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Muhammad Jaffar Khan, Yasir Eltayeb, Arunabha Karmakar, Rohma Malik, Tarig Elsafi Department of Anesthesiology, Critical Care and Perioperative Medicine, Hamad Medical Corporation, Doha, QatarCorrespondence: Muhammad Jaffar Khan, Department of Anesthesiology, Critical Care and Perioperative Medicine, Hamad Medical Corporation, P.O. Box 3050, Doha, Qatar, Tel +97444394444, Email mkhan44@hamad.qaBackground: Patients diagnosed with Heart Failure with Reduced Ejection Fraction (HFrEF) are at high risk of perioperative cardiovascular complications. While it is important to focus on optimizing their cardiac function, it is also crucial to address and optimize any other modifiable risk factors that could potentially impact postoperative outcome. This also includes careful consideration of anesthetic techniques to suit the patient and facilitate the surgery. However, there is a scarcity of evidence regarding the safety of specific anesthetic approaches for heart failure patients.Case Presentation: We describe the case of an adult patient in mid-50s, with a history of ischemic dilated cardiomyopathy with reduced Ejection Fraction (about 25%) who presented with acute gangrenous appendicitis and was scheduled for an open appendectomy. It was deemed to be a high-risk patient for general and spinal anesthesia. With the guidance of a multidisciplinary team, surgery was successfully performed using a quadratus lumborum block with standard monitoring. The patient was comfortable and hemodynamically stable throughout the procedure. The postoperative course was uneventful.Conclusion: Quadratus Lumborum Block for open appendectomy can be a beneficial alternative anesthesia technique in high-risk patients that significantly lowers perioperative cardiovascular risk, maintains hemodynamics, enhances satisfaction, and shortens hospital stay.Keywords: quadratus lumborum block, regional anesthesia, heart failure with reduced ejection fraction, left ventricular ejection fraction, quadratus l

Scarcity in fossil fuel reserves and their environmental impacts has forced the world towards the production of clean and environment-friendly fuels called biofuels. This review focuses on the importance of different machine learning models and optimization techniques to simulate and optimize process conditions, yield and parameters in the fermentation of cellulosic biomass from fifty recent studies. The superiority of ML models, especially ANN dominance in 70 % of studies with highest coefficient of regression over conventional techniques in the production of bioethanol and biohydrogen is comprehensively reviewed. Research gaps and studies directed toward the usage of most optimum ML models in future are directed after the sensitivity analysis with 5 % variation that suggest the stability of ML models. It is intended to spur further investigation into the development and use of ML models combined with optimization methods and CFD in the fermentation process to produce bioethanol and biohydrogen.

The China-Pakistan Economic Corridor (CPEC) is a significant development in South Asia, enhancing economic ties between China and Pakistan. It involves energy projects and infrastructure development, fostering collaboration and altering power balances among neighboring nations. The CPEC's dual nature, involving economic interests, security considerations, and geopolitical alliances, shapes the future of South Asian geopolitics, promoting competition and cooperation. Emphasizes the geostrategic dimensions of CPEC and its implications for the region, Further this study Analyse the CPEC and Convergence among the South Asian States This paper, drawing on qualitative data from diverse secondary sources. It is concluded that the CPEC's success could significantly impact South Asia's economic and geopolitical landscape by fostering regional cooperation and competition, potentially influencing the region's larger dynamics. Advocating for a comprehensive partnership, the study suggests that transparent implementation and inclusive policies involving all stakeholders can positively impact the economic conditions of Pakistan and the broader South Asian region, promoting recovery and cooperation amidst regional challenges.

The China-Pakistan Economic Corridor (CPEC) is a significant development in South Asia, enhancing economic ties between China and Pakistan. It involves energy projects and infrastructure development, fostering collaboration and altering power balances among neighboring nations. The CPEC's dual nature, involving economic interests, security considerations, and geopolitical alliances, shapes the future of South Asian geopolitics, promoting competition and cooperation. Emphasizes the geostrategic dimensions of CPEC and its implications for the region, Further this study Analyse the CPEC and Convergence among the South Asian States This paper, drawing on qualitative data from diverse secondary sources. It is concluded that the CPEC's success could significantly impact South Asia's economic and geopolitical landscape by fostering regional cooperation and competition, potentially influencing the region's larger dynamics. Advocating for a comprehensive partnership, the study suggests that transparent implementation and inclusive policies involving all stakeholders can positively impact the economic conditions of Pakistan and the broader South Asian region, promoting recovery and cooperation amidst regional challenges.

The massive yearly population growth is causing hazards to spread swiftly around the world and have a detrimental impact on both human life and the world economy. By ensuring early prediction accuracy, remote sensing enters the scene to safeguard the globe against weather-related threats and natural disasters. Convolutional neural networks, which are a reflection of deep learning, have been used more recently to reliably identify land use in remote sensing images. This work proposes a novel bottleneck residual and self-attention fusion-assisted architecture for land use recognition from remote sensing images. First, we proposed using the fast neural approach to generate cloud-effect satellite images. In neural style, we proposed a 5-layered residual block CNN to estimate the loss of neural-style images. After that, we proposed two novel architectures, named 3-layered bottleneck CNN architecture and 3-layered bottleneck self-attention CNN architecture, for the classification of land use images. Training has been conducted on both proposed and original neural-style generated datasets for both architectures. Subsequently, features are extracted from the deep layers and merged employing an innovative serial approach based on weighted entropy. By removing redundant and superfluous data, a novel Chimp Optimization technique is applied to the fused features in order to further refine them. In conclusion, selected features are classified using the help of neural network classifiers. The experimental procedure yielded respective accuracy rates of 99.0% and 99.4% when applied to both datasets. When evaluated in comparison to state-of-the-art (SOTA) methods, the outcomes generated by the proposed framework demonstrated enhanced precision and accuracy.

Purpose – Balochistan, which makes up roughly 44 percent of Pakistan’s total land area, is home to 6 percent of the nation’s inhabitants. Due to long distances and low population density, service delivery is particularly challenging. The province’s educational services are impacted by natural disasters like earthquakes, floods, droughts, and migration. Disaster risk reduction is a widely recognized concept that emphasizes appropriate education to lower an individual’s personal, familial, and communal vulnerability. The role of the school is crucial in Disaster Risk Reducation (DRR) education. As a result, the study’s goal was to explore the approaches adopted for the inclusion of DDR through teaching in classroom and school activities. Methodology – A focus group discussion with three groups of Pakistan studies and Geography teachers was conducted that consisted of 10 male and 14 female members. Findings – Findings demonstrate that the current textbook continues to teach students less about disaster risk reduction; teachers include knowledge from their personal experience in planning lessons about DRR. School assemblies, child clubs and activities designed by school management, and social organizations play a prominent role in DRR education. Further, the role of teachers and school management was identified in psycho-social support during disasters and pandemics. Significance – The study concludes that in addition to extracurricular activities and the teacher’s role, prior disaster experience, school, and social organization played a significant role in DRR education in rural Balochistan. The study results will assist curriculum developers, policymakers, and education leadership in developing more effective school disaster management plans. The results will also clarify how schools and teachers can close the knowledge gap in disaster preparedness education. Organizations working on disaster risk education and education in emergencies will also benefit from

