bluuebunny/crossref_metadata_2025 huggingface dataset:
Comparative Evaluation of Remote Sensing Platforms for Almond Yield Prediction
Authors: Guimarães Nathalie , Fraga Helder , Sousa Joaquim J. , Pádua Luís , Bento Albino , Couto Pedro
Published: January 2024

Almonds are becoming a central element in the gastronomic and food industry worldwide. Over the last few years, almond production has increased globally. Portugal has become the third most important producer in Europe, where this increasing trend is particularly evident. However, the susceptibility of almond trees to changing climatic conditions presents substantial risks, encompassing yield reduction and quality deterioration. Hence, yield forecasts become crucial for mitigating potential losses and aiding decisionmakers within the agri-food sector. Recent technological advancements and new data analysis techniques have led to the development of more suitable methods to model crop yields. Herein, an innovative approach to predict almond yields in the Trás-os-Montes region of Portugal was developed, by using machine learning regression models (i.e., the random forest regressor, XGBRegressor, gradient boosting regressor, bagging regressor, and AdaBoost regressor), coupled with remote sensing data obtained from different satellite platforms. Satellite data from both proprietary and free platforms at different spatial resolutions were used as features in the study (i.e., the GSMP: 11.13 km, Terra: 1 km, Landsat 8: 30 m, Sentinel-2: 10 m, and PlanetScope: 3 m). The best possible combination of features was analyzed and hyperparameter tuning was applied to enhance the prediction accuracy. Our results suggest that high-resolution data (PlanetScope) combined with irrigation information, vegetation indices, and climate data significantly improves almond yield prediction. The XGBRegressor model performed best when using PlanetScope data, reaching a coefficient of determination (R2) of 0.80. However, alternative options using freely available data with lower spatial resolution, such as GSMaP and Terra MODIS LST, also showed satisfactory performance (R2 = 0.68). This study highlights the potential of integrating machine learning models and remote sensing data for accurate crop yield prediction, providing valuable insights for informed decision support in the almond sector, contributing to the resilience and sustainability of this crop in the face of evolving climate dynamics.
Effects of Polymer Conditioner and Nitrogen Fertilizer Application on Nitrogen Absorption and Utilization of Drip-Irrigated Wheat in Arid Areas
Authors: Hong Dashuang , Chang Doudou , Shao Changlong , Cui Wenli , Lu Xiaoyu , Dong Wen , Fan Hua , Wang Kaiyong , Liu Yantao
Published: January 2024

Nitrogen (N), an important element for crop growth, has a great impact on dry matter weight and yield. Currently, improving N fertilizer use rate is an urgent problem to be solved in agricultural production in the world. In this field experiment, a self-developed water-soluble polymer material (PPM) with water retention and slow-release characteristics was combined with different doses of N fertilizer (N300 (100% N), PN300 (PPM + 100% N), PN240 (PPM + 80% N), PN180 (PPM + 60% N), CK (no N and PPM)) to analyze the impacts on N uptake and use efficiency of wheat plants. The results showed that the combined application of PPM and N fertilizer significantly improved yield, plant height, biomass, and N uptake and use efficiency of drip irrigated wheat, and the PN240 group had the highest N use rate. In addition, the PN300 group had the highest yield. N use efficiency in the PN240 group was 40.23% higher than that in the N300 group. Therefore, the combined application of PPM and N fertilizer, especially PN240, can reduce the N fertilizer application rate by increasing N use efficiency. This study provides technical reference for improving the N use efficiency of drip-irrigated wheat in arid areas.
Benefits of Non-Commercial Urban Agricultural Practices—A Systematic Literature Review
Authors: Boukharta Ouiam Fatiha , Huang Iona Yuelu , Vickers Laura , Navas-Gracia Luis Manuel , Chico-Santamarta Leticia
Published: January 2024

Urban agriculture refers to any type of activity located within or around a city designed to provide ecosystem services. Given the rapid population growth and urbanization, urban agriculture is seen as a potential alternative route to a more sustainable urban food system. This review answers the main question: What are the benefits of non-commercial of Urban Agriculture (NCUA) forms and its contribution towards food production? using a systematic literature review approach. The methodology involved capturing 1355 recent articles from qualified search engines, using key terms according to the defined question, then screened for relevance and the defined scope of this review, resulting in a final selection of 40 articles for analysis. The results show that implementing NCUA practices has multifaced social, economic, and environmental benefits, such as improving people’s health, reducing expenditure on food and creating sustainable cities, highlighting the need to recognize the multifaceted role of NCUA in promoting a more sustainable lifestyle and strengthening local communities and engagement. Moreover, awareness of urban agriculture differs between developed and developing countries, as does the recognition and valorization of its benefits. Further research is needed to examine the enabling factors and barriers to NCUA adoption in different urban context, the resource implications, and the long-term sustainability of these practices.
Metabolomics and Physiological Methods Revealed the Effects of Drought Stress on the Quality of Broomcorn Millet during the Flowering Stage
Authors: Ren Jiangling , Liu Yuhan , Mao Jiao , Xu Yuanmeng , Wang Mengyao , Hu Yulu , Wang Shu , Liu Sichen , Qiao Zhijun , Cao Xiaoning
Published: January 2024

