bluuebunny/crossref_metadata_2025 huggingface dataset:
Lethal and Sublethal Effects of an Essential Oil-Based Emulsion of Patchouli, Pogostemon cablin (Lamiaceae), on the Tomato Leafminer
Authors: Costa Thiago Leandro , Santos Renata Cordeiro dos , Santos Abraão Almeida , Pimentel Emílio de Souza , Lima Eraldo , Batista Claudio Vieira , Bacci Leandro , Freitas Damaris Rosa de , Picanço Marcelo Coutinho
Published: August 2023

There has been an excitement toward novel eco-friendly alternatives to pest management, particularly formulations based on essential oils (EOs). Here, the biological activity of an EO-based emulsion derived from patchouli, Pogostemon cablin, was assessed against Tuta absoluta (Meyrick) (Lepidoptera: Gelechiidae), a devastating and invasive pest in tomato crops worldwide. Laboratory bioassays were carried out to determine and compare lethal doses, lethal times, oviposition of treated individuals, and oviposition of T. absoluta on treated leaves of tomato to pure patchouli essential oil or its emulsion containing 18% of oil. The LD50 were 10.06 and 2.57 µg of patchouli per mg of insect for the EO and emulsion, respectively. Oviposition was reduced in adults derived from the second instar treated with LD10 by 78.5% (EO) and 85.4% (emulsion). The EO and its emulsion conferred similar avoidance to adults when sprayed on tomato leaves. Therefore, both formulations present similar lethal and sublethal effects against T. absoluta. This study demonstrated a remarkable potential of an emulsion containing 18% of P. cablin oil to be employed for T. absoluta management on tomato crops. Further studies are needed to assess and guarantee open field applications.
The Influence of Phytohormones on Antioxidative and Antibacterial Activities in Callus Cultures of Hypericum perforatum L.
Authors: Jonuškienė Ilona , Stankevičienė Rima , Kantminienė Kristina , Tumosienė Ingrida
Published: August 2023

Natural extracts of Hypericum perforatum L. are widely used in the pharmaceutical industry due to their antiviral, antioxidant, antibacterial, antidiabetic, and antidepressant activities. Plant biotechnological methods are gaining more attention as efficient and biosustainable approaches for the production of high value compounds by using plant callus cultures in vitro. The aim of this research was to evaluate the influence of phytohormones on the formation of Hypericum perforatum L. callus culture, to explore antioxidant and antibacterial activities, and to determine the amounts of phytochemicals in the analyzed extracts. Callus cultures were induced on Murashige and Skoog basal medium supplemented with phytohormones (auxins, cytokinins, and salicylic acid), and containing newly synthesized compound N-(1,3-dioxoisoindolin-2-yl)-3-((4-methoxyphenyl)amino)propanamide. The antioxidant activities of callus cultures were evaluated using DPPH and FRAP assays and the enzyme antioxidants (superoxide dismutase, catalase, and ascorbate peroxidase) were evaluated. The antibacterial activity of plant extracts was screened against Escherichia coli and Bacillus subtilis bacteria by the diffusion agar method. There was a significant positive correlation between total phenolic content and high antioxidant efficiency in Hypericum perforatum L. callus cultures, which were formed on Murashige and Skoog medium supplemented with auxin, cytokinin, and salicylic acid (100 µM). Our results have demonstrated that callus cultures generated on MS medium supplemented with N-(1,3-dioxoisoindolin-2-yl)-3-((4-methoxyphenyl)amino)propanamide and cytokinin BAP (0.5 mg L−1) exhibited improved antioxidant activities for the first time.
A Vibration Reduction Control Method for Tractor Rear Hydraulic Hitch Based on Pressure Feedback
Authors: Liu Changqing , Gu Jinheng , Du Xin , Yang Le , Du Yuefeng , Mao Enrong
Published: August 2023

Tractors transporting heavy hitches tend to tilt severely, resulting in significant dynamic loads on the front axle and affecting handling stability. Tractors and rear hitches can be considered vibration systems with two coupled masses. Thus, active damping control strategies between tractors and rear hitches are proposed in this study. The complexity and versatility of tractor hydraulic hitching during tractor transit transport are considered. A method of improving the tractor hydraulic hitch damping ratio with pressure feedback is proposed. The dynamic characteristics of the pressure feedback hydraulic hitch system are analyzed. A dynamic model of the tractor transfer transport unit is established, and a numerical simulation is carried out to verify the effectiveness of the proposed hydraulic hitch vibration reduction control strategy based on pressure feedback. A real test platform for tractor vibration reduction control is built. The test results show that the pressure feedback vibration reduction control method proposed in this paper affects tractor pitching motion suppression. In addition, the proposed control strategy does not require a force pin sensor. Tractor hydraulic hitch damping control costs are reduced. The vibration reduction control strategy proposed in this study has high reliability and can be used as a reference for non-road-vehicle vibration reduction control.
Enhancing Rice Crop Management: Disease Classification Using Convolutional Neural Networks and Mobile Application Integration
Authors: Hasan Md. Mehedi , Rahman Touficur , Uddin A. F. M. Shahab , Galib Syed Md. , Akhond Mostafijur Rahman , Uddin Md. Jashim , Hossain Md. Alam
Published: August 2023

