bluuebunny/crossref_metadata_2025 huggingface dataset:
Multispectral Portable Fibre-Optic Reflectometer for the Classification of the Origin of Chicken Eggshells in the Case of Mycoplasma synoviae Infections
Authors: Pakuła Anna , Żołnowski Wojciech , Paśko Sławomir , Kursa Olimpia , Marć Paweł , Jaroszewicz Leszek R.
Published: November 2022

The proper classification of the origins of food products is a crucial issue all over the world nowadays. In this paper, the authors present a device—a multispectral portable fibre-optic reflectometer and signal processing patch—together with a machine-learning algorithm for the classification of the origins of chicken eggshells in the case of Mycoplasma synoviae infection. The sensor device was developed based on previous studies with a continuous spectrum in transmittance and selected spectral lines in reflectance. In the described case, the sensor is based on the integration of reflected spectral data from short spectral bands from the VIS and NIR region, which are produced by single-colour LEDs and introduced to the sample via a fibre bundle. The measurement is carried out in a sequence, and the reflected signal is pre-processed to be put in the machine learning algorithm. The support vector machine algorithm is used together with three different types of data normalization. The obtained results of the F-score factor for classification of the origins of samples show that the percentages of eggs coming from Mycoplasma synoviae infected hens are up to 87% for white and 96% for brown eggshells.
Range Spectral Filtering in SAR Interferometry: Methods and Limitations
Authors: Mestre-Quereda Alejandro , Lopez-Sanchez Juan M. , Mallorqui Jordi J.
Published: November 2022

A geometrical decorrelation constitutes one of the sources of noise present in Synthetic Aperture Radar (SAR) interferograms. It comes from the different incidence angles of the two images used to form the interferograms, which cause a spectral (frequency) shift between them. A geometrical decorrelation must be compensated by a specific filtering technique known as range filtering, the goal of which is to estimate this spectral displacement and retain only the common parts of the images’ spectra, reducing the noise and improving the quality of the interferograms. Multiple range filters have been proposed in the literature. The most widely used methods are an adaptive filter approach, which estimates the spectral shift directly from the data; a method based on orbital information, which assumes a constant-slope (or flat) terrain; and slope-adaptive algorithms, which consider both orbital information and auxiliary topographic data. Their advantages and limitations are analyzed in this manuscript and, additionally, a new, more refined approach is proposed. Its goal is to enhance the filtering process by automatically adapting the filter to all types of surface variations using a multi-scale strategy. A pair of RADARSAT-2 images that mapped the mountainous area around the Etna volcano (Italy) are used for the study. The results show that filtering accuracy is improved with the new method including the steepest areas and vegetation-covered regions in which the performance of the original methods is limited.
A Low-Latency Optimization of a Rust-Based Secure Operating System for Embedded Devices
Authors: Culic Ioana , Vochescu Alexandru , Radovici Alexandru
Published: November 2022

Critical systems such as drone control or power grid control applications rely on embedded devices capable of a real-time response. While much research and advancements have been made to implement low-latency and real-time characteristics, the security aspect has been left aside. All current real-time operating systems available for industrial embedded devices are implemented in the C programming language, which makes them prone to memory safety issues. As a response to this, Tock, an innovative secure operating system for embedded devices written completely in Rust, has recently appeared. The only downside of Tock is that it lacks the low-latency real-time component. Therefore, the purpose of this research is to leverage the extended Berkeley Packet Filter technology used for efficient network traffic processing and to add the low-latency capability to Tock. The result is a secure low-latency operating system for embedded devices and microcontrollers capable of handling interrupts at latencies as low as 60 µs.
Unveiling the Use of Wide Horizontal Rim Vessels (Bronze Age Northwest Iberian Peninsula)
Authors: Oliveira César , Vilaça Raquel , Pereira André Lopes , Vitale Anna Lígia
Published: November 2022

This paper addresses a “wide horizontal rim vessel” belonging to the collection of Fundação Sousa d’Oliveira (Azores). Although its provenance and the circumstances of its discovery are currently unknown, the authors contend that this vessel should be attributed to the Iberian Northwest and, more specifically, to the Portuguese territory, in line with the highly homogenous distribution of this type of pottery. A morphological and stylistic study has been carried out establishing its singularity with regards to the decorative composition of the rim, which is without parallel amongst dozens of vessels of the same “family”. During the study of this piece, it has been possible to observe traces of soot and organic residues deposited both on its interior and exterior surfaces, which is recurrent in these vessels. The nature of these substances has never been determined in previous studies. In this article, we present and discuss the results obtained from the chromatographic analyses of the organic residue traces found on the vessel.
Conditional Kaplan–Meier Estimator with Functional Covariates for Time-to-Event Data
Authors: Tholkage Sudaraka , Zheng Qi , Kulasekera Karunarathna B.
Published: November 2022