The flowering stage is a critical period for water sensitivity and quality formation of broomcorn millets. However, the effects and mechanisms of drought stress on the quality formation of broomcorn millets are not clear. We used the drought-resistant variety Hequ red millet (H) and the drought-sensitive variety Yanshu No. 10 (Y) were used as materials for drought stress treatment during the flowering stage, metabolomics and physiological methods were used to study the differences in protein, starch, amino acids, medium and medium-long chain fatty acids, and their response characteristics to drought in broomcorn millet. The results showed that different genotypes of broomcorn millets exhibited different response mechanisms in the face of drought stress. In Hequ red millet, drought stress significantly increased the contents of amylopectin (2.57%), pyridoxine (31.89%), and anthocyanin, and significantly decreased the contents of water-soluble protein (5.82%), glutelin (10.07%), thiamine (14.95%) and nicotinamide (23.01%). In Yanshu No. 10, drought significantly decreased amylose by 6.05%, and significantly increased riboflavin and nicotinamide contents by 21.11% and 32.59%. Correlation analysis showed that total starch and amylose were highly significantly positively correlated with methyl palmitate; negatively correlated with amylopectin, vitamins, proteins, free amino acids, and medium-long chain fatty acids; and amylopectin was significantly positively correlated with water-soluble protein, riboflavin, and pyridoxine. Water-soluble protein and glutelin were significantly positively correlated with most free amino acids, medium-long chain fatty acids, and nicotinamide. Thiamine showed significant positive correlation with nicotinamide and significant negative correlation with pyridoxine. Riboflavin was significantly positively correlated with nicotinamide, pyridoxine, and water-soluble protein, and pyridoxine was significantly positively correlated with water-soluble protein. Hequ red millet transforms into amylopectin by consuming water-soluble protein and glutelin, and improves drought resistance by accumulating pyridoxine, and changes its physicochemical properties by decreasing the content of amylose and protein and elevating the content of amylopectin. Yanshu No. 10 resisted drought by catabolizing lipids to produce fatty acids and by consuming amylose for conversion into other metabolites. The present study helps to understand the response of the nutritional quality of millets to drought stress at the flowering stage and provides a theoretical basis for the selection and breeding of superior varieties of millets and drought resistance research.
Construction and Identification of Cold Tolerance in Different Broccoli Cultivars at the Seedling Stage
Authors: Wen Dongna , Han Fengqing , Zhao Yongyu , Liu Yuxiang , Liu Yumei , Huang Jianxin , Li Zhansheng
Published: January 2024

This study aimed to develop a systematic method for assessing the cold tolerance of broccoli seedlings, which is helpful to evaluating the cold tolerance of broccoli cultivars. We selected 14 classical broccoli cultivars and evaluated their cold tolerance by examining physiological indicators including the levels of cold resistance, electrical conductivity, malondialdehyde (MDA), soluble sugar, and hydrogen peroxide (H2O2). The results showed that there were significant differences in detected characteristics in all cultivars after cold stress during the seedling stage (p < 0.05). Among them, Meiqing had the strongest cold tolerance, followed by King 11, Zhongqing 15, Meiao 7172, Zhongqing 318, Zheqing 80, Zhongqing 16, Zhongqing 319, and Lvxiong 90. However, Zhongqing 11, Yanxiu, Qianghan, and Feicui 5, showed the worst cold tolerance (all died). Pearson correlation analysis indicated that there was a significantly negative correlation between the cold tolerance and the electrical conductivity during broccoli seedling stage, with a correlation coefficient of −0.586 (p < 0.05). At the same time, we found that the electrical conductivity of all broccoli cultivars showed a positive correlation with the MDA and soluble sugar levels, with the correlation coefficients 0.650 and 0.573, respectively (p < 0.05). This study not only firstly provides a fundamental method for evaluating the cold tolerance in different broccoli genotypes and the other cruciferous vegetables, but also offers a scientific evidence explaining the cold tolerance of the Meiqing, King 11, and Zhongqing 15 cultivars widely cultivated in China.
A Study on the Impact of Air Pollution on Health Status of Traffic Police Personnel in Kolkata, India
Authors: Kar Sayanti , Chowdhury Santanu , Gupta Tanya , Hati Dipsita , De Arindam , Ghatak Ziniya , Tinab Tahsin , Rahman Iffa Tasnim , Chatterjee Shreyashi , RoyChowdhury Abhishek
Published: January 2024

