bluuebunny/crossref_metadata_2025 huggingface dataset:
Macro-economic determinants, maternal and infant SDG targets in Nigeria: Correlation and predictive modeling
Authors: Adegoke Yetunde Oluranti , Mbonigaba Josue , George Gavin
Published: December 2022

Objectives

Unambiguously, Nigeria is off-track in achieving the health-related SDGs. Consequentially, this study aligns with SDG 3 which calls for “good health and wellbeing for people by ensuring healthy lives and promoting wellbeing for all at all ages”. This article examines the combined effect of health expenditure and other key macro-economic factors on health indices such as maternal and newborn and child mortality in Nigeria. Contrary to existing literature, we formulated a model that predicts the level of macro-economic determinants needed to achieve the SDG targets for maternal and newborn and child mortality in Nigeria by 2030.

Methodology

The study used Autoregressive Distributed Lag (ARDL), which is usually used for large T models. The study period spans from 1995 to 2020.

Results

We found a significant negative relationship between health outcomes and macro-economic determinants namely, household consumption, total health expenditure, and gross fixed capital while we determined a significant positive relationship between health outcomes and unemployment. Our findings are further supported by out-of-sample forecast results suggesting a reduction in unemployment to 1.84 percent and an increase in health expenditure, gross fixed capital, household consumption, control of corruption to 1,818.87 billon (naira), 94.46 billion (naira), 3.2 percent, and −4.2 percent respectively to achieve SDG health targets in Nigeria by 2030.

Policy implication

The outcome of this result will give the Nigerian government and stakeholders a deeper understanding of the workings of the macro-economic factors, concerning health performance and will help position Nigeria, and other SSA countries by extension, toward reducing maternal mortality to 70 per 100,000 and newborn and child mortality to 25 per 1,000 births by 2030. The African leaders should consider passing into law the need for improvement in macro-economic factors for better health in Africa. We also recommend that the Nigerian government should steadily increase health expenditure to reach and move beyond the forecast level for improvement in maternal and infant mortality, given the present low and unimpressive funding for the health sector in the country.
Genome-wide association studies of viral infections—A short guide to a successful experimental and statistical analysis
Authors: Butković Anamarija , Elena Santiago F.
Published: December 2022

Genome-wide association studies (GWAS) have been gaining popularity over the last decade as they provide new insights into the genetic architecture of many disease-related traits. GWAS is based on the common disease common variant hypothesis, allowing identification of alleles associated with susceptibility and symptomatology of most common infectious diseases, such as AIDS, common cold, flu, and many others. It depends on the natural variation in a host population which can help identify genetic variants responsible for virus disease-related traits. Considering the prevalence of viruses in the ecosystem and their societal burden, identification of potential resistance loci or therapeutic targets is of great interest. Here, we highlight the most important points necessary for a successful GWAS of viral infectious diseases, focusing on the study design and various statistical methods used. Finally, we exemplify this application with studies done with human immunodeficiency virus type 1 and turnip mosaic virus.
Research and Experiments of Hazelnut Harvesting Machine Based on CFD-DEM Analysis
Authors: Ren Dezhi , Yu Haolin , Zhang Ren , Li Jiaqi , Zhao Yingbo , Liu Fengbo , Zhang Jinhui , Wang Wei
Published: December 2022

To solve the problem of difficult hazelnut harvesting in mountainous areas of Liaoning, China, a small pneumatic hazelnut harvesting machine was designed, which can realize negative pressure when picking up hazelnut mixtures and positive pressure when cleaning impurities. The key structure and parameters of the harvesting machine were determined by constructing a mechanical model of the whole machine and combining theoretical analysis and operational requirements. To explore the harvesting machine scavenging performance, Liaoning hazelnut No. 3 with a moisture content of 7.47% was used as the experimental object. Firstly, the terminal velocity of hazelnuts and fallen leaves was measured using a material suspension velocity test bench. Secondly, the gas–solid two-phase flow theory was applied comprehensively, and the motion state, particle distribution, and air flow field distribution of hazelnuts from the inlet to the outlet of the pneumatic conveying device were simulated and analyzed using the coupling of computational flow fluid dynamics method (CFD) and discrete element method (DEM) to evaluate the cleaning performance from the perspective of the net fruit rate of hazelnuts in the cleaning box. Finally, a Box–Behnken design experiment was conducted with the sieve plate angle, the distance of the sieve plate, and the air flow velocity as factors and the net fruit rate of hazelnuts as indicators to explore the influence of the three factors on the net fruit rate of hazelnuts. The parameter optimization module of Design-Expert software was used to obtain the optimal combination of parameters for the factors. The experimental results show that the test factors affecting the test index are the following: the air flow rate, the angle of the screen plate, and the distance of the screen plate. The best combination of parameters was an air flow velocity of 14.1 m∙s−1, a sieve plate angle of 55.7°, and a distance of the sieve plate of 33.2 mm. The net fruit rate of hazelnuts was 95.12%. The clearing performance was stable and can guarantee the requirements of hazelnut harvester operation, which provides a certain theoretical basis for the design of a nut harvester.
Assessing Drought, Flood, and High Temperature Disasters during Sugarcane Growth Stages in Southern China
Authors: Yao Pei , Qian Long , Wang Zhaolin , Meng Huayue , Ju Xueliang
Published: December 2022

