bluuebunny/crossref_metadata_2025 huggingface dataset:
Can Technological Innovation and Financial Agglomeration Promote the Growth of Real Economy? Evidence from China
Authors: Wang Tao , Wang Shuhong , Ding Wei , Guo Huiwen
Published: November 2023

In the backdrop of China’s evolving economic landscape, the real economy confronts a myriad of challenges, both domestically and on the global front. Technological innovation, characterized by its capital intensity and the unpredictable nature of its returns, stands as a pivotal force poised to rejuvenate nascent sectors and overhaul the existing industrial framework. Parallel to this, financial agglomeration emerges with a bifurcated function: it not only directly propels the real economic trajectory but also exerts an indirect influence via the channels of technological advancement. Delving deep into this interplay, our study dissected data collated from 30 major provinces and cities across mainland China, spanning the years 2011 to 2018. We employed the nuanced techniques of fuzzy matter–element analysis combined with the location entropy method. By anchoring our findings on a spatial econometric model, we uncovered the intricate dynamics of how technological ingenuity and financial clustering drive real economic growth, shedding light on the spatial reverberations that ripple across regions. Building on the tangible empirical evidence reflecting the trajectory of technological innovation and financial agglomeration within China, this article distills and presents the salient conclusions drawn from the investigation.
The Hard Worker, the Hard Earner, the Young and the Educated: Empirical Study on Economic Growth across 11 CEE Countries
Authors: Batrancea Larissa M.
Published: November 2023

Economic growth is an important metric for the sustainable development of any region or country. Central and Eastern Europe members of the European Union are important players of the single market, which implements regional policies to mitigate socio-economic differences between its newer and established members. The present study examines the factors that shape the phenomenon of economic growth across 62 NUTS 2 regions from 11 countries in Central and Eastern Europe during the period 2011–2020. The study investigates determinants related to education level, involvement of young people in the labor market, household net income, high-speed internet facilities and overall hours spent at work during a year. Three panel data models estimated with first-differenced generalized method of moments showed that regional economic growth was significantly influenced mainly by income, the rate of young employees and educational attainment level. Relevant insights and policy implications for regions in CEE countries are addressed.
Drought Assessment in Greece Using SPI and ERA5 Climate Reanalysis Data
Authors: Kourtis Ioannis M. , Vangelis Harris , Tigkas Dimitris , Mamara Anna , Nalbantis Ioannis , Tsakiris George , Tsihrintzis Vassilios A.
Published: November 2023

The present work aims to assess the spatial variability and the trends of the annual rainfall and meteorological drought in the entire territory of Greece utilising the ERA5 reanalysis precipitation dataset of the European Centre for Medium-Range Weather Forecasts (ECMWF), which spans from January 1940 to December 2022 (an 83-year period). Drought assessment took place based on the Standardized Precipitation Index (SPI) for timescales ranging from 1 month to 12 months. Evaluation was carried out by calculating SPI using observed rainfall data from five meteorological stations. The annual rainfall and drought severity trends for timescales of 1 (SPI-1), 3 (SPI-3), 6 (SPI-6) and 12 (SPI-12) months were analysed using the Theil–Sen slope method and the Mann–Kendall trend test. The results indicate significant, both increasing and decreasing, annual precipitation trends at the 95% significance level for the Aegean Islands, western Crete and western mainland of Greece. The results also indicate significant drought trends for SPI-12 for the Aegean Islands and western Peloponnese. Trend analysis for SPI-1, SPI-3 and SPI-6 indicate a mixture of non-significantly increasing wetting trends and increasing drought trends at the national scale. In conclusion, the ERA5 dataset seems to be a valuable tool for drought monitoring at the spatial scale.
A Comparison of Feedstock from Agricultural Biomass and Face Masks for the Production of Biochar through Co-Pyrolysis
Authors: Yusoff Yasirah , Tan Ee Sann , Ismail Firas Basim
Published: November 2023

This study explores the pyrolysis of disposable face masks to produce chemicals suitable for use as fuel, addressing the environmental concern posed by single-use face masks. Co-pyrolysis of biomass with face mask plastic waste offers a promising solution. The research focuses on the co-pyrolysis of biomass and face masks, aiming to characterise the properties for analysis and optimisation. Selected agricultural biomass and face mask plastic waste were subjected to temperatures from 250 °C to 400 °C for co-pyrolysis. Slow pyrolysis was chosen because face masks cannot be converted into useful bioproducts at temperatures exceeding 400 °C. The samples were tested in four different ratios and the study was conducted under inert conditions to ensure analysis accuracy and reliability. The results indicate that face masks exhibit a remarkable calorific value of 9310 kcal/kg. Face masks show a two-fold increase in calorific value compared with biomass alone. Additionally, the low moisture content of face masks (0.10%) reduces the heating value needed to remove moisture, enhancing their combustion efficiency. This study demonstrates the potential of co-pyrolysis with face masks as a means of generating valuable chemicals for fuel production, contributing to environmental sustainability.
Simulation of the Impacts of Sea-Level Rise on Coastal Ecosystems in Benin Using a Combined Approach of Machine Learning and the Sea Level Affecting Marshes Model
Authors: Deguenon Sèna Donalde Dolorès Marguerite , Hounmenou Castro Gbêmêmali , Adade Richard , Teka Oscar , Toko Ismaila Imorou , Aheto Denis Worlanyo , Sinsin Brice
Published: November 2023

Sea-level rise in Benin coastal zones leads to risks of erosion and flooding, which have significant consequences on the socio-economic life of the local population. In this paper, erosion, flood risk, and greenhouse gas sequestration resulting from sea-level rise in the coastal zone of the Benin coast were assessed with the Sea Level Affecting Marshes Model (SLAMM) using ArcGIS Pro 3.1 tools. The input features used were the Digital Elevation Map (DEM), the National Wetland Inventory (NWI) categories, and the slope of each cell. National Wetland Inventory (NWI) categories were then created using Support Vector Machines (SVMs), a supervised machine learning technique. The research simulated the effects of a 1.468 m sea-level rise in the study area from 2021 to 2090, considering wetland types, marsh accretion, wave erosion, and surface elevation changes. The largest land cover increases were observed in Estuarine Open Water and Open Ocean, expanding by approximately 106.2 hectares across different sea-level rise scenarios (RCP 8.5_Upper Limit). These gains were counterbalanced by losses of approximately 106.2 hectares in Inland Open Water, Ocean Beaches, Mangroves, Regularly Flooded Marsh, Swamp, Undeveloped, and Developed Dryland. Notably, Estuarine Open Water (97.7 hectares) and Open Ocean (8.5 hectares) experienced the most significant expansion, indicating submergence and saltwater intrusion by 2090 due to sea-level rise. The largest reductions occurred in less tidally influenced categories like Inland Open Water (−81.4 hectares), Ocean Beach (−7.9 hectares), Swamp (−5.1 hectares), Regularly Flooded Marsh (−4.6 hectares), and Undeveloped Dryland (−2.9 hectares). As the sea-level rises by 1.468 m, these categories are expected to be notably diminished, with Estuarine Open Water and Open Ocean becoming dominant. Erosion and flooding in the coastal zone are projected to have severe adverse impacts, including a gradual decline in greenhouse gas sequestration capacity. The outputs of this research will aid coastal management organizations in evaluating the consequences of sea-level rise and identifying areas with high mitigation requirements.
Impact of Financial Development Shocks on Renewable Energy Consumption in Saudi Arabia
Authors: Elzaki Raga M.
Published: November 2023

The demand for renewable energy is increasing globally due to concerns about climate change, pollution, and the finite nature of fossil-fuel resources, and renewable energy has been recognized as a significant factor in realizing sustainable development. The government of Saudi Arabia adopted the reduction in fossil-fuel subsidies policy as a financial motivation for supporting both the production and consumption of fossil fuels. Therefore, this study aims to investigate the influence and shocks of Saudi financial development indicators on renewable energy consumption (REC) and to examine the track of causality between financial development indicators and REC. The study covers the annual data period of 1990–2021 and applies the Basic Vector Autoregressive model (VAR), the Granger causality test, forecast-error variance decomposition (FEVD), and the impulse response function (IRF). In the short run, the VAR results indicate a positive and significant impact of stock price volatility and private credit on REC. The results of causality between REC and financial development indicators were conflicting. The Granger causality test shows significant causality running from stock price volatility and private credit to REC. The FEVD results reveal that REC variation is explained by its innovative shocks and has a positive response to shocks in financial development. The IRF results show that REC has a positive response to shock on private credit, liquid liabilities, and stock price volatility. Authorities can encourage investment in renewable energy consumption by providing financial incentives; also, governments can foster national and international partnerships between investors, policymakers, and industry stakeholders. Employing different determinants of financial development indicators and incorporating population factors in the REC function will be highly recommended for forming the renewable energy demand in Saudi Arabia. Conducting a micro-level analysis of specific sectors within renewable energy, such as solar, wind, and others, can provide actionable insights for policymakers.
Correction: Dou et al. Public Concern and Awareness of National Parks in China: Evidence from Social Media Big Data and Questionnaire Data. Sustainability 2023, 15, 2653
Authors: Dou Yaquan , Wu Changhao , He Youjun
Published: November 2023

The authors would like to make the following corrections about the published paper [...]
The Impact of Digitization on the Formation of a New Model for Geospatial Data
Authors: Jovanovic-Milenkovic Marina , Petrovic Filip
Published: November 2023

The introduction of digitization has changed all spheres of business on a global level, including geospatial data. The general goal of the paper includes the formation of a new model of geospatial data management. The authors propose the formation of an eSpace model that includes the ePlan system. In order to achieve the goal of the paper, the authors conducted a survey in which representatives of local self-governments and holders of public authority participated through a structured online survey. A pilot study for the formation of a geospatial data model is an overview of spatial and urban planning. The focus is on looking at the real state of spatial and urban planning documents and the possibility of establishing a central database of spatial planning documents in digital format and its further distribution through a single system. In this way, easy access to digital plan data expands the community of users and enables communication with different groups of stakeholders. The introduction of the described model affects the further development of society as a whole.
Spatiotemporal Variation in Water-Related Ecosystem Services during 2000–2020 and Ecological Management Zoning in the Xiangjiang River Basin, China
Authors: Deng Meirong , Mao Dehua , Li Yeye , Wang Ting , Hu Zui
Published: November 2023

Exploring the spatiotemporal distribution and interrelationships among water-related ecosystem services (WESs) and conducting ecological management zoning are crucial for regional sustainable development. Taking the Xiangjiang River Basin (XJRB) as an example, this study first quantified three primary WESs, including water conservation, soil retention, and water purification, from 2000 to 2020. Second, the spatiotemporal variation in the interrelationships among WESs were analyzed using global and local bivariate spatial autocorrelation. Third, a water ecological zoning rule was constructed to divide the watershed into three primary and eight secondary water ecological management zones. The results indicate a strong consistency in the changes in the three WESs throughout the period from 2000 to 2020 in the XJRB. Precipitation patterns and urban expansion were the primary factors affecting alterations in the WESs. Spatial heterogeneity and dependence were evident across these ecosystem services. Both trade-offs and synergies were observed among WESs, with synergies playing a dominant role. Positive synergies occurred primarily in woodlands and grasslands, while negative synergies were observed in cultivated land, water areas, and construction land. Three water ecological management zones, including core water ecological management zones, general management zones, and restoration management zones, were delineated at the grid and country scales according to the aggregation properties of the WESs. Ecological management strategies were proposed for different zones. These findings can offer valuable insights for policy makers in land use planning and water ecological management within the XJRB, and can facilitate similar management endeavors in other regions.
Reviewing Advanced Treatment of Hydrocarbon-Contaminated Oilfield-Produced Water with Recovery of Lithium
Authors: Khatoon Rabia , Raksasat Ratchaprapa , Ho Yeek Chia , Lim Jun Wei , Jumbri Khairulazhar , Ho Chii-Dong , Chan Yi Jing , Abdelfattah Eman Alaaeldin , Khoo Kuan Shiong
Published: November 2023

The global demand for lithium, which is indispensable for electric cars and electrical devices, has increased. Lithium recovery from oilfield-produced water is necessary to meet the growing need for lithium-ion batteries, protect the environment, optimize resource utilization, and cut costs to ensure a successful energy transition. It is useful for keeping water supplies in good condition, adhering to legal requirements, and making the most of technological advances. Oil and gas companies might see an increase in revenue gained through the lithium extraction from generated water due to the recouping of energy costs. Therefore, this review focuses on contamination and treatment strategies for the oilfield-produced water. It includes a discussion of the global lithium trade, a financial analysis of lithium extraction, and a comparison of the various methods currently in use for lithium extraction. It was evaluated that economic considerations should be given priority when selecting environmentally friendly methods for lithium recovery from oilfield-produced water, and hybrid methods, such as adsorption–precipitation systems, may show promising results in this regard. Lastly, future prospects for the lithium industry were also discussed.
Quantitative, Qualitative and Thermal Aspects of Rainwater Retention on Wetland Roofs
Authors: Karczmarczyk Agnieszka , Baryła Anna , Szejba Daniel , Miechowicz Barbara , Amroziński Radosław , Ciuraj Marcin
Published: November 2023

Wetland roofs (WRs) are a multi-functional green infrastructure measure to mitigate the negative effects of climate change. The present work advances knowledge in the field of WRs by analyzing the performance of rainwater management, focused on water sufficiency, water quality and cooling potential. Automatic monitoring, covering weather conditions, temperature and the conductivity of WR water, and the amount of outflow into retention tanks, was supported with automated sampling of water for laboratory analysis of BOD5, phosphate phosphorus, suspended solids, electrical conductivity (EC), redox potential (Eh), color and pH. From April to September 2022, a precipitation deficit of 395.45 mm and a negative climatic water balance of 267.91 mm were observed. It was necessary to fill up the system several times in order to maintain water at the assumed level. In most cases, the values of EC observed during the monitoring period were higher than those reported for rainwater. Continuous monitoring of EC in the wetland was a useful tool for the observation of operating activities in the system; however, it was not sufficient for system control. BOD5 values did not exceed 6 mg dm−3 and were lower than reported for urban rainwater retention reservoirs. Suspended solids values did not exceed 27 mg dm−3. Color varied between 0 and 101 PtCo, with the highest values noted in July and the beginning of August. The pH value ranged between 7.28 and 8.24. The Eh varied between 155 and 306 mV, with lower values associated with the filling up of the wetland. Peak values of PO4-P were observed between the end of July and the beginning of September 2022, with a maximum concentration of 232 µg dm−3 utilized by the wetland within one month. Monitoring of the water and air temperature showed a thermal buffering effect of the wetland. The results of the research, conducted during the growing season, allow for better management of rainwater on the roof. However, there is a need to expand the scope of the analyzed water quality parameters. Although there are several limitations to the analysis, the present study partially fills the existing knowledge gap and may generate further interest in this topic among researchers and decision-makers.
Determinants of College Students’ Online Fragmented Learning Effect: An Analysis of Teaching Courses on Scientific Research Software on the Bilibili Platform
Authors: Li Zhigang , Yang Yalin
Published: November 2023

In the era of mobile Internet, online fragmented learning has become one of the mainstream ways for college students to study independently. Analyzing the online fragmented learning effect (OFLE) has essential reference value for guiding the online learning behavior of college students and optimizing the allocation of online learning platform resources. It also provides sustainable solutions for enhancing college students’ online independent learning effect. For this paper, we took college students who have studied teaching courses on scientific research software (TCSRS) on Bilibili as our research subjects, constructed a theoretical model of college students’ OFLE based on the theory of online learning and fragmented learning, verified the model through using questionnaire data, and analyzed the determinants of college students’ OFLE and its mechanisms. Our results indicate the following: (1) Most college students spend a dispersed amount of time learning TCSRS, showing the characteristics of “fragmentation”. (2) Learning motivation (LM), self-efficacy (SE), and fragmented time utilization (FTU) have a significant positive effect on college students’ OFLE. (3) Knowledge fragmentation (KF) affects college students’ OFLE, but it is not significant. These dimensions provide a theoretical reference for quantitative research on the impact of college students’ OFLE. Finally, also in this paper, improvement countermeasures are proposed from the perspective of improving college students’ OFLE and ability.
Blow-Up Analysis for a Reaction–Diffusion System Coupled via Lα-Norm-Type Sources under Positive Boundary Value Conditions
Authors: Zhong Guangsheng , Zhang Qinghua
Published: November 2023

This article mainly deals with the blow-up properties of nonnegative solutions for a reaction–diffusion system coupled with norm-type sources under positive boundary value conditions. The local existence of a nonnegative solution and the comparison principle are given. The criteria for the global existence or finite time blow-up of the solutions are obtained by constructing new functions and utilizing the super- and -sub-solution method. The results reveal a correlation between the blow-up profiles of the solutions and the size of the domain, as well as the positive boundary value.
Blockchain-Embedded Strategic Options for Satellite Operators: Sell, SataaS, or Dual?
Authors: Jing Yihan , Chen Chenyi , Dong  Jichang , He Zhou
Published: November 2023

With the rise of satellite-as-a-service subscriptions as technology improves, our paper examines how satellite operators (SOs) can choose between traditional channels for selling satellites, satellite-as-a-service (SataaS), and dual-channel strategies. In the space supply chain, commercial satellites display several distinct characteristics that differentiate them from other physical commodities in traditional supply chains, most notably their exposure to significant launch risks. In addition, SataaS suffers from the risk of secure data transmission. However, the emergence of novel technologies such as blockchain technology (BCT) could help to mitigate such risks. Therefore, our study analyzes the optimal strategy among the sell, SataaS, and dual-channel approaches for SOs by considering the above distinctive characteristics in the case without blockchain and the case with blockchain. Our paper reveals the existence of a dual-channel strategy that generates the highest profit for the SO and yields the highest consumer utility when launch success is high and when SataaS fixed costs are low. When the launch success rate is very high, the dual-channel strategy transforms into a pure sell strategy. After the adoption of BCT, when the cost of BCT is low, the SO’s profit is enhanced in all three sales channels compared to the case without blockchain. Notably, in SataaS as well as in the dual-channel approach, the adoption of BCT always improves consumer utility compared to the case without blockchain. However, in the sell channel, the consumer benefits depend on the relatively low cost of blockchain customization.
Lipopolysaccharides of Brucella suis S2 Impaired the Process of Decidualization in Early Pregnancy in Mice
Authors: Lei Lanjie , Wang Xiangguo , Zhang Jianpo , Yin Jiaojiao , Xu Qin , Wang Ting , Jin Yaping , Wang Aihua
Published: November 2023

Brucellosis is a notorious zoonotic disease caused by Brucella, which can lead to reproductive diseases in humans and animals, such as infertility and abortion. Lipopolysaccharides (LPS) are the main virulence factor of Brucella. LPS derived from Brucella are different and non-classical and are less toxic and less active than LPS isolated from E. coli. However, the effects and possible mechanisms of Brucella LPS-caused pregnancy loss remain to be revealed. In the present study, we investigated the effects of Brucella suis S2 LPS on early pregnancy loss in mice. The results indicated that embryo implantation failure was induced by Brucella LPS treatment in a dose-dependent manner. The injection of Brucella LPS mainly resulted in fibrinolysis in the decidual area of the uterus on the 6th day post coition (dpc), infiltration of large granular cells among the decidual cells near the embryo on the 8th dpc, a large number of gaps in the decidual area, and cell necrosis around the embryo. In addition, the expression of Cyclin D3 mRNA in the uterus on the 7th and 8th dpc and IGFBP-1 mRNA and the progesterone receptor in the uterus on the 6th and 7th dpc were also inhibited. Moreover, the expression of decidualization marker Cyclin D3 and decidualization prolactin-associated protein (dPRP) in endometrial stromal cells were also inhibited by Brucella LPS treatment in vitro. In summary, Brucella LPS affect the process of endometrial decidualization in mice by affecting the structure of the decidua and the expression of decidual marker factors in endometrial stromal cells.
Consistent Couplings between a Massive Spin-3/2 Field and a Partially Massless Spin-2 Field
Authors: Boulanger Nicolas , Lhost Guillaume , Thomée Sylvain
Published: November 2023

We revisit the problem of constructing consistent interactions between a massive spin-3/2 field and a partially massless graviton in four-dimensional (anti) de Sitter (A)dS4 spacetime. We use the Stueckelberg formulation of the action principle for these fields and find two non-trivial cubic vertices with less than two derivatives when moving to the unitary gauge. One of the vertices is reminiscent of the minimal coupling of the massive spin-3/2 field to gravity, except that now the graviton is partially massless.
Diffractive and Photon-Induced Production of Top Quark
Authors: Pitt Michael
Published: November 2023

The top quark plays a central role in particle physics, as many experiments at the Large Hadron Collider scrutinize its properties within the Standard Model. Although most of the measurements of the top quarks today concentrate on production modes initiated by quarks or gluons, this review will highlight the lesser-explored modes initiated by pomerons or photons. It aims to provide an in-depth look into both the phenomenological studies and the existing experimental measurements, emphasizing the necessity of exploring the diffractive and photon-induced production of top quarks to enhance the accuracy of top-quark measurements.
The Circulating miRNA Profile of Chronic Hepatitis D and B Patients Is Comparable but Differs from That of Individuals with HBeAg-Negative HBV Infection
Authors: Cavallone Daniela , Ornos Eric , Ricco Gabriele , Oliveri Filippo , Coco Barbara , Colombatto Piero , De Rosa Laura , Dalmacio Leslie , Bonino Ferruccio , Brunetto Maurizia
Published: November 2023

miRNAs circulating in whole serum and HBsAg-particles are differentially expressed in chronic hepatitis B (CHB) and HBeAg-negative-HBV infection (ENI); their profiles are unknown in chronic hepatitis D (CHD). Serum- and HBsAg-associated miRNAs were analyzed in 75 subjects of 3 well-characterized groups (CHB 25, CHD 25, ENI 25) using next-generation sequencing (NGS). Overall miRNA profiles were consonant in serum and HBsAg-particles but significantly different according to the presence of hepatitis independently of Hepatitis D Virus (HDV)-co-infection. Stringent (Bonferroni Correction < 0.001) differential expression analysis showed 39 miRNAs upregulated in CHB vs. ENI and 31 of them also in CHD vs. ENI. miRNA profiles were coincident in CHB and CHD with only miR-200a-3p upregulated in CHB. Three miRNAs (miR-625-3p, miR-142-5p, and miR-223-3p) involved in immune response were upregulated in ENI. All 3 hepatocellular miRNAs of MiR-B-Index (miR-122-5p, miR-99a-5p, miR-192-5p) were overexpressed in both CHB and CHD patients. In conclusion, CHD and CHB patients showed highly similar serum miRNA profiling that was significantly different from that of individuals with HBeAg-negative infection and without liver disease.
Phenotypic Characterization of Recombinant Marek’s Disease Virus in Live Birds Validates Polymorphisms Associated with Virulence
Authors: Kim Taejoong , Hearn Cari J. , Mays Jody , Velez-Irizarry Deborah , Reddy Sanjay M. , Spatz Stephen J. , Cheng Hans H. , Dunn John R.
Published: November 2023

Marek’s disease (MD) is a highly infectious lymphoproliferative disease in chickens with a significant economic impact. Mardivirus gallidalpha 2, also known as Marek’s disease virus (MDV), is the causative pathogen and has been categorized based on its virulence rank into four pathotypes: mild (m), virulent (v), very virulent (vv), and very virulent plus (vv+). A prior comparative genomics study suggested that several single-nucleotide polymorphisms (SNPs) and genes in the MDV genome are associated with virulence, including nonsynonymous (ns) SNPs in eight open reading frames (ORF): UL22, UL36, UL37, UL41, UL43, R-LORF8, R-LORF7, and ICP4. To validate the contribution of these nsSNPs to virulence, the vv+MDV strain 686 genome was modified by replacing nucleotides with those observed in the vMDV strains. Pathogenicity studies indicated that these substitutions reduced the MD incidence and increased the survival of challenged birds. Furthermore, using the best-fit pathotyping method to rank the virulence, the modified vv+MDV 686 viruses resulted in a pathotype similar to the vvMDV Md5 strain. Thus, these results support our hypothesis that SNPs in one or more of these ORFs are associated with virulence but, as a group, are not sufficient to result in a vMDV pathotype, suggesting that there are additional variants in the MDV genome associated with virulence, which is not surprising given this complex phenotype and our previous finding of additional variants and SNPs associated with virulence.
Retrospective Assessment of Thirty-Two Cases of Pelvic Fractures Stabilized by External Fixation in Dogs and Classification Proposal
Authors: Flores Jose Antonio , Rovesti Gian Luca , Gimenez-Ortiz Lucia , Rodriguez-Quiros Jesus
Published: November 2023

The goals of this study were to evaluate the outcomes of bone healing, patient comfort during the treatment, functional results, and complications in pelvic fractures treated with external fixation, as well as to propose a classification system for the applied external frames. A total of thirty-two canine patients with pelvic fractures of different origins were treated. To provide a better reference for the frames used, an alphanumeric classification system was developed, detailing the frame structure and the number and location of the pins used. In this study, eighty-six fractures were treated in the 32 patients of this work, with an average fixation time of 9.88 ± 4.15 weeks. No major complications were detected in this case cohort, and the outcomes were rated at 9.46 based on a visual assessment scale for the patient’s comfort during treatment. Outcomes graded as excellent and good were 96%. The use of external fixation for stabilization of pelvic fractures should be considered as a technical option, especially for minimally invasive stabilization of complex fractures, either as a primary or secondary stabilization.
Intestine Health and Barrier Function in Fattening Rabbits Fed Bovine Colostrum
Authors: Aidos Lucia , Pallaoro Margherita , Mirra Giorgio , Serra Valentina , Castrica Marta , Agradi Stella , Curone Giulio , Vigo Daniele , Riva Federica , Balzaretti Claudia Maria , De Bellis Roberta , Pastorelli Grazia , Brecchia Gabriele , Modina Silvia Clotilde , Di Giancamillo Alessia
Published: November 2023

The permeability of the immature intestine is higher in newborns than in adults; a damaged gut barrier in young animals increases the susceptibility to digestive and infectious diseases later in life. It is therefore of major importance to avoid impairment of the intestinal barrier, specifically in a delicate phase of development, such as weaning. This study aimed to evaluate the effects of bovine colostrum supplementation on the intestinal barrier, such as the intestinal morphology and proliferation level and tight junctions expression (zonulin) and enteric nervous system (ENS) inflammation status (through the expression of PGP9.5 and GFAP) in fattening rabbits. Rabbits of 35 days of age were randomly divided into three groups (n = 13) based on the dietary administration: commercial feed (control group, CTR) and commercial feed supplemented with 2.5% and 5% bovine colostrum (BC1 and BC2 groups, respectively). Rabbits receiving the BC1 diet showed a tendency to have better duodenum morphology and higher proliferation rates (p < 0.001) than the control group. An evaluation of the zonulin expression showed that it was higher in the BC2 group, suggesting increased permeability, which was partially confirmed by the expression of GFAP. Our results suggest that adding 2.5% BC into the diet could be a good compromise between intestinal morphology and permeability, since rabbits fed the highest inclusion level of BC showed signs of higher intestinal permeability.
Utilization of Mirror Visual Feedback for Upper Limb Function in Poststroke Patients: A Systematic Review and Meta-Analysis
Authors: Kim Hyunjoong , Lee Eunsang , Jung Jihye , Lee Seungwon
Published: November 2023

Mirror visual feedback (MVF), a noninvasive treatment method, is attracting attention as a possibility to promote the recovery of upper limb function in stroke patients. However, the cognitive effects of this therapy have received limited attention in the existing literature. To address this gap, we conducted a systematic review and meta-analysis to investigate the relationship between upper limb function and cognition in stroke patients and to evaluate the effect of MVF on improving upper limb function. A comprehensive search was performed on the Embase, MEDLINE, and PubMed databases to identify original articles and clinical studies published between 2013 and 2022. Qualitative analysis was performed using the Cochrane Risk of Bias tool, and in the quantitative analysis, a random-effects model was used as the effect model, and standard mean difference (SMD) was used as the effect measure. Eight studies that met the inclusion criteria were entered in the analysis. Data extraction included an assessment tool for upper extremity function. Results of the quantitative analysis demonstrate that MVF was effective in improving upper extremity function in stroke patients (SMD = 0.94, 95% CI 0.69 to 1.20). In conclusion, this systematic review and meta-analysis provides evidence supporting the effectiveness of MVF in improving upper limb function in stroke patients. However, further studies are needed to investigate the cognitive effects of MVF and elucidate the underlying mechanisms.
A Cyber-Physical All-Hazard Risk Management Approach: The Case of the Wastewater Treatment Plant of Copenhagen
Authors: Bosco Camillo , Thirsing Carsten , Jaatun Martin Gilje , Ugarelli Rita
Published: November 2023

The ongoing digitalization of critical infrastructures enables more efficient processes, but also comes with new challenges related to potential cyber-physical attacks or incidents. To manage their associated risk, a precise and systematic framework should be adopted. This paper describes a general methodology that is consistent with the Risk Management ISO (31000-2018) and builds on specific tools developed within the H2020 digital-water.city (DWC) project. The approach has been demonstrated for a digital solution of the DWC project that allows to visualize inflow predictions for the Wastewater Treatment Plant (WWTP) in the city of Copenhagen. Specifically, the risk assessment and risk treatment steps are demonstrated in the case of the spoofing of the web interface where misleading forecast data may turn into fallacious maintenance schedules for the operators. The adopted methodology applied to the selected use case led to the identification of convenient measures for risk mitigation.
Study of the Spatiotemporal Variations, Source Determination, and Potential Ecological Risk of Organophosphate Esters in Typical Coastal Tourist Resorts in China
Authors: Cao Xuezhi , Wang Bingbing , Liu Xinxin , Cheng Jichun , Wang Shiliang
Published: November 2023

Investigation of the environmental occurrence and behavior of organophosphate esters (OPEs) is very important and is becoming a hot topic in the academic community. In this study, 12 targeted OPEs in the water and sediment from 19 coastal tourist resorts in the Shandong Peninsula in China were analyzed to show their concentrations, spatial variations, and potential ecological risks. The results showed that the total concentrations of OPEs (ΣOPEs) were in the range of 18.52–3069.43 ng/L in the water and 3.20–568.76 ng/g in the sediment. The dominant OPEs in the water and sediment were tris (2-chloroisopropyl) phosphate (TCIPP), tris (2-chloroethyl) phosphate (TCEP), and triethyl phosphate (TEP). The OPE concentrations in the water were ranked as dry season > normal season > wet season. The sewage treatment plants near tourist resorts were important contributors to the level of OPEs in the water. Triphenyl phosphate (TPHP), tri-n-butyl phosphate (TNBP), and resorcinol-bis(diphenyl)phosphate (RDP) had a relatively higher ecological risk than other OPEs in the water samples. Industrial emissions might be the main source of OPEs in the coastal tourist resorts of Shandong Peninsula in China. The results of this study verified that OPEs occur in the water and sediment of coastal tourist resorts, and more attention should be given to the existence of OPEs and the safety of aquatic environments near coastal tourist resorts.
Method for Distinguishing Sargassum and Zostera in the Seto Inland Sea Using Sentinel-2 Data
Authors: Song Shilin , Sakuno Yuji
Published: November 2023

Coastal blue carbon ecosystems are crucial to mitigating global warming. To accurately calculate the blue carbon stock, the existing amount of each species in seaweed and seagrass (SWSG) beds must be estimated to calculate the amount of CO2 absorbed by each species. However, there exists no efficient and comprehensive method for separating SWSG species. Remote sensing techniques hold promise in addressing this issue. This study used satellite Sentinel-2 data to differentiate and map the areas in which Sargassum and Zostera flourish in the Seto Inland Sea. A two-step approach was proposed to separate these algae. First, the SWSG bed area was estimated using the bottom index method, which has been commonly used for sediment mapping. Consequently, using spectral characteristics obtained from field surveys, the Sargassum and Zostera distinguishing index was developed to efficiently separate Sargassum and Zostera. This algorithm was applied to Sentinel 2 data to create a distribution map of Sargassum and Zostera in the Seto Inland Sea. When the map was compared with SWSG bed maps, obtained using field survey-based methods, it showed high credibility, meaning that the proposed method can be used to repeatedly and easily understand seasonal changes in SWSG types in this area in the future.
Flood Forecasting Using Hybrid LSTM and GRU Models with Lag Time Preprocessing
Authors: Zhang Yue , Zhou Zimo , Van Griensven Thé Jesse , Yang Simon X. , Gharabaghi Bahram
Published: November 2023

Climate change and urbanization have increased the frequency of floods worldwide, resulting in substantial casualties and property loss. Accurate flood forecasting can offer governments early warnings about impending flood disasters, giving them a chance to evacuate and save lives. Deep learning is used in flood forecasting to improve the timeliness and accuracy of flood water level predictions. While various deep learning models similar to Long Short-Term Memory (LSTM) have achieved notable results, they have complex structures with low computational efficiency, and often lack generalizability and stability. This study applies a spatiotemporal Attention Gated Recurrent Unit (STA-GRU) model for flood prediction to increase the models’ computing efficiency. Another salient feature of our methodology is the incorporation of lag time during data preprocessing before the training of the model. Notably, for 12-h forecasting, the STA-GRU model’s R-squared (R2) value increased from 0.8125 to 0.9215. Concurrently, the model manifested reduced root mean squared error (RMSE) and mean absolute error (MAE) metrics. For a more extended 24-h forecasting, the R2 value of the STA-GRU model improved from 0.6181 to 0.7283, accompanied by diminishing RMSE and MAE values. Seven typical deep learning models—the LSTM, the Convolutional Neural Networks LSTM (CNNLSTM), the Convolutional LSTM (ConvLSTM), the spatiotemporal Attention Long Short-Term Memory (STA-LSTM), the GRU, the Convolutional Neural Networks GRU (CNNGRU), and the STA-GRU—are compared for water level prediction. Comparative analysis delineated that the use of the STA-GRU model and the application of the lag time pre-processing method significantly improved the reliability and accuracy of flood forecasting.
Revealing the Extent of Pesticide Runoff to the Surface Water in Agricultural Watersheds
Authors: Kim Young-Eun , Jeon Darae , Lee Hyeri , Huh Yujeong , Lee Soohyung , Kim Jong Guk , Kim Hyoung Seop
Published: November 2023

Pesticides are beneficial in protecting crops from pests and improving agricultural productivity; however, concerns on pesticide pollution in water have increased due to their indiscriminate use and lack of adequate regulations. Many studies have focused on the risks of pesticides considering the limited number and types of pesticide residues in crops and soils, and duration, and very few have focused on surface water throughout the year. Therefore, this study comprehensively identified 308 pesticides in surface water samples collected monthly over one year in the Saemangeum Basin, Korea. Both targeted and non-targeted analyses were used to identify 171 and 24 pesticides, respectively. Results highlight the extensive extent of pesticide contamination. Among the quantified pesticides, bromobutide and pretilachlor consistently exhibited high concentrations and risk levels, as indicated by their elevated risk quotient (RQ) values. Seasonal variations in pesticide concentrations revealed distinct patterns with intensified herbicide use during summer and increased insecticide concentrations during autumn. This study highlights the presence, distribution, and associated ecological risks of pesticides in surface waters, emphasizing the necessity of comprehensive monitoring and regulatory measures to protect aquatic ecosystems. The high RQ values identified for specific pesticides underscore the urgent need to implement effective strategies to mitigate these environmental risks.
Correction: Yasmeen et al. The Synergy of Water Resource Agglomeration and Innovative Conservation Technologies on Provincial and Regional Water Usage Efficiency in China: A Super SBM-DEA Approach. Water 2023, 15, 3524
Authors: Yasmeen Rizwana , Hao Gang , Ye Yusen , Shah Wasi Ul Hassan , Tang Caihong
Published: November 2023

In the original publication [...]
Tap Water Quality: Challenges and Psychological Consequences
Authors: Khalid Warda , Shiyi Chen , Ngata Mbega Ramadhani , Ali Asmat , Alrefaei Abdulwahed Fahad , Almutairi Mikhlid H. , Kulsoom Isma , Hussain Wakeel , Jat Baloch Muhammad Yousuf
Published: November 2023

Investigating drinking water quality is crucial for public health, as clean water access is a fundamental requirement for a healthy life. To comprehensively assess Karachi’s drinking water quality, 152 water samples were systematically collected from five districts: Malir, Karachi West, Karachi East, Karachi South, and Karachi Central. The investigation involved analyzing various physicochemical and microbiological parameters in comparison to WHO 2011 guidelines. Additionally, integrated techniques like principal component analysis and water quality index computation offer insights into both potable and non-potable water aspects, with a focus on health-related well-being. Elevated levels of turbidity and chloride were identified across all five districts, with the residual chloride surpassing permissible limits in Karachi West and Karachi Central. Coliform and E. coli levels exhibited significant variations, with the highest mean values recorded in Karachi Central and the lowest in Karachi East. The overall analysis revealed that only 16.67%, 38.71%, 50%, 43.33%, and 58.06% of the water supply is suitable for drinking in Malir, Karachi West, Karachi East, Karachi South, and Karachi Central, respectively, while 83.33%, 61.29%, 50%, 56.67%, and 41.94% are unsuitable for drinking, posing substantial health risks. Urgent interventions in water quality management and public health are imperative to mitigate these risks associated with substandard drinking water.
Optimizing Voltage Stability in Distribution Networks via Metaheuristic Algorithm-Driven Reactive Power Compensation from MDHD EVs
Authors: Zhang Chen , Sedghisigarchi Kourosh , Sheinberg Rachel , Narayana Gowda Shashank , Gadh Rajit
Published: November 2023

The deployment of medium-duty and heavy-duty (MDHD) electric vehicles (EVs), characterized by their substantial battery capacity and high charging power demand, poses a potential threat to voltage stability within distribution networks. One possible solution to voltage instability is reactive power compensation from charging MDHD EVs. However, this process must be carefully facilitated in order to be effective. This paper introduces an innovative distribution network voltage stability solution by first identifying the network’s weakest buses and then utilizing a metaheuristic algorithm to schedule reactive power compensation from MDHD EVs. In the paper, multiple metaheuristic algorithms, including genetic algorithms, particle swarm optimization, moth flame optimization, salp swarm algorithms, whale optimization, and grey wolf optimization, are subjected to rigorous evaluation concerning their efficacy in terms of voltage stability improvement, power loss reduction, and computational efficiency. The proposed methodology optimizes power flow with the salp swarm algorithm, which was determined to be the most effective tool, to mitigate voltage fluctuations and enhance overall stability. The simulation results, conducted on a modified IEEE 33 bus distribution system, convincingly demonstrate the algorithm’s efficacy in augmenting voltage stability and curtailing power losses, supporting the reliable and efficient integration of MDHD EVs into distribution networks.
Klasifikasi Rentang Usia Dan Gender Dengan Deteksi Suara Menggunakan Metode Deep Learning Algoritma Cnn (Convolutional Neural Network)
Authors: Karenina Vita , Erinsyah Moh Fiqih , Wibowo Dega Surono
Published: November 2023

The research discusses the identification of human voices based on gender by utilizing the differences in voice characteristics between males and females. In addition to differences in vocal tract size, factors such as length, thickness, and stiffness of the vocal cords also play a role in producing the differences in fundamental frequency between the two genders. Fundamental frequency serves as an indicator used in acoustic analysis to classify gender based on voice. In the automatic classification of voices, sound processing techniques and machine learning are key in system development. Gender recognition methods based on voice involve acoustic analysis using voice features such as fundamental frequency, formants, duration, intensity, and intonation patterns. Diverse voice datasets containing recordings of both male and female voices are used to train gender recognition models. From the results of research from modeling using CNN on audio to get 92% accuracy and for testing results it is good enough in classifying.

Keywords – Deep Learning, Voice Recognition, Audio Classification, CNN, Gender
Alat Pengolah Limbah Rumah Tangga Menjadi Kompos Berbasis Mikrokontroler
Authors: Khakim Lukmanul , Budihartono Eko
Published: November 2023

Rumah tangga merupakan penyumbang sampah terbanyak, berbagai jenis sampah dihasilkan, mulai dari sampah organik, non organik dan lain sebagainya. Jika setiap rumah tangga menghasilkan 2 kg sampah setiap harinya, dan sampah tersebut langsung dibuang ke tempat pembuangan sampah sementara (TPS), maka sangat banyak jumlah sampah yang tertimbun di TPS tersebut. Maka dari itu diperlukan alat yang berfungsi untuk mengolah sampah yang dapat didaur ulang menjadi kompos, yaitu sampah atau sisa makanan yang tergolong sampah organik. Alat yang dimaksud terdiri dari motor stepper nema 17 sebagai pemotong dan pengaduk sampah supaya tercampur dengan tanah, sensor YL-69 sebagai pendeteksi kelembapan tanah, sensor DS18B20 sebagai pendeteksi suhu tanah dan dua pompa mini sebagai penyuplai air dan EM4. Dari hasil penelitian ini, YL-69 mendeteksi kelembapan tanah 17% sampai 86%, artinya kelembapan tanah meningkat, maka stepper akan aktif untuk mengaduk tanah dan sampah organik. Selanjutnya DS18B20 mendeteksi suhu tanah 25℃ sampai 34℃, artinya ketika suhu antara 30℃ sampai 34℃ maka proses pengomposan berlangsung, suplai air dan EM4 terhenti secara otomatis.

Kata Kunci – Sampah Organik; Kompos; Mikrokontroler; DS18B20, YL-69.