bluuebunny/crossref_metadata_2025 huggingface dataset:
Application of Quality 4.0 (Q4.0) and Industrial Internet of Things (IIoT) in Agricultural Manufacturing Industry
Authors: Singh Jagmeet , Ahuja Inderpreet Singh , Singh Harwinder , Singh Amandeep
Published: March 2023

The objective of this research is to apply Quality 4.0 (Q4.0) concept in Agriculture 4.0 (A4.0) to digitize the traditional quality management (QM) system and demonstrate the effectiveness of zero-defect manufacturing (ZDM) in the agricultural part manufacturing industry. An autonomous quality management system was developed based on the ZDM system using the Industrial Internet of Things (IIoT). Both traditional and autonomous quality management systems were evaluated using six-sigma quality indicators and machining and inspection cost analysis. The ZDM resulted in a significant improvement in the quality of CARD148 manufacturing, increasing the manufacturing process from a low level of sigma to a high level of sigma (0.75 to 5.10 sigma). The component rejection rate was reduced by a high percentage, leading to significant economic benefits and a significant reduction in machining cost. The process yield was also increased to a high percentage. The developed ZDM was found to be consistent in improving the quality of the turning process, with notable increases in tool life and reduction in inspection cost. The total component cost was reduced significantly, while the PPM value increased notably. While this study focuses on agriculture-related manufacturing organizations, the developed ZDM has potential for other machining industries to improve sigma levels, particularly in industries such as automotive and medical.
Associations between Somatic Cell Count and Milk Fatty Acid and Amino Acid Profile in Alpine and Saanen Goat Breeds
Authors: Šlyžius Evaldas , Anskienė Lina , Palubinskas Giedrius , Juozaitienė Vida , Šlyžienė Birutė , Juodžentytė Renalda , Laučienė Lina
Published: March 2023

The main goal of this study was to evaluate the relation of different SCC levels in goat milk with goat milk yield, milk composition, FA, and AA profiles. Whereas the investigated herd was composed of Alpine and Saanen goats, the influence of breed on milk parameters and milk yield was also assessed. The research was carried out in 2022 at a Lithuanian dairy goat farm with 135 goats (Saanen = 66 and Alpine = 69) without evidence of clinical mastitis. The current research revealed a relationship between SCC with goat milk yield and composition. Goats with a high SCC had significantly lower milk yield (p < 0.001), lower content of lactose (p < 0.01), fat (p < 0.001) and higher protein content (p < 0.05) in their milk. The increase in most AA was significantly associated with increased SCC. The higher quantity of Asp, Glu, Ala, Met, His, Lys, Arg, EAA, NEAA, and TAA (compared with the low SCC group) (p < 0.05–0.01), Leu, Tyr, and BCAA (compared with the low and medium SCC group) were found in the milk of the high SCC group (p < 0.05–0.01). The distribution of the main FA groups was also related to SCC and showed a significant decrease in SCFA (p < 0.01–0.001) and an increase in LCFA, PUFA, and BCFA in the high SCC group (p < 0.05). All individual AA and their groups (EAA, NEAA, TAA, BCAA) were significantly lower in the milk of the Saanen goat breed (p < 0.001). The most individual FA ranged between goat breeds, while the total amount of SFA, UFA, and MUFA wasn’t affected by breed (p > 0.05). The research revealed a statistically significant relationship between SCC, AA, and FA, suggesting that these traits may be used as a biomarker in the goat selection process.
Citrus Flavonoids Supplementation as an Alternative to Replace Zinc Oxide in Weanling Pigs’ Diets Minimizing the Use of Antibiotics
Authors: Paniagua Montserrat , Villagómez-Estrada Sandra , Crespo Francisco Javier , Pérez José Francisco , Arís Anna , Devant Maria , Solà-Oriol David
Published: March 2023

Since citrus flavonoids have antioxidant and anti-inflammatory properties, it was hypothesized that these compounds would become a suitable alternative to the use of therapeutic doses of zinc oxide at weaning. A total of 252 weaned pigs ([LargeWhite × Landrace] × Pietrain) were distributed according to BW (5.7 kg ± 0.76) into 18 pens (6 pens per diet, 14 pigs/pen). Three experimental diets for the prestarter (0–14 d postweaning) and starter (15–35 d postweaning) period were prepared: (i) a nonmedicated (CON) diet, (ii) a CON diet supplemented with zinc oxide at 2500 mg/kg, amoxicillin at 0.3 mg/kg and apramycin at 0.1 mg/kg (ZnO), and (iii) CON diet with the addition of a commercial citrus flavonoid extract at 0.3 mg/kg and amoxicillin at 0.3 mg/kg (FLAV). Pig BW, ADG, ADFI, and FCR were assessed on d7, d14, and d35. Samples of intestinal tissue, cecal content, and serum were collected on day seven (18 piglets). FLAV treatment achieved greater BW and ADG during the starter and for the entire experimental period compared with the CON diet (p < 0.05), whereas ZnO pigs evidenced intermediate results. Jejunum tissue analysis showed that pigs fed the FLAV diet overexpressed genes related to barrier function, digestive enzymes, and nutrient transport compared to those pigs fed the CON diet (p < 0.05). An increase in the abundance of bacterial genera such as Succinivibrio, Turicibacter, and Mitsuokella (p < 0.05) was observed in the FLAV compared with the CON and ZnO piglets. ZnO and FLAV increased the expression of TAS2R39, while ZnO pigs also expressed greater TAS2R16 than CON (p < 0.05) in the intestine. FLAV treatment improved the gut function, possibly explaining a higher performance at the end of the nursery period. Consequently, citrus flavonoids supplementation, together with amoxicillin, is a promising alternative to the use of zinc oxide plus amoxicillin and apramycin in weanling pigs, minimizing the use of antibiotics.
High Dietary Cation and Anion Difference and High-Dose Ascorbic Acid Modify Acid–Base and Antioxidant Balance in Dairy Goats Fed under Tropical Conditions
Authors: Semsirmboon Sapon , Do Nguyen Dang Khoa , Chaiyabutr Narongsak , Poonyachoti Sutthasinee , Lutz Thomas A. , Thammacharoen Sumpun
Published: March 2023

