Comprehensive Survey Research Articles

Assessing the current landscape of AI and sustainability literature: identifying key trends, addressing gaps and challenges

The United Nations’ 17 Sustainable Development Goals stress the importance of global and local efforts to address inequalities and implement sustainability. Addressing complex, interconnected sustainability challenges requires a systematic, interdisciplinary approach, where technology, AI, and data-driven methods offer potential solutions for optimizing resources, integrating different aspects of sustainability, and informed decision-making. Sustainability research surrounds various local, regional, and global challenges, emphasizing the need to identify emerging areas and gaps where AI and data-driven models play a crucial role. The study performs a comprehensive literature survey and scientometric and semantic analyses, categorizes data-driven methods for sustainability problems, and discusses the sustainable use of AI and big data. The outcomes of the analyses highlight the importance of collaborative and inclusive research that bridges regional differences, the interconnection of AI, technology, and sustainability topics, and the major research themes related to sustainability. It further emphasizes the significance of developing hybrid approaches combining AI, data-driven techniques, and expert knowledge for multi-level, multi-dimensional decision-making. Furthermore, the study recognizes the necessity of addressing ethical concerns and ensuring the sustainable use of AI and big data in sustainability research.

Understanding life cycle of parasitic weed Phelipanche ramosa infesting Brassica juncea in India: new host species and seed coat structure

ABSTRACT Broomrape (Phelipanche ramosa) is an obligate root parasitic plant that is known to infest many important crops. It is emerging as a serious biotic threat for Brassica juncea cultivation in India. There is very limited information available about broomrape species and its infestation in B. juncea. Hence, the present study encompassed a comprehensive five-year field survey spanning from 2018 to 2023 of 47 different B. juncea fields in the states of Rajasthan and Haryana in India. The level of broomrape infestation varied from season to season and field to field. In the B. juncea fields, broomrape with blue/violet color corolla, along with occasionally white color type were also noticed. The hairy anther, corolla shape and use of mitochondrial DNA-specific molecular markers revealed that both these broomrape types belong to Phelipanche ramosa. Scanning electron microscopy (SEM) analysis showed that P. ramosa seeds have varying shapes and seed coat have fibrillar periclinal cell wall. In addition to all the known host species for P. ramosa till date, we also identified a new host, a wild Brassicaceae weed species; Lepidium didymum in Haryana. The presence of an alternative weed host may help P. ramosa survive even in the absence of major crop host species. Overall, the present study revealed some insights into the P. ramosa-B. juncea host-parasite complex and its effect on B. juncea which could be further investigated in more detail.

92 Factors influencing bull selection in Illinois beef producers: Analysis of retained and non-retained ownership producers

Abstract The objective was to understand decision-making factors for bull selection of producers participating in the Illinois Performance Tested (IPT) bull sale. The IPT bull sale has served Illinois beef producers for the last 54 yr offering around 50 bulls annually. A comprehensive survey targeted a diverse group of beef producers that had previously attended the IPT bull sale. The survey was developed through Qualtrics and provided to producers via email. The survey consisted of 40 questions based on four categories: farm location, herd demographics, bull selection criteria, and feedback from previous experiences at the IPT bull sale. There were a variety of question types including multiple choice, select all that apply, open-ended, ranking of importance, and select on a scale from one to ten. Specific responses on bull selection criteria focused on expected progeny differences and functional traits. Survey results were grouped based on whether producers retained ownership of feedlot cattle; regularly retained ownership (RET; n = 12) and never retained ownership (NRET; n = 15). Data were analyzed with the MIXED and GLIMMIX procedures of SAS 9.4. For RET and NRET producers, there were no observed differences in mature cow body weight and herd size (P ≥ 0.42). Most producers responded that they calved in March and April. Producer groups did not differ (P = 0.99) in the percentage of respondents retaining replacement heifers, as 66% of RET and NRET producers retained replacements. However, RET producers tended to be more likely (P = 0.07) to regularly sell freezer beef. Specifically, 75% of RET producers regularly sell freezer beef compared with 13% of NRET producers. Additionally, RET producers tended to prioritize (P = 0.1) carcass trait expected progeny differences in bull selection more than NRET producers (66 vs 33%, respectively). There was no difference (P = 0.2) in the percentage of respondents that selected the weaning weight expected progeny difference in their top three traits. However, NRET producers were much more likely (P < 0.01) to prioritize yearling weight expected progeny difference in their bull selection decisions. Specifically, 66% of RET producers used yearling weight expected progeny difference in their bull selection compared with 0% of NRET producers. Lastly, there was no difference (P = 0.61) in the percentage of respondents who included docility in their top three functional traits. In conclusion, bull buyers at the IPT bull sale that regularly retain ownership of feedlot cattle were more likely to prioritize expected progeny differences for yearling weight and carcass traits while functional traits priorities were similar to producers that did not retain ownership of feedlot cattle.

