Human Life Research Articles

Evaluation of different evaluation methods for selection of a conceptual design

Designing plays an important part in the production of an artifact, as it is the mental creation before the product becomes a reality. It also plays an interesting engineering activity that affects almost all areas of human life and uses the laws and insights of science. After the various design concepts have been successfully carried out, the evaluation stage becomes crucial in the selection of the best solution. A thorough study of the literature suggests that not too many works have been done on evaluating different evaluation methods in selecting a concept. The objective of this study was to evaluate four design concept evaluation methods for selecting a car hitch. The study found that for a robust selection of solutions, Verein Deutscher Ingenieure (VDI) guidelines and Technical Economic Evaluations were more appropriate to be used.

Promoting high health, safety, and environmental standards during subsea operations

Subsea operations play a vital role in various industries, including oil and gas, renewable energy, and telecommunications. However, these operations come with inherent risks to human lives, the environment, and operational integrity. This abstract presents a comprehensive approach to promoting high health, safety, and environmental (HSE) standards during subsea operations. The importance of adhering to HSE standards cannot be overstated, as they serve as a safeguard against potential accidents, environmental damage, and reputational harm. This paper outlines the regulatory framework and industry standards governing subsea operations, emphasizing the necessity of compliance and the consequences of non-compliance. Risk assessment and management are essential components of ensuring safety in subsea operations. Strategies for identifying, assessing, and mitigating risks are discussed, alongside the importance of continuous improvement through training and competency development. Furthermore, technology and innovation play a crucial role in enhancing safety and efficiency in subsea operations. From remote monitoring systems to autonomous vehicles, advancements in technology offer new opportunities to minimize risks and improve operational performance. Collaboration among stakeholders, including industry players, government agencies, and research institutions, is essential for driving progress in HSE standards. Effective communication and information sharing facilitate the exchange of best practices and lessons learned, fostering a culture of continuous improvement. In conclusion, prioritizing high HSE standards in subsea operations is paramount for sustainable and responsible development. By embracing collaboration, innovation, and continuous improvement, stakeholders can collectively ensure the safety of personnel, protect the environment, and uphold operational integrity in subsea operations.

Mild endoplasmic reticulum stress alleviates FB1-triggered intestinal pyroptosis via the Sec62-PERK pathway

Fumonisin B1 (FB1), a water-soluble mycotoxin released by Fusarium moniliforme Sheld, is widely present in corn and its derivative products, and seriously endangers human life and health. Recent studies have reported that FB1 can lead to pyroptosis, however, the mechanisms by which FB1-induced pyroptosis remain indistinct. In the present study, we aim to investigate the mechanisms of pyroptosis in intestinal porcine epithelial cells (IPEC-J2) and the relationship between FB1-induced endoplasmic reticulum stress (ERS) and pyroptosis. Our experimental results showed that the pyroptosis protein indicators in IPEC-J2 were significantly increased after exposure to FB1. The ERS markers, including glucose-regulated Protein 78 (GRP78), PKR-like ER kinase protein (PERK), and preprotein translocation factor (Sec62) were also significantly increased. Using small interfering RNA silencing of PERK or Sec62, the results demonstrated that upregulation of Sec62 activates the PERK pathway, and activation of the PERK signaling pathway is upstream of FB1-induced pyroptosis. After using the ERS inhibitor 4-PBA reduced the FB1-triggered intestinal injury by the Sec62-PERK pathway. In conclusion, we found that FB1 induced pyroptosis by upregulating Sec62 to activate the PERK pathway, and mild ERS alleviates FB1-triggered damage. It all boils down to one fact, the study provides a new perspective for further, and improving the toxicological mechanism of FB1.Graphical