High ambient temperature (HTa) causes acid–base imbalance and systemic oxidative stress, and this may indirectly affect the mammary gland. Furthermore, HTa induces intracellular oxidative stress, which has been proposed to affect cell metabolism directly. We previously showed in dairy goats that the negative effect of HTa was compromised by enhancing heat dissipation during a high dietary cation and anion difference (DCAD) regimen. Moreover, high-dose vitamin C or ascorbic acid (AA) supplements have been used to manage oxidative stress in ruminants. The present study hypothesized that high DCAD and AA supplements that could alleviate the HTa effect would influence the milk synthesis pathway and mammary gland function. The results showed that goats fed with high DCAD had higher blood pH than control goats in the 4th week. The high dose of AA supplement decreases urine pH in the 8th week. The percent reduction of urine pH from the AA supplement was significant in the DCAD group. The high-dose AA supplement decreased plasma glutathione peroxidase activity and malonaldehyde. This effect was enhanced by a high DCAD supplement. In addition, supplementation with AA increased milk protein and citrate and decreased milk FFA. These alterations indicate the intracellular biochemical pathway of energy metabolism and milk synthesis. It can be concluded that a high DCAD regimen and AA supplement in dairy goats fed under HTa could influence the milk synthesis pathway. The evidence suggests that HTa decreases mammary gland function by modification of acid–base homeostasis and oxidative stress.
Using Species Knowledge to Promote Pro-Environmental Attitudes? The Association among Species Knowledge, Environmental System Knowledge and Attitude towards theEnvironment in Secondary School Students
Authors: Härtel Talia , Randler Christoph , Baur Armin
Published: March 2023

Scientists and conservationists suggest species knowledge as a possible starting point when it comes to creating deeper knowledge and awareness of nature, the environment, and biodiversity. The aim of this work was to analyze secondary school students’ species knowledge of vertebrates and invertebrates. This is one of the first studies that also draws on invertebrates. Furthermore, we investigated whether knowledge of species forms a basis for the formation of environmental knowledge and attitude towards the environment. For this purpose, a questionnaire on species knowledge was developed. In addition, a questionnaire was used to measure environmental system knowledge, and the 2-MEV Attitude Scale to measure attitude towards the environment. The questionnaires were completed by 103 seventh and eighth-grade (age: 12–13) students of a secondary German school (Gymnasium, highest stratification level). The students identified more vertebrates than invertebrates (50.15% vs. 36.7%). The structural equation model with the latent variables species knowledge, environmental system knowledge, and attitude towards the environment showed that species knowledge has a highly significant influence on the two other latent variables. More precisely species knowledge explained 28% of the variance in environmental systems knowledge and 17% of the variance in attitude towards the environment. This study can therefore draw attention to the relevance of teaching species knowledge in the sense of Education for Sustainable Development, in order not to promote decreasing biodiversity through dwindling species knowledge.
Long-Term Seed Dispersal within an Asymmetric Lizard-Plant Interaction
Authors: Pérez-Cembranos Ana , Pérez-Mellado Valentín
Published: March 2023

During the last 24 years, the mutualistic interaction between the dead horse arum, Helicodiceros muscivorus, and the Balearic lizard, Podarcis lilfordi, was studied on Aire Island (Balearic Islands, Spain). From a small population of a hundred plants, the dead horse arum expanded extraordinarily throughout the island, reaching the highest known densities of the species and occupying areas of the island where it was not previously present. The current abundance of plants is a direct effect of the frugivorous activity of the Balearic lizard, which is the main, if not the only, effective seed disperser of the plant on Aire Island. However, abiotic factors predominated over biotic factors in driving abundance of plants. Over the years, plant densities varied significantly depending on the aridity of the island, with higher densities recorded in drier years. Lizards’ frugivorous activity and dispersal intensity was inversely correlated with annual rainfall. We found higher dispersal intensity in years with lower rainfall. We propose that the years of lower rainfall are those in which there is a lower prey availability. In such years, lizards compensate the shortage of other trophic resources with a more intense consumption of dead horse arum fruits. The mutualistic interaction is therefore asymmetric, since there is a greater influence of the frugivorous activity of the lizards on the plants than of the plants on lizards. It is, in short, a system chronically out of balance.
A Longitudinal Study with a Laser Methane Detector (LMD) Highlighting Lactation Cycle-Related Differences in Methane Emissions from Dairy Cows
Authors: Pereira Ana Margarida , Peixoto Pedro , Rosa Henrique J. D. , Vouzela Carlos , Madruga João S. , Borba Alfredo E. S.
Published: March 2023

