban conditions and varying propagation scenarios were considered in SAR calculations. By varying the road user’s position within 1.5–300 m from transmitting cars, the SAR distribution was determined. Median SAR remained consistently low, around 0.70 mW/kg, even with multiple transmitting cars and multiple emitting antennas, using maximum power allowed in US (44.8 dBm). The 99th percentile of SAR distribution varied based on body mass, decreasing for heavier models (typically adults) and increasing with the number of transmitting cars and antennas. The highest absorbed dose (73 mW/kg) occurred in a child model. The SAR consistently remained below the 80 mW/kg limit for whole-body exposure to electromagnetic fields in the 100 kHz–300 GHz range.
Linking Adjoint Sensitivity Maps with CAD Parameters

Modern CAD systems provide parametric geometric models which allow variations in shape to optimize function. However the models produced can be so complex, with tens or hundreds of parameters, that it is very difficult to choose which parameters or set of parameters should be used in design optimization. The boundary method of shape sensitivity allows a single adjoint analysis to determine a sensitivity map over the domain boundary which quantifies the performance improvement caused by inward or outward perturbation of the boundary at any point. The “design velocity” field quantifies the shape change caused by a given parametric change. Combining the sensitivity map with the design velocity fields, the performance sensitivity to any parametric change can be determined from a single analysis. This combination gives the steepest descent vector in parameter space and suggests possible methods for adding new design features in simulation-driven design.
Comparative analysis of tumor biology and prognosis in mucinous and signet-ring cell colon cancers versus classical adenocarcinoma

Background: Limited information is currently available on the natural history and prognosis of two distinct histological subtypes of adenocarcinoma (AC) in the colon: mucinous adenocarcinoma (MAC) and signet-ring cell carcinoma (SRCC). Therefore, the aim of this study is to examine the clinicopathological characteristics of colon MAC and SRCC, comparing them to classical AC, using a large cohort of cases from the United States. Methods: Patients diagnosed with colon AC, MAC, or SRCC from the SEER database between 2000 and 2018 were included in our study. Incidence trends, patient demographics, tumor characteristics, treatment, and survival were analyzed. Results: In our study, we analyzed a total of 310,813 patients with colon cancers, including 271,382 cases of classical AC, 34,750 cases of MAC, and 4,681 cases of SRCC. Over the study period, we observed a decline in the age-adjusted incidence rates of colon AC, MAC, and SRCC. Notably, the MAC and SRCC cohorts differed significantly from AC in terms of patient characteristics, tumor locations, and treatment patterns. Patients with MAC and SRCC had poorer survival outcomes compared to those with AC. Factors associated with worse survival included older age, male sex, poorly differentiated tumors, advanced stage, and the presence of MAC or SRCC histology. On the other hand, surgical intervention was associated with improved survival. Conclusion: Our study underscores the significance of recognizing the distinct features and outcomes associated with different histological subtypes of colon cancer. Further research is warranted to delve into the underlying biological traits that contribute to these differences and to develop more tailored treatment strategies.
Análisis de la educación técnica laboral en educación media, de la teoría a la práctica

El bajo porcentaje de ingreso de estudiantes a la universidad demuestra la necesidad de una educación media técnica de calidad, que ofrezca posibilidades laborales a los bachilleres. Son claras las problemáticas presentes en la educación media técnica. Baja calidad, pertinencia y cobertura son algunos de los problemas; sin contar el poco interés de los estudiantes en esta formación. Es necesario realizar estudios que permitan identificar las problemáticas presentes, analizar la realidad de la educación técnica ofrecida en las Instituciones y orientar sobre las falencias que, por el análisis de normatividad, informes y experiencias propias, se ponen en evidencia. En este estudio se presenta un análisis crítico a la pertinencia y buen funcionamiento de la especialidad técnica en cinco instituciones del occidente del departamento de Boyacá, trabajando desde una investigación analítica, con el objetivo de analizar la aplicación de educación media técnica establecida por entes estatales y su aplicación en las instituciones estudiadas, de manera que este estudio dejo en evidencia desde una visión general, la poca articulación , el abandono y la falta de política pública seria y disciplinada del estado hacia la educación media técnica en las Instituciones educativas que en Colombia se inclinan por promocionar las especialidades industriales en la nación.
An Introduction to Causal Mediation Analysis With a Comparison of 2 R Packages

Traditional mediation analysis, which relies on linear regression models, has faced criticism due to its limited suitability for cases involving different types of variables and complex covariates, such as interactions. This can result in unclear definitions of direct and indirect effects. As an alternative, causal mediation analysis using the counterfactual framework has been introduced to provide clearer definitions of direct and indirect effects while allowing for more flexible modeling methods. However, the conceptual understanding of this approach based on the counterfactual framework remains challenging for applied researchers. To address this issue, the present article was written to highlight and illustrate the definitions of causal estimands, including controlled direct effect, natural direct effect, and natural indirect effect, based on the key concept of nested counterfactuals. Furthermore, we recommend using 2 R packages, ‘medflex’ and ‘mediation’, to perform causal mediation analysis and provide public health examples. The article also offers caveats and guidelines for accurate interpretation of the results.
Talent Management in Five-Star Hotels in Egypt: An Exploratory Study

