bluuebunny/crossref_metadata_2025 huggingface dataset:
Feammox Bacterial Biofilms as an Alternative Biological Process for the Removal of Nitrogen from Agricultural Wastewater
Authors: Cerda Ámbar , González Macarena , Rodríguez Carolina , Serrano Jennyfer , Leiva Eduardo
Published: March 2023

The excessive deposition of ammonium (reactive nitrogen) in the environment has led to losses of biodiversity and the eutrophication of ecosystems. Anthropogenic sources contribute twice the natural rate of terrestrial reactive nitrogen and provide about 45% of the total amount of it produced annually on Earth. Recently, a biological process that anaerobically metabolizes ammonium and facilitates iron reduction, termed Feammox, was discovered. The use of Feammox activity together with hollow fiber membrane bioreactors (HFMB), for which the latter are based on the formation of biofilms of bacterial communities, constitutes an efficient and sustainable method for the removal of ammonium from agriculturally derived wastewater. To implement the use of HFMB with Feammox activity, the formation of Feammox bacterial biofilms from wastewater sludge samples from a brewery was evaluated. The cultures were enriched with two different carbon sources, namely, sodium acetate and sodium bicarbonate; then, ferrous iron and ammonium concentrations, which were used as indicators of reactive nitrogen removal, were measured. The measurements revealed that the ammonium removal level reaches 20.4% when sodium acetate is used as carbon source. Moreover, an increase in the ferrous iron concentration of +Δ84.6 mg/L was observed, indicating that Feammox activity had been generated. Biofilm formation was observed under Feammox conditions on the hollow fibers. These results showed that Feammox bacteria can form biofilms and efficiently remove ammonium from wastewater, constituting an essential feature with which to scale up the process to HFMBs. Overall, these results contribute to a better understanding of the Feammox process that can be used to implement these processes in agriculture and thus progress towards a more sustainable industry.
Swine Breeding in the Villages of Vâlcea County, Oltenia (Romania)—Tradition or Necessity?
Authors: Teodorescu Camelia , Burcea Marin , Lequeux-Dincă Ana-Irina , Merciu Florentina-Cristina , Jipa Adrian-Nicolae , Szemkovics Laurenţiu-Ştefan
Published: March 2023

Food supply has been a constant source of concern for mankind. In the present context, with food security a priority of European and national policies, an analysis of pig farming in a representative NUTS2 administrative level of Romania that emphasizes the proportion of households raising at least one pig and the main factors influencing farmers to adopt or give up swine breeding could allow a much clearer understanding of this phenomenon that lies at the border between cultural tradition and socio-economic necessity. This study uses mixed methods that complement each another to help reveal this complex phenomenon in the analyzed territory. Cluster analysis shows the concentration of swine breeding and maps its spread in terms of both subsistence and larger farms, and qualitative interviews prove the motivation of farmers to continue in this occupation. As a primary result, the study visualizes the spatial distribution of pig farming in the rural environment of Vâlcea county, Romania, from a diachronic perspective in the post-communist period. It also reveals areas of differing concentrations of both very small-sized farms, which prioritize meeting their own food needs, and larger farms, which prioritize commercial production to supplement their revenue streams. Both categories, but particularly the latter, are of particular interest in a period in which the socio-economic environment after 1990—marked by economic restructuring, unemployment, population migration, the economic crisis of 2008–2010, the pandemic of 2020–2021, and the most recent energy crisis—periodically highlights the importance of rural areas in ensuring food security and sufficiency at both the local and regional levels.
Assessment of Photoperiod Sensitivity and the Effect of Sowing Date on Dry-Season Sorghum Cultivars in Southern Chad
Authors: Naoura Gapili , Emendack Yves , Sawadogo Nerbéwendé , Djirabaye Nadjiam , Tabo Ramadjita , Laza Haydee , Atchozou Eyanawa A.
Published: March 2023

The cultivation of dry-season sorghum on residual moisture in West and Central Africa is highly affected by sowing dates and ecotypes used. Fifty-five dry-season sorghum ecotypes collected from three zones in southern Chadian were sown on two dates, early and late, in 2013 and 2014, in an α-Lattice, and replicated five times to evaluate the effect of sowing date on potential yield, flowering time, and other agro-morphological traits and to determine their photoperiod sensitivity. Trials were conducted in the research fields at the Agricultural Research Extension Farm in Youé, Chad. Year, sowing date, and their interaction significantly affected most of the assessed traits. Delaying sowing significantly decreased potential yield, duration of vegetative phase, and other agro-morphological traits, except staygreen. All cultivars were photoperiodic with late sowing requiring a lower cumulative growing degree unit to flower. The flowering window was not affected by sowing dates across cultivars; however, the flowering time was affected by a decrease in daylength, but not low night temperatures. Generally, late sowing decreased potential yield across cultivars. However, this decrease varied with the region of origin, with seven cultivars having average potential yields at or above the regional potential yield of 1 t/ha, irrespective of year or sowing dates.
Spectral Quantitative Analysis and Research of Fusarium Head Blight Infection Degree in Wheat Canopy Visible Areas
Authors: Chen Yanyu , Wang Xiaochan , Zhang Xiaolei , Sun Ye , Sun Haiyan , Wang Dezhi , Xu Xin
Published: March 2023