Early diagnosis of rice disease is important because it poses a considerable threat to agricultural productivity as well as the global food security of the world. It is challenging to obtain more reliable outcomes based on the percentage of RGB value using image processing outcomes for rice disease detections and classifications in the agricultural field. Machine learning, especially with a Convolutional Neural Network (CNN), is a great tool to overcome this problem. But the utilization of deep learning techniques often necessitates high-performance computing devices, costly GPUs and extensive machine infrastructure. As a result, this significantly raises the overall expenses for users. Therefore, the demand for smaller CNN models becomes particularly pronounced, especially in embedded systems, robotics and mobile applications. These domains require real-time performance and minimal computational overhead, making smaller CNN models highly desirable due to their lower computational cost. This paper introduces a novel CNN architecture which is comparatively small in size and promising in performance to predict rice leaf disease with moderate accuracy and lower time complexity. The CNN network is trained with processed images. The image processing is performed using segmentation and k-means clustering to remove background and green parts of affected images. This technique proposes to detect rice disease of rice brown spot, rice bacterial blight and leaf smut with reliable outcomes in disease classifications. The model is trained using an augmented dataset of 2700 images (60% data) and validated with 1200 images of disease-affected samples to identify rice disease in agricultural fields. The model is tested with 630 images (14% data); testing accuracy is 97.9%. The model is exported into a mobile application to introduce the real-life application of the outcome of this work. The model accuracy is compared to others work associated with this type of problem. It is found that the performance of the model and the application are satisfactory compared to other works related to this work. The over-all accuracy is notable, showing the reliability and dependability of this model to classify rice leaf diseases.
Genetic Potential of Tropically Adapted Exotic Maize (Zea mays L.) Heat-Tolerant Donor Lines in Sub-Tropical Breeding Programs
Authors: Mukaro Ronica , Kamutando Casper Nyaradzai , Magorokosho Cosmos , Mutari Bruce , Zaidi Pervez Haider , Kutywayo Dumisani , Sibiya Julia
Published: August 2023

Breeding for heat stress tolerance became a priority in sub-Saharan Africa (SSA), as projections are showing an increase in frequency, duration, and severity. In this study, 14 heat stress tolerant-donor lines (HSTDLs) sourced from CIMMYT-India (males) were crossed with 15 locally adapted elite lines (females) developed within the CIMMYT-Zimbabwe maize-breeding program using the North Carolina Design II mating scheme. The resultant 175 single crosses were evaluated alongside five commercial hybrids and adjacent to the trial of parental lines used in the crosses across two locations representing heat stress and optimal environments in Zimbabwe. The design II analysis showed significant (p < 0.01) general combining ability (GCA) effects for exotic heat donor lines and specific combining ability (SCA) effects on grain yield under heat stress, optimal conditions, and across locations; demonstrating additive and non-additive genetic inheritance of grain yield. High Baker’s ratios observed in this study indicate predominance of additive over non-additive gene effects. Three exotic HSTDLs, namely CAL14138, CAL152, and CAL1440, exhibited significant (p < 0.001) and positive GCA effects under heat stress conditions. The results imply that these exotic lines could serve as valuable genetic resources for introgression of heat tolerant alleles into local maize populations for accelerated yield genetic gains. Single crosses, DJ265-15 × VL1018816 and DJ267-9 × CAL1440, exhibited positive and significant (p < 0.01) and (p < 0.05) SCA effects for grain yield under heat stress conditions, respectively. These crosses can be used for further breeding and can contribute to grain yield performance under heat stress conditions. The exotic HSTDLs, CAL14138, CAL152, and VL109126 showed superior per se performance under heat, optimal conditions, and across environments. Overall data demonstrate the potential of exotic HSTDLs for improving the adaptation of maize to heat stress in sub-tropical breeding programs.
Influence of Long-Term Soil Management Practices on Carbon Emissions from Corn (Zea mays L.) Production in Northeast Croatia
Authors: Galic Marija , Bilandzija Darija , Zgorelec Zeljka
Published: August 2023

Sustainable management of agricultural resources is needed to meet people’s increasing demands for food, fiber and energy while maintaining the quality of the environment and protecting natural resources. With the rapid growth of agriculture and the mechanization of farming, the agricultural sector has become one of the main contributors to the increase in CO2 emissions and other greenhouse gases in the world. Therefore, the aim of this study was to determine the effect, dependence and correlations of CO2 in soil with native vegetation (presence/absence, corn yield) and climatic conditions (soil temperature and moisture) during three years of measurements under different management practices in a classical conventional agroecosystem. This research contains four different treatments: control treatment (CT), dolomite/organic fertilization (DOL/OF), mineral fertilization (MF) and black fallow (BF). During the investigated period, the average overall C-CO2 flux ranged from 7.98 kg ha−1 day−1 on bare soil to 16.26 kg ha−1 day−1 on soil treated with mineral fertilization. No statistically significant difference was observed among different fertilization treatments, except in 2013 and 2015 when comparing different fertilization treatments to bare soil. In all three years, there was a positive correlation between average C-CO2 fluxes and soil temperature. Additionally, in 2013 and 2017, there was a positive correlation between average C-CO2 fluxes and soil moisture, while a negative correlation was observed in 2015. Obtained values of crop yield ranged from 0.89 t ha−1 in the control treatment (in 2015) to 14.81 t ha−1 in the treatment with mineral fertilization (in 2017). Growing global concern about the effects of climate change calls for intensive research on the carbon cycle, and these results will contribute to the understanding of carbon transformation in different crops and soil management practices.
Comparison of Cortisol Concentrations in Different Matrices in Alpine Ibex (Capra ibex) at the Zoo
Authors: Kastelic Marjan , Gregurić Gračner Gordana , Tomažič Iztok , Kvapil Pavel , Harej Mojca , Dovč Alenka
Published: August 2023

