bluuebunny/crossref_metadata_2025 huggingface dataset:
Synthesis, Characterization and Sorption Properties of Biochar, Chitosan and ZnO-Based Binary Composites towards a Cationic Dye
Authors: Roy Hridoy , Islam Md. Shahinoor , Arifin Mohammad Tanvir , Firoz Shakhawat H.
Published: November 2022

Industrial effluents contaminated with different types of organic dyes have become a major concern to environmentalists due to the carcinogenic nature of the dyes, which are harmful to human and aquatic life. In recent years, the treatment of contaminated effluents by natural resources has been proposed as the most sustainable solution for this problem. In this work, Moringa oleifera (M. oleifera) seed-derived biochar composites, e.g., Biochar-Chitosan (BC), Biochar-ZnO (BZ), and Chitosan-ZnO (CZ) were produced and characterized. The synthesized materials were then utilized to adsorb a cationic dye, methylene blue. Spectroscopic analysis of the biochar-based composites revealed that the modification of biochar by chitosan and ZnO introduced different functional and active groups in the biochar surface. Pore development in the structure of biochar nanocomposites was visible in surface morphological images. The derived biochar was fully amorphous and increased crystallinity by the ZnO modification. The obtained surface area varied from 0.90 ± 0.00 to 14.48 ± 1.13 m2 g−1 for prepared sorbents, where BZ corresponds to the highest and BC corresponds to the lowest surface area, respectively. The basic pH (9) was the most favorable condition for sorption. The sorption reached equilibrium at 90 min. Isotherm revealed the favorability of the Langmuir model over the Freundlich and Temkin models. The highest sorption capacity (~170 mg/g) was found for BC. The BC and BZ showed a 75% increase and 16% decrease in removal due to the chitosan and ZnO modification, respectively. Response surface methodology (RSM) optimization for BC showed similar results to the analytical experiments. The characterization and experimental results prefigure the chemical functionalities as the critical parameter over the surface area for the adsorption process.
Principal Component Analysis (PCA)–Geographic Information System (GIS) Modeling for Groundwater and Associated Health Risks in Abbottabad, Pakistan
Authors: Akbar Tahir Ali , Javed Azka , Ullah Siddique , Ullah Waheed , Pervez Arshid , Akbar Raza Ali , Javed Muhammad Faisal , Mohamed Abdullah , Mohamed Abdeliazim Mustafa
Published: November 2022

Drinking water quality is a major problem in Pakistan, especially in the Abbottabad region of Pakistan. The main objective of this study was to use a Principal Component Analysis (PCA) and integrated Geographic Information System (GIS)-based statistical model to estimate the spatial distribution of exceedance levels of groundwater quality parameters and related health risks for two union councils (Mirpur and Jhangi) located in Abbottabad, Pakistan. A field survey was conducted, and samples were collected from 41 sites to analyze the groundwater quality parameters. The data collection includes the data for 15 water quality parameters. The Global Positioning System (GPS) Essentials application was used to obtain the geographical coordinates of sampling locations in the study area. The GPS Essentials is an android-based GPS application commonly used for collection of geographic coordinates. After sampling, the laboratory analyses were performed to evaluate groundwater quality parameters. PCA was applied to the results, and the exceedance values were calculated by subtracting them from the World Health Organization (WHO) standard parameter values. The nine groundwater quality parameters such as Arsenic (As), Lead (Pb), Mercury (Hg), Cadmium (Cd), Iron (Fe), Dissolved Oxygen (DO), Electrical Conductivity (EC), Total Dissolved Solids (TDS), and Colony Forming Unit (CFU) exceeded the WHO threshold. The highly exceeded parameters, i.e., As, Pb, Hg, Cd, and CFU, were selected for GIS-based modeling. The Inverse Distance Weighting (IDW) technique was used to model the exceedance values. The PCA produced five Principal Components (PCs) with a cumulative variance of 76%. PC-1 might be the indicator of health risks related to CFU, Hg, and Cd. PC-2 could be the sign of natural pollution. PC-3 might be the indicator of health risks due to As. PC-4 and PC-5 might be indicators of natural processes. GIS modeling revealed that As, Pb, Cd, CFU, and Hg exceeded levels 3, 4, and 5 in both union councils. Therefore, there could be greater risk for exposure to diseases such as cholera, typhoid, dysentery, hepatitis, giardiasis, cryptosporidiosis, and guinea worm infection. The combination of laboratory analysis with GIS and statistical techniques provided new dimensions of modeling research for analyzing groundwater and health risks.
Comparison of CLDAS and Machine Learning Models for Reference Evapotranspiration Estimation under Limited Meteorological Data
Authors: Qian Long , Wu Lifeng , Liu Xiaogang , Cui Yaokui , Wang Yongwen
Published: November 2022

The accurate calculation of reference evapotranspiration (ET0) is the fundamental basis for the sustainable use of water resources and drought assessment. In this study, we evaluate the performance of the second-generation China Meteorological Administration Land Data Assimilation System (CLDAS) and two simplified machine learning models to estimate ET0 when meteorological data are insufficient in China. The results show that, when a weather station lacks global solar radiation (Rs) data, the machine learning methods obtain better results in their estimation of ET0. However, when the meteorological station lacks relative humidity (RH) and 2 m wind speed (U2) data, using RHCLD and U2CLD from the CLDAS to estimate ET0 and to replace the meteorological station data obtains better results. When all the data from the meteorological station are missing, estimating ET0 using the CLDAS data still produces relevant results. In addition, the PM–CLDAS method (a calculation method based on the Penman–Monteith formula and using the CLDAS data) exhibits a relatively stable performance under different combinations of meteorological inputs, except in the southern humid tropical zone and the Qinghai–Tibet Plateau zone.
Effect of LMWOAs on Maize Remediation of Cadmium and Plumbum Pollution in Farmland
Authors: Tao Ronghao , Hu Jingyi , Cao Chi , Zheng Jing , Zhou Xiaotian , Hu Hongxiang , Ma Youhua , Ye Wenling , Ma Zhongwen , Lu Hongjuan
Published: November 2022