As a globally important sugarcane-producing region, Southern China (SC) is severely affected by various agrometeorological disasters. This study aimed to comprehensively assess multiple sugarcane agrometeorological disasters with regards to sugarcane yield in SC. The standardized precipitation evapotranspiration index and the heat degree-days were employed to characterize drought, flood, and high temperature (HT) during sugarcane growth stages in three provinces in SC in the period 1970–2020. Moreover, the relationships between sugarcane climatic yield and disaster intensities were investigated. The results indicated that the most recent decade witnessed the most intensive sugarcane agrometeorological disasters; sugarcane drought and HT intensities significantly (p < 0.05) increased in one and two provinces, respectively. Central and western SC was most drought-prone, while eastern SC was most flood-prone; sugarcane HT was concentrated in southwestern SC. The mature stage exhibited the greatest monthly intensities of drought and flood; the most HT-prone growth stage varied with provinces. The relationships between drought/flood intensity and sugarcane climatic yield were significant in seven districts; the yield-reducing effect of sugarcane flood was more obvious than that of drought. In conclusion, this study provides references for agrometeorological disaster risk reduction for sugarcane in SC.
Parameter Optimization of Reciprocating Cutter for Chinese Little Greens Based on Finite Element Simulation and Experiment
Authors: Wang Wei , Lv Xiaolan , Yi Zhongyi
Published: December 2022

Optimizing the working performance of the cutting device for harvesting Chinese little greens is crucial to reducing energy consumption in cutting and improving cutting quality. To explore the mechanical characteristics of leafy vegetables in cutting, the dynamic process of cutting Chinese little greens with a cutter was simulated numerically by using the finite element method based on theoretical analysis. In the numerical simulation, the response-surface methodology (RSM) and central composite rotatable design (CCD) were used to describe the influence rule of sliding–cutting angle (X1), oblique angle (X2), and the average cutting speed (X3) on cutting stress. Then, the stress distribution pattern produced by the cutting blade and the stalks were evaluated by using different working parameters. Subsequently, taking the minimum cutting stress as the target value, the best combination of cutter structure and working parameters were obtained: the sliding–cutting angle was 29°, the oblique angle was 38°, and the average cutting speed was 500 mm/s. At the condition of optimal parameter combinations, the ultimate cutting stress of the upper cutting blade was 0.95 Mpa and that of the bottom cutting blade was 0.77 Mpa. A cutting test was carried out by using a bench test of the cutting performance, and the mechanical properties of cutting at different cutting speeds were studied. Test results showed that at the optimal cutting speed of 500 mm/s, the cutting stress on the cutter was relatively small and the cutting effect reached the best value. The finite element simulation of cutting the little greens reduced the test cost and provided a reference for the development of a cutting device with low power consumption.
Paradigm and Framework of WUS-CLV Feedback Loop in Stem Cell Niche for SAM Maintenance and Cell Identity Transition
Authors: Agarwal Yamini , Shukla Bhavya , Manivannan Abinaya , Soundararajan Prabhakaran
Published: December 2022

Shoot apical meristem (SAM) consists of stem cells that act as a reservoir for the aerial growth. It plays an important role in the differential architectural development in plants. SAM actively performs parallel functions by maintaining the pluripotent of stem cells and continuous organogenesis throughout the plant’s life cycle. Molecular mechanisms regulating the signaling networks of this dual function of the SAM have been progressively understood. In the SAM, the feedback loop of WUSCHEL (WUS)-CLAVATA (CLV) has been found to be the key regulator in stabilizing stem cell proliferation and differentiation. In general, WUS migrates into central zone (CZ) from organizing center (OC) and activates the expression of CLV3 by binding to the promoter elements. CLV3 acts as a ligand to interact with the CLV1, leucine rich repeats (LRR) receptor-like kinase (RLK) and LRR receptor-like protein CLV2, and protein kinase coryne (CRN) (CLV2/CRN) to restrict WUS transcription to the OC. Evolution of CLV3 is one of the main factors contributing to the transformation of two-dimensional (2D) to 3D plants. WUS-CLV loop is involved in several pathways and networks that integrate on meristem maintenance and cell identity transition. WUS-CLV maintains stem cells with simultaneous differentiation signals by the spatial-temporal signaling of the phytohormones. WUS-CLV loop has an interaction with reactive oxygen species (ROS), an important signaling molecules regulating cell proliferation and developmental transition. WUS also forms feedback loop with AGAMOUS (AG) for differentiation, proliferation, and termination of floral meristem. These loops might also involve in interaction with vernalization and its regulatory factors that oversees the precise timing of flowering after exposure to cold temperatures. In this review, we highlight the evolutionary and developmental importance of the WUS-CLV feedback loop on SAM maintenance and cell identity transition for inflorescence and floral meristem development.
Genetic Resistance of Switchgrass to Rust Evaluated in a Composite Upland × Lowland Population in Lab and Field Settings
Authors: Edmé Serge J. , Palmer Nathan A. , Sarath Gautam , Muhle Anthony A. , Mitchell Rob , Yuen Gary
Published: December 2022