Diabetes mellitus (DM), an endocrine syndrome characterized by high blood glucose levels due to abrogated insulin activity. The existing treatments for DM have side effects and varying degrees of efficacy. Therefore, it is paramount that novel approaches be developed to enhance the management of DM. Therapeutic plants have been accredited as having comparatively high efficacy with fewer adverse effects. The current study aims to elucidate the phytochemical profile, anti-hyperlipidemic, and anti-diabetic effects of methanolic extract D. salicifolia (leaves) in Alloxan-induced diabetic mice. Alloxan was injected intraperitoneally (150 mg kg-1, b.w), to induced diabetes in mice. The mice were divided into three groups (n=10). Group 1 (normal control) received normal food and purified water, Group II (diabetic control) received regular feed and clean water and group III (diabetic treated) received a methanolic extract of the plant (300 mg kg-1) for 28 days with a typical diet and clean water throughout the experiment. Blood samples were collected to checked serum glucose and concentration of LDL, TC, TG. The extract demonstrated significant antihyperglycemic activity (P<0.05), whereas improvements in mice’s body weight and lipid profiles were observed after treatment with the extract. This study establishes that the extract has high efficacy with comparatively less toxicity that can be used for DM management. © 2024, Instituto Internacional de Ecologia. All rights reserved. Diabetes mellitus (DM) é uma síndrome endócrina caracterizada por níveis elevados de glicose no sangue devido à atividade anulada da insulina. Os tratamentos existentes para o DM têm efeitos colaterais e vários graus de eficácia. Portanto, é fundamental que novas abordagens sejam desenvolvidas para aprimorar o manejo do DM. As plantas terapêuticas foram acreditadas como tendo eficácia comparativamente alta com menos efeitos adversos. O presente estudo visa elucidar o perfil fitoquímico, efeitos anti

Alexithymia, a psychological condition characterized by difficulty in identifying and describing emotions, has been linked to various mental health symptoms. This study aims to elucidate the differential responses to prolonged occupational stress, particularly among medical professional, by examining the role of alexithymia and emotional intelligence in the development of burnout. A cross-sectional experimental design was employed, involving a voluntary and anonymous questionnaire survey completed by 200 medical practitioners. The survey encompassed demographic information, occupational detail and measures of emotional intelligence, burnout & Alexithymia. Results, accounting for work- related characteristics, indicate that alexithymia significantly contributed to the depersonalization and personal accomplishment dimensions of burnout, contrary to expectations, emotional intelligence did not demonstrate greater explanatory power for burnout compared alexithymia as a more critical predictor of burnout in medical professionals than emotional intelligence, suggesting the need for targeted intervention focusing on emotional processing skills within the population.

The swift advancement of sustainable energy technologies, coupled with the urgent need to address environmental challenges, has generated considerable interest in the multifaceted applications of biochar materials to promote energy, water, and environmental sustainability. This comprehensive review examines recent advancements in the production and applications of functionalized biochar materials, emphasizing their pivotal roles in energy conversion and storage, wastewater treatment, CO2 reduction, soil amelioration, and the promotion of carbon neutrality within a circular economy framework. The functionalization of biochar materials involves surface chemistry and porosity modifications, achieved through techniques like templating, chemical activation, metal impregnation, or heteroatom doping. These modifications substantially enhance the catalytic activity, energy storage capacity, and cycling stability of biochar materials, making them particularly effective in diverse energy applications such as water splitting, fuel cells, and supercapacitors. Additionally, functionalized biochar materials demonstrate remarkable efficacy as catalysts and adsorbents in wastewater treatment, proficiently removing pollutants like heavy metals, organic contaminants, and nutrients, thereby facilitating resource recovery from wastewater. The review also underscores the potential of functionalized biochar materials in CO2 capture and conversion, exploring innovative strategies to augment their CO2 adsorption capacity and state-of-the-art catalytic processes for transforming captured CO2 into valuable fuels and chemicals. In summary, this review offers valuable insights into the recent advancements in biochar research, underscoring its substantial commercial potential as a versatile material contributing to a cleaner and more sustainable future.Article HighlightsThe current status of biochar research is comprehensively reviewed.The potential of biochar in energy, water, and environmenta

Background: Over the last few years, the principle of cross-docking has prominently spreadthrough the companies in which they try hard to make their supply chain channels efficientand achieve higher demands of the society. Studies claimed that inventory management remains to be challenge for professionals of supply chain as long-term processing times may result in considerable financial losses for firms. Aim: This research aims to evaluate the effectiveness of Hub-and-Spoke cross-dockingstrategy in inventory management by understanding the impact, outcomes or efficacy of its implementation. Methodology: This research has adopted qualitative research method to generate extensive data and deep insights to underlying factors behind organizations' decisions and behavior on the implementation of cross-docking concept. The interviews have been chosen as the main data collection method of this research because it has been used successfully in order to produce rich and detailed information about the participants in the supply chain management.The total sample size of the participants is 10. For instance, the research conducted interviews via In-person, Zoom and WhatsApp video calls. The researcher recruited supply chain managers including companies’ representatives, supply chain practitioners, logistic managers,inventory managers and related stakeholders responsible for executing and overviewing inventory management approaches within their firms operating in Sweden. Thus, individuals can offer useful information related to supply planning, implementing and optimising cross-docking operations within their organisations. Findings and Conclusion: The research has, however, led to the impact of the organizational culture on the sustainable Hub-and-Spoke cross-docking strategy with the participants, all agreeing on the role that culture plays in shaping the structure of the strategy in the long-term. Finally, organizational culture was considered to be the cornerstone s

The exterior beam-column joint (BCJ) within reinforced concrete (RC) frame structures is acknowledged as a vulnerable component prone to seismic failure. This article proposes a practical and economical strengthening method for exterior BCJs using a perforated steel haunch system. This method is designed to mitigate damage in BCJs and improve the seismic performance of the structure. Employing finite element modeling (FEM) techniques, the study evaluates the impact of perforated steel haunches on the BCJs’ behavior and performance. The investigation involves creating nine distinct models, each representing a BCJ with a steel haunch system. These models include a control model without any perforations and eight variations with different levels of perforation (ranging from 10% to 50%) within the steel haunch system. Furthermore, the study analyzes the influence of perforation shapes on the connections’ performance, considering square, circular, hexagonal, and triangular shapes. The results reveal that utilizing a steel haunch without perforations significantly increases the load-carrying capacity of a BCJ by about 89%. Additionally, circular or square-shaped perforations, up to 30–35% within the steel haunch, effectively prevent the joints’ failure and promote the ductile behavior. These findings hold the potential to advance the design methodology for RC joints subjected to seismic loads, thereby enhancing the structural resilience in earthquake-prone regions.