Talent management is considered one of the main obstacles facing hospitality industry on a global scale. It is especially challenging in the current volatile and dynamic business environment. The aim of this paper is to identify awareness of concept and importance of talent management in five-star hotels in Greater Cairo and to identify the impact of applying of talent management on improving performance in five-star hotels. This research used the quantitative approach to achieve its objectives. Data collection based on the online questionnaire. The study sample consists general managers, human resources managers, and human resources supervisors in five-star hotels in Greater Cairo. The total number of questionnaires distributed was 168 copies out of which only 129 have been returned with a response rate 76%. SPSS (Version, 26) software was used for analysis data. The results showed there is a positive significant statistical relationship between hotel talent recruitment and performance. It also reported that there is a positive significant statistical relationship between the motivation and performance, and talent retention in the hotel performance, it also showed that there is a positive relationship between hotel talent assessments and performance.
Knowledge and practices of maternity nurses related to the potential impacts of climate change on women's health.

Background : Climate change represents a significant global health issue that has rapidly ascended to the forefront of the global health agenda. Its impact can be profound, affecting individuals not only on a physical level but also psychologically and socially. Specifically, women are a population that may be particularly susceptible to the ramifications of climate change, and their quality of life may be threatened. It is worth noting that nurses are the frontline of any health system; therefore, it is essential to have a knowledgeable and skilled workforce to ensure the health of the community, particularly during crises such as climate change. Aim of the study: to assess knowledge and practices of maternity nurses related to the potential impacts of climate change on women's health. Design : A cross-sectional descriptive research design was implemented. Subjects : A convenient sample of 255 maternity nurses were enrolled from four maternity hospitals at Alexandria Governorate, Egypt. Tools : Data was collected using three tools namely, maternity nurses' basic data structured questionnaire, maternity nurses' knowledge related to the potential impacts of climate change on women's health structured questionnaire, and maternity nurses' practices related to the potential impacts of climate change on women's health structured questionnaire. Results : the mean score of the overall knowledge is 36.40±7.84 with a total percent score of 62.77% indicating fair knowledge, while the overall practices were unsatisfactory in the majority (93.3%) of nurses with a mean score of 8.76±2.65. Conclusion: The current study concluded that the overall score of maternity nurses' knowledge was fair while the overall mean score of their practices was unsatisfactory. Therefore, there is a gap between knowledge and practice. Recommendations: It is suggested that the responsible authorities should conduct educational programs and training workshops to raise maternity nurses' awareness of climate change and its impacts on women's health as well as incorporating climate change in nursing curricula in all levels of study.
|Vtd/Vts| from B→Vγ

The dominant theoretical uncertainty in extracting |Vtd/Vts| from the ratio of branching ratios R≡(B→(ρ,ω)γ)/(B→K*γ) is given by the ratio of form factors ξ≡T1B→K*(0)/T1B→ρ(0). We re-examine ξ in the framework of QCD sum rules on the light-cone, taking into account hitherto neglected SU(3)-breaking effects. We find ξ = 1.17±0.09. Using QCD factorisation for the branching ratios, and the current experimental average for R quoted by HFAG, this translates into |Vtd/Vts|HFAG = 0.179±0.022(exp)±0.014(th). This result agrees, within errors, with that obtained from the Standard Model unitarity triangle based on tree-level-only processes and with |Vtd/Vts| inferred from the two-sided bound on Δms reported recently by the D0 collaboration.
Hardware Implementation for Convolutional Neural Networks in Artificial Intelligence

Artificial Intelligence (AI) has brought great convenience and help to human society by improving efficiency, increasing productivity and reducing cost. As a part of deep learning, convolutional neural networks (CNNs) have been widely concerned by researchers in recent years. In this paper, five parts of the CNN structure, including input layer, convolutional layer, pooling layer, fully connected layer, activation function and output layer are going to be elaborated. Besides, four different kinds of hardware, which can be used in AI implementation, including graphics processing unit (GPU), field programmable gate array (FPGA), application-specific integrated circuit (ASIC) and brain-like chips will be discussed in this paper. Based on the different characteristics of these four groups of hardware, this paper will analyze their feasibility to implement artificial intelligence algorithm. After contrasting their cost, flexibility and power consumption, it is concluded that different hardware has different advantages to implement AI under different circumstances. GPU performs better to handle with parallel operations or construct complex network models of AI. FPGA is able to achieve flexible AI model programming. On the other hand, ASIC is preferred considering its low power consumption and cost to implement AI. Although brain-like chip is not as well developed as the other three chips, it is promising to implement AI in the future.