Maintaining low levels of rust incidence (caused by Puccinia novopanici) in switchgrass (Panicum virgatum L.) breeding populations is a priority for the USDA-ARS program engaged in improving cultivars for high biomass yield and quality. Essential to this goal is the unbiased and accurate estimation of genetic parameters to predict the merits of parents and progeny. Spores of the fungus were inoculated in greenhouse-grown seedling progeny of 31 half-sib families in generation 2 (Gen 2) of a composite Summer × Kanlow population for evaluation of rust incidence on the leaves with a 0–9 rating scale. Two parents were later chosen to cross and develop a linkage mapping population as Gen 3. The Gen 2, 3, and Kanlow seedlings were transplanted into the field located near Mead, NE, in early June 2020 and laid out as a replicated row–column design with six blocks of single-row plots of five plants each. The field trial was rated in September 2021 and 2022 with a 0–4 scale. Lab and field data were subjected to univariate linear mixed models via the restricted maximum likelihood to extract the variance components needed to predict the breeding values. The additive genetic variation was substantial (p < 0.01), enough to result in high heritability estimates ranging from 0.42 ± 14 to 0.73 ± 0.09 at the individual and family mean levels. This result implies that rust resistance is under strong genetic control to use mass selection for obtaining satisfactory gains. A possible rust incidence x year interaction was detected with a Spearman correlation of breeding values of −0.38, caused by significant rank changes of the Gen 3 genotypes in 2022 (a high heat and drought year). Genetic gains were predicted to reduce rust incidence scores by at least two points on the rating scale when selecting backwards, and by one point when selecting individual candidates as parents of the next generation. Faster gains (31 and 59%) were realized relative to the second generation by respectively selecting the top 10% of the families in Gen 3 or the top 10% of genotypes within this group. Based on these results, strategies for controlling the incidence of rust will be developed to optimize gains in the other traits of economic importance.
Mitigating against Sclerotinia Diseases in Legume Crops: A Comprehensive Review
Authors: Antwi-Boasiako Augustine , Wang Yu , Dapaah Harrison Kwame , Zhao Tuanjie
Published: December 2022

Legumes are essential foods for man and animal. They contribute to food security globally. However, they are negatively affected by Sclerotinia diseases caused by Sclerotinia sclerotiorum, which infects over 600 plant species. There is a limited number of review studies on the management of the Sclerotinia sclerotiorum disease in legume crops. Here, we explore earlier studies on the occurrences, yield losses, and other negative effects caused by Sclerotinia spp. in legumes. Additionally, we studied the various strategies used in controlling Sclerotinia sclerotiorum diseases in legume crops. We conclude that the impact of Sclerotinia diseases on legume crops causes an economic loss, as it reduces their quality and yield. Among the management strategies explored, genetic control is challenging due to the limited resistance among germplasm, while biological agents show promising results. Fungicide application is effective during outbreaks of Sclerotinia diseases. Lastly, this review has uncovered gaps in the current knowledge regarding the alleviation of Sclerotinia diseases in legume crops.
Laboratory and Field Trials to Identify Reduced-Risk Insecticides for the Control of the Golden Twin-Spot Moth Chrysodeixis chalcites (Esper) (Lepidoptera: Noctuidae) in Banana Plantations
Authors: Cakmak Taylan , Hernández-Suárez Estrella , Kaydan Mehmet Bora , Tange Denis Achiri , Perera Santiago , Piedra-Buena Díaz Ana
Published: December 2022

The golden twin-spot moth (Chrysodeixis chalcites) is one of the most important pests in banana production on the Canary Islands (Spain). The efficacy of different biorational insecticides based on bioenzyme complexes (Intruder®), plant extracts: Rutaceae and Piperaceae (Avenger®), Rutaceae and Lauraceae (BioKnock®), cinnamon, citronella, and Menta (Cinamite®), Alliaceae and Solanacea (Garlitrol-Forte®), citrus (Prevam®), and neem oil (Indasol®) was assessed against C. chalcites. Laboratory assays included: choice (repellent effect), no choice, and contact toxicity on C. chalcites 2nd instar larvae. The highest repellent effect was observed with Prevam® (85.19 ± 1.7%), followed by Garlitrol® (68.44 ± 5.7%) and Intruder® (67.54 ± 4.3%). In no choice assays, Prevam® (0.92 ± 0.4%), Indasol® (0.98 ± 0.33%), and Intruder® (2.7 ± 0.33%) had the lowest leaf consumption. The contact toxicity assays showed the highest mortality with Intruder® both at 1 day and 7 days post-application (20.22 ± 2.98% and 77.77 ± 5.7%, respectively). In the screenhouse trial, the best results for C. chalcites larvae mortality, fruit damage, and fruit classification in quality categories 7 days after application of the bioinsecticide were obtained with Intruder®, Prevam®, and Indasol®. An economic analysis of biorational treatments was also performed. The results of this study provide successful alternatives to chemical pesticides for the control of C. chalcites on banana plants in the Canary Islands.
Greater Horseshoe Bats Recognize the Sex and Individual Identity of Conspecifics from Their Echolocation Calls
Authors: Tan Xiao , Lin Aiqing , Sun Keping , Jin Longru , Feng Jiang
Published: December 2022

