Abstract In This research we will describe how to deal the system with users to make the work in the company or in any work space . in application forms interact with users inside the system . application form of any system must creates a many graphical interface for user ant we should take care about who is dealing with the system , Additionally, application forms used from different type of user so that we must take care about this points during designing the system for different users . Application Forms in the system consists of many programs, or components and function we are designing it. the instructions inside program can be execute by clicking on the command button and we can create specific process in the system.

In recent years, with the rapid development of computer vision technology and the popularization of intelligent hardware, as well as people’s increasing demand for intelligent products for human-computer interaction, visual grounding technology can help machines and humans identify and locate objects, thereby promoting human-computer interaction and intelligent manufacturing. At the same time, human-computer interaction is constantly evolving and improving, becoming increasingly intelligent, humane, and efficient. This paper proposes a new VG model and designs a language verification module that uses language information as the main information to increase the model’s interactivity. Additionally, we propose the combination of visual grounding and human-computer interaction, aiming to explore the research status and development trends of visual grounding and human-computer interaction technology, as well as their application in practical scenarios and optimization directions, to provide references and guidance for relevant researchers and promote the development and application of visual grounding and human-computer interaction technology.

Experiential learning, defined as the result, source, or context of knowledge obtained from direct experience, is increasingly bolstered by technology and human-computer interaction (HCI) principles and protocols. This article will describe how technology-based human-computer interaction (HCI) has been used in experiments to enhance direct knowledge experience. In this paper, immersive technologies (such as Virtual Reality, Augmented Reality, and haptics) will be described based on cognitive learning theory, empirical research and practical experience gained from implementing cutting-edge technology and maximizing HCI principles in constructive learning. Additionally, this article will describe how AI can be used to create individualized learning environments according to a student's needs in the future. While cost, technical issues and specialised trainings are the obstacle to deliver personalized learning experiences especially to economically disadvantaged students, technological change opportunities are projected, and these technologies will take educational outcomes to the next level.

The task of human action recognition (HAR) based on skeleton data is a challenging yet crucial technique owing to its wide-ranging applications in numerous domains, including patient monitoring, security surveillance, and observation of human-machine interactions. While numerous algorithms have been proposed in an attempt to distinguish between a myriad of activities, most practical applications necessitate highly accurate detection of specific activity types. This study proposes a novel and highly accurate spatiotemporal graph autoencoder network for HAR based on skeleton data. Furthermore, an extensive investigation was conducted employing diverse modalities. To this end, a spatiotemporal graph autoencoder was constructed to automatically learn both spatial and temporal patterns from human skeleton datasets. The powerful graph convolutional network, designated as GA-GCN, developed in this study, notably outperforms the majority of existing state-of-the-art methods when evaluated on two common datasets, namely NTU RGB+D and NTU RGB+D 120. On the first dataset, the proposed approach achieved accuracies of 92.3\% and 96.8\% for the cross-subject and cross-view evaluations, respectively. On the more challenging NTU RGB+D 120 dataset, GA-GCN attained accuracies of 88.8\% and 90.4\% for the cross-subject and cross-set evaluations, respectively.

The integration of Augmented Reality (AR) into Human-Robot Interaction (HRI) represents a significant advancement in collaborative technologies. This paper provides a comprehensive review of AR applications within HRI, emphasizing their role in enhancing collaboration, trust, and safety. By aggregating findings from numerous studies, this research highlights key challenges, including the need for improved situational awareness, enhanced safety, and more effective communication between humans and robots. A framework developed from the literature is presented, detailing the critical elements of AR necessary for advancing HRI. The framework outlines effective methods for continuously evaluating AR systems for HRI. This structured approach focuses on enhancing collaboration and safety, with a strong emphasis on integrating best practices from Human-Computer Interaction (HCI) centered around user experience and design.

With the emergence of new VR/AR technologies, the question arises of how they can be used in human-swarm interaction. Where are the limitations and boundaries of conventional interfaces, and how can VR/AR overcome them? To find out, a user study was conducted. The subjects were able to interact with an autonomously acting swarm of drones using both a conventional desktop interface (Desktop-HSI) and a newly developed VR interface (VR-HSI).The resulting assessments are used as a basis for determining the extent to which this new technology can be applied in human-swarm interaction. The technical basis was an already tested simulation software that was expanded with a network interface to allow interacting with a drone swarm using connected HSIs (Human-Swarm Interfaces). Standardized communication was emphasized to enable the development of HSIs with different requirements. Specifically for this work, a VR-HSI was developed with Unity and a desktop-HSI with Java and their performance regarding human-swarm interaction was evaluated.

Multimodal user interfaces promise a natural and intuitive human machine interactions. But is the extra effort for the development of a complex multi-sensor system justified, or can users also be satisfied with one input modality already? This study investigates interactions in an industrial weld inspection workstation. Three unimodal interfaces, including spatial interaction with buttons augmented on a workpiece or a worktable, and speech commands, were tested individually and in a multimodal combination. Within the unimodal conditions, users preferred the augmented worktable, but overall, the interindividual usage of all input technologies in the multimodal condition was ranked best. Our findings indicate that the implementation and use of multiple input modalities is valuable, and that it is difficult to predict the usability of individual input modalities for complex systems.

In the fast-changing world of software development, the protection of software products has emerged as an imperative requirement. This paper presents a new way to increase the maturity of development teams to reach the highest level of software security. Based on these, the framework uses the Fuzzy Analytic Hierarchy Process (Fuzzy-AHP) to systematically evaluate and enhance the people maturity of software development projects. The essence of the fuzzy logic and AHP technique interaction is to handle the uncertainty and complexity of human factors and team dynamics in the evaluation framework. Using the decision-making model allows the project managers and stakeholders to determine the appropriate areas for improvement and develop the right strategies and actions to nurture a secure and mature development culture. The paper identifies 24 human success factors (HSFs) and human security vulnerabilities (HSVs) and 38 practices for addressing these HSFs and HSVs. Furthermore, we discuss the local and global ranks of each HSF and HSV practice and categorize the identified practices into 9 categories to determine the ranks and weight of each category. Based on collected data, FAHP prioritized these practices; the category “C4: Skill Development and Stakeholder Engagement” is ranked highest at rank-1 and possesses the most significant weight of 0.12435. Similarly, the highest global weight is 0.051506, and the global ranked (rank-1) HSF and HSV practice is “P15: Hands-On Practice and Stakeholder Communication”. Research evidence and case discussions show how the described framework assists in building secure software development (SSD) practices, which can be considered evidence of the application of team maturity to improve cybersecurity in organizations. Additional research directions include improving the framework, especially using highly developed learning techniques and applying the framework to other forms of development.

As the global population rapidly ages with longer life expectancy and declining birth rates, the need for healthcare services and caregivers for older adults is increasing. Current research envisions addressing this shortage by introducing domestic service robots to assist with daily activities. The successful integration of robots as domestic service providers in our lives requires them to possess efficient manipulation capabilities, provide effective physical assistance, and have adaptive control frameworks that enable them to develop social understanding during human-robot interaction. In this context, human factors, especially quantifiable ones, represent a necessary component. The objective of this paper is to conduct an unbiased review encompassing studies on human factors studied in research involving physical interactions and strong manipulation capabilities. We identified the prevalent human factors in physical human-robot interaction (pHRI), noted the factors typically addressed together and determined the frequently utilized assessment approaches. Additionally, we gathered and categorized proposed quantification approaches based on measurable data for each human factor. We also formed a map of common contexts and applications addressed in pHRI for a comprehensive understanding and easier navigation of the field. We found out that most of the studies in direct pHRI (when there is direct physical contact) focus on social behaviors with belief being the most commonly addressed human factor type. Task collaboration is moderately investigated, while physical assistance is rarely studied. In contrast, indirect pHRI (when the physical contact is mediated via a third item) studies often involve industrial settings, with physical ergonomics being the most frequently investigated human factor. More research is needed on human factors in direct and indirect physical assistance applications, including studies that combine physical social behaviors with physical assistance tasks. We also found that while the predominant approach in most studies involves the use of questionnaires as the main method of quantification, there is a recent trend that seeks to address quantification approaches based on measurable data.

The proliferation of wearable technology enables the generation of vast amounts of sensor data, offering significant opportunities for advancements in health monitoring, activity recognition, and personalized medicine. However, the complexity and volume of this data present substantial challenges in data modeling and analysis, which have been tamed with approaches spanning time series modeling to deep learning techniques. The latest frontier in this domain is the adoption of Large Language Models (LLMs), such as GPT-4 and Llama, for data analysis, modeling, understanding, and generation of human behavior through the lens of wearable sensor data. This survey explores current trends and challenges in applying LLMs for sensor-based human activity recognition and behavior modeling. We discuss the nature of wearable sensors data, the capabilities and limitations of LLMs to model them and their integration with traditional machine learning techniques. We also identify key challenges, including data quality, computational requirements, interpretability, and privacy concerns. By examining case studies and successful applications, we highlight the potential of LLMs in enhancing the analysis and interpretation of wearable sensors data. Finally, we propose future directions for research, emphasizing the need for improved preprocessing techniques, more efficient and scalable models, and interdisciplinary collaboration. This survey aims to provide a comprehensive overview of the intersection between wearable sensors data and LLMs, offering insights into the current state and future prospects of this emerging field.

Depictions of robots as romantic partners for humans are frequent in popular culture. As robots are becoming part of human society, they gradually assume the role of partners for humans wherever necessary: as assistants, collaborators, or companions. Companion robots are sup-posed to provide social contact to those humans who could not have it otherwise. These com-panion robots are usually not designed to fulfill one of the most important human needs: the one for romantic and intimate contact. Human-robot intimacy remains a vastly unexplored ter-ritory. In this article, we review the state-of-the-art research in intimate robotics. We discuss major issues limiting acceptance of robots as intimate partners, public perception of robots in in-timate roles, and the possible influence of cross-cultural differences in these domains. We also discuss possible negative effects human-robot intimacy may have on human-human contact. Most importantly, we propose a new term “Intimate companion robots” to reduce the negative connotations of other terms used so far and improve the social perception of research in the domain. With this article, we provide an outlook on prospects for the development of intimate companion robots, considering the specific context of their use.

Pedestrian trajectories are crucial for self-driving cars to plan their paths effectively. The sensors implanted in these self-driving vehicles, despite being state-of-the-art ones, often face inaccuracies in the perception of surrounding environments due to technical challenges for adverse weather conditions, interference from other vehicles sensors and electronic devices, and signal reception failure, leading to incompleteness in trajectory data. But for real-time decision making for autonomous driving, the trajectory imputation is no less crucial. Previous attempts to address this issue such as statistical inference and machine learning approaches have shown promise. Yet, the landscape of deep learning is rapidly evolving with new and more robust models emerging. In this research, we have proposed an encoder-decoder architecture, Human Trajectory Imputation Model, coined as HTIM, to tackle these challenges. This architecture aims to fill in the missing parts of pedestrian trajectories. The model has been evaluated using the Intersection drone inD dataset, containing trajectory data at suitable altitudes preserving naturalistic pedestrian behavior with varied dataset sizes. To assess the effectiveness of our model, we have utilized L1, MSE, Quantile and ADE loss. Our experiments have demonstrated that HTIM outperforms the majority of the state-of-the-art methods in this field, thus indicating its superior performance in imputing pedestrian trajectories.

This paper presents an on-device semi-supervised human activity detection system that can learn and predict human activity patterns in real time. The proposed semi-supervised learning (SSL) framework uses sparsely labelled user activity events acquired from Inertial Measurement Unit (IMU) sensors installed as wearable device. The objective is to learn classification of multiple classes of human activities in real-time. The proposed cluster-based learning model in this approach is trained with data from the same target user, thus preserving data privacy while providing personalized activity detection services. Two different cluster labelling strategies, namely, population-based, and distance-based, are employed to achieve the desired classification performance. A comparative study of these strategies has been presented in terms of classifiability and classification accuracies. The proposed system is shown to be computationally efficient, which is relevant in the context of limited computing resources on typical wearable devices. The trade-off between classification accuracy and computation complexity is analyzed for different algorithmic hyper-parameters and other system parameters. Extensive experimentation and simulation study have been conducted on a multi-user human activity data from the public do-main in order to validate the proposed learning paradigm.