Plant extraction is a thorough remediation method to remove heavy metals from soil. Chelating agents can enhance the extraction effect of heavy metals from soil by plants. In this study, low molecular weight organic acids (LMWOAs), such as citric acid (CA), tartaric acid (TA) and polyaspartate (PASP), were added to the farmland soil contaminated with Cd and Pb and combined with corn to enhance the absorption and extraction of Cadmium (Cd) and Plumbum (Pb). The effects of LMWOAs on the growth and yield of maize, Cd and Pb concentrations in each part of maize, rhizosphere soil pH, total cadmium and lead content and DTPA-Cd and Pb concentrations were studied. The enrichment, transport and extraction ability of maize were analyzed, and calcium chloride (CaCl2) was compared. The results showed that: (1) Exogenous LMWOAs increased the biomass and yield of maize compared with no material added (CK), and CA increased the yield of maize by 6.33%. (2) Exogenous LMWOAs promoted the uptake of Cd and Pb in all parts of maize, and the distribution of Cd and Pb in all organs was as follows: straws > roots > maize cobs > kernels and roots > straws > maize cobs > kernels. The Cd and Pb concentrations in maize kernels were in line with GB 13078-2017 in China, which could be used as feed maize. (3) Exogenous LMWOAs enhanced the enrichment of Cd and Pb in maize straws and roots. PASP had a good enrichment effect on Cd and Pb. CA and CaCl2 could enhance the transport capacity of Cd and Pb from maize roots to straw. (4) Compared with CK, the total amount of Cd and Pb in rhizosphere soil decreased by 6.93–26.99% and 2.74–6.79%, respectively. LMWOAs could promote the concentration of DTPA-Cd and Pb in rhizosphere soil, and PASP had the most significant increase in DTPA-Cd and Pb in rhizosphere soil. Compared with CK, the soil pH value decreased by 0.03–0.14 units. LMWOAs can enhance the removal of heavy metals from maize, and PASP has the most significant comprehensive effect.
Comprehensive Evaluation of China’s Input–Output Sector Status Based on the Entropy Weight-Social Network Analysis Method
Authors: Jin Yanling , Xu Yi , Li Rui , Zhao Changping , Yuan Zhenghui
Published: November 2022

In order to understand the source of China’s global influence, the key sectors and important connections in China’s economic and trade networks should be identified. Based on China’s 2002–2018 input–output data, this study uses the entropy weight method to determine weights, and then combines the social network analysis method in order to construct a comprehensive index system for industry status evaluation. Research results indicate that the high-risk financial industry occupies the top position among all industries. Additionally, resource-consuming industries represented by the coal mining industry and highly polluting industries still occupy an important position in China’s economy. Machinery, electronics manufacturing, and other real industries show increasing value-added products, steadily improving technology intensity, and continue to climb the industrial value chain. The conclusions of this study provide a comprehensive and detailed industrial understanding of the formulation of comprehensive and systematic national economic strategies as well as targeted industrial policies to achieve sustainable development.
Energy Storage Capacity Planning Method for Improving Offshore Wind Power Consumption
Authors: Yu Hao , Yang Xiaojuan , Chen Honglin , Lou Suhua , Lin Yong
Published: November 2022

This paper proposes a method of energy storage capacity planning for improving offshore wind power consumption. Firstly, an optimization model of offshore wind power storage capacity planning is established, which takes into account the annual load development demand, the uncertainty of offshore wind power, various types of power sources and line structure. The model aims at the lowest cost of investment, operation and maintenance of the system, and takes lower than a certain abandoned wind level as the strict constraint to obtain two parameters of power capacity and energy capacity of energy storage on the source side. Secondly, taking a coastal power grid as a typical case, the energy storage capacity planning method is verified. Finally, the key factors affecting offshore wind power consumption are summarized, and the sensitivity analysis is carried out from the point of view of the transmission protocol of the transmission lines outside the province and the capacity allocation of the tie lines in the province. This study will be helpful for the planning and operation of the high-proportion of offshore wind energy power systems.
Adaptive Deep Q-Network Algorithm with Exponential Reward Mechanism for Traffic Control in Urban Intersection Networks
Authors: Fuad Muhammad Riza Tanwirul , Fernandez Eric Okto , Mukhlish Faqihza , Putri Adiyana , Sutarto Herman Yoseph , Hidayat Yosi Agustina , Joelianto Endra
Published: November 2022