Pre‐service teachers' inclination to integrate AI into STEM education: Analysis of influencing factors

AbstractIn the ever‐evolving AI‐driven education, integrating AI technologies into teaching practices has become increasingly imperative for aspiring STEM educators. Yet, there remains a dearth of studies exploring pre‐service STEM teachers' readiness to incorporate AI into their teaching practices. This study examined the factors influencing teachers' willingness to integrate AI (WIAI), especially from the perspective of pre‐service STEM teachers' attitudes towards the application of AI in teaching. In the study, a comprehensive survey was conducted among 239 pre‐service STEM teachers, examining the influences and interconnectedness of Technological Pedagogical Content Knowledge (TPACK), Perceived Usefulness (PU), Perceived Ease of Use (PE), and Self‐Efficacy (SE) on WIAI. Structural Equation Modeling (SEM) was employed for data analysis. The findings illuminated direct influences of TPACK, PU, PE, and SE on WIAI. TPACK was found to directly affect PE, PU, and SE, while PE and PU also directly influenced SE. Further analysis revealed significant mediating roles of PE, PU, and SE in the relationship between TPACK and WIAI, highlighting the presence of a chain mediation effect. In light of these insights, the study offers several recommendations on promoting pre‐service STEM teachers' willingness to integrate AI into their teaching practices. Practitioner notesWhat is already known about this topic? The potential of AI technologies to enrich learning experiences and improve outcomes in STEM education has been recognized. Pre‐service teachers' willingness to integrate AI into teaching practice is crucial for shaping the future learning environment. The TAM and TPACK frameworks are used to analyse teacher factors in technology‐supported learning environments. Few studies have been conducted for examining factors of pre‐service teachers' willingness to integrate AI into teaching practices in the context of STEM education. What this paper adds? A survey was designed and developed for exploring pre‐service STEM teachers' WIAI and its relationships with factors including TPACK, PE, PU, and SE. TPACK, SE, PU, and PE have direct impact on pre‐service STEM teachers' WIAI. SE, PU, and PE have been identified as mediating variables in the relationship between TPACK and WIAI. Two sequential mediation effects, TPACK → PE → SE → WIAI and TPACK → PU → SE → WIAI, among pre‐service STEM teachers were further identified. Implications of this study for practice and/or policy Pre‐service STEM teachers are encouraged to explore and utilize AI technology to enhance their confidence and self‐efficacy in integrating AI into teaching practices. Showcasing successful cases and practical experiences is essential for fostering awareness of AI integration in STEM education. It is recommended to introduce AI education courses in teacher training programs. Offering internship and practicum opportunities related to AI technologies can enhance their practical skills in integrating AI into education.

Robust language-based mental health assessments in time and space through social media

In the most comprehensive population surveys, mental health is only broadly captured through questionnaires asking about “mentally unhealthy days” or feelings of “sadness.” Further, population mental health estimates are predominantly consolidated to yearly estimates at the state level, which is considerably coarser than the best estimates of physical health. Through the large-scale analysis of social media, robust estimation of population mental health is feasible at finer resolutions. In this study, we created a pipeline that used ~1 billion Tweets from 2 million geo-located users to estimate mental health levels and changes for depression and anxiety, the two leading mental health conditions. Language-based mental health assessments (LBMHAs) had substantially higher levels of reliability across space and time than available survey measures. This work presents reliable assessments of depression and anxiety down to the county-weeks level. Where surveys were available, we found moderate to strong associations between the LBMHAs and survey scores for multiple levels of granularity, from the national level down to weekly county measurements (fixed effects β = 0.34 to 1.82; p < 0.001). LBMHAs demonstrated temporal validity, showing clear absolute increases after a list of major societal events (+23% absolute change for depression assessments). LBMHAs showed improved external validity, evidenced by stronger correlations with measures of health and socioeconomic status than population surveys. This study shows that the careful aggregation of social media data yields spatiotemporal estimates of population mental health that exceed the granularity achievable by existing population surveys, and does so with generally greater reliability and validity.