The echolocation calls of bats are mainly used for navigation and foraging; however, they may also contain social information about the emitter and facilitate social interactions. In this study, we recorded the echolocation calls of greater horseshoe bats (Rhinolophus ferrumequinum) and analyzed the acoustic parameter differences between the sexes and among individuals. Then, we performed habituation-discrimination playback experiments to test whether greater horseshoe bats could recognize the sex and individual identity of conspecifics from their echolocation calls. The results showed that there were significant differences in the echolocation call parameters between sexes and among individuals. When we switched playback files from a habituated stimuli to a dishabituated stimuli, the tested bats exhibited obvious behavioral responses, including nodding, ear or body movement, and echolocation emission. The results showed that R. ferrumequinum can recognize the sex and individual identity of conspecifics from their echolocation calls alone, which indicates that the echolocation calls of R. ferrumequinum may have potential communication functions. The results of this study improve our understanding of the communication function of the echolocation calls of bats.
The Aleutians and Beyond: Distribution, Size Composition, and Catch Dynamics of the Aleutian Skate Bathyraja aleutica across the North Pacific
Authors: Grigorov Igor V. , Kivva Kirill K. , Orlov Alexei M.
Published: December 2022

The results of long-term (1948–2021) studies on the spatial and vertical distribution, dynamics of abundance, and size composition of the Aleutian skate Bathyraja aleutica in the North Pacific Ocean are presented. Maximum densities of this species were characteristic of the eastern Bering Sea slope, off the central Aleutian Islands, consisting of the Pacific waters off southeastern Kamchatka and the northern Kurils, and northeastern Sakhalin. This species was most abundant at depths of 100–600 m; in the cold months, B. aleutica migrates to greater depths for over-wintering, and in warm months it feeds at shallower depths. Bathyraja aleutica was most common at the bottom, at temperatures around 3 °C. The total length of individuals ranged from 9.6–170 cm, with a predominance of skates with a length of 50–100 cm. Males did not differ significantly from females in body weight and length. The maximum values of the condition factor were typical for the autumn–winter period. Across years, there was an increase in Aleutian skate catch rates from the western Bering Sea and the Sea of Okhotsk, and a decrease in the Pacific waters off the Kuril Islands and Kamchatka, as well as in Alaskan waters.
Combined Anti-Bacterial Actions of Lincomycin and Freshly Prepared Silver Nanoparticles: Overcoming the Resistance to Antibiotics and Enhancement of the Bioactivity
Authors: Abdul-Jabbar Amna M. , Hussian Nehia N. , Mohammed Hamdoon A. , Aljarbou Ahmed , Akhtar Naseem , Khan Riaz A.
Published: December 2022

Bacterial drug resistance to antibiotics is growing globally at unprecedented levels, and strategies to overcome treatment deficiencies are continuously developing. In our approach, we utilized metal nanoparticles, silver nanoparticles (AgNPs), known for their wide spread and significant anti-bacterial actions, and the high-dose regimen of lincosamide antibiotic, lincomycin, to demonstrate the efficacy of the combined delivery concept in combating the bacterial resistance. The anti-bacterial actions of the AgNPs and the lincomycin as single entities and as part of the combined mixture of the AgNPs–lincomycin showed improved anti-bacterial biological activity in the Bacillus cereus and Proteus mirabilis microorganisms in comparison to the AgNPs and lincomycin alone. The comparison of the anti-biofilm formation tendency, minimum bactericidal concentration (MBC), and minimum inhibitory concentration (MIC) suggested additive effects of the AgNPs and lincomycin combination co-delivery. The AgNPs’ MIC at 100 μg/mL and MBC at 100 μg/mL for both Bacillus cereus and Proteus mirabilis, respectively, together with the AgNPs–lincomycin mixture MIC at 100 + 12.5 μg/mL for Bacillus cereus and 50 + 12.5 μg/mL for Proteus mirabilis, confirmed the efficacy of the mixture. The growth curve test showed that the AgNPs required 90 min to kill both bacterial isolates. The freshly prepared and well-characterized AgNPs, important for the antioxidant activity levels of the AgNPs material, showed radical scavenging potential that increased with the increasing concentrations. The DPPH’s best activity concentration, 100 μg/mL, which is also the best concentration exhibiting the highest anti-bacterial zone inhibition, was chosen for evaluating the combined effects of the antibiotic, lincomycin, and the AgNPs. Plausible genotoxic effects and the roles of AgNPs were observed through decreased Bla gene expressions in the Bacillus cereus and BlaCTX-M-15 gene expressions in the Proteus mirabilis.
Bacteria and Boar Semen Storage: Progress and Challenges
Authors: Contreras María José , Núñez-Montero Kattia , Bruna Pablo , García Matías , Leal Karla , Barrientos Leticia , Weber Helga
Published: December 2022

Porcine breeding today is based on artificial insemination with chilled semen. This is stored at 5 °C with antibiotic supplementation to avoid bacteriospermia. There are many negative consequences on sperm quality and functionality as a result of bacterial contamination, as well as on the health of the sow. Nowadays, various techniques are being developed to reduce the indiscriminate use of antibiotics and thus avoid the generation of antibiotic resistance genes. This review aims to inform about the bacterial contamination consequences of storing liquid semen from boar and to provide an update on current methods and alternatives to antibiotic use in cold storage.
Plasmid-Coded Linezolid Resistance in Methicillin-Resistant Staphylococcus aureus from Food and Livestock in Germany
Authors: Lienen Tobias , Grobbel Mirjam , Tenhagen Bernd-Alois , Maurischat Sven
Published: December 2022

