bluuebunny/crossref_metadata_2025 huggingface dataset:
Opto-Electronic Hybrid Network Based on Scattering Layers
Authors: Zhu Jiakang , An Qichang , Yang Fei , Liu Yuanguo , Huo Yinlong
Published: October 2023

Owing to the disparity between the computing power and hardware development in electronic neural networks, optical diffraction networks have emerged as crucial technologies for various applications, including target recognition, because of their high speed, low power consumption, and large bandwidth. However, traditional optical diffraction networks and electronic neural networks are limited by long training durations and hardware requirements for complex applications. To overcome these constraints, this paper proposes an innovative opto-electronic hybrid system that combines optical diffraction networks with electronic neural networks. Using scattering layers to replace the diffraction layers in traditional optical diffraction networks, this hybrid system circumvents the challenging training process associated with diffraction layers. Spectral outputs of the optical diffraction network were processed using a simple backpropagation neural network, forming an opto-electronic hybrid network exhibiting exceptional performance with minimal data. For three-class target recognition, this network attains a classification accuracy of 93.3% within a substantially short training time of 9.2 s using only 100 data samples (training: 70 and testing: 30). Furthermore, it demonstrates exceptional insensitivity to position errors in scattering elements, enhancing its robustness. Therefore, the proposed opto-electronic hybrid network presents substantial application prospects in the fields of machine vision, face recognition, and remote sensing.
iCanClean Removes Motion, Muscle, Eye, and Line-Noise Artifacts from Phantom EEG
Authors: Downey Ryan J. , Ferris Daniel P.
Published: October 2023

The goal of this study was to test a novel approach (iCanClean) to remove non-brain sources from scalp EEG data recorded in mobile conditions. We created an electrically conductive phantom head with 10 brain sources, 10 contaminating sources, scalp, and hair. We tested the ability of iCanClean to remove artifacts while preserving brain activity under six conditions: Brain, Brain + Eyes, Brain + Neck Muscles, Brain + Facial Muscles, Brain + Walking Motion, and Brain + All Artifacts. We compared iCanClean to three other methods: Artifact Subspace Reconstruction (ASR), Auto-CCA, and Adaptive Filtering. Before and after cleaning, we calculated a Data Quality Score (0–100%), based on the average correlation between brain sources and EEG channels. iCanClean consistently outperformed the other three methods, regardless of the type or number of artifacts present. The most striking result was for the condition with all artifacts simultaneously present. Starting from a Data Quality Score of 15.7% (before cleaning), the Brain + All Artifacts condition improved to 55.9% after iCanClean. Meanwhile, it only improved to 27.6%, 27.2%, and 32.9% after ASR, Auto-CCA, and Adaptive Filtering. For context, the Brain condition scored 57.2% without cleaning (reasonable target). We conclude that iCanClean offers the ability to clear multiple artifact sources in real time and could facilitate human mobile brain-imaging studies with EEG.
Directional Resonant MEMS Acoustic Sensor and Associated Acoustic Vector Sensor
Authors: Ivancic Justin , Karunasiri Gamani , Alves Fabio
Published: October 2023

This paper reports on the design, modeling, analysis, and evaluation of a micro-electromechanical systems acoustic sensor and the novel design of an acoustic vector sensor array (AVS) which utilized this acoustic sensor. This research builds upon previous work conducted to develop a small, lightweight, portable system for the detection and location of quiet or distant acoustic sources of interest. This study also reports on the underwater operation of this sensor and AVS. Studies were conducted in the lab and in the field utilizing multiple acoustic sources (e.g., generated tones, gun shots, drones). The sensor operates at resonance, providing for high acoustic sensitivity and a high signal-to-noise ratio (SNR). The sensor demonstrated a maximum SNR of 88 dB with an associated sensitivity of −84.6 dB re 1 V/μPa (59 V/Pa). The sensor design can be adjusted to set a specified resonant frequency to align with a known acoustic signature of interest. The AVS demonstrated an unambiguous, 360-degree, in-plane, azimuthal coverage and was able to provide an acoustic direction of arrival to an average error of within 3.5° during field experiments. The results of this research demonstrate the potential usefulness of this sensor and AVS design for specific applications.
Indoor Localization Algorithm Based on a High-Order Graph Neural Network
Authors: Kang Xiaofei , Liang Xian , Liang Qiyue
Published: October 2023