Due to the wide availability of functional data from multiple disciplines, the studies of functional data analysis have become popular in the recent literature. However, the related development in censored survival data has been relatively sparse. In this work, we consider the problem of analyzing time-to-event data in the presence of functional predictors. We develop a conditional generalized Kaplan–Meier (KM) estimator that incorporates functional predictors using kernel weights and rigorously establishes its asymptotic properties. In addition, we propose to select the optimal bandwidth based on a time-dependent Brier score. We then carry out extensive numerical studies to examine the finite sample performance of the proposed functional KM estimator and bandwidth selector. We also illustrated the practical usage of our proposed method by using a data set from Alzheimer’s Disease Neuroimaging Initiative data.
Study on Analysis Principle of Spatial System Method for a Hydraulic Steel Gate
Authors: Zhang Xuecai , Lou Senyuan , Chen Liye , Wang Zhengzhong , Zhang Fufu
Published: November 2022

The target of this paper is to ensure that the spatial system method has scientific and efficient rules to follow in structural analysis of a hydraulic steel gate, and to overcome the problems of randomness and fuzziness in the analysis process. Based on the idea of part and whole, the analysis principle of the spatial system method for a steel gate is systematically studied using the combination of theoretical calculation, finite element analysis, and prototype testing. First, the method is verified, with theoretical calculation used to ensure the authenticity of geometric modeling, the appropriateness of the element type, the rationality of meshing, the accuracy of constraints, and load application when the spatial system method is used to analyze the gate structure (panel, arm, and beam). The specific and practical feasible analysis principles of using the spatial system method to analyze the gate structure are provided. Second, the analysis of the gate structure is carried out using the analysis principle of the spatial system method. Finally, a prototype test is used to verify the analysis results of the spatial system method. Based on the prototype test results, the maximum absolute error of static displacement is 0.58 mm and the maximum relative error of static stress is 9.19%, which verifies the rationality and accuracy of the analysis principle of the spatial system method. The key technical problems restricting the transition of the gate structure analysis from the plane system method to the spatial system method are preliminarily solved. This first exploration is made for the popularization and application of the spatial system method, and lays a technical foundation for improving the quality and efficiency of gate structure design.
Developing Effective Measures of Organizational Capability of Manufacturing Firms: An Exploratory Case Study of Japanese Manufacturing Firms
Authors: Fujimoto Takahiro , Fukuzawa Mitsuhiro , Park Young Won , Hong Paul
Published: November 2022

The present article explores the flow-oriented and routine-based concept of organizational capability in manufacturing and proposes a practical method of measuring it by using the flow map of material and information (FMMI), including the value stream map (VSM). The environment surrounding manufacturing companies is becoming increasingly turbulent, making it increasingly difficult for them to survive and prosper. For example, global companies face challenges on multiple fronts such as international trade tensions, pandemic lockdowns, and competitive challenges from firms in emerging economies. In addition, in digital markets, supply chain transparency and resiliency require visualizing the flow of materials and information across a wide range of global activities. Business activities are conceived as flows of design and control information from across functions for value creation and transfer. A high level of value creation is built on the excellence of vital function. In this context, this study aims to identify key characteristics of high-performance firms. In particular, the flow map of material and information (FMMI) assumes simultaneous execution of capability-building and capability-measuring. This research team reports the series of workshops and survey results based on (1) the work of the industry-university consortium, (2) the collaborative learning process through trust and information sharing among participating companies, (3) sharing improvement activities, and (4) identifying areas of poor flow (issues for each company). In addition, several selected case studies of Japanese firms highlight the impact of using FMMI for improving multiple performance outcomes and measuring their manufacturing capabilities at the same time. The lessons and implications are discussed.
From Panarchy to World-Ecology: Combining the Adaptive Cycle Heuristic with Historical-Geographical Approaches to Explore Socio-Ecological Systems’ Sustainability
Authors: Menegat Stefano
Published: November 2022

This article investigates the dynamics of socio-ecological systems’ (SESs) unsustainability. By adopting a theoretical standpoint grounded in systems’ theory, the analysis shows how SESs’ teleology (or final cause) is of the utmost relevance for understanding the relationship between humans and ecosystems and how it is pivotal for envisioning possible evolutionary trajectories towards sustainability. Building on the contributions of both system and social scientists, the study argues that SESs’ teleology is determined by dominant social ontologies that require a dialectical lens to be properly dealt with. The article therefore proposes the adoption of the adaptive cycle heuristic complemented by an historical-geographical approach based on world-ecology theory as a means to interpret SESs’ behavior. Such a perspective allows for the direct comparison between the four stages of the panarchy cycle (reorganization, exploitation, conservation, and release) and the four stages theorized by the world-ecology dialectics (expansion, appropriation, capitalization, crisis). In conclusion, the article claims that both system and social scientists would benefit from including concepts and definitions from the other field in their analysis, since both provide valuable insights about SESs’ processes of change and both are necessary to envision transition pathways towards sustainability.
Identification of Fungal Communities Isolated from Himalayan Glacier Cryoconites
Authors: Dhume Gandhali M. , Tsuji Masaharu , Singh Shiv Mohan
Published: November 2022

The current study focuses on fungi that were isolated from cryoconite holes of the Hamtah glacier in the Himalayas. Cryoconite holes have ecological and biotechnological importance. A total of seven cryoconite samples were collected from different locations and subjected to the isolation of psychotropic fungi at 1, 4, 15 and 22 °C. Isolates were identified by ITS and D1/D2 region sequences. The result showed culturable yeasts (45) and filamentous fungi (10) belonging to four ascomycetous classes (Dothideomycetes, Eurotiomycetes, Saccharomycetes and Sordariomycetes) and two basidiomycetes’ classes (Microbotryomycetes and Tremellomycetes). Physiological characteristics such as the pH, temperature, salt tolerance, carbon source utilization and antibiotics sensitivity of the isolates were studied. All the isolates were grown from acidic to alkaline pH and were able to grow at 1 to 22 °C. The fungal cultures isolated were screened to produce cold active enzymes such as amylase, cellulase, lipase, protease and catalase. Cellulase activity was detected at its maximum at both 4 and 15 °C. Himalayan cryoconites fungi showed immense potential for biotechnological and industrial applications. To the best of our knowledge, this is the first record of the characterization of fungal communities present in the glacier cryoconites of the Himalayas.
Evaluating the Impacts of Climate Change on Irrigation Water Requirements
Authors: Makar Randa S. , Shahin Sahar A. , El-Nazer Mostafa , Wheida Ali , Abd El-Hady Mohamed
Published: November 2022

Climate change and its impact on agriculture and water resources have become a global concern. The implications of extreme weather events on food production and water resource availability are starting to have social and economic effects worldwide. The present research aims at integrating the analysis of the atmospheric parameters with remote sensing, geographic information systems, and CROPWAT 8 model to evaluate the impacts of climate change on the irrigation water requirements estimates in a selected area in El-Beheira governorate, Egypt. Remote sensing and GIS are incorporated to produce land-use/land-cover maps and soil properties maps. On the other hand, the atmospheric parameters were analyzed using python analytical coding. The study utilized the Land-use/Land-cover (LU/LC) map produced from Sentinel-2 data. The agricultural area covered about 89% of the studied area and was occupied by seven crops. Wheat and berseem were the major crops in the area and covered about 67% of the studied area; therefore, their irrigation water requirements were calculated utilizing the CROPWAT 8 model. Furthermore, citrus irrigation water requirements were also included in this research, even though it only covered 10% of the studied area because it had the highest amount of irrigation water requirements. Forecasting the potential climate changes under the best-case scenario for the next thirty years revealed that the studied area will have no rain and a slight decrease in the average temperature. Accordingly, the irrigation water requirements will increase by almost 4% under current practices, and the increase will reach about 13% under no-field loss practices.
The Roles of Service Recovery and Perceived Justice on Post-Recovery Satisfaction in M-Commerce
Authors: Liao Ying Kai , Wu Chih Ying , Truong Giang Nu To , Do Yen Thi
Published: November 2022

Mobile commerce is a fast-growing industry expected to grow continuously thanks to the wide acceptance of mobile phones and the worldwide 4G infrastructure. Previous research on m-commerce mostly focused on theory, technology acceptance, and legal issues, while service failure and recovery in m-commerce have not yet been covered. However, service failure is inevitable as the service process is complicated, and successful service recovery can retain customers. This research adopts an experimental study to discover the relationship between service failure, service recovery strategy, perceived justice, and post-recovery satisfaction in mobile commerce. The results confirm that, for different types of service failure, the effect of satisfaction level would differ for a different recovery strategy. Moreover, perceived justice would be affected by the service failure magnitude and service recovery strategy and would further affect post-recovery satisfaction. This study will provide an essential reference for both academicians and professionals to conduct further empirical validation or develop appropriate programs to solve service recovery issues.
Industry 5.0 and the Circular Economy: Utilizing LCA with Intelligent Products
Authors: Turner Chris , Oyekan John , Garn Wolfgang , Duggan Cian , Abdou Khaled
Published: November 2022

While the move towards Industry 4.0 has motivated a re-evaluation of how a manufacturing organization should operate in light of the availability of a new generation of digital production equipment, the new emphasis is on human worker inclusion to provide decision making activities or physical actions (at decision nodes) within an otherwise automated process flow; termed by some authors as Industry 5.0 and seen as related to the earlier Japanese Society 5.0 concept (seeking to address wider social and environmental problems with the latest developments in digital system, artificial Intelligence and automation solutions). As motivated by the EU the Industry 5.0 paradigm can be seen as a movement to address infrastructural resilience, employee and environmental concerns in industrial settings. This is coupled with a greater awareness of environmental issues, especially those related to Carbon output at production and throughout manufactured products lifecycle. This paper proposes the concept of dynamic Life Cycle Assessment (LCA), enabled by the functionality possible with intelligent products. A particular focus of this paper is that of human in the loop assisted decision making for end-of-life disassembly of products and the role intelligent products can perform in achieving sustainable reuse of components and materials. It is concluded by this research that intelligent products must provide auditable data to support the achievement of net zero carbon and circular economy goals. The role of the human in moving towards net zero production, through the increased understanding and arbitration powers over information and decisions, is paramount; this opportunity is further enabled through the use of intelligent products.
Factors Impacting SME Business Resilience Post-COVID-19
Authors: Brown Kerry , Jie Ferry , Le Thi , Sharafizad Jalleh , Sharafizad Fleur , Parida Subhadarsini
Published: November 2022

The ability of an organization to respond to a crisis with agility is vital for business leaders to maintain business continuity. Our paper examined how business owners responded to the challenges caused by the pandemic. Using online surveys for data collection, we investigated a critical agility issue of supply chain risks through understanding the interrelationship of various business capability factors. Partial least squares path modeling (PLS-PM) was applied to a sample of 220 participants who were owners of micro, small, and medium businesses in Western Australia. The findings showed that the businesses’ efficiency, financial strength, and flexibility in sourcing affected the businesses’ supply chain risks negatively. More support for labor productivity, asset utilization, waste elimination, financial reserves, portfolio diversification, and credit access needs to be introduced to enhance the resilience of the business supply chain. This paper is novel, as we used the data collected in Western Australia, where the SMEs were still affected by the global supply chain disruption but lacked protracted lockdowns, as had occurred nationally and globally during the COVID-19 period.
Particle Flow Analysis on Mechanical Characteristics of Rock with Two Pre-Existing Fissures
Authors: Yu Zhenzi , Li Ang , Zhang Bo , Li Hongyue , Mu Qian , Zhou Yonggen , Gao Shuai
Published: November 2022

Many research results show that under any stress state the rock mass is most likely to crack, swell, bifurcate, and infiltrate from the fissure tip, resulting in rock engineering instability and failure. In order to study the influence of double fissure angles on rock mechanical characteristics, five rock numerical models with different fissure angles were established by numerical simulation software. Uniaxial compression tests were carried out, and the variation characteristics of rock stress, strain, failure, microcrack, and acoustic emission (AE) were recorded. The test results show that: With increases in the fissure angles, the elastic modulus of rock increased, while the peak strength decreased first and then increased. The number of microcracks in rock was greater at 15° and 75° than at other angles. The microcracks in rock were mainly tensile cracks, and relatively few were shear cracks. The angles of microcracks were mostly concentrated between 0 and 180°, most of which were between 60 and 110°. The failure of rock was relatively light when the fissure angle was15° or 75°, but it produced more and smaller fragments, and the failure was the most serious when the fissure angle was 30°. The angles of the fissures affected the maximum number of AE events, the strain values for the initial AE event, and the maximal AE event. This research can provide some reference for disasters caused by rocks with pre-existing fissures.
Research on the Correlation and Influencing Factors of Digital Technology Innovation in the Guangdong–Hong Kong–Macao Greater Bay Area
Authors: Chen Diexin , Xiao Yuxiang , Huang Kaicheng , Li Xiumin
Published: November 2022

We investigated the digital technology innovation association’s spatial distribution characteristics and influencing factors using social network analysis and a negative binomial gravity regression model. The model was based on the transfer of digital technology patent rights among cities in the Guangdong–Hong Kong–Macao Greater Bay Area from 2010 to 2020. The following are the paper’s main findings: First, the digital technology innovation association among cities in the Guangdong–Hong Kong–Macao Greater Bay Area is strengthening, and the accessibility and agglomeration of each city node are improving, as are small-world characteristics. Second, for a long time, the four cities of Guangzhou, Shenzhen, Dongguan, and Foshan have been at the epicenter of digital technology innovation. Third, in a more peripheral position, Zhongshan, Huizhou, and Zhaoqing have gradually increased the number of digital technology innovation linkages with other cities. Fourth, technological and institutional proximity positively impact digital technology innovation associations in the Greater Bay Area, whereas geographical distance has a negative impact. The study’s findings can be used to help promote digital technology innovation linkages and develop policies for innovation development in the Greater Bay Area.
Spatial Analysis of Environmentally Sensitive Areas to Soil Degradation Using MEDALUS Model and GIS in Amazonas (Peru): An Alternative for Ecological Restoration
Authors: Meza Mori Gerson , Torres Guzmán Cristóbal , Oliva-Cruz Manuel , Salas López Rolando , Marlo Gladys , Barboza Elgar
Published: November 2022

Land degradation is a permanent global threat that requires an interdisciplinary approach to addressing solutions in a given territory. This study, therefore, analyses environmentally sensitive areas to land degradation using the Mediterranean Desertification and Land Use (MEDALUS) and Geographic Information System (GIS) method through a multi-criteria approach in the district of Florida (Peru). For the method, we considered the main quality indicators such as: Climate Quality Index (CQI), Soil Quality Index (SQI), Vegetation Quality Index (VQI), and Management Quality Index (MQI). There were also identified groups of parameters for each of the quality indicators analyzed. The results showed that 2.96% of the study area is classified as critical; 48.85% of the surface is classified as fragile; 15.48% of the areas are potentially endangered, and 30.46% are not threatened by degradation processes. Furthermore, SQI, VQI, and MQI induced degradation processes in the area. Based on the results, five restoration proposals were made in the study area: (i) organic manure production, (ii) cultivated and improved pastures and livestock improvement, (iii) native forest restoration, (iv) construction of reservoirs in the top hills and (v) uses of new technologies. The findings and proposals can be a basic support and further improved by decision-makers when implemented in situ to mitigate degradation for a sustainable use of the territory.
Analyzing the Effect of Crowds on Passenger Behavior Inside Urban Trains through Laboratory Experiments—A Pilot Study
Authors: Seriani Sebastian , Barriga Jose Miguel , Peña Alvaro , Valencia Alejandra , Aprigliano Vicente , Jorquera Lorena , Pinto Hernan , Valenzuela Matías , Fujiyama Taku
Published: November 2022

The objective is to study the distribution of passengers inside urban trains for different levels of crowding. The study is carried out through the observation of videos made by laboratory experiments in which a mock-up of a carriage represented the boarding and alighting process. The Fruin’s Level of Service (LOS) was adopted, but with a different approach, in which the train is divided into five zones (central hall, central aisle, side aisle, central seats and side seats). The experiments are based on the behavior of passengers in the London Underground; however, this study could be expanded to any conventional rail or LRT system. For the laboratory experiments, it is proposed to build a metro carriage and a corresponding platform section, and the scenarios will include different levels of crowding of passengers boarding and alighting to produce a variation in the density on the platform. According to the crowding level, the results allow obtaining the distribution and movements generated by passengers in the five zones for different instants of time during the process of boarding and alighting. It is observed that passengers are distributed according to safety and efficiency conditions. For example, passengers tried to avoid contact with each other unless it is inevitable. In relation to comfort, the seats of the carriage are always used even if there is a low level of crowding. If the crowding level increases, the boarding and alighting time go up. In addition, passengers will spend one or two seconds more if the “let’s get off before getting on the carriage” behavior is breached. This kind of experiment can be used in further research as a way to test “what-if” scenarios using this new method of discretization of the space inside the train, which cannot be tested in existing stations due to restrictions such as the weather, variability of the train frequency, current design of the trains, among others. New experiments are necessary for future research to include other types of passengers such as people with disabilities or reduced mobility.
Analysis and Research on Temporal and Spatial Variation of Color Steel Tile Roof of Munyaka Region in Kenya, Africa
Authors: Zhang Wenzhi , Liu Gunangchun , Ding Laizhong , Du Menghao , Yang Sen
Published: November 2022

In Africa, the distribution of color steel tile roof (CSTR) can reflect the living standard of residents, and the analysis of its temporal and spatial changes can reflect the local changes in local living conditions. It is helpful to analyze the change of the local economic level. By using the satellite remote sensing image processing method to obtain the temporal and spatial change characteristics of CSTR and to analyze the changes in residents’ living conditions in Munyaka, Eldoret, Kenya, Africa, the model of multifeature decision tree method (DTM) extraction was established. The Normalized Difference Vegetation Index (NDVI) and Normalized Difference Building Index (NDBI) were used to remove farmland from the difference of the CSTR. The Normalized Difference Surface Index (NCSI) was constructed, and the texture features were analyzed to eliminate wasteland and bare land, respectively. The research results show that the Kappa coefficient is 0.9223, and the user precision and mapping precision are 97.79% and 91.10%, respectively. At the same time, combined with the Erdoret municipal road project, the changes of CSTR before and after the project in 2016–2020 are studied. Compared the area change of CSTR in 2016–2018 with that in 2018–2020, the annual growth rate before the construction of the municipal road project is about 3.47%. After the completion of the project, the annual growth rate is 7.29%, more than twice the rate before the construction. This method can realize the dynamic monitoring of CSTR, reflect the changes of the residents’ living environment in the region, help analyze the improvement of poverty in Africa, and help understand the changes of African economic conditions.
The g-Good-Neighbor Conditional Diagnosability of Exchanged Crossed Cube under the MM* Model
Authors: Wang Xinyang , Li Haozhe , Sun Qiao , Guo Chen , Zhao Hu , Wu Xinyu , Wang Anqi
Published: November 2022

Diagnosability plays an important role in appraising the reliability and fault tolerance of symmetrical multiprocessor systems. The novel g-good-neighbor conditional diagnosability restrains that every fault-free node contains at least g fault-free neighbors and is suitable for large scale multiprocessor systems, attracting a lot of research attention. The relationships between the g-good-neighbor connectivity and g-good-neighbor diagnosability of graphs under the MM* model are separately studied, but only applicable in regular graphs or just ranges rather than exact values. As a promising network structure, in 2019, Guo et al. obtained that the g-good-neighbor diagnosability of the exchanged crossed cube (ECQ(s,t)) under the PMC model is 2g(s+2−g)−1 (t≥s>g). We noticed that the exact value of the g-good-neighbor diagnosability of ECQ(s,t) under the MM* model is still to be determined. In this paper, by proving the upper and lower bounds of the g-good-neighbor diagnosability of ECQ(s,t), for the first time, we derive that the exact value of its g-good-neighbor diagnosability under the MM* model is tgm(ECQ(s,t))=2g(s+2−g)−1 (t≥s>g), achieving the unity of the g-good-neighbor diagnosability of ECQ(s, t) under both the PMC model and MM* model. Towards the end, simulation experiments are conducted to evaluate the correctness and effectiveness of our conclusion. Our research provides an important supplement to the g-good-neighbor diagnosability of ECQ(s,t).
Cryptosystems Based on Tropical Congruent Transformation of Symmetric Matrices
Authors: Huang Huawei
Published: November 2022

Recently, public-key cryptography based on tropical semi-rings have been proposed. However, the majority of them are damaged. The main reason is that they use a public matrix to construct commutative matrix semi-rings. New public-key cryptosystems are proposed in this paper. They are based on tropical congruent transformation of symmetric matrix by circular matrix. The NP-hard problem of solving a tropical system of nonlinear equations underlies the cryptosystem’s security. Since a known matrix cannot express the used commutative subsemi-rings of circular matrices and there is no tropical matrix addition operation and power of matrix, the cryptosystems can withstand known attacks, including the KU attack, RM attack, and IK attack. The length of the public key and private key of the new cryptosystems is half that of those described in the literature.
Developmental Noise and Biological System Condition: Prolegomena
Authors: Zakharov Vladimir M. , Trofimov Ilya E.
Published: November 2022

Developmental noise is a variety that is not related to the usually distinguished sources of phenotypic diversity, i.e., differences in the genotype and in the environment. This variation arises in the process of the realization of genetic information and reflects the imperfection of ontogenetic processes. The most common measure of it is the value of fluctuating asymmetry as slight deviations from the symmetry. Developmental noise proves to be one of the main sources of intrapopulation phenotypic diversity. The magnitude of this variability is an ontogenetic response to environmental or genetic stress, and its assessment, in fact, provides a unique opportunity to estimate the developing system condition. The level of developmental noise, characterizing an organism’s condition, acts as another population parameter that allows to approach the evaluation of the community condition. Initial deviations in the system condition can be detected even against the background of optimal estimates of abundance, biodiversity, and ecosystem functioning.
Characterization of Urinary Pesticide Metabolite Concentrations of Pregnant Women in Suriname
Authors: Alcala Cecilia , Lichtveld Maureen , Wickliffe Jeffrey , Zijlmans Wilco , Shankar Arti , Rokicki Ellen , Covert Hannah , Abdoel Wahid Firoz , Hindori-Mohangoo Ashna , van Sauers-Muller Alies , van Dijk Carmen , Roosblad Jimmy , Codrington John , Wilson Mark
Published: November 2022

Prenatal exposure to pesticides and the association with adverse health outcomes have been examined in several studies. However, the characterization of pesticide exposure among Surinamese women during pregnancy has not been assessed. As part of the Caribbean Consortium of Research in Environmental and Occupational Health research program, 214 urine samples were collected from pregnant women living in three regions in Suriname with different agricultural practices: capital Paramaribo, the rice producing district Nickerie, and the tropical rainforest, the Interior. We used isotope dilution tandem mass spectrometry to quantify urinary concentrations of biomarkers of three pesticide classes, including phenoxy acid herbicides and organophosphate and pyrethroid insecticides, all of which are commonly used in agricultural and residential settings in Suriname. We observed that participants residing in Nickerie had the highest urinary metabolite concentrations of 2,4-dichlorophenoxyacetic acid and pyrethroids compared to those from Paramaribo or the Interior. Paramaribo had the highest concentrations of organophosphate metabolites, specifically dialkyl phosphate metabolites. Para-nitrophenol was detected in samples from Paramaribo and the Interior. Samples from Nickerie had higher median urinary pesticide concentrations of 2,4-dichlorophenoxyacetic acid (1.06 μg/L), and the following metabolites, 3,5,6-trichloro-2-pyridinol (1.26 μg/L), 2-isopropyl-4-methyl-6-hydroxypyrimidine (0.60 μg/L), and 3-phenoxybenzoic acid (1.34 μg/L), possibly due to residential use and heavy rice production.
Polycyclic Aromatic Hydrocarbons Induced by Smoking and Air Pollution: Correlation with Oxidative Stress in Chronic Obstructive Pulmonary Disease Patients
Authors: Buculei Ioana , Dobrin Mona Elisabeta , Matei Daniela , Onu Ilie , Vicol Cristina , Cioroiu Ionel Bogdan , Niculaua Marius , Iordan Daniel Andrei , Cernomaz Andrei , Trofor Antigona Carmen
Published: November 2022

Oxidative stress is induced by tobacco smoking and is also associated with exposure to air pollution, which are two of the most important risk factors for chronic obstructive pulmonary disease (COPD). The aim of this study was to correlate tobacco use and exposure to air pollution with oxidative stress markers useful in clinical practice in patients with COPD. A total of 102 patients were included and the levels of polycyclic aromatic hydrocarbons (PAHs), malondialdehyde, uric acid and number of packs-years (PY) were determined. Also, six different ratios were used to assess the source of exposure. The results obtained in this study show an admission of pollutants according to smoking status (former smokers/smoker/non-smokers) quantified in average total concentrations for the group of patients with COPD of 4.12 ng/mL, 6.76 ng/mL, 6.04 ng/mL. The six ratios used show that in COPD, the content of PAHs in the blood could be a result of diesel emissions and fuel combustion. Uric acid levels were lower in the smoker group of COPD patients (mean = 5.21 mg/dL), which indicates that oxidative stress is intensified with each cigarette smoked. Additionally, high concentrations of malondialdehyde were quantified for smoking patients diagnosed with COPD (mean = 2.72 µmol/L) compared to former smokers (mean = 2.43 µmol/L) and non-smoking (mean = 2.32 µmol/L) patients, which is another indicator of the implication of smoking in oxidative stress in COPD patients.
Isolation and Characterization of Two New Deoxynivalenol-Degrading Strains, Bacillus sp. HN117 and Bacillus sp. N22
Authors: Li Beibei , Duan Jiaqi , Ren Jie , Francis Frédéric , Li Guangyue
Published: November 2022

Deoxynivalenol (DON), produced by Fusarium species, is one of the most common trichothecenes detected in cereals pre- and post-harvest, which poses a great threat to the health of livestock and human beings due to its strong toxicity. In this study, we isolated and characterized two DON-degrading bacterial strains, Bacillus sp. HN117 and Bacillus sp. N22. Both strains could degrade DON efficiently in a wide range of temperatures (from 25 °C to 42 °C) and concentrations (from 10 mg/L to 500 mg/L). After optimization of the degradation conditions, 29.0% DON was eliminated by HN117 in 72 h when it was incubated with 1000 mg/L DON; meanwhile, the DON degradation rate of N22 was boosted notably from 7.41% to 21.21% within 120 h at 500 mg/L DON. Degradation products analysis indicated HN117 was able to transform DON into a new isomer M-DOM, the possible structure of which was deduced based on LC-MS and NMR analysis, and N22 could convert DON into potential low-toxic derivatives norDON E and 9-hydroxymethyl DON lactone. These two strains have the potential to be developed as new biodegrading agents to control DON contamination in food and feed industries.
Proposed Algorithm for Integrated Management of TB-SARS-CoV-2 Co-Infection in a TB-Endemic Country
Authors: Mertaniasih Ni Made , Soedarsono Soedarsono , Pakasi Tiffany Tiara , Nuha Zakiyathun , Ato Manabu
Published: November 2022

Tuberculosis (TB) and COVID-19 have become significant health problems globally, especially in countries with high prevalence. Therefore, this research aims to examine all possibilities and predict the impact of TB-SARS-CoV-2 co-infection to anticipate the cascade effect of both diseases in all sectors. The conceptual strategy of the algorithm in TB-COVID-19 is needed to create an integrated management system. It includes the stages of early detection with accurate and effective methods, as well as the synchronization of TB-COVID-19 health services, starting from primary health facilities to secondary and tertiary referral centers. The algorithm in TB-COVID-19 is crucial to prepare future strategies for PTB co-infection viral respiratory infections other than SARS-CoV-2, ILI, ARI, and SARI. Since the implementation involves all health services, there is a need to integrate the governance of TB-COVID-19 and other comorbidities in good health services based on research and multicentre design.
Antiviral Treatment against Monkeypox: A Scoping Review
Authors: Ortiz-Saavedra Brando , León-Figueroa Darwin A. , Montes-Madariaga Elizbet S. , Ricardo-Martínez Alex , Alva Niza , Cabanillas-Ramirez Cielo , Barboza Joshuan J. , Siddiq Abdelmonem , Coaguila Cusicanqui Luis A. , Bonilla-Aldana D. Katterine , Rodriguez-Morales Alfonso J.
Published: November 2022

During the COVID-19 pandemic, the increase in reports of human monkeypox virus infection cases spreading in many countries outside Africa is a major cause for concern. Therefore, this study aimed to explore the evidence of antiviral pharmacotherapy available for the treatment of adult patients with monkeypox. A scoping review of the literature was conducted using PubMed, Scopus, Web of Science, Embase, and CENTRAL databases until 12 September 2022. The key search terms used were “monkeypox” and “treatment”. A total of 1927 articles were retrieved using the search strategy. After removing duplicates (n = 1007) and examining by title, abstract, and full text, 11 studies reporting case reports of monkeypox with antiviral treatment were included, detailing the number of monkeypox cases, clinical manifestations, number of participants with antiviral treatment, history of sexually transmitted diseases, method of diagnosis, location of skin lesions, drugs used in antiviral treatment, route of administration, and outcome. A total of 1281 confirmed cases of monkeypox have been reported, of which 65 monkeypox cases had antiviral treatment distributed most frequently in the United States (n = 30), the United Kingdom (n = 6), and Spain (n = 6). Of the total cases, 1269 (99.1%) were male with an age range of 18 to 76 years, and 1226 (95.7%) had a sexual behavior of being men who have sex with men. All confirmed cases of monkeypox were diagnosed by reverse transcriptase polymerase chain reaction (RT-PCR). The most frequent clinical manifestations were skin lesions, fever, lymphadenopathy, headache, fatigue, and myalgia. The most frequent locations of the lesions were perianal, genital, facial, and upper and lower extremities. The most commonly used drugs for antiviral treatment of monkeypox were: tecovirimat, cidofovir, and brincidofovir. All patients had a complete recovery. According to current evidence, the efficacy and safety of antiviral drugs against monkeypox is of low quality and scarce.
Using Video Analytics to Improve Traffic Intersection Safety and Performance
Authors: Mishra Ahan , Chen Ke , Poddar Subhadipto , Posadas Emmanuel , Rangarajan Anand , Ranka Sanjay
Published: November 2022

Road safety has always been a crucial priority for municipalities, as vehicle accidents claim lives every day. Recent rapid improvements in video collection and processing technologies enable traffic researchers to identify and alleviate potentially dangerous situations. This paper illustrates cutting-edge methods by which conflict hotspots can be detected in various situations and conditions. Both pedestrian–vehicle and vehicle–vehicle conflict hotspots can be discovered, and we present an original technique for including more information in the graphs with shapes. Conflict hotspot detection, volume hotspot detection, and intersection-service evaluation allow us to understand the safety and performance issues and test countermeasures comprehensively. The selection of appropriate countermeasures is demonstrated by extensive analysis and discussion of two intersections in Gainesville, Florida, USA. Just as important is the evaluation of the efficacy of countermeasures. This paper advocates for selection from a menu of countermeasures at the municipal level, with safety as the top priority. Performance is also considered, and we present a novel concept of a performance–safety trade-off at intersections.
Climate Change Impacts on Runoff in the Fujiang River Basin Based on CMIP6 and SWAT Model
Authors: Wang Yong , Xu Hong-Mei , Li Yong-Hua , Liu Lyu-Liu , Hu Zu-Heng , Xiao Chan , Yang Tian-Tian
Published: November 2022

Understanding the responses of the hydrological cycle and extreme events to climate change is essential for basin water security. This study systematically assessed climate change impacts on runoff and floods in the Fujiang River basin, which is the main tributary of the upper Yangtze River, China, using the Soil Water Assessment Tool (SWAT) driven by the latest climate simulation of 14 General Circulation Models (GCMs) under two Shared Socioeconomic Pathways (SSP2-4.5 and SSP5-8.5). This study indicates a generally warmer and wetter climate projected in the Fujiang River basin, and correspondingly an overall increase in projected ensemble annual mean runoff, monthly runoff, monthly high flow (Q05), and monthly low flow (Q95) in the periods of 2021–2060 and 2061–2100, with the long-term period being more substantial than that of the near future, especially for SSP5-8.5. However, the projected changes in monthly runoff show a large spread across GCMs, with greater increases mainly occurring in the early rainy season. Most of the GCMs show that projections of Q95 will substantially increase compared to Q05. The intensity and frequency of floods with a 30-year return period are likely to increase, especially under SSP5-8.5. Despite the uncertainties in projected future changes in runoff, these findings highlight the complexity of runoff response to climate change, promoting the need for adaptive water resource management.
Synchronization-Enhanced Deep Learning Early Flood Risk Predictions: The Core of Data-Driven City Digital Twins for Climate Resilience Planning
Authors: Ghaith Maysara , Yosri Ahmed , El-Dakhakhni Wael
Published: November 2022

Floods have been among the costliest hydrometeorological hazards across the globe for decades, and are expected to become even more frequent and cause larger devastating impacts in cities due to climate change. Digital twin technologies can provide decisionmakers with effective tools to rapidly evaluate city resilience under projected floods. However, the development of city digital twins for flood predictions is challenging due to the time-consuming, uncertain processes of developing, calibrating, and coupling physics-based hydrologic and hydraulic models. In this study, a flood prediction methodology (FPM) that integrates synchronization analysis and deep-learning is developed to directly simulate the complex relationships between rainfall and flood characteristics, bypassing the computationally expensive hydrologic-hydraulic models, with the City of Calgary being used for demonstration. The developed FPM presents the core of data-driven digital twins that, with real-time sensor data, can rapidly provide early warnings before flood realization, as well as information about vulnerable areas—enabling city resilience planning considering different climate change scenarios.
A Linear Programming Model for Operational Optimization of Agricultural Activity Considering a Hydroclimatic Forecast—Case Studies for Western Bahia, Brazil
Authors: Boninsenha Igor , Mantovani Everardo Chartuni , Costa Marcos Heil , da Silva Júnior Aziz Galvão
Published: November 2022

The water crisis is a reality in Western Bahia. In this region, a hydroclimatic monitoring system capable of providing water availability information in advance for water users was implemented objectively to avoid water conflicts. In this study, we proposed the integration between the hydroclimatic monitoring system and a linear programming method to optimize the agricultural net benefit considering the scenarios of rainfall delay or reduction. Case studies were demonstrated in five farms and three municipalities of Western Bahia. The results show that in irrigated areas, the model optimizes the net economic benefit by the possibility of a continuous or double-cropping system, even in rainfall delay or reduction, where irrigation can supply the water demand of crops. In rainfed areas, it is noticeable that in rainfall delay or reduction scenarios, the model response is not to crop, due to the accentuated water deficit in crops, which may cause a significant yield reduction. It was found in a farm-level analysis, where the model response was not to crop, and farmers had a yield reduction of 61% in rainfed areas. This study opens the integration between the optimization methodologies and the hydroclimatic monitoring system with new insights into how this integration can guide water governance actions in regions where the water crisis is a reality.