The usefulness of blood collection using venipuncture versus kissing bugs or medicinal leeches and the collection of saliva, faeces, hair, urine, and tears for measuring “immunoreactive” C (iC) concentration in Alpine ibexes was verified using commercial enzyme immunoassays. The mean value of serum C was highest in serum collected using venipuncture and lowest in serums collected using kissing bugs. Statistically significant differences were observed between venipuncture and kissing bugs and between leeches and kissing bugs. However, no statistically significant difference was found in C concentrations between samples collected with venipuncture and those collected with leeches. The highest mean value of C concentration was measured in serum (all three methods), followed by that in hair and faeces, and the lowest mean value was found in saliva. Statistically significant differences were found between saliva and faeces samples and between saliva and hair samples. The difference between the concentrations for faeces and hair was not statistically significant. A significant difference in C concentration between males and females was found in saliva. A significant difference in C concentration among different ages was measured in serum obtained using venipuncture in all three groups and in faeces between the groups older than ten years and younger than 10 months. Highly significant differences in C concentrations were also found between hair sampled in summer and hair sampled in autumn. Collecting tear and urine samples is a laborious procedure and is therefore less acceptable for C determination. Due to the small number of samples, statistical values are not given for these two matrices.
Maternal Supplementary Tapioca Polysaccharide Iron Improves the Growth Performance of Piglets by Regulating the Active Components of Colostrum and Cord Blood
Authors: Deng Shengting , Fang Chengkun , Zhuo Ruiwen , Jiang Qian , Song Yating , Yang Kaili , Zhang Sha , Hao Juanyi , Fang Rejun
Published: August 2023

The purpose of this study was to investigate the effect of maternal supplementation with TpFe (tapioca polysaccharide iron) on reproductive performance, colostrum composition, cord blood active components of sows, and growth performance of their nursing piglets. Sixty healthy Duroc × Landrace × Yorkshire sows were randomly assigned to three groups at day 85 of gestation. The experimental diets included a basal diet supplemented with 100 mg/kg FeSO4·H2O (CON group), the basal diet supplemented with 50 mg/kg TpFe (TpFe50 group), and the basal diet supplemented with 100 mg/kg TpFe (TpFe100 group), as calculated by Fe content. The experiment lasted from day 85 of gestation to the end of weaning (day 21 of lactation). Results showed that maternal supplementation with 100 mg/kg TpFe improved (p < 0.05) feed intake during lactation, live births, and birth weight of the litter (alive) and increased (p < 0.05) colostrum IgM (immunoglobulin m), IgA (immunoglobulin A), as well as the IgG levels, while it decreased (p < 0.05) the urea nitrogen and somatic cell count of sows. Moreover, sows in the TpFe100 group had higher (p < 0.05) serum iron levels and IgG. Additionally, maternal supplementation with 100 mg/kg TpFe increased (p < 0.05) iron level, total antioxidant capacity (T-AOC), glutathione peroxidase (GSH-px), catalase (CAT), IgG, red blood cells (RBC), and hemoglobin (Hb) of cord blood, similar with the iron content, T-AOC, GSH-px, IgG, RBC, Hb, hematocrit (HCT), and mean corpuscular volume (MCV) of weaned piglet blood. The diarrhea and mortality rates among the nursing piglets were decreased (p < 0.05), while the average weight at day 21 of age was increased (p < 0.05) in the TpFe100 group. Serum PRL (prolactin) levels of sows exhibited a positive correlation (p < 0.05) with live births. Suckling piglet diarrhea was positively correlated with colostrum urea nitrogen level but negatively correlated with colostrum IgM, IgG, and cord blood Hb content (p < 0.05). The mortality of suckling piglets was negatively correlated with serum iron content and IgM in colostrum, GSH-px, and IgG in cord serum of sows (p < 0.05). The average weight of weaning piglets was positively (p < 0.05) related to colostrum IgM and IgG levels, as well as cord serum RBC counts of sows on day 21. In conclusion, maternal supplementation with TpFe can improve the active components of colostrum and umbilical cord blood and improve the growth performance of suckling piglets.
The Effects of Zinc Supplementation on Growth, Diarrhea, Antioxidant Capacity, and Immune Function in Holstein Dairy Calves
Authors: Liu Junhao , Ma Fengtao , Degen Allan , Sun Peng
Published: August 2023

The current study examined the effects of supplementary zinc proteinate (ZnPro) and zinc oxide (ZnO) on growth performance, diarrhea, antioxidant capacity, immune function, and mineral element concentrations of calves aged 1 to 28 days. A total of twenty-four newborn calves were divided randomly into 3 groups (n = 8; 2 males and 6 females per group), and each received: 0 mg/d Zn (CON), 627 mg/d ZnPro (80 mg/d Zn; ZnPro group), and 101 mg/d ZnO (80 mg/d Zn; ZnO group). The calves received the additive in their milk during the first 28 days of life. Compared with the CON group: ZnPro and ZnO improved average daily gain (ADG) and decreased the feed:gain ratio (FGR) between days 1 and 14 (p < 0.05), while the ADG increased and FGR decreased only in the ZnPro group between days 1 and 28 (p < 0.05). The incidence of diarrhea decreased (p < 0.05) in the ZnPro and ZnO groups between days 15 and 28 as well as days 1 and 28, but decreased (p < 0.05) only in the ZnPro group between days 1 and 14. The serum immunoglobulin G (IgG) concentration of the ZnPro and ZnO groups increased on days 14 and 28 (p < 0.05). ZnPro supplementation increased serum IgM concentration during the whole study, while ZnO enhanced serum IgM concentration only on day 14 (p < 0.05). In the ZnO group, the serum concentration of cytokines interleukin (IL)-10 increased on day 14, while that of IL-1β increased on day 28 (p < 0.05). In addition, ZnPro reduced the serum malondialdehyde (MDA) concentration on days 14 and 28 (p < 0.05). Both ZnPro and ZnO increased the serum concentrations of alkaline phosphatase (ALP) and metallothionein (MT) on day 14 (p < 0.05). With zinc supplementation, plasma Zn concentration increased (p < 0.05) on days 14 and 28 of age. We concluded that supplementary ZnPro and ZnO reduced incidences of diarrhea and promoted the immune function, but ZnPro improved the growth performance and antioxidant capacity of Holstein dairy calves to a greater extent.
Public Knowledge, Attitudes, and Practices towards Antibiotic Use and Antimicrobial Resistance in Eastern Region of Bosnia and Herzegovina in the COVID-19 Pandemic
Authors: Drakul Dragana , Joksimović Bojan , Milić Marija , Radanović Milica , Dukić Nikolina , Lalović Nenad , Nischolson Desmond , Mijović Biljana , Sokolović Dragana
Published: August 2023

The constant worsening of antimicrobial resistance (AMR) imposes the need for an urgent response. Use of antibiotics (AB), both due to irrational prescribing by doctors and irrational use by patients, is recognized as one of the leading causes of this problem. This study aimed to identify knowledge, attitudes, and practices about AB use and AMR within the general population, stratified by age, gender, and urban/rural areas during the COVID-19 pandemic. This questionnaire-based cross-sectional study was conducted in April 2022 among patients who visited three health centers in the eastern region of Bosnia and Herzegovina. A high frequency of AB use was observed during the COVID-19 pandemic (64.2% of respondents were treated with AB). Age and place of residence have not been shown to be factors associated with AB use practices that pose a risk for AMR. However, female gender (β = 0.063; p = 0.041), better knowledge (β = 0.226; p < 0.001), and positive attitudes (β = 0.170; p < 0.001) about use of AB and towards to AMR proved to be factors associated with better practice by respondents. Women, younger respondents, and respondents from urban areas showed better knowledge, attitudes, and behavior about the use of AB and AMR during the COVID-19 pandemic.
Synergistic Antibacterial Effects of Amoxicillin and Gold Nanoparticles: A Therapeutic Option to Combat Antibiotic Resistance
Authors: Giráldez-Pérez Rosa M. , Grueso Elia M. , Carbonero Alfonso , Álvarez Márquez Juan , Gordillo Mirian , Kuliszewska Edyta , Prado-Gotor Rafael
Published: August 2023

Compacted Au@16-mph-16/DNA-AMOX (NSi) nanosystems were prepared from amoxicillin (AMOX) and precursor Au@16-mph-16 gold nanoparticles (Ni) using a Deoxyribonucleic acid (DNA) biopolymer as a glue. The synthesized nanocarrier was tested on different bacterial strains of Escherichia coli, Staphylococcus aureus, and Streptococcus pneumoniae to evaluate its effectiveness as an antibiotic as well as its internalization. Synthesis of the nanosystems required previous structural and thermodynamic studies using circular dichroism (CD) and UV-visible techniques to guarantee optimal complex formation and maximal DNA compaction, characteristics which facilitate the correct uptake of the nanocarrier. Two nanocomplexes with different compositions and structures, denoted NS1 and NS2, were prepared, the first involving external Au@16-mph-16 binding and the second partial intercalation. The Ni and NSi nanosystems obtained were characterized via transmission electron microscopy (TEM), zeta potential, and dynamic light scattering (DLS) techniques to measure their charge, aggregation state and hydrodynamic size, and to verify their presence inside the bacteria. From these studies, it was concluded that the zeta potential values for gold nanoparticles, NS1, and NS2 nanosystems were 67.8, −36.7, and −45.1 mV. Moreover, the particle size distribution of the Au@16-mph-16 gold nanoparticles and NS2 nanoformulation was found to be 2.6 nm and 69.0 nm, respectively. However, for NS1 nanoformulation, a bimodal size distribution of 44 nm (95.5%) and 205 nm (4.5%) was found. Minimal inhibitory concentration (MIC) values were determined for the bacteria studied using a microdilution plates assay. The effect on Escherichia coli bacteria was notable, with MIC values of 17 µM for both the NS1 and NS2 nanosystems. The Staphylococcus aureus chart shows a greater inhibition effect of NS2 and NP2 in non-diluted wells, and clearly reveals a great effect on Streptococcus pneumoniae, reaching MIC values of 0.53 µM in more diluted wells. These results are in good agreement with TEM internalization studies of bacteria that reveal significant internalization and damage in Streptococcus pneumoniae. In all the treatments carried out, the antibiotic capacity of gold nanosystems as enhancers of amoxicillin was demonstrated, causing both the precursors and the nanosystems to act very quickly, and thus favoring microbial death with a small amount of antibiotic. Therefore, these gold nanosystems may constitute an effective therapy to combat resistance to antibiotics, in addition to avoiding the secondary effects derived from the administration of high doses of antibiotics.
A High-Performance Antibacterial Nanostructured ZnO Microfluidic Device for Controlled Bacterial Lysis and DNA Release
Authors: Xesfyngi Yvonni , Georgoutsou-Spyridonos Maria , Tripathy Abinash , Milionis Athanasios , Poulikakos Dimos , Mastellos Dimitrios C. , Tserepi Angeliki
Published: August 2023

In this work, the antibacterial properties of nanostructured zinc oxide (ZnO) surfaces are explored by incorporating them as walls in a simple-to-fabricate microchannel device. Bacterial cell lysis is demonstrated and quantified in such a device, which functions due to the action of its nanostructured ZnO surfaces in contact with the working fluid. To shed light on the mechanism responsible for lysis, E. coli bacteria were incubated in zinc and nanostructured ZnO substrates, as well as the here-investigated ZnO-based microfluidic devices. The unprecedented killing efficiency of E. coli in nanostructured ZnO microchannels, effective after a 15 min incubation, paves the way for the implementation of such microfluidic chips in the disinfection of bacteria-containing solutions. In addition, the DNA release was confirmed by off-chip PCR and UV absorption measurements. The results indicate that the present nanostructured ZnO-based microfluidic chip can, under light, achieve partial inactivation of the released bacterial DNA via reactive oxygen species-mediated oxidative damage. The present device concept can find broader applications in cases where the presence of DNA in a sample is not desirable. Furthermore, the present microchannel device enables, in the dark, efficient release of bacterial DNA for downstream genomic DNA analysis. The demonstrated potential of this antibacterial device for tailored dual functionality in light/dark conditions is the main novel contribution of the present work.
From Challenge to Opportunity: Addressing Oxidative Stress in Animal Husbandry
Authors: Zhang Shihai
Published: August 2023

Years of study have explored the issues caused by oxidative stress in livestock and poultry production [...]
Quercetin’s Dual Mode of Action to Counteract the Sp1-miR-27a Axis in Colorectal Cancer Cells
Authors: Fosso Emanuele , Leo Manuela , Muccillo Livio , Mandrone Vittorio Maria , Di Meo Maria Chiara , Molinario Annamaria , Varricchio Ettore , Sabatino Lina
Published: August 2023

Quercetin (Qc) inhibits cell proliferation and induces apoptosis in a variety of cancer cells. The molecular mechanism of action has not been fully elucidated; however, interplay with some miRNAs has been reported, specifically with miR-27a, an onco-miRNA overexpressed in several malignancies. Here, we show that Qc reduces cell viability and induces apoptosis in HCT116 and HT-29 colon cancer cells, by upregulating negative modulators of proliferation pathways such as Sprouty2, PTEN and SFRP1. These are targets of miR-27a whose high expression is reduced by Qc. Moreover, miR-23a, and miR-24-2, the two other components of the unique gene cluster, and the pri-miRNA transcript are reduced, evoking a transcriptional regulation of the entire cluster by Sp1. Mechanistically, we show that Qc is rapidly internalized and localizes in the nucleus, where it likely interacts with Sp1, inducing its proteasomal degradation. Sp1 is further repressed by ZBTB10, an Sp1 competitor for DNA binding that is an miR-27a target and whose levels increase following Qc. SP1 mRNA is also reduced, supporting the regulation of its own gene transcription. Finally, Sp1 knockdown elicits the impaired transcription of the entire cluster and the upregulation of the miR-27a targets, phenocopying the effects of Qc. Through this dual mode of action, Qc counteracts the protumoral Sp1-miR-27a axis, opening the way for novel therapies based on its association as neoadjuvant with known anticancer treatments.
Effects of Prometryn Exposure on Hepatopancreas Oxidative Stress and Intestinal Flora in Eriocheir sinensis (Crustacea: Decapoda)
Authors: Huang Peng , Cao Liping , Du Jinliang , Gao Jiancao , Zhang Yuning , Sun Yi , Li Quanjie , Nie Zhijuan , Xu Gangchun
Published: August 2023

There is growing evidence that long-term exposure to prometryn (a widely used herbicide) can induce toxicity in bony fish and shrimp. Our previous study demonstrated its 96 h acute toxicity on the crab Eriocheir sinensis. However, studies on whether longer exposure to prometryn with a lower dose induces toxicity in E. sinensis are scarce. Therefore, we conducted a 20 d exposure experiment to investigate its effects on the hepatopancreas and intestine of E. sinensi. Prometryn reduce the activities of antioxidant enzymes, increase the level of lipid peroxidation and cause oxidative stress. Moreover, long-term exposure resulted in immune and detoxification fatigue, while short-term exposure to prometryn could upregulate the expression of genes related to immunity, inflammation and detoxification. Prometryn altered the morphological structure of the hepatopancreas (swollen lumen) and intestine (shorter intestinal villi, thinner muscle layer and thicker peritrophic membrane). In addition, prometryn changed the species composition of the intestinal flora. In particular, Bacteroidota and Proteobacteria showed a dose-dependent decrease accompanied by a dose-dependent increase in Firmicutes at the phylum level. At the genus level, all exposure groups significantly increased the abundance of Zoogloea and a Firmicutes bacterium ZOR0006, but decreased Shewanella abundance. Interestingly, Pearson correlation analysis indicated a potential association between differential flora and hepatopancreatic disorder. Phenotypic abundance analysis indicated that changes in the gut flora decreased the intestinal organ’s resistance to stress and increased the potential for opportunistic infection. In summary, our research provides new insights into the prevention and defense strategies in response to external adverse environments and contributes to the sustainable development of E. sinensis culture.
Energy Efficiency in Historic Architecture: The “Ex Institute of Zoology and Comparative Anatomy” in Palermo
Authors: Curto Domenico , Franzitta Vincenzo , Guercio Andrea , Mantegna Miriam , Milone Daniele
Published: August 2023

In Italy, a large part of the buildings classified as historical–artistic heritage is in a state of degradation and requires urgent interventions. Among the needs, a reduction in the high energy consumption and an improvement of the indoor comfort are mandatory. The case study of the “Ex Institute of Zoology of Palermo” shows how it is possible to achieve a reduction in energy consumption and preserve the building’s historicity through the estimation of energy loads and the subsequent processing. To quantify the energy savings of the structure, it was necessary to follow a few steps, namely an inspection of the building and an evaluation of its consumption. To elaborate a correct energy analysis, the thermal conductance was calculated by considering measurements over a period of 60 days and proceeding with the calculation of the transmittance. The resulting data are imported in the energy model developed with the TERMUS BIM software. In the case study, a potential energy saving equal to 35% of the current energy consumption can be avoided by replacing the lamps with LED ones, installing photovoltaic panels, replacing the heat pumps with a centralized system and the current fixtures with double thermal break fixtures. These interventions are implemented in compliance with the architectural peculiarities.
Attention-Based Hybrid Deep Learning Network for Human Activity Recognition Using WiFi Channel State Information
Authors: Mekruksavanich Sakorn , Phaphan Wikanda , Hnoohom Narit , Jitpattanakul Anuchit
Published: August 2023

The recognition of human movements is a crucial aspect of AI-related research fields. Although methods using vision and sensors provide more valuable data, they come at the expense of inconvenience to users and social limitations including privacy issues. WiFi-based sensing methods are increasingly being used to collect data on human activity due to their ubiquity, versatility, and high performance. Channel state information (CSI), a characteristic of WiFi signals, can be employed to identify various human activities. Traditional machine learning approaches depend on manually designed features, so recent studies propose leveraging deep learning capabilities to automatically extract features from raw CSI data. This research introduces a versatile framework for recognizing human activities by utilizing CSI data and evaluates its effectiveness on different deep learning networks. A hybrid deep learning network called CNN-GRU-AttNet is proposed to automatically extract informative spatial-temporal features from raw CSI data and efficiently classify activities. The effectiveness of a hybrid model is assessed by comparing it with five conventional deep learning models (CNN, LSTM, BiLSTM, GRU, and BiGRU) on two widely recognized benchmark datasets (CSI-HAR and StanWiFi). The experimental results demonstrate that the CNN-GRU-AttNet model surpasses previous state-of-the-art techniques, leading to an average accuracy improvement of up to 4.62%. Therefore, the proposed hybrid model is suitable for identifying human actions using CSI data.
XGBoost Prediction Model Optimized with Bayesian for the Compressive Strength of Eco-Friendly Concrete Containing Ground Granulated Blast Furnace Slag and Recycled Coarse Aggregate
Authors: Al-Taai Salwa R. , Azize Noralhuda M. , Thoeny Zainab Abdulrdha , Imran Hamza , Bernardo Luís F. A. , Al-Khafaji Zainab
Published: August 2023

The construction industry has witnessed a substantial increase in the demand for eco-friendly and sustainable materials. Eco-friendly concrete containing Ground Granulated Blast Furnace Slag (GGBFS) and Recycled Coarse Aggregate (RCA) is such a material, which can contribute to a reduction in waste and promote environmental sustainability. Compressive strength is a crucial parameter in evaluating the performance of concrete. However, predicting the compressive strength of concrete containing GGBFS and RCA can be challenging. This study presents a novel XGBoost (eXtreme Gradient Boosting) prediction model for the compressive strength of eco-friendly concrete containing GGBFS and RCA, optimized using Bayesian optimization (BO). The model was trained on a comprehensive dataset consisting of several mix design parameters. The performance of the optimized XGBoost model was assessed using multiple evaluation metrics, including Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and coefficient of determination (R2). These metrics were calculated for both training and testing datasets to evaluate the model’s accuracy and generalization capabilities. The results demonstrated that the optimized XGBoost model outperformed other state-of-the-art machine learning models, such as Support Vector Regression (SVR), and K-nearest neighbors algorithm (KNN), in predicting the compressive strength of eco-friendly concrete containing GGBFS and RCA. An analysis using Partial Dependence Plots (PDP) was carried out to discern the influence of distinct input features on the compressive strength prediction. This PDP analysis highlighted the water-to-binder ratio, the age of the concrete, and the percentage of GGBFS used, as significant factors impacting the compressive strength of the eco-friendly concrete.
Special Issue on Intelligent Processing on Image and Optical Information III
Authors: Yeom Seokwon
Published: August 2023

Intelligent image and optical information processing have paved the way for the recent epoch of the new intelligence and information era [...]
A Deep Learning Technique to Improve Road Maintenance Systems Based on Climate Change
Authors: Elwahsh Haitham , Allakany Alaa , Alsabaan Maazen , Ibrahem Mohamed I. , El-Shafeiy Engy
Published: August 2023

Road maintenance systems (RMS) are crucial for maintaining safe and efficient road networks. The impact of climate change on road maintenance systems is a concern as it makes them more susceptible to weather events and subsequent damages. To tackle this issue, we propose an RMSDC (Road Maintenance Systems Using Deep Learning and Climate Adaptation) technique to improve road maintenance systems based on Deep learning and Climate Adaptation. RMSDC aims to use the multivariate classification technique and divides the dataset into training and test datasets. The RMSDC combines Convolutional Long Short-Term Memory (ConvLSTM) techniques with road weather information and sensor data. However, in emerging nations, the effects of climate change are already apparent, which makes road networks particularly susceptible to extreme weather, floods, and landslides. Therefore, climate adaptation of road networks is essential, especially in developing nations with limited financial resources. To address this issue, we propose an intelligent and effective RMSDC that utilizes deep learning algorithms based on climate change predictions. The ConvLSTM block effectively captures the relationship between input features over time to calculate the root-mean deviation (RMSD). We evaluate RMSDC performance against frameworks for downscaling climate variables using two metrics: root-mean-square error (RMSE) and mean absolute difference. Through real evaluations, RMSDC consistently outperforms approaches with a reduced RMSE of 0.26. These quantitative results highlight how effective RMSDC is in addressing maintenance systems on road networks leading to proactive road maintenance strategies that enhance traffic safety, reduce costs, and improve environmental sustainability.
Photoplethysmographic Signal-Diffusive Dynamics as a Mental-Stress Physiological Indicator Using Convolutional Neural Networks
Authors: de Pedro-Carracedo J. , Clemente J. , Fuentes-Jimenez D. , Cabrera-Umpiérrez M. F. , Gonzalez-Marcos A. P.
Published: August 2023

Stress is one of the primary triggers of serious pathologies (e.g., depression, obesity, heart attack). Prolonged exposure to it can lead to addictive substance consumption and even suicide, without ignoring other adverse side effects in the economic, work and family spheres. Early detection of stress would relax the pressure of medical practice exercised by the population affected and result in a healthier society with a more satisfying quality of life. In this work, a convolutional-neural-network (CNN) model is proposed to detect an individual’s stress state by analyzing the diffusive dynamics of the photoplethysmographic (PPG) signal. The characteristic (p,q)-planes of the 0–1 test serve as a framework to preprocess the PPG signals and feed the CNN with the dynamic information they supply to typify an individual’s stress level. The methodology follows CRISP-DM (Cross Industry Standard Process for Data Mining), which provides the typical steps in developing data-mining models. An adaptation of CRIPS-DM is applied, adding specific transitions between the usual stages of deep-learning models. The result is a CNN model whose performance amounts to 97% accuracy in diagnosing the stress level; it compares with other published results.
Deformation Energy Estimation of Cherry Tomato Based on Some Engineering Parameters Using Machine-Learning Algorithms
Authors: Kabas Onder , Kayakus Mehmet , Ünal İlker , Moiceanu Georgiana
Published: August 2023

For the design and sizing of equipment and structures in agricultural operations concerning the cherry tomato industry, especially harvesting operations and postharvest operations of the crops, it is very important to determine their mechanical properties. In the study, mass, length, thickness, width, geometric diameter, sphericity, surface area, rupture force, firmness, Poisson’s ratio, and modulus of elasticity were used as independent variables in the data set, and the dependent variable and deformation energy was estimated. Min–max normalization methods were used to increase the success and performance of the models. Three machine learning methods were utilized in the study, and statistical parameters, such as R2, MAE, and MSE, were used to evaluate the performance of the methods. The R2 of the artificial neural network (ANN), applied in the model as one of the machine learning methods, was found to be 96.8%, revealing the highest predictive power. Logistic regression with a 91.1% success rate, and decision tree regression with an 81.3% success rate, came second and third, respectively.
Experimental Research on the Influence of Size Ratio on the Effector Movement of the Manipulator with a Large Working Area
Authors: Krogul Piotr , Cieślik Karol , Łopatka Marian Janusz , Przybysz Mirosław , Rubiec Arkadiusz , Muszyński Tomasz , Rykała Łukasz , Typiak Rafał
Published: August 2023

More and more commonly, manipulators and robots equipped with effectors are used to replace humans in the implementation of tasks that require significant working abilities or are used in dangerous zones. These constructions have considerable ranges and are capable of carrying heavy loads. The specificity of the tasks performed with the use of mentioned devices requires their control by a human. Intuitive tracking systems are used to control them. Problems in their use result from the kinematic amplification between the effector and the operator’s hand. Proper design of the drive and control systems for these manipulators requires knowledge of the maximum velocities of the manipulator’s effectors, which significantly depend on the scale ratio. The article presents the results of the effector’s velocity movements while performing a specific task by the operator’s hand with different velocities and scale ratios.
Optimal Performance of Mg-SiC Nanocomposite: Unraveling the Influence of Reinforcement Particle Size on Compaction and Densification in Materials Processed via Mechanical Milling and Cold Iso-Static Pressing
Authors: Rahimi Mehr Fatemeh , Kamrani Sepideh , Fleck Claudia , Salavati Mohammad
Published: August 2023

Achieving uniformly distributed reinforcement particles in a dense matrix is crucial for enhancing the mechanical properties of nanocomposites. This study focuses on fabricating Mg-SiC nanocomposites with a high-volume fraction of SiC particles (10 vol.%) using cold isostatic pressing (CIP). The objective is to obtain a fully dense material with a uniform dispersion of nanoparticles. The SiC particle size impact on the compressibility and density distribution of milled Mg-SiC nanocomposites is studied through the elastoplastic Modified Drucker-Prager Cap (MDPC) model and finite element method (FEM) simulations. The findings demonstrate significant variations in the size and dispersion of SiC particles within the Mg matrix. Specifically, the Mg-SiC nanocomposite with 10% submicron-scale SiC content (M10Sµ) exhibits superior compressibility, higher relative density, increased element volume (EVOL), and more consistent density distribution compared to the composite containing 10% nanoscale SiC (M10Sn) following CIP simulation. Under 700 MPa, M10Sµ shows improvements in both computational and experimental results for volume reduction percentage, 2.31% and 2.81%, respectively, and relative density, 4.14% and 3.73%, respectively, compared to M10Sn. The relative density and volume reduction outcomes are in qualitative alignment with experimental findings, emphasizing the significance of particle size in optimizing nanocomposite characteristics.
P System Design for Integer Factorization
Authors: Nan Hai , Xue Zhijian , Li Chaoyue , Zhou Mingqiang , Liu Xiaoyang
Published: August 2023

Membrane computing is a natural computing branch inspired by the structure of biological cells. The mathematical abstract model of a membrane computing system is called a P System, which is one of the main topics in membrane computing research for the design and verification of a P System. Integer factorization is still a world-class problem and a very important research direction. If a fast method can be found to solve the integer factorization problem, several important cryptographic systems including the RSA public key algorithm will be broken. The aim of this paper is to design a P System capable of implementing integer decomposition, taking advantage of the characteristics of parallelism of P Systems. We construct a process with a main goal to study the modal exponential function f(x) = ax mod N and explore the possible periodic behavior for different values of a. We attempt to compute nontrivial prime factors by the period found and constrain the operation of the P System in polynomial time.
Dynamic Mechanical Characteristics of Horseshoe Tunnel Subjected to Blasting and Confining Pressure
Authors: He Chenglong , Yao Yingkang , Liu Yaqing , Mao Xiang , Chen Qihui
Published: August 2023

The blast loading direction and in-situ stress field have an effect on the destruction process in the surrounding rock around the tunnel. Five blasting directions are considered in the experiment and simulation. The static stress distribution by confining pressure and the superposition stress waves process are discussed by simulation in LS-DYNA. Results indicated that the hoop stress accelerates the radial cracks growing, and the damage around the hole is not influenced by the blasting direction. The stress wave superposition and failure process along the tunnel are affected by the blasting direction. The distribution of static prestress is symmetrical under the uniform confining pressure (k = 1) and decelerates the crack extension by confining pressure. Under the non-uniform confining pressure loading (k ≠ 1), the tensile prestress is formed with a k increase and accelerates the horizontal crack propagation after blast loading. The concentrated stress is serious in the partial region along the tunnel, especially in the vault position under the static-dynamic coupling loading. Notably, the horizontal destruction area between the hole and the tunnel further expands when k increases.
Dominant Partitioning of Discontinuities of Rock Masses Based on DBSCAN Algorithm
Authors: Ruan Yunkai , Liu Weicheng , Wang Tanhua , Chen Jinzi , Zhou Xin , Sun Yunqiang
Published: August 2023

In the analysis of rock slope stability and rock mass hydraulics, the dominant partitioning of discontinuities of rock masses is a very important concept, and it is still a key for establishing the three-dimensional (3-D) network model of random discontinuities. The traditional graphical analysis method is inadequate and greatly influenced by subjective experience. A new method using density-based spatial clustering of applications with noise (DBSCAN) algorithm is proposed for the dominant partitioning of discontinuities of rock mass. In the proposed method, we do not need to determine the centers of every cluster before clustering, and the acnodes or outliers can be eliminated effectively after clustering. Firstly, the spatial coordinate transformation of the discontinuity occurrence is carried out and the objective function is established by using the sine value of the angle of the unit normal vector as the similarity measure standard. The DBSCAN algorithm is used to establish the optimal clustering centers by searching the global optimal solution of the objective function, and the fuzzy C-means clustering algorithm is optimized and the mathematical model of the advantage grouping of rock discontinuities is established. The new method and the fuzzy C-means method are compared and verified by using the artificially randomly generated discontinuity occurrence data. The proposed method is a better method than the fuzzy C-means method in general cases, and it can provide more accurate results by eliminating the acnodes or outliers. Finally, the proposed method is applied to discontinuity orientation partition data at Maji dam site, Nujiang River, and there is good agreement with the in situ measurement.