The demand for transportation has increased significantly in recent decades in line with the increasing demand for passenger and freight mobility, especially in urban areas. One of the most negative impacts is the increasing level of traffic congestion. A possible short-term solution to solve this problem is to utilize a traffic control system. However, most traffic control systems still use classical control algorithms with the green phase sequence determined, based on a specific strategy. Studies have proven that this approach does not provide the expected congestion solution. In this paper, an adaptive traffic controller was developed that uses a reinforcement learning algorithm called deep Q-network (DQN). Since the DQN performance is determined by reward selection, an exponential reward function, based on the macroscopic fundamental diagram (MFD) of the distribution of vehicle density at intersections was considered. The action taken by the DQN is determining traffic phases, based on various rewards, ranging from pressure to adaptive loading of pressure and queue length. The reinforcement learning algorithm was then applied to the SUMO traffic simulation software to assess the effectiveness of the proposed strategy. The DQN-based control algorithm with the adaptive reward mechanism achieved the best performance with a vehicle throughput of 56,384 vehicles, followed by the classical and conventional control methods, such as Webster (50,366 vehicles), max-pressure (50,541 vehicles) and uniform (46,241 vehicles) traffic control. The significant increase in vehicle throughput achieved by the adaptive DQN-based control algorithm with an exponential reward mechanism means that the proposed traffic control could increase the area productivity, implying that the intersections could accommodate more vehicles so that the possibility of congestion was reduced. The algorithm performed remarkably in preventing congestion in a traffic network model of Central Jakarta as one of the world’s most congested cities. This result indicates that traffic control design using MFD as a performance measure can be a successful future direction in the development of reinforcement learning for traffic control systems.
A Retrospective on the Innovative Sustainable Valorization of Cereal Bran in the Context of Circular Bioeconomy Innovations
Authors: Tufail Tabussam , Ain Huma Bader Ul , Saeed Farhan , Nasir Makia , Basharat Shahnai , Mahwish  , Rusu Alexandru Vasile , Hussain Muzzamal , Rocha João Miguel , Trif Monica , Aadil Rana Muhammad
Published: November 2022

Handling industrial agricultural wastes is a requirement for industrial waste management in the context of circular bioeconomy innovations. The recovery and re-use of agricultural wastes and their by-products have become an important topic of research and development to investigate their functional and nutraceutical properties. The bioeconomy provides an opportunity to create innovative bio-based products and processes, thereby opening up new markets. Agricultural waste contains a high concentration of protein, fat, carbohydrates, fiber, and other functional compounds such as antioxidants, which can be used to add value to a variety of food products. Due to its higher nutritional profile, cereal bran, as an agricultural waste and by-product, has a variety of functional and nutraceutical properties. Despite the fact that it is rich in bioactive compounds with health benefits, cereal bran is still underutilized in the food system. It can be used either directly for the processing of various foods or the extraction of various bioactive components present therein. Furthermore, the extracts from cereal bran have been used to obtain antioxidants, antibiotics, vitamins, and enzymes as functional components to be employed in agri-food and animal feed, pharmaceutical, and cosmetics industries. Therefore, this review aims to promote cereal bran waste and by-products, highlighting how to use them as functional ingredients with health-promoting properties and desirable technological aspects. Currently, there are few data on the nutritional exploration of these by-products as health-promoting agri-food products. Cereal bran is a nutritious natural agricultural by-product, but its potential application in the food industry is still limited due to a lack of literature focused on its quality attributes, which may become useful for informal explanation and evaluation during food product formulation. With the growing demand for fiber-rich foods, cereal bran valorization can generate revenue for milling industries.
Three-Dimensional Analysis of Air-Admission Orifices in Pipelines during Hydraulic Drainage Events
Authors: Paternina-Verona Duban A. , Coronado-Hernández Oscar E. , Espinoza-Román Hector G. , Besharat Mohsen , Fuertes-Miquel Vicente S. , Ramos Helena M.
Published: November 2022

Air valves operate as protection devices in pipelines during drainage processes in order to mitigate vacuum pressures and control the transient flows. Currently, different authors have proposed one-dimensional models to predict the behaviour of orifices during filling and draining events, which offer good numerical results. However, the three-dimensional dynamic behaviour of air-admission orifices during drainage processes has not been studied in depth in the literature. In this research, the effects of air inflow on an orifice installed in a single pipe during drainage events are analysed using a three-dimensional computational fluid dynamics model by testing orifices with diameters of 1.5 and 3.0 mm. This model was validated with different experimental measurements associated to the vacuum pressure, obtaining good fits. The three-dimensional model predicts additional information associated to the aerodynamic effects that occur during the air-admission processes, which is studied. Subsonic flows are observed in different orifices with Mach numbers between 0.18 and 0.30. In addition, it is shown that the larger-diameter orifice ensures a more effective airflow control compared to the smaller-diameter orifice.
Factors Influencing Residential Location Choice towards Mixed Land-Use Development: An Empirical Evidence from Pakistan
Authors: Shaikh Fahad Ahmed , Talpur Mir Aftab Hussain , Chandio Imtiaz Ahmed , Kalwar Saima
Published: November 2022

This study is aimed to determine the MLU development factors by executing a Delphi Method (DM). The MLU factors can contribute to the land-use development process in the thickly populated urban centers of developing countries. This is the first study of its type conducted to clarify MLU development factors in urbanized settlements of Sindh province, Pakistan. Karachi and Hyderabad are thickly populated cities in Pakistan where mixed land-use (MLU) development prevails over the years. The DM was attempted in two rounds focusing on the opinion of urban development specialists and academic experts. The experts initially provided a set of forty-two factors identified from the literature. These factors were arranged in a Likert-based questionnaire and determined through the coefficient variation. The prominent factors were identified as household savings, travel costs and low rent, nearby household items and shared utility services, economic vitality, variety in purchasing grocery and shopping items, demographic change and social poverty, accessibility to nearby public services, reduction in commuting time and easy access to restaurants. This proposed research recommends policy implications focusing on identified key parameters of MLU development, such as low carbon exposure, livable environment, and planned municipal system.
Emulating Epileptic Seizures on Coupled Chua’s Circuit Networks
Authors: Karamani Rafailia-Eleni , Tsakalos Karolos-Alexandros , Sirakoulis Georgios Ch.
Published: November 2022

Irregular brain activity is of interest to researchers and scientists who are trying to understand, model, compare, and provide novel solutions to existing and challenging issues. Neurological disorders such as epilepsy, Alzheimer’s disease, Parkinson’s disease, and schizophrenia have been extensively studied. Among those diseases, epileptic seizures are the most commonly occurring ones. In this work, as a simplification of the complete biological operations of the brain, it was viewed as a system that consists of coupled oscillators. This allowed us to examine epilepsy as a pathological manifestation of the system. Emerging behaviors that arise from the spatiotemporal interactions of simple oscillators, namely, Chua’s Circuit, allowed us to observe how irregularities and changes to the coupling parameters of a neuromorphic network affect their synchronization and result in the emergence of epileptic activity. To achieve this, the characteristics of novel nanoelectronic devices, namely, memristors, have been exploited through their integration into two-dimensional crossbar arrays that offer the advantages of reprogrammability, low area, and low power consumption.
An Efficient Method to Assess Resilience and Robustness Properties of a Class of Cyber-Physical Production Systems
Authors: Hsieh Fu-Shiung
Published: November 2022

Widely available real-time data from the sensors of IoT infrastructure enables and increases the adoption and use of cyber-physical production systems (CPPS) to provide enterprise-wide status information to promptly respond to business opportunities through real-time monitoring, supervision and control of resources and activities in production systems. In CPPS, the failures of resources are uncertainties that are inevitable and unexpected. The failures of resources usually lead to chaos on the shop floor, delayed production activities and overdue orders. This calls for the development of an effective method to deal with failures in CPPS. An effective method to assess the impacts of failures on performance and create an alternative plan to mitigate the impacts is important. Robustness, which refers to the ability to tolerate perturbations, and resilience, which refers to the capability to recover from perturbations, are two concepts to evaluate the influence of resource failures on CPPS. In this study, we developed a method to evaluate the influence of resource failures on CPPS based on the concepts of robustness and resilience. We modeled CPPS by a class of discrete timed Petri nets. A model of CPPS consists of asymmetrically decomposed models of tasks. The dynamics of tasks can be represented by spatial-temporal networks (STN) with a similar but asymmetrical structure. A joint spatial-temporal networks (JSTN) model constructed based on the fusion of the asymmetrical STNs is used to develop an efficient algorithm to optimize performance. We characterized robustness and resilience as properties of CPPS with respect to the failures of resources. We analyzed the complexity of the proposed method and conducted experiments to illustrate the scalability and efficiency of the proposed method.
Overlapping Community Hiding Method Based on Multi-Level Neighborhood Information
Authors: Yang Guoliang , Wang Yanwei , Chang Zhengchao , Liu Dong
Published: November 2022

The overlapping community detection algorithm divides social networks into multiple overlapping parts, and members can belong to multiple communities at the same time. Although the overlapping community detection algorithm can help people understand network topology, it exposes personal privacy. The BIH algorithm is proposed to solve the problem of personal privacy leaks in overlapping areas. However, some specific members in overlapping areas do not want to be discovered to belong to some specific community. To solve this problem, an overlapping community hiding algorithm based on multi level neighborhood information (MLNI) is proposed. The MLNI algorithm defines node probability of community based on multi-layer neighborhood information. By adjusting the probability of the target node belonging to each community, the difference between the probability that the target node belongs to outside and inside the target community is maximized. This process can be regarded as an optimization problem. In addition, the MLNI algorithm uses the genetic algorithm to find the optimal solution, and finally achieves the purpose of moving the target node in the overlapping area out of a specific community. The effectiveness of the MLNI algorithm is demonstrated through extensive experiments and baseline algorithms. The MLNI algorithm effectively realizes the protection of personal privacy in social networks.
Adversarial Malicious Encrypted Traffic Detection Based on Refined Session Analysis
Authors: Li Minghui , Wu Zhendong , Chen Keming , Wang Wenhai
Published: November 2022

The detection of malicious encrypted traffic is an important part of modern network security research. The producers of the current malware do not pay attention to the fact that malicious encrypted traffic can also be detected; they do not construct further adversarial malicious encrypted traffic to deceive existing malicious encrypted traffic detection methods. However, with the increasing confrontation between attack and defense, adversarial malicious encrypted traffic samples will appear gradually, which will make the existing malicious encrypted traffic detection methods obsolete. In this paper, an adversarial malicious encrypted traffic detection method based on refined session analysis (ADRSA) is proposed. The key ideas of this method are: (1) interpretability analysis is used to extract malicious traffic features that are not easily affected by encryption, (2) restoration technology is used to further improve traffic separability, and (3) a deep neural network is used to identify adversarial malicious encrypted traffic. In experimental tests, the ADRSA method could accurately detect malicious encrypted traffic, particularly adversarial malicious encrypted traffic, and the detection rate is more than 95%. However, the detection rate of other malicious encrypted traffic detection methods is almost zero when facing adversarial malicious encrypted traffic. The detection performance of ADRSA exceeds that of the most popular detection methods.
Polytopic Robust Stability for a Dual-Capacitor Boost Converter in Symmetric and Non-Symmetric Configurations
Authors: Rodríguez Licea Martín Antonio
Published: November 2022