Harnessing the Power of Cheminformatics Tools for Accelerated Drug Discovery in the Digital Era

Cheminformatics serves as a foundation in present day medicate disclosure, encouraging the productive utilization of broad chemical information storehouses and empowering educated decision-making forms. This comprehensive survey investigates the differing applications of cheminformatics all through the sedate disclosure pipeline, extending from target distinguishing proof and lead optimization to pharmacokinetic profiling and harmfulness forecast. At the onset of sedate disclosure, amid target recognizable proof and approval, cheminformatics apparatuses play a significant part in analyzing natural information to recognize potential targets and comprehend their inclusion in infection pathways. The comprehension and expectation of solvency stand as fundamental contemplations over different logical spaces, affecting basic segments such as medicate advancement, natural hazard appraisals, and materials building. This thinks around burrows into the creative utilize of machine learning (ML) models to expect the liquid dissolvability of normal particles, promoting a point-by-point examination of a dataset comprising 1144 particles. Through fastidious pre-processing, highlight diminishing, and cautious examination, the inquire around considers the common sense of orchestrated ML calculations, checking Subjective Timberland (RF) and Additional Tree (ET), in dissolvability want. The consider places fundamental complement on interpretability, laying out how key descriptors influence dissolvability gauges. Besides, it looks at the solidification of hyperparameter tuning and explainability procedures to update appear execution and straightforwardness. By comparing the shows of assorted ML models and tending to challenges related to complexity and interpretability, this examines underscores the reasonability of ML in foreseeing solubilities over diverse settings.

Optimal load forecasting and scheduling strategies for smart homes peer-to-peer energy networks: A comprehensive survey with critical simulation analysis

Optimal load forecasting and scheduling strategies for smart homes peer-to-peer energy networks: A comprehensive survey with critical simulation analysis

Surveillance and detection of Haemaphysalis longicornis (Acari: Ixodidae) in protected areas from Georgia, USA.

The invasion of the Asian longhorned tick, Haemaphysalis longicornis Neumann, into the United States poses a significant ecological, veterinarian, and public health threat. We conducted a comprehensive tick survey using standard tick flagging protocol for collection over 3 field seasons, March-August, and 56 surveyed sites to identify the presence of H. longicornis in the native ecosystem and prove its establishment according to USDA criteria. Of the total 56 state parks and wildlife management areas (WMA) surveyed, only one was found to be invaded by H. longicornis; detection of H. longicornis occurred at Buck Shoals Wildlife Management area in White County, GA. This site is maintained by the state of Georgia, has no agricultural animals present, and hosts a large white-tailed deer population. After the initial detection of H. longicornis in 2022, an additional field season occurred in 2023, where H. longicornis was confirmed as established based on USDA criteria. The increase in H. longicornis populations from 2021 to 2023 at Buck Shoals WMA points to the rapid spread of this tick within the environment. Our findings provide evidence of the rapid establishment of H. longicornis in the southern edge of suitability for this tick andwithin the native ecosystem beyond farmlands and private land.

An updated survey of freshwater fishes within Letchworth State Park and surrounding area's of the Genesee River.

The goal of this study was to gather information about freshwater fishes in Letchworth State Park (42.615275° N, -77.992825° W), a portion of New York State-owned land located in the Genesee River Watershed that lacks known data about its fish diversity. Fish collection took place between 2017 and 2019 in the Genesse River upstream and downstream of the falls using electrofishing, gill, hoop, and seine netting. This was the first attempt at a comprehensive survey of this portion of the river, which allowed for a baseline to be established regarding fish biodiversity in the region. The updated total number of species found in this portion of the Genesee River was 25, 22 of which were newly identified downstream of the falls in Letchworth State Park. We encourage further collection and continuation of this survey with consistent sampling techniques to raise awareness about the importance of freshwater fish diversity in stream ecosystems across the globe.

"An Investigation of Privacy and Security Concerns in the Internet of Things: A Comprehensive Survey"

"An Investigation of Privacy and Security Concerns in the Internet of Things: A Comprehensive Survey"

Evaluating the Impact of Financial Incentives for Employees of the Libyan Rural Bank

This study aimed to clarify the impact and importance of types of financial incentives, and to evaluate the current status of the incentive system for bank employees, which included various categories of employees in the general administration of the Libyan Rural Bank, so that the problems and obstacles they face are identified, and to present a package of proposals and recommendations that can help increase.Individual performance and improving and developing the incentive system. The study was conducted on 71 individuals working at the bank, who occupy most of the senior, intermediate and lower administrative positions working in the general administration of the Libyan Bank. Therefore, a comprehensive survey was preferred over selecting a random sample representative of the research community. The most important results revealed by this study are the presence of a strong correlation between the general performance variable and other variables, and it is arranged in descending order as follows: material incentives, general satisfaction, then training and promotions. There is no correlation between the general performance variable and the variables of the impact of material and moral incentives on employees and attention to them. The perception of the study community's vocabulary was positive regarding phrases in the field of general job performance, phrases in the field of material incentives, and phrases in the field of the impact of material and moral incentives on employees. There are no statistically significant differences between the vocabularies categories of the research community regarding phrases in all fields related to gender, age, marital status, number of family members, educational level, housing, years of experience, or income, while there are only differences in the field of material incentives belongs to gender.

Understanding value of digital service delivery by governments in Mexico

Over the years, governments have leveraged various technologies to streamline internal operations for greater efficiency and to create value through digitally delivered public services (i.e., digital services) for several stakeholders, including citizens. While prior studies have contributed to understanding the institutional and organizational determinants of government digital services, much less is known about their utilization and the actual public value they generate from the perspective of the citizen, particularly in developing countries. Some research on technology, economic, and other social divides even suggests that both the use and value of digital services are potentially limited. In this paper, we apply the Delone and McLean model, a well-established information systems theory, to examine citizens' use of government digital services and their perceptions of public value derived from such use. Based on data from a comprehensive national phone survey across 32 Mexican States with 4300 respondents, our structural equation modeling reveals that system quality is the most significant predictor of use and user satisfaction with digital services. Furthermore, use and user satisfaction lead to public value as measured by the conveniences, flexibilities, and process simplifications the system affords. Our study contributes to digital government literature by using the concept of public value as a measure of digital government services' impact and success from the perspective of the citizens.

New Perceptions of Ancient Commerce Driven by Underwater Ancient Site Investigations: A Case Study of Xinfeng River Basin

In the 1950s and 1960s, to address the flooding issues and power shortage that hindered national construction, the Xinfeng River hydropower plant was planned and built to prevent floods, store water, and generate electricity. Consequently, many ancient ruins in the study area were drowned, including ancient post roads, channels, villages, towns, bridges, and other relic sites. By checking historical data and adopting integrated underwater acoustic detection, we conducted a comprehensive cultural-relics survey on the flooded area under Wanlv Lake in the Xinfeng River Basin. A side-scan sonar detection of the underwater relics within the flooded area confirmed the spatial distribution of cultural relics in the Xinfeng River Basin. It portrayed ancient people’s production and life scenarios, outlined the migration and trade history within the region and beyond, and contributed to the enrichment of the literature and understanding of ancient shipping and trade in the basin.

Party Realignment: Ethnic Identity versus Egocentrism among Malaysian Voters

This study investigates the dynamics of voting intention concerning party realignment among voters in Malaysia using a Theory of Reasoned Action-based model. It delves into the roles of attitudes and subjective norms in shaping party preferences and aligns with quantitative methodology. A comprehensive self-administered survey questionnaire engaged 450 participants from diverse ethnic backgrounds in the Batang Kali State Constituency to elucidate party realignment complexities. They are chosen using stratified random sampling, based on a race proportion of 5:1:1. The findings reveal that voter attitudes wielded a more significant impact than subjective norms associated with ethnic identity. This outcome underscores the pivotal role of attitudes in influencing decision-making, while the influence of subjective norms remains limited. The research highlights the subjective norm's role in a multicultural context, clarifying that it is not the primary catalyst for party realignment. Instead, personal beliefs (people's egocentric behaviour) play a substantial role in shaping voter attitudes. These findings contribute to a deeper understanding of the interplay between subjective norms (ethnic identity), attitudes (egocentrism), and party realignment within Malaysia's diverse social landscape. Moreover, they hold significant implications for formulating effective political strategies and government policies within a multicultural society.

Forum: The Past, Present, and Futures of Modern British History

Abstract For the first issue of the renamed journal, Modern British History co-editor Erik Linstrum convened a group of scholars to reflect on the past, present, and possible futures of the field. The resulting contributions make no claim to provide a comprehensive or representative survey. Rather, they offer a variety of perspectives on where modern British history has been and where it might be going. Several contributions, written by former editors of Twentieth Century British History, drawn on the history of the journal as a way of thinking about the direction of the field and its subfields. Others consider the place of modern Britain in the wider discipline of history, grappling with questions of temporality and embodiment; the institutional and material contexts of scholarship; the role of national histories in a transnational world; and the response of historical writing to epidemiological, humanitarian, and ecological crisis. The sequence of contributions mirrors the evolution of the journal since its founding in 1990, beginning with political history and gradually encompassing a much broader range of subjects and methodologies as well as an expanded geographical ambit. Here are archive stories, pleas for new subjects, roadmaps for new approaches to old subjects, and attempts to identify master narratives. Taken together, these contributions demonstrate that modern British history has many houses—which is both a sign of intellectual vitality and a challenge for anyone wishing to generalize about the ‘state of the field’. If British modernity remains an abundant resource for ‘thinking with’, its contours and frontiers are tantalizingly up for grabs.

Sociodemographic characteristics help predict Canadian urbanites’ acceptability of restaurant food environment policies

IntroductionPublic acceptability of policies aiming to improve the healthfulness of the restaurant food environment is key to their successful implementation. Yet, the acceptability of these policies remains ambiguous, especially across diverse population groups. This study aims to examine associations between sociodemographic characteristics and acceptability levels of three restaurant food environment policies of varying degrees of intrusiveness across 17 urban Canadian jurisdictions.MethodsData was extracted from the THEPA survey, one of the largest and most jurisdictionally comprehensive surveys on intervention acceptability (N = 27,162). To account for potential jurisdictional differences in acceptability, for each policy, multilevel logistic regression models were developed.ResultsResults indicated that, on average, those in complete agreement with the implementation of the targeted policies represented 20.3%–26.9% of participants, depending on the policy. Acceptability varied according to policy intrusiveness, jurisdiction, and participants’ sociodemographic characteristics. Women, individuals with household incomes of &amp;lt;$40,000/year, immigrants from a high-income country other than Canada, and Indigenous peoples were more likely to express complete agreement with all policies, versus men, participants with household incomes of $40,000–$79,999/year, Canadian-born individuals, and non-Indigenous individuals. A lower likelihood of expressing complete agreement with all policies was observed for those with a $80,000–$119,999/year household income, versus those with a $40,000–$79,999/year household income. For selected policies and models, other sociodemographic characteristics (i.e., age, education, and being born in a low-or middle-income country) predicted acceptability. The examined sociodemographic characteristics did not explain jurisdictional differences in acceptability.DiscussionUnderstanding jurisdictional differences in acceptability merits further research. Policy implications involve engaging diverse sociodemographic groups in conversations about acceptable ways in which their restaurant food environment could be rendered more healthful.

Eye Abnormalities Detection Using Machine Learning

Abstract: The most common cause of irreversible visualimpairment and incapacity around the world is glaucoma. In any case, the larger part of patients are uninformed of their condition. Despite headways in innovation, diagnosing the movement of glaucoma remains a challengein clinical hone. Observing glaucoma movement ordinarilyincludes a manual examination of the retinal layer, which is time-consuming. This issue can be tended to by computerizing glaucoma conclusions utilizing profound learning and machine learning strategies. A comprehensive survey of various computerized glaucoma forecast and discovery strategies was conducted in this orderly audit. Over 100 papers on machine learning (ML) strategies were analyzed, covering outlines, strategies, goals, execution, benefits, and downsides, with clear charts and tables. Machine learning approaches such as the Resnet calculation and Convolutional Neural Organize are commonly utilized for diagnosing and foreseeing glaucoma. Through precise audits, the most solid strategy for glaucoma discovery and forecast can be distinguished to improve future treatments. Cataracts are the driving cause of visual This ponder givesa comprehensive outline of current headways in machine learning strategies for assessing and classifying cataracts utilizing ophthalmic pictures. The study highlights the qualities and shortcomings of existing investigations and addresses challenges related to independent cataract classification and evaluating utilizing machine learningprocedures, advertising potential arrangements forencourage examination

Impact of Women\'s Participation in Local Governance on Socio-Economic Development: A Case Study of Panchayati Raj Institutions in Maharashtra

Abstract: The participation of women in local governance, particularly in Panchayati Raj Institutions (PRIs), is increasingly recognized as crucial for fostering socio-economic development. This study focuses on the state of Maharashtra, India, examining the impact of women’s involvement in PRIs on various socio-economic indicators. Utilizing empirical data from a comprehensive survey conducted across multiple districts, the study analyzes the correlation between women’s representation in PRIs and key development parameters. Findings reveal a positive association between higher levels of women’s participation in PRIs and improvements in socio-economic indicators. Specifically, districts with greater female representation in PRIs demonstrate enhanced access to basic services such as healthcare, education, and sanitation. For instance, districts with more than 50% female representation in PRIs saw a 25% increase in primary healthcare coverage compared to districts with lower female representation.

Morphological and molecular characterization of Heterodera ripae, a new record cyst nematode in the rhizosphere soil of Fagopyrum esculentum

Numerous plant parasitic nematodes (PPNs) have the potential to inflict considerable damage on agricultural crops. Through a comprehensive survey aimed at identifying PPNs affecting crops, cyst nematodes were isolated from the rhizosphere soil of buckwheat (Fagopyrum esculentum). Employing both molecular and morphological techniques, this cyst nematode was conclusively identified as Heterodera ripae. Notably, this represents the first documented occurrence of this particular cyst nematode species within the rhizosphere soil of F. esculentum.

Update on the composition and distribution of the mosquito fauna (Diptera: Culicidae) in Cabo Verde, a country at risk for mosquito-borne diseases.

Mosquitoes play a critical role as vectors of pathogens affecting both humans and animals. Therefore, understanding their biodiversity and distribution is crucial to developing evidence-based vector control strategies. The current study updated the composition and distribution of mosquito species through a comprehensive survey of all municipalities of Cabo Verde. From October 2017 to September 2018, mosquito larvae and pupae were collected from 814 aquatic habitats. Anopheles gambiae (Giles, 1902) and Culex pipiens (Linnaeus, 1758) complexes were subjected to PCR-based techniques for sibling species identification. Ten mosquito species from 5 genera were identified: Aedes aegypti (Linnaeus, 1762), Aedes caspius (Pallas, 1771), Anopheles arabiensis (Patton, 1905), Anopheles pretoriensis (Theobald, 1903), Culex bitaeniorhynchus (Giles, 1901), Cx. pipiens, Culex quinquefasciatus (Say, 1823), Culex tritaeniorhynchus (Giles, 1901), Culiseta longiareolata (Macquart, 1838), and Lutzia tigripes (de Grandpre & de Charmoy, 1901). Santiago Island reported the highest number of species (n = 8). Ae. aegypti and Cx. quinquefasciatus were the most widely distributed species across the country. An. arabiensis was the sole species identified within the An. gambiae complex. The findings from our study will help guide health policy decisions to effectively control mosquito-borne diseases.