The global concern of escalating ambient air pollution and its profound impact on human health is paramount. While traffic police personnel are critical for maintaining the road safety and transportation system of any city in India, they are susceptible to occupational health risks due to ambient air pollution. This study investigated health challenges faced by traffic police personnel due to prolonged exposure to air pollutants prevalent in traffic-congested areas, including particulate matter (PM2.5 and PM10), nitrogen dioxide, and sulfur dioxide. The first phase of this study collected and analyzed secondary air quality data over five years (2019–2023) across six locations in Kolkata, India. The second phase employed a questionnaire-based survey to assess the health implications of air pollution exposure. The survey questionnaire captured information on physical health symptoms, stress-related indicators, lifestyle habits, and work hours of around 100 police personnel from Kolkata with indoor (control group) and outdoor (exposed group) work responsibilities. The results of this study established a strong positive correlation between air pollution and a range of health issues experienced by the exposed group. The outcome of this study is significant for urban planning, policy formulation, and public health interventions geared toward minimizing the adverse impacts of air pollution on traffic police personnel.
The Effects of Different Zilpaterol Hydrochloride Feed Supplements and Extended Aging Periods on the Meat Quality of Feedlot Bulls
Authors: Webb Edward C. , Emmenis Rochelle van , Cassens Andrew M.
Published: January 2024

This study researched the effects of two commercially available zilpaterol hydrochloride (ZH) β-adrenergic agonists, denoted as ZH-A and ZH-B, on the meat quality characteristics of typical South African feedlot bulls (taurine × indicus composites), over extended aging periods of up to 120 days. The effects of ZH were studied to address concerns about the possible adverse effects of ZH on beef quality following extended aging, which typically occurs during the exportation of beef by boat. The completely randomized control study consisted of 3 homogenous experimental groups, with 3 replicates per treatment and 50 bulls per replicate = 450 animals. Treatments were a negative control (CT) with no ZH supplementation added to the basal diet or a basal diet supplemented with either zilpaterol hydrochloride A (ZH-A) or zilpaterol hydrochloride B (ZH-B), both at 105 g ZH/ton, fed from the first day of the finishing period (D0) for 30 days. Subsamples were collected from 38 random carcasses from each treatment for proximate analysis and meat quality analysis using Longissimus dorsi samples. ZH supplementation decreased meat tenderness (Warner–Bratzler shear force values (WBSF)) of bulls fed ZH-A or ZH-B, compared to those fed the CT diet (p < 0.05; η2 = 0.24). The WBSF values of both ZH treatments were about 0.5–0.8 kg higher during the aging periods compared to the CT, but ZH did not affect post-mortem meat aging or meat quality characteristics differently compared to the CT. Post-mortem aging per se influenced all meat quality characteristics investigated (p < 0.001; η2 > 0.30), showing improvements in WBSF, a decrease in meat colour and an increase in drip and cooking losses. L*-values increased from 3 to 56 days of aging and then decreased to day 120 (p < 0.001; η2 = 032). Chroma values decreased from day 3 to day 120 (p < 0.001; η2 = 0.50). Hue° decreased from day 3 to day 7 and stabilized until day 120 (p < 0.001; η2 = 0.40). Moisture and cooking loss (CL) increased to 56 days and then decreased to 120 days.
Epidemiology and Scenario Simulations of the Middle East Respiratory Syndrome Corona Virus (MERS-CoV) Disease Spread and Control for Dromedary Camels in United Arab Emirates (UAE)
Authors: Ali Magdi Mohamed , Fathelrahman Eihab , El Awad Adil I. , Eltahir Yassir M. , Osman Raeda , El-Khatib Youssef , AlRifai Rami H. , El Sadig Mohamed , Khalafalla Abdelmalik Ibrahim , Reeves Aaron
Published: January 2024

Middle East Respiratory Syndrome (MERS-CoV) is a coronavirus-caused viral respiratory infection initially detected in Saudi Arabia in 2012. In UAE, high seroprevalence (97.1) of MERS-CoV in camels was reported in several Emirate of Abu Dhabi studies, including camels in zoos, public escorts, and slaughterhouses. The objectives of this research include simulation of MERS-CoV spread using a customized animal disease spread model (i.e., customized stochastic model for the UAE; analyzing the MERS-CoV spread and prevalence based on camels age groups and identifying the optimum control MERS-CoV strategy. This study found that controlling animal mobility is the best management technique for minimizing epidemic length and the number of affected farms. This study also found that disease dissemination differs amongst camels of three ages: camel kids under the age of one, young camels aged one to four, and adult camels aged four and up; because of their immunological state, kids, as well as adults, had greater infection rates. To save immunization costs, it is advised that certain age groups be targeted and that intense ad hoc unexpected vaccinations be avoided. According to the study, choosing the best technique must consider both efficacy and cost.
Correction: Park et al. Effect of Particulate Matter 2.5 on Fetal Growth in Male and Preterm Infants through Oxidative Stress. Antioxidants 2023, 12, 1916
Authors: Park Sunwha , Kwon Eunjin , Lee Gain , You Young-Ah , Kim Soo Min , Hur Young Min , Jung Sooyoung , Jee Yongho , Park Mi Hye , Na Sung Hun , Kim Young-Han , Cho Geum Joon , Bae Jin-Gon , Lee Soo-Jeong , Lee Sun Hwa , Kim Young Ju
Published: January 2024