Culverts fulfill the vital function of safely channeling water beneath railway tracks, highways, and overpasses. They serve various purposes, including facilitating drainage in areas such as watercourses, drainage zones, and regions with restricted ground-bearing capacity. Precast reinforced concrete (RC) box culverts are a popular choice because they are strong, durable, rigid, and economical. However, culverts are prone to corrosion due to exposure to a range of environmental factors and aggressive chemicals. Therefore, enhancing the design and construction of this crucial infrastructure is imperative to effectively combat corrosion and to adhere to modern standards of reliability and affordability. In this study, carbon fiber-reinforced polymer (CFRP) was used to strengthen corroded culverts, with promising potential to improve safety and longevity in these structures. This study compared the behavior of corroded RC box culverts to CFRP-strengthened ones using the finite element method (FEM). It explored the impact of varying the damage thicknesses owing to corrosion, ranging from 0 mm to 20 mm, on the structural performance of the box culverts. The results showed that the CFRP model exhibited a substantial 25% increase in the capacity and reduced the damage compared to the reference model. Moreover, a parametric study was conducted for establishing a cost-effective design, in which numerous CFRP strip configurations were examined for a damaged-culvert model. The results indicated that a complete CFRP sheet was most effective for the maximum design capacity and repair effectiveness. The study’s outcomes provide valuable insights for professionals engaged in enhancing the strength of box culverts, aiming to increase the capacity, enhance the stability, and strengthen corroded culverts.

The swift advancement of sustainable energy technologies, coupled with the urgent need to address environmental challenges, has generated considerable interest in the multifaceted applications of biochar materials to promote energy, water, and environmental sustainability. This comprehensive review examines recent advancements in the production and applications of functionalized biochar materials, emphasizing their pivotal roles in energy conversion and storage, wastewater treatment, CO2 reduction, soil amelioration, and the promotion of carbon neutrality within a circular economy framework. The functionalization of biochar materials involves surface chemistry and porosity modifications, achieved through techniques like templating, chemical activation, metal impregnation, or heteroatom doping. These modifications substantially enhance the catalytic activity, energy storage capacity, and cycling stability of biochar materials, making them particularly effective in diverse energy applications such as water splitting, fuel cells, and supercapacitors. Additionally, functionalized biochar materials demonstrate remarkable efficacy as catalysts and adsorbents in wastewater treatment, proficiently removing pollutants like heavy metals, organic contaminants, and nutrients, thereby facilitating resource recovery from wastewater. The review also underscores the potential of functionalized biochar materials in CO2 capture and conversion, exploring innovative strategies to augment their CO2 adsorption capacity and state-of-the-art catalytic processes for transforming captured CO2 into valuable fuels and chemicals. In summary, this review offers valuable insights into the recent advancements in biochar research, underscoring its substantial commercial potential as a versatile material contributing to a cleaner and more sustainable future.Article HighlightsThe current status of biochar research is comprehensively reviewed.The potential of biochar in energy, water, and environmenta

Alexithymia, a psychological condition characterized by difficulty in identifying and describing emotions, has been linked to various mental health symptoms. This study aims to elucidate the differential responses to prolonged occupational stress, particularly among medical professional, by examining the role of alexithymia and emotional intelligence in the development of burnout. A cross-sectional experimental design was employed, involving a voluntary and anonymous questionnaire survey completed by 200 medical practitioners. The survey encompassed demographic information, occupational detail and measures of emotional intelligence, burnout & Alexithymia. Results, accounting for work- related characteristics, indicate that alexithymia significantly contributed to the depersonalization and personal accomplishment dimensions of burnout, contrary to expectations, emotional intelligence did not demonstrate greater explanatory power for burnout compared alexithymia as a more critical predictor of burnout in medical professionals than emotional intelligence, suggesting the need for targeted intervention focusing on emotional processing skills within the population.

The swift advancement of sustainable energy technologies, coupled with the urgent need to address environmental challenges, has generated considerable interest in the multifaceted applications of biochar materials to promote energy, water, and environmental sustainability. This comprehensive review examines recent advancements in the production and applications of functionalized biochar materials, emphasizing their pivotal roles in energy conversion and storage, wastewater treatment, CO2 reduction, soil amelioration, and the promotion of carbon neutrality within a circular economy framework. The functionalization of biochar materials involves surface chemistry and porosity modifications, achieved through techniques like templating, chemical activation, metal impregnation, or heteroatom doping. These modifications substantially enhance the catalytic activity, energy storage capacity, and cycling stability of biochar materials, making them particularly effective in diverse energy applications such as water splitting, fuel cells, and supercapacitors. Additionally, functionalized biochar materials demonstrate remarkable efficacy as catalysts and adsorbents in wastewater treatment, proficiently removing pollutants like heavy metals, organic contaminants, and nutrients, thereby facilitating resource recovery from wastewater. The review also underscores the potential of functionalized biochar materials in CO2 capture and conversion, exploring innovative strategies to augment their CO2 adsorption capacity and state-of-the-art catalytic processes for transforming captured CO2 into valuable fuels and chemicals. In summary, this review offers valuable insights into the recent advancements in biochar research, underscoring its substantial commercial potential as a versatile material contributing to a cleaner and more sustainable future.Article HighlightsThe current status of biochar research is comprehensively reviewed.The potential of biochar in energy, water, and environmenta

The swift advancement of sustainable energy technologies, coupled with the urgent need to address environmental challenges, has generated considerable interest in the multifaceted applications of biochar materials to promote energy, water, and environmental sustainability. This comprehensive review examines recent advancements in the production and applications of functionalized biochar materials, emphasizing their pivotal roles in energy conversion and storage, wastewater treatment, CO2 reduction, soil amelioration, and the promotion of carbon neutrality within a circular economy framework. The functionalization of biochar materials involves surface chemistry and porosity modifications, achieved through techniques like templating, chemical activation, metal impregnation, or heteroatom doping. These modifications substantially enhance the catalytic activity, energy storage capacity, and cycling stability of biochar materials, making them particularly effective in diverse energy applications such as water splitting, fuel cells, and supercapacitors. Additionally, functionalized biochar materials demonstrate remarkable efficacy as catalysts and adsorbents in wastewater treatment, proficiently removing pollutants like heavy metals, organic contaminants, and nutrients, thereby facilitating resource recovery from wastewater. The review also underscores the potential of functionalized biochar materials in CO2 capture and conversion, exploring innovative strategies to augment their CO2 adsorption capacity and state-of-the-art catalytic processes for transforming captured CO2 into valuable fuels and chemicals. In summary, this review offers valuable insights into the recent advancements in biochar research, underscoring its substantial commercial potential as a versatile material contributing to a cleaner and more sustainable future.Article HighlightsThe current status of biochar research is comprehensively reviewed.The potential of biochar in energy, water, and environmenta

The exterior beam-column joint (BCJ) within reinforced concrete (RC) frame structures is acknowledged as a vulnerable component prone to seismic failure. This article proposes a practical and economical strengthening method for exterior BCJs using a perforated steel haunch system. This method is designed to mitigate damage in BCJs and improve the seismic performance of the structure. Employing finite element modeling (FEM) techniques, the study evaluates the impact of perforated steel haunches on the BCJs’ behavior and performance. The investigation involves creating nine distinct models, each representing a BCJ with a steel haunch system. These models include a control model without any perforations and eight variations with different levels of perforation (ranging from 10% to 50%) within the steel haunch system. Furthermore, the study analyzes the influence of perforation shapes on the connections’ performance, considering square, circular, hexagonal, and triangular shapes. The results reveal that utilizing a steel haunch without perforations significantly increases the load-carrying capacity of a BCJ by about 89%. Additionally, circular or square-shaped perforations, up to 30–35% within the steel haunch, effectively prevent the joints’ failure and promote the ductile behavior. These findings hold the potential to advance the design methodology for RC joints subjected to seismic loads, thereby enhancing the structural resilience in earthquake-prone regions.