A Comparison of Human Life in Christian and Chinese Buddhist Bioethics

Bioethics provides a new perspective for the comparative study of Christianity and Chinese Buddhism. This paper provides a comprehensive comparison of the sources, states of existence, and fundamental principles and purposes of the Christian and Chinese Buddhist perspectives on human life, focusing specifically on the realm of bioethics. It places special emphasis on teachings about God’s creation and dependent origination, original sin and Buddhist causality, as well as love and compassion. Despite the significant geographic distance between Christianity and Chinese Buddhism, the dialogue highlights potential cultural differences and interpretations. It also demonstrates mutual acceptance and the process of redefining one’s own identity. Religious bioethics greatly benefits from a comprehensive study of various religions from around the world. It aims to encourage cross-cultural and interdisciplinary research on different religions globally. It promotes religious bioethics as a relevant field of study.

Why religion and spirituality are important in human biological research.

The study of human biology includes exploration of all the genetic and environmental influences on human variation and life history, including impacts of sociocultural and physical environments. Religious practice and spirituality may be one of these influences. There are more than 5.8 billion religiously affiliated adults and children, accounting for 84% of the world's 6.9 billion people. Furthermore, 70% of Americans consider themselves spiritual in some way, including 22% who do not consider themselves religious, and the numbers for Europe are lower but proportionally similar. Such a high rate of religious affiliation and spiritual belief suggests that religion and spirituality could be sociocultural influences on human variation, but human biologists have scarcely attended to their impacts, as indicated by the limited numbers of relevant articles in the two flagship human biology journals. In this article, we discuss why human biologists may have overlooked this important force for human variability and highlight foundational work from human biology and other disciplines that can give our colleagues directions forward. We review the impacts of religion and spirituality at population and individual levels and call for human biologists to attend to the many aspects of religion and spirituality that can impact human biology and are much more than simply influences of denominational affiliation.

Corrosion Characterization of Engine Connecting Rods Using Fringe Projection Profilometry and Unsupervised Machine Learning

Abstract The consequences associated with corrosion, a global industrial peril, cost an estimated $ 2.5 trillion annually to inspect, rectify, and prevent. In addition to significant economic losses, corrosion-induced failure of critical components in transport systems, like automobiles, may also lead to loss of human life. Hence, it is essential to eradicate corrosion in its early stages. The most vital automobile component is its engine, whose failure can cause fatal accidents. Regular quality inspection and maintenance by skilled personnel is essential to prevent this. Automating this task will address this domain's personnel shortage while mitigating the risk of human error. To enable the performance of this task without the need for human intervention, we determine the morphological parameters affected by corrosion in automotive engine components, namely connecting rods, using Fringe Projection Profilometry (FPP), a high-speed 3D profiling technique capable of achieving sub-millimeter accuracy. We then perform classification using k-means clustering into low, medium, and high corrosion bands, based on the parameters obtained from 3D imaging. The model was able to achieve a high accuracy of 88.57%. The accuracy was determined by considering the visual classification performed by a Material Science Expert as the ground truth.

Ti3C2 Nanosheets Functionalized with Ferritin–Biomimetic Platinum Nanoparticles for Electrochemical Biosensors of Nitrite

Nitrites widely exist in human life and the natural environment, but excessive contents of nitrites will result in adverse effects on the environment and human health; hence, sensitive and stable nitrite detection systems are needed. In this study, we report the synthesis of Ti3C2 nanosheets functionalized with apoferritin (ApoF)–biomimetic platinum (Pt) nanoparticle (Pt@ApoF/Ti3C2) composite materials, which were formed by using ApoF as a template and protein-inspired biomineralization. The formed nanohybrid exhibits excellent electrochemical sensing performance towards nitrite (NaNO2). Specifically, the Pt@ApoF catalyzes the conversion of nitrites into nitrates, converting the chemical signal into an electrical signal. The prepared Pt@ApoF/Ti3C2-based electrochemical NaNO2 biosensors demonstrate a wide detection range of 0.001–9 mM with a low detection limit of 0.425 μM. Additionally, the biosensors possess high selectivity and sensitivity while maintaining a relatively stable electrochemical sensing performance within 7 days, enabling the monitoring of NaNO2 in complex environments. The successful preparation of the Pt@ApoF/Ti3C2 nanohybrid materials provides a new approach for constructing efficient electrochemical biosensors, offering a simple and rapid method for detecting NaNO2 in complex environments.