Obtaining complete and consistent spectral images of wheat ears in the visible areas of in situ wheat canopies poses a significant challenge due to the varying growth posture of wheat. Nevertheless, detecting the presence and degree of wheat Fusarium head blight (FHB) in situ is critical for formulating measures that ensure stable grain production and supply while promoting green development in agriculture. In this study, a spectral quantitative analysis model was developed to evaluate the infection degree of FHB in an in situ wheat canopy’s visible areas. To achieve this, a spectral acquisition method was used to evaluate the infection degree of FHB in a wheat canopy’s visible areas. Hyperspectral images were utilized to obtain spectral data from healthy and mildly, moderately, and severely infected wheat ear canopies. The spectral data were preprocessed, and characteristic wavelengths were extracted using twelve types of spectral preprocessing methods and four types of characteristic wavelength extraction methods. Subsequently, sixty-five spectral quantitative prediction models for the infection degree of FHB in the in situ wheat canopy visible areas were established using the PLSR method, based on the original spectral data, preprocessed spectral data, original spectral characteristic wavelengths extracted data, and preprocessed spectral characteristic wavelengths extracted data. Comparative analysis of the models indicated that the MMS + CARS + PLSR model exhibited the best prediction effect and could serve as the spectral quantitative analysis model for the evaluation of the infection degree of FHB in an in situ wheat canopy’s visible areas. The model extracted thirty-five characteristic wavelengths, with a modeling set coefficient of determination (R2) of 0.9490 and a root-mean-square error (RMSE) of 0.2384. The testing set of the coefficient of determination (R2) was 0.9312, with a root-mean-square error (RMSE) of 0.2588. The model can facilitate the spectral quantitative analysis of the infection degree of FHB in the in situ wheat canopy visible areas, thereby aiding in the implementation of China’s targeted poverty alleviation and agricultural power strategy.
Integration Vis-NIR Spectroscopy and Artificial Intelligence to Predict Some Soil Parameters in Arid Region: A Case Study of Wadi Elkobaneyya, South Egypt
Authors: El-Sayed Moatez A. , Abd-Elazem Alaa H. , Moursy Ali R. A. , Mohamed Elsayed Said , Kucher Dmitry E. , Fadl Mohamed E.
Published: March 2023

Understanding and determining soil properties is reflected in improving farm management and crop production. Soil salinity, pH and calcium carbonate are among the factors affecting the soil’s physical and chemical properties. Hence, their estimation is very important for agricultural management, especially in arid regions (Wadi Elkobaneyya valley, located in the northwest of Aswan Governorate, Upper Egypt). The study objectives were to characterize and develop prediction models for soil salinity, pH and calcium carbonate (CaCO3) using integration soil analysis and spectral reflectance vis-NIR spectroscopy. To achieve the study objectives, three multivariate regression models: Partial Least Squares Regression (PLSR), Multivariate Adaptive Regression Splines (MARS) and Least Square-Support Vector Regression (LS-SVR)); and two machine learning algorithms, Random Forest (RF) and Artificial Neural Networks (ANN) were used. Ninety-six surface soil samples were collected from the study area at depths 0–5 cm. The data were divided into a calibration dataset (70% of the total) and a validation dataset (30% of the total dataset). The obtained results represent that the PLSR model was the best model for soil pH parameters where R2 of calibration and validation predictability = 0.68 and 0.52, respectively. The LS-SVR model was the best model to predict soil Electrical Conductivity (EC) and soil Calcium Carbonate (CaCO3) content, with R2 0.70 and 0.74 for calibration and R2 0.26 and 0.47 for validation, respectively. On the other hand, the results of the implemented machine learning algorithm model showed that RF was the best model to predict soil pH and CaCO3, as the R2 was 0.82 for calibration and 0.57 for validation, respectively. Nevertheless, the best model for predicting soil EC was ANN, with an R2 of 0.96 for calibration and 64 for validation. The results show the advantages of machine learning models for predicting soil EC, pH and CaCO3 by Vis-NIR spectroscopy. Therefore, Vis-NIR spectroscopy is considered faster and more cost-efficient and can be further used in environmental monitoring and precision farming.
Identification and Analysis of the Catalase Gene Family Response to Abiotic Stress in Nicotiana tabacum L.
Authors: Liu Zhonghui , Wang Di , Tang Heng , Li Haozhen , Zhang Xiaohua , Dong Shaolin , Zhang Li , Yang Long
Published: March 2023

Catalase (CAT) is an enzyme encoded by the catalase gene family that plays an important role in the removal of reactive oxygen species. In this study, seven CAT genes were identified in Nicotiana tabacum L. and were classified into three groups. Gene structure analysis revealed that NtCAT1–6 has six or seven introns while NtCAT7 only contains one. The relative position of introns in NtCAT1 and NtCAT2 had high similarity. Tissue-specific analysis shows that NtCAT1–4 were expressed intensively in the shoot while NtCAT5 and NtCAT6 were in the root. NtCAT7 expression was influenced by circadian rhythms. NtCATs expression had the greatest change under drought stress. Additionally, expression of NtCAT5, NtCAT6 and NtCAT7 were upregulated under cold stress but downregulated under drought and salt stress. This study will help in understanding the behavior of CAT genes during environmental stress in tobacco.
Very Early Biomarkers Screening for Water Deficit Tolerance in Commercial Eucalyptus Clones
Authors: Corrêa Thais R. , Picoli Edgard Augusto de T. , Pereira Washington Luiz , Condé Samyra A. , Resende Rafael T. , de Resende Marcos Deon V. , da Costa Weverton Gomes , Cruz Cosme Damião , Zauza Edival Angelo V.
Published: March 2023

The identification of genotypes more tolerant to water deficit is a challenge to breeding programs. In this research, our objectives were to identify and validate traits for tolerance to water deficit in eucalypts. The estimation of genotypic parameters and early selection are proposed based on mixed models, selection indexes and validation schemes. Seedlings with 110 days were grown in a greenhouse for 12 weeks, and two water deficit treatments were conducted (polyethylene glycol and water limitation). A total of 26 biomarkers were evaluated, and 15 of them were significant, exhibited adequate heritability, and used for screening: final plant height, increment in height, increment in diameter, area of mature and fully expanded leaf, nutrient contents of N, K, Ca, Mg, S, Cu, Zn, Mn and B, photosynthesis (A) and stomatal conductance (gs). Both treatments were adequate to discriminate water deficit-tolerant clones. The ranking of tolerant clones according to their phenotype in the field demonstrates the potential for early selection and is consistent with the maintenance of water-deficit-tolerance mechanisms until adulthood. There is evidence that the choice of biomarker depends on the species involved and different strategies contributing to the tolerance trait.
Greywater Vertical Treatment and Possibility of Reuse in the Fields from Peri-Urban Area
Authors: Filali Hanen , Barsan Narcis , Hörmann Georg , Nedeff Valentin , Irimia Oana , Nedeff Florin , Hachicha Mohamed
Published: March 2023

This study highlighted the potential for greywater reuse in irrigation of olive trees. An experimental field was set up in a household of Soukra, located northwest of Tunis City, to test the performance of vertical greywater treatment. Treated greywater (TGW) was used for the irrigation of two olive tree varieties (Chétoui and Picholine) during five years. The results show high performance of the treatment, as reflected by the good quality of TGW. The chemical and biological parameters of this TGW are under the threshold values of the Tunisian Norms of Treated Wastewaters for agriculture use (NT106.03). The BOD5 average decreased from 160.44 mg O2/L for UGW (Untreated greywater) to 15.32 mg O2/L for TGW. The COD average recorded a high reduction from 290.15 mg O2/L for UGW to 49.58 mg O2/L for TGW. The average removal rate was 90% for BOD5 and 83% for COD, proving the high performance of the treatment. The average increases in height, diameter, and olive production are significantly high for the two varieties of olive trees irrigated with treated greywater (ITGW), compared to those not irrigated and under natural conditions. In this regard, the present study has shown promising potentials for the reuse of TGW in agriculture.
Short-Term Co-Application of Organic and Chemical Fertilizer Benefits Topsoil Properties and Maize Productivity in a Medium-Productivity Meadow-Cinnamon Soil
Authors: Zhai Lichao , Zheng Mengjing , Zhang Lihua , Chen Jing , Zhang Jingting , Jia Xiuling
Published: March 2023

Co-application of organic-chemical fertilizer (CAOFCF) has attracted wide attention in China in recent years. However, its short-term effect on topsoil quality and maize yield in a medium-productivity meadow-cinnamon soil is not clear. In order to address this problem, a 3-year (2019–2021) field trial was established by arranging the following five treatments: (1) CF, applying chemical fertilizer alone; (2) OFCF1, 15% organic fertilizer + 85% chemical fertilizer; (3) OFCF2, 30% organic fertilizer + 70% chemical fertilizer; (4) OFCF3, 45% organic fertilizer + 55% chemical fertilizer; (5) OFCF4, 60% organic fertilizer + 40% chemical fertilizer. The results showed that short-term CAOFCF treatments were beneficial to the topsoil aggregate stability by increasing the percentage and mean weight diameter of macro-aggregate in topsoil. In addition, lower soil bulk density and higher soil organic carbon sequestration in topsoil were observed under the CAOFCF treatments. There was no difference in rhizosphere microbial diversity among all treatments. Compared to CF, OFCF1 and OFCF2 improved the activities of some key enzymes, including sucrase, urease, and acid phosphatase. Moreover, higher relative abundance of Actinobacteria and Chloroflexi were observed under the CAOFCF treatments. The root-shoot dry matter and maize grain yield were obviously higher in OFCF1 and OFCF2 than in CF; however, no significant difference was found in the OFCF3 and OFCF4 treatments compared to CF. The analysis of correlation suggested that there were no direct correlations between maize yield and various soil indexes measured. Nevertheless, root dry weight and root-shoot ratio were positively correlated with the activities of urease and sucrase. Meanwhile, the relationships between root dry weight, root-shoot ratio, shoot dry weight, and grain yield were all significant. In conclusion, short-term co-application of organic and chemical fertilizer (i.e., replacing 15–30% chemical fertilizer with organic fertilizer with an equal N rate) was beneficial to soil properties and maize grain yield in a medium-productivity meadow-cinnamon soil. The higher grain yield was associated with a strong maize root system, which was driven by the improved rhizosphere urease and sucrase activities.
Integrated Proteomic and Metabolomic Analysis of Cassava cv. Kasetsart 50 Infected with Sri Lankan Cassava Mosaic Virus
Authors: Siriwan Wanwisa , Vannatim Nattachai , Chaowongdee Somruthai , Roytrakul Sittiruk , Charoenlappanit Sawanya , Pongpamorn Pornkanok , Paemanee Atchara , Malichan Srihunsa
Published: March 2023

Cassava mosaic disease (CMD) is a major disease affecting cassava production in Southeast Asia. This study aimed to perform an integrated proteomics and metabolomics analysis of cassava cv. Kasetsart 50 infected with Sri Lankan cassava mosaic virus (SLCMV). Proteomics analyses revealed that 359 proteins were enriched in the plant–pathogen interaction, plant hormone signal transduction, and MAPK signaling pathways. A total of 79 compounds were identified by metabolomics analysis of the healthy and SLCMV-infected cassava plants. Integrated omics analysis revealed that 9 proteins and 5 metabolites were enriched in 11 KEGG pathways. The metabolic pathways, plant hormone signal transduction, and plant–pathogen interaction pathway terms were specifically investigated. The findings revealed that caffeic acid and chlorogenic acid were associated with the plant–pathogen interaction pathway, histidine (HK3) was involved in plant hormone signal transduction, while citric acid and D-serine were associated with the metabolic pathways. KEGG functional enrichment analysis revealed that plant–pathogen interaction, plant hormone signal transduction, and metabolic pathways were linked via the enriched protein (protein phosphatase 2C) and metabolites (cyclic nucleotide-binding (AT2G20050) and D-serine). The available information and resources for proteomics and metabolomics analyses of cassava can elucidate the mechanism of disease resistance and aid in cassava crop improvement programs.
Analysis of the Genetic Parameters for Dairy Linear Appraisal and Zoometric Traits: A Tool to Enhance the Applicability of Murciano-Granadina Goats Major Areas Evaluation System
Authors: Fernández Álvarez Javier , Navas González Francisco Javier , León Jurado Jose Manuel , Iglesias Pastrana Carlos , Delgado Bermejo Juan Vicente
Published: March 2023

Selection for zoometrics defines individuals’ productive longevity, endurance, enhanced productive abilities and consequently, their long-term profitability. When zoometric analysis is aimed at large highly selected populations or in those at different levels of selection, linear appraisal systems (LAS) provide a timely response. This study estimates genetic and phenotypic parameters for zoometric/LAS traits in Murciano-Granadina goats, estimating genetic and phenotypic correlations among all traits, and determining whether major area selection would be appropriate or if adaptability strategies may need to be followed. Heritability estimates for the zoometric/LAS traits were low to high, ranging from 0.09 to 0.43, and the accuracy of estimation has improved after decades, rendering standard errors negligible. Scale inversion of specific traits may need to be performed before major areas selection strategies are implemented. Genetic and phenotypic correlations suggests that negative selection against thicker bones and higher rear insertion heights indirectly results in the optimization of selection practices in the rest of the traits, especially those in the structure, capacity and mammary system major areas. The integration and implementation of the strategies proposed within the Murciano-Granadina breeding program maximizes selection opportunities and the sustainable international competitiveness of the Murciano-Granadina goat in the dairy goat breed panorama.
The Mechanisms of BDNF Promoting the Proliferation of Porcine Follicular Granulosa Cells: Role of miR-127 and Involvement of the MAPK-ERK1/2 Pathway
Authors: Zheng Xue , Chen Lu , Chen Tong , Cao Maosheng , Zhang Boqi , Yuan Chenfeng , Zhao Zijiao , Li Chunjin , Zhou Xu
Published: March 2023

As a member of the neurotrophic family, brain-derived neurotrophic factor (BDNF) provides a key link in the physiological process of mammalian ovarian follicle development, in addition to its functions in the nervous system. The emphasis of this study lay in the impact of BDNF on the proliferation of porcine follicular granulosa cells (GCs) in vitro. BDNF and tyrosine kinase B (TrkB, receptor of BDNF) were detected in porcine follicular GCs. Additionally, cell viability significantly increased during the culture of porcine GCs with BDNF (100 ng/mL) in vitro. However, BDNF knockdown in GCs decreased cell viability and S-phase cells proportion—and BDNF simultaneously regulated the expression of genes linked with cell proliferation (CCND1, p21 and Bcl2) and apoptosis (Bax). Then, the results of the receptor blocking experiment showed that BDNF promoted GC proliferation via TrkB. The high-throughput sequencing showed that BDNF also regulated the expression profiles of miRNAs in GCs. The differential expression profiles were obtained by miRNA sequencing after BDNF (100 ng/mL) treatment with GCs. The sequencing results showed that, after BDNF treatment, 72 significant differentially-expressed miRNAs were detected—5 of which were related to cell process and proliferation signaling pathways confirmed by RT-PCR. Furthermore, studies showed that BDNF promoted GCs’ proliferation by increasing the expression of CCND1, downregulating miR-127 and activating the ERK1/2 signal pathway. Moreover, BDNF indirectly activated the ERK1/2 signal pathway by downregulating miR-127. In conclusion, BDNF promoted porcine GC proliferation by increasing CCND1 expression, downregulating miR-127 and stimulating the MAPK-ERK1/2 signaling cascade.
Blood Gas, Acid-Base and Electrolyte Analysis in Healthy Dromedary Camel Calves up to 21 Days of Life
Authors: Osman Taher , Probo Monica , Monaco Davide , Shafiek Hazem Karem , Freccero Francesca
Published: March 2023

The importance of prompt evaluation and care of the newborn is essential for reducing neonatal mortality, which represents a major cause of loss in camelids. This study investigated the blood gases, acid-base and electrolyte profiles in healthy dromedary calves during the first 3 weeks of life, assessing possible associations with age. Twenty-one dromedary camel calves aged 1 to 21 days were sampled, and venous whole blood analyzed through a VETSTAT® analyzer. The following parameters were measured: sodium (Na+), potassium (K+), chloride (Cl–), hydrogen ion concentration (pH), partial pressure carbon dioxide (pCO2), partial pressure oxygen (pO2), total hemoglobin concentration (tHb), hemoglobin oxygen saturation (sO2), total carbon dioxide (tCO2), bicarbonate (HCO3–), base excess (BE) and anion gap (AG). Calves were divided in two groups; younger calves (1–10 d), and older calves (11–21 d). Statistical analysis showed an effect of age, with lower K+ (p < 0.001) and higher Na+ and Cl− (p < 0.05) mean concentrations in the younger calves compared to the older ones, and higher pCO2 and lower sO2 mean concentrations in the older group. These preliminary results firstly described the blood gas, acid-base and electrolyte profiles in the healthy dromedary calf during the first 3 weeks of age, suggesting an effect of age on some parameters.
Detection of Selected Canine Viruses in Nigerian Free-Ranging Dogs Traded for Meat Consumption
Authors: Ndiana Linda A. , Lanave Gianvito , Desario Costantina , Odigie Amienwanlen E. , Madubuike Kelechi G. , Lucente Maria Stella , Ezeifeka Chukwuemeka A. , Patruno Giovanni , Lorusso Eleonora , Elia Gabriella , Buonavoglia Canio , Decaro Nicola
Published: March 2023

Animal trade favors the spreading of emerging and re-emerging pathogens. Concerns have been previously expressed regarding the risks of dog trade in spreading zoonotic pathogens in Nigeria. However, the role of these dogs in disseminating highly pathogenic canine viruses has not yet been explored. The present study aimed to identify selected canine viruses in dogs traded for meat consumption in Nigeria. A total of 100 blood samples were screened for carnivore protoparvovirus-1 (CPPV-1), canine adenovirus 1/2 (CAdV-1/2), canine circovirus (CaCV), and canine distemper virus (CDV) by using real-time PCR and conventional PCR and/or sequencing. CPPV-1 DNA was identified in 83% of canine samples while CaCV DNA and CDV RNA were detected in 14% and 17% of the dog samples, respectively. None of the dogs tested positive for CAdV-1/2. The CaCVs identified in this study clustered along with other European, Asian, and American strains. Moreover, CDV strains identified in Nigeria clustered in a separate lineage with the closest genetic relatedness to the Europe–South America-1 clade. Further surveys prior to and after arrival of dogs at the slaughtering points are required to clarify the real virus burden in these animals.
Housing Conditions Affect Adult Zebrafish (Danio rerio) Behavior but Not Their Physiological Status
Authors: Jorge Sara , Félix Luís , Costas Benjamín , Valentim Ana M.
Published: March 2023

Zebrafish is a valuable model for neuroscience research, but the housing conditions to which it is exposed daily may be impairing its welfare status. The use of environmental enrichment and the refinement of methodology for cortisol measurement could reduce stress, improving its welfare and its suitability as an animal model used in stress research. Thus, this study aimed to evaluate (I) the influence of different housing conditions on zebrafish physiology and behavior, and (II) skin mucus potential for cortisol measurement in adult zebrafish. For this, AB zebrafish were raised under barren or enriched (PVC pipes and gravel image) environmental conditions. After 6 months, their behavior was assessed by different behavioral paradigms (shoaling, white-black box test, and novel tank). The physiological response was also evaluated through cortisol levels (whole-body homogenates and skin mucus) and brain oxidative stress markers. The results revealed that enriched-housed fish had an increased nearest neighbors’ distance and reduced activity. However, no effect on body length or stress biomarkers was observed; whole-body and skin mucus cortisol levels had the same profile between groups. In conclusion, this study highlights the skin mucus potential as a matrix for cortisol quantification, and how housing conditions could influence the data in future studies.
Applications of Technology to Record Locomotion Measurements in Dairy Cows: A Systematic Review
Authors: Bradtmueller Anna , Nejati Amir , Shepley Elise , Vasseur Elsa
Published: March 2023

Lameness within the dairy industry is a concern because of its associated costs and welfare implications. Visual locomotion scoring has been commonly used for assessing cows’ locomotion quality, but it can have low reliability and is relatively subjective compared to automated methods of assessing locomotion. Kinematic, kinetic, and accelerometric technologies can provide a greater number of more detailed outcome measurements than visual scoring. The objective of this systematic review was to determine outcome measurements, and the relationships between them, that have been recorded using kinematic, kinetic, and accelerometric technologies, as well as other approaches to evaluating cow locomotion. Following PRISMA guidelines, two databases were searched for studies published from January 2000 to June 2022. Thirty-seven articles were retained after undergoing a screening process involving a title and abstract evaluation, followed by a full-text assessment. Locomotion measurements recorded using these technologies often overlapped, but inconsistencies in the types of technology, the arrangement of equipment, the terminology, and the measurement-recording approaches made it difficult to compare locomotion measurements across studies. Additional research would contribute to a better understanding of how factors regarding the health, environment, and management of dairy cows affect aspects of locomotion, as recorded through the detailed, objective outcome measurements provided by these technologies.
The Effect of Encapsulated Propyl Propane Thiosulfonate (PTSO) on Apparent Ileal Digestibility and Productive Performance in Broiler Chickens
Authors: Villar-Patiño Gonzalo , Camacho-Rea María del Carmen , Olvera-García Myrna Elena , Soria-Soria Arturo , Baltazar-Vázquez Julio César , Gómez-Verduzco Gabriela , Solano Lourdes , Téllez Guillermo , Ramírez-Pérez Aurora Hilda
Published: March 2023

This study analyzed the effects of different dietary doses of encapsulated propyl propane thiosulfonate (Pe-PTSO) on the apparent ileal digestibility (AID) of nutrients and productive performance in broilers. A total of 100 one-day-old Cobb 500 were housed in battery cages for 20 days. At 10 days of age, the birds were assigned to one of five diets: negative control (P0), 250 mg/kg of Pe-PTSO (P250), 500 mg/kg of Pe-PTSO (P500), 750 mg/kg of Pe-PTSO (P750), and positive control, nicarbazin–narasin (ION). Titanium dioxide was the external marker, which was added to the diets from day 17 to 20. In the birds fed the P250 diet, there was a significant difference (p ≤ 0.05) in the AID values for amino acids and energy compared to those that consumed the P0 diet. Furthermore, the P250 diet significantly increased (p ≤ 0.05) the average daily weight gain compared to the P0 diet. No significant differences were observed between treatments in average daily feed intake and feed conversion ratio. In summary, the inclusion of 250 mg of encapsulated PTSO per kg in broiler chickens diet improved the digestibility of amino acids and energy, as well as weight gain.
Advanced Processing of Giant Kelp (Macrocystis pyrifera) for Protein Extraction and Generation of Hydrolysates with Anti-Hypertensive and Antioxidant Activities In Vitro and the Thermal/Ionic Stability of These Compounds
Authors: Biparva Paniz , Mirzapour-Kouhdasht Armin , Valizadeh Shahriyar , Garcia-Vaquero Marco
Published: March 2023

In this study, giant kelp was explored under various conventional and ultrasound-assisted extraction (UAE) conditions for the extraction of protein, its hydrolysis, and ultrafiltration to generate multiple fractions. The amino acid composition of all the fractions and their biological activities in vitro, including angiotensin-converting enzyme I (ACE) inhibitory activity and antioxidant activities (2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging, reducing power (RP), and ferrous chelating (FC) activities) were tested by storing the compounds for 2 weeks at various temperatures (−20–60 °C) and pHs (2–11) to elucidate their thermal and ionic stability, respectively. The yield of protein extraction using the conventional method was lower (≈39%) compared to the use of UAE (150 W, 15 min), which achieved protein recoveries of approximately 60%. After enzymatic hydrolysis and ultrafiltration, low-molecular-weight (MW) hydrolysates had the highest levels of ACE inhibitory (80%), DPPH (84%), RP (0.71 mM trolox equivalents), and FC (81%) activities. Amino acids associated with peptides of high biological activities, such as Val, Ala, Asx, Gly, Lys, Met, Leu, and His, were at higher levels in the low MW fraction compared to any other sample. The biological activities in vitro of all the samples fluctuated under the multiple storage conditions studied, with the highest stability of all the samples appreciated at −20 °C and pH 7. This study shows for the first time the use of giant kelp as a promising source of bioactive peptides and indicates the optimum processing and storing conditions for the use of these compounds as nutraceuticals or functional foods that could help in the prevention of cardiovascular disorders and multiple chronic diseases associated with oxidative damage.
Electro-Thermal Properties of Carbon-Fiber-Reinforced Mortar Prisms
Authors: Son Jung-Young , Kim Jung , Venkel Tetiana , Park Jongun , Heo Gwanghee
Published: March 2023

The thermal properties of electrically heated carbon-fiber-reinforced mortar prisms with 0.5%, 1.0%, 1.5% and 2.0% of their volumes are investigated. Each prism dimension is 40 mm × 40 mm × 160 mm. When the constant power of 30W is applied to two conductive-gel strips painted on the prisms’ surfaces as the electrodes, for 5 min, the prisms show that: (1) their surface heating patterns have mostly the shape of two semi-circles centered at each of the electrodes; (2) their surface temperatures increase more for those with higher fiber percentages; (3) their surface’s average temperature increments are the highest for the first 1 min of heating; (4) the lines representing the lowest and highest temperature zones and one of the normal lines to two electrodes record the highest temperature increment for the first 1 min of heating; (5) the temperature ratio of two points on the surface of each of four different percentage prisms has almost an unchanging value for all heating time periods especially when the two points are close to the volume defined by two electrodes; (6) the average temperature increments decrease with time. These facts are for all percentage prisms.
Segmentation Agreement and AI-Based Feature Extraction of Cutaneous Infrared Images of the Obese Abdomen after Caesarean Section: Results from a Single Training Session
Authors: Childs Charmaine , Nwaizu Harriet , Voloaca Oana , Shenfield Alex
Published: March 2023

Background: Infrared thermography in women undergoing caesarean section has promise to identify a surgical site infection prodrome characterised by changes in cutaneous perfusion with concomitant influences on temperature distribution across the abdomen. This study was designed to compare abdominal and wound regions of interest (ROI) and feature extraction agreement between two independent users after a single training session. Methods: Image analysis performed manually in MATLAB with each reviewer ‘blind’ to results of the other. Image ROIs were annotated via pixel-level segmentation creating pixel masks at four time-points during the first 30 days after surgery. Results: A total of 366 matched image pairs (732 wound and abdomen labels in total) were obtained. Distribution of mask agreement using Jacquard similarity co-efficient ranged from 0.35 to 1. Good segmentation agreement (coefficient ≥ 0.7) (for mask size and shape) was observed for abdomen, but poor for wound (coefficient < 0.7). From feature extraction, wound cold spots were observed most in those who later developed wound infections. Conclusions: Reviewer performance, with respect to the input (image) data in the first stage of algorithm development, reveals a lack of correspondence (agreement) of the ROI indicating the need for further work to refine the characteristics of output labels (masks) before an unsupervised algorithm works effectively to learn patterns and features of the wound.
Target Detection and Recognition for Traffic Congestion in Smart Cities Using Deep Learning-Enabled UAVs: A Review and Analysis
Authors: Iftikhar Sundas , Asim Muhammad , Zhang Zuping , Muthanna Ammar , Chen Junhong , El-Affendi Mohammed , Sedik Ahmed , Abd El-Latif Ahmed A.
Published: March 2023

In smart cities, target detection is one of the major issues in order to avoid traffic congestion. It is also one of the key topics for military, traffic, civilian, sports, and numerous other applications. In daily life, target detection is one of the challenging and serious tasks in traffic congestion due to various factors such as background motion, small recipient size, unclear object characteristics, and drastic occlusion. For target examination, unmanned aerial vehicles (UAVs) are becoming an engaging solution due to their mobility, low cost, wide field of view, accessibility of trained manipulators, a low threat to people’s lives, and ease to use. Because of these benefits along with good tracking effectiveness and resolution, UAVs have received much attention in transportation technology for tracking and analyzing targets. However, objects in UAV images are usually small, so after a neural estimation, a large quantity of detailed knowledge about the objects may be missed, which results in a deficient performance of actual recognition models. To tackle these issues, many deep learning (DL)-based approaches have been proposed. In this review paper, we study an end-to-end target detection paradigm based on different DL approaches, which includes one-stage and two-stage detectors from UAV images to observe the target in traffic congestion under complex circumstances. Moreover, we also analyze the evaluation work to enhance the accuracy, reduce the computational cost, and optimize the design. Furthermore, we also provided the comparison and differences of various technologies for target detection followed by future research trends.
Tiling Photonic Topological Insulator for Laser Applications
Authors: Kim Petr N. , Fedchenko Dmitry P. , Rudakova Natalya V. , Timofeev Ivan V.
Published: March 2023

A photonic topological insulator is a structure that isolates radiation in the bulk rather than at the edge (surface). Paradoxically, applications of such an insulator focus on its conducting edge states, which are robust against structural defects. We suggest a tiling photonic topological insulator constructed from identical prism resonators connected to each other. The light beam circulates inside the tiling bulk without propagation. However, we experimentally demonstrate a topologically-protected propagating state due to the disconnected faces of the edge resonators. The investigated state is robust against removing or attaching prism resonators. Moreover, the protection principle is phase-free and therefore highly scalable both in wavelength and resonator size. The tiling is suggested for active topological photonic devices and laser arrays.
Forest, Crop and Grassland Leaf Area Index Estimation Using Remote Sensing: A Review of Current Research Methods, Sensors, Estimation Models and Accomplishments
Authors: Mthembu Nokukhanya , Lottering Romano , Kotze Heyns
Published: March 2023

Leaf area index (LAI) is an important parameter in plant ecophysiology; it can be used to quantify foliage directly and as a measure of the photosynthetic active area and, thus, the area subject to transpiration in vegetation. The aim of this paper was to review work on remote sensing methods of estimating LAI across different forest ecosystems, crops and grasslands in terms of remote sensing platforms, sensors and models. To achieve this aim, scholarly articles with the title or keywords “Leaf Area Index estimation” or “LAI estimation” were searched on Google Scholar and Web of Science with a date range between 2010 and 2020. The study’s results revealed that during the last decade, the use of remote sensing to estimate and map LAI increased for crops and natural forests. However, there is still a need for more research concerning commercial forests and grasslands, as the number of studies remains low. Of the 84 studies related to forests, 60 were related to natural forests and 24 were related to commercial forests. In terms of model types, empirical models were most often used for estimating the LAI of forests, followed by physical models.
Model-Based Deep Reinforcement Learning with Traffic Inference for Traffic Signal Control
Authors: Wang Hao , Zhu Jinan , Gu Bao
Published: March 2023

In the modern world, the extremely rapid growth of traffic demand has become a major problem for urban traffic development. Continuous optimization of signal control systems is an important way to relieve traffic pressure in cities. In recent years, with the impressive development of deep reinforcement learning (DRL), some DRL approaches have started to be applied to traffic signal control. Unlike traditional signal control methods, agents trained using DRL approaches continuously receive feedback from the environment to continuously improve the policy. Since current research in the field is more focused on the performance of the agent, data efficiency during training is ignored to some extent. However, in traffic signal control tasks, the cost of trial and error is very expensive. In this paper, we propose a DRL approach based on a traffic inference model. The proposed traffic inference model is based on the future information given based on upstream intersections and data from the environment to continuously learn the changing patterns of the traffic environment in order to make inferences about changes in the traffic environment. In the proposed algorithm, the inference model interacts with the agent instead of the environment. Through comprehensive experiments based on realistic datasets, we demonstrate that our proposed algorithm is superior to other algorithms in terms of its data efficiency and stronger performance.
Research of Peak Searching Technology for Separating Lithium from Coal Based on XRD Pattern
Authors: Jiang Xiaoping , Liu Yurong , Xiu Tianning
Published: March 2023

X-ray diffraction technology (XRD) is one of the common means of mineral separation, and peak identification and comparison is a key step. The symmetric zero-area conversion method (SZAC) performs well in peak searching of spectral lines, but its wide application is limited by problems such as inaccurate identification results in specific scenes and dependence of parameter selection on spectral data. In this article, an improved symmetric zero-area conversion method (ISZAC) is proposed by combining the ideas of data fusion and passive anti-counterfeiting. The comparison method and flat peak screening were introduced, and the function group was designed to convert the spectral data after background deduction and intensity screening. The results were fused to obtain the peak address determination. Simulation and experimental results show that the improved method has higher accuracy and applicability. In addition, the method is easy to expand, and the conversion function group can be adjusted according to the spectral data characteristics to improve the recognition efficiency.
Analysis of Cleaner Production Performance in Manufacturing Companies Employing Artificial Neural Networks
Authors: Penchel Rafael Abrantes , Aldaya Ivan , Marim Lucas , dos Santos Mirian Paula , Cardozo-Filho Lucio , Jegatheesan Veeriah , de Oliveira José Augusto
Published: March 2023

Cleaner production has emerged as a comprehensive paradigm, aiming to reduce, or even avoid, the environmental impact in the production stage, in a broad variety of fields. However, the great number of interacting factors makes the assessment of efficiency and the identification of critical factors pose significant challenges to researchers and companies. Artificial intelligence and, particularly, artificial neural networks have proven their suitability to lead with diverse multi-variable problems, but have not yet been applied to model production systems. In this work, we employ dimensionality reduction in combination with a fully connected feed-forward multi-layer perceptron to model the relation between the input (cleaner production techniques) and output variables (cleaner production performance) and, subsequently, quantify the sensibility of the different output variables on the input variables. In particular, we consider Product Design, Production Processes, and Reuse as the input latent variables, whereas the Environmental Performance of Product, Environmental Performance of Processes, and Economic Performance comprises the output variables of our model. The results, employing data collected from a direct survey of 205 Brazilian companies, reveal that the best configuration for the ANN uses eight neurons in the hidden layer. Regarding sensitivity, the obtained results show that improving practices with poor marks leads to a higher enhancement of output figures. In particular, since reuse presents mainly low marks, it can be identified as an area for improvement, in order to increase overall performance.
A Demographic Characteristics-Based Study on the Visual Impact Assessment of the External Form of Entrance Pavilions to the Underground Stations of China’s Subway
Authors: Li Guanjun , Han Chenping , Shen Jiamin , Wang Xinyu , Gu Tao , Yang Zhongju , Zhang Lin
Published: March 2023

The subway is one of urban residents’ main means of public transportation. The design of entrance pavilions to subway stations has shown a diverse development trend over time. Since most of the subway building space is underground, it is very difficult for subway users or the public to view the structure fully. In this instance, the ground-level entrance pavilion becomes the most eye-catching element in the subway system. From the perspective of the urban spatial environment, the external form of entrance pavilions is one of the components of urban architecture. The design of the external form of entrance pavilions has an important impact on the urban spatial form and affects people’s feelings about the urban space. Therefore, it is essential to study the external form of entrance pavilions. This study investigated 42 subway entrance pavilions in 17 cities in China. The following features were studied: exterior contour, façade permeability, cultural characteristics, decorative materials, and the number of exterior colors. The photostimulation method was adopted to evaluate the influence of the physical features of the external form of the entrance pavilions on respondents’ visual impact assessment. The data analysis showed that respondents with different demographic characteristics provided different visual impact assessments of the external form of the entrance pavilions, and all five physical features influenced their assessment. This study offers a valuable reference for constructing entrance pavilions and urban spaces in Chinese cities in the future.
The Biomechanical Effects of Cross-Legged Sitting on the Lower Limbs and the Implications in Rehabilitation
Authors: Alsirhani Hadeel , Arnold Graham , Wang Weijie
Published: March 2023

Background: While cross-legged-sitting (CLS) posture is widely practised in some communities, its biomechanical effect on the lower limbs is not clear. This study aimed to investigate whether CLS would affect biomechanical parameters in lower limbs during gait. Methods: Thirty healthy volunteers participated in this study and performed CLS on ground for 20 min. Their modes of gait were compared before and after CLS regarding to temporospatial parameters and the kinetic and kinematic parameters in the lower limb joints. Results: CLS significantly increased walking cadence and speed. In kinematics, the ranges of motion for almost all lower limb joints were increased after CLS except the knee in sagittal plane. In kinetics, the medial and lateral forces increased significantly after CLS in the lower limb joints, e.g., the hip posterior force was increased more than 14% on both sides. Furthermore, all hip, knee, and ankle powers were increased significantly after CLS. Conclusion: CLS has a positive impact on the biomechanical parameters of almost all lower limb joints except the knee flexion/extension angle and internal/external joint moments. Therefore, CLS can be used in the daily routine and in any rehabilitation programme to improve the biomechanical parameters of the lower extremities.