Given that fingerprint localization methods can be effectively modeled as supervised learning problems, machine learning has been employed for indoor localization tasks based on fingerprint methods. However, it is often challenging for popular machine learning models to effectively capture the unstructured data features inherent in fingerprint data that are generated in diverse propagation environments. In this paper, we propose an indoor localization algorithm based on a high-order graph neural network (HoGNNLoc) to enhance the accuracy of indoor localization and improve localization stability in dynamic environments. The algorithm first designs an adjacency matrix based on the spatial relative locations of access points (APs) to obtain a graph structure; on this basis, a high-order graph neural network is constructed to extract and aggregate the features; finally, the designed fully connected network is used to achieve the regression prediction of the location of the target to be located. The experimental results on our self-built dataset show that the proposed algorithm achieves localization accuracy within 1.29 m at 80% of the cumulative distribution function (CDF) points. The improvements are 59.2%, 51.3%, 36.1%, and 22.7% compared to the K-nearest neighbors (KNN), deep neural network (DNN), simple graph convolutional network (SGC), and graph attention network (GAT). Moreover, even with a 30% reduction in fingerprint data, the proposed algorithm exhibits stable localization performance. On a public dataset, our proposed localization algorithm can also show better performance.
CANAttack: Assessing Vulnerabilities within Controller Area Network
Authors: Oladimeji Damilola , Rasheed Amar , Varol Cihan , Baza Mohamed , Alshahrani Hani , Baz Abdullah
Published: October 2023

Current vehicles include electronic features that provide ease and convenience to drivers. These electronic features or nodes rely on in-vehicle communication protocols to ensure functionality. One of the most-widely adopted in-vehicle protocols on the market today is the Controller Area Network, popularly referred to as the CAN bus. The CAN bus is utilized in various modern, sophisticated vehicles. However, as the sophistication levels of vehicles continue to increase, we now see a high rise in attacks against them. These attacks range from simple to more-complex variants, which could have detrimental effects when carried out successfully. Therefore, there is a need to carry out an assessment of the security vulnerabilities that could be exploited within the CAN bus. In this research, we conducted a security vulnerability analysis on the CAN bus protocol by proposing an attack scenario on a CAN bus simulation that exploits the arbitration feature extensively. This feature determines which message is sent via the bus in the event that two or more nodes attempt to send a message at the same time. It achieves this by prioritizing messages with lower identifiers. Our analysis revealed that an attacker can spoof a message ID to gain high priority, continuously injecting messages with the spoofed ID. As a result, this prevents the transmission of legitimate messages, impacting the vehicle’s operations. We identified significant risks in the CAN protocol, including spoofing, injection, and Denial of Service. Furthermore, we examined the latency of the CAN-enabled system under attack, finding that the compromised node (the attacker’s device) consistently achieved the lowest latency due to message arbitration. This demonstrates the potential for an attacker to take control of the bus, injecting messages without contention, thereby disrupting the normal operations of the vehicle, which could potentially compromise safety.
Analysis of the Correctness of Mapping the Passage of a Semi-Trailer through a Road Obstacle on a Road Simulator
Authors: Czarnuch Arkadiusz , Stembalski Marek , Szydłowski Tomasz , Batory Damian
Published: October 2023

Road simulators enable accelerated durability tests under similar-to-real road conditions. However, the road simulator itself generates the signals with the appropriate strength and amplitude that is adequate to the response registered by the sensors during the real run. Therefore, there is a need for verification of the validity of the representation of vehicle runs on a road simulator in terms of the shape of the generated profile and possible sources of uncertainty. The tests in this study were carried out for a multi-axle vehicle passing an obstacle of known shape. Various signals were registered while the vehicle was passing over the obstacle. The MTS (System Corporation) road simulator’s response to the signal given by the obstacle was then checked. The results showed a 99% correlation between the simulation and the road test results. A numerical model of the vehicle was developed to verify the quality of representation of the real conditions by the road simulator, especially in terms of forces resulting from the road profile. Interestingly, the input signal generated by the road simulator provided a very good accuracy of the vehicle response, as tested with use of the numerical model.
State-of-the-Practice Survey: United States Departments of Transportation Worker Injuries and Safety Program Efforts
Authors: Marji Lana K. , Zech Wesley C. , Kirby Jason T.
Published: October 2023

The State-of-the-Practice Survey on United States Departments of Transportation (DOTs) Worker Injuries and Safety Program Efforts is a comprehensive report that provides valuable insights into the safety programs of state DOTs. The survey was conducted using a web-based questionnaire that was distributed to all 50 state DOTs and received a response rate of 44% (22 states). The survey consisted of 40 questions that were designed to gather information about the safety programs of state DOTs, including their training and education efforts, injury analysis practices, and safety efforts. The survey responses were analyzed using descriptive statistics and a thematic analysis approach. The results highlighted contrasts in safety efforts across responding DOTs, with various methods of injury documentation, data collection, and the implementation of safety-related policies and procedures. The report offers recommendations for reducing worker injuries and illnesses, including the need for standardized injury documentation and data collection practices, the provision of regular and updated training to address new hazards that may arise due to changes in job tasks or procedures, the allocation of adequate funding and resources to support safety programs, and the development of a return-to-work program to facilitate the prompt return of injured workers. Additionally, ergonomic assessments and training should be provided to prevent musculoskeletal injuries. The report concludes that state DOTs can benefit from sharing best practices and collaborating on safety initiatives in order to improve worker safety and reduce the incidence of injuries and illnesses. The findings of this survey may be beneficial to any DOT implementing worker safety best practices within their respective agency. The limitations of the study include a lack of inferential statistical analysis due to the restricted statistical power of the sample size.
Impact of Large-Scale Electric Vehicles’ Promotion in Thailand Considering Energy Mix, Peak Load, and Greenhouse Gas Emissions
Authors: Paudel Ashok , Pinthurat Watcharakorn , Marungsri Boonruang
Published: October 2023

