Potential Challenges Research Articles

Multilevel Democratic Iterative Coordination (MDIC): A Path for Socialism beyond the Market/Central Planning Dilemma

Interest in socialism is growing throughout the world. But “socialism” too often simply means belief in equality, democracy, and solidarity with working and oppressed people. That vision remains crucial; but we also need to re-develop the theory of a socialist system—not just a middle path, a “mixed economy” between the excesses of market-driven behavior (“capitalism”) and the inadequacies of central planning (“socialism”). A re-envisioned socialism can draw upon both historical experience and modern technology, to become a new and distinctive way of life, one that truly meets the awesome challenges of human potential.

A qualitative exploration of the experiences of transdermal alcohol sensor devices amongst alcohol service practitioners (South London, UK)

Background A qualitative exploration into the views of alcohol service staff on transdermal alcohol sensors (TAS) within three alcohol services in South London, UK. This study aims to assess the acceptability and feasibility of TAS implementation in alcohol services to provide treatment in clinical settings and identify potential challenges and solutions from the perspective of service providers. Methods Ten participants, in a patient-facing role with alcohol-related treatment, completed a semi-structured interview. Results Three core theoretical themes guided the analysis: perceived usefulness, perceived ease of use and attitudes toward use. Participants thought TAS could be useful as part of alcohol treatment in their service. They thought their service users may face some challenges using the TAS, (such as wearing the device; misplacing it, and/or remembering to remove and replace it for bathing). In general, participant attitudes toward TAS tended to be positive but there were some concerns about the cost and staff training. Participants believed their service users would be skeptical about wearing it, but that it could complement their treatment and motivate them toward their treatment goals. Conclusion Results support the acceptability and feasibility of TAS within alcohol services. Participants suggested potential methods of implementing TAS within their treatment plans which could benefit both staff and users. Participants were agreeable and willing to learn more about TAS including the practicalities of implementing TAS. TAS were seen as a potentially useful treatment facilitator, if implemented correctly with sufficiently motivated service users and if specific challenges were addressed.

Apolipoprotein E Genetic Testing in a New Age of Alzheimer Disease Clinical Practice.

The recent FDA approval of amyloid-lowering drugs is changing the landscape of Alzheimer disease (AD) clinical practice. Previously, apolipoprotein E (APOE) genetic testing was not recommended in the care of people with AD because of limited clinical utility. With the advent of amyloid-lowering drugs, APOE genotype will play an important role in guiding treatment recommendations. Recent clinical trials have reported strong associations between APOE genotype and the safety and possibly the efficacy of amyloid-lowering drugs. Therefore, a clinical workflow that includes biomarker and genetic testing should be implemented to provide patients with the opportunity to make informed decisions and instruct safety monitoring for clinicians. Pretest consent, education, and counseling will be an essential aspect of this process for patients and their family members to understand the implications of these tests and their results. Given that the approved amyloid-lowering drugs are indicated for patients with mild cognitive impairment or mild dementia with biomarker evidence of AD, biomarker testing should be performed before genetic testing and genetic testing should only be performed in patients interested in treatment with amyloid-lowering drugs. It is also important to consider other implications of genetic testing, including burden on and need for additional training for clinicians, the role of additional providers, and the potential challenges for patients and families.

Digitization Process of Archives: A Case Study of the Punjab Archives, Lahore

The digitization process of archives involves the conversion of physical documents, records, and artefacts into digital formats, enabling easier access, preservation, and dissemination of valuable historical information.The present study aimed to explore the digitization and preservation of archives: a case study of the Punjab Archives, Lahore. This study uses a qualitative research methodology in order to achieve the study's goals. An inductive approach was used to collect the data. Data was collected from the staff of the Punjab archives team, the project team and primary sources. Data was converted into written transcripts with the help of NVivo software. The benefits of digitization, such as improved accessibility, enhanced searchability, increased security, efficiency of accessing resources, and the protection of cultural heritage, are discussed, along with potential benefits, challenges, and solutions. The findings of the study revealed that the Punjab archives are the richest and oldest archives in the region. Seven million archives are available in different forms (documents, manuscripts, government records, coins, stamps, lithography, books, pictures, maps, etc.) in the Punjab Archives, and 114,592 documents have been selected for the initial phase of digitization. The purpose of the project was to preserve damaged, forged, and torn records in digital form.