The use of Instagram to improve students' EFL Writing

Good communication makes it easier for us to connect with the community and other individuals with various backgrounds. Language is also a catalyst for us to understand ourselves and others, and is the key that opens the window of our world’s view. Every aspect on human life is very dependent on the proficiency of language skills. The goal of this paper was to see how the use of Instagram improved the students’ EFL writing ability. The method used to conduct this paper was Systematic Literature Review. There are 10 articles from various journals that are analyzed and synthetized to extract the data from. Based on the authors finding, the use of Instagram brought forth positive improvement on the students’ writing ability, as well as their motivation in language acquisition study.

Quality of Life and Geriatric Depression among Elderly Residents in Old Age Homes and Domestic Environments in Kerala.

Aging is a natural and essential part of human life. The Quality of Life (QoL) for the elders indicates their overall well-being and might be a risk factor for many conditions like geriatric depression. The study aims to compare older people living in domestic environments with those in Old Age Homes (OAH) to examine the variations in life quality and the prevalence of geriatric depression. The study followed a mixed-method approach and was conducted in two phases. Phase 1 includes a comprehensive understanding of QoL and geriatric depression that was established by an in-depth random data collection from 80 older adults aged between 60 and 90 years in Kerala, India, using the WHOQOL-BREF and Geriatric Depression Scale (GDS). Data was then analyzed statistically by using an independent sample t-test, Karl Pearson's correlation, linear regression, and descriptive statistics. In Phase 2, by using semi-structured interviews, a random sample of eight people aged between 60 and 80 years was chosen from the Phase 1 pool which involved comparing and identifying the factors influencing geriatric depression and QoL in both living situations using thematic analysis. The findings show that there is a significant negative relationship between quality of life and geriatric depression among older individuals. The elders in old age homes reported a higher quality of life and lower geriatric depression. There were negligible gender differences. Physical, psychological, social, and environmental factors affect the quality of life and geriatric depression. The study also reveals that old age homes provide a better environment for elderly care compared to domestic environments, as they provide enhanced social support, structured caregiving, and better access to healthcare. This study thus paves the way for more compassionate approaches to elderly care and well-being.

Application of Game Theory in Solving Urban Water Challenges in Ibadan-North Local Government Area, Oyo State, Nigeria

The significance of water in human life cannot be ignored, but in most of the developing countries; availability, provision and access to good water source to the citizens has post major challenges. The nature of water scarcity has been majorly attributed to seasonal factor and high population pressure. This study therefore aimed at developing a practical approach and mechanism to solving water challenges in urban areas in Nigeria by means of game theory. The findings revealed that majority of respondents lack access to portable or drinkable water from water agency and that regular water supply sources have been traced to be borehole or well which was provided by citizens in the community at a cost. Applying the game theory approach, the outcome of the game indicates that the equilibrium value for the two players (the water agency and the residents) is N2,000 for 1,000 liters of water supply monthly. However, the payoff can be maiximised by every player (monetary values for the water agency and satisfactory water consumption for the residents). It is therefore importance that water agency should improve in the quality of their work in providing adequate water supply to the community to reduce or eradicate ailment arises from non availability of quality water.