Thailand’s policies are in accord with the global drive to electrify transportation vehicle fleets due to climate concerns. This dedication is evident through its adoption of the 30@30 initiative and the planned ban on new internal combustion (IC) engine vehicles by 2035, showcasing a strong commitment. The objective of this study was to utilize the Low Emission Analysis Platform (LEAP) software to model the transition possibilities for electric vehicle (EV). Emphasis was placed on the future of the light-duty vehicle (LDV) sector, encompassing the energy sources, electric power demands, and greenhouse gas (GHG) emissions. Two scenarios were evaluated: one involving rapid economic growth and the other characterized by a more-gradual expansion. The former projection foresees 382 vehicles per thousand people by 2040, while the latter estimate envisions 338 vehicles. In the scenario of high growth, the vehicle stock could surge by 70% (27-million), whereas in the case of low growth, it might experience a 47% rise (23.3-million) compared to the base year (15.8 million). The increased adoption of EVs will lead to a decrease in energy demand owing to improved fuel efficiency. Nonetheless, even in the most-extreme EV scenarios, the proportion of electricity in the energy mix will remain below one-third. While GHG emissions will decrease, there is potential for even greater emission control through the enforcement of stricter emission standards. Significant EV adoption could potentially stress power grids, and the demand for charging might give rise to related challenges. The deployment of public fast charging infrastructure could provide a solution by evenly distributing the load across the day. In the most-rapid EV penetration scenario, a public charging program could cap the demand at 9300 MW, contrasting with the 21,000 MW demand for home charging. Therefore, a recommended approach involves devising an optimal strategy that considers EV adoption, a tariff structure with incentives, and the preparedness of the infrastructure.
Compensation Admittance Load Flow: A Computational Tool for the Sustainability of the Electrical Grid
Authors: Risi Benedetto-Giuseppe , Riganti-Fulginei Francesco , Laudani Antonino , Quercio Michele
Published: October 2023

Compensation Admittance Load Flow (CALF) is a power flow analysis method that was developed to enhance the sustainability of the power grid. This method has been widely used in power system planning and operation, as it provides an accurate representation of the power system and its behavior under different operating conditions. By providing a more accurate representation of the power system, it can help identify potential problems and improve the overall performance of the grid. This paper proposes a new approach to the load flow (LF) problem by introducing a linear and iterative method of solving LF equations. The aim is to obtain fast results for calculating nodal voltages while maintaining high accuracy. The proposed CALF method is fast and accurate and is suitable for the iterative calculations required by large energy utilities to solve the problem of quantifying the maximum grid acceptance capacity of new energy from renewable sources and new loads, known as hosting capacity (HC) and load capacity (LC), respectively. Speed and accuracy are achieved through a properly designed linearization of the optimization problem, which introduces the concept of compensation admittance at the node. The proposed method was validated by comparing the results obtained with those coming from state-of-the-art methods.
Do Geographical Indication Products Promote the Growth of the Agricultural Economy? An Empirical Study Based on Meta-Analysis
Authors: Li Chunyan , Gao Jianmei , Ge Lanqing , Hu Weina , Ban Qi
Published: October 2023

Do geographical indication products help facilitate the development of the agricultural economy? This problem is a point of controversy in the field of global agricultural intellectual property. For a long time, there have been different viewpoints on this problem; that is, there is a positive correlation, negative correlation, U-shape correlation, or no correlation between the geographical indication products and the development of the agricultural economy in the context of different studies. To clarify the influence mechanism between the two and explain why there are these disputes, this study used the meta-analysis method to statistically reanalyze 405 observation values provided in 64 independent research samples from the context of different regions around the world. The study results show that geographical indications not only generate more economic benefits than ordinary products but also contribute to the growth of the agricultural economy by effectively promoting the development of agricultural product trade and the enhancement of agricultural product price. There exists a low positive correlation between the geographical indication products and the agricultural economy (r = 0.176, 95% CI = [0.126, 0.225]). In addition, the promotion effect of geographical indication products on the agricultural economy is regulated by the country of origin of the samples, sample level, publication journal, data type, data acquisition approach, and research method. Our research findings further revealed the internal relationship mechanism between the geographical indication products and the agricultural economy and lay a foundation for better protecting and developing geographical indication products.
Evaluating the Effect of Using Different Levels of Sunflower Hulls as a Source of Fiber in a Complete Feed on Naemi Ewes’ Milk Yield, Composition, and Fatty Acid Profile at 6, 45, and 90 Days Postpartum
Authors: Alobre Mohsen M. , Abdelrahman Mutassim M. , Alhidary Ibrahim A. , Matar Abdulkareem M. , Aljumaah Riyadh S. , Alhotan Rashed A.
Published: October 2023

This study was conducted to evaluate the effect of using different levels of sunflower hulls (SFH) as a source of fiber in a complete feed on Naemi ewes’ milk yield, composition, and fatty acid profile at 6, 45, and 90 days postpartum. In this study, 48 primiparous lactating Naemi ewes were randomly selected for the four treatment groups as follows: C (control), total mixed ratio (TMR; 0% SFH); TMR1, including S12% SFH; TMR2, including S20% SFH; and TMR3, including S28% SFH. The data were analyzed by SAS software 9.4 as a complete randomized design with repeated measurements. Both the S20 and S28 groups showed significant effects on milk yield and persistence at 45 and 90 days compared to the control and S12 groups. The triglyceride concentration level at 6 and 90 days postpartum was significantly higher (p < 0.05; p < 0.001) in the blood serum. The treatment significantly affected fat, protein, and total solids (p < 0.05), with quadratic and cubic responses, respectively. The time significantly influenced protein (p < 0.001), lactose (p < 0.01), and total solids (p < 0.05). A significant difference (p < 0.05) in the treatments showed varying responses in the fatty acid concentration in milk. Saturated fatty acids (SFAs) and omega 6 (n-6)/omega 3 (n-3) in the milk fat of ewes from the S12, S20, and S28 groups were significantly lower compared to the others. Furthermore, the (n-6) and atherogenicity (AI) were high and low, respectively, in S28, which is considered beneficial to human health. In conclusion, ewes can be fed up to 28% SFH during lactation as a complete pelleted feed to obtain an acceptable milk yield, nutritive value, and healthy fatty acid profile.
Towards a Sustainable Future: Economic Cybernetics in Analyzing Romania’s Circular Economy
Authors: Nica Ionuț , Chiriță Nora , Delcea Camelia
Published: October 2023

The Circular Economy represents an essential strategy for a more sustainable future, both for the environment and for the economy and society. The main purpose of this article is to conduct a holistic analysis that highlights Romania’s perspectives in the transition and integration process towards the Circular Economy. In this research, we will use economic cybernetics and complex adaptive systems to uncover the complexity of the Circular Economy. Our aim is also to identify the connections and interactions among its various components. To complete this holistic analysis framework, multiple linear regression (MLR) and autoregressive distributed lag (ARDL) models were employed. MLR was applied to assess the impact of variables such as Waste per capita, Recycling rate by region, Labor productivity, Production of environmental goods, and Circular material use rate on real Gross Domestic Product (GDP) per capita. The time series are extracted from Eurostat databases and cover the period 2010–2021. Given the results obtained through MLR, we applied the ARDL model to study the long-run and short-run causal impact of independent variables on real GDP per capita. The analysis results led us to create an ARDL model from another perspective, namely, to examine how greenhouse gas emissions from production activities and labor productivity per person employed and hour worked affect the generation of municipal waste per capita. Our study delves into the Circular Economy as a pivotal strategy for fostering sustainability, offering an exhaustive, data-backed analysis of its effects on economic performance and environmental health in Romania. In light of our findings, we strongly recommend that future policy development in Romania should be aligned with the National Strategy for the Circular Economy. This would facilitate a more effective transition to sustainable practices, not only enhancing economic indicators but also reducing environmental impact.
Investigation of Exponential Distribution Utilizing Randomly Censored Data under Balanced Loss Functions and Its Application to Clinical Data
Authors: Hasaballah Mustafa M. , Balogun Oluwafemi Samson , Bakr Mahmoud E.
Published: October 2023

In this research, random censoring is employed as a methodology for parameter estimation within the context of an exponential distribution. These parameter estimations are conducted using both the Bayesian and maximum likelihood approaches. In the Bayesian framework, Lindley’s approximation method is applied to derive estimates, which are subsequently assessed under three distinct balanced loss functions. To gauge the efficacy of different estimation techniques, simulation-based investigations are conducted. Additionally, a real-world data analysis is executed to illustrate the practical applicability of these methodologies. The findings consistently underscore the superiority of Bayesian parameter estimates in comparison with their maximum likelihood counterparts across all analyzed methodologies.
Log-Extended Exponential–Geometric Distribution: Moments and Inference Based on Generalized Order Statistics
Authors: AL-Zaydi Areej M.
Published: October 2023

In this paper, we provide explicit expressions as well as recurrence relations for the single and product moments of generalized order statistics from the log-extended exponential–geometric distribution. These relations are utilized to discuss the special cases of generalized order statistics, and some numerical computations are carried out. Further, we use these results to obtain the best linear unbiased estimators for the location and scale parameters based on progressively Type-II right censored samples. Finally, a real data application is presented.
Digitalisation and IT Strategy in the Hospitality Industry
Authors: Wynn Martin , Lam Carmen
Published: October 2023

This article explores how digitalisation is impacting the hospitality industry and assesses the evolving role of an Information Technology (IT) strategy in the digitalisation process. The research approach is qualitative and inductive, based on six in-depth interviews with senior IT professionals in the hospitality industry. Findings indicate significant differences in the role of an IT strategy in guiding digitalisation in the companies studied. The depth of information provided by the interviewees supports the development and application of a model that profiles the companies regarding their degree of digitalisation and technology integration. Analysis of interview material allows the identification of key properties for successful digitalization: process agility, workforce adaptability, and technology manageability, along with a clear data culture and ensured cybersecurity. However, disparate systems and technologies, and a lack of data integrity, are key issues that leave hospitality companies with difficult choices in progressing digitalisation initiatives. The applied model and identification of key properties for successful digitalisation contribute to the development of related theory and can also be used as a reference point for senior IT professionals working in the industry.
Association of Bone Disorder and Gene Polymorphism of PPAR-γ Pro12 Ala in Egyptian Children with β-Thalassemia
Authors: Hamied Ahmed M. Abdel , Ahmed Heba Mostafa , Eldahshan Dina H. , Morgan Dalia S. , Meged Abdel Meged A. Abdel , Elgendy Marwa O. , Imam Mohamed S. , Alotaibi Turki A. H. , Alotaibi Majed M. S. , Alotaibi Manal T. N. , Alshalan Sarah S. S. , Elgendy Sara O.
Published: October 2023

β-thalassemia is a genetic disorder affecting chromosome 16, inherited from one or both parents. In spite of the improved treatment of the hematological disorder and its complications, β-thalassemic patients still exhibit an imbalance in bone mineral turnover, resulting in diminished bone mineral density (BMD), more evident in the lumbar spine. The purpose of this study was to investigate the association between genetic polymorphism of the PPAR-γ gene and the presence of osteopenia or osteoporosis in children with β-thalassemia. This case–control study was conducted on 50 children with β-thalassemia from the pediatric hematology unit of Beni-Suef University Hospital, including 50 healthy children as the control group. The age range was 8 to 18 years. Samples of patients and control subjects were analyzed for the presence of polymorphisms of the PPAR-γ gene and other blood labs. An assay of BMD measure using dual-energy X-ray absorptiometry (DXA) was performed to investigate osteopenia or osteoporosis. Statistical analysis was used to investigate the relationship between the risk of osteopenia or osteoporosis and the presence of PPAR-γ Pro12Ala gene polymorphism. Eighteen (eleven males and seven females) of fifty patients (representing 36% of the patients group) have osteopenia with low bone mineral density (Z-score is −1 or less than 1). There was no statistically significant difference between BMD measurements in males and females. By comparing the frequency of 12 Ala gene polymorphisms between the patient group and the control group, we found that no statistically significant difference was detected. The BMD values were not significantly different between the groups of PPAR-γ Pro12Ala gene polymorphism. In conclusion, decreased BMD levels are frequent in β-thalassemia patients. PPAR-γ Pro12Ala gene polymorphism is not common in Egyptian patients with β-thalassemia. No significant relationship was found between the PPAR-γ Pro12Ala gene polymorphism and low BMD levels or osteopenia in Egyptian β-thalassemia patients. However, further studies on a larger population of Egyptian patients are needed to confirm this finding.
In Situ Toxicity Reduction and Food Safety Assessment of Pak Choi (Brassica campestris L.) in Cadmium-Contaminated Soil by Jointly Using Alkaline Passivators and Organic Fertilizer
Authors: Jiao Wei , Li Zhi , Li Ruiping , Guo Jiafeng , Hou Xiaoshu , Zhang Xi , Wang Fangli
Published: October 2023

An economical and effective method is still lacking for cadmium (Cd) toxicity reduction and food product safety improvement in soil–vegetable systems. Therefore, this study aimed to reduce the Cd toxicity to pak choi (Brassica campestris L.) by jointly using passivators and organic fertilizer, highlighting food products’ safety based on pot experiments. The results showed that compared with the control, organic fertilizer decreased the Cd content in edible parts and the soil’s available Cd by 48.4% and 20.9% on average, respectively, due to the 0.15-unit increases in soil pH. Once jointly applied with passivators, the decrements increased by 52.3–72.6% and 32.5–52.6% for the Cd content in edible parts and for the soil’s available Cd, respectively, while the pH increment increased by 0.15–0.46 units. Compared with the control, the transport factor of Cd was reduced by 61.9% and 50.9–55.0% when applying organic fertilizer alone and together with the passivators, respectively. The combination treatment of biochar and organic fertilizer performed the best in decreasing the Cd content in the edible parts and the soil’s available Cd. The combination treatment of fish bone meal and organic fertilizer induced the greatest increases in soil pH. The grey relational analysis results showed that the combination treatment of biochar and organic fertilizer performed the best in reducing the potential Cd pollution risk, thereby highlighting the vegetable food safety. This study provides a potential economical and effective technology for toxicity reduction and food safety in Cd-polluted soil.
CKM Matrix Parameters from the Exceptional Jordan Algebra
Authors: Patel Aditya Ankur , Singh Tejinder P.
Published: October 2023

We report a theoretical derivation of the Cabibbo–Kobayashi–Maskawa (CKM) matrix parameters and the accompanying mixing angles. These results are arrived at from the exceptional Jordan algebra applied to quark states, and from expressing flavor eigenstates (i.e., left chiral states) as a superposition of mass eigenstates (i.e., the right chiral states) weighted by the square root of mass. Flavor mixing for quarks is mediated by the square root mass eigenstates, and the mass ratios used are derived from earlier work from a left–right symmetric extension of the standard model. This permits a construction of the CKM matrix from first principles. There exist only four normed division algebras, and they can be listed as follows: the real numbers R, the complex numbers C, the quaternions H and the octonions O. The first three algebras are fairly well known; however, octonions as algebra are less studied. Recent research has pointed towards the importance of octonions in the study of high-energy physics. Clifford algebras and the standard model are being studied closely. The main advantage of this approach is that the spinor representations of the fundamental fermions can be constructed easily here as the left ideals of the algebra. Also, the action of various spin groups on these representations can also be studied easily. In this work, we build on some recent advances in the field and try to determine the CKM angles from an algebraic framework. We obtain the mixing angle values as θ12=11.093∘,θ13=0.172∘,θ23=4.054∘. In comparison, the corresponding experimentally measured values for these angles are 13.04∘±0.05∘,0.201∘±0.011∘,2.38∘±0.06∘. The agreement of theory with experiment is likely to improve when the running of quark masses is taken into account.
Source Apportionment and Health Risk Assessment of Heavy Metals in Karst Water from Abandoned Mines in Zhangqiu, China
Authors: Han Yu , Liu Yuxiang , Wei Shanming , Wang Min , Ding Guantao , Song Xiaoyu , Shen Dandan , Gao Shuai , Tang Cui , Ma Guanqun
Published: October 2023

This study investigated the hydrochemical characteristics and human health risks of groundwater in a pollution accident site. By collecting 27 samples, the content of the heavy metal(oid)s (As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn) was tested, statistical analysis of heavy metal ion concentration was conducted, and the Nemerow comprehensive contamination index was determined. The health risk assessment was conducted based on the test results, and correlation analysis, as well as principal component analysis, were used to resolve the possible sources of heavy metal contamination. The results showed that the total hardness and total dissolved solids were significantly higher, and the potassium permanganate index and ammonia nitrogen content were higher in some samples. The heavy metal content was higher than the Class III groundwater quality standard (GB/T14848-2017). The health risk assessment showed that the total health risks posed by the eight heavy metal(oid)s in the study area through drinking water and dermal contact exceeded the maximum acceptable level. In general, the health risk is slightly higher for adults than for children. The groundwater in the abandoned mines has unsafe levels of heavy metal(oid)s for human health, but the normal drinking water remains safe for surrounding residents. Carcinogenic heavy metal(oid)s are the main source of health risks in the region, and the impact of Cr on human health requires further attention.
Advanced Oxidation Process: Applications and Prospects
Authors: Hodaifa Gassan , Zuorro Antonio , Dominguez Joaquín R. , Rodríguez Juan García , Peres José A. , Frontistis Zacharias , Albqmi Mha
Published: October 2023

The generation of waste has increased significantly over the last 50 years [...]
Modeling Wetland Functions: Is Space-to-Time Substitution of the Perimeter–Area Relationship Appropriate?
Authors: Park Junehyeong , Kumar Mukesh , Jones C. Nathan
Published: October 2023

Wetlands’ morphometric or shape properties, such as their area and perimeter, impact a multitude of ecosystem functions and services. However, current models used to quantify these functions often only use area as an independent variable, as the static area and perimeter of different wetlands have been found to be closely related. The study uses monthly inundation maps, derived from remote sensing data, to assess the temporal covariation of geographically isolated wetlands’ perimeter and surface area. The results show that using static representations of wetlands to evaluate temporal dynamic perimeter–area relationships can introduce significant discrepancies and that these discrepancies can be reduced if evaluations using static data are performed separately for each wetlandscape. This study concludes that models that use implicit area–perimeter relationships based on static wetland representations, as is usually the case, should be applied with caution. Additionally, it suggests that incorporating perimeter–area relationships from temporally dynamic data can improve estimates of wetland functions.
Poor Water Quality Persists in Diverse Urban Communities
Authors: Cade Rae , Yu Danlin , Whyte Kyle , Lal Pankaj , Borgerson Cortni
Published: October 2023

While humans need water to survive, water can also efficiently transmit microbial diseases and heavy metals to consumers. Over 50,000 water violations occurred in 2020 and such burdens were not borne equally amongst consumers. Yet, the factors that drive such variation remain unclear. We examined the interactions between water quality and inherited equity gaps in one of the most diverse urban areas in the United States. We used publicly available drinking water datasets to determine which contaminant was most prevalent between 2010–2020 and who was significantly more likely to be affected by this contamination. We found that a lack of legal rights to control the water quality in one’s home (i.e., renting) was the number one predictor of heavy metal violations in a municipality. Individuals who spoke a language other than English were significantly more likely to rent homes with unsafe drinking water. To ensure equity in public health outcomes, current mandates must expand to include the design of actionable plans which include linguistically and culturally diverse residents, landlords, and tenants, as stakeholders in public water and housing decision making and remediation processes.
Recent Progress on Acid Mine Drainage Technological Trends in South Africa: Prevention, Treatment, and Resource Recovery
Authors: Baloyi Jeffrey , Ramdhani Nishani , Mbhele Ryneth , Ramutshatsha-Makhwedzha Denga
Published: October 2023

South Africa is the home of major global mining operations, and the acid mine drainage (AMD) contribution has been attributed to abandoned mine sites and huge pyrite-bearing tailings from coal and gold mines. Determining the true economic impact and environmental liability of AMD remains difficult. Researchers have been looking into several treatment technologies over the years as a way to reduce its possible environmental impact. Different methods for active and passive remediation have been developed to treat AMD. The aim of this review was to describe the AMD-impacted environments and critically discuss the properties of AMD and current prediction and preventative methods and technologies available to treat AMD. Furthermore, this study critically analysed case studies in South Africa, gaps in AMD research, and the limitations and prospects offered by AMD. The study outlined future technological interventions aimed at a pattern shift in decreasing sludge volumes and operational costs while effectively improving the treatment of AMD. The various treatment technologies have beneficial results, but they also have related technical problems. To reduce the formation of AMD, it is recommended that more preventive methods be investigated. Moreover, there is a current need for integrated AMD treatment technologies that result in a well-rounded overall approach towards sustainability in AMD treatment. As a result, a sustainable AMD treatment strategy has been made possible due to water reuse and recovery valuable resources such sulphuric acid, rare earth elements, and metals. The cost of AMD treatment can be decreased with the use of recovered water and resources, which is essential for developing a sustainable AMD treatment process. More study is required in the future to improve the effectiveness of the various strategies used, with a focus on reducing the formation of secondary pollutants and recovery of valuable resources.
Prediction of Daily Water Consumption in Residential Areas Based on Meteorologic Conditions—Applying Gradient Boosting Regression Tree Algorithm
Authors: Li Zhengxuan , Peng Sen , Zheng Guolei , Chu Xianxian , Tian Yimei
Published: October 2023

A more accurate way of water consumption forecasting can be used to help people develop a scheduling plan of water workers more targeting; therefore, this paper aims to establish a forecast model of daily water consumption based on meteorological conditions. At present, most studies of daily water consumption forecasts focus on historical data or single water use influencing factors; moreover, daily water consumption could be influenced by meteorologic conditions. The influence of complex meteorology factors on water consumption is analyzed based on a gradient-boosted regression tree (GBRT) model. The correlation of 10 meteorologic factors has been discussed and divided into 5 categories, including temperature factor, pressure factor, precipitation factor, sunshine factor, and wind factor. Through the GBRT algorithm, the daily water consumption of residential area could be predicted with a maximum error of ±8%. The results show that the average ground temperature (the feature importance accounts for 81% of the total) has the greatest impact on the daily water consumption of the residential community, followed by the somatosensory temperature (the feature importance accounts for 7% of the total). The method can provide the daily water consumption of water consumption nodes with higher precision for municipal water supply network model accuracy. It also provides a reference for water utility operation schemes and urban development planning.
Groundwater Flow Model along a Vertical Profile of the Sardas Landfill in Sabiñánigo, Huesca, Spain
Authors: Samper Javier , Sobral Brais , Pisani Bruno , Naves Acacia , Guadaño Joaquín , Gómez Jorge , Fernández Jesús
Published: October 2023

Lindane (a harmful contaminant) was produced in Sabiñánigo (Huesca, Spain) and deposited at the Sardas landfill. This site contains a large mass of pollutants, which have an extremely large contamination potential of the Ebre River. The site has undergone numerous human interventions that have modified the natural conditions. The site exhibits complex hydrogeological patterns and has been monitored systematically for a long period of time, and a large amount of geological, hydrological, and hydrogeological data are available. Here, a 2D finite element groundwater flow model along a vertical profile heading east–west along the thalweg of the former gully is presented. The main goal is modelling groundwater flow through the landfill, the Gállego River alluvial aquifer, and its interactions with the Sabiñánigo reservoir. The numerical model confirms the prevailing conceptual hydrogeological model of the site. The main results include: (1) Groundwater flows into the landfill mainly along perimeter ditches, which do not properly drain the surface and subsurface runoff (13.84 m3/d) and from the underlying marly rock (8.84 m3/d); (2) The total landfill leachate outflow towards the alluvial floodplain underneath the front slurry wall through a shallow marl layer is equal to 17 m3/d; (3) The oscillations of the Sabiñánigo reservoir water level produce a tidal effect that results in periodic changes of the hydraulic gradient between the alluvial gravels and the reservoir; (4) Groundwater flows generally from the alluvial aquifer towards the reservoir in an average E–W direction with an average Darcy velocity equal to 5 cm/d. The flow direction, however, changes to W–E when the reservoir level rises suddenly and; (5) The hydrodynamic parameters of the alluvial silts and reservoir silting sediments are crucial in determining the influence radius of the inversion of groundwater flow direction when the reservoir level rises suddenly. Model results enhance the confidence of the conceptual model, provide the basis for detailed specific models of the landfill and the alluvial aquifer, and highlight the importance of considering the tidal effect of the reservoir level oscillations. They also provide valuable information for managing the landfill and its impact on the surrounding groundwater system.
Wastewater-Based Epidemiology of SARS-CoV-2 and Other Respiratory Viruses: Bibliometric Tracking of the Last Decade and Emerging Research Directions
Authors: Waseem Hassan , Abid Rameesha , Ali Jafar , Oswald Claire J. , Gilbride Kimberley A.
Published: October 2023