Reversing climate change requires broad, cohesive, and strategic plans for the mitigation of greenhouse gas emissions from animal farming. The implementation and evaluation of such plans demand accurate and accessible methods for monitoring on-field CH4 concentration in eructating breath. Therefore, this paper describes a longitudinal study over six months, aiming to test a protocol using a laser methane detector (LMD) to monitor CH4 emissions in semi-extensive dairy farm systems. Over 10 time points, CH4 measurements were performed in dry (late gestation) and lactating cows at an Azorean dairy farm. Methane traits including CH4 concentration related to eructation (E_CH4) and respiration (R_CH4), and eructation events, were automatically computed from CH4 measured values using algorithms created for peak detection and analysis. Daily CH4 emission was estimated from each profile’s mean CH4 concentration (MEAN_CH4). Data were analyzed using a linear mixed model, including breed, lactation stage, and parity as fixed effects, and cow (subject) and time point as random effects. The results showed that Holsteins had higher E_CH4 than Jersey cows (p < 0.001). Although a breed-related trend was found in daily CH4 emission (p = 0.060), it was not significant when normalized to daily milk yield (p > 0.05). Methane emissions were lower in dry than in lactation cows (p < 0.05) and increased with the advancement of the lactation, even when normalizing it to daily milk yield (p < 0.05). Primiparous cows had lower daily CH4 emissions related to R_ CH4 compared to multiparous (p < 0.001). This allowed the identification of periods of higher CH4 emissions within the milk production cycle of dairy cows, and thus, the opportunity to tailor mitigation strategies accordingly.
Correction: van Lent et al. Kittens That Nurse 7 Weeks or Longer Are Less Likely to Become Overweight Adult Cats. Animals 2021, 11, 3434
Authors: van Lent Denise , Vernooij Johannes C. M. , Stolting Marcellina M. , Corbee Ronald Jan
Published: March 2023

The authors would like to make the following corrections to the publication [...]
The Use of Sand Substrate Modulates Dominance Behaviour and Brain Gene Expression in a Flatfish Species
Authors: Almeida Maria Mafalda , Cabrita Elsa , Fatsini Elvira
Published: March 2023

Physical complexity adds physical enrichment to rearing conditions. This enrichment promotes fish welfare and reduces detrimental characteristics that fish develop in captivity. Senegalese sole (Solea senegalensis) is an important species for European aquaculture, where it is reared in intensive conditions using fibreglass tanks. However, reproductive dysfunctions present in this species do not allow it to complete its life cycle in captivity. Recently, dominance behaviour has been studied to try to solve this problem. The present study aimed to assess the effect of sand as environmental enrichment in the dominance behaviour and brain mRNA abundance of Senegalese sole juveniles. Four tanks of sole (n = 48 fish in total) were established in two different environments (with and without sand). Juveniles were subjected to dominance tests of feeding and territoriality. Behaviours analysed by video recordings related to the distance from the food delivered and harassment behaviour towards other individuals (e.g., resting of the head on another individual). In both environments, dominant sole were the first to feed, displayed more head-resting behaviour and dominated the area close to the feeding point, where the events were reduced in fish maintained in the sand. mRNA expression related to differentiation of dopamine neurons (nr4a2) and regulation of maturation (fshra) were significantly upregulated in dominant fish in the sand environment compared to dominants maintained without sand. The use of an enriched environment may affect Senegalese sole dominance, enhance welfare and possibly advance future maturation.
High Frequency of Apodemus Mice Boosts Inverse Activity Pattern of Bank Voles, Clethrionomys glareolus, through Non-Aggressive Intraguild Competition
Authors: Probst Remo , Probst Renate
Published: March 2023

Sympatric animals with similar requirements can separate their ecological niches along the microhabitat, food and time axes. There may be alternative reasons for an interspecific different activity pattern, such as intraspecific social constraints, predator avoidance or physical conditions such as temperature, precipitation and illumination. We investigated the importance of intraguild competition in a 2-year study in an inner-alpine mixed forest, using small forest rodents as our model species. Apodemus mice were the physically superior, and bank voles, Clethrionomys glareolus, the inferior competitor. We predicted that bank voles would exhibit increased diurnal activity when frequencies of the almost exclusively nocturnal Apodemus mice were high during a seed mast year. To investigate this, we recorded 19,138 1 min videos. Controlling for confounding variables, bank vole diurnal activity was significantly related to the frequency of Apodemus mice. We assume that at high densities of Apodemus mice, a purely nocturnal separation in the niche dimensions of time, habitat and microhabitat is no longer sufficient, and therefore an inverse activity pattern by the bank voles is reinforced. Our videos showed, however, that this does not require persistent aggressive meetings and we explain this by the long co-evolution of the taxa under study.
Microbiology Clinical Culture Diagnostic Yields and Antimicrobial Resistance Proportions before and during the COVID-19 Pandemic in an Indian Community Hospital and Two US Community Hospitals
Authors: Gandra Sumanth , Alvarez-Uria Gerardo , Stwalley Dustin , Nickel Katelin B. , Reske Kimberly A. , Kwon Jennie H. , Dubberke Erik R. , Olsen Margaret A. , Burnham Jason P.
Published: March 2023