Culverts fulfill the vital function of safely channeling water beneath railway tracks, highways, and overpasses. They serve various purposes, including facilitating drainage in areas such as watercourses, drainage zones, and regions with restricted ground-bearing capacity. Precast reinforced concrete (RC) box culverts are a popular choice because they are strong, durable, rigid, and economical. However, culverts are prone to corrosion due to exposure to a range of environmental factors and aggressive chemicals. Therefore, enhancing the design and construction of this crucial infrastructure is imperative to effectively combat corrosion and to adhere to modern standards of reliability and affordability. In this study, carbon fiber-reinforced polymer (CFRP) was used to strengthen corroded culverts, with promising potential to improve safety and longevity in these structures. This study compared the behavior of corroded RC box culverts to CFRP-strengthened ones using the finite element method (FEM). It explored the impact of varying the damage thicknesses owing to corrosion, ranging from 0 mm to 20 mm, on the structural performance of the box culverts. The results showed that the CFRP model exhibited a substantial 25% increase in the capacity and reduced the damage compared to the reference model. Moreover, a parametric study was conducted for establishing a cost-effective design, in which numerous CFRP strip configurations were examined for a damaged-culvert model. The results indicated that a complete CFRP sheet was most effective for the maximum design capacity and repair effectiveness. The study’s outcomes provide valuable insights for professionals engaged in enhancing the strength of box culverts, aiming to increase the capacity, enhance the stability, and strengthen corroded culverts.

This paper explores how deep learning enhances Internet of Things (IoT) cybersecurity, examining advanced methods like convolutional and recurrent neural networks for detailed IoT data analysis. It highlights the importance of real-time threat detection and classification, focusing on innovative Graph Neural Networks and Transformer Models for better network security. The study also considers Federated Learning and Edge Computing for decentralized, privacy-friendly data handling, and Explainable AI for clarity in decision-making. It addresses the growing challenges of creating scalable, adaptable deep learning models for ever-changing IoT environments and cyber threats, emphasizing the need for ongoing research in developing resilient IoT cybersecurity solutions. The analysis further reveals that deep learning techniques are increasingly effective in anomaly detection and predictive maintenance, reducing false positives, and adapting to new types of cyber threats dynamically. Specifically, it emphasizes how Transformer Models and Graph Neural Networks offer promising results in contextualizing and mitigating complex multi-stage cyber-attacks, enhancing the robustness of IoT systems against evolving threats.

In today technological world we can easily accessed on to the desired information through Intelligent Personal Assistants. These Intelligent Personal Assistants performs concierge-type tasks or provides input based on voice inputs or commands. We found still other issues related to the intelligent Personal Assistants published during our study 1) IPA security needs to be done in order to enhance the system intelligence. 2) Voice recognition sometimes fails to recognize voice. 3) IPA intelligence will be challenged if learning and suggestions failed. 4) Set standards between personal and professional tasks. 5) IPA has to go through intense knowledge that’s helps react when user is not available to perform task in his absence. 6) Improvement in IPAs in terms of the context awareness IPAs. 7) IPA intense knowledge that’s helps react when user is not available to perform task. In this paper we will explore the mentioned usability issues of Intelligent Personal Assistants with their suggested solutions. Our focus is only to provide the concept and idea and maybe there is need to explore each of the issue in detail in future aspects.

Purpose - This study examines whether a firm's management earnings forecasts affect its technical innovation activities. Our study also examines whether the cost of debt plays a mediating role between the management earnings forecasts and the innovation nexus. Design/methodology/approach - We obtained data from 1032 Chinese non-financial firms listed on the Shanghai and Shenzhen stock markets from 2005 to 2022 (i.e., 18576 firm-year observations). We used various econometrics techniques, such as Heckman's (1979) two-stage selection method and two-stage least square, to examine the relationship between management earnings forecasts and the firm's technical innovation activities. Findings - We find a positive relationship between management earnings forecasts and the firms' technical innovation. We also find that the cost of debt mediates the relationship between management earnings forecast and technical innovation. Further analysis indicates that frequent earnings forecasts provide incremental information regarding a firm's future value and cash flows, thus reducing the volatility and uncertainty in cash flow calculations. Our findings are robust to several tests. Research Implications - Our study has implications for policymakers, practitioners, and high-level management of Chinese firms, enabling them to understand the relationship between management earnings forecasts and firms' innovation activities.

Technical revolutions and scientific advancements are conspicuous, but still, false beliefs and superstitious behaviour are quite commonplace. It could be believed that these beliefs are held by less educated people. Therefore, the present study investigated superstitions among educated urban people. Using a qualitative research method, data was collected through interviews and analyzed through thematic analysis. A total of 8 participants (i.e., 2 males and 6 females) participated in the study. All of the participants were highly educated (16 years’ education or above). A purposive sampling technique was used to include participants in this research. Detailed semi-structured interviews were conducted with each participant with their consent. Seven themes were derived including brooming, marriage fixing, palm itching, eye blink, glass break, lucky stones, and lucky numbers. The study recommends inculcating scientific knowledge on a broader level in Pakistan.

This study explored the infrastructural needs for the establishment of Non-Formal Schools (NFSs) within the existing setup of mosques and guesthouses of the community, aiming to enrol out-of-school children and alleviate illiteracy in Kunar province, Afghanistan. Employing a case study and qualitative research design, 62 research participants from the education sector and the Hajj and Islamic Affairs sector were purposively selected. Data was collected through semi-structured interviews and was analysed using thematic analysis. Findings revealed that generally buildings and carpets were the available facilities for the initiative; however, other essential facilities such as furniture, teaching materials, stationery, and qualified teaching staff were needed for the establishment of NFSs in the province. The study suggests that the government need to collaborate with non-governmental organizations and support the initiative by devising comprehensive policies, allocating sufficient funds, and providing the basic infrastructure facilities to open NFSs addressing the issue of illiteracy in the province and the country.

This study employs Marxist analysis to the novel To Kill a Mockingbird by Harper Lee, focusing on the portrayal of class divide within the story. The examination of social stratification is a prominent subject in Marxism, and Marx himself asserts in the Communist Manifesto that the progression of all societies throughout history is characterized by conflicts between different social classes (Marx & Engels, 1969). Marxism is a prominent literary criticism theory that examines issues such as injustice, exploitation, class separation, and alienation. Marxism posits that the primary purpose of literature is to foster class consciousness and incite a revolution among the working class (Beteillie, 2007). The study is characterized by its qualitative nature and employs an interpretive methodology. The story is analyzed using a dialectical approach, revealing that class separation serves as the fundamental source of injustice, social discrimination, and exploitation. The study demonstrates that American society was fragmented based on both social class and race. In America, race not only served as a means of categorization but also contributed to the split between the privileged upper class and the economically disadvantaged and marginalized class.