The COVID-19 pandemic has prompted an overwhelming surge in research investigating different aspects of the disease and its causative agent. In this study, we aim to discern research themes and trends in the field of wastewater-based epidemiology (WBE) of SARS-CoV-2 and other respiratory viruses over the past decade. We examined 904 papers in the field authored by researchers from 87 countries. Despite the low reported incidence of COVID-19 in 2023, researchers are still interested in the application of WBE to SARS-CoV-2. Based on network visualization mapping of 189 keyword co-occurrences, method optimization, source, transmission, survival, surveillance or early-warning detection systems, and variants of concern in wastewater were found to be the topics of greatest interest among WBE researchers. A trend toward evaluations of the utility of new technologies such as digital PCR and WBE for other respiratory viruses, particularly influenza, was observed. The USA emerged as the leading country in terms of research publications, citations, and international collaborations. Additionally, Science of the Total Environment stood out as the journal with the highest number of publications and citations. The study highlighted areas for further research, including data normalization and biosensor-based data collection, and emphasized the need for international collaboration and standardized methodology for WBE in future research directions.
Spatial–Temporal Distribution and Interrelationship of Sulfur and Iron Compounds in Seabed Sediments: A Case Study in the Closed Section of Mikawa Bay, Japan
Authors: Waku Mitsuyasu , Sone Ryota , Inoue Tetsunori , Ishida Toshiro , Suzuki Teruaki
Published: October 2023

Herein, the distribution of sulfur and iron compounds (dissolved sulfide: H2S and HS−, iron sulfide: FeS, and ionized iron: Fe2+ and Fe3+) in sediments (0–15 cm depth) at four stations in Mikawa Bay, Japan, was evaluated from April 2015 to March 2016. The maximum dissolved sulfide concentrations in the upper part of the sediment porewater (0–4 cm depth) (within 1.4–8.1 mmol·L−1) varied among stations located in a waterway of a large-scale port with a significant dead zone. Moreover, the iron sulfide and ionized iron concentrations in the upper part were highest at a station where the dissolved sulfide concentration was relatively low compared with that of the other sites. Analysis of the theoretical and hypothetical accumulation of particulate oxidized iron (FOOH) at the stations located in the dead zone revealed that the estimated particulate oxidized iron accumulation was higher (2303 mmol·m−2) at a station in which the dissolved sulfide concentration was low compared with the other stations (142–384 mmol·m−2). Altogether, these findings suggest that the sulfur–iron cycling can determine the amount of dissolved sulfides that accumulate in sediments. Hence, artificially adding iron compounds to the seabed may help mitigate free sulfides accumulation and prevent extreme hypoxia.
Evolution Characteristics of Landscape Patterns and the Response of Surface Runoff in a Rapid Urbanization Area: Focus on the Chang–Zhu–Tan Metropolitan Area of China
Authors: Li Tang , Chen Cunyou , Li Qizhen , Liu Luyun , Wang Zhiyuan , Hu Xijun , Thapa Saroj
Published: October 2023

With the acceleration of urbanization, the disturbance to urban landscape patterns causes changes to urban surface runoff and increases the risk of urban waterlogging. We studied the response relationship between landscape pattern change and surface runoff in the Chang–Zhu–Tan metropolitan area for the period from 2000 to 2020, analyzing the driving factors that affected surface runoff. The influence of landscape pattern evolution on surface runoff was studied using the SCS-CN flow generation model, the moving window method, and Pearson’s analysis. The analysis showed that between 2000 and 2020, the forest area decreased, while the impermeable land area increased substantially. At the same time, the landscape spread degree (CONTAG) decreased, whereas the landscape fragmentation degree (DIVISION) increased, and the Shannon diversity index (SHDI) and landscape shape index (LSI) increased. The surface runoff in the main urban areas of Chang–Zhu–Tan increased substantially. The results showed that surface runoff is negatively correlated with SHDI, LSI, and DIVISION but displays a positive relationship to CONTAG. Soil texture and precipitation had the greatest impact on surface runoff. This study emphasizes the importance of landscape pattern evolution to surface runoff in rapidly developing metropolitan areas in terms of reducing surface runoff, alleviating urban waterlogging and preventing regional floods. Our research additionally seeks to optimize the landscape pattern of the Chang–Zhu–Tan metropolitan area.