Studies comparing the impact of the COVID-19 pandemic on diagnostic microbiology culture yields and antimicrobial resistance proportions in low-to-middle-income and high-income countries are lacking. A retrospective study using blood, respiratory, and urine microbiology data from a community hospital in India and two community hospitals (Hospitals A and B) in St. Louis, MO, USA was performed. We compared the proportion of cultures positive for selected multi-drug-resistant organisms (MDROs) listed on the WHO’s priority pathogen list both before the COVID-19 pandemic (January 2017–December 2019) and early in the COVID-19 pandemic (April 2020–October 2020). The proportion of blood cultures contaminated with coagulase-negative Staphylococcus (CONS) was significantly higher during the pandemic in all three hospitals. In the Indian hospital, the proportion of carbapenem-resistant (CR) Klebsiella pneumoniae in respiratory cultures was significantly higher during the pandemic period, as was the proportion of CR Escherichia coli in urine cultures. In the US hospitals, the proportion of methicillin-resistant Staphylococcus aureus in blood cultures was significantly higher during the pandemic period in Hospital A, while no significant increase in the proportion of Gram-negative MDROs was observed. Continuity of antimicrobial stewardship activities and better infection prevention measures are critical to optimize outcomes and minimize the burden of antimicrobial resistance among COVID-19 patients.
‘Brave Enough’: A Qualitative Study of Veterinary Decisions to Withhold or Delay Antimicrobial Treatment in Pets
Authors: Scarborough Ri O. , Sri Anna E. , Browning Glenn F. , Hardefeldt Laura Y. , Bailey Kirsten E.
Published: March 2023

Veterinarians sometimes prescribe antimicrobials even when they know or suspect that they are unnecessary. The drivers of this behaviour must be understood to design effective antimicrobial stewardship interventions. Semi-structured interviews were conducted with 22 veterinarians who treated companion animals in Australia. The Theory of Planned Behaviour was used to organise interview themes, focusing on a decision to withhold antimicrobial therapy in the absence of a clear indication. Many background factors influenced antimicrobial-withholding decisions, including the veterinarian’s communication skills, general attitudes towards antimicrobial resistance (AMR), habits and energy levels. Client awareness of AMR and the veterinarian–client relationship were also important. Beliefs about the consequences of withholding antimicrobials (behavioural beliefs) were dominated by fears of the animal’s condition deteriorating and of failing to meet client expectations. These fears, weighed against the seemingly distant consequences of AMR, were major barriers to withholding antimicrobials. Normative beliefs were primarily focused on the expected approval (or disapproval) of the client and of other veterinarians. Control beliefs about the difficulty of withholding antimicrobials centred around client factors, most importantly, their capacity to adequately monitor their animal, to pay for further investigations, or to undertake non-antimicrobial management, such as wound care, at home. The use of antimicrobials by companion animal veterinarians in the absence of a clear indication is often powerfully driven by behavioural beliefs, chiefly, fears of clinical deterioration and of failing to meet client expectations.
A Selective Survey Review of Computational Intelligence Applications in the Primary Subdomains of Civil Engineering Specializations
Authors: Demertzis Konstantinos , Demertzis Stavros , Iliadis Lazaros
Published: March 2023

Artificial intelligence is the branch of computer science that attempts to model cognitive processes such as learning, adaptability and perception to generate intelligent behavior capable of solving complex problems with environmental adaptation and deductive reasoning. Applied research of cutting-edge technologies, primarily computational intelligence, including machine/deep learning and fuzzy computing, can add value to modern science and, more generally, to entrepreneurship and the economy. Regarding the science of civil engineering and, more generally, the construction industry, which is one of the most important in economic entrepreneurship both in terms of the size of the workforce employed and the amount of capital invested, the use of artificial intelligence can change industry business models, eliminate costly mistakes, reduce jobsite injuries and make large engineering projects more efficient. The purpose of this paper is to discuss recent research on artificial intelligence methods (machine and deep learning, computer vision, natural language processing, fuzzy systems, etc.) and their related technologies (extensive data analysis, blockchain, cloud computing, internet of things and augmented reality) in the fields of application of civil engineering science, such as structural engineering, geotechnical engineering, hydraulics and water resources. This review examines the benefits and limitations of using computational intelligence in civil engineering and the challenges researchers and practitioners face in implementing these techniques. The manuscript is targeted at a technical audience, such as researchers or practitioners in civil engineering or computational intelligence, and also intended for a broader audience such as policymakers or the general public who are interested in the civil engineering domain.
Energy Efficiency Optimization in Onboard SWRO Desalination Plants Based on a Genetic Neuro-Fuzzy System
Authors: López Ángela Hernández , Camacho-Espino Jorge , Peñate Suárez Baltasar , Plasencia Graciliano Nicolás Marichal
Published: March 2023

This work presents a novel intelligent control system based on a Genetic Neuro-Fuzzy tool to optimize and improve the performance of a seawater reverse osmosis desalination plant (SWRO) on board a marine vessel. This investigation pays special attention to minimizing energy consumption to improve the energy efficiency of this marine installation. The system analyzes measurements of different variables—seawater pH, seawater conductivity, permeate flow rate, permeate conductivity, and total energy consumed—in order to provide the most appropriate value of permeate flow rate control and operating pressure of the high-pressure pump (HPP). This intelligent method allows the plant to achieve output values nearer to the desired setpoints set by the plant operators.
A Dynamic Multiple-Query RRT Planning Algorithm for Manipulator Obstacle Avoidance
Authors: Yuan Chengren , Shuai Changgeng , Zhang Wenqun
Published: March 2023