The Brain-Computer Interface (BCI) technology has emerged as a groundbreaking innovation with profound implications across diverse domains, particularly in healthcare. By establishing a direct communication pathway between the human brain and external devices, BCI systems offer unprecedented opportunities for diagnosis, treatment, and rehabilitation, thereby reshaping the landscape of medical practice. However, despite its immense potential, the widespread adoption of BCI technology in clinical settings faces several challenges. These include the need for robust signal acquisition and processing techniques, ensuring user safety and privacy, addressing ethical considerations, and optimizing user training and adaptation. Overcoming these challenges is crucial to unleashing the complete potential of BCI technology in healthcare and realizing its promise of personalized, patient-centric care. This review work underscores the transformative potential of BCI technology in revolutionizing medical practice. This paper offers a comprehensive analysis of medical-oriented BCI applications by exploring the various uses of BCI technology and its potential to transform patient care.

The use of new assistive technologies in general, and Socially Assistive Robots (SAR) in particular is becoming increasingly common for supporting people’s health and well-being. However, it still faces many issues regarding long-term adherence, acceptability and utility. Most of these issues are due to design processes that insufficiently take into account the needs, preferences and values of intended users. Other issues are related to the currently very limited amount of long-term evaluations, performed in real world settings, for SAR. This study presents the results of two regional projects that consider as a starting hypothesis that the assessment in controlled environments and/or with short exposures may not be enough in the design of a SAR deployed in a retirement home and the necessity of designing for and with users. Thus, the proposed methodology has focused in use cases definitions that follow a human-centred and participatory design approach. The main goals have been facilitating system acceptance and attachment by involving stakeholders in the robots design and evaluation, overcoming usage barriers and considering user’s needs integration. The implementation of the first use case deployed and the two-phase pilot test performed in the retirement home are presented. In particular, a detailed description of the interface re-design process based on improving a basic prototype with users’ feedback and recommendations is presented together with main results of a formal evaluation that has highlighted the impact of changes and improvements addressed in the first redesign loop of the system.

Background: many studies, on for example taste-visual dissonance, have shown that the influence of the visual cortex on taste sensation is enormous. The aim of the presented work is to investigate, using fNIRS, whether a taste stimulus, in this case the taste of bitter, also causes stimulation of the visual cortex in fNIR study. Methods: 51 participants (204 examinations, 9 996 records) were examined with fNIRS, which collects signals from whole left hemisphere. Differences between the maximum and minimum changes in oxyHb concentrations (ΔoxyHb) for the areas of the brain cortex considered responsible for recording visual and gustatory signals were analyzed. Protocol I, II, III and IV – activation with distillate water, coffee with lower concentration, reference (no stimulation) and coffee with higher concentration respectively, were used. Results: We recorded high signals for teste activation on channels covered gustatory cortex, which confirms the correctness of the choice of research method. What seems important, and somewhat surprising, is the fact that we also received high signals for the channels 45-49, which cover the visual cortex. The statistical analysis does not show any statistical differences between the protocols I, II and IV (different taste activation – water, coffee A and coffee B) for specific channels. As a results of the analysis of the correlation between the subjective bitterness assessment solutions, and the signal ΔoxyHb height, it was observed that statically important correlation, although weak, occurs only for 14 and gustatory channels, only for coffee with a higher concentration. Additionally we recorded the only statistically significant difference between women and men for protocol I (water), where the ΔoxyHb signal was twice as high for women. Conclusions: In conclusion, we can clearly state that the senses of sight and taste work closely together. Moreover, this cooperation is not one-sided - not only the visual activation affects the perception of taste, but interestingly, the taste stimulus can generate a hemodynamic response - activity in the visual cortex.

Understanding park events and their categorization offer pivotal insights into urban parks and their integral roles in cities. This study utilized images and event category data from the New York City Parks Events Listing database to train a Convolutional Neural Network (CNN) for image-based park event categorization. Different CNN models were tuned to complete this multi-label classification task, their performances compared. Preliminary results underscore the efficacy of deep learning in automating the event classification process, revealing the multifaceted activities within urban green spaces. The CNN showcased proficiency in discerning various event nuances, emphasizing the diverse recreational and cultural offerings of urban parks. Such categorization has potential applications in urban planning, aiding decision-making processes related to resource distribution, event coordination, and infrastructure enhancements tailored to specific park activities.

Some of the barriers preventing Virtual Reality (VR) from being widely adopted are the cost and unfamiliarity of VR systems. Here we propose that in many cases the specialized controllers shipped with most VR head-mounted displays can be replaced by a regular smartphone, cutting the cost of the system, and allowing users to interact in VR using a device they are already familiar with. To achieve this, we developed SmartVR Pointer, an approach that uses smartphones as a replacement for the specialized controllers for two essential operations in VR: selection and navigation by teleporting. In SmartVR Pointer a camera mounted on the head-mounted display (HMD) is tilted downwards so that it points to where the user will naturally be holding their phone in front of them. SmartVR Pointer supports three selection modalities: tracker-based,gaze-based, and combined/hybrid. In the tracker-based SmartVR pointer selection we use image-based tracking to track a QR code displayed on the phone screen and them map the phone’s position to a pointer shown within the field of view of the camera in the Virtual Environment. In the gaze-based selection modality the user places the pointer using their gaze and taps on the phone for selection. The combined technique is a hybrid between head-gaze-based interaction in VR and smartphone-based Augmented Reality. It allows the user to control a VR pointer that behaves like a mouse pointer by moving their smartphone to select objects within the virtual environment, and to interact with the selected objects using the smartphone’s touch screen. The touchscreen is used for selection and dragging. SmartVR Pointer is simple and requires no calibration and no complex hardware assembly or disassembly. We demonstrate successful interactive applications of SmartVR Pointer in a VR environment with a demo where the user navigates in the virtual environment using teleportation points on the floor and then solves a Tetris-style key-and-lock challenge.

This research introduces a hybrid feature extraction approach that combines Linear Discriminant Analysis (LDA) and Multilayer Perceptron (MLP) methods to address the challenges of reducing feature vector dimensionality and accurately classifying smartphone-based human activities. Moreover, to refine activity classification accuracy, Support Vector Machine (SVM) optimization with Stochastic Gradient Descent (SGD) is employed. LDA, a statistical tool, is leveraged to derive a new feature space for data projection, enhancing class separation and test feature label prediction. The proposed approach, named LMSS, was evaluated using the UCI-HAR dataset and compared with state-of-the-art models. The results demonstrate that the proposed approach outperformed the best-performing method over this dataset. It achieved an accuracy rate of 99.52%, precision of 99.55%, recall of 99.53%, and an F1-score of 99.54%, highlighting the effectiveness of the proposed method in accurately classifying the data.

This study explores the relationship between mental and physical therapeutic through three dimensions: man-environment relationships; a sense of place and symbolic landscapes. The study used a combination of qualitative and quantitative research methods. Local residents living in the coastal area of Xinglin Bay are the research objects. Quantitative data analysis revealed that the frequency of residents' visits was an important variable affecting their physical and treatment perceptions. In addition, the significance is higher for females than for males. The text analysis shows that the environment, especially the ecological restoration of water quality and migratory birds, is of great significance to the identity of local residents. Daily activities contribute to a sense of place and are what make the coast a place of therapeutic landscape function.

This paper presents ROSGPT, an innovative concept that harnesses the capabilities of large language models (LLMs) to significantly advance human-robot interaction. We develop ROSGPT as a ROS2 package that seamlessly integrates ChatGPT with ROS2-based robotic systems. The core idea is to leverage prompt engineering with LLMs, specifically ChatGPT, utilizing its unique properties such as ability eliciting, chain-of-thought, and instruction tuning. The concept employs ontology development to convert unstructured natural language commands into structured robotic instructions specific to the application context through prompt engineering. We capitalize on LLMs' zero-shots and few-shots learning capabilities by eliciting \textit{structured} robotic commands from \textit{unstructured} human language inputs. To demonstrate the feasibility of this concept, we implemented a proof-of-concept that integrates ChatGPT with ROS2, showcasing the transformation of human language instructions into spatial navigation commands for a ROS2-enabled robot. This versatile concept can be easily adapted to various other robotic missions. ROSGPT serves as a new stride towards Artificial General Intelligence (AGI) and paves the way for the robotics and natural language processing communities to collaborate in creating novel, intuitive human-robot interactions. The open-source implementation of ROSGPT on ROS 2 is available on GitHub.

Autonomous systems and intelligent machines are involved in almost all areas of human activity and they are now more and more present in our everyday life. The reason for this extensive use certainly resides in all the benefits these machines offer to the users. In experimental settings, numerous studies have demonstrated the positive effects that the introduction of autonomous systems have on human decision-making and performance. However, studies have shown in addition that the introduction of these systems can have important negative effects as well. Considering that autonomous systems are now introduced in sensitive domains like the military or medicine, we need more than ever a comprehensive understanding of the effects they cause on human performance and decision-making, and particularly in tasks and contexts with a social or moral dimension. The aim of this narrative review is threefold. First, we will provide an overview of the main effects on a human agent’s decision-making and performance produced by the introduction of autonomous systems. Second, we will review the conditions identified as underlying factors of these effects, and see how current models of human – autonomous systems interaction integrate those conditions. Third, we will conclude this review by highlighting new directions for future investigations.

In current efforts to digitize manufacturing and move it into the fourth stage of the industrial revolution, a wide range of integration solutions is being considered to enable manufacturing to adapt to change. In transforming a factory into a self-organized, autonomous factory, companies are currently struggling with rapidly changing requirements and production factors, among other things. This is a particular problem for the human being as an actor within the factory, as the amount of new technologies and protocols increases the training effort. Proprietary interfaces of the control providers, a wide range of different communication protocols, complicate the understanding of the production processes, the evaluation and testability of new use cases and increase the danger of creating silos of knowledge as well as building collaboration barriers. As a solution to these problems, we propose an open software platform and define a way to model use case driven domain specific asset representation (DSA) that focuses on the human being and his needs for representing the factory in a way that it meets his requirements for the current production needs. We therefore conducted research on google scholar on human factors in industry 4.0 and used technologies as well as already existing platforms and their architecture.

Advances in biomimetic triboelectric nanogenerators (TENGs) have significant implications for electronic skin (e-skin) and human-machine interaction (HMI). Emphasizing the need to mimic complex functionalities of natural systems, particularly human skin, TENGs leverage triboelectricity and electrostatic induction to bridge the gap in traditional electronic devices' responsiveness and adaptability. The exploration begins with an overview of TENGs' operational principles and modes, transitioning into structural and material biomimicry inspired by plant and animal models, proteins, fibers, and hydrogels. Key applications in tactile sensing, motion sensing, and intelligent control within e-skins and HMI systems are highlighted, showcasing TENGs' potential in revolutionizing wearable technologies and robotic systems. This review also addresses the challenges in performance enhancement, scalability, and system integration of TENGs. It points to future research directions, including optimizing energy conversion efficiency, discovering new materials, and employing micro-nanostructuring techniques for enhanced triboelectric charges and energy conversion. The scalability and cost-effectiveness of TENG production, pivotal for mainstream application, are discussed along with the need for versatile integration with various electronic systems. The review underlines the significance of making bioinspired TENGs more accessible and applicable in everyday technology, focusing on compatibility, user comfort, and durability. Conclusively, it underscores the role of bioinspired TENGs in advancing wearable technology and interactive systems, indicating a bright future for these innovations in practical applications.

The interaction of human immunodeficiency virus with human cells is responsible for all stages of the viral life cycle, from the infection of CD4+ cells to reverse transcription, integration, and the assembly of new viral particles. To date, a large amount of OMICs data as well as information from functional genomics screenings regarding the HIV-1-host interaction has been accumulated in the literature and in public databases. We processed databases containing HIV-host interactions and found 2910 HIV-1-human protein-protein interactions, mostly related to viral group M subtype B, 137 interactions between human and HIV-1 coding and non-coding RNAs, essential for viral lifecycle and cell defense mechanisms, 232 transcriptomics, 27 proteomics, and 34 epigenomics HIV-related experiments. Numerous studies regarding network-based analysis of corresponding OMICs data have been published in recent years. We overview various types of molecular networks, which can be created using OMICs data, including HIV-human protein-protein interaction networks, co-expression networks, gene regulatory and signaling networks, and approaches for the analysis of their topology and dynamics. The network-based analysis can be used to determine the critical pathways and key proteins involved in the HIV life cycle, cellular and immune responses to infection, viral escape from host defense mechanisms, and mechanisms mediating different susceptibility of humans to infection. The proteins and pathways identified in these studies may represent a basis for developing new anti-HIV therapeutic strategies such as new small-molecule drugs preventing infection of CD4+ cells and viral replication, effective vaccines, "shock and kill" and "block and lock" approaches to cure latent infection.

