bluuebunny/crossref_metadata_2025 huggingface dataset:
Finding Oasis Cold Island Footprints Based on a Logistic Model—A Case Study in the Ejina Oasis
Authors: Wu Wentong , Chen Rensheng
Published: August 2024

Oases play a crucial role in arid regions within the human–environmental system, holding significant ecological and biological importance. The Oasis Cold Island Effect (OCIE) represents a distinct climatic feature of oases and serves as a vital metric for assessing oasis ecosystems. Previous studies have overlooked the spatial extent of the Oasis Cold Island Effect (OCIE), specifically the boundary delineating areas influenced and unaffected by oases. This boundary is defined as the Oasis Cold Island Footprint (OCI FP). Utilizing Logistic modeling and MODIS data products, OCI FPs were calculated for the Ejina Oasis from 2000 to 2019. The assessment results underscore the accuracy and feasibility of the methodology, indicating its potential applicability to other oases. Spatial and temporal distributions of OCI FPs and the intensity of the Oasis Cold Island Effect Intensity (OCIEI) in the Ejina Oasis were analyzed, yielding the following findings: (1) OCI FP area and complexity were smallest in summer and largest in autumn. (2) Over the period 2000–2019, OCI FPs exhibited a pattern of increase, decrease, and subsequent increase. (3) OCIEI peaks in summer and reaches its lowest point in winter. Lastly, the study addresses current limitations and outlines future research objectives.
BresNet: Applying Residual Learning in Backpropagation Neural Networks to Predict Ground Surface Concentration of Primary Air Pollutants
Authors: Shi Zekai , Zhang Meng , Han Mei , Zhang Yaowei , Ma Guodong , Ren Haoyuan
Published: August 2024

Monitoring air pollution is important for human health and the environment. Previous studies on the prediction of air pollutants from satellite images have employed machine learning, yet there are few enhancements to the constructure of model. Moreover, the existing models have been successful in predicting pollutants like PM2.5, PM10, and O3. They have not been as effective in predicting other primary air pollutants. To improve the overall prediction performance of the existing model, a novel residual learning backpropagation model, abs. as BresNet, has been proposed in this research. This model has revealed the availability to precisely predict the ground-surface concentration of the six primary air pollutants, PM2.5, PM10, O3, NO2, CO, and SO2, based on the satellite imagery of MODIS AOD. Two of the most commonly used machine learning models so far, viz. the multilayer backpropagation neural network (MLBPN) and random forest (RF), were employed as the control. In the conducted experiments, the proposed BresNet model demonstrated significant improvements of 18.75%/31.94%, 33.82%/85.71%, 15.00%/35.29%, 39.06%/134.21%, 23.23%/68.00%, and 137.14%/260.87% in terms of R2 for the six primary air pollutants, compared to the RF/MLBPN model. Moreover, the convergence speed and loss function of the BresNet model compared to that of the MLBPN decreased by 55.15%, revealing superior convergence speed with the lower loss function.
Delay-Doppler Map Shaping through Oversampled Complementary Sets for High-Speed Target Detection
Authors: Zhu Jiahua , Xie Zhuang , Jiang Nan , Song Yongping , Han Sudan , Liu Weijian , Huang Xiaotao
Published: August 2024

Advanced waveform design schemes have been widely employed for radar and sonar remote sensing analysis such as target detection and separation, where significant range sidelobe is a main factor that limits the improvement of analysis performance. As an extensional type of Golay complementary waveforms, complementary sets are a waveform design scenario of concern that shows more diversity in the design of transmission order, and results in a different distribution of range sidelobes. This work proposes an oversampled generalized Prouhet–Thue–Morse (OGPTM) method for the transmitted signal design of complementary sets, with comprehensive analysis to the influence on the sidelobe distribution. Based on this idea and our previous work, we further put forward a pointwise multiplication processor (PMuP) to integrate two delay-Doppler maps of oversampled complementary sets, which achieve much better sidelobe suppression performance on high-speed target detection with range migration.
Mapping Irrigated Rice in Brazil Using Sentinel-2 Spectral–Temporal Metrics and Random Forest Algorithm
Authors: Fernandes Filho Alexandre S. , Fonseca Leila M. G. , Bendini Hugo do N.
Published: August 2024

Brazil, a leading rice producer globally, faces challenges in systematically mapping its diverse rice fields due to varying cropping systems, climates, and planting calendars. Existing rice mapping methods often rely on complex techniques like deep learning or microwave imagery, posing limitations for large-scale mapping. This study proposes a novel approach utilizing Sentinel-2 spectral–temporal metrics (STMs) in conjunction with a random forest classifier for rice paddy mapping. By extracting diverse STMs and training both regional and global classifiers, we validated the method across independent areas. While regional models tended to overestimate rice areas, the global model effectively reduced discrepancies between our data and the reference maps, achieving an overall classifier accuracy exceeding 80%. Despite the need for further refinement to address confusion with other crops, STM exhibits promise for national-scale rice paddy mapping in Brazil.
LAQUA: a LAndsat water QUality retrieval tool for east African lakes
Authors: Byrne Aidan , Lomeo Davide , Owoko Winnie , Aura Christopher Mulanda , Nyakeya Kobingi , Odoli Cyprian , Mugo James , Barongo Conland , Kiplagat Julius , Mwirigi Naftaly , Avery Sean , Chadwick Michael A. , Norris Ken , Tebbs Emma J. ,   on behalf of the NSF-IRES Lake Victoria Research Consortium
Published: August 2024