Resistance of methicillin-resistant Staphylococcus aureus (MRSA) from food and livestock to last resort antibiotics such as linezolid is highly concerning, since treatment options for infections in humans might be diminished. Known mechanisms of linezolid resistance include point mutations in the 23S rRNA gene and in the ribosomal proteins L3, L4 and L22 as well as an acquisition of the cfr, optrA or poxtA gene. The objective of our study was to characterize antimicrobial resistance (AMR) determinants and phylogenetic relationships among linezolid-resistant (LR-) MRSA from food and livestock. In total, from more than 4000 incoming isolates in the years 2012 to 2021, only two strains from 2015 originating from pig samples exhibited linezolid resistance in the antimicrobial susceptibility testing with MICs of ≥8 mg/L. These LR-MRSA were characterized in detail by whole-genome sequencing and phylogenetic analyses using cgMLST. The LR-MRSA strains showed resistances to ten and eight different antibiotics, respectively. Both strains harbored plasmid-coded cfr genes mediating the linezolid resistance. The cfr genes showed identical sequences in both strains. In addition to the cfr gene, genes for phenicol and clindamycin resistance were detected on the respective plasmids, opening the possibility for a co-selection. The LR-MRSA differed distantly in the phylogenetic analyses and also to other MRSA from pig samples in the year 2015. In conclusion, the occurrence of LR-MRSA in food and livestock seems to be very rare in Germany. However, carriage of plasmids with linezolid resistance determinants could lead to further linezolid-resistant strains by horizontal gene transfer.
Ensemble Clustering in GPS Velocities: A Case Study of Turkey
Authors: Kılıç Batuhan , Özarpacı Seda
Published: December 2022

Block modeling is an effective way to understand Earth’s crustal deformation. However, the choice of block boundaries and the number of blocks affect the model results. Therefore, the subjectivity of this analysis should be avoided. Clustering analysis can be used to define the blocks of GPS (Global Positioning System) velocity fields without a priori information. Unfortunately, clustering methods also have unique solutions and differ with various algorithms. Ensemble methods could be an answer to enhance the clustering results for GPS velocities. In this study, we use ensemble clustering to identify block boundaries before block modeling without a priori information about the data. The ensemble clustering method is used for the first time in the clustering of GPS velocities and the case of Turkey is discussed. The published horizontal GPS velocities were first clustered with five different clustering methods and the optimum classes were determined using ensemble clustering methods. It is proven that the Meta-CLustering Algorithm can be used in terms of ensemble clustering for this region.
Experimental and Theoretical Investigations of Argania spinosa’s Extracts on the Antioxidant Activity and Mild Steel Corrosion’s Inhibition in 1 M HCl
Authors: Laaroussi Hamid , Aouniti Abdelouahad , Mokhtari Ouafae , Hafez Baraa , Sheikh Ryan Adnan , Sameeh Manal Y. , Khowdiary Manal M. , Alderhami Suliman A. , Elhenawy Ahmed A. , Azzouzi Mohamed El , Rahhou Ilyesse , Belbachir Chaouki , Hammouti Belkheir , Hadda Taibi Ben , Elmsellem Hicham
Published: December 2022

The aim of the present research is the evaluation of the extraction process effect on the chemical composition, the antioxidant activities, and the mild steel corrosion inhibition ability of Argania spinosa’s extracts (alimentary oil (AO) and hexanic extract of roasted almonds (HERA)). The chemical composition revealed that both extracts have the same major compounds: Palmitic, linoleic, and stearic acids, with their order slightly different. Electrochemical impedance spectroscopy (EIS), weight loss measurements, and polarization curves were used to estimate AO and HERA’s mild steel corrosion’s inhibition capacity. Based on these three methods, AO registered, respectively, 81%, 87%, and 87% inhibition efficiency while HERA registered 78%, 84%, and 82% inhibition efficiency. The antioxidant activity of AO and HERA was examined in parallel with standard antioxidants (gallic acid and quercetin) using two assays: DPPH* scavenging assay and ferric reducing antioxidant power assay (FRAP). AO had less EC50 in both techniques (DPPH*: 3559.08 ± 161.75 μg/mL; FRAP 1288.58 ± 169.21 μg/mL) than HERA (DPPH*: 3621.43 ± 316.05 μg/mL; FRAP 1655.86 ± 240.18 μg/mL). Quantum chemical and molecular dynamic studies were employed to suggest the adsorption mechanism.
Enhancing Semantic-Consistent Features and Transforming Discriminative Features for Generalized Zero-Shot Classifications
Authors: Yang Guan , Han Ayou , Liu Xiaoming , Liu Yang , Wei Tao , Zhang Zhiyuan
Published: December 2022