Manipulator motion planning for real-time obstacle avoidance in a dynamic environment is explored in this article. To address obstacle avoidance problems, a multiple-query and sampling-based motion replanning algorithm with the dynamic bias-goal factor, rapidly exploring random tree (DBG-RRT), is proposed to achieve a rapid response and a high success rate. Differently from other studies on path planning, a relay-node method is adopted on the basis of motion planning to generate a new collision-free trajectory. Subsequently, an un-interrupt strategy is embraced to judge whether the generated trajectory would be interfered with by dynamic obstacles. In the end, the DBG-RRT algorithm is applied, and the results demonstrate its effectiveness for manipulator motion planning in a dynamic environment.
Isolation, Specificity, and Application of β-N-Acetylhexosaminidases from Penicillium crustosum
Authors: Ondrejková Ema , Hronská Helena , Štefuca Vladimír , Bláhová Mária , Rosenberg Michal
Published: March 2023

β-N-acetylhexosaminidases have great potential in applied biocatalysis owing to their ability to act on a wide range of natural and modified substrates. In this work, β-N-acetylhexosaminidases from four Penicillium crustosum strains (PcHex) were studied. The production strains showed the highest enzymatic activity in the culture medium after 11–14 days of cultivation. The specific activity of the isolated and purified PcHex of hydrolysis of 4-nitrophenyl-N-acetyl-β-D-galactopyranoside was 15–20 U/mg protein. All isolated β-N-acetylhexosaminidases showed similar pH–activity profiles, with the optimum pH being 4.0–5.0 and the optimum temperature being 40 °C–50 °C. Apart from standard substrates, two synthetic substrates (5-bromo-4-chloro-3-indolyl-N-acetyl-β-D-galactoside and 2-chloro-4-nitrophenyl-β-D-galactopyranoside) were tested and successfully hydrolyzed using β-N-acetylhexosaminidase preparations. Maximum activity toward the fluorogenic substrate 4-methylumbelliferyl-N-acetyl-β-D-galactopyranoside (4MU-β-GalNAc) was observed for enzyme preparations from PcHex1 (15.38 U/mg protein) isolated from swab samples of books in the Slovak National Museum in Martin (Slovak Republic) and stored in our laboratory. The same enzyme preparation was used for the selective hydrolysis of β-anomer of 4MU-GalNAc from an anomeric mixture of 4MU-α/β-GalNAc. Thus, pure α-anomer (with the total yield being 90%) was separated from the mixture, which suggests the application potential of these enzymes.
LUCC Simulation Based on RF-CNN-LSTM-CA Model with High-Quality Seed Selection Iterative Algorithm
Authors: Liu Minghao , Chen Haiyan , Qi Liai , Chen Chun
Published: March 2023

Land use/cover change (LUCC) models are essential for studying the profound impact of land use/cover dynamics on various aspects of the natural and social environment. Cellular Automata (CA) is widely used in the dynamic modeling of complex LUCC systems. In the traditional machine learning CA model, when using statistical methods to obtain neighborhood features, there is usually the problem that the spatio-temporal feature learning of neighborhood factors is insufficient. At the same time, the CA dynamic iteration module using the random seed selection mechanism often has the problem that the seed selection efficiency is very low. In this paper, taking the Chongqing Metropolitan Area as an example, convolutional neural networks (CNN)-Long Short-Term Memory Network (LSTM) is introduced to improve the learning effect of the traditional random forest (RF)-CA model in the spatial and temporal characteristics of neighborhood factors. CNN is used to extract the spatial dimension features of LUCC in the neighborhood, and the LSTM model is used to extract the time dimension features and long-term dependencies. At the same time, a high-quality seed selection iterative algorithm (HQSSIA) is used to improve the accuracy of the multi-land-use dynamic change model and the efficiency of the iterative algorithm. The results show that, the proposed model performs better than other models in simulating the LUCC from 2015 to 2020 (Kappa = 0.9684, FOM = 0.1744, Accuracy = 0.9829, F1 = 0.9641, Hamming = 0.0171) and from 2010 to 2020 (Kappa = 0.9599, FOM = 0.4662, Accuracy = 0.9785, F1 = 0.8113, Hamming = 0.0214). After introducing the CNN-LSTM model, the Figure of Merit (FOM) increased by 1.56% and 18.88% for 2015–2020 and 2010–2020. Compared with the CA model-based random seed selection algorithm, the FOM of the model using HQSSIA in the dynamic iteration module are improved by 11.60% and 24.79% for 2015–2020 and 2010–2020, and the operation efficiency of the dynamic iteration module is improved by about 19 times. Compared with the current mainstream LUCC models PLUS and FLUS, the proposed model has improved 14.38%, 37.55%, and 14.93%, 37.74% in FOM, respectively, for 2015–2020 and 2010–2020. The research shows that: (1) RF-CNN-LSTM-CA model not only retains the interpretability advantage of the traditional RF-CA model, but also improves the accuracy of the whole model by improving the spatio-temporal characteristics of neighborhood factors through in-depth learning; (2) the HQSSIA can quickly and accurately search for cells to be converted with higher conversion probability in the observed data, which can not only significantly reduce the time complexity of the model, but also improve the accuracy of LUCC simulation.
A Study on the Super Resolution Combining Spatial Attention and Channel Attention
Authors: Lee Dongwoo , Jang Kyeongseok , Cho Soo Young , Lee Seunghyun , Son Kwangchul
Published: March 2023