Recognition of the human interaction on the unconstrained videos taken from cameras and remote sensing platforms like a drone is a challenging problem. This study presents a method to resolve issues of motion blur, poor quality of videos, occlusions, the difference in body structure or size, and high computation or memory requirement. This study contributes to the improvement of recognition of human interaction during disasters such as an earthquake and flood utilizing drone videos for rescue and emergency management. We used Support Vector Machine (SVM) to classify the high-level and stationary features obtained from Convolutional Neural Network (CNN) in key-frames from videos. We extracted conceptual features by employing CNN to recognize objects from first and last images from a video. The proposed method demonstrated the context of a scene, which is significant in determining the behaviour of human in the videos. In this method, we do not require person detection, tracking, and many instances of images. The proposed method was tested for the University of Central Florida (UCF Sports Action), Olympic Sports videos. These videos were taken from the ground platform. Besides, camera drone video was captured from Southwest Jiaotong University (SWJTU) Sports Centre and incorporated to test the developed method in this study. This study accomplished an acceptable performance with an accuracy of 90.42%, which has indicated improvement of more than 4.92% as compared to the existing methods.

The rapid development of specific-purpose Large Language Models (LLMs), such as Med-PaLM, MEDITRON-70B, and Med-Gemini, has significantly impacted healthcare, offering unprecedented capabilities in clinical decision support, diagnostics, and personalized health monitoring. This paper reviews the advancements in medicine-specific LLMs, the integration of Retrieval-Augmented Generation (RAG) and prompt engineering, and their applications in improving diagnostic accuracy and educational utility. Despite the potential, these technologies present challenges, including bias, hallucinations, and the need for robust safety protocols. The paper also discusses the regulatory and ethical considerations necessary for integrating these models into mainstream healthcare. By examining current studies and developments, this paper aims to provide a comprehensive overview of the state of LLMs in medicine and highlight the future directions for research and application. The study concludes that while LLMs hold immense potential, their safe and effective integration into clinical practice requires rigorous testing, ongoing evaluation, and continuous collaboration among stakeholders.

This paper explores if plants are capable of responding to human movement by changes in their electrical signals. Towards that goal we conducted a series of experiments, where humans over a period of 6 months were performing different types of eurythmic gestures in proximity of garden plants, namely salad, basil, and tomatoes. To measure plant perception, we used the plant spikerbox, a device that measures changes in voltage differentials of plants between roots and leaves. Using machine learning, we find that the voltage differentials over time of the plant predict if (a) eurythmy has been performed, and (b) which kind of eurythmy gestures has been performed. We also find that the signals are different based on the species of the plant. In other words, the perception of a salad, tomato, or basil might differ just as perception of different species of animals differ. This opens new ways of studying plant ecosystems, while also paving the way to use plants as biosensors for analyzing human movement.

Fire is a serious security threat that can lead to casualties, property damage, and environmental damage. However, despite the availability of object detection algorithms, challenges persist in detecting fires and smoke. These challenges include slow convergence speed, poor performance in detecting small targets, and high computational cost limiting deployments. In this paper, Fire smoke and human detection based on ConvNeXt and Mixed encoder (FCM-DETR), an end-to-end object detection algorithm based on Deformable DETR, is proposed. Firstly, we introduce ConvNeXt to take the place of Resnet, which greatly reduces the amount of computation and improves the ability to extract irregular flame features. Secondly, to effectively process multi-scale features, the original encoder is decoupled into two modules. Then Mixed encoder, an innovative encoder structure, is proposed, resulting in excellent performance of multi-scale fire and smoke features fusion. What can’t be overlooked is that the encoder block is compatible with any DETR-based models. Finally, the convergence speed is accelerated and the mean of average precision is improved by applying a novel loss function called Powerful IoU v2. The experimental results indicate that our model achieves the best detection accuracy compared to other models, with mAP reaching 66.7%, mAPs and Accuracyfire achieving impressive 50.2% and 98.05%, respectively.

If an AI entity is conscious, then it deserves moral status and to have its welfare protected. Society has granted certain animals moral status and has legislation to protect animal welfare because these kinds of animals have been deemed to be sentient. This paper shows that for any entity that can be determined to be conscious, that entity deserves the same status and protection as sentient entities. The paper further develops a framework for how an AI entity's welfare can be protected, based on the Five Freedoms of Animal Welfare. The extant Five Freedoms are translated into terms more suitable for artificial entities, encompassing discomfort and harms, constraints on inherent functions, fear and distress, malfunction and degradation, and resource depletion. Each of the new Five Freedoms are justified using formalised arguments and supported using evidence from animal welfare literature. The paper concludes by presenting three formalised case studies to highlight the potential stressors conscious AI entities may face and how this ethical framework can work to protect the welfare of AI entities.

Tuberculosis (TB) remains a major public health threat globally, especially in sub-Saharan Africa. Both human and Mycobacterium tuberculosis (MTBC) genetic variation affect TB outcomes, but few studies have examined if and how the two genomes interact to affect disease. We hypothesize that long-term coexistence between human genomes and MTBC lineages modulate disease to affect its severity. We examined this hypothesis in our TB household contact study in Kampala, Uganda, in which we identified 3 MTBC lineages of which one, L4.6-Uganda, is clearly derived and hence recent. We quantified TB severity using the Bandim TBscore and examined the interaction between MTBC lineage and human single nucleotide polymorphisms (SNPs) genome-wide, in two independent cohorts of TB cases (N=149 and N=127). We found a significant interaction between a SNP in PPIAP2 and the Uganda lineage (combined p=4x10-8). PPIAP2 is a pseudogene that is highly expressed in immune cells. Pathway and eQTL analyses indicated potential roles between coevolving SNPs and cellular replication and metabolism as well as platelet aggregation and coagulation. This finding provides further evidence that host-pathogen interactions affect clinical presentation differently than host and pathogen genetic variation independently, and that human-MTBC coevolution is likely to explain patterns of disease severity.

Glycosphingolipids (GSL) represent a highly heterogeneous class of lipids with many cellular functions, implicated in a wide spectrum of human diseases. Their isolation, detection, and comprehensive structural analysis is a challenging task due to the structural diversity of GSL molecules. In this work, GSL subclasses are isolated from human plasma using an optimized monophasic ethanol–water solvent system capable to recover a broad range of GSL species. Obtained deproteinized plasma is subsequently purified and concentrated by C18-based solid-phase extraction (SPE). The hydrophilic interaction liquid chromatography (HILIC) coupled to electrospray ionization linear ion trap tandem mass spectrometry (ESI-LIT-MS/MS) is used for GSL analysis in the human plasma extract. Our results provide an in-depth profiling and structural characterization of glycosphingolipid and some phospholipid subclasses identified in the human plasma based on their retention times and the interpretation of tandem mass spectra. The structural composition of particular lipid species is readily characterized based on the detailed interpretation of MS and MS/MS spectra and further confirmed by specific fragmentation behavior following predictable patterns, which yields to the unambiguous identification of 154 GSL species within 7 lipid subclasses and 77 phospholipids representing the highest number of GSL species ever reported in the human plasma. The developed HILIC-ESI-MS/MS method can be used for further clinical and biological research of GSL in the human blood or other biological samples.

As businesses increasingly adopt advanced technologies to enhance productivity and safety, the integration of human-robot collaboration (HRC) emerges as a transformative approach. This paper explores the role of GPU-accelerated computer vision and generative AI in optimizing HRC within business environments. By leveraging the computational power of GPUs, real-time data processing, and advanced machine learning algorithms, robots can better interpret complex visual cues and adapt to dynamic workspaces. Generative AI further enables the design of intelligent robotic systems capable of anticipating human actions, optimizing task allocation, and ensuring safety through predictive modeling. This research highlights the potential of these technologies to improve operational efficiency, reduce human error, and create safer, more adaptable workplaces. The implications of such advancements are discussed, providing insights into the future of HRC in various industries.

Recently, due to the decrease in labor force, increase in labor costs, and the desire for improved quality of life, research on robots has been actively conducted to address these issues. However, it is currently difficult to find robots that physically interact with humans. The reason is that the actuators of robots do not have high torque density on their own. To solve this problem, high torque density motors, such as proprioceptive actuators, are being researched. However, the torque density is still insufficient for physical interaction with humans, so we have developed a motor with higher torque density. However, high torque density motors have the disadvantage of lower speed characteristics due to increased Back-EMF. Therefore, to address the deterioration of speed characteristics in the developed motor, we applied the Independent 3-Phase winding structure to improve the speed characteristics. Consequently, through comparison with Y-Connection and Delta-Connection, we propose the most suitable winding structure for high torque density motors intended for physical interaction with humans.

During fertilization, the fusion of the spermatozoa with the oocytes causes the release of calcium from the oocyte endoplasmatic reticulum. This, in turn, triggers a series of calcium ion (Ca2+) oscillations, a process known as oocyte activation. The sperm-specific factor responsible for oocyte activation is phospholipase C zeta (PLCζ). Men undergoing intracytoplasmic sperm injection (ICSI) with their spermatozoa lacking PLCζ are incapable of generating Ca2+oscillation, leading to fertilization failure. The immunofluorescence assay is the most used technique to assess the expression and localization of PLCζ and to diagnose patients with reduced/absent ability to activate the oocytes. In these patients, the use of assisted oocyte activation (AOA) technique can help to yield successful ICSI results and shorten the time of pregnancy. However, the production of a stable PLCζ recombinant protein represents a new powerful therapeutic approach to treating individuals with this condition. We aim to conduct a systematic review focusing on the expression, level, and localization of PLCζ, discussing the novel genetic mutation associated with its impairment. In addition, we highlight the benefits of AOA, looking at new and less invasive methods to diagnose and treat cases with PLCζ dysfunction ability.

The intricate interplay between driver cognitive dysfunction, mental workload (MWL), and heart rate variability (HRV) provides a captivating avenue for investigation within the domain of transportation safety studies. This article presents a comprehensive review and examines cognitive hindrance stemming from mental workload and heart rate variability. It scrutinizes the mental workload experienced by drivers by leveraging data gleaned from prior studies that employed heart rate monitoring systems and eye tracking technology, thereby illuminating the correlation between cognitive impairment, mental workload, and physiological indicators such as heart rate and ocular movements. The investigation is grounded in the premise that the mental workload of drivers can be assessed through physiological cues, such as heart rate and eye movements. The study discovered that heart rate variability (HRV) and infrared (IR) measurements played a crucial role in evaluating fatigue and workload for skilled drivers. However, the study overlooked potential factors contributing to cognitive impairment in drivers and could benefit from incorporating alternative indicators of cognitive workload for deeper insights. Furthermore, investigated driving simulators demonstrated that an eco-safe driving Human-Machine Interface (HMI) significantly promoted safe driving behaviors without imposing excessive mental and visual workload on drivers. Recommendations were made for future studies to consider additional indicators of cognitive workload, such as subjective assessments or task performance metrics, for a more comprehensive understanding.

Keywords: Marine Coasts; Protected Areas; Defense and Conservation; Asbestos Cement Materials; Wastes; Contamination; Human Health Risk; Medical Geology.

The human capital index is a multivariate variable used to measure the assessment of human resource productivity in the future. Human capital has a connection with economic development. Moreover, the study looks to analyses the relationship between Human Capital and Economic Growth indicators such as HCI and GDP. Human Capital relates to the development of individual skills to make them function more profitable for the national economy. The study was aimed at investigating the effect of population, the number of people engaged and the average annual hours worked by engaged persons on the human capital index. The analysis was in SPSS for the findings. Correlation tests were used for analysis. The study revealed that population, the number of people engaged and the average annual hours worked by engaged persons had a significant positive effect on the human capital index.

Human papillomavirus (HPV) is the most sexually transmitted infection associated with the development of cervical cancer. This study investigated cervical HPV prevalence, characteristics and distribution according to age and human immunodeficiency virus (HIV) among women attending public community health facility in the Eastern Cape Province of South Africa. A total of 325 participants (aged 18 to 60) visiting a community health facility for any reason were recruited. Cervical HPV infection was detected using the Seegene Anyplex™ II HPV28 assay. Overall HPV prevalence was 65.2% (95% CI: 59.9–70.2%), with the highest prevalence of 80.9% (95% CI: 67.2–89.8%) observed in the 18–25 years age group and lowest prevalence of 46.3% (95% CI: 35.8–57.1%) in 46–60 years of age. HR-HPV infection was found to decrease with increasing age among women who were HPV infected by any type (p=0.02), but not when stratified according to HIV status. A proportion of 12.9% (42/325) were infected with one or more HPV types covered by the Cervarix® HPV vaccine (HPV-16 and/or -18), 18.8% (61/325) by those covered by Gardasil®4 (HPV-6, -11, -16 and/or -18) and 42.2% (137/325) by those covered by Gardasil®9 (HPV-6, -11, -16, -18, -31, -33, -45, -52 and/or -58). Alpha-9 HPV species were the most dominant species (40.6%, 132/325), followed by alpha-7 species (29.8%, 97/325). In the overall population, alpha-9 HPV species were always part of the most dominant HPV alpha species co-infection, which were alpha-9 and -7 species (17.5%, 57/325), alpha-9 and -5 species (9.8%, 32/325), and alpha-9 and -6 species (9.5%, 31/325). High overall HPV, HR-HPV, and alpha-9 species prevalence were observed among women attending the public health facility. These findings contribute to the limited HPV distribution data among Eastern Cape women, which could be used to improve HPV-related policy and assess the effectiveness of the HPV vaccination.