East African lakes support the food and water security of millions of people. Yet, a lack of continuous long-term water quality data for these waterbodies impedes their sustainable management. While satellite-based water quality retrieval methods have been developed for lakes globally, African lakes are typically underrepresented in training data, limiting the applicability of existing methods to the region. Hence, this study aimed to (1) assess the accuracy of existing and newly developed water quality band algorithms for East African lakes and (2) make satellite-derived water quality information easily accessible through a Google Earth Engine application (app), named LAndsat water QUality retrieval tool for east African lakes (LAQUA). We collated a dataset of existing and newly collected in situ surface water quality samples from seven lakes to develop and test Landsat water quality retrieval models. Twenty-one published algorithms were evaluated and compared with newly developed linear and quadratic regression models, to determine the most suitable Landsat band algorithms for chlorophyll-a, total suspended solids (TSS), and Secchi disk depth (SDD) for East African lakes. The three-band algorithm, parameterised using data for East African lakes, proved the most suitable for chlorophyll-a retrieval (R2 = 0.717, p < 0.001, RMSE = 22.917 μg/L), a novel index developed in this study, the Modified Suspended Matter Index (MSMI), was the most accurate for TSS retrieval (R2 = 0.822, p < 0.001, RMSE = 9.006 mg/L), and an existing global model was the most accurate for SDD estimation (R2 = 0.933, p < 0.001, RMSE = 0.073 m). The LAQUA app we developed provides easy access to the best performing retrieval models, facilitating the use of water quality information for management and evidence-informed policy making for East African lakes.
Determining the Factors Influencing the Behavioral Intention of Job-Seeking Filipinos to Career Shift and Greener Pasture
Authors: Belida Prince Reuben C. , Ong Ardvin Kester S. , Young Michael N. , German Josephine D.
Published: August 2024

The current diverse opportunities available worldwide have caused an increase in the pursuit of changing jobs in the Philippines for greener pastures, leading to a decrease in organization efficiency due to career shifts or intentions for shifting. With the evident movement of workers, this study aimed to establish a model for determining the factors that influence job-seeking Filipino workers to shift careers and seek greener pastures by holistically analyzing variables using the Theory of Planned Behavior and the Value-Belief-Norm. A total of 210 valid responses among employees who shifted careers were collected through online surveys via social media platforms using purposive sampling. Partial least square structural equation modeling as the main multivariate tool was utilized to assess the hypothesized relationships. The findings of this study revealed that self-transcendence values in shaping personal norms and ascription to responsibility affected the intention to career shift or greener pasture-seeking behavior. In addition, subjective norms affected attitude, while organizational commitment negatively affected intention for greener pastures. It was seen that the factors that affect intention behavior the most among Filipinos were better opportunities, financial stability, workplace environment, and work–life balance—a notion that connects with the Protestant Work Ethics. It was evident that self-perception of a better career, growth, and overall profit merged to influence the intention of a career shift. It could be suggested that job rotation and job enhancement may reduce these intentions and lead to satisfaction among employees. Moreover, job roles may be reevaluated to identify (dis)satisfaction among employees, so the spearheading team may evaluate what actions are needed. Enhancement of skills and development through seminars and training may also be considered.
Smartphone and Tablet as Digital Babysitter
Authors: Andrisano Ruggieri Ruggero , Mollo Monica , Marra Grazia
Published: August 2024

Several scientific studies have highlighted the negative impact of new technologies (NTs) on children’s psychological development, both in terms of emotional and cognitive development. NTs, such as smartphones, tablets, and video games, have a significant impact on children’s development, both in terms of social relationships and cognitive functions. This study aims to identify and explore the cultural models that shape children’s exposure to new technologies in early childhood. This study involved 48 subjects between parents and infant educators. Unstructured interviews were conducted. Emotional Text Analysis was applied. The findings reveal the existence of three cultural repertoires (clusters): Connected but isolated (45.2), Technology education (30%), and Mistrust (24.8%). Their placement in the factorial space explains how the negative effects on children’s psychological development are determined. Technology education seems to be a protective factor for the cognitive and affective development of children. These findings are discussed, comparing them with Musk’s recent experiment and the rapid loss of social ties due to the lack of an educational plan.
Barriers to Implementing Environmental Sustainability in UAE Construction Project Management: Identification and Comparison of ISO 14001-Certified and Non-Certified Firms
Authors: Bashir Hamdi , Al-Hawarneh Ammar , Haridy Salah , Shamsuzzaman Mohammed , Aydin Ridvan
Published: August 2024

Firms in the construction industry are under increasing pressure from regulatory bodies, clients, and the public to integrate sustainability into their business strategies. However, they encounter numerous barriers that hinder the implementation of environmental sustainability practices in construction project management. This study aimed to examine these barriers within the context of the United Arab Emirates’ (UAE’s) construction industry. To achieve this, the research employed a mixed-method approach. Initially, interviews were conducted to identify the prevalent barriers, resulting in the identification of twelve key barriers. Subsequently, a structured questionnaire was distributed to project managers from 90 firms, both ISO 14001-certified and non-certified, to rank these barriers and assess their significance. The findings revealed that “economic benefits placed above meeting environmental sustainability requirements” was the most critical barrier. Through factor analysis, three latent factors were extracted: (1) organizational and policy barriers, (2) compliance and resource efficiency barriers, and (3) sustainable design implementation barriers. Notably, significant differences were observed between ISO 14001-certified and non-certified firms, particularly regarding the importance of “economic benefits placed above meeting environmental sustainability requirements” and “insufficient consultation with stakeholders”. This study highlights the critical barriers to implementing environmental sustainability practices in the UAE’s construction industry and provides actionable suggestions for policymakers and decision-makers to overcome these challenges, with implications for similar environments worldwide.
Advances in Geochemical Monitoring Technologies for CO2 Geological Storage
Authors: Ma Jianhua , Zhou Yongzhang , Zheng Yijun , He Luhao , Wang Hanyu , Niu Lujia , Yu Xinhui , Cao Wei
Published: August 2024

CO2 geological storage, as a large-scale, low-cost, carbon reduction technology, has garnered widespread attention due to its safety. Monitoring potential leaks is critical to ensuring the safety of the carbon storage system. Geochemical monitoring employs methods such as gas monitoring, groundwater monitoring, tracer monitoring, and isotope monitoring to analyze the reservoir’s storage state and secondary changes after a CO2 injection. This paper summarizes the recent applications and limitations of geochemical monitoring technologies in CO2 geological storage. In gas monitoring, the combined monitoring of multiple surface gasses can analyze potential gas sources in the storage area. In water monitoring, pH and conductivity measurements are the most direct, while ion composition monitoring methods are emerging. In tracer monitoring, although artificial tracers are effective, the environmental compatibility of natural tracers provides them with greater development potential. In isotope monitoring, C and O isotopes can effectively reveal gas sources. Future CO2 geological storage project monitoring should integrate various monitoring methods to comprehensively assess the risk and sources of CO2 leakage. The incorporation of artificial intelligence, machine learning technologies, and IoT monitoring will significantly enhance the accuracy and intelligence of numerical simulations and baseline monitoring, ensuring the long-term safety and sustainability of CO2 geological storage projects.
Air Quality Monitoring and Total Factor Productivity of Polluting Firms in China
Authors: Liu Xiao , He Lingyan , He Jianfei , Zhou Rongxi
Published: August 2024

In recent decades, sustainable development and environmental protection, especially air quality, have become key concerns for governments as well as scholars. As a typical regulation for air quality monitoring, the Ambient Air Quality Standard (AAQS) (2012) is a good attempt at balancing economic growth and environmental protection in development exploration. Therefore, this paper takes the AAQS (2012) as a quasi-natural experiment to detect its influence on the total factor productivity (TFP) of polluting firms. The results of a DID model suggest that the AAQS (2012) significantly improves the TFP of polluting firms in China even after several robust tests. Further, this paper also finds that firms in high urbanization and with over-investment experience are more sensitive to the new standard. As for the channels, the results show that air quality monitoring affects firms’ TFP by adjusting the industry concentration level and innovation capabilities. This research offers a novel perspective for decision-makers, highlighting the importance of harmonizing economic growth with environmental sustainability.
The Importance of Measures Undertaken to Improve the Quality of Life in the Problem Areas: A Case Study in Warmia and Mazury Region in Poland
Authors: Kryszk Hubert , Kurowska Krystyna , Marks-Bielska Renata
Published: August 2024

State agencies set up to manage the agricultural properties of the State Treasury, in subsequent years of their operation, have been implementing programs that are also intended to improve the social and living situation of the inhabitants of former state-owned farm villages. Such measures include non-refundable financial support distributed by the National Support Centre for Agriculture (NSCA). The research aimed to assess whether non-refundable financial aid improves the quality of life of local communities living in rural areas, particularly in former state-owned farm areas identified as problem areas. Another objective aspect of the research was to indicate the importance of this assistance in the opinion of the beneficiaries of this form of support (district authorities) and local communities. Improvement of the quality of life of rural inhabitants and support for the development of rural areas by local governments can be achieved by taking advantage of potential development factors and opportunities emerging in the environment and by being able to establish effective cooperation with various institutions. For local development to proceed smoothly, especially in rural areas, various institutions and economic players need to reach a consensus, become involved, and work together efficiently. A possible instrument to achieve this is the non-repayable financial support distributed by the National Support Centre for Agriculture (NSCA), which-according to the research-brings measurable effects.
The Influence of Work-Related Communication Technology Use during Non-Working Hours on Innovative Behavior: A Study on Government Employees in Hunan
Authors: Liu Wei , Shi Ting
Published: August 2024

The sustainability of government innovation relies on the continuous innovative behavior of government employees. Information technology drives innovation, but its extensive use leads government employees to work outside of regular hours. This not only burdens them but also causes stress and tension, disrupting their innovative behavior. This study investigates the link between work connectivity behavior after hours (WCBA) and the innovative behavior of government employees using the resource conservation theory. It examines the mediating role of work engagement and the moderating effect of psychological resilience. Analyzing data from 275 government employees through questionnaires using Mplus 8.3, we discovered that WCBA negatively impacts innovative behavior and work engagement. Work engagement partially mediates the relationship between WCBA and innovative behavior. Additionally, psychological resilience negatively moderates the connection between WCBA and work engagement, influencing the innovative behavior of government employees. The findings offer theoretical and practical insights into reducing government burdens and fostering innovation, suggesting sustainable innovations for government employees.
Climate Impacts on Tangible Coastal Cultural Heritage in the United States: Towards Sustainable and Adaptive Coastal Heritage Management
Authors: Axon Stephen , Chapman Anya , Light Duncan
Published: August 2024

Climate change is predicted to have severe impacts on coastal communities, including sea level rise, flooding, and coastal erosion, and is expected to reshape many coastlines. One further, and often overlooked, consequence of the climate crisis is the threat posed to cultural heritage sites in the coastal zone. The threat to coastal cultural heritage (CCH) will inevitably impact both tangible (physical and material) and intangible (socio-cultural) components of cultural, historical, and archaeological character along frontline coastal communities. This poses substantial sustainability challenges for stakeholders and decision-makers for the management of cultural heritage assets and for management practices to respond to increasing threats from climate change. This paper uses five illustrative examples based on maximum variation principles to evaluate different strategies (or ‘steering’ processes) for managing coastal heritage resources in the context of climate change. These include the traditional ‘preservationist’ perspective and trajectories based on discontinuity or transformation. We examine these issues with reference to five post-European heritage assets located along the East Coast of the USA. While a consideration of steering processes is important, we argue that it is necessary to also embrace the policies and strategies for adapting to and mitigating the impacts of climate change through which processes of managing CCH unfold. Adopting such a perspective can lead to more nuanced approaches for understanding how CCH can respond to the challenges of a changing climate.
Contribution of Mangrove Ecosystem Services to Local Livelihoods in the Indian Sundarbans
Authors: Sarkar Piyali , Banerjee Saon , Biswas Saroni , Saha Sarathi , Pal Dolgobinda , Naskar Manish Kumar , Srivastava Sanjeev K. , Barman Dhananjay , Kar Gouranga , Mukul Sharif A.
Published: August 2024

Mangrove forests, apart from their carbon sequestration and coastal protection benefits, provide a wide range of ecosystem services to people in tropical developing countries. Local people living in and around forests in the developing tropics also depend heavily on these mangrove ecosystem services for their livelihoods. This study examines the impact of mangrove ecosystem services on the livelihoods of people in Indian part of the Sundarbans—the largest contagious mangrove forest on earth. To achieve this objective, a household survey was undertaken to gather data on the diverse range of provisioning and regulating ES local people derived from mangrove forests living near the Indian Sundarbans. Surveys were carried out in nine villages across the Kultali, Basanti, and Gosaba blocks, involving over one hundred respondents. Our study reveals the active participation of locals in gathering various ecosystem services, with fishing and crab collection being the most common in the area. Due to numerous challenges in the agricultural sector, such as soil salinity and frequent extreme weather events, people increasingly depend on non-farming incomes, particularly fishing. A questionnaire was used to assess the dependence of local people on different ecosystem services. Some villages, such as Amlamethi, Satyanarayanpur, Mathurakhand, Vivekananda Palli, and Second Scheme, demonstrated a higher reliance on forest ecosystem services compared to other villages. The study indicates that the contribution of ecosystem services sometimes surpasses traditional activities like farming and daily contractual work. River transportation emerged as the most crucial service, followed by freshwater, food, and fiber. While certain resources like fuel, natural medicine, and genetic resources may not be prioritized, they still hold significance within the community, contrasting with ornamental resources, which are considered the least important. Our findings underscore the importance of preserving natural services in the Sundarbans forest, highlighting the need to conserve the mangrove ecosystem services to ensure the long-term well-being of local communities.
Mitigation Measures for Information Asymmetry between Participants in Construction Projects: The Impact of Trust
Authors: Ivić Ivona , Cerić Anita
Published: August 2024

Sustainability requirements pose complex challenges for the construction industry, requiring adaptation strategies, innovative solutions, and collaboration between stakeholders to build resilient structures for the future. Nevertheless, effective collaboration between stakeholders is hindered by information asymmetry, which can produce disputes, endanger honest communication between the participants, and in the long term, negatively affect industrial productivity. To improve the sustainability of construction businesses and construction projects, there is a need for the implementation of mitigation measures for information asymmetry risks. This study presents possible mitigation measures for information asymmetry between clients and contractors in the construction industry. Mitigation measures were identified through a literature review and semi-structured interviews with industry professionals. Furthermore, a questionnaire was designed and employed to prioritize mitigation measures and explore their utility for mitigating three types of risks: adverse selection, moral hazard, and hold-up. The results of this study indicate that building trust, regular supervision and monitoring of work, thorough verification of bidders, and fair distribution of risks between the client and the contractor have the most utility in mitigating information asymmetry in construction projects. The practical contribution of this research includes defining the most useful measures to mitigate risks caused by information asymmetry. Project managers can apply the results of this research for more successful achievement of their project goals. Implementing effective risk management strategies, such as building trust between stakeholders, can help mitigate the impacts of unforeseen events and build resilience in construction projects.
Overview of B→K(∗)ℓℓ Theoretical Calculations and Uncertainties
Authors: Mahmoudi Farvah , Monceaux Yann
Published: August 2024

The search for New Physics (NP) beyond the Standard Model (SM) has been a central focus of particle physics, including in the context of B-meson decays involving b→sℓℓ transitions. These transitions, mediated by flavour-changing neutral currents, are highly sensitive to small NP effects due to their suppression in the SM. While direct searches at colliders have not yet led to NP discoveries, indirect probes through semi-leptonic decays have revealed anomalies in observables such as the branching fraction B(B→Kμμ) and the angular observable P5′(B→K∗μμ). In order to assess the observed tensions, it is essential to ensure an accurate SM prediction. In this review, we examine the theoretical basis of the B→K(∗)ℓℓ decays, addressing in particular key uncertainties arising from local and non-local form factors. We also discuss the impact of QED corrections to the Wilson coefficients, as well as the effect of CKM matrix elements on the predictions and the tension with the experimental measurements. We discuss the most recent results, highlighting ongoing efforts to refine predictions and to constrain potential signs of NP in these critical decay processes.
O4 -Symmetry-Based Non-Perturbative Analytical Calculations of the Effect of the Helical Trajectories of Electrons in Strongly Magnetized Plasmas on the Width of Hydrogen/Deuterium Spectral Lines
Authors: Oks Eugene
Published: August 2024

The effects of the helical trajectories of the perturbing electrons in magnetized plasmas on the dynamical Stark width of hydrogen or deuterium spectral lines have been studied analytically in our previous two papers—specifically in the situation where the magnetic field B is so strong that the dynamical Stark width of these lines reduces to the so-called adiabatic Stark width because the so-called nonadiabatic Stark width is completely suppressed. This situation corresponds, for example, to DA and DBA white dwarfs. We obtained those analytical results by using the formalism of the so-called conventional (or standard) theory of the impact Stark broadening: namely, by performing calculations in the second order of the Dyson perturbation expansion. The primary outcome was that the dynamical Stark broadening was found to not depend on the magnetic field B (for sufficiently strong B). In the present paper, we use the O4 symmetry of hydrogen atoms for performing the corresponding non-perturbative analytical calculations equivalent to accounting for all orders of the Dyson perturbation expansion. The results, obtained by using the O4 symmetry of hydrogen atoms, differ from our previous ones not only quantitatively, but—most importantly—qualitatively. Namely, the dynamical Stark broadening does depend on the magnetic field B, even for strong B. These results should be important for revising the interpretation of the hydrogen Balmer lines observed in DA and DBA white dwarfs. We also address confusion in the literature on this subject.
Searching for Extra Higgs Boson Effects in General Two-Higgs Doublet Model (2HDM)
Authors: Hou George Wei-Shu
Published: August 2024

Starting from our current impasse at the LHC, of observing an SM-like Higgs boson but nothing beyond, we focus on the General 2HDM (G2HDM), which possesses extra sets of Yukawa couplings as a likely Next New Physics. After expounding its merits, we explore our “Decadal Mission of the New Higgs/Flavor era”, reporting on an Academic Summit Project (ASP) in Taiwan that conducts a four-pronged pursuit of G2HDM: CMS and Belle II searches, a lattice study of first-order electroweak phase transition, and phenomenology. The ASP Midterm report is based on ATLAS and CMS searches for cg→tH/tA→ttc¯, where H and A are exotic neutral scalar bosons, and now progressing onto a post-Midterm cg→bH+→btb¯ search, where H+ is the exotic charged Higgs boson, plus a few other searches at the LHC, all with discovery potential. We then discuss a plethora of flavor observables that can be explored by CMS and Belle II, as well as other dedicated experiments. Finally, we elucidate why G2HDM, providing myriad new dynamics, can remain well hidden so far. This brief report summarizes the progress of the ASP of the NSTC of Taiwan.
The Effect of Botulinum Neurotoxin-A (BoNT-A) on Muscle Strength in Adult-Onset Neurological Conditions with Focal Muscle Spasticity: A Systematic Review
Authors: Gill Renée , Banky Megan , Yang Zonghan , Medina Mena Pablo , Woo Chi Ching Angie , Bryant Adam , Olver John , Moore Elizabeth , Williams Gavin
Published: August 2024

Botulinum neurotoxin-A (BoNT-A) injections are effective for focal spasticity. However, the impact on muscle strength is not established. This study aimed to investigate the effect of BoNT-A injections on muscle strength in adult neurological conditions. Studies were included if they were Randomised Controlled Trials (RCTs), non-RCTs, or cohort studies (n ≥ 10) involving participants ≥18 years old receiving BoNT-A injection for spasticity in their upper and/or lower limbs. Eight databases (CINAHL, Cochrane, EMBASE, Google Scholar, Medline, PEDro, Pubmed, Web of Science) were searched in March 2024. The methodology followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and was registered in the Prospective Register of Systematic Reviews (PROSPERO: CRD42022315241). Quality was assessed using the modified Downs and Black checklist and the PEDro scale. Pre-/post-injection agonist, antagonist, and global strength outcomes at short-, medium-, and long-term time points were extracted for analysis. Following duplicate removal, 8536 studies were identified; 54 met the inclusion criteria (3176 participants) and were rated as fair-quality. Twenty studies were analysed as they reported muscle strength specific to the muscle injected. No change in agonist strength after BoNT-A injection was reported in 74% of the results. Most studies’ outcomes were within six weeks post-injection, with few long-term results (i.e., >three months). Overall, the impact of BoNT-A on muscle strength remains inconclusive.
Changes in the Pneumococcal Vaccination Uptake and Its Determinants before, during, and after the COVID-19 Pandemic among Community-Living Older Adults in Hong Kong, China: Repeated Random Telephone Surveys
Authors: Chan Paul Shing-fong , Poon Josiah , Han Soyeon Caren , Ye Danhua , Yu Fuk-yuen , Fang Yuan , Wong Martin C. S. , Mo Phoenix K. H. , Wang Zixin
Published: August 2024

Pneumococcal vaccination (PV) is effective in preventing vaccine-type pneumococcal diseases. This study investigated the changes in PV uptake and its determinants before, during, and after the Coronavirus Disease 2019 (COVID-19) pandemic among community-living older adults aged ≥65 years in Hong Kong, China. Three rounds of random telephone surveys were conducted every two years from May 2019 to October 2023. Multivariate logistic regression models were fitted to examine the between-round differences in PV uptake rate and factors associated with PV uptake in each round. This study included 1563 participants. The standardized PV uptake rate in Round 1, 2, and 3 was 17.3%, 28.3%, and 35.5%, respectively. A significant difference in the PV uptake rate was found between Rounds 2 and 1 (p = 0.02), but not between Rounds 3 and 2 (p = 0.98). Perceived barriers, cue to action and self-efficacy, were significant determinants of PV uptake in all rounds. Perceived benefits were significant determinants of PV uptake in the first and second rounds, but not in the third round. Continuous monitoring of PV uptake and its determinants, and evaluating and adjusting the PV program, might contribute to the success of such a vaccination program in the post-pandemic era.
Vaccination Coverage of People Living with HIV: Before and after Interventional Action
Authors: Gerin Larissa , Gir Elucir , Neves Lis Aparecida de Souza , Passos Luzia Márcia Romanholi , Kfouri Renato de Ávila , Spire Bruno , Reis Renata Karina
Published: August 2024

This is a quasi-experimental study that assessed PLHIV vaccination coverage before and after health professionals participated in a training course on PLHIV immunization. The vaccination coverage of 645 PLHIV was assessed in the pre-intervention phase. The vaccine with the best coverage was diphtheria and tetanus (82.64%) and the one with the lowest rate of adequately vaccinated was measles, mumps, and rubella (38.27%). Individuals aged between 30 and 39 years had a 74.00% (1–0.26) lower chance of having the full vaccination schedule when compared to those aged between 10 and 19 years, and among those over 40 years, the chance was 87.00% (1–0.13) lower. Those who were vaccinated in Specialized Care Services (SCS) were 5.77 times more likely to be adequately vaccinated when compared to those who were vaccinated in other health services. Regarding the entire vaccination schedule evaluated, the number of adequately vaccinated increased from 47 (7.29%) to 76 (11.78%). Interventions targeting health professionals were effective in increasing vaccination coverage among PLHIV; however, the achieved coverage remained below the desired level. It is necessary to act on health professionals’ knowledge and other aspects to effectively increase vaccination coverage.
Development and Application of Automated Sandwich ELISA for Quantitating Residual dsRNA in mRNA Vaccines
Authors: Holland David A. , Acevedo-Skrip Jillian , Barton Joshua , Thompson Rachel , Bowman Amy , Dewar Emily A. , Miller Danielle V. , Zhao Kaixi , Swartz Andrew R. , Loughney John W.
Published: August 2024

The rise of mRNA as a novel vaccination strategy presents new opportunities to confront global disease. Double-stranded RNA (dsRNA) is an impurity byproduct of the in vitro transcription reaction used to manufacture mRNA that may affect the potency and safety of the mRNA vaccine in patients. Careful quantitation of dsRNA during manufacturing is critical to ensure that residual dsRNA is minimized in purified mRNA drug substances. In this work, we describe the development and implementation of a sandwich Enzyme-Linked Immunosorbent Assay (ELISA) to quantitate nanogram quantities of residual dsRNA contaminants in mRNA process intermediates using readily available commercial reagents. This sandwich ELISA developed in this study follows a standard protocol and can be easily adapted to most research laboratory environments. Additionally, a liquid handler coupled with an automated robotics system was utilized to increase assay throughput, improve precision, and reduce the analyst time requirement. The final automated sandwich ELISA was able to measure <10 ng/mL of dsRNA with a specificity for dsRNA over 2000-fold higher than mRNA, a variability of <15%, and a throughput of 72 samples per day.
Characteristics and Nitrogen Removal Performance Optimization of Aerobic Denitrifying Bacteria Bacillus cereus J1 under Ammonium and Nitrate-Nitrogen Conditions
Authors: Cao Ying , Jin Yi , Lu Yao , Wang Yanling , Zhao Tianyu , Chen Pengfei , Huang Shaobin , Zhang Yongqing
Published: August 2024

A novel aerobic denitrifying bacterium Bacillus cereus J1 was isolated from a sewage treatment plant. Its characteristics under two distinct nitrogen sources were systematically investigated. According to the results of whole-genome sequencing, we inferred that strain J1 removes nitrogen through processes such as aerobic denitrification, dissimilatory nitrate reduction to ammonium, and ammonium assimilation. The degradation process of COD and total inorganic nitrogen (TIN) correlated to the zero-order degradation kinetics equation, and the maximum removal rate of NO3−−N reached 3.17 mg/L/h and that of NH4+−N was 3.79 mg/L/h. Utilizing single-factor experiments and response surface methodology, the optimal conditions for nitrate removal were determined as a shaking speed of 115 rpm, COD/nitrogen mass (C/N ratio) of 12.25, and salinity of 3.44 g/L, with the C/N ratio exerting the most significant influence. Similarly, for the maximum ammonium removal, the ideal conditions involved a shaking speed of 133 rpm, C/N ratio of 29, and salinity of 13.30 g/L, with the shaking speed exerting the most significant influence. These findings demonstrate that large amounts of ammonium and nitrate can be quickly removed with the help of Bacillus cereus J1, indicating that strain J1 may be applied to alleviate nitrogen pollution in aquatic environments.
Generalization Ability of Bagging and Boosting Type Deep Learning Models in Evapotranspiration Estimation
Authors: Kumar Manoranjan , Agrawal Yash , Adamala Sirisha , Pushpanjali  , Subbarao A. V. M. , Singh V. K. , Srivastava Ankur
Published: August 2024

The potential of generalized deep learning models developed for crop water estimation was examined in the current study. This study was conducted in a semiarid region of India, i.e., Karnataka, with daily climatic data (maximum and minimum air temperatures, maximum and minimum relative humidity, wind speed, sunshine hours, and rainfall) of 44 years (1976–2020) for twelve locations. The Extreme Gradient Boosting (XGBoost), Gradient Boosting (GB), and Random Forest (RF) are three ensemble deep learning models that were developed using all of the climatic data from a single location (Bengaluru) from January 1976 to December 2017 and then immediately applied at eleven different locations (Ballari, Chikmaglur, Chitradurga, Devnagiri, Dharwad, Gadag, Haveri, Koppal, Mandya, Shivmoga, and Tumkuru) without the need for any local calibration. For the test period of January 2018–June 2020, the model’s capacity to estimate the numerical values of crop water requirement (Penman-Monteith (P-M) ETo values) was assessed. The developed ensemble deep learning models were evaluated using the performance criteria of mean absolute error (MAE), average absolute relative error (AARE), coefficient of correlation (r), noise to signal ratio (NS), Nash–Sutcliffe efficiency (ɳ), and weighted standard error of estimate (WSEE). The results indicated that the WSEE values of RF, GB, and XGBoost models for each location were smaller than 1 mm per day, and the model’s effectiveness varied from 96% to 99% across various locations. While all of the deep learning models performed better with respect to the P-M ETo approach, the XGBoost model was able to estimate ETo with greater accuracy than the GB and RF models. The XGBoost model’s strong performance was also indicated by the decreased noise-to-signal ratio. Thus, in this study, a generalized mathematical model for short-term ETo estimates is developed using ensemble deep learning techniques. Because of this type of model’s accuracy in calculating crop water requirements and its ability for generalization, it can be effortlessly integrated with a real-time water management system or an autonomous weather station at the regional level.
Numerical Simulation Study of Factors Influencing Ultrasonic Cavitation Bubble Evolution on Rock Surfaces during Ultrasonic-Assisted Rock Breaking
Authors: Feng Jinyu , Yan Tie , Hou Zhaokai
Published: August 2024

With the increasing demand for deep oil and gas exploration and CCUS (Carbon Capture, Utilization, and Storage) engineering, improving rock-crushing efficiency stands as a pivotal technology. Ultrasonic vibration-assisted drilling has emerged as a novel rock-breaking technology. The high-frequency vibrations of ultrasonic waves impact rocks, inducing resonance and accelerating their fragmentation. At the same time, ultrasonic waves generate cavitation bubbles in the liquid near rock surfaces; the expansion and collapse of these bubbles further contribute to rock damage, thereby improving crushing efficiency. Therefore, investigating the dynamics and failure characteristics of cavitation bubbles near rock surfaces under ultrasonic influence is crucial for advancing ultrasonic-assisted rock-breaking technology. This study treats the liquid as compressible flow and investigates the movement and rupture of bubbles near rock surfaces under varying ultrasonic parameters, rock properties, characteristics of the circulating medium, and other relevant factors. The findings show that ultrasonic waves induce the oscillation, translation, collapse, and rebound of bubbles near rock surfaces. Higher ultrasonic frequencies correspond to larger collapse pressures and amplitudes near surrounding rocks, as well as longer expansion times and shorter collapse durations. In addition, bubble movement and collapse lead to rock material deformation, influenced by the rheological properties of the liquid medium. The study outcomes serve as a foundation for optimizing engineering parameters in ultrasonic-assisted rock breaking and provide theoretical support for the advancement of this technology.
Water, Energy and Food Nexus: A Project Evaluation Model
Authors: Neto Ruy de Castro Sobrosa , Bohner João Paulo , Birch Robert Samuel , Junges Ivone , Mussi Clarissa Carneiro , Soares Sandro Vieira , Dutra Ana Regina de Aguiar , Salgueirinho Osório de Andrade Guerra José Baltazar
Published: August 2024

The connections between universal rights to water supply, energy security, and food supply stand out as a challenge that requires project evaluation models that can capture the complex dynamics and interdependencies of these resources. This study proposes the elaboration of a nexus evaluation model (NEM) for projects related to the water–energy–food nexus (WEFN) from the perspective of sustainability, Industry 4.0, and the Sustainable Development Goals (SDGs). The model considers the three dimensions of sustainability—economic, environmental, and social; the three structuring factors of Industry 4.0—physical, biological, and digital; and the 17 SDGs proposed by the United Nations. A Design Science Research (DSR) approach was adopted in which the design and development of the model, and demonstration and evaluation phases, were supported by a group of experts. The model was applied to three different projects focused on sustainable technological innovation in energy and agriculture, with the results presented in the RGB color scale represented numerically as a number from 0 to 255. The results demonstrated that, in the relationship between nexus and sustainability, the projects presented scores between 162 and 217 for the environmental dimension, between 158 and 202 for the economic dimension and between 170 and 212 for the social dimension. In the nexus and Industry 4.0 relationship, the projects obtained scores ranging from 9 to 94 in the biological factor, from 13 to 141 in the digital factor, and from 13 to 141 in the physical factor. In the nexus and SDG relationship, scores ranged from 214 to 244 for water, from 195 to 255 for energy, and from 30 to 255 for food. These results from the model were consistent with the reality of the projects being evaluated, demonstrating a greater alignment of the projects with the dimensions of sustainability and the SDGs than with the factors of Industry 4.0. The proposal of the model contributes to broaden the understanding of how projects related to the nexus can be evaluated considering multiple contemporary dimensions.
CRITERION FOR EFFICIENT OPERATION ASSESSMENT OF HEAT NETWORK
Authors: Gridin Sergey , Biryukov Aleksey
Published: August 2024

The article is dedicated to the actual problem of assessing the energy efficiency of the process of transporting a heat carrier through heating network pipelines. A brief analysis of the existing scientific research on the problem under consideration is given. The task is to develop a criterion for evaluating the effective functioning of heating networks, which would take into account the key indicators of their energy efficiency. The parameters of the thermal regime of thermal networks and the factors influencing them are considered and the key ones for evaluating the energy efficiency of thermal networks are highlighted. Based on the selected parameters, a criterion is proposed for the practical assessment of the energy efficiency of heating networks, which allows, with a minimum of measured parameters and ease of calculation, to give an idea of the energy efficiency of the heating network and determine the proportion of thermal energy lost in pipelines. The criterion is suitable both for evaluating the energy efficiency of an individual section of the heat network and for the entire heat network.
ANALYSIS OF METHODS FOR MODELING POWER THREE WINDING TRANSFORMERS
Authors: Mikhailovich Maksim , Leonov Sergey , Mamonova Tatiana
Published: August 2024

This article presents a comparison of two approaches to modeling three-phase power transformers and the stages of further use of the model to create a digital twin of the product, including the application of neural network algorithms for classifying various modes of operation of an electrical apparatus. The first model was created using the standard Simulink block. The second model is developed on the basis of a T-shaped transformer replacement circuit, taking into account the active and inductive resistances of the windings and the magnetic circuit. The paper presents the corresponding limitations for the models being developed. The values of the magnetic circuit parameters are calculated based on the passport data of the physical object. To validate the model, acceptance tests of the transformer were carried out, namely, experiments on idling and short circuit. According to the data obtained, appropriate conclusions have been drawn about the correctness of using the presented computer model, which fully reflects all the physical phenomena of such an electrostatic device as a transformer and can be further used to train neural networks to solve a number of practical problems.