Existing CNN-based super resolution methods have low emphasis on high-frequency features, resulting in poor performance for contours and textures. To solve this problem, this paper proposes single image super resolution using an attention mechanism that emphasizes high-frequency features and a feature extraction process with different depths. In order to emphasize the high-frequency features of the channel and space, it is composed of CSBlock that combines channel attention and spatial attention. Attention block using 10 CSBlocks was used for high-frequency feature extraction. In order to extract various features with different degrees of feature emphasis from insufficient low-resolution features, features were extracted from structures connected with different numbers of attention blocks. The extracted features were expanded through sub-pixel convolution to create super resolution images, and learning was performed through L1 loss. Compared to the existing deep learning method, it showed improved results in several high-frequency features such as small object outlines and line patterns. In PSNR and SSIM, it showed about 11% to 26% improvement over the existing Bicubic interpolation and about 1 to 2% improvement over VDSR and EDSR.
E-APTDetect: Early Advanced Persistent Threat Detection in Critical Infrastructures with Dynamic Attestation
Authors: Genge Béla , Haller Piroska , Roman Adrian-Silviu
Published: March 2023

Advanced Persistent Threats (APTs) represent a complex series of techniques directed against a particular organization, where the perpetrator is able to hide its presence for a longer period of time (e.g., months, years). Previous such attacks have demonstrated the exceptional impact that a cyber attack may have on the operation of Supervisory Control And Data Acquisition Systems (SCADA), and, more specifically, on the underlying physical process. Existing techniques for the detection of APTs focus on aggregating results originating from a collection of anomaly detection agents. However, such approaches may require an extensive time period in case the process is in a steady-state. Conversely, this paper documents E-APTDetect, an approach that uses dynamic attestation and multi-level data fusion for the early detection of APTs. The methodology leverages sensitivity analysis and Dempster-Shafer’s Theory of Evidence as its building blocks. Extensive experiments are performed on a realistic Vinyl Acetate Monomer (VAM) process model. The model contains standard chemical unit operations and typical industrial characteristics, which make it suitable for a large variety of experiments. The experimental results conducted on the VAM process demonstrate E-APTDetect’s ability to efficiently detect APTs, but also highlight key aspects related to the attacker’s advantage. The experiments also highlight that the adversary’s advantage is affected by two major factors: the number of compromised components; and, the precision of manipulation.
The Importance of Conceptualising the Human-Centric Approach in Maintaining and Promoting Cybersecurity-Hygiene in Healthcare 4.0
Authors: Kioskli Kitty , Fotis Theofanis , Nifakos Sokratis , Mouratidis Haralambos
Published: March 2023

The cyberspace depicts an increasing number of difficulties related to security, especially in healthcare. This is evident from how vulnerable critical infrastructures are to cyberattacks and are unprotected against cybercrime. Users, ideally, should maintain a good level of cyber hygiene, via regular software updates and the development of unique passwords, as an effective way to become resilient to cyberattacks. Cyber security breaches are a top priority, and most users are aware that their behaviours may put them at risk; however, they are not educated to follow best practices, such as protecting their passwords. Mass cyber education may serve as a means to offset poor cyber security behaviours; however, mandatory education becomes a questionable point if the content is not focused on human factors, using human-centric approaches and taking into account end users’ behaviours, which is currently the case. The nature of the present paper is largely exploratory, and the purpose is two-fold: To present and explore the cyber hygiene definition, context and habits of end users in order to strengthen our understanding of users. Our paper reports the best practices that should be used by healthcare organisations and healthcare professionals to maintain good cyber hygiene and how these can be applied via a healthcare use case scenario to increase awareness related to data privacy and cybersecurity. This is an issue of great importance and urgency considering the rapid increase of cyberattacks in healthcare organisations, mainly due to human errors. Further to that, based on human-centric approaches, our long-term vision and future work involves facilitating the development of efficient practices and education associated with cybersecurity hygiene via a flexible, adaptable and practical framework.
Geometric Confinement of 3D Smectic Liquid Crystal Foams
Authors: Fu Changshuo , Dunn Meghann L. , Nere Rachel N. , Varon Weinryb Roy , Gharbi Mohamed Amine
Published: March 2023

Due to their long history and extensive applications within modern society, foams have always been a popular topic of study. These systems are present everywhere in our life. They are also valuable in many industrial applications. For this reason, it is essential to continue investigating their properties and develop new materials to fabricate them. In this paper, we demonstrate a new way to create 3D foams by using an ordered viscoelastic material, the smectic liquid crystal (LC). Because of their lamellar structure, which is similar to soap, and their tunable properties that can be controlled via geometric confinement and external fields, smectic LCs are suitable for the fabrication of bubbles and foams. In this work, we present a compelling study of the parameters that influence the fabrication of LC foams in 3D. Particularly, we analyze the effects of the airflow rate and the geometry of confining boundaries on the assembly of their cells. We also compare our results to foams made with sodium dodecyl sulfate (SDS) and discuss the difference between their behaviors. Finally, we discuss how LC elasticity can substantially affect the stability and organization of foams. This work paves the way to exploiting new materials to fabricate foams with better monodispersity, uniformity, and controlled ordering that are useful in a wide range of industrial applications for which the tuning of properties is required. This includes the fields of oil recovery, decontamination, architecture, and design.
Overlap in Automatic Root Cause Analysis in Manufacturing: An Information Theory-Based Approach
Authors: e Oliveira Eduardo , Miguéis Vera L. , Borges José L.
Published: March 2023