Generalized zero-shot learning (GZSL) aims to classify classes that do not appear during training. Recent state-of-the-art approaches rely on generative models, which use correlating semantic embeddings to synthesize unseen classes visual features; however, these approaches ignore the semantic and visual relevance, and visual features synthesized by generative models do not represent their semantics well. Although existing GZSL methods based on generative model disentanglement consider consistency between visual and semantic models, these methods consider semantic consistency only in the training phase and ignore semantic consistency in the feature synthesis and classification phases. The absence of such constraints may lead to an unrepresentative synthesized visual model with respect to semantics, and the visual and semantic features are not modally well aligned, thus causing the bias between visual and semantic features. Therefore, an approach for GZSL is proposed to enhance semantic-consistent features and discriminative features transformation (ESTD-GZSL). The proposed method can enhance semantic-consistent features at all stages of GZSL. A semantic decoder module is first added to the VAE to map synthetic and real features to the corresponding semantic embeddings. This regularization method allows synthesizing unseen classes for a more representative visual representation, and synthetic features can better represent their semantics. Then, the semantic-consistent features decomposed by the disentanglement module and the features output by the semantic decoder are transformed into enhanced semantic-consistent discriminative features and used in classification to reduce the ambiguity between categories. The experimental results show that our proposed method achieves more competitive results on four benchmark datasets (AWA2, CUB, FLO, and APY) of GZSL.
Cooperative Transmission Mechanism Based on Revenue Learning for Vehicular Networks
Authors: Chen Mingyang , Cui Haixia , Nie Mingsheng , Chen Qiuxian , Yang Shunan , Du Yongliang , Dai Feipeng
Published: December 2022

With the rapid development of science and technology and the improvement of people’s living standards, vehicles have gradually become the main means of travel. The increase in vehicles has also brought about an increasing incidence of car accidents. In order to reduce traffic accidents, many researchers have proposed the use of vehicular networks to quickly transmit information. As long as these vehicles can receive information from other vehicles or buildings nearby in a timely manner, they can avoid accidents. In vehicular networks, the traditional double connection technique, through interference coordination scheduling strategy based on graph theory, can ensure the fairness of vehicles and obtain suitable neighborhood interference resistance with limited computing resources. However, when a base station transmits data to the vehicular user, the nearby base station and the vehicular network user may be in a state of suspended communication. Thus, the resource utilization of the above double connection vehicular network is not sufficient, resulting in a waste of resources. To solve this issue, this paper presents a study based on earnings learning with a vehicular network multi-point collaborative transmission mechanism, in which the vehicular network users communicate with the surrounding collaborative transmission. We use the Q-learning algorithm in the reinforcement learning process to enable vehicular network users to learn from each other and make cooperative decisions in different environments. In reinforcement learning, the agent makes a decision and changes the state of the environment. Then, the environment feeds back the benefit to the agent through the related algorithm so that the agent gradually learns the optimal decision. Simulation results demonstrate the superiority of our proposed approach with the revenue machine learning model compared with the benchmark schemes.
Development of an ANN-Based Closed-Form Equation for the Prediction of Airblast Overpressure Induced by Construction Rock Excavation Blasting in Urban Areas
Authors: Ogunsola Nafiu Olanrewaju , Shin Chanhwi , Kim Young-Keun , Lawal Abiodun Ismail , Cho Sangho
Published: December 2022

Blasting has been proven to be the most cost-effective method for rock excavation known to man. The cost-effectiveness advantage of blasting is overshadowed by its unpleasant environmental problems, particularly at construction sites close to human settlements and public utilities. Therefore, efforts are required to develop closed-form equations that can accurately predict environmental problems associated with blasting. This study proposes an ANN-based closed-form explicit equation for forecasting airblast overpressure (AOp) at multiple construction sites in South Korea. Nine important factors that affect AOp generation were used to develop the model. First, a stand-alone ANN was initiated, and the hyperparameters of the optimum ANN structure were tuned using two novel and robust metaheuristic algorithms: the slime mould algorithm (SMA) and multi-verse optimization (MVO). To appraise the predictive accuracy of the developed soft computing models, multilinear regression (MLR) and a generalized empirical predictor were developed for comparison. The analysis showed that the SMA-ANN and MVO-ANN models predicted AOp with the highest accuracy compared with the other models. The two hybrid ANN-based models were transformed into closed-form and explicit equations to aid in the easy forecasting of AOp when planning a blasting round at construction sites. The developed model equations were validated for practical engineering applications and a comprehensive relative importance analysis of the AOp input parameters was performed. The relevance importance analysis shows that the rock mass rating (RMR), charge per delay (Q), and monitoring distance (DIS) have the highest impacts on AOp.
Road Safety Management of Uncontrolled Access Points: Design Criteria and Insights into Risk Factors
Authors: Perri Giusi , Vaiana Rosolino
Published: December 2022

This study provides a comprehensive approach to the management of uncontrolled accesses, namely, access points without traffic lights, stop signs, right-of-way, yield signs, or right-turn acceleration/deceleration lanes. These elements of the road network are often associated with several safety issues given the inadequate conditions and limitations regarding their location, design, and visibility. This paper provides new insights into the geometric and functional design of uncontrolled accesses and contributes to the area of safety management measures. The implementation of the approach to a selected case study allows for the description of the methodology and to find interesting results concerning the cause-effect relationship between geometry-related variables and accidental events. In particular, the study focuses attention on the key factors of the geometric and functional design of accesses: radius and width, with the aim of defining more adequate design criteria aimed at improving safety. Furthermore, several interesting considerations are drawn relating to the types of connection transition shapes, allowing the selection of the most dangerous type for the safety of drivers and pedestrians. The most important finding is the high risk correlated to an access point with no materialised elements guiding the entry manoeuvre.
Bacterial Cellulose Production by Komagateibacter xylinus with the Use of Enzyme-Degraded Oligo- and Polysaccharides as the Substrates
Authors: Przygrodzka Katarzyna , Charęza Magdalena , Banaszek Agnieszka , Zielińska Beata , Ekiert Ewa , Drozd Radosław
Published: December 2022