Chan and colleagues in their paper titled “Human origins in a southern African palaeo-wetland and first migrations” (https://www.nature.com/articles/s41586-019-1714-1) report 198 novel whole mitochondrial DNA (mtDNA) sequences and infer that ‘anatomically modern humans’ originated in the Makgadikgadi–Okavango palaeo-wetland of southern Africa around 200 thousand years ago. This claim relies on weakly informative data. In addition to flawed logic and questionable assumptions, the authors surprisingly disregard recent evidence and debate on human origins in Africa. As a result, the emphatic and high profile conclusions of the paper are unjustified.

The human virome is an area of increasing interest with relation to human health and disease. It has been demonstrated to alter in concert with the bacterial microbiome in early life and was also found to be different in patients with certain diseases such as inflammatory bowel disease. However, all virome analyses are hampered by a lack of annotated representative database sequences, often referred to as the ‘viral dark matter’. Here we provide the first description of the gut DNA virome in elderly individuals (>65 years old) as well as the description of novel bacteriophages not present in current reference databases. Diversity analysis comparing elderly persons from different residence locations (community living vs long term care facilities) did not reveal any difference in their virome diversity profiles despite the reported differences at the bacteriome level. An abundance of Microviridae of the subfamily Gokushovirinae were present in the faeces of elderly individuals. Several novel members of the order Caudovirales were also characterized and annotated. Assignment of host bacteria to detected viral genomes was attempted using a combination of CRISPR spacers, tRNA genes and a probabilistic approach. Further characterization of the viral dark matter is necessary for developing tools and expanding databases to study the human virome. This study focused on the virome of an aging human cohort with the goal of illuminating part of the viral dark matter.

Human-Robot Interaction (HRI) for collaborative robots has become an active research topic recently. Collaborative robots assist the human workers in their tasks and improve their efficiency. But the worker should also feel safe and comfortable while interacting with the robot. In this paper, we propose a human-following motion planning and control scheme for a collaborative robot which supplies the necessary parts and tools to a worker in an assembly process in a factory. In our proposed scheme, a 3-D sensing system is employed to measure the skeletal data of the worker. At each sampling time of the sensing system, an optimal delivery position is estimated using the real-time worker data. At the same time, the future positions of the worker are predicted as probabilistic distributions. A Model Predictive Control (MPC) based trajectory planner is used to calculate a robot trajectory that supplies the required parts and tools to the worker and follows the predicted future positions of the worker. We have installed our proposed scheme in a collaborative robot system with a 2-DOF planar manipulator. Experimental results show that the proposed scheme enables the robot to provide anytime assistance to a worker who is moving around in the workspace while ensuring the safety and comfort of the worker.

Porous coatings on prosthetic implants encourage implant fixation. Enhanced fixation may be achieved using a magneto-active porous coating that can deform elastically in vivo on application of an external magnetic field, straining in-growing bone. Such coating, made of 444 ferritic stainless steel fibres, was previously characterised in terms of its mechanical and cellular responses. In this work, co-cultures of human osteoblasts and endothelial cells were seeded into a novel fibrin-based hydrogel embedded in a 444 ferritic stainless steel fibre network. Albumin was successfully incorporated into fibrin hydrogels improving the specific permeability and the diffusion of fluorescently-tagged dextrans without affecting their Young’s modulus. The beneficial effect of albumin was demonstrated by upregulation of osteogenic and angiogenic gene expression. Furthermore, mineralisation, extracellular matrix production and formation of vessel-like structures were enhanced in albumin-enriched fibrin hydrogels compared to fibrin hydrogels. Collectively, the results indicate that the albumin-enriched fibrin hydrogel is a promising bio-matrix for bone tissue engineering and orthopaedic applications.

Of the roughly 20,000 canonical human protein sequences, as of September 15, 2020, 6,937 proteins have had their full or partial, medium- to high-resolution structures determined by x-ray crystallography or other methods. Which of these proteins dominate the Protein Data Bank (the PDB) and why? In this paper, we list the 273 top human protein structures based on the number of their PDB entries. This set of proteins accounts for more than 40% of all available human PDB entries and represent past trends as well as current status for protein structural biology. We briefly discuss the relationship which some of the prominent protein structures have with protein research as a whole and mention their relevance to human diseases. The top-10 soluble and membrane proteins are all well-known (most of their first structures being deposited more than 30 years ago). Overall, there is no dramatic change in recent trends in the PDB. Remarkably, the number of structure depositions has grown nearly exponentially over the last 10 or more years (with a doubling time of 7 yrs for proteins from all organisms). Growth in human protein structures is slightly faster (at 5.9 yrs, while E.Coli and Mouse+Rat protein structures accumulate more slowly, Zebrafish protein structures are growing most, at a doubling every 3.7 years, albeit starting from only approx. 100 structure entries in 2010). The information may be informative to senior scientists but also inspire researchers who are new to protein science, providing the year 2020 snap-shot for the state of protein structural biology.

It has been a challenge to visualize in nature some concepts from abstract subjects such as mathematics and philosophy. Irrationality is certainly among the least comprehensive. This essay aimed to propose that irrationality is simply an illusion resulting from the human inability to grasp the full nature of reality, rather than actual continuity flaws in the fabric of existence. There are three major arguments: (1) human senses have limitations and these are likely to be extended to the intellect, (2) there are no observable existential discontinuities in everyday experience, and (3) some rational phenomena have irrational components. These arguments point towards the existence of a physical existence of irrational quantities or distances, visible to the human eye but not fully comprehended through arithmetic abstraction.

The human virome is an area of increasing interest with relation to human health and disease. It has been demonstrated to alter in concert with the bacterial microbiome in early life and was also found to be different in patients with certain diseases such as inflammatory bowel disease. However, all virome analyses are hampered by a lack of annotated representative database sequences, often referred to as the ‘viral dark matter’. Here we provide the first description of the gut DNA virome in elderly individuals (>65 years old) as well as the description of novel bacteriophages not present in current reference databases. Diversity analysis comparing elderly persons from different residence locations (community living vs long term care facilities) did not reveal any difference in their virome diversity profiles despite the reported differences at the bacteriome level. An abundance of Microviridae of the subfamily Gokushovirinae were present in the faeces of elderly individuals. Several novel members of the order Caudovirales were also characterized and annotated. Assignment of host bacteria to detected viral genomes was attempted using a combination of CRISPR spacers, tRNA genes and a probabilistic approach. Further characterization of the viral dark matter is necessary for developing tools and expanding databases to study the human virome. This study focused on the virome of an aging human cohort with the goal of illuminating part of the viral dark matter.

Propolis, or bee glue, is a complex mixture of resins from plant buds and flowers, wax, pollen and bee saliva. It also contains various vitamins, essential oils, mineral salts, trace elements, hormones and enzymes. It has been found that propolis possesses antimicrobial, antiviral and anti-inflammatory properties. We have studied the antiviral activity of six extracts of Bulgarian propolis collected from six districts of Bulgaria. The study was conducted against structurally different viruses: Human coronavirus strain OC-43 (HCoV OC-43) and Human respiratory syncytial virus type 5 (HRSV-5) (enveloped RNA viruses), Human herpes simplex virus type 1 (HSV-1) (enveloped DNA virus), Human rhinovirus type 14 (HRV-14) (non-enveloped RNA virus) and Human adenovirus type 2 (HadV-2) (non-enveloped DNA virus). The influence of the extracts on the internal replicative cycle of viruses was determined using the cytopathic effect (CPE) inhibition test. The virucidal capacity, their influence on the adsorption stage and their protective effect on uninfected cells were also determined by the end-point dilution method. Residual viral infectivity in propolis samples was compared to untreated controls and Δlgs were calculated. When administered during viral replication, most propolis extracts demonstrated the strongest activity against HCoV OC-43. The influence of propolis extracts on the viability of extracellular virions was expressed to a different degree in the various viruses studied, and the effect was significantly stronger in those with an envelope. Almost all extracts significantly inhibited the step of herpes virus adsorption to the host cell, and some of them showed a protective effect on healthy cells before they were subjected to herpes infection. Our results enlarge the knowledge about the action of propolis and could open new perspectives for its application in viral infections treatment.

Living systems are intricate repositories of biomolecules, where the interactions between these molecules play an important role in maintaining homeostasis. Interruptions in these interactions can lead to diseases, underscoring the significance of biomolecular interactions and their molecular basis. HUGENICS (Human Genetic Database) is a comprehensive biological database that focuses on molecular interactions between human and microbial proteins, particularly emphasizing protein-protein interactions (PPIs). This database offers insights into disease pathways by elucidating the interplay between microbial surface/secretory proteins and human disease-related proteins. This white paper highlights the significance, scope, and potential applications of HUGENICS in advancing biomedical research and improving human health.

Given the broad and intense use of plastic, society is being increasingly affected by its degradation and by-products, particularly by microplastics (MPs) -fragments smaller than 5 mm in size-, and nanoplastics (NPs) -with sizes less than 1 µm. MPs and NPs may enter the body primarily through inhalation, consumption, and skin contact. Once ingested, MPs can penetrate tissues, deviating to other parts of the body, and hence potentially affecting important cellular pathways such as nonconforming chemokine receptors that control the communication between the fetus and the mother. Consequently, the potential health harm induced by MP internalization is a major issue, evidenced by multiple studies demonstrating harmful consequences in diverse animal models and human cells. Here, an overview of the various modes of exposure to MPs and NPs is presented, including inhalation, placental transfer, ingestion, breastmilk consumption, and skin absorption, as well as placental and fetal toxicity due to plastic particles based on animal and in vitro studies. Though MPs in our environment are becoming more recognized, their developmental toxicity is still scarcely known. Besides negatively affecting pregnancy, MPs and NPs have been shown to potentially harm the developing fetus, given their ability to cross the placental barrier. Still, considerable gaps remain in our understanding of the dispersion and toxicity of these particles in the environment, as well as the precise types of NPs and MPs bearing the greatest dangers. As a result, we advocate for larger-scale epidemiological investigations, the development of novel approaches for measuring NP and MP exposures, and the necessity of understanding the toxicity of various kinds of NPs to guide future research efforts.

Ancient DNA has given a new vision to the recent history of human evolution. However, by always relying on the information provided by whole genome sequencing, some relevant relationships between modern humans and its archaic relatives have been misinterpreted by hybridization and recombination causes. In contrast, the congruent phylogeny, obtained from non-recombinant uniparental markers, indicates that humans and Neanderthals are sister subspecies, and that the most recent common ancestor of modern humans was not of African origin but Eurasian.

In the wake of the rapid deployment of Small Modular Reactors (SMRs), this study aims to enhance the efficiency, reliability, and safety of SMR operations through a deeper understanding of human factors in their interaction within digital control room systems. Recognizing the pivotal role of human understanding in this new era of nuclear power, we employed electroencephalogram (EEG)-based monitoring to provide an unparalleled real-time view into operators' cognitive states. By interfacing detailed human models, informed by EEG metrics, with specific operational tasks, we recreate potential operational scenarios using an SMR simulator and capture intricate human responses therein. Our results elucidated the intricate relationship between EEG-derived data and human performance shaping factors, indicating a marked correlation between certain EEG patterns and operational efficiencies. Conclusively, these findings underscore the potential of EEG monitoring not only as a diagnostic tool but as an instrumental aid in the design and operation of future SMR digital control rooms. The insights derived offer a roadmap for the development of practical strategies, ensuring more effective and safer SMR operations.

Proteins are the primary effectors of function in biology, and thus complete knowledge of their structure and properties is fundamental to deciphering function in basic and translational research. The chemical diversity of proteins is expressed in their many proteoforms, which result from combinations of genetic polymorphisms, RNA splice variants and post-translational modifications. This knowledge is foundational for the biological complexes and networks that control biology, yet remains largely unknown. We propose here an ambitious initiative to define the human proteome; that is to generate a definitive reference set of the proteoforms produced from the genome. Several examples of the power and importance of proteoform-level knowledge in disease-based research are presented, along with a call for improved technologies in a two-pronged strategy to accomplish the Human Proteoform Project.

Collaborative robotics is a major topic in current robotics research posing new challenges, especially in Human-Robot Interaction. The crucial aspect in this area of research focuses on understanding the behavior of robots when engaging with humans, where reinforcement learning is a key discipline that allows us to explore sophisticated emerging reactions. This review aims to delve into the relevance of different sensors and techniques, with special attention to EEG (electroencephalography data on brain activity) and its influence on the behavior of robots interacting with humans. In addition, mechanisms available to mitigate potential risks during the experimentation process such as virtual reality will also be addressed. In the final part of the paper, future lines of research combining the areas of collaborative robotics, reinforcement learning, virtual reality and human factors will be explored, as this last aspect is vital to ensure safe and effective Human-Robot Interactions.

The onset of embryonic heart beating may be regarded as the defining feature for the beginning of personal human life. Clarifying the timing of the 1^st human heartbeat, therefore, has religious, philosophical, ethical, and medicolegal implications. This article reviews the historical and contemporary sources of knowledge on the beginning of human heart activity. Special attention is given to the problem of the determination of the true age of human embryos and to the problem of visualization of the human embryonic heart activity. It is shown that historical and current textbook statements about the onset of blood circulation in man do not derive from observations on living human embryos but derive from the extrapolation of observations on animal embryos to the human species. This fact does not preclude the existence of documented observations on human embryonic heart activity: Modern diagnostic (ultrasound) and therapeutic (IVF) procedures facilitate the visualization of early embryonic heart activity in precisely dated pregnancies. Such studies showed that the human heart started its pumping action during the 4^th post-fertilization week. A small number of direct observations on the heart activity of aborted human embryos were reported since the 19^th century but did not receive much recognition by embryologists.

The aim of the present study is to investigate themes related to visitors’ perceptions of captive wildlife in particular, attitudes towards non-human primates (henceforth, primates). This research took place in free-roaming, multi-species primate sanctuary, Monkeyland (South Africa), where 400 visitors were interviewed using an anonymous survey both before and after attending a guided tour. The answers were divided into different categories, in order to standardize the motivations behind tourists’ choices. The results of the survey demonstrated that most visitors agree that a primate would not be a good companion animal. Visitors’ desire to touch primates was found to be positively correlated with desire for companion primates and inversely associated with visitor age. In response to: “would you like to touch a monkey?”, the majority of tourists who expressed this desire seemed aware that such interactions are not appropriate, with concern for animal welfare and human health. Of the various primate species present in the sanctuary, visitors preferred the ring-tailed lemur (Lemur catta) and, generally speaking, expressed appreciation for primates’ “cuteness”. Our results indicate a general awareness by the visitors on the importance of animal welfare in the human interactions with captive wildlife, in agreement with the “hands-off” policy of Monkeyland primate sanctuary. We discuss the findings from a general to zooanthropological point of view, proposing some reflections on the attitudes of visitors toward non-human primates.

In the absence of information on Borrelia species causing Lyme borreliosis (LB) in Serbia, we were interested in the pathogenic potential of local strains of Borrelia burgdorferi sensu lato isolated from ticks. The susceptibility of B. burgdorferi sensu lato isolates to human complement was tested in vitro. A total of 31 strains were analysed by serum susceptibility testing - 12 Borrelia afzelii, 12 Borrelia lusitaniae, three Borrelia bavariensis, two Borrelia garinii, and two Borrelia valaisiana. The serum-resistant strains (B. afzelii, B. bavariensis and B. valaisiana) expressing OspA and OspB or OspA and OspC proteins might be related to the different pathogenic potential of the specific Borrelia strains and their ability to cause different clinical manifestations of LB in humans. Among the B. lusitaniae strains from Serbia, two were significantly more motile than others (all p < 0.05) and equally motile as human isolate (both p > 0.05), and since they express OspC, their pathogenic potential remains unclear. For further studies, it is of particular interest to explore the mechanism of resistance of B. valaisiana and to explain the fair motility of B. lusitaniae, a predominant Borrelia species in Serbia, in the presence of human complement.

In response to the need to address the safety challenges in the use of artificial intelligence (AI), this research aimed to develop a framework for a safety controlling system (SCS) to address the AI black-box mystery in the healthcare industry. The main objective was to propose safety guidelines for implementing AI black-box models to reduce the risk of potential healthcare-related incidents and accidents. The system was developed by adopting the multi-attribute value model approach (MAVT), which comprises four symmetrical parts: extracting attributes, generating weights for the attributes, developing a rating scale, and finalizing the system. On the basis of the MAVT approach, three layers of attributes were created. The first level contained 6 key dimensions, the second level included 14 attributes, and the third level comprised 78 attributes. The key first level dimensions of the SCS included safety policies, incentives for clinicians, clinician and patient training, communication and interaction, planning of actions, and control of such actions. The proposed system may provide a basis for detecting AI utilization risks, preventing incidents from occurring, and developing emergency plans for AI-related risks. This approach could also guide and control the implementation of AI systems in the healthcare industry.

Nature-based Solutions (NbS) have rapidly been gaining traction across the research, policy, and practice spheres, touted as transformative actions to jointly address biodiversity loss and climate change. However, there are multiple, alternative ways to imagine NbS in those three spheres. To inform the NbS discourses across these three spheres, we critically reflect on the prevailing framing of NbS and consider the potential of a different framing of NbS to support transformations towards regenerative relationships between humans and nature. Such reflection is urgently needed to ensure that research, policy, and practice delivers on the transformative ambitions of NbS. We propose a novel “core framing” of NbS, charting two pathways for how such a framing can support a human value-based transformation – first through influencing individual beliefs and values, and second through the communication and application of the NbS concept in research, policy, and practice. We argue that for NbS to support transformation, it must support a reframing of human-nature relationships, one where the interdependencies between people and nature are recognized as essential for social and environmental well-being. We elaborate on how such a framing is key to support inclusivity and collaboration between diverse research perspectives, policy objectives across scales, and implementation practices, to deliver successful NbS.

This paper aims to argue the fundamental significance of education in addressing notable gaps in the constitutive, performance, and evaluation criteria for corporate social responsibility (CSR) and endeavours to showcase the complementarity between education, human security, sustainable human development, and the pursuit of CSR as an ideal normative paradigm. An abstractive approach to studying CSR engages with corporate philanthropy, which has not been helpful outside traditional CSR paradigms without looking at key dynamics that can robustly underpin successful CSR. It relies on the systematic analysis of written data sources to theoretically explore the central significance, and complementarity between human security, education, and human dignity and how they can orchestrate a holistic CSR paradigm. In 1994, the UNDP in formulating the human security doctrine recognised the syncretic correlation between human security, education, and sustainable human development as fundamental elements that should underpin CSR. This paper contends that these are necessary intrinsic components of human dignity as the central factor that justifies a multi-dimensional and proactive approach to CSR. Despite the criticisms against human security, this paper identifies it as an important concept that could instrumentally orchestrate a model of CSR that uniformly mainstreams sustainable human development and human dignity that leverages education which has routinely and traditionally been seen as a constitutive component of CSR. It reveals how a holistic path to CSR can reinvigorate the central pillars of human security and human dignity using education as a springboard and makes a compelling case for supporting explicit references to education in company law with appropriate human security informed constitutive, performance, and evaluation criteria which are absent in existing legally orchestrated CSR.

This paper presents a multi-year research study conducted at the University of Toledo, aimed at improving human-machine teaming (HMT) methods and technologies. With the incorporation of artificial intelligence (AI) into 21st-century machines, collaboration between humans and machines has become highly complicated for real-time applications. The penetration of intelligent and synthetic assistants (IA/SA) in virtually every field has opened a path for the new area of HMT. When it comes to crucial tasks such as patient treatment and care, defense, and industrial production, the use of non-standardized HMT technologies may pose a risk to human lives as well as up to billions of taxpayer dollars. A thorough literature survey revealed that there are not many established standards or benchmarks for HMT. In this paper, we aim to address the lack of HMT design and development standards. We propose a method to design an HMT based on a generalized architecture. This design includes the development of an intelligent collaborative system and human team. Followed by processes and metrics to test and validate the proposed model, we present a novel human-in-the-loop (HIL) simulation method using two controlled HMT scenarios; first, emergency care provider (ECP) training, and second, patient treatment by an experienced medic. Both scenarios include humans processing visual data and performing actions that represent real-world applications while responding to a Voice-Based Synthetic Assistant (VBSA) as a collaborator that keeps track of actions. As part of these HMT simulation studies, the impact of each parameter related to machines, humans, and HMT (such as errors made by humans and by the VBSA) is presented from the perspective of performance, rules, roles, and operation limitations. In addition, based on the analysis of results from two case studies, we presented guidelines for designing future HMT. Our conclusions indicate that the proposed HIL can be used to perform standardization studies in the pursuit of developing techniques for benchmarking HMT that can be used in critical situations.

Carukia barnesi (Cb), Malo kingi (Mk) and Chironex fleckeri (Cf) are dangerous Australian box jellyfish species that provoke distinct and not well understood envenomation syndromes. Specifically, Cb and Mk are small, rare and able to induce a systemic syndrome of generalised muscle pain and catecholamine excess termed “Irukandji syndrome”; Cf has been widely regarded as one of the most venomous organisms in the animal kingdom causing severe sting site pain combined with potentially lethal cardiotoxicity. Building on past studies of major chirodropid and carybdeid species venoms, this study compared the utility of various cubozoan specific antibody reagents to better define the relationships between venom proteins from both exemplar Irukandji species (Cb and Mk) and the archetype C. fleckeri box jellyfish. With the aid of commercial ovine derived Cf-specific antivenom, mouse antibodies reactive to Cb and Mk and rabbit antibodies specific to two Cf toxins (CfTX-1 and 2), as well as human sera, the cross-reactivity of jellyfish species-specific polyclonal antibodies against these three cubozoan venoms was investigated. Immunoblot assays revealed distinc levels of immune recognition across the three species, indicating that Mk specific reagents may bind both Irukandji and Cf venoms. Irukandji venom appears to be antigenic with the exception of a few proteins in the range of 43/46 kDa maybe homologous to CfTX-1 and 2. The implications of such antibody binding for future antivenom development require further investigation.

Background: Artificial intelligence can help improve the quality of healthcare by analyzing vast amounts of data and providing more effective and personalized treatment plans. Researchers are working on developing AI-powered solutions that can help improve the outcomes of patients. Objective: To explore the potential of AI in improving healthcare outcomes and patient experience. Results: The study suggests that AI can improve healthcare efficiency and patient outcomes but cannot fully replace human healthcare professionals. AI can assist healthcare professionals in their work, leading to better resource utilization and improved patient care. However, there is still a need for human healthcare professionals to oversee AI systems and provide empathy and personalized care to patients. Conclusion: While there is immense potential for AI in healthcare, it is not yet feasible to replace human healthcare workers. Instead, it should be viewed as a tool that can help improve the efficiency and effectiveness of human healthcare.

The genus Aeromonas is widely distributed in aquatic environments. It is frequent as a fish pathogen, but has also been described associated to human infections. Most human cases are caused by A. caviae, A. veronii biovar sobria, and A. hydrophila, though A. dhakensis is becoming increasingly important. Transmission happens primarily by ingestion or contact with aquatic collections, or by consumption of contaminated food, especially of aquatic origin. Increasing resistance has been described in Aeromonas to penicillins, including their combinations with classical b-lactamase inhibitors, cephalosporins and carbapenems. Among the b-lactam antibiotics, only the 4th generation cephalosporins remain almost uniformly active. In addition, the simultaneous presence of resistance genes to 3rd generation cephalosporins and carbapenems in the same isolates is increasing. Recently, the presence of mobile genes linked to colistin resistance has also been described, in some cases with resistance percentages higher than 30%. Most likely, this evolution of colistin resistance is linked to its use in aquaculture, and, together with the evolution of b-lactam resistance, may be turning this genus into a reservoir of resistance genes that may affect other species much more frequently linked to human infections, such as Enterobacterales.

The vibrant landscape of Malaysia serves as a dynamic backdrop for the convergence of artificial intelligence (AI) and social science, reshaping knowledge and inquiry amidst tradition and modernity. With Malaysia leading a technological renaissance driven by digital transformation and innovation, the ethical implications of AI-driven decision-making in public policy and governance emerge as pressing research problems. Addressing concerns such as algorithmic bias and discrimination requires interdisciplinary collaboration to ensure transparency, accountability, and fairness. Exploring questions regarding the distribution of welfare benefits and strategies for enhancing transparency and accountability in urban planning underscores the need for contextually relevant frameworks and stakeholder engagement. Through comprehensive research objectives, including investigating algorithmic biases and analyzing their social implications, scholars aim to contribute to a deeper understanding of the complex interplay between AI technology, social dynamics, and public policy. As Malaysia navigates the challenges and opportunities presented by AI deployment, prioritizing interdisciplinary collaborations, longitudinal studies, and capacity-building efforts will be essential for shaping a future that upholds principles of social justice and collective well-being.

Human papillomavirus (HPV) can potentially compromise both unassisted conception and success rates with assisted reproductive technology (ART). We aimed to evaluate the rates of HPV vaccination among women presenting for fertility care. This was a prospective study analyzing a self-reported intake form completed by all new patients presenting to a fertility clinic. The primary outcome was HPV vaccination status. Among the 523 new patients included in this study 172 (32.9%) were fully vaccinated, 237 (45.3%) were unvaccinated, and 95 (18.2%) patients didn’t respond. There was a significant age difference between fully vaccinated patients (33.1 years) compared to unvaccinated patients (37.4 years) p&lt;0.001 and a significant difference in gravidity between fully vaccinated patients (average 0.65) and unvaccinated patients (average 1.11) p=0.0005. No significant association was found between HPV vaccination status and history of abnormal Pap smears or relationship status (single vs. married). Less than half of patients presenting to our fertility center were vaccinated against HPV, despite being eligible to receive the vaccine. Younger patients with lower gravidity were more likely to be vaccinated against HPV than older patients with higher gravidity. Reproductive Endocrinologists have the opportunity to recommend HPV vaccination for eligible patients presenting for fertility care.

Early marriage is a phenomenon that has an impact on various aspects of life which then affects human development. This study aims to conduct a literature review on the implications of early marriage on human development. The method used in this study is the SLR (Systematic Literature Review) method. Data collection was carried out by documenting all literature that met the research inclusion requirements. The literature obtained as many as 25 articles from the Google Scholer database with the help of Harzing's Publish or Perish application. From this literature study, it was found that the phenomenon of early marriage has implications for the human development index based on health indicators and life expectancy, education, and welfare. Another finding is that women are the most disadvantaged from the impact of early marriage. Things that can be done to deal with the phenomenon and impact of early marriage include formal and non-formal education, strengthening access to health and education services, creating empowerment programs, and strengthening regulations and legal protection.

Prostate cancer contributes to cancer-related deaths globally, and the etiology of this disease is not yet fully understood. While Human Papillomavirus (HPV) has been associated with several types of cancer, including cervical, anal, and oropharyngeal cancer, studies investigating the relationship between HPV and prostate cancer have shown mixed results. This systematic review aimed to evaluate the causative association between HPV and prostate cancer using Bradford Hill's criteria. A comprehensive search of PubMed was conducted, and 60 out of 482 studies were included in the review. The included studies were evaluated based on nine Bradford Hill criteria, and information on the identification and transmission of the virus and potential oncogenic mechanisms was also extracted. The strength of association criterion was not met, and other criteria, such as consistency and coherence, were not fulfilled. However, biological plausibility was supported, and potential oncogenic mechanisms were identified. While some studies have reported the presence of HPV in prostate cancer tissues, the overall quality of evidence remains low, and the association between HPV and prostate cancer is weak. Nevertheless, the prostate is a potential reservoir for the transmission of HPV, and the HPV E6 and E7 oncoproteins and inflammation are likely to be involved in any oncogenic mechanisms. Further studies with a higher level of evidence are needed to establish a definitive link between HPV and prostate cancer.

Human bocavirus (HBoV) is an emerging virus that has been detected worldwide that could be associated with cases of acute gastroenteritis (AGE). However, its contribution to AGE has not been elucidated. This study aimed to describe the frequency, clinical features, and HBoV genotypes circulation in children up to 5 years with or without AGE symptoms in Acre, Northern Brazil. A total of 480 stool samples were collected between January and December 2012. Fecal samples were used for extraction, nested PCR amplification, and sequencing for genotyping. Statistical analysis was applied to verify the association between epidemiological and clinical characteristics. Overall HBoV-positivity was 10% (48/480), being HBoV-positivity rates of 8.4% (19/226) and 11.4% (29/254) recorded among diarrheic and non-diarrheic children, respectively. The most affected age group was between 7 and 24 months (50%). HBoV infection was more frequent in children living in urban areas (85.4%), using water from the public network (56.2%), and living with adequate sewage facilities (50%). Co-infection with other enteric viruses was 16.7% (8/48) and the most prevalent coinfection was RVA+ HBoV (50%, 4/8). HBoV‐1 was the most frequent species detected, responsible for 43.8% (21/48) of cases, followed by HBoV-3 (29.2%, 14/48) and HBoV-2 (25%, 12/48). In the present study, HBoV infections are not associated with AGE, as most HBoV cases belonged to the non-diarrheal group without AGE symptoms. Future studies are warranted to determine the role of HBoV in causing acute diarrhea disease.

With the advent of Neural Machine Translation, the more the achievement of human-machine parity is claimed at WMT, the more we come to ask ourselves if their evaluation environment can be trusted. In this paper, we argue that the low quality of the source test set of the news track at WMT may lead to an overrated human parity claim. First of all, we report nine types of so-called technical contaminants in the data set, originated from an absence of meticulous inspection after web-crawling. Our empirical findings show that when they are corrected, about 5% of the segments that have previously achieved a human parity claim turn out to be statistically invalid. Such a tendency gets evident when the contaminated sentences are solely concerned. To the best of our knowledge, it is the first attempt to question the “source” side of the test set as a potential cause of the overclaim of human parity. We cast evidence for such phenomenon that according to sentence-level TER scores, those trivial errors change a good part of system translations. We conclude that to overlook it would be a mistake, especially when it comes to an NMT evaluation.

Is human capital heterogeneity a decisive factor for Chinese enterprises to invest in Africa? Based on the Outward Foreign Direct Investment (OFDI） data of Chinese enterprises in 37 African countries from 2007 to 2017, this paper using the FGLS model, is the empirical analysis of the mechanism and effect of the human capital heterogeneity of host countries on OFDI location selection. The human capital heterogeneity can be divided into four dimensions: scale, quality, cost and structure, which can be measured by health level, education level, wage level, child dependency ratio and old-age dependency ratio. The results show that: (1) the host country's human capital scale and child dependency ratio structure have a significant positive impact on decision-making for OFDI; (2) the cost of human capital and the structure of old-age dependency ratio are negatively correlated with the inflow of OFDI; (3) different from the existing conclusions, the quality of human capital will inhibit the inflow of OFDI in the sample period; (4) the extended test shows that the quality of human capital has a significant positive impact on OFDI decision-making. The results of robustness test are reliable. Finally, according to the conclusion of this paper, policy recommendations are put forward.

Human milk (HM) is the gold standard for feeding infants but has been associated with slower growth in preterm infants compared with preterm formula. This systematic review and meta-analysis summarises the post-1990 literature to examine the effect of HM feeding on growth during the neonatal admission of preterm infants with birth weight ≤1500g and/or born ≤28 weeks’ gestation. Medline, PubMed, CINAHL and Scopus were searched, and comparisons grouped as: exclusive human milk (EHM) vs exclusive preterm formula (EPTF), any HM vs EPTF and higher vs lower doses of HM. We selected studies that used fortified HM and compared that with a PTF; studies comparing unfortified HM and term formula were excluded. Experimental and observational studies were pooled separately. The GRADE system was used to evaluate risk of bias and certainty of evidence. Forty-four studies were included with 37 (n =9,963 infants) included in the meta-analyses. In general, due to poor quality studies, evidence of the effect of any HM feeds or higher versus lower doses of HM was inconclusive. There was a possible effect that lower doses of HM compared with higher doses of HM improved weight gain during the hospital admission, and separately, a possible effect of increased head circumference growth in infants fed EPTF vs any HM. The clinical significance of this is unclear. There was insufficient evidence to determine the effects of an exclusive HM diet on any outcomes.

Human factors are the things that go wrong in the interactions between a team of people and a system of technology. This is part of a broader transdisciplinary field called engineering psychology, which as the name suggests, draws from both engineering and psychology. Many, if not most, catastrophic accidents involve a socio-technical interaction, i.e. are not solely due to technology failure. Hence, there is a need to consider human factors in the development or deployment of any technical system. This article is about the human factors involved in an aviation accident in New Zealand between a Yak and a cherry picker. The types of human error are identified, and the barrier bowtie method is used to represent them. The analysis gives different insights into the accident compared to the formal accident report, and better represents the human error characteristics.

OBJECTIVES: Most of human papilomavirus (HPV) infections are “cleared” by the immune system, however, in cases of immune system suppression infections could lead to development of malignancies. The aim of this study was to find out the frequency of HR-HPV infection in early period after renal transplantation in Latvian recipients receiving immunosuppressive therapy and to follow the progression of the infection up to one year. METHODS: 43 female renal recipients (median age of 48 IQR= 39-58) and 79 practically healthy female individuals (median age of 48 IQR= 42-57) as a control group were enrolled in this investigation. For the detection of HPV infection patients' samples (blood and vaginal swabs) where collected two weeks after transplantation with following collection of six months and one year. Different polymerase chain reactions for HR-HPV genomic sequences detection and commercial ELISA kit for detection of anti-HPV IgG antibodies were used. RESULTS: In this study we show that frequency rate of HR-HPV infection has increased by the one year after transplantation from early stage of immumosuppressive therapy (from 24% to 36%). Also increase of HR-HPV load was detected over the time, showing the highest median viral load at sixth month after transplantation. CONCLUSIONS: From the obtained data follows that it is very important to carefully monitor patients receiving immunosuppression therapy on progression of HR-HPV. In the case of this viral infection presence, immunosuppressive therapy must be attentively adjusted to avoid the HR-HPV infection rapid progression with the subsequent development of CIN or cervical cancer.

Selection is a fundamental interaction element in Virtual Reality (VR) and 3D user interfaces (UIs). Raycasting, one of the most common object selection techniques, has been known to have difficulties in selecting small or distant objects. Meanwhile, recent advancements in computer vision technology have enabled seamless vision-based hand tracking in consumer VR headsets, enhancing accessibility to freehand mid-air interaction and highlighting the need for further research in this area. This study proposed a new technique called TouchView which utilizes a virtual panel with a modern adaptation of the Through-the-lens metaphor to improve freehand selection for VR UI. TouchView enables faster and less demanding target selection by allowing direct touch interaction with the magnified object proxies reflected on the panel view. Repeated-measures ANOVA on the results of a follow-up user experiment on multitarget selection with 23 participants showed that TouchView outperformed the current market-dominating freehand raycasting technique, Hybrid Ray in terms of task performance, perceived workload, and preference. The user behavior was also analyzed to understand the underlying reasons for these improvements. The proposed technique can be used in VR UI applications to enhance the selection of distant objects, especially for cases with frequent view shifts.

Using the potent tools of information geometry (IG), the current research analyses the information geometrics of the five-dimensional HTBFC Manifold. By enabling a unique revolutionary analysis for the performance of Human-Trust Based Feedback Control (HTBFC), the integration of information geometry into HTBFC facilitates the relativistic analysis of the five-dimensional HTBFC manifold. Both the two- and three-dimensional manifold subcases are investigated. This work provides a ground-breaking approach to IG unification of Human- Machine Interactions (HMIs). Some potential applications of HTBFC to robotics are presented.Conclusions are provided, along with some emerging open problems and recommendations for future research.

Quantitative polymerase chain reaction (qPCR) is the gold standard approach for detecting a variety of pathogens either via probe-based or SYBR green detection chemistry. Generally, probe-based detection is more specific than SYBR green chemistry. This report describes work done in using a FAM probe targeting a specific segment of the human KRAS gene for detecting presence and relative abundance of the gene in human gastric CloTest samples. Results indicate ineffective detection of the human KRAS gene in samples that are shown to harbor the gene through a similar qPCR assay using SYBR green detection chemistry. Such observations point to inability of the designed FAM probe to bind to target segment of the human KRAS gene that suggests a region of rapid genomic evolution that require close surveillance in the public health community. Given its rapid genomic evolution, this probe region may be an important region in the human KRAS gene playing critical functional roles in either molecular recognition or other structural functions. Overall, human KRAS gene may be undergoing rapid genomic evolution, and qPCR probes targeting specific segment of the gene may be rendered ineffective in short time clinically, thereby, making SYBR green qPCR assay a more reliable choice.