AI Consciousness and Technological Advancement in Bangladesh's Higher Education: AI Awareness among the Learners

This comprehensive research article explores the transformative potential and multifaceted challenges of integrating Artificial Intelligence (AI) consciousness and technological advancements into the higher education system in Bangladesh. The study delves into various dimensions of this integration, including its implications for pedagogy, curriculum, institutional policy, and technological innovation. A particular emphasis is placed on addressing disparities in AI awareness among future students in Bangladesh's higher education system. The research adopts a balanced approach, juxtaposing the promise of technological advancements with critical concerns related to data privacy, educational equity, and cultural preservation. Through interdisciplinary analysis and a robust set of policy recommendations, the study posits that Bangladesh stands at a pivotal moment. It can either seize this technological epoch to elevate its higher education system to global standards while mitigating AI awareness disparities or risk exacerbating existing educational inequities.

Перспективы применения нейронных сетей для процедурной генерации игрового контента в киберспорте

This article provides an overview of research and practices on using neural network technologies in the field of procedural content generation for esports games. The authors explore the history, current approaches to using artificial neural networks in creating game elements, including levels, characters and scenarios, with the aim of enhancing the gaming experience and increasing the uniqueness of the virtual game world. The article covers various aspects of using neural network methods, such as generative models, autoencoders, generative adversarial networks, deep learning, and recurrent neural networks, for creating dynamic and unpredictable content. Examples of the successful implementation of these technologies in popular esports games are discussed, and potential challenges and issues related to applying neural networks in this context are explored. The authors discuss the prospects for the further development of neural network technologies in esports and offer recommendations for their optimal implementation. Overall, the article presents an analysis of the current state and future opportunities for using neural network approaches for procedural content generation in esports scenarios.

Forecasting some climate parameters of Türkiye using the SSP3-7.0 scenario for the years 2040–2059

This study employs the Coupled Model Inter-comparison Projects (CMIPs) and the Sixth phase of CMIPs (CMIP6) to unravel the multifaceted impacts of global climate change on climate of Türkiye. The CMIP6 data, fundamental to the Intergovernmental Panel on Climate Change (IPCC) Assessment Reports, forms the basis for projecting future climate scenarios, specifically under the medium-high reference scenario SSP3-7. Utilizing a suite of global climate models, including the innovative Multi-Model Ensemble (MME) approach, this study combines predictions to enhance the precision climate projections of Türkiye. Historical data spanning from 1951 to 2020 were subjected to rigorous statistical analysis, including descriptive statistics and regression analysis. The findings reveal an unequivocal upward trajectory in Türkiye’s annual mean temperature, with an accelerated pace in recent decades. Despite a lack of a significant long-term trend in annual precipitation from 1951 to 2020, the rate of change in precipitation is accelerating, indicating potential future challenges. Projections for 2040-2059 under the SSP3-7.0 scenario indicate a non-uniform increase in mean temperature across Türkiye, with the southern and western regions facing the most significant impact. This warming trend poses imminent threats to agriculture, altering crop yields and increasing the risk of heat stress for livestock. Additionally, the projected decrease in precipitation, alongside a surge in hot days and tropical nights, underscores the urgency for adaptive measures. As Türkiye navigates the complex terrain of climate change, this study provides valuable insights, emphasizing the significance of robust climate modeling for informed decision-making. The results underscore the imminent challenges Türkiye faces and emphasize the critical importance of proactive climate action on both national and global fronts.