Bacterial cellulose (BC) is a unique biopolymer synthesised by many bacteria as a critical element of their biofilm matrix. The most known and efficient producers of BC are bacteria from the genus of Komagataeibacter. Bacterial cellulose, with its unique properties, high crystallinity, mechanical strength, and unprecedented ability to hold water, is an object of interest in many industries. Despite the enormous efforts that have been made to develop an effective process, the economic aspect of BC production is still a limiting factor for broadening applications, and new “breaking point” solutions are highly anticipated. In this study, the possibility of using sucrose, lactose, and starch as alternative carbon sources converted to simple sugars directly in the culture medium by microbial glycohydrolases, β-D-fructofuranosidase, β-galactosidase, and glucoamylase in the process of BC synthesis was analysed. The results showed the high potential of the enzyme-assisted fermentation process that, for most used raw carbons sources, was highly efficient, with a yield higher (i.e., lactose 40% more) or comparable to the cultures maintained on standard Hestrin-Schramm media with glucose as a sole carbon source. The X-ray diffraction, Fourier transform infrared spectroscopy, and scanning electron microscope analyses did not reveal any negative influence of enzyme-assisted cultivation on the BC material properties, such as crystallinity, swelling ratio, and moisture content. Applying specific enzymes for converting inaccessible, raw-form carbon sources to the culture medium of Komagateibacter xylinus opens a simple way to use various oligo- and polysaccharides acquired from many kinds of biomass sources in the BC production process.
Smartphone Use in Traffic: A Pilot Study on Pedestrian Behavior
Authors: Frej Damian , Jaśkiewicz Marek , Poliak Miloš , Zwierzewicz Zenon
Published: December 2022

Mobile phones accompany us in every area of life and at the same time keep us busy while performing other basic activities such as running, cycling, driving or walking in traffic. The problem of using cell phones while driving is of interest to many scientists around the world. This offense is severely punished in many countries. The problem of using mobile phones in moving vehicles has been largely resolved; however, there is a visible high percentage of pedestrians and cyclists who are used to checking their devices while moving in traffic. The aim of the article is to get acquainted with the issues of using mobile phones by pedestrians when crossing a pedestrian crossing and to escalate the problem. Despite the introduction of a ban on the use of mobile phones when crossing a pedestrian crossing in the Polish law on road traffic, many road users still use phones. The conducted observation shows that at least 2 out of 10 people pass through the pedestrian crossing with a mobile phone in their hand.
High-Accuracy Insulator Defect Detection for Overhead Transmission Lines Based on Improved YOLOv5
Authors: Huang Yourui , Jiang Lingya , Han Tao , Xu Shanyong , Liu Yuwen , Fu Jiahao
Published: December 2022

As a key component in overhead cables, insulators play an important role. However, in the process of insulator inspection, due to background interference, small fault area, limitations of manual detection, and other factors, detection is difficult, has low accuracy, and is prone to missed detection and false detection. To detect insulator defects more accurately, the insulator defect detection algorithm based on You Only Look Once version 5 (YOLOv5) is proposed. A backbone network was built with lightweight modules to reduce network computing overhead. The small-scale network detection layer was increased to improve the network for small target detection accuracy. A receptive field module was designed to replace the original spatial pyramid pooling (SPP) module so that the network can obtain feature information and improve network performance. Finally, experiments were carried out on the insulator image dataset. The experimental results show that the average accuracy of the algorithm is 97.4%, which is 7% higher than that of the original YOLOv5 network, and the detection speed is increased by 10 fps, which improves the accuracy and speed of insulator detection.
Special Issue on Critical Metal Occurrence, Enrichment, and Application
Authors: Wang Changming , Zhu Jiaxuan , Bagas Leon
Published: December 2022

Critical metals are a new resource concept introduced in recent years, referring to a category of metal elements that have essential and irreplaceable uses for emerging industries such as new energy, new materials, information technology, and defense industries [...]
Geometrical Effect of Active Material on Electrode Tortuosity in All-Solid-State Lithium Battery
Authors: Park So-Yeon , Jeong Jiung , Shin Heon-Cheol
Published: December 2022