Recently, a well-deserved attention was brought to the intersection between crime response and resilience as a human right. The paper explores the resilience concept within the domain of human rights, spotting the light on critical tendencies in crime and responses and reviewing the ‘human rights’ and ‘resilience’ perspectives. Shaping the principles and approaches of both, it implies that resilience and human rights perspectives should be applied simultaneously in criminal justice. The source provides an in-depth legal research analysis that helps to better understand the value and implications of such an approach. Overall, the notion defends the holistic and rights-centred approaches to crime processing.

This study aims to use updated data sets for China from 1990 to 2022 to study the relationship between business growth and environmental factors and regulations such as environmental policies, taxes, green technologies, and environmental revenues. The first study confirmed that none of the variables used was static in I(II), while the ADF and PP unit root tests proved that all variables were static at the level, and confirmed the first difference in the ARDL model. Results demonstrate that environmental taxes stimulate business growth, a phenomenon explained by the Porter Hypothesis, suggesting that effective regulations related to environment can spur innovation and efficiency. The significant influence of environmental revenues further illuminates the potential of the green economy. The findings underscore the need for governments and businesses to adopt stringent environmental regulations, promote green technologies, and exploit the burgeoning opportunities in the green economy. The interplay between environmental factors and business growth not only fosters economic prosperity (SDG 8) but also aids in combatting climate change and promoting sustainable industrialization (SDG 9, 13), offering a roadmap towards a sustainable future.

This study aims to explore the relationship between violence and drug use among school students and highlight the role of peace education in addressing these issues. Previous research has shown a strong link between violence and drug use, with shared risk factors such as socio-economic status, family dynamics, peer influence, and mental health issues. However, there is a need for more in-depth studies on the causative pathways and educational interventions to address these issues. The researcher chooses a qualitative approach to recruit a smaller sample of teachers and students for in-depth interviews and focus group discussions. The researcher applied thematic content analysis. The study found that teachers need a better understanding of violence and drug use among students. They also lack a good knowledge of modern concepts and theories related to these issues. The authors suggest that teacher training programs should focus on addressing misconceptions about teaching violence and drug use to students. Effective peace education should also consider the relationship between drug use and violent attitudes among adolescents and the parental climate surrounding these issues.

Transportation systems primarily depend on vehicular flow on roads. Developed countries have shifted towards automated signal control, which manages and updates signal synchronisation automatically. In contrast, traffic in underdeveloped countries is mainly governed by manual traffic light systems. These existing manual systems lead to numerous issues, wasting substantial resources such as time, energy, and fuel, as they cannot make real-time decisions. In this work, we propose an algorithm to determine traffic signal durations based on real-time vehicle density, obtained from live closed circuit television camera feeds adjacent to traffic signals. The algorithm automates the traffic light system, making decisions based on vehicle density and employing Faster R-CNN for vehicle detection. Additionally, we have created a local dataset from live streams of Punjab Safe City cameras in collaboration with the local police authority. The proposed algorithm achieves a class accuracy of 96.6% and a vehicle detection accuracy of 95.7%. Across both day and night modes, our proposed method maintains an average precision, recall, F1 score, and vehicle detection accuracy of 0.94, 0.98, 0.96 and 0.95, respectively. Our proposed work surpasses all evaluation metrics compared to state-of-the-art methodologies.

Culverts fulfill the vital function of safely channeling water beneath railway tracks, highways, and overpasses. They serve various purposes, including facilitating drainage in areas such as watercourses, drainage zones, and regions with restricted ground-bearing capacity. Precast reinforced concrete (RC) box culverts are a popular choice because they are strong, durable, rigid, and economical. However, culverts are prone to corrosion due to exposure to a range of environmental factors and aggressive chemicals. Therefore, enhancing the design and construction of this crucial infrastructure is imperative to effectively combat corrosion and to adhere to modern standards of reliability and affordability. In this study, carbon fiber-reinforced polymer (CFRP) was used to strengthen corroded culverts, with promising potential to improve safety and longevity in these structures. This study compared the behavior of corroded RC box culverts to CFRP-strengthened ones using the finite element method (FEM). It explored the impact of varying the damage thicknesses owing to corrosion, ranging from 0 mm to 20 mm, on the structural performance of the box culverts. The results showed that the CFRP model exhibited a substantial 25% increase in the capacity and reduced the damage compared to the reference model. Moreover, a parametric study was conducted for establishing a cost-effective design, in which numerous CFRP strip configurations were examined for a damaged-culvert model. The results indicated that a complete CFRP sheet was most effective for the maximum design capacity and repair effectiveness. The study’s outcomes provide valuable insights for professionals engaged in enhancing the strength of box culverts, aiming to increase the capacity, enhance the stability, and strengthen corroded culverts.

The exterior beam-column joint (BCJ) within reinforced concrete (RC) frame structures is acknowledged as a vulnerable component prone to seismic failure. This article proposes a practical and economical strengthening method for exterior BCJs using a perforated steel haunch system. This method is designed to mitigate damage in BCJs and improve the seismic performance of the structure. Employing finite element modeling (FEM) techniques, the study evaluates the impact of perforated steel haunches on the BCJs’ behavior and performance. The investigation involves creating nine distinct models, each representing a BCJ with a steel haunch system. These models include a control model without any perforations and eight variations with different levels of perforation (ranging from 10% to 50%) within the steel haunch system. Furthermore, the study analyzes the influence of perforation shapes on the connections’ performance, considering square, circular, hexagonal, and triangular shapes. The results reveal that utilizing a steel haunch without perforations significantly increases the load-carrying capacity of a BCJ by about 89%. Additionally, circular or square-shaped perforations, up to 30–35% within the steel haunch, effectively prevent the joints’ failure and promote the ductile behavior. These findings hold the potential to advance the design methodology for RC joints subjected to seismic loads, thereby enhancing the structural resilience in earthquake-prone regions.

This research work was conducted to investigate the anatomical and antioxidant studies of some ethnoveterinary grasses (Cenchrus pennisetiformis and Dichanthium annulatum). The anatomical characteristics (compact epidermal layer, large cortical cells, thickened sclerenchyma, central and scattered vascular bundles, large metaxylem, small protoxylem, and centrally located pith) were observed. For the antioxidant activity studies, the crude methanol extract was prepared by maceration techniques and different fractions were prepared (n-hexane, chloroform, and aqueous solution). The maximum antioxidant potential in DPPH was shown by C. pennisetiformis at a concentration of 250 µL in the chloroform fraction, while D. annulatum showed a maximum value of 68.47±0.30 at a concentration of 250 µL in the methanolic extract. In both species, chloroform extract in TAA showed maximum potency at a concentration of 500 µL, but C. pennisetiformis showed a higher value (i.e. 1.15±0.0018) and D. annulatum showed a lever value (i.e. 1.05±0.0017). The best reducing power in FRAP was shown by D. annulatum followed by C. pennisetiformis. C. pennisetiformis showed the highest value in the chloroform fraction while D. annulatum showed a higher significant value in the methanol fraction. These grasses have the potential to control several diseases caused by ROS in animals.