Exploring Stresses in Mandibular Jawbone during Implant Insertion: A Three-Dimensional Explicit Dynamic Analysis

In dental implant insertion, an artificial foundation is prepared for the prosthetic device, which involves the surgical positioning of the implant in the jaw bone. The success of dental implants relies on the osseointegration process. The biomechanical factors, such as stress and strain, developed during the insertion affect the jawbone and its surroundings. In this current study, the stresses during the implant insertion in the mandibular jawbone bone are analyzed using three-dimensional explicit dynamic analysis, and the Cowper–Symonds model is implemented with the damage model. The implant’s design has a substantial impact on stress distribution within the cancellous bone during the insertion procedure. The stress variation takes place as the implant moves into the pre-drilled hole. This is because of the contact between the bone and the fixture on the implant. The upper edge of the predrilled site shows that the stresses are more at the crestal region of the implant due to surface area. There is a gradual increase in the stress level as the implant reaches the lower edge from the top edge. This is because of the concept of mechanical interlocking. Clinicians can use this information to anticipate and address potential stress-related challenges during implant placement.

Energy‐saving technologies and energy efficiency in the post‐COVID era

AbstractThe COVID‐19 pandemic made people reevaluate their energy consumption and energy efficiency. It held up a mirror to humanity's opportunistic and ruthless deployment of energy sources. As the city streets went empty and the international air traffic stopped altogether, people witnessed the significant drop in CO2 emissions, realized their dependence upon energy sources, and became aware of global climate change. In addition, with lockdowns and home offices, the demand for energy and the usual peak hours shifted offering a new perspective in energy consumption. The pandemic delivered a devastating blow to the human belief in having the constant and everlasting supply of energy that can be relied upon in everything. All these attracted the attention of researchers focusing on energy consumption and efficiency during the COVID‐19 pandemic. As a result, the vast body of academic literature on the topic burgeoned in the past four years yielding many exciting perspectives and viewpoints. Our paper conducts a comprehensive review of this body of literature employing the bibliometric network analysis of 12960 publications indexed in Web of Science database. It demonstrates the potential benefits and challenges associated with implementing energy‐saving technologies, altering energy consumption behavior, and implementing novel ICT solutions in a post‐COVID world. In addition, it highlights the importance of energy efficiency measures and examines novel technologies that can contribute to a sustainable and resilient energy future. Our findings emphasize the need for robust policies, technological advancements, and public engagement for fostering energy efficiency and mitigating environmental impacts of post‐pandemic energy consumption.

Identification of Surfactant Impact on a Monoclonal Antibody Characterization via HPLC-Separation Based and Biophysical Methods.

Surfactants, including polysorbates and poloxamers, play a crucial role in the formulation of therapeutic proteins by acting as solubilizing and stabilizing agents. They help prevent protein aggregation and adsorption, thereby enhancing the stability of drug substance and products., However, it is important to note that utilizing high concentrations of surfactants in protein formulations can present significant analytical challenges, which can ultimately affect the product characterization. In our study, we specifically investigated the impact of elevated surfactant concentrations on the characterization of monoclonal antibodies. We employed various analytical techniques including size-exclusion chromatography (SEC), capillary electrophoresis (CE-SDS), a cell based functional assay, and biophysical characterization. The findings of our study indicate that higher levels of Polysorbate 80 (PS-80) have adverse effects on the measured purity, biological activity, and biophysical characterization of biologic samples. Specifically, the elevated levels of PS-80 cause analytical interferences, which can significantly impact the accuracy and reliability of analytical studies. Our study results highlight a significant risk in analytical investigations, especially in studies involving the isolation and characterization of impurities. It is important to be cautious of surfactant concentrations, as they can become more concentrated during common sample manipulations like buffer exchange. Indeed, the research presented in this work emphasizes the necessity to evaluate the impact on analytical assays when there are substantial alternations in the matrix composition. By doing so, valuable insights can be gained regarding potential challenges associated with assay development and characterization of biologics with complex formulations.

Aging Increases Global Annual Food Greenhouse Gas Emissions up to 300 Million Tonnes by 2100.

The dietary preferences of the elderly population exhibit distinct variations from the overall averages in most countries, gaining increasing significance due to aging demographics worldwide. These dietary preferences play a crucial role in shaping global food systems, which will result in changed environmental impacts in the future such as greenhouse gas (GHG) emissions. We present a quantitative evaluation of the influence of population aging on the changes in GHG emissions from global food systems. To achieve this, we developed regional dietary coefficients (DCs) of the elderly based on the Global Dietary Database (GDD). We then reconciled the GDD with the dataset from the Food and Agriculture Organization of the United Nations (FAO) to calculate the food GHG emissions of the average population in each of the countries. By applying the DCs, we estimated the national food GHG emissions and obtained the variations between the emissions from aged and average populations. We employed a modified version of the regional integrated model of climate and the economy model (RICE) to forecast the emission trends in different countries based on FAO and GDD data. This integrated approach allowed us to evaluate the dynamic relationships among aging demographics, food consumption patterns, and economic developments within regions. Our results indicate that the annual aging-embodied global food GHG emissions will reach 288 million tonnes of CO2 equivalent (Mt CO2e) by 2100. This estimation is crucial for policymakers, entrepreneurs, and researchers as it provides insights into a potential future environmental challenge and emphasizes the importance of sustainable food production and consumption strategies to GHG emission mitigations associated with aging dietary patterns.

Integrating Student Reasoning and Mathematics in Instruction: A New Research Perspective

Traditional mathematics education prioritizes content transmission, often overlooking the intricate ways students’ reasoning and understanding are constructed. This research perspective proposes Integrating Student Reasoning and Mathematics in Instruction (ISRMI) as a novel approach that centers student thinking, integrating it seamlessly with formal mathematical concepts and procedures. ISRMI emphasizes tasks promoting explanation and justification, enabling educators to uncover and build upon existing student reasoning patterns. By challenging teacher-centered knowledge transfer, ISRMI empowers students to apply reasoning skills to solve problems, ultimately fostering deeper conceptual understanding and motivation in learning mathematics. While potential challenges lie in teacher training, curriculum design, and assessment of student reasoning, the potential benefits of improved problem-solving, engagement, and critical thinking skills necessitate further exploration and development of effective ISRMI implementation strategies. Design/Methodology/Approach: The research questions of this study are pursued using a systematic research analysis. We stress the importance of advancing research on integrating student reasoning and mathematics in instruction. We discuss many methods for incorporating student reasoning and mathematics into classroom instruction. We conducted this research by systematically searching and screening for relevant research articles through secondary sources and analyzing them to answer our scientific question. This research is a descriptive study. Secondary data was collected from various sources, such as magazines, journals, other publications, etc. This data was then analyzed and reviewed for inferences and conclusions. Findings/Result: Integrating student reasoning and mathematics in instruction can be the foundation for building a common locus between mathematics and reasoning abilities in educational practice.

Artificial intelligence in capsule endoscopy: development status and future expectations

In this review, we aim to illustrate the state-of-the-art artificial intelligence (AI) applications in the field of capsule endoscopy. AI has made significant strides in gastrointestinal imaging, particularly in capsule endoscopy - a non-invasive procedure for capturing gastrointestinal tract images. However, manual analysis of capsule endoscopy videos is labour-intensive and error-prone, prompting the development of automated computational algorithms and AI models. While currently serving as a supplementary observer, AI has the capacity to evolve into an autonomous, integrated reading system, potentially significantly reducing capsule reading time while surpassing human accuracy. We searched Embase, Pubmed, Medline, and Cochrane databases from inception to 06 Jul 2023 for studies investigating the use of AI for capsule endoscopy and screened retrieved records for eligibility. Quantitative and qualitative data were extracted and synthesised to identify current themes. In the search, 824 articles were collected, and 291 duplicates and 31 abstracts were deleted. After a double-screening process and full-text review, 106 publications were included in the review. Themes pertaining to AI for capsule endoscopy included active gastrointestinal bleeding, erosions and ulcers, vascular lesions and angiodysplasias, polyps and tumours, inflammatory bowel disease, coeliac disease, hookworms, bowel prep assessment, and multiple lesion detection. This review provides current insights into the impact of AI on capsule endoscopy as of 2023. AI holds the potential for faster and precise readings and the prospect of autonomous image analysis. However, careful consideration of diagnostic requirements and potential challenges is crucial. The untapped potential within vision transformer technology hints at further evolution and even greater patient benefit.

On the use of RWD in support of regulatory submission in drug development

ABSTRACT For the approval of a drug product, the United States Food and Drug Administration requires substantial evidence (SE) regarding effectiveness and safety of the test drug to be provided. In recent years, the use of real-world data in support of regulatory submission of pharmaceutical development has received much attention, and real-world evidence (RWE) is treated as complementary to SE by evaluating the real-world performance of the test treatment. In this article, we start by summarizing current regulatory perspectives on drug evaluation and some potential challenges in using RWE. To test for superiority in co-primary endpoints, a two-stage hybrid RCT/RWS adaptive design that combines randomized control trial for providing SE and real-world study for generating RWE is proposed. We use superiority in effectiveness and non-inferiority in safety as an example to illustrate how to implement this design. Numerical studies have shown that the proposed design has merits in reducing the required sample size compared with traditional co-primary endpoint tests while maintaining statistical power and controlling type I error inflation. The proposed design can be implemented in drug development considering co-primary endpoints, especially for oncology and rare disease drug development.

Open Science and the impact of Open Access, Open Data, and FAIR publishing principles on data-driven academic research: Towards ever more transparent, accessible, and reproducible academic output?

Contemporary evidence-informed policy-making (EIPM) and societies require openly accessible high-quality knowledge as input into transparent and accountable decision-making and informed societal action. Open Science1 supports this requirement. As both enablers and logical consequences of the paradigm of Open Science, the ideas of Open Access, Open Data, and FAIR publishing principles revolutionise how academic research needs to be conceptualised, conducted, disseminated, published, and used. This ‘academic openness quartet’ is especially relevant for the ways in which research data are created, annotated, curated, managed, shared, reproduced, (re-)used, and further developed in academia. Greater accessibility of scientific output and scholarly data also aims at increasing the transparency and reproducibility of research results and the quality of research itself. In the applied ‘academic openness quartet’ perspective, they also function as remedies for academic malaises, like missing replicability of results or secrecy around research data. Against this backdrop, the present article offers a conceptual discussion on the four academic openness paradigms, their meanings, interrelations, as well as potential benefits and challenges arising from their application in data-driven research.

Targeting the gut microbiota to enhance the antitumor efficacy and attenuate the toxicity of CAR-T cell therapy: a new hope?

Chimeric antigen receptor (CAR) -T cell therapy has achieved tremendous efficacy in the treatment of hematologic malignancies and represents a promising treatment regimen for cancer. Despite the striking response in patients with hematologic malignancies, most patients with solid tumors treated with CAR-T cells have a low response rate and experience major adverse effects, which indicates the need for biomarkers that can predict and improve clinical outcomes with future CAR-T cell treatments. Recently, the role of the gut microbiota in cancer therapy has been established, and growing evidence has suggested that gut microbiota signatures may be harnessed to personally predict therapeutic response or adverse effects in optimizing CAR-T cell therapy. In this review, we discuss current understanding of CAR-T cell therapy and the gut microbiota, and the interplay between the gut microbiota and CAR-T cell therapy. Above all, we highlight potential strategies and challenges in harnessing the gut microbiota as a predictor and modifier of CAR-T cell therapy efficacy while attenuating toxicity.