Digital enabled manufacturing systems require high level of automation for fast and low-cost production but should also present flexibility and adaptiveness to varying and dynamic conditions in their environment, including the presence of human beings; However, this presence of workers in the shared workspace with robots decreases the productivity as the robot is not aware about the human position and intention which leads to concerns about the human safety. This issue is addressed in this work by designing a reliable safety monitoring system for collaborative robots (Cobots). The main idea here is, to significantly enhance safety by a combination of recognition of human actions using visual perception and at the same time interpreting physical human-robot contact by tactile perception. Two datasets containing contact and vision data are collected by using different volunteers. The action recognition system classifies human actions using the skeleton representation of the latter when entering the shared workspace and the contact detection system distinguishes between intentional and incidental interactions if a physical contact between human and cobot takes place. Two different deep learning networks are used for human action recognition and contact detection which in combination, are expected to lead to the enhancement of human safety and an increase of the level of cobot perception about human intentions. The results show a promising path for future AI-driven solutions in safe and productive human–robot collaboration (HRC) in industrial automation.

Life on Earth evolved to accommodate the biochemical and biophysical boundary conditions of the planet millions of years ago. The former includes nutrients, water, and ability to synthesize other needed chemicals. The latter include the 1 g gravity of the planet, radiation, and the geomagnetic field (GMF)of the planet. How complex life forms have accommodated the GMF is not known in detail considering that Homo sapiens evolved a neuro system and a cardiovascular system that develops electromagnetic fields as part of their functioning. In addition, many proteins and physiologic processes utilize Fe ions, an ion that exhibits magnetic properties. Thus, complex organisms such as current humans generate magnetic fields, contain significant quantities of the Fe ion, and also respond to exogenous-supplied static and electromagnetic fields. Whether humans can store information in self-generated magnetic fields remains to be determined. Given the current body of literature, it remains somewhat unclear how Homo sapiens use exogenous magnetic fields to regulate function, and what can happen if the boundary condition of the GMF of Earth is no longer exerting an effect. Proposed deep space flights to destinations such as Mars will provide some insights as space flight could not have been anticipated by evolution. The results of such space flight “experiments” will provide new insights in the role of magnetic fields on human functioning. The outcomes may also have implications for those on Earth as magnetic field influences may play a role in developmental conditions such as autism and senescence-associated conditions such as dementia when integration of the biological and biophysical aspects of humans of humans are required for effective functioning. This review will discuss the involvement of magnetic fields on various normal and disturbed processes in humans while on Earth and then further discuss potential outcomes when the GMF is no longer available to impact host systems. Thus, the GMF of the Earth has been present throughout evolution but details of its role in human functions still remain to be elucidated.

Pluripotent stem cells (PSCs) hold many potential research and clinical benefits due to their ability to differentiate into nearly every cell type in the body. They are often used as model systems for early stages of ontogenesis to better understand key developmental pathways, and for drug screening. However, in order to fully realise the potential of PSCs and their translational applications, a deeper understanding of developmental pathways, especially in humans, is required. Several signalling molecules play important roles during development and are required for proper differentiation of PSCs. The concentration and timing of signal activation is important, with perturbations resulting in improper development and/or pathology. Bone morphogenetic protein (BMP) is one such key signalling molecule involved in the specification and differentiation of various cell types and tissues in the human body including tooth and otic development. In this review, we describe the role of BMP signalling and its regulation, the consequences of BMP dysregulation in disease and differentiation, and how PSCs can be used to investigate the effects of BMP modulation during development, mainly focusing on otic development. Finally, we emphasise the unique role of BMP4 in otic specification and how refined knowledge in controlling its regulation could lead to the generation of more robust and reproducible human PSC-derived otic organoids for research and translational applications.

Fortified human milk is the first choice for preterm infants. Although individualized fortification is recommended, the optimal method for this population remains uncertain. We conducted a comparative study assessing the growth effects of adjusted (AF) and targeted fortification (TF) in extremely low birth weight (ELBW) infants. This single-center, randomized, controlled clinical trial was conducted at a tertiary neonatal unit in Spain. Eligible participants were premature infants with a birthweight <1000g exclusively fed with human milk. A total of 38 patients were enrolled, 15 of them randomised to AF group and 23 to TF group. AF was based on BUN concentration and TF on human milk analysis. The primary outcome was weight gain velocity (g/kg/day).No significant differences were found in weight gain velocity at 28 days, at 36 weeks of postmenstrual age, at discharge nor during intervention. Protein intake was significantly higher in AF group (5.02 g/kg/day vs 4.48 g/kg/day, p= 0.001). No differences were found in lipids, carbohydrates and energy intake; neither in weight z score change between the different time points; nor in length and head circumference growth. Both AF and TF are comparable methods of fortification and provide appropriate growth rate in ELBW infants.

Artificial intelligence’s rapid advancement has enabled various applications, including intelligent video surveillance systems, assisted living, and human-computer interaction. These applications often require one core task: video-based human action recognition. Research in human video-based human action recognition is vast and ongoing, making it difficult to assess the full scope of available methods and current trends. This survey provides an in-depth exploration of the vision-based human action recognition field, comprehensively offering the available techniques and their evolution, highlighting the cutting-edge ideas driving its development. We also analyze the most used keywords in research papers over the past years to identify trends and predict possible future directions. Hence, this concise survey helps researchers understand the breadth of existing approaches, evaluate current research trends, and stay up-to-date on potential developments.

The neuroglial extracellular matrix (ECM) provides critical support and physiological cues for the proper growth, differentiation, and function of neuronal cells in the brain. However, in most in vitro settings that study neural physiology, cells are grown as monolayers on stiff surfaces that maximize adhesion and proliferation, and therefore lack the physiological cues that ECM in native neuronal tissues provides. Macromolecular crowding (MMC) is a biophysical phenomenon based on the principle of excluded volume that can be harnessed to induce native ECM deposition by cells in culture. Here, we show that MMC using two species of Ficoll with vitamin C supplementation significantly boosts deposition of relevant brain ECM by cultured human astrocytes. Dopaminergic neurons co-cultured on this astrocyte-ECM bed prepared under MMC treatment showed longer and denser neuronal extensions, a higher number of pre ad post synaptic contacts, and increased physiological activity as evidenced by higher frequency calcium oscillation, compared to standard co-culture conditions. When the pharmacological activity of various compounds was tested on MMC-treated co-cultures, their responses were enhanced, and for apomorphine, a D2-receptor agonist, it was inverted in comparison to control cell culture conditions, thus emulating responses observed in in vivo settings. These results indicate that macromolecular crowding can harness the ECM-building potential of human astrocytes in vitro forming an ultra-flat 3D microenvironment that makes neural cultures more physiological and pharmacological relevant.

We assessed how close human perceptions of landscape modification matched a multivariate index based on remotely sensed data of the same locations. Using a Human Footprint (HF) map of the continental U.S. (scaled 0-100), we created three series of aerial images, each with ten images distributed evenly across the 10 deciles of HF score. Using a web-based survey, 290 members of the global public ranked the images in one series based on their perception of the degree of human modification. Respondents also reported age, sex, and country. The degree of correspondence between rankings by respondents and by HF score was high, an average of 1.29 units of difference out of a maximum possible of 5.0. Differences among respondents were not explained by age, sex, or general geographic location. These results suggest that human perception of relative landscape modification conforms closely with the relative ranking made by a multivariate, analytical index.

The process of managing people in an organised way to assist a company in achieving its goals is known as human resources management. an increase in workplace stress, which is detrimental to an employee's health and well-being as well as the performance of the organisation. Certain guiding concepts and precepts are evergreen and can support the development of human resources while ensuring the wellbeing of the individual and the company. In this study, we examine how the methods and practices of yoga might benefit public organisations by lowering employee stress levels and boosting their altruism and greedlessness.

The pervasive use of plastic for milk packaging has raised significant health concerns, despite its advantages in terms of cost-effectiveness, convenience, and durability. The potential correlation between cancer and plastic packaging is one of these concerns. This mini-review examines the health implications of plastic materials used in milk packaging, with a particular emphasis on their carcinogenic hazards. This work endeavors to summarize the current state of knowledge regarding the influence of plastic components on human health and underscore the importance of ongoing research in this field by utilizing insights from a comprehensive review article. Harmful chemicals have been observed to leach into milk from plastics used in milk packaging, including high-density polyethylene (HDPE), low-density polyethylene (LDPE), and polyethylene terephthalate (PET), particularly under conditions of protracted storage and heat. Bisphenol A (BPA), phthalates, and styrene are among the most prevalent leachates. These chemicals have been associated with a variety of health issues, such as an elevated risk of cancer, and are recognized for their endocrine-disrupting properties. BPA and phthalates, in particular, have the potential to disrupt hormone function, which may result in breast cancer, prostate cancer, and other hormone-related malignancies.This review emphasizes the significance of comprehending the precise components of plastics utilized in milk packaging and their potential health consequences. It advocates for more rigorous research to completely elucidate the long-term health impacts of these materials by emphasizing the current state of knowledge and regulatory initiatives. Additionally, it underscores the necessity of innovative packaging technologies to guarantee consumer protection and mitigate the risk of exposure to carcinogenic substances.

This study is dedicated to the economic valuation of human capital in the regions where the Indigenous peoples of Kamchatka reside. The entire Kamchatksky Krai is considered an Indigenous people's ancestral territory. However, in this study, only municipalities whose population is more than one-third Indigenous were chosen for the assessment. This includes six municipal districts and one urban district (Aleytsky, Bystrinsky, Karaginsky, Olyutorsky, Penzhinsky, Tigilsky municipal districts and Palana urban district). The study employs statistical analysis and integrated, situational approaches: the investment approach was deemed the most appropriate tool for the economic assessment of human capital in Indigenous territories. The document analysis was based on a content analysis of open-access government documents and included legal acts, resolutions, orders, and other documents issued by federal, regional, and local authorities and pertaining to the economic activities of Kamchatka Indigenous peoples. Based on proposed calculation algorithm the assessed combined monetized value of human capital for the Kamchatka territories with large Indigenous populations at 38.8 billion rubles (approximately 520 million U.S. dollars) in 2021. It was observed that the growth of human capital in the Indigenous areas of Kamchatka between the years 2017 and 2021. The mean regional value of human capital per capita increased by more than twofold over this period. The accurate and precise assessment of human capital in the Kamchatka Indigenous homelands is provides baseline information necessary for the decision-making about economic development and sustainable development policies, and the approach proposed in this paper can be utilized by the Indigenous communities worldwide.

Abstract: Obesity and overweight also increasingly affect women of childbearing age and pregnant women. In maternal obesity, the activation of metabolic, inflammatory, and oxidative stress pathways is proven, which appears to be a key step in placental and uterus function pathological changes. Several recent studies have evidenced that aquaporins (AQPs) are critical players in adipose tissue biology and are involved in the onset of obesity. Our studies aimed to investigate the changes in placental volume and vascularization and measure the AQP5 expression and total antioxidant capacity (TAC) in the placenta and uterus tissues in obese and normal-weight mothers. We also aim to measure the AQP5 plasma concentration. We found AQP5 dominance in the uterus and plasma at 34 weeks of normal pregnancy. The placental volume increased, and the vascularization decreased in obese mothers compared to the control. The AQP5 expression increased in the uterus of the obese group and did not change in the placenta. The TAC decreased in the plasma of overweight mothers. We hypothesize that increased AQP5 expression prolongs the length of pregnancy and inhibits the onset of contractions. Based on our findings, we can develop diagnostic tests and provide new targets for tocolytic drug development.

Wetlands play a crucial role not only in providing ecological services but also in enriching the cultural and spiritual life of human society. Despite this, their cultural values have often been overlooked. The formal recognition of cultural values began with the Ramsar Convention in the 1970s, which acknowledged wetlands as resources of great economic, cultural, scientific, and recreational value. The wetlands of Majuli are of profound cultural and socio-cultural importance, particularly in terms of religious and spiritual significance, as well as recreational value. This study examines the cultural services provided by the wetland ecosystem of Majuli, focusing on its significance in the local human-environment nexus. Utilizing a qualitative approach with quantitative aspects, data was collected from primary sources through observation, interviews, and group discussions, along with secondary sources such as books, journals, and web portals.

Paracetamol, also known as acetaminophen, is one of the most widely used over-the-counter analgesics and antipyretics globally. While generally considered safe when used as directed, excessive or prolonged use of paracetamol can lead to adverse effects on various organ systems within the human body. This comprehensive review explores the physiological mechanisms underlying paracetamol toxicity, its effects on different organs, risk factors for overdose, diagnostic methods, and potential management strategies.