Automatic Root Cause Analysis solutions aid analysts in finding problems’ root causes by using automatic data analysis. When trying to locate the root cause of a problem in a manufacturing process, an issue-denominated overlap can occur. Overlap can impede automated diagnosis using algorithms, as the data make it impossible to discern the influence of each machine on the quality of products. This paper proposes a new measure of overlap based on an information theory concept called Positive Mutual Information. This new measure allows for a more detailed analysis. A new approach is developed for automatically finding the root causes of problems when overlap occurs. A visualization that depicts overlapped locations is also proposed to ease practitioners’ analysis. The proposed solution is validated in simulated and real case-study data. Compared to previous solutions, the proposed approach improves the capacity to pinpoint a problem’s root causes.
A Comparison of Surface Deformation Measurement Methods for Slopes
Authors: Song Chung R. , Wood Richard L. , Bekele Binyam , Glennie Nikolas , Silvey Alex , Nasimi Mitra
Published: March 2023

This study aimed to promote an efficient and reliable collection of deformation data for earthen slopes by comparing the Total Station (TS), Distributed Strain Sensing (DSS), and Uncrewed Aerial System (UAS)-based deformation measurement methods. The TS-based method was a two-person task with a longstanding “tried and true” reputation, and it provided acceptable results. However, it included a major portion of manual work in the field, potentially consuming extended time to obtain high-resolution data. The DSS-based method was a fiber optic cable-based one-person work, and it showed substantially faster and easier measurement. This method possessed the capability of collecting unattended measurements. The method also required anchor posts to measure deformation in segmented sections; some anchor posts became loose from shrinkage cracks and resulted in invalid measurements, particularly for soils of high plasticity. The UAS-based method was an aerial photogrammetric method. It provided an extremely high-resolution deformation profile but required a manual survey for an elevation check at reference points, although the surveying took a short amount of time by utilizing a Global Navigational Satellite Survey (GNSS) technique. This method required one operator and an assistant. From a comparison of the characteristics of the three different methods, it was found that each technique has its pros and cons, and the combination of different methods may greatly enhance the accuracy and convenience of the measurement.
The Impact of Clay Minerals on the Porosity Distribution of Clastic Reservoirs: A Case Study from the Labuan Island, Malaysia
Authors: Risha Muhammad , Tsegab Haylay , Rahmani Omeid , Douraghi Jalal
Published: March 2023

Clay mineral content and diagenetic processes are vital factors that affect reservoir quality, especially in tight clastic reservoirs, which are crucial for industrial and scientific purposes. The presence of clay minerals poses one of the most significant challenges in evaluating sandstone reservoirs’ quality. Even though wireline logs may provide a good indication of the reservoir quality, there have been cases where they have failed. This work focuses on the clay minerals’ impact on the porosity and permeability of a clastic reservoir. Typical outcrops from Labuan Island, Brunei–Sabah Basin, were chosen as a case study to investigate the petrophysical and petrographic parameters together with clay mineralogy profiling. The effects of the clays on the petrophysical parameters of the sandstone reservoir were evaluated through air permeability, spectral gamma ray measurements, a petrographic thin section analysis, a visual porosity estimation, and a grain size analysis. Field and petrographic studies revealed that Belait and Temburong formations contain massive, interbedded, laminated, and cross-bedded sandstones. Using an image analysis of the thin sections, porosity values ranged from 7.3% to 23.5%, with different macro and micro porosity distributions. According to the spectral gamma-ray investigation and air permeability, permeability reduction is strongly associated with clay minerals. The microporosity and permeability of the analyzed samples showed a unique pattern influenced by the grain size distribution. It was found that the textures dominated by mud grain size had a more significant impact on the air permeability and visual porosity, with coefficient of determination values of 0.83 and 0.70, respectively. The Belait Formation displayed a higher porosity and permeability compared to the Temburong Formation. This research provides new insight into the potential reservoir of Stage IV (the Belait Formation offshore equivalent) compared to Stage II (the Temburong Formation offshore equivalent).
Investigation of Tearing Modes on the Spherical Tokamak Globus-M2 Using the Doppler Backscattering Method
Authors: Yashin Alexander , Ponomarenko Anna , Balachenkov Ivan , Kurskiev Gleb , Kiselev Evgenii , Minaev Vladimir , Petrov Alexander , Petrov Yury , Sakharov Nikolay , Zhiltsov Nikita
Published: March 2023