Robotic Process Automation in Artificial Intelligence

This paper explores the symbiotic relationship between Robotic Process Automation (RPA) and Artificial Intelligence (AI) and their collective impact on streamlining and optimizing various business processes. We delve into the integration of AI technologies, such as machine learning and natural language processing, with Robotic Process Automation to create intelligent automation solutions. Furthermore, it examines how the infusion of Artificial Intelligence into RPA empowers systems to adapt and learn, fostering adaptability and agility within organizations. The abstract concludes by highlighting the potential benefits, challenges, and future prospects of this amalgamation, emphasizing the transformative impact on businesses in the era of intelligent automation.

Telemedicine for Routine Prenatal Care: Use and Satisfaction During the COVID-19 Pandemic.

Telemedicine use in prenatal care has greatly expanded without substantial research. Optimizing user experiences can increase telemedicine's utilization to support care access. The purpose of this study was to explore patient and provider experiences using telemedicine for routine prenatal care during the COVID-19 pandemic, identifying factors affecting its utilization and satisfaction. In this mixed methods study, online surveys and semi-structured interviews with pregnant and postpartum patients and perinatal providers across the United States were used to explore experiences with telemedicine and prenatal care during the COVID-19 pandemic. Data were collected from July to December 2021. Survey findings were analyzed using descriptive and inferential statistics, and interviews were thematically coded and analyzed, followed by mixed methods analysis. Results of 946 surveys (750 patients and 196 providers) and 30 interviews (15 patients and 15 providers) met inclusion for analysis. Telemedicine was utilized by 42% of patients and 72% of perinatal provider participants. The primary reason patients did not use telemedicine was because it was not offered. Patients and providers who did not use telemedicine expressed the following main concerns with virtual care: uncertainty about care quality, particularly when blood pressure and the fetal heart rate were not assessed, and potential challenges with developing trusting patient-provider relationships. Patients and providers who used telemedicine rated their experience as mild to moderate satisfaction across the 6 Telehealth Usability Questionnaire domains. Satisfaction scores were not dependent on whether physical examination components were included in virtual visits. Providing patients with the choice to use telemedicine as needed or combined with in-person visits for routine prenatal care may increase care utilization. Although not directly linked with satisfaction, interest in using telemedicine would likely increase for patients and providers concerned with care quality if blood pressure and fetal heart rate are assessed during virtual visits.

Striding Toward Cardiovascular Health: The Impact of Step Counts on Heart Wellness.

In an era characterized by sedentary lifestyles, cardiovascular diseases pose a significant global health challenge. As preventive healthcare strategies evolve, this article explores the tangible and accessible metric of step counts and their implications for cardiovascular health. The review provides insights into potential benefits, challenges, and future directions in promoting physical activity for heart wellness.

Processes and mechanisms in remediation of aqueous chromium contamination by sulfidated nano-scale zerovalent iron (S-nZVI): Experimental and computational investigations

Sulfidated nano-scale zerovalent iron (S-nZVI) has emerged as an advanced functional nanomaterial for efficiently remediating Cr(VI) contamination in aqueous environments. However, there is an insufficient understanding of its coherent process, removal pathway, and hydrochemical reactive mechanisms, presenting potential challenges for its future environmental applications. To address this gap, this study successfully synthesized S-nZVI through a chemical precipitation method and effectively applied it for the removal of Cr(VI). Additional characterization revealed that the removal of Cr(VI) followed a sequence of rapid chemisorption and intraparticle diffusion processes, concomitant with an increase in pH and a decrease in oxidation-reduction potential. The remediation mechanism encompassed a synergistic reduction of Cr(VI) to Cr(III) and simultaneous immobilization via Cr2FeO4 coprecipitation. The highest Cr(VI) removal capacity of 75 mg/g was attained during dynamic removal experiments in the sand column packed with S-nZVI. Further computational analysis, employing density functional theory calculations based on the experimental data, revealed the involvement of multiple molecular orbitals of Cr(VI) in the removal process. It also elucidated a step-by-step reduction pathway for Cr(VI) characterized by decreasing free energy. These findings provide evidence-based insights into Cr(VI) remediation using S-nZVI and can serve as valuable technical support for future environmental management of heavy metals.