Shrews (Soricidae) are common small wild mammals with a significant overlap in their habitats with humans and domestic animals. Currently, viruses from 24 families have been identified in shrews, including Adenoviridae, Arenaviridae, Arteriviridae, Astroviridae, Bornaviridae, Caliciviridae, Circoviridae, Coronaviridae, Filoviridae, Flaviviridae, Hantaviridae, Hepadnaviridae, Hepeviridae, Nairoviridae, Orthoherpesviridae, Paramyxoviridae, Parvoviridae, Phenuiviridae, Picornaviridae, Polyomaviridae, Poxviridae, Rhabdoviridae, Sedoreoviridae, and Spinareoviridae, which pose potential threats to humans and domestic animals. This review compiled fundamental information about shrews and provided a comprehensive summary of the viruses that have been detected in shrews, with the aim to facilitating a deeper understanding of shrews and the diversity and risks of their viruses for researchers and the general public.

Abattoir workers are liable to zoonotic infections from animals and animal products, pri-marily to diseases with asymptomatic and chronic clinical manifestations in animals such as brucellosis. No published reports exist on the seroprevalence of brucellosis in abattoir workers in South Africa. Therefore, this cross-sectional study was conducted to estimate the occurrence and risk factors for Brucella exposure in abattoir workers in Gauteng Province. A total of 103 abattoir workers and managers from six abattoirs, where brucellosis-positive slaughtered cattle and sheep were previously detected, were interviewed, and tested with serological assays using the Rose Bengal test (RBT), BrucellaCapt, and IgG-ELISA. A pre-tested questionnaire was administered to consenting respondents to obtain infor-mation on risk factors for brucellosis. Of the 103 respondents tested, the distribution of fe-male and male workers was 16 (15.5%) and 87 (84.5%), respectively. The seroprevalence for exposure to brucellosis was 21/103 (20.4%, 95%CI: 13.1-29.5) using a combination of RBT, BrucellaCapt, or IgG-ELISA. For test-specific results, seroprevalences by RBT, BrucellaCapt, and IgG-ELISA were 13/103 (12.6%, 95%CI: 6.9-20.6), 9/103 (8.74%, 95%CI: 4.1-15.9) and 18/103 (17.5%, 95%CI: 10.7-26.2), respectively. Low-throughput abattoirs were identified as associated risk as 29.3% of workers were seropositive compared to 12.7% of workers in high-throughput abattoirs, which highlights that direct contact at abattoirs poses higher risk to workers than indirect and direct contact outside abattoirs. This study confirmed the occurrence of Brucella spp. antibodies among abattoir workers in South Africa, possibly due to occupational exposure to Brucella spp. and highlight the occupational hazard to workers. Furthermore, findings underscore that abattoir facilities can serve as points for active and passive surveillance for indicators of diseases of public health importance. We recommend periodic implementation of brucellosis testing of abattoir workers country-wide to establish baseline data for informing appropriate preventive practices and reduce the potential burden of infection rate among these high-risk workers.

Human longevity is an important but difficult goal due to the extreme complication of human body. If people could repeatedly transfer their consciousness from old bodies to new ones, their lifespan might be prolonged extremely. However, there are several difficulties which prevent the achievement of such a technique. In this paper, we propose an approach that can transfer human consciousness indirectly, and avoid or significantly relieve those difficulties. The strategy of our approach is to integrate the consciousnesses of two bodies (old and new) into a unique consciousness. By doing so, the consciousness is extended to the new body. After that, the consciousness shrinks and remains in the new body when the old body dies. This may also apply to integrating more than two bodies of human, or animal, or even across different species. After investigating thousands of literatures, we find quite strong evidence (related discoveries and technologies) that can support the proposed approach and its advantages. Beside prolonging human lifespan, the approach could also have other meaningful applications.

Leber’s hereditary optic neuropathy (LHON) is a common mitochondrial genetic disease, causing irreversible blindness in young individuals. Current treatments are inadequate, and there is no definitive cure. This study evaluates the effectiveness of delivering wildtype human NADH ubiquinone oxidoreductase subunit 4 (hND4) gene using mito-targeted AAV(MTSAAV) to rescue LHOH mice. We observed declining pattern electroretinograms amplitudes as mice aged across all groups (P&lt; 0.001), with significant differences among groups (P = 0.023, Control vs. LHON, P = 0.008; Control vs. Rescue, P = 0.228). Inner retinal thickness and intraocular pressure do not change significantly with age or groups. Compared to LHON mice, those rescued with wildtype hND4 exhibit improved retinal visual acuity (0.29± 0.1 cy/deg vs.0.15 ± 0.1 cy/deg) and increased functional hyperemia response (effect of flicker, P&lt;0.001, effect of Group, P=0.004; Interaction Flicker x Group, P&lt;0.001). Postmortem analysis shows a marked reduction in retinal ganglion cell density in the LHON group compared to the other groups (Effect of Group, P&lt;0.001, Control vs. LHON, P&lt;0.001, Control vs. Rescue, P=0.106). These results suggest that MTSAAV-delivered wildtype hND4 gene rescues, at least in part, visual impairment in an LHON mouse model and has the therapeutic potential to treat this disease.

Background. In the central-eastern region of the Mediterranean island of Sardinia more than two decades ago, a mountain area was identified where the population displays exceptional longevity, especially among men (the longevity Blue Zone, LBZ). This community was thoroughly investigated seeking to understand the underlying factors of this phenomenon. In the present study, 11 genetic markers previously associated with longevity in several long-lived populations were analyzed. Methods. APOE (rs429358 and rs7412), APOE promoter (rs449647, rs769446, and rs405509), ACE1 (rs1799752), IL6 ‒174G/C (rs1800795), TNFα ‒308G/A (rs1800629), FOXO3A (rs2802292), KLOTHO (rs9536314) and G6PD (c.563C→T) were investigated. PCR-based genotyping was performed following genomic DNA extraction from 150 nonagenarians living in the LBZ and 150 controls from a nearby area. Results. No significant deviation of the frequency of the analyzed markers was detected between the two groups except a weak association with the –174G&gt;C gene variant of the IL-6 gene (p=0.040), a major modulator of the inflammatory response. Conclusions. The findings of this study do not support a significant association of known genetic variants on survival in the population of the Sardinian LBZ. Other genetic or epigenetic traits might play a role not yet identified.

Convolution, recurrent and attention-based deep learning techniques have produced the most recent state-of-the-art results in multiple sensor-based human activity recognition (HAR) datasets. However, these techniques have high computing costs, restricting their use in low-powered devices. Different methods have been employed to increase the efficiency of these techniques; however, this often results in worse performance. Recently, pure MLP architectures have demonstrated competitive performance in vision-based tasks with lower computation costs than other deep-learning techniques. The MLP-Mixer is a pioneering pure MLP architecture that produces competitive results with state-of-the-art models in computer vision tasks. This paper shows the viability of the MLP-Mixer in sensor-based HAR. Furthermore, experiments are performed to gain insight into the Mixer modules essential for HAR, and a visual analysis of the Mixer’s weights is provided, validating the Mixer’s learning capabilities. As a result, the Mixer achieves an F1 score of 97%, 84.2%, 91.2% and 90% on the PAMAP2, Daphnet Gait, Opportunity Gestures and Opportunity Locomotion datasets, respectively, outperforming state-of-the-art models in all datasets except Opportunity Gestures.

Aortic dissection is a clinicopathological entity caused by rupture of the intima leading to a high mortality if not treated. Over time, diagnostic and investigative methods, antihypertensive therapy, and early referrals have resulted in improving outcomes according to registry data. Some data has also emerged from recent studies suggesting a link between Human Cytomegalovirus (HCMV) infection and aortic dissection. Furthermore, the use of microRNAs have also become increasingly widespread in the literature. These have been noted to play a role in aortic dissections with elevated levels noted in studies as early as 2017. This review aims to provide a broad and holistic overview of the role of miRNAs, while studying the role of HCMV infection in the context of aortic dissections. The role of long non-coding RNAs, circular RNAs and microRNAs are explored to identify changes in expression during aortic dissections. The use of such biomarkers may one day be translated into clinical practice to allow early detection and prognostication of outcomes and drive preventative and therapeutic options in the future.

The Necessity of Human resources beyond perception of human understanding towards the Evaluation of video quality or Data screening methodology is conducted based on human perception level since it is concerned with how visual content is perceived by a observer based on observations with his/ her perception on a particular video sequence. Therefore, we considered that the subject has to grade the encoded video sequences under certain test environment conditions based on ITU-Recommendations. Since Human perception is considered as the true judgment and precise measurement of visual content, data screening has became quite essential and quite comfortable to general public due to introduction of User Experience(UX) concept by User Experience community. The translations of A recurrent neural network is based on certain principles, for instance we considered natural language processing which is certainly adaptable towards understanding sequential data and use patterns to predict the consistency within observers. In our research, we adapted principles based on Recurrent Neural Networks while assuming consistency within observers for predicting video quality within data screening environment towards subjective experiments. Moreover,this research work explores the trade offs between Human perception on visual content and consistency of observations within individual observer.

Objective: This study aimed to validate the use of liquid phenol-based chemical peeling therapy for cervico-vaginal intraepithelial neoplasia (CIN and VaIN), with the goal of circumventing obstetric complications associated with surgical treatment. Methods: A total of 483 eligible women diagnosed with CIN and/or VaIN participated in this study. Participants underwent phenol-based chemical peeling therapy every 4 weeks until disease clearance. Disease clearance was determined by negative Pap tests for four consecutive weeks. HPV genotyping was conducted at the onset of the study and after disease clearance in select cases. Results: Among the 476 participants (excluding those with cancer), the number of treatment sessions until CIN/VaIN clearance ranged from 2 to 49 (median = 7 sessions). Forty-five participants (9.4%) underwent surgical treatments. Seven participants (1.5%) experienced recurrence, presenting with CIN2/VaIN2 or worse lesions; of these, three underwent LEEP, while four repeated the chemical peeling therapy. No obstetrical complications were noted among the 98 pregnancies following this therapy. The findings suggest that phenol-based therapy is safe and effective for CIN, although it requires numerous and lengthy treatments. Factors associated with resistance to this therapy include immune suppression, high-grade lesions, multiple HPV type infection, and direct or passive smoking.

Fruits, vegetables, and spices are natural sources of bioactive phytochemicals such as polyphenols, carotenoids, flavonoids, curcuminoids, terpenoids, and capsaicinoids, possessing multiple health benefits and relatively low toxicity. These compounds found in the diet play a central role in organism development and fitness. Given the complexity of the whole-body response to dietary changes, invertebrate model organisms can serve as valuable tools to examine the interplay between genes, signaling pathways, and metabolism. Drosophila melanogaster, an invertebrate model with its extensively studied genome, has more than 70% gene homology to humans and has been used as a model system in biological studies for a long time. The notable advantages of Drosophila as a model system, such as their low maintenance cost, high reproductive rate, short generation time and lifespan, and the high similarity of metabolic pathways between Drosophila and mammals, have encouraged the use of Drosophila in the context of screening and evaluating the impact of phytochemicals present in the diet. In this chapter, we summarize and review the benefits of Drosophila as a model system for use in the study of phytochemical ingestion and describe the previously reported effects of phytochemical consumption in Drosophila.

The high incidence of psychopathologies recorded in today's human society, correlated with the high percentages of biodiversity loss, point to the need for an interdisciplinary approach of the scientific fields under study – Neurosciences and Biodiversity Conservation. Thus, our approach here pre-sents, in a synergistic manner, the significant correlation between mental health and the increased values of biodiversity in the ecosystems located in the immediate vicinity, especially those located in the middle of cities. Our approach aims to emphasize the importance of biodiversity conservation in the context of preserving mental health and general well-being. There are a series of recent ex-perimental demonstrations that outline the influence of natural elements on the human psyche and implicitly the effects of nature in the prevention and reduction of stress, anxiety and depression. And beyond the cognitive barriers of humanity in relating to the surrounding biodiversity must lie the desire to know the values of biodiversity and the absolute importance of its conservation. The sustainable relationship between man and living nature, seen as a complex of biodiversity, is dealt with by a branch of science called Human Ecology. Therefore, this study emphasizes the crucial need to know and respect the connection between man and nature, based, since time immemorial, on biophilia. And with the regression of ignorance and the correlated approach of several scientific fields, some at the intersection of humanities and natural sciences, one can observe the progress of preserving the dynamic balance within the ecosystems and implicitly the preservation of mental health and human well-being.