In this study, we observed magnetohydrodynamic (MHD) activity of the spherical tokamak Globus-M2 which led to a deterioration in plasma confinement, such as a transition from the H-mode to L-mode, or even disruption. This instability was found to be tearing modes, which are a result of the formation of magnetic islands in plasma and which impose limits on plasma pressure. The width and velocity of the islands are key parameters that determine their impact on plasma confinement. The Doppler backscattering (DBS) method has been shown to be effective for the study of MHD activity. This method was employed on the spherical tokamak Globus-M2, together with an array of magnetic probes, to study the tearing modes. The available DBS systems allowed for simultaneous measurements from half of the minor radius to the separatrix. The results are presented of our investigation of tearing modes that lead to a transition from the H-mode or a disruption. Comparative analysis was conducted of the observed tearing modes and the influence of different plasma parameters on their development.
Identification of Surveillance Procedures for Diseases and Deaths Potentially Caused by Air Pollution and Possible Solutions as a Proposal for a Binational Surveillance System: A Case Study of Mexicali B.C., México-Imperial Valley, United States
Authors: Reyna Marco A. , Cuevas-González Daniel , Avitia Roberto L. , Nieblas Efrain C. , Mérida Juan V. , Nava Martha L.
Published: March 2023

In this paper, an integrative analysis is conducted for both sides of the border of Mexicali B.C. and Imperial Valley, regarding the official procedures and ways in which the collection, organization and disposal of data is carried out for the following: pollutant molecules such as PM2.5, PM10, CO, and O3; meteorological data such as temperature and relative humidity; data produced by epidemiological surveillance of acute respiratory infections; and deaths from all causes minus external ones. Some points around the binational surveillance system, raised in a technical report, are collected, giving continuity to the previous work carried out on this matter. Challenges are identified, recommendations are made, and possible solutions are offered to achieve a binational, unified and integrative system that centralizes meteorological, clinical, and pollution data, and that guarantees the quality and expeditious availability of the data concerning of the effects of air pollution on respiratory diseases and/or natural deaths of the local population. According to our results, air monitoring in Mexicali, clinical data on acute respiratory infections, morbidity, and mortality records must be improved, as well as the cooperation and coordination with the institutions of Imperial Valley. Finally, we show that despite the deficiencies and limitations found in the data generated in the locality, especially data on pollution and clinical data, it is possible, with great effort, to build models that measure and explain the effects of air pollution on health. Examples include the relative risk of death from exposure to PM2.5, PM10, CO, and O3; particulate matter air pollution effects on activation of pulmonary tuberculosis; the association between personal PM10 exposure and pulmonary function; and the estimation of costs and public health benefits by PM10 mitigation, among others.
Global Navigation Satellite System-Based Retrieval of Precipitable Water Vapor and Its Relationship with Rainfall and Drought in Qinghai, China
Authors: Zhang Shengpeng , Liu Fenggui , Li Hongying , Zhou Qiang , Chen Qiong , Ma Weidong , Luo Jing , Huang Yongsheng
Published: March 2023

Qinghai Province is situated deep in inland China, on the Qinghai-Tibet plateau, and it has unique climate change characteristics. Therefore, understanding the temporal and spatial distributions of water vapor in this region can be of great significance. The present study applied global navigation satellite system (GNSS) technology to retrieve precipitable water vapor (PWV) in Qinghai and analyzed its relationship with rainfall and drought. Firstly, radiosonde (RS) data is used to verify the precision of the surface pressure (P) and temperature (T) from the fifth-generation atmosphere reanalysis data set (ERA5) of the European Centre for Medium-Range Weather Forecasts (ECMWF), as well as the zenith troposphere delay (ZTD), calculated based on the data from continuously operating reference stations (CORS) in Qinghai. Secondly, a regional atmospheric weighted mean temperature (Tm) (QH-Tm) model was developed for Qinghai based on P, T, and relative humidity, as well as the consideration of the influence of seasonal changes in Tm. Finally, the PWV of each CORS in Qinghai was calculated using the GNSS-derived ZTD and ERA5-derived meteorological data, and its relationship with rainfall and drought was evaluated. The results show that the ERA5-derived P and T have high precision, and their average root mean square (RMS), mean absolute error (MAE) and bias were 1.06/0.85/0.01 hPa and 2.98/2.42/0.03 K, respectively. The RMS, MAE and bias of GNSS-derived ZTD were 13.2 mm, 10.3 mm and −1.8 mm, respectively. The theoretical error for PWV was 1.98 mm; compared with that of RS- and ERA5-derived PWV, the actual error was 2.69 mm and 2.16 mm, respectively. In addition, the changing trend of GNSS-derived PWV was consistent with that of rainfall events, and it closely and negatively correlated with the standardized precipitation evapotranspiration index. Therefore, the PWV retrieved from GNSS data in this study offers high precision and good feasibility for practical applications; thus, it can serve as a crucial tool for investigating water vapor distribution and climate change in Qinghai.
Dynamic Response of Atmospheric and Ocean Parameters and Their Relation to Typhoon Haikui (2012) Using Satellite Data
Authors: Zhu Wangyuan , Subrahmanyam Mantravadi Venkata , Wang Liuzhu , Guo Biyun
Published: March 2023

Typhoon Haikui (2012) occurred in the northwestern Pacific Ocean, and landfall on the east coast of China brought heavy rainfall with strong winds. Because of Typhoon Haikui, sea surface temperature (SST) cooling of 3 °C occurred on the right side of the track, mainly due to Ekman transport and upwelling. SST cooling on the left side was lower than on the right side, mainly due to the rainfall. Heavy precipitation occurred on both sides of the typhoon track; however, rainfall was higher on the left side of the typhoon track. This paper explains the dynamic process between atmospheric and oceanographic parameters and verifies the variations in chlorophyll and sea surface height data before, during, and after the typhoon. Typhoon Haikui demonstrates dynamic variations and intuitively illustrates the relationship between the ocean and atmospheric parameters.