Power relations in the novel My Name is Alam by Leila S. Chudori

Exploring discursive formations in literary works allows researchers to analyze how language and discourse shape meaning, power dynamics, and cultural ideologies within a specific literary context. Understanding the discursive formations in literary works is crucial for comprehending the historical and social context in which these works were produced. This research aims to describe the forms and representations of power relations in the novel My Name is Alam by Leila S. Chudori. This is qualitative descriptive research where the data is interpreted using the genealogical and archaeological analysis methods promoted by Foucault. This method aims to uncover and understand hidden power dynamics in various aspects of human life. The research results prove that the author's statements were spread across various formations and became material for discussion. Two forms of power relations are being discussed; the first is the New Order government's practice of authoritarian power in its various policies, which limits human rights. Second, there is resistance from marginalized groups, namely political prisoners and their families. This form of resistance is an effort by marginalized groups to fight for equality and justice. The New Order government in Indonesia constructed a discourse to create a simulated space to legitimize its power within national memory politics. This simulated world is a blend of reality and fantasy constantly reproduced. As a result, the actual reality becomes obscured, and the symbols created are perceived as reality.

Harnessing LSTM and XGBoost algorithms for storm prediction

Storms can cause significant damage, severe social disturbance and loss of human life, but predicting them is challenging due to their infrequent occurrence. To overcome this problem, a novel deep learning and machine learning approach based on long short-term memory (LSTM) and Extreme Gradient Boosting (XGBoost) was applied to predict storm characteristics and occurrence in Western France. A combination of data from buoys and a storm database between 1996 and 2020 was processed for model training and testing. The models were trained and validated with the dataset from January 1996 to December 2015 and the trained models were then used to predict storm characteristics and occurrence from January 2016 to December 2020. The LSTM model used to predict storm characteristics showed great accuracy in forecasting temperature and pressure, with challenges observed in capturing extreme values for wave height and wind speed. The trained XGBoost model, on the other hand, performed extremely well in predicting storm occurrence. The methodology adopted can help reduce the impact of storms on humans and objects.

DATFNets-dynamic adaptive assigned transformer network for fire detection

AbstractFires cause severe damage to the ecological environment and threaten human life and property. Although the traditional convolutional neural network method effectively detects large-area fires, it cannot capture small fires in complex areas through a limited receptive field. At the same time, fires can change at any time due to the influence of wind direction, which challenges fire prevention and control personnel. To solve these problems, a novel dynamic adaptive distribution transformer detection framework is proposed to help firefighters and researchers develop optimal fire management strategies. On the one hand, this framework embeds a context aggregation layer with a masking strategy in the feature extractor to improve the representation of low-level and salient features. The masking strategy can reduce irrelevant information and improve network generalization. On the other hand, designed a dynamic adaptive direction conversion function and sample allocation strategy to fully use adaptive point representation while achieving accurate positioning and classification of fires and screening out representative fire samples in complex backgrounds. In addition, to prevent the network from being limited to the local optimum and discrete points in the sample from causing severe interference to the overall performance, designed a weighted loss function with spatial constraints to optimize the network and penalize the discrete points in the sample. The mAP in the three baseline data sets of FireDets, WildFurgFires, and FireAndSmokes are 0.871, 0.909, and 0.955, respectively. The experimental results are significantly better than other detection methods, which proves that the proposed method has good robustness and detection performance.

Personalized Stress Detection Using Biosignals from Wearables: A Scoping Review

Stress is a natural yet potentially harmful aspect of human life, necessitating effective management, particularly during overwhelming experiences. This paper presents a scoping review of personalized stress detection models using wearable technology. Employing the PRISMA-ScR framework for rigorous methodological structuring, we systematically analyzed literature from key databases including Scopus, IEEE Xplore, and PubMed. Our focus was on biosignals, AI methodologies, datasets, wearable devices, and real-world implementation challenges. The review presents an overview of stress and its biological mechanisms, details the methodology for the literature search, and synthesizes the findings. It shows that biosignals, especially EDA and PPG, are frequently utilized for stress detection and demonstrate potential reliability in multimodal settings. Evidence for a trend towards deep learning models was found, although the limited comparison with traditional methods calls for further research. Concerns arise regarding the representativeness of datasets and practical challenges in deploying wearable technologies, which include issues related to data quality and privacy. Future research should aim to develop comprehensive datasets and explore AI techniques that are not only accurate but also computationally efficient and user-centric, thereby closing the gap between theoretical models and practical applications to improve the effectiveness of stress detection systems in real scenarios.

Predictive value of Cmmi-MHR combined with thromboelastography parameters in acute cerebral infarction.

Cerebral infarction is a common neurological disease with high rates of morbidity, mortality, and recurrence, posing a great threat to human life and health. Cerebral infarction is the second leading cause of death in the world and the leading cause of long-term disability in humans. The results of the third national retrospective sampling survey on causes of death in 2008 showed that cerebral infarction has become the leading cause of death in China and its mortality rate is 4-5 times that of European and American countries. Therefore, this article proposed a study on the predictive value of Cmmi-MHR combined with thromboelastography parameters that was performed for acute cerebral infarction. This paper mainly proposed a high frame rate imaging technology and analyzed its algorithm. In this article, in the experimental part, an in-depth analysis of the predictive value of the Monocyte-to-high-density lipoprotein cholesterol ratio (MHR) combined with thromboelastography parameters was performed for acute cerebral infarction. The final experimental results showed that HDL (OR = 1.695%, P-trend = 0.049) had a probability of death within 90days of hospitalization (OR = 0.81, 95% CI = 1.06-3.11, P-trend = 0.523). There were no significant differences in mortality rate after 90days. Regardless of adjusting for confounders such as age, gender, and NIHSS score, there was no significant difference in the risk of MHR or monocyte count within 90days of hospitalization. The conclusion indicates that the combination of Cmmi-MHR and thromboelastography parameters provides a new perspective and method for the diagnosis and treatment of cerebral infarction, and provides important support for personalized treatment and management of cerebral infarction.

Energy Expenditure in Humans: Principles, Methods, and Changes Throughout the Life Course.

Humans require energy to sustain their daily activities throughout their lives. This narrative review aims to (a) summarize principles and methods for studying human energy expenditure, (b) discuss the main determinants of energy expenditure, and (c) discuss the changes in energy expenditure throughout the human life course. Total daily energy expenditure is mainly composed of resting energy expenditure, physical activity energy expenditure, and the thermic effect of food. Total daily energy expenditure and its components are estimated using variations of the indirect calorimetry method. The relative contributions of organs and tissues determine the energy expenditure under different physiological conditions. Evidence shows that energy expenditure varies along the human life course, at least in part due to changes in body composition, the mass and specific metabolic rate of organs and tissues, and levels of physical activity. This information is crucial to estimate human energy requirements for maintaining health throughout the life course.

Multistakeholder Participation, Collaboration, and Networking in Disaster Risk Reduction and Pandemic Management: Insights and Future Policy Framework

The natural and manmade disasters impact a society with loss of assets and human lives. Disasters leavepeople in vulnerable conditions and an overall economic slowdown is observed. The impact of disasters is highly complex and multidimensional in nature. It becomes imperative to handle the complexity of issues with comprehensive approach. Managing disasters effectively is one of the important challenges any government faces when it tries to be prepared with appropriate mitigation, rescue, and relief strategies. The unexpected nature and urgency related to Disaster Risk Reduction makes it important and relevant to involvemultistakeholders. This will help to bring down the severity and impact of the disaster on human lives and losses. Disaster Risk Reductionrequires meticulous planning and sharing of the responsibility among multistakeholders through networking so as to bring down the severity and minimize the negative impact of a disaster. Many research studies have suggested the multistakeholder approach in addressing the disasters. There are several gaps such as inefficiency of vertical management to deal the issues, involvement of multiple stakeholders, and lack of local public supportfor disaster. This paper, considering the case of COVID-19 as a pandemic and disaster, discusses the importance of multistakeholder participation. The paper presents an extensive review of the papers on the relevance ofparticipation of multistakeholdersin Disaster Risk Reduction and explores the scope and challenges involved and suggests policies to address the disasters, which utilizes Multistakeholder Participation.