Technical revolutions and scientific advancements are conspicuous, but still, false beliefs and superstitious behaviour are quite commonplace. It could be believed that these beliefs are held by less educated people. Therefore, the present study investigated superstitions among educated urban people. Using a qualitative research method, data was collected through interviews and analyzed through thematic analysis. A total of 8 participants (i.e., 2 males and 6 females) participated in the study. All of the participants were highly educated (16 years’ education or above). A purposive sampling technique was used to include participants in this research. Detailed semi-structured interviews were conducted with each participant with their consent. Seven themes were derived including brooming, marriage fixing, palm itching, eye blink, glass break, lucky stones, and lucky numbers. The study recommends inculcating scientific knowledge on a broader level in Pakistan.

Technical revolutions and scientific advancements are conspicuous, but still, false beliefs and superstitious behaviour are quite commonplace. It could be believed that these beliefs are held by less educated people. Therefore, the present study investigated superstitions among educated urban people. Using a qualitative research method, data was collected through interviews and analyzed through thematic analysis. A total of 8 participants (i.e., 2 males and 6 females) participated in the study. All of the participants were highly educated (16 years’ education or above). A purposive sampling technique was used to include participants in this research. Detailed semi-structured interviews were conducted with each participant with their consent. Seven themes were derived including brooming, marriage fixing, palm itching, eye blink, glass break, lucky stones, and lucky numbers. The study recommends inculcating scientific knowledge on a broader level in Pakistan.

This study explored the infrastructural needs for the establishment of Non-Formal Schools (NFSs) within the existing setup of mosques and guesthouses of the community, aiming to enrol out-of-school children and alleviate illiteracy in Kunar province, Afghanistan. Employing a case study and qualitative research design, 62 research participants from the education sector and the Hajj and Islamic Affairs sector were purposively selected. Data was collected through semi-structured interviews and was analysed using thematic analysis. Findings revealed that generally buildings and carpets were the available facilities for the initiative; however, other essential facilities such as furniture, teaching materials, stationery, and qualified teaching staff were needed for the establishment of NFSs in the province. The study suggests that the government need to collaborate with non-governmental organizations and support the initiative by devising comprehensive policies, allocating sufficient funds, and providing the basic infrastructure facilities to open NFSs addressing the issue of illiteracy in the province and the country.

The translocation of wild ungulates poses significant stress to the animal species being transported, necessitating careful consideration. Chemical restraint helps to reduce the stress levels significantly by minimizing the mobility of the animals. Capture myopathy, a leading cause of mortality during chemical immobilization, is a critical concern. However, the Boma method offers a promising alternative to the conventionally used translocation methods. Objective: To compare the survival outcomes of the spotted deer captured and transported using both chemical restraint and the Boma method, therefore assessing their respective effectiveness. Methods: In the study, we used 22 spotted deer for chemical restraint method and 30 spotted deer were captured through Boma method and both of techniques were assessed, how capture methods influenced the fatality rate of the highly sensitive spotted deer which were being trans-located from Safari Zoo, Lahore to other captive sites of Punjab Pakistan. Results: The exceptional record of zero mortality in the Boma procedure was seen as compared to the chemical immobilization in which 31% of the total shifted animals were expired. The pathognomic white streaked/pale muscles in necropsy findings of dead animals later on confirmed the dead due to capture myopathy. Conclusions: The study established the finding that Boma technique is safer technique for trans-location of ungulates especially spotted deer as compared to the chemical immobilization.

The Indian One-Horned Rhinoceros (Rhinoceros unicornis), commonly referred to as the Indian Rhinoceros, is an endangered species inhabiting the floodplains and grasslands of the Indian subcontinent. Once abundant, the species now faces a vulnerable status in its homeland, as confirmed by the International Union for The Conservation of Nature IUCN’s assessment. Objective: To record Rhinoceros unicornis' biometric body measurements for the first time. Methods: The following study delves into the significance of body biometry data for the conservation of this remarkable species Indian One Horned Rhinoceros housed at Lal Suhanra National Park, Punjab, Pakistan. In order to give conservationists, the resources they need to develop more effective methods involving habitat management, population monitoring, and captive breeding programs, a thorough analysis of the physical characteristics, growth trends, and sexual dimorphism of 42-year-old Indian Rhinos via the evaluation of the body measurements was conducted. Results: This study presents comprehensive body measurements of the Indian One-Horned Rhinoceros which have never been published before. The length of the rhino itself spanned 143 inches, encapsulating the magnitude of this magnificent creature. These insightful observations are crucial for protecting the threatened species, particularly considering the growing threats caused by habitat loss, poaching, and the effects of climate change. Conclusions: Biometric analysis of large mammals assumes a pivotal role when designing enclosures and estimating the enclosure dimensions.

Mohammad Mohsin Arshad, Muhammad Mohsin Khan, Ghanem Al Sulaiti, Ghaya Al Rumaihi Department of Neurosurgery, Neuroscience Institute, Hamad Medical Corporation, Doha, QatarCorrespondence: Mohammad Mohsin Arshad, Hamad Medical Corporation, PO Box 3050, Doha, Qatar, Tel +974 33159377, Fax +974 44398190, Email marshad3@hamad.qaIntroduction: Upper thoracic spine fractures are rare as compared to other spine segments due to anatomical landmarks. If they occur, they are usually associated with paraplegia or any other neurological dysfunction. We report upper thoracic fracture without neurological dysfunction which is a rare entity along with its radiological imaging, and management plan.Case Description: Forty-years old male presented after RTA. CT spine showed T2 vertebral body fracture with dislocation/locking of the right T2-T3 facet joint. The patient underwent surgical fixation and was neurologically intact.Conclusion: Upper thoracic spine fracture is a rare entity due to its anatomical location. And sometimes it is missed as well. Proper imaging should be considered if there is high suspicion and early surgery is warranted to prevent permanent damage.Keywords: unilateral locked facet, upper thoracic spine, spinal trauma, thoracic dislocation, fracture, spine

Lama Sultan,1,2 Nynke de Jong,3 Basim Alsaywid,4,5 Muhammad Anwar Khan,6 Jascha de Nooijer7 1Department of Clinical Nutrition, Ministry of National Guard Health Affairs, King Abdulaziz Medical City, Jeddah, KSA, Saudi Arabia; 2School of Health Professions Education, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, Netherlands; 3Department of Health Services Research, School of Health Professions Education, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, NL, Saudi Arabia; 4Urology Department, King Faisal Specialist Hospital & Research Center, Riyadh, KSA, Saudi Arabia; 5Education and Research Skills Directory, Saudi National Institute of Health, Riyadh, KSA, Saudi Arabia; 6College of Medicine, King Saud Bin Abdulaziz University for Health Sciences, Jeddah, KSA, Saudi Arabia; 7Department of Health Promotion, School of Health Professions Education, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, NetherlandsCorrespondence: Lama Sultan, Department of Clinical Nutrition, Ministry of National Guard Health Affairs- Jeddah, King Abdulaziz Medical City, Mail Code 6660, P.O. Box.9515, Jeddah, 21423, Kingdom of Saudi Arabia, Tel +966553343478, Email sultanla@mngha.med.sa; lama.sultan@hotmail.comBackground: Palliative care teams provide support to patients and their caregivers during terminal illness, which requires interprofessional collaboration. One of the foundational skills is to assist patients with decision-making. This can be facilitated through interprofessional shared decision-making (IP-SDM). So far, IP-SDM education frameworks have only been used to a limited extent in the area of palliative care.Aim: This study aims to explore perceptions and practices of faculty members, health professionals, and students toward IP-SDM education in palliative care and to indicate associated factors to implement an IP-SDM in undergraduate health professions education in palliativ

This research work was conducted to investigate the anatomical and antioxidant studies of some ethnoveterinary grasses (Cenchrus pennisetiformis and Dichanthium annulatum). The anatomical characteristics (compact epidermal layer, large cortical cells, thickened sclerenchyma, central and scattered vascular bundles, large metaxylem, small protoxylem, and centrally located pith) were observed. For the antioxidant activity studies, the crude methanol extract was prepared by maceration techniques and different fractions were prepared (n-hexane, chloroform, and aqueous solution). The maximum antioxidant potential in DPPH was shown by C. pennisetiformis at a concentration of 250 µL in the chloroform fraction, while D. annulatum showed a maximum value of 68.47±0.30 at a concentration of 250 µL in the methanolic extract. In both species, chloroform extract in TAA showed maximum potency at a concentration of 500 µL, but C. pennisetiformis showed a higher value (i.e. 1.15±0.0018) and D. annulatum showed a lever value (i.e. 1.05±0.0017). The best reducing power in FRAP was shown by D. annulatum followed by C. pennisetiformis. C. pennisetiformis showed the highest value in the chloroform fraction while D. annulatum showed a higher significant value in the methanol fraction. These grasses have the potential to control several diseases caused by ROS in animals.

Introduction Anti-mitosis has been a key strategy of anti-cancer therapies, targeting at a fundamental property of cancer cells, their non-controllable proliferation due to overactive mitotic divisions. For improved anti-cancer therapies, it is important to find out whether cancer cells can proliferate independent of mitosis and become resistant to anti-mitotic agents. Results In this study, live-cell imaging was applied to both primary-cultures of tumor cells, and immortalized cancer cell lines, to detect aberrant proliferations. Cells isolated from various malignant tumors, such as Grade-III hemangiopericytoma, atypical meningioma, and metastatic brain tumor exhibit distinct cellular behaviors, including amoeboid sequestration, tailing, tunneling, nucleic DNA leakage, as well as prokaryote-like division such as binary fission and budding-shedding, which are collectively referred to and reported as 'non-mitotic proliferation' in this study. In contrast, benign tumors including Grade-I hemangiopericytoma and meningioma were not obvious in such behaviors. Moreover, when cultured in medium free of any anti-cancer drugs, cells from a recurrent Grade-III hemangiopericytoma that had been subjected to pre-operation adjuvant chemotherapy gradually shifted from non-mitotic proliferation to abnormal mitosis in the form of daughter number variation (DNV) and endomitosis, and eventually regular mitosis. Similarly, when treated with the anti-cancer drugs Epirubicin or Cisplatin, the cancer cell lines HeLa and A549 showed a shift from regular mitosis to abnormal mitosis, and further to non-mitosis as the dominant mode of proliferation with increasing drug concentrations. Upon removal of the drugs, the cells reversed back to regular mitosis with only minor occurrences of abnormal mitosis, accompanied by increased expression of the stem cell markers ALDH1, Sox, Oct4 and Nanog. Conclusions The present study revealed that various types of malignant, but not benign, cancer cells exhi

Fairness is a critical concern in deep learning, especially in healthcare, where these models influence diagnoses and treatment decisions. Although fairness has been investigated in the vision-only domain, the fairness of medical vision-language (VL) models remains unexplored due to the scarcity of medical VL datasets for studying fairness. To bridge this research gap, we introduce the first fair vision-language medical dataset Harvard-FairVLMed that provides detailed demographic attributes, ground-truth labels, and clinical notes to facilitate an in-depth examination of fairness within VL foundation models. Using Harvard-FairVLMed, we conduct a comprehensive fairness analysis of two widely-used VL models (CLIP and BLIP2), pre-trained on both natural and medical domains, across four different protected attributes. Our results highlight significant biases in all VL models, with Asian, Male, Non-Hispanic, and Spanish being the preferred subgroups across the protected attributes of race, gender, ethnicity, and language, respectively. In order to alleviate these biases, we propose FairCLIP, an optimal-transport-based approach that achieves a favorable trade-off between performance and fairness by reducing the Sinkhorn distance between the overall sample distribution and the distributions corresponding to each demographic group. As the first VL dataset of its kind, Harvard-FairVLMed holds the potential to catalyze advancements in the development of machine learning models that are both ethically aware and clinically effective. Our dataset and code are available at https://ophai.hms.harvard.edu/datasets/harvard-fairvlmed10k., Comment: CVPR 2024

Sleep health is integral to the overall well-being of nursing students, yet it is prevalent. Objective: The primary objective of this study was to determine the insomnia among nursing students. Methods: A total of 100 nursing students, both male and female, from different academic years participated in the study. A structured questionnaire was utilized to collect demographic information, including gender, age, and academic year. The Athens Insomnia Scale (AIS) was employed to assess the prevalence of insomnia among participants. Results: The study findings revealed that most participants, constituting 70%, identified as male, while the remaining 30% identified as female. The analysis of insomnia status revealed that 37% reported no insomnia and 63% experienced insomnia. Conclusions: The findings highlight a diverse landscape of insomnia prevalence among nursing students, necessitating targeted interventions to promote sleep health.

Stress is a complex process when people interpret demands, restrictions, or possibilities as challenging their ability to cope effectively. Objective: To explore the correlation of academic stress with age and academic year among nursing students at the private nursing institute in Karachi, Pakistan. Methods: This cross-sectional analytical study was conducted from February to July 2023. A convenience sampling technique was utilized to approach study participants. A total of 206 nursing students were part of this study. Moreover, a reliable questionnaire was used for the data collection, consisting of demographic data, stress levels, contributing factors, and coping mechanisms. Results: This study revealed that 80.6% of nursing students had moderate and 14.1% had high academic stress. The study also identifies a significant association between academic year and age and academic stress (p-0.006) and (p-0.033). Conclusions: Educational institutions should develop specialized support programs because 80.6% of nursing students experience moderate academic stress and 14.1% experience high stress. Implement stress-management classes, counseling, and academic resources to assist students in handling the challenging tasks of their coursework. Students can be given valuable tools to handle academic stresses by including stress management techniques in the curriculum. These abilities include time management, study strategies, mindfulness, and relaxation techniques.

Background Dengue Viral Infection (DVI) has become endemic in Pakistan since the first major outbreak in Karachi in 1996. Despite aggressive measures taken by relevant authorities, Pakistan has been dealing with a worsening dengue crisis for the past two decades. DHF is severe form of dengue infection which is linked with significant morbidity and mortality. Early identification of severe dengue infections can reduce the morbidity and mortality. In this context we planned current study in which we find out the different factors related with DHF as well as clinical laboratory features of DHF and compare them to DF so that patients can be best evaluated for DHF and managed accordingly at admission. Methods Retrospective study conducted over a period of 6 years (2013-2018) in two tertiary care hospitals in Pakistan. Data were collected by using a pre-structured data collection form. Data were statistically analyzed to determine the clinical and laboratory characteristics of DVI and risk factors of dengue hemorrhagic fever (DHF). Results A total 512 dengue cases (34.05 +/- 15.08 years; Male 69.53%) were reviewed. Most common clinical manifestations of DVI were fever (99.60%), headache (89.1%), chills (86.5%), rigors (86.5%), myalgia (72.3%). Less common clinical manifestations were vomiting (52.5%), arthralgia (50.2%) and skin rashes (47.5%). Furthermore, nasal bleeding (44.1%), gum bleeding (32.6%), pleural effusion (13.9%) and hematuria (13.1%) were more profound clinical presentations among DHF patients. Mortality rate was 1.5% in this study. Logistic regression analysis indicated that delayed hospitalization (OR: 2.30) and diabetes mellitus (OR:2.71), shortness of breath (OR:2.21), association with risk groups i.e., living near stagnant water, travelling to endemic areas, living in endemic regions (OR:1.95), and presence of warning signs (OR:2.18) were identified as risk factors of DHF. Statistically we found that there is strong association of diabetes mellitus (DM

With the ever-growing power of generative artificial intelligence, deepfake and artificially generated (synthetic) media have continued to spread online, which creates various ethical and moral concerns regarding their usage. To tackle this, we thus present a novel exploration of the trends and patterns observed in real, deepfake and synthetic facial images. The proposed analysis is done in two parts: firstly, we incorporate eight deep learning models and analyze their performances in distinguishing between the three classes of images. Next, we look to further delve into the similarities and differences between these three sets of images by investigating their image properties both in the context of the entire image as well as in the context of specific regions within the image. ANOVA test was also performed and provided further clarity amongst the patterns associated between the images of the three classes. From our findings, we observe that the investigated deeplearning models found it easier to detect synthetic facial images, with the ViT Patch-16 model performing best on this task with a class-averaged sensitivity, specificity, precision, and accuracy of 97.37%, 98.69%, 97.48%, and 98.25%, respectively. This observation was supported by further analysis of various image properties. We saw noticeable differences across the three category of images. This analysis can help us build better algorithms for facial image generation, and also shows that synthetic, deepfake and real face images are indeed three different classes.

Unsupervised landmarks discovery (ULD) for an object category is a challenging computer vision problem. In pursuit of developing a robust ULD framework, we explore the potential of a recent paradigm of self-supervised learning algorithms, known as diffusion models. Some recent works have shown that these models implicitly contain important correspondence cues. Towards harnessing the potential of diffusion models for the ULD task, we make the following core contributions. First, we propose a ZeroShot ULD baseline based on simple clustering of random pixel locations with nearest neighbour matching. It delivers better results than existing ULD methods. Second, motivated by the ZeroShot performance, we develop a ULD algorithm based on diffusion features using self-training and clustering which also outperforms prior methods by notable margins. Third, we introduce a new proxy task based on generating latent pose codes and also propose a two-stage clustering mechanism to facilitate effective pseudo-labeling, resulting in a significant performance improvement. Overall, our approach consistently outperforms state-of-the-art methods on four challenging benchmarks AFLW, MAFL, CatHeads and LS3D by significant margins., Comment: Accepted in CVPR 2024

Unmanned aerial systems (UAS) rely on various avionics systems that are safety-critical and mission-critical. A major requirement of international safety standards is to perform rigorous system-level testing of avionics software systems. The current industrial practice is to manually create test scenarios, manually/automatically execute these scenarios using simulators, and manually evaluate outcomes. The test scenarios typically consist of setting certain flight or environment conditions and testing the system under test in these settings. The state-of-the-art approaches for this purpose also require manual test scenario development and evaluation. In this paper, we propose a novel approach to automate the system-level testing of the UAS. The proposed approach (AITester) utilizes model-based testing and artificial intelligence (AI) techniques to automatically generate, execute, and evaluate various test scenarios. The test scenarios are generated on the fly, i.e., during test execution based on the environmental context at runtime. The approach is supported by a toolset. We empirically evaluate the proposed approach on two core components of UAS, an autopilot system of an unmanned aerial vehicle (UAV) and cockpit display systems (CDS) of the ground control station (GCS). The results show that the AITester effectively generates test scenarios causing deviations from the expected behavior of the UAV autopilot and reveals potential flaws in the GCS-CDS.

Purpose - This study examines whether a firm's management earnings forecasts affect its technical innovation activities. Our study also examines whether the cost of debt plays a mediating role between the management earnings forecasts and the innovation nexus. Design/methodology/approach - We obtained data from 1032 Chinese non-financial firms listed on the Shanghai and Shenzhen stock markets from 2005 to 2022 (i.e., 18576 firm-year observations). We used various econometrics techniques, such as Heckman's (1979) two-stage selection method and two-stage least square, to examine the relationship between management earnings forecasts and the firm's technical innovation activities. Findings - We find a positive relationship between management earnings forecasts and the firms' technical innovation. We also find that the cost of debt mediates the relationship between management earnings forecast and technical innovation. Further analysis indicates that frequent earnings forecasts provide incremental information regarding a firm's future value and cash flows, thus reducing the volatility and uncertainty in cash flow calculations. Our findings are robust to several tests. Research Implications - Our study has implications for policymakers, practitioners, and high-level management of Chinese firms, enabling them to understand the relationship between management earnings forecasts and firms' innovation activities.

As robots grow more and more integrated into numerous industries, it is critical to comprehend how humans respond to their failures. This paper systematically studies how trust dynamics and system design are affected by human responses to robot failures. The three-stage survey used in the study provides a thorough understanding of human-robot interactions. While the second stage concentrates on interaction details, such as robot precision and error acknowledgment, the first stage collects demographic data and initial levels of trust. In the last phase, participants' perceptions are examined after the encounter, and trust dynamics, forgiveness, and propensity to suggest robotic technologies are evaluated. Results show that participants' trust in robotic technologies increased significantly when robots acknowledged their errors or limitations to participants and their willingness to suggest robots for activities in the future points to a favorable change in perception, emphasizing the role that direct engagement has in influencing trust dynamics. By providing useful advice for creating more sympathetic, responsive, and reliable robotic systems, the study advances the science of human-robot interaction and promotes a wider adoption of robotic technologies., Comment: 6 pages, 6 figures, 1 table, Ro-Man 2024