In this study, the effect of the active material geometry on the tortuosity in the ion transport path of the electrode composite of an all-solid-state lithium battery was systematically analyzed in terms of the different design and process factors of an electrode. A direct current technique (i.e., chronoamperometry) using an electron-blocking cell was used to analyze the tortuosity to minimize the experimental error. In addition, aluminum oxide was selected as a hypothetical active material in a composite electrode to exclude the possible disturbance of the ion transport signal caused by real active materials. The experimental results showed that the shape and composition of the active material had significant influences on the ion transport characteristics. In particular, when a fibrous material was applied with a high active material ratio, the degree of tortuosity was significantly increased, reaching values as high as 45, due to the insufficient filling in the micropores formed by particle aggregation. Moreover, the tortuosity degree decreased below 15 as the pressing pressure increased during electrode manufacturing, and the cause of this decrease differed with the active material’s particle shape. The analysis results confirmed that the change in tortuosity resulting from the electrode design factors of an all-solid-state battery has distinctive features compared to that for a conventional liquid electrolyte-based lithium-ion battery.
Multi-Subject Image Retrieval by Fusing Object and Scene-Level Feature Embeddings
Authors: Ban Chung-Gi , Hwang Youngbae , Park Dayoung , Lee Ryong , Jang Rae-Young , Choi Myung-Seok
Published: December 2022

Most existing image retrieval methods separately retrieve single images, such as a scene, content, or object, from a single database. However, for general purposes, target databases for image retrieval can include multiple subjects because it is not easy to predict which subject is entered. In this paper, we propose that image retrieval can be performed in practical applications by combining multiple databases. To deal with multi-subject image retrieval (MSIR), image embedding is generated through the fusion of scene- and object-level features, which are based on Detection Transformer (DETR) and a random patch generator with a deep-learning network, respectively. To utilize these feature vectors for image retrieval, two bags-of-visual-words (BoVWs) were used as feature embeddings because they are simply integrated with preservation of the characteristics of both features. A fusion strategy between the two BoVWs was proposed in three stages. Experiments were conducted to compare the proposed method with previous methods on conventional single-subject datasets and multi-subject datasets. The results validated that the proposed fused feature embeddings are effective for MSIR.
JARUA: Joint Embedding of Attributes and Relations for User Alignment across Social Networks
Authors: Yang Min , Chen Baiyang , Chen Xiaoliang
Published: December 2022

User alignment (UA), a central issue for social network analysis, aims to recognize the same natural persons across different social networks. Existing studies mainly focus on the positive effects of incorporating user attributes and network structure on UA. However, there have been few in-depth studies into the existing challenges for the joint integration of different types of text attributes, the imbalance between user attributes and network structure, and the utilization of massive unidentified users. To this end, this paper presents a high-accuracy embedding model named Joint embedding of Attributes and Relations for User Alignment (JARUA), to tackle the UA problem. First, a mechanism that can automatically identify the granularity of user attributes is introduced for handling multi-type user attributes. Second, a graph attention network is employed to extract the structural features and is integrated with user attributes features. Finally, an iterative training algorithm with quality filters is introduced to bootstrap the model performances. We evaluate JARUA on two real-world data sets. Experimental results demonstrate the superiority of the proposed method over several state-of-the-art approaches.
The Effect of the Digital Manufacturing Technique, Preparation Taper, and Cement Type on the Retention of Aged Anterior Provisional Crowns: An In Vitro Study
Authors: Lunkad Honey , Sayed Mohammed E. , Alhazmi Abdullah Essa , Alwadani Bandar , Shafei Ameen Marwei , Ayoub Muath Naji , Shabi Maan Mohammed A. , Mesawa Sara Ahmad , Abdulfatah Basmah Alhassan , Alqarni Hatem , Alqahtani Saeed M. , Alamoudi Ahmed , Almalki Mohammed Salman , Jethlia Ankur , Jain Saurabh
Published: December 2022

A well-made provisional fixed prosthesis must present as a preview of the future prosthesis and may also augment the health of the abutments and periodontium. Provisional restorations have been prepared chairside with polymethyl methacrylate (PMMA) since time immemorial. CAD/CAM additive and subtractive technologies have revolutionized the fabrication of interim restorations in dental clinics. The current literature lacks substantial data about retention of provisional crowns manufactured using Computer-Aided Design/Computer-Aided Manufacturing (CAD/CAM) additive and subtractive techniques with various temporary cements. This in vitro study aims to assess and compare the retention of temporary/provisional anterior crowns based on the combined effect of different digital manufacturing techniques, preparation tapers, and the temporary cements used for cementation. Two maxillary right central incisor typodont teeth were prepared to receive all-ceramic crowns, one with a 10-degree taper and the other with a 20-degree taper. Forty 3D-printed working models with the 10° taper and forty working models with the 20° taper were prepared to receive the temporary crowns. Forty temporary crowns were 3D-printed and forty crowns were milled (20 from each taper group). Kerr Temp-Bond NE conventional cement and Kerr Temp-Bond clear cement were used for cementation in the two groups. The number of samples per test group was 10. All samples were thermocycled and subjected to a universal testing machine to measure the pull-off force until retention loss (N) under tension with a crosshead speed of 5 mm/min. The pull-off force was highest for group 8, i.e., 3D-printed crowns with a 20° taper and cemented with Kerr Temp-Bond clear cement, followed by groups 6, 7, 4, 5, 3, and 2. Group 1, i.e., milled crowns with 10° taper cemented with Kerr Temp-Bond NE conventional cement, exhibited the lowest pull-off retentive force. The clinical selection of long-term provisional crowns fabricated using 3D-printing technology, prepared with 10° or 20° tapers, and cemented with clear cement, is the most favorable in terms of the retention of provisional crowns. 3D-printed provisional crowns can be used as an alternative to conventional and CAD/CAM-milled crowns for long-term provisionalization.