A STUDY ON ROLE OF LIFE INSURANCE CORPORATION OF INDIA WITH REFERENCE TO JEEVAN LAKSHYA POLICY

The most important aspect of human life is its uncertainty. In the modern industrialized era. Human life and property are inevitably exposed to different kinds and varying degrees of risks and uncertainties. Human beings to protect themselves and their property from total disaster. Resort intelligently to protection coverage extended by the insurance companies which act as a trustee to the amount collected through premiums and provide certainty in the place of uncertainty. This article reveals the awareness. About LIC JEEVAN LAKSH POLICY holders five point there are a number insurance companies and different policy are available now but the role of JEEVAN LAKSH POLICY influencing peoples has to be calculated In this highly competition environment JLP has to satisfy the customers to gain more than other insurance policy . So understanding the customer needs their problems will enable the JLP to design appropriate products determine price correctly and increase their profitability. Key words : LIC JEEVAN LAKSH POLICY Schemes

Determination of Public Goals in Times of Volatility and Complexity

Purpose: The purpose of this text is to critically analyse the traditional approach to the formulation and application of legal rules, arguing that they are outdated and insufficient for addressing the complexities anddynamics of modern society and technology.Design/Methodology/Approach: Employing a qualitative research methodology, the paper adopts a case study approach, focused mainly on the practices of the legislature in determining public goals. The analysis identifies themes and patterns related to different practices regarding the determination of public goals and their impact on the legislature. The findings are discussed in relation to the theoretical framework established both in the literature review and this paper. The paper concludes with a summary of the findings, practical implications, and suggestions for future research.Findings and Practical Implications: Although technology nowadays plays a central role in human life, legislative public goals are still determined statically, reflecting a traditional Newtonian mechanistic perspective grounded in the principle of causality. Looking ahead, the paper speculates on potential scenarios. It suggests that the balance between nature, technology, law, and humanity requires careful management to ensure a harmonious but flexible co-existence. In the realm of complex legal issues, certainly can, to some extent, be maintained through an array of innovative methods. These include results- and procedure-oriented approaches to interactions between individuals and collectives, a legal system informed by feedback mechanisms and thresholds, the use of collective intelligence, the anticipation of adverse scenarios, and the implementation of adaptable norms. Such methodologies are intrinsically better equipped to navigate the unpredictability and complexity of modern legal challenges than traditional legalistic frameworks.Originality: The paper integrates insights from various disciplines, including law, system theory, and technology studies. This interdisciplinary approach offers a more comprehensive understanding of the intricate interplaybetween nature, technology, and law, a perspective often neglected in more narrowly focused studies. The originality of the paper lies in challenging existing forms of regulation and proposing new regulatory approaches grounded in the evolving nature of facts and associated rights and obligations of individuals and groups.

A Review of quantum algorithms for prediction of hazardous asteroids

Quantum computing (QC) and quantum machine learning (QML), two emerging technologies, have the potential to completely change how we approach solving difficult problems in physics and astronomy, among other fields. Potentially Hazardous Asteroids (PHAs) can produce a variety of damaging phenomena that put biodiversity and human life at serious risk. Although PHAs have been identified through the use of machine learning (ML) techniques, the current approaches have reached a point of saturation, signaling the need for additional innovation. This paper provides an in-depth examination of various machine learning (ML) and QML techniques for precisely identifying potentially hazardous asteroids. The study attempts to provide information to improve the efficiency and accuracy of asteroid categorization by combining QML techniques like deep learning with a variety of machine learning (ML) algorithms, such as Random Forest and support vector machines. The study highlights weaknesses in existing approaches, including feature selection and model assessment, and suggests directions for further investigation. The results highlight the significance of developing QML techniques to increase the prediction of asteroid hazards, consequently supporting enhanced risk assessment and space exploration efforts. Paper reviews might not be related because the study only looks at generic paper reviews.