The step-up power electronic converter, which is easily implemented with two symmetric parallel-boost stages, has recently been proposed in the literature, showing considerable voltage gains with no excessive duty cycle, thus minimizing heat and other adverse effects. Its other advantages are floating-output voltage and increased power density because of the diminution of the capacitors’ voltage rating. In this paper, the Lyapunov-based robust stability of a converter operating in both closed- and open-loop is proved, showing its versatility even during the variation of parameters, which nullifies the symmetry of the converter. Simulation and experimental data allow the corroboration of the analysis.
Accelerometery-Based Load Symmetry in Track Running Kinematics concerning Body Location, Track Segment, and Distance in Amateur Runners
Authors: Antúnez Antonio , Rojas-Valverde Daniel , Flores-Leonés Ana , Gómez-Carmona Carlos D. , Ibáñez Sergio J.
Published: November 2022

Background: Previous studies indicate that running at maximum speed on short or curved sections is slower than running on straight sections. This study aimed to analyse the external load symmetry in track running kinematics concerning body location (left vs. right, caudal vs. cephalic), track segment (straight vs. curved) and distance (150 m vs. 300 m). Methods: Twenty experienced athletes ran 150 m and 300 m on an official athletic track and were monitored by Magnetic, Angular Rate and Gravity sensors attached to six different body segments (thorax, lumbar, knees and malleolus). Player Load was quantified as a valid, effective and representative Accelerometery-based variable. Results: (1) Principal component analysis explained 62–93% of the total variance and clustered body locations relevance in curved (knees and malleolus) vs. straight (lumbar, knees, malleolus) running segments; (2) Player Load statistical differences by track segment (curved vs. straight) were found in all body locations; and (3) there were no differences in bilateral symmetries by distance or running segment. Conclusions: Track segment and body location directly impacted accelerometery-based load. Acceleration in straight segments was lower compared to that in curved segments in all the body locations (lumbar, knee and ankle), except in the thorax. Strength and conditioning programs should consider the singularity of curved sprinting (effects of centripetal–centrifugal force) for performance enhancement and injury prevention and focus on the knees and malleolus, as shown in the principal component analysis results.
Association of Core Muscle Endurance with Weekly Workout Time, Speed, and the Symmetry of Frontal Core Motion during Indoor Walking and Cycling
Authors: Park Ju-Hyun , Kim Ae-Ryeong , Kim Si-Hyun , Kim Kwang Bok , Park Kyue-Nam
Published: November 2022

This study investigated the factors that influence core muscle endurance, i.e., the symmetry of frontal core motion during indoor walking and cycling, the symmetry of lateral core muscle endurance, the symmetry of the hip abductor strength, the weekly workout time and fast walking and cycling speeds, while controlling for gender. Seventy-nine healthy young adults participated in this study. In a regression analysis, the core muscle endurance time was the dependent variable. The independent variables were the symmetry of frontal core motion (measured using a wireless earbud sensor during walking and cycling), the symmetry of side plank time and of hip abductor strength, the weekly workout time and fast walking and cycling speeds. In the multiple regression analysis, weekly workout time, fast walking speed, symmetry of frontal core motion during fast cycling and symmetry of lateral side plank time predicted core muscle endurance (adjusted R2 = 0.42). Thus, clinicians and fitness personnel should consider the association of core muscle endurance with the symmetry of frontal core motion during cycling and the symmetry of side plank holding time, as well as with the weekly workout time and a fast walking speed, when designing core muscle exercise programmes.
Finite Element Analysis of an Implant-Supported FDP with Different Connector Heights
Authors: Alberto Laura H. J. , Kalluri Lohitha , Esquivel-Upshaw Josephine F. , Duan Yuanyuan
Published: November 2022

All-ceramic fixed dental prostheses (FDPs) tend to fracture in the connector areas, due to the concentration of tensile stresses. This study aimed to evaluate the role of connector height on the stress distribution of a posterior three-unit implant-supported all-ceramic FDP using finite element analysis (FEA). Two titanium dental implants, their abutments, screws, and a three-unit all-ceramic FDP were scanned using a micro-CT scanner. Three 3D models with altered distal connector heights (3, 4, and 5 mm) were generated and analyzed on ABAQUS FEA software. The maximum principal stress values in MPa observed for each model with different connector heights and their respective locations (MA = mesial abutment; DA = distal abutment; F = framework; V = veneer) were: 3 mm—219 (MA), 88 (DA), 11 (F), 16 (V); 4 mm—194 (MA), 82 (DA), 8 (F), 18 (V); 5 mm—194 (MA), 80 (DA), 8 (F), and 18 (V). All the assembled models demonstrated the peak stresses at the neck area on the mesial abutments. The connector height had a significant influence on the stress distribution of the prosthesis. The models with higher distal connectors (4 and 5 mm) had a lower and more uniform distribution of maximum principal stresses (except for the veneer layer) when compared with the model with the smallest distal connector.
Inhibitory Effect of α1 Receptor Antagonists on Paclitaxel-Induced Peripheral Neuropathy in a Rodent Model and Clinical Database
Authors: Mori Kohei , Kawashiri Takehiro , Mine Keisuke , Inoue Mizuki , Kudamatsu Hibiki , Uchida Mayako , Egashira Nobuaki , Kobayashi Daisuke , Shimazoe Takao
Published: November 2022

The anticancer drug, paclitaxel, is widely used for ovarian, breast, non-small cell lung, and gastric cancers; however, it induces peripheral neuropathy as a side effect. There is insufficient evidence-based prophylaxis, and new prophylaxis and treatment methods are required. We examined the effect of α1-receptor antagonists on paclitaxel-induced peripheral neuropathy using Sprague-Dawley rats and a large adverse event database. The repeated administration of doxazosin or tamsulosin significantly reduced the response threshold to paclitaxel administration in animal models. In the sciatic nerve tissue, axonal degeneration and myelopathy were significantly suppressed. Furthermore, an analysis of the Food and Drug Administration Adverse Event Reporting System (FAERS) database suggested that the group using α1 inhibitors showed a lower reporting rate for paclitaxel-related peripheral neuropathy than the group that did not use these inhibitors (odds ratio (95% confidence interval): tamsulosin 0.21 (0.08–0.56), p < 0.01, doxazosin 0.41 (0.10–1.65), p = 0.195; any α1 receptor antagonist 0.54 (0.38–0.76), p < 0.01). Thus, doxazosin and tamsulosin may inhibit the development of paclitaxel-induced peripheral neuropathy by suppressing neurodegeneration, particularly axonal degeneration and myelopathy.
Petroleum in Pesticides: A Need to Change Regulatory Toxicology
Authors: Jungers Gérald , Portet-Koltalo Florence , Cosme Julie , Seralini Gilles-Eric
Published: November 2022

Toxicological investigations of pesticides largely focus on the declared active ingredient, which constitutes only between a few percent to around 50% of the total formulation. The complete formulations are unknown. For each declared active ingredient, there are dozens or hundreds of formulations. We demonstrate that petroleum has always been and is still always in pesticides. Gas chromatography and mass spectrometry (GC-MS) were applied for 24 pesticides. The measured compounds were the 16-priority polycyclic aromatic hydrocarbons (PAHs). The ratio of the PAHs to the threshold of toxicity was from 2.16 to 8288 times. The levels and distribution of PAHs per pesticide were different. Petroleum residues appear to be a waste product. The declared active component is taken alone for toxicity calculations, such as the acceptable daily intake (ADI). The PAHs with 2–3 cycles are more represented in pesticides than those with 4–6 cycles, which underlines that the petroleum residues appear to come mainly from crude unburned material. The ADI should be divided by 1000 if it is considered that petroleum residues amplify the toxicity by 1000. The admixture of PAHs in pesticides can be highly carcinogenic or toxic in the long term, even more than the declared active ingredient itself.
BmooMPα-I, a Metalloproteinase Isolated from Bothrops moojeni Venom, Reduces Blood Pressure, Reverses Left Ventricular Remodeling and Improves Cardiac Electrical Conduction in Rats with Renovascular Hypertension
Authors: Estrada Jorge Eduardo Chang , Rodrigues Keuri Eleutério , Maciel Anderson , Bannwart Cahy Manoel , Dias Wictória Farias , Hamoy Moisés , Zingali Russolina Benedeta , Soares Andreimar Martins , Ribeiro Carolina Heitmann Mares Azevedo , Gerlach Raquel Fernanda , Monteiro Marta Chagas , Prado Alejandro Ferraz
Published: November 2022

BmooMPα-I has kininogenase activity, cleaving kininogen releasing bradykinin and can hydrolyze angiotensin I at post-proline and aspartic acid positions, generating an inactive peptide. We evaluated the antihypertensive activity of BmooMPα-I in a model of two-kidney, one-clip (2K1C). Wistar rats were divided into groups: Sham, who underwent sham surgery, and 2K1C, who suffered stenosis of the right renal artery. In the second week of hypertension, we started treatment (Vehicle, BmooMPα-I and Losartan) for two weeks. We performed an electrocardiogram and blood and heart collection in the fourth week of hypertension. The 2K1C BmooMPα-I showed a reduction in blood pressure (systolic pressure: 131 ± 2 mmHg; diastolic pressure: 84 ± 2 mmHg versus 174 ± 3 mmHg; 97 ± 4 mmHg, 2K1C Vehicle, p < 0.05), improvement in electrocardiographic parameters (Heart Rate: 297 ± 4 bpm; QRS: 42 ± 0.1 ms; QT: 92 ± 1 ms versus 332 ± 6 bpm; 48 ± 0.2 ms; 122 ± 1 ms, 2K1C Vehicle, p < 0.05), without changing the hematological profile (platelets: 758 ± 67; leukocytes: 3980 ± 326 versus 758 ± 75; 4400 ± 800, 2K1C Vehicle, p > 0.05), with reversal of hypertrophy (left ventricular area: 12.1 ± 0.3; left ventricle wall thickness: 2.5 ± 0.2; septum wall thickness: 2.3 ± 0.06 versus 10.5 ± 0.3; 2.7 ± 0.2; 2.5 ± 0.04, 2K1C Vehicle, p < 0.05) and fibrosis (3.9 ± 0.2 versus 7.4 ± 0.7, 2K1C Vehicle, p < 0.05). We concluded that BmooMPα-I improved blood pressure levels and cardiac remodeling, having a cardioprotective effect.
Antiviral Potential of Natural Resources against Influenza Virus Infections
Authors: Eichberg Johanna , Maiworm Elena , Oberpaul Markus , Czudai-Matwich Volker , Lüddecke Tim , Vilcinskas Andreas , Hardes Kornelia
Published: November 2022

Influenza is a severe contagious disease caused by influenza A and B viruses. The WHO estimates that annual outbreaks lead to 3–5 million severe infections of which approximately 10% lead to the death of the patient. While vaccination is the cornerstone of prevention, antiviral drugs represent the most important treatment option of acute infections. Only two classes of drugs are currently approved for the treatment of influenza in numerous countries: M2 channel blockers and neuraminidase inhibitors. In some countries, additional compounds such as the recently developed cap-dependent endonuclease inhibitor baloxavir marboxil or the polymerase inhibitor favipiravir are available. However, many of these compounds suffer from poor efficacy, if not applied early after infection. Furthermore, many influenza strains have developed resistances and lost susceptibility to these compounds. As a result, there is an urgent need to develop new anti-influenza drugs against a broad spectrum of subtypes. Natural products have made an important contribution to the development of new lead structures, particularly in the field of infectious diseases. Therefore, this article aims to review the research on the identification of novel lead structures isolated from natural resources suitable to treat influenza infections.
Serological Evidence of Exposure to Saint Louis Encephalitis and West Nile Viruses in Horses of Rio de Janeiro, Brazil
Authors: Chalhoub Flávia Löwen Levy , Horta Marco Aurélio Pereira , Alcantara Luiz Carlos Junior , Morales Alejandra , dos Santos Lilha Maria Barbosa , Guerra-Campos Vinícius , Rodrigues Cintia D. S. , Santos Carolina C. , Mares-Guia Maria Angélica M. , Pauvolid-Corrêa Alex , de Filippis Ana Maria Bispo
Published: November 2022

Infections with arboviruses are reported worldwide. Saint Louis encephalitis (SLEV) and West Nile viruses (WNV) are closely related flaviviruses affecting humans and animals. SLEV has been sporadically detected in humans, and corresponding antibodies have been frequently detected in horses throughout Brazil. WNV was first reported in western Brazil over a decade ago, has been associated with neurological disorders in humans and equines and its prevalence is increasing nationwide. Herein, we investigated by molecular and serological methods the presence or evidence of SLEV and WNV in equines from Rio de Janeiro. A total of 435 serum samples were collected from healthy horses and tested for specific neutralizing antibodies by plaque reduction neutralization test (PRNT90). Additionally, serum and central nervous system samples from 72 horses, including horses with neurological disorders resulting in a fatal outcome or horses which had contact with them, were tested by real-time reverse transcription–polymerase chain reaction (RT-qPCR) for both viruses. Adopting the criterion of four-fold antibody titer difference, 89 (20.4%) horses presented neutralizing antibodies for SLEV and five (1.1%) for WNV. No evidence of SLEV and WNV infection was detected by RT-qPCR and, thus, such infection could not be confirmed in the additional samples. Our findings indicate that horses from Rio de Janeiro were exposed to both SLEV and WNV, contributing to the current knowledge on the distribution of these viruses flaviviruses in Brazil.
Occurrence and Molecular Variability of the Main Kiwifruit Viruses in the Sichuan Province of China
Authors: Shang Jing , Jia Qi , Zhang Lei , Zhang Siqi , Du Junbo , Wang Wenming , Shui Jing
Published: November 2022

Viruses cause important yield losses in kiwifruit. Here, we studied the occurrence and population structure of the major kiwifruit viruses in the Sichuan province of China. RT-PCR results showed the presence of Actinidia virus A (AcVA), Actinidia virus B (AcVB), Actinidia chlorotic ringspot-associated virus (AcCRaV), and the cucumber mosaic virus (CMV). AcCRaV was widely distributed, followed by CMV. These two viruses were often detected in co-infection with AcVA and AcVB. The virus detection rate was positively correlated with vine age. Four phylogenetic groups of AcVA and AcVB were identified, with AcVA isolates clustering mainly in subgroup I, and AcVB isolates clustering mainly in subgroups II, III, and IV. All CMV isolates clustered in subgroup II, and AcCRaV isolates clustered in subgroup IA. The genome of AcVA and AcCRaV was under negative selection pressure, while the genome of AcVB and CMV was under positive selection pressure. All the viruses, except AcVB, were in a state of expansion. The full-length genome of the most widely distributed AcCRaV isolate in kiwifruits in the Sichuan province was characterized by sequencing. Unique eight-nucleotide (TTTTTGAT) repeats were found in the 5′-terminal non-coding region of the AcCRaV RNA3 in a possible association with reduced disease symptoms. This is the first study of kiwifruit viruses in Sichuan.
In Silico Genome Analysis Reveals the Evolution and Potential Impact of SARS-CoV-2 Omicron Structural Changes on Host Immune Evasion and Antiviral Therapeutics
Authors: Chauhan Dhruv , Chakravarty Nikhil , Jeyachandran Arjit Vijey , Jayakarunakaran Akshaya , Sinha Sanjeev , Mishra Rakesh , Arumugaswami Vaithilingaraja , Ramaiah Arunachalam
Published: November 2022

New variants of SARS-CoV-2 continue to evolve. The novel SARS-CoV-2 variant of concern (VOC) B.1.1.529 (Omicron) was particularly menacing due to the presence of numerous consequential mutations. In this study, we reviewed about 12 million SARS-CoV-2 genomic and associated metadata using extensive bioinformatic approaches to understand how evolutionary and mutational changes affect Omicron variant properties. Subsampled global data based analysis of molecular clock in the phylogenetic tree showed 29.56 substitutions per year as the evolutionary rate of five VOCs. We observed extensive mutational changes in the spike structural protein of the Omicron variant. A total of 20% of 7230 amino acid and structural changes exclusive to Omicron’s spike protein were detected in the receptor binding domain (RBD), suggesting differential selection pressures exerted during evolution. Analyzing key drug targets revealed mutation-derived differential binding affinities between Delta and Omicron variants. Nine single-RBD substitutions were detected within the binding site of approved therapeutic monoclonal antibodies. T-cell epitope prediction revealed eight immunologically important functional hotspots in three conserved non-structural proteins. A universal vaccine based on these regions may likely protect against all these SARS-CoV-2 variants. We observed key structural changes in the spike protein, which decreased binding affinities, indicating that these changes may help the virus escape host cellular immunity. These findings emphasize the need for continuous genomic surveillance of SARS-CoV-2 to better understand how novel mutations may impact viral spread and disease outcome.
Immunogenicity of an mRNA-Based COVID-19 Vaccine among Adolescents with Obesity or Liver Transplants
Authors: Tubjaroen Chomchanat , Prachuapthunyachart Sittichoke , Potjalongsilp Nattakoon , Sodsai Pimpayao , Hirankarn Nattiya , Jaru-Ampornpan Peera , Chongsrisawat Voranush
Published: November 2022

There are limited data regarding the immunogenicity of mRNA-based SARS-CoV-2 vaccine BNT162b2 among immunosuppressed or obese adolescents. We evaluated the humoral immune response in adolescents with obesity and adolescent liver transplant recipients (LTRs) after receiving two BNT162b2 doses. Sixty-eight participants (44 males; mean age 14.9 ± 1.7 years), comprising 12 LTRs, 24 obese, and 32 healthy adolescents, were enrolled. Immunogenicity was evaluated by anti-SARS-CoV-2 spike protein immunoassay and surrogate viral neutralization tests (sVNT) against the Delta and Omicron (BA.1) variants. At 27.1 ± 3.2 days after the second dose, the antibody levels were 1476.6 ± 1185.4, 2999.4 ± 1725.9, and 4960.5 ± 2644.1 IU/mL in the LTRs, obese adolescents, and controls, respectively (p < 0.001). Among obese individuals, liver stiffness <5.5 kPa was associated with higher antibody levels. The %inhibition of sVNT was significantly lower for the Omicron than that for the Delta variant. Injection site pain was the most common local adverse event. Nine participants (three obese and six controls) developed COVID-19 at 49 ± 11 days after the second vaccination; four were treated with favipiravir. All infections were mild, and the patients recovered without any consequences. Our study supports the need for the booster regimen in groups with an inferior immunogenic response, including LTRs and obese individuals.
Using the Women Empowerment in Livestock Index (WELI) to Examine Linkages between Women Smallholder Livestock Farmers’ Empowerment and Access to Livestock Vaccines in Machakos County of Kenya: Insights and Critiques
Authors: Kaluwa Catherine , Oduma Jemimah , Abdirahman Faduma Abdullahi , Kitoga Byalungwa Kyotos , Opondoh Angela A. , Muchibi John , Bagnol Brigitte , Rosenbaum Marieke , Onchaga Sylvia , Stanley Meghan , Amuguni Janetrix Hellen
Published: November 2022

Livestock diseases are a major barrier to productivity for both male and female livestock keepers in Africa. In Kenya, two of the most devastating livestock diseases are Newcastle Disease (ND) in poultry and Contagious Caprine Pleuropneumonia (CCPP) in goats. Female livestock keepers tend to own more small ruminants (goats, sheep, etc.) and poultry and their livelihoods are adversely affected if their herds are not vaccinated against these diseases. Livestock farming has gender specific challenges and opportunities, with implications for the empowerment of women smallholder farmers, their household well-being, food security, and livelihoods. There is a need to estimate the level to which women benefit personally, socially, and economically from keeping livestock, yet there are very few studies that can measure if livestock production does in fact empower women smallholder livestock farmers. This study was done to examine linkages between women’s empowerment and access and control over livestock products and vaccines. The Women Empowerment in Livestock Index (WELI) tool, which was customized to include questions on livestock vaccine access, was used to capture baseline data on empowerment scores for women in Machakos county, Kenya, prior to implementation of animal health and vaccine test models. In total, 400 participants were surveyed in two wards of Machakos County, Kola and Kalama, which were purposively selected. Women’s empowerment was mapped to three domains (3DE): intrinsic agency (power within), instrumental agency (power to), and collective agency (power with) measured against adequacy in 13 indicators. Our results indicate that the household structure (female headed or dual headed household), age of respondents and number of members in a household influence the adequacy score. Work balance was the most significant negative contributor to women’s disempowerment. Women contributed the most to livestock productive activities and attained adequacy in this area compared to men, directly impacting the WELI score. Women smallholder livestock farmers report low CCPP and ND vaccination rates, minimal knowledge on livestock diseases, a lack of access to cold chain storage and rarely visited veterinarians. The WELI score was 0.81 indicating a high level of empowerment for women in this community compared to men leading us to conclude that the overall WELI score was not an accurate indicator of women‘s empowerment in Machakos County. However, the decomposability of the index allows us to disaggregate the drivers of change and to examine how individual indicators contribute to disempowerment.