In the original publication [...]
Neuroprotection Afforded by an Enriched Mediterranean-like Diet Is Modified by Exercise in a Rat Male Model of Cerebral Ischemia
Authors: Romaus-Sanjurjo Daniel , Castañón-Apilánez María , López-Arias Esteban , Custodia Antía , Martin-Martín Cristina , Ouro Alberto , López-Cancio Elena , Sobrino Tomás
Published: January 2024

Ischemic stroke is an important cause of mortality and disability worldwide. Given that current treatments do not allow a remarkably better outcome in patients after stroke, it is mandatory to seek new approaches to preventing stroke and/or complementing the current treatments or ameliorating the ischemic insult. Multiple preclinical and clinical studies highlighted the potential beneficial roles of exercise and a Mediterranean diet following a stroke. Here, we investigated the effects of a pre-stroke Mediterranean-like diet supplemented with hydroxytyrosol and with/without physical exercise on male rats undergoing transient middle cerebral artery occlusion (tMCAO). We also assessed a potential synergistic effect with physical exercise. Our findings indicated that the diet reduced infarct and edema volumes, modulated acute immune response by altering cytokine and chemokine levels, decreased oxidative stress, and improved acute functional recovery post-ischemic injury. Interestingly, while physical exercise alone improved certain outcomes compared to control animals, it did not enhance, and in some aspects even impaired, the positive effects of the Mediterranean-like diet in the short term. Overall, these data provide the first preclinical evidence that a preemptive enriched Mediterranean diet modulates cytokines/chemokines levels downwards which eventually has an important role during the acute phase following ischemic damage, likely mediating neuroprotection.
Impact and Classification of Body Stature and Physiological Variability in the Acquisition of Vital Signs Using Continuous Wave Radar
Authors: Soares Beatriz , Gouveia Carolina , Albuquerque Daniel , Pinho Pedro
Published: January 2024

The Bio-Radar system, useful for monitoring patients with infectious diseases and detecting driver drowsiness, has gained popularity in the literature. However, its efficiency across diverse populations considering physiological and body stature variations needs further exploration. This work addresses this gap by applying machine learning (ML) algorithms—Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Random Forest—to classify subjects based on gender, age, Body Mass Index (BMI), and Chest Wall Perimeter (CWP). Vital signs were collected from 92 subjects using a Continuous Wave (CW) radar operating at 5.8 GHz. The results showed that the Random Forest algorithm was the most accurate, achieving accuracies of 76.66% for gender, 71.13% for age, 72.52% for BMI, and 74.61% for CWP. This study underscores the importance of considering individual variations when using Bio-Radar, enhancing its efficiency and expanding its potential applications.
Inverse Problem Protocol to Estimate Horizontal Groundwater Velocity from Temperature–Depth Profiles in a 2D Aquifer
Authors: Alhama Francisco , Jiménez-Valera José Antonio , Alhama Iván
Published: January 2024

A general and precise protocol that follows the standards of an inverse problem in engineering is proposed to estimate groundwater velocity from experimental lectures of temperature vertical profiles in a 2D aquifer. Several values of error in the temperature measurements are assumed. Since a large quantity of parameters and initial conditions influence the solution of this process, the protocol is very complex and needs to be tested to ensure its reliability. The studied scenario takes into account the input temperature of the water as well as the isothermal conditions at the surface and bottom of the aquifer. The existence of an input region, in which profiles develop to become linear, allows us to eliminate experimental measurements beyond such a region. Once the protocol is developed and tested, it is successfully applied to estimate the regional (lateral) groundwater velocity of the real aquifer and the result compared with estimations coming from the piezometric map.
Computerized Generation and Surface Deviation Correction of Ruled Surface for Face Gear Drives
Authors: Peng Xianlong , Wu Yikai
Published: January 2024

In order to solve the problems of low efficiency and complex cutting tools in conventional face gear machining, this paper presents a machining method of ruled surface face gears with conical cutters and proposes a new pinion to correct deviation and its machining method. Firstly, the mathematical models of ruled surface face gears and conical cutters are established, the motion rules of the conical cutter are derived, and the influence of basic parameters on the tooth surface deviation between ruled surface and conventional surface is analyzed. Secondly, for the sake of correction of tooth surface deviation, reverse conjugation is applied to the ruled surface to obtain a corrected pinion. On the basis of hobbing cylindrical gears, the purpose of machining corrected pinions is achieved by increasing CNC motions. Finally, the manufacturing process is simulated by VERICUT software, the results demonstrate that the machining error of ruled surface and pinion do not exceed 10 μm, and through LTCA, the meshing performance of the ruled surface face gear pair is basically the same as that of conventional face gear pair, proving the feasibility of replacing the latter with the former. This study provides a new manufacturing method for face gears.
PRC-Light YOLO: An Efficient Lightweight Model for Fabric Defect Detection
Authors: Liu Baobao , Wang Heying , Cao Zifan , Wang Yu , Tao Lu , Yang Jingjing , Zhang Kaibing
Published: January 2024

Defect detection holds significant importance in improving the overall quality of fabric manufacturing. To improve the effectiveness and accuracy of fabric defect detection, we propose the PRC-Light YOLO model for fabric defect detection and establish a detection system. Firstly, we have improved YOLOv7 by integrating new convolution operators into the Extended-Efficient Layer Aggregation Network for optimized feature extraction, reducing computations while capturing spatial features effectively. Secondly, to enhance the performance of the feature fusion network, we use Receptive Field Block as the feature pyramid of YOLOv7 and introduce Content-Aware ReAssembly of FEatures as upsampling operators for PRC-Light YOLO. By generating real-time adaptive convolution kernels, this module extends the receptive field, thereby gathering vital information from contexts with richer content. To further optimize the efficiency of model training, we apply the HardSwish activation function. Additionally, the bounding box loss function adopts the Wise-IOU v3, which incorporates a dynamic non-monotonic focusing mechanism that mitigates adverse gradients from low-quality instances. Finally, in order to enhance the PRC-Light YOLO model’s generalization ability, we apply data augmentation techniques to the fabric dataset. In comparison to the YOLOv7 model, multiple experiments indicate that our proposed fabric defect detection model exhibits a decrease of 18.03% in model parameters and 20.53% in computational load. At the same time, it has a notable 7.6% improvement in mAP.
Sports Video Classification Method Based on Improved Deep Learning
Authors: Gao Tianhao , Zhang Meng , Zhu Yifan , Zhang Youjian , Pang Xiangsheng , Ying Jing , Liu Wenming
Published: January 2024

Classifying sports videos is complex due to their dynamic nature. Traditional methods, like optical flow and the Histogram of Oriented Gradient (HOG), are limited by their need for expertise and lack of universality. Deep learning, particularly Convolutional Neural Networks (CNNs), offers more effective feature recognition in sports videos, but standard CNNs struggle with fast-paced or low-resolution sports videos. Our novel neural network model addresses these challenges. It begins by selecting important frames from sports footage and applying a fuzzy noise reduction algorithm to enhance video quality. The model then uses a bifurcated neural network to extract detailed features, leading to a densely connected neural network with a specific activation function for categorizing videos. We tested our model on a High-Definition Sports Video Dataset covering over 20 sports and a low-resolution dataset. Our model outperformed established classifiers like DenseNet, VggNet, Inception v3, and ResNet-50. It achieved high precision (0.9718), accuracy (0.9804), F-score (0.9761), and recall (0.9723) on the high-resolution dataset, and significantly better precision (0.8725) on the low-resolution dataset. Correspondingly, the highest values on the matrix of four traditional models are: precision (0.9690), accuracy (0.9781), F-score (0.9670), recall (0.9681) on the high-resolution dataset, and precision (0.8627) on the low-resolution dataset. This demonstrates our model’s superior performance in sports video classification under various conditions, including rapid motion and low resolution. It marks a significant step forward in sports data analytics and content categorization.
The Impact of Fine-Layering of Tailings Dam on the Variation Pattern of Infiltration Lines
Authors: Geng Wenze , Song Zhifei , He Cheng , Wang Hongtao , Dong Xinyi
Published: January 2024

The type of soil and its compactness significantly influence its permeability coefficient, which in turn affects the drainage difficulty of soil pore water and the distribution of the infiltration line. However, current tailings dam models typically consider only a single soil layer instead of taking into account the differences in soil types and compactness, resulting in a deviation between simulated results and actual conditions. To address this issue, this study proposes three models with a gradually increasing degree of layering refinement based on soil type and compactness. These models aim to simulate the variations in the infiltration line under three different strategies: constant head, rainfall, and drainage. The simulation results indicate that the average increase in the infiltration line of the three schemes after rainfall is 46.2%, 65.88%, 83.52%, respectively; the fitting percentages for each scheme of infiltration line after 720 days of drainage and the constant head stage are 72.38%, 88.27%, and 93.61%, respectively. It can be seen that the higher the refinement level of the layered model, the more sensitive it is to changes in the infiltration line. Furthermore, as the refinement level of the layered model increases, the simulation effect on the changes in the infiltration line improves, and the simulated results become more consistent with the actual situation. This finding provides a strategy and possibility for the study of the tailings dam’s infiltration lines, safety, and stability.
Exploring the Potential Protective Effect of Probiotics in Obesity-Induced Colorectal Cancer: What Insights Can In Vitro Models Provide?
Authors: Viana Rejane , Rocha Ana C. , Sousa André P. , Ferreira Diogo , Fernandes Rúben , Almeida Cátia , Pais Patrick J. , Baylina Pilar , Pereira Ana Cláudia
Published: January 2024

Colorectal cancer (CRC) is the third most common cancer diagnosed today and the third leading cause of death among cancer types. CRC is one of the gastrointestinal tumors with obesity as the main extrinsic risk factor, since, according to authors, the meta-inflammation sustained by the excess adipose tissue can provide abundant circulating lipids, as well as hormones and metabolites crucial to tumor development and aggressiveness. The gut microbiota can protect the colon from meta-inflammation and endocrine changes caused by obesity. The present study aimed to investigate the antitumor activity of a commercial probiotic in intestinal tumor cells under two adiposity conditions. Experimental assays were performed on the Caco2 cell line (colon adenocarcinoma) supplemented with differentiated adipocyte’s secretomes of the 3T3-L1 cell line (mouse pre-adipocytes) in two adiposity conditions: (i) differentiation without the use of Pioglitazone (noPGZ) and (ii) differentiation using Pioglitazone (PGZ). The Caco2 cells were first exposed to both secretomes for 24 h and evaluated and subsequently exposed to probiotic extract followed by secretome and evaluated. The effects of these treatments were evaluated using cytotoxicity assays by MTT, cell migration by injury, and antioxidant activity by glutathione assay. The use of secretomes showed a statistically significant increase in cell viability in Caco2 cells, either in noPGZ (p < 0.01) or PGZ (p < 0.05), and the probiotic was not able to reduce this effect. In the injury assay, secretome increased cell migration by more than 199% in both adiposity conditions (p < 0.001 in noPGZ and p < 0.01 in PGZ). In the probiotic treatment, there was a reduction in cell migration compared to the control in adiposity conditions. The antioxidant response of Caco2 cells was increased in both adiposity conditions previously exposed to the probiotic supernatant. This pilot work brings to light some findings that may answer why the modulation of the intestinal microbiota using probiotics is an alternative strategy leading to improvements in the condition and stage of the colon tumor. Additional studies are needed to clarify the role of Pioglitazone in this type of tumor and the metabolites of obesity that are attenuated by the use of probiotics.
Improvements in Rock Mass Description for Stope Design by Geophysical and Geochemical Methods
Authors: Rinne Mikael , Janiszewski Mateusz , Pontow Sebastian , Uotinen Lauri , Kiuru Risto , Kangas Lasse , Laine Ilkka , Leveinen Jussi
Published: January 2024

Stope design is an important part of mine planning, and it aims to balance ore recovery, ore dilution, and production costs without compromising the safety aspects. This paper summarizes the main results from the research, which aims to introduce new techniques to describe the ore body and surrounding rock mass at the tunnel face prior to stope excavation. The research comprises a literature review and a survey among mining professionals to assess current stope design practices. The study identifies geotechnical data, software improvements, and integration of design into mine planning as the most critical areas for improvement. The empirical part of the study proposes new techniques for fast data acquisition. The laser-induced breakdown spectrometry (LIBS) technique is developed for measurements at the tunnel face and from core boxes to provide mineralogical and geometallurgical data. Ground-penetrating radar (GPR) studies are conducted to improve discontinuity characterization, and rapid photogrammetric methods are proposed for efficient tunnel geometry characterization. The techniques discussed in this paper already have many industrial applications. This study reveals their potential to be adopted and further developed to serve ore and rock mass characterization for stope design.
Optimizing Coverage in Wireless Sensor Networks: A Binary Ant Colony Algorithm with Hill Climbing
Authors: Kurian Alwin M. , Onuorah Munachimso J. , Ammari Habib M.
Published: January 2024

Wireless sensor networks (WSNs) play a vital role in various fields, but ensuring optimal coverage poses a significant challenge due to the limited energy resources that constrain sensor nodes. To address this issue, this paper presents a novel approach that combines the binary ant colony algorithm (BACA), a variant of ant colony optimization (ACO), with other search optimization algorithms, such as hill climbing (HC) and simulated annealing (SA). The BACA is employed to generate an initial solution by emulating the foraging behavior of ants and the pheromone trails they leave behind in their search for food. However, we acknowledge that the BACA alone may not guarantee the most optimal solution. Subsequently, HC and SA are optimization search algorithms that refine the initial solution obtained by the BACA to find a more enhanced solution. Through extensive simulations and experiments, we demonstrate that our proposed approach results in enhanced coverage and energy-efficient coverage in a two-dimensional (2D) field. Interestingly, our findings reveal that HC consistently outperforms SA, particularly in less complex search spaces, leveraging its robust exploitation approach. Our research contributes valuable insights into optimizing WSN coverage, highlighting the superiority of HC in this context. Finally, we outline promising future research directions that can advance the optimization of WSN coverage.
An Estimation of Speech Privacy Class Based on ISO Parameter
Authors: Bjelić Miloš , Miljković Tatjana , Mijić Miomir , Pavlović Dragana Šumarac
Published: January 2024

This paper examines speech privacy in both residential and commercial spaces. The ASTM E2638 standard defines the Speech Privacy Class (SPC) parameter, which measures speech privacy based on the signal-to-noise ratio at the listener’s position. This paper proposes estimating the SPC value using relevant ISO parameters commonly used in European practice: the apparent sound reduction index in dB (defined by ISO 16283-1, 2 standards) and the equivalent ambient noise level in dBA (defined by the ISO 1996-1 standard). The estimated value of the SPC parameter in this paper is referred to as the Speech Privacy Index (SPI). A diverse range of situations, i.e., rooms, was analyzed in the field. These rooms varied in terms of purpose, organization, dimensions, furnishings, isolation from other spaces, and internal and external environments. The results of the experiments demonstrate a strong correlation between the SPC value estimated according to ISO parameters (the proposed method) and the SPC as defined in the ASTM E standard. This indicates that the proposed method can provide an indicator of the state of speech privacy in buildings. The significance of the proposed calculation method (i.e., the STI parameter) lies in its ability to be applied at the building design stage, as well as after its completion, during routine testing.
A Structural Health Monitoring System for Bond Line Flaws Detection on a Full-Scale Wingbox Section Demonstrator
Authors: Pellone Lorenzo , Ciminello Monica , Mercurio Umberto , Apuleo Gianvito , Concilio Antonio
Published: January 2024

In recent years, there has been a significant increase in the use of structural health monitoring (SHM) technologies as systems for monitoring the integrity of aircraft’s structures. The use of compact and embeddable sensor networks, like the ones based on fibre optics (FO), is particularly attractive from the perspective of releasing an integrated structural system with intrinsic sensing capacity. Usually, an SHM system architecture is completed by a dedicated algorithm that processes the data gathered from the sensors to elaborate on the level of damage currently suffered by the structure, with the further possibility of providing information to the relevant specialists involved with its supervision. One of the main SHM applications that is attracting major interest is related to the inspection and detection of anomalies in bonded joints, which is extremely relevant in many composite realizations. Aeronautical regulations allow the use of bonded joints on an aircraft’s primary structure but require the implementation of a means to ensure their absolute safety, such as the introduction of further mechanical links aimed at stopping the propagation of a possible flaw or the availability of Non-Destructive Inspection (NDI) systems to prove the absence of relevant damaged areas. Generally, the main typical defects occurring during the manufacturing of bonded joints include adhesive curing, kissing bonds, poor porosity, and poor surface preparation. The current NDI systems more widely used and available to detect defects are still inaccurate due to the lack of standard procedures for the creation of representative defects in a controlled manner, which would allow for the development of reliable methodologies and tools able to ensure the safety of a bonded joint, as required by safety regulations. This paper shows the results relative to the implementation of an SHM system developed by the Italian Aerospace Research Centre (CIRA) aimed at monitoring the bonding lines between spar caps and panels of a typical composite wingbox section and detecting faults in location and length. The work was performed during typical ground static tests by using a fibre optical sensing network embedded within relevant adhesive paste layers during the manufacturing process of the structure. In the reported investigation, the SHM system assumed the function of an NDI system tool. The results show that the developed SHM system has good reliability for the detection of both the position and size of damage areas that were artificially inserted within the test article during the bonding phase, showing its potential as a candidate to be used as a tool to verify the conditions of a bonded joint, as required by aviation authorities’ regulations.
Continuous Feed Grinding Milling Process of Soda-Lime Glass Using Smoothed-Particle Hydrodynamics
Authors: Alamo Joshua , Pitcheralle Jameson , Merrett Craig G. , Bazzocchi Michael C. F. , Martinez Marcias
Published: January 2024

A smoothed-particle hydrodynamics (SPH) modeling technique was applied in conjunction with the Johnson–Holmquist (JH-2) ceramic material constitutive model to replicate the fracture of soda-lime glass in a milling manufacturing process. Four-point bending tests were conducted to validate the soda-lime glass bulk material properties prior to its implementation in ABAQUS CAE™ Explicit (Version 2017). The JH-2 material constitutive model replicated the fracture load and time to fracture for the four-point bending load cases as per ASTM C158. This study showed how SPH in combination with a validated JH-2 material model in a milling process simulation was able to replicate the output size distribution at 5000 and 6500 revolutions per minute (RPM). For operations at 3000 RPM or lower, it was shown that it is necessary to include additional effects in the model, such as fluid–structure interactions, to improve the correlation with the experimental data. The SPH model was validated through an experimental campaign using high-speed cameras and a particle Camsizer. The experimental results clearly indicate a direct relation between the mill’s RPM and the output particle size distribution.
On Generalized Class of Bell Polynomials Associated with Geometric Applications
Authors: Al-Jawfi Rashad A. , Muhyi Abdulghani , Al-shameri Wadia Faid Hassan
Published: January 2024

In this paper, we introduce a new class of special polynomials called the generalized Bell polynomials, constructed by combining two-variable general polynomials with two-variable Bell polynomials. The concept of the monomiality principle was employed to establish the generating function and obtain various results for these polynomials. We explore certain related identities, properties, as well as differential and integral formulas. Further, specific members within the generalized Bell family—such as the Gould-Hopper-Bell polynomials, Laguerre-Bell polynomials, truncated-exponential-Bell polynomials, Hermite-Appell-Bell polynomials, and Fubini-Bell polynomials—were examined, unveiling analogous outcomes for each. Finally, Mathematica was utilized to investigate the zero distributions of the Gould-Hopper-Bell polynomials.
Solving the Fornberg–Whitham Model Derived from Gilson–Pickering Equations by Analytical Methods
Authors: O’Regan Donal , Aderyani Safoura Rezaei , Saadati Reza , Allahviranloo Tofigh
Published: January 2024

This paper focuses on obtaining traveling wave solutions of the Fornberg–Whitham model derived from Gilson–Pickering equations, which describe the prorogation of waves in crystal lattice theory and plasma physics by some analytical techniques, i.e., the exp-function method (EFM), the multi-exp function method (MEFM) and the multi hyperbolic tangent method (MHTM). We analyze and compare them to show that MEFM is the optimum method.
Comparative Analysis of Energy Storage and Buffer Units for Electric Military Vehicle: Survey of Experimental Results
Authors: Pham Ngoc Nam , Bloudicek Radim , Leuchter Jan , Rydlo Stanislav , Dong Quang Huy
Published: January 2024

This paper deals with the analyses of batteries used in current military systems to power the electric drives of military vehicles. The article focuses on battery analyses based on operational data obtained from measurements rather than analyses of the chemical composition of the tested batteries. The authors of the article used their experience from the development test-laboratory of military technology. This article presents a comparative analysis of existing and promising technologies in the field of energy storage and buffering for military electric vehicles. The overview of these technologies, including the design, operating principles, advantages, and disadvantages, are briefly presented to produce theoretical comparative analyses. However, this article mainly focuses on the experimental verification of operational ability in varied conditions, as well as the comparison and analysis of these results. The main part of the article provides more experimental studies on technologies of energy storage and buffering using the results of several experiments conducted to demonstrate the behavior of each technology in different working conditions. The output parameters, as well as the state of charge of each technology’s samples, were surveyed in various temperatures and loading characteristics. The results presented in this paper are expected to be useful for optimizing the selection of energy storage and buffering solutions for military electric vehicles in different applications and functional environments.
Validation of N-Methylpyridinium as a Feasible Biomarker for Roasted Coffee Intake
Authors: Brandl Beate , Czech Coline , Wudy Susanne I. , Beusch Anja , Hauner Hans , Skurk Thomas , Lang Roman
Published: January 2024

Health-related nutritional human studies rely on the validity of dietary data provided by study participants. Reliable biomarkers for food intake help objectify data collected by food frequency questionnaires. They facilitate the monitoring of compliance with the study requirements, e.g., abstinence from food, help clean biased data, and remove non-compliant individuals. Biomarker candidates are often revealed by sophisticated metabolomics analyses of body fluids, e.g., urine or plasma, collected from case and control study populations. However, validation for using a biomarker candidate in real-life scenarios is seldomly executed. Coffee is a food item of high interest because of the abundance of bioactive compounds and the regularity of life-time consumption by a large part of the population. Coffee has been found to positively impact cardiovascular risk, type 2 diabetes, and cognitive decline. Coffee and its health implications, therefore, are of high interest. A suitable dietary biomarker for coffee consumption is desirable for the clear classification of study participants as coffee drinkers or non-coffee drinkers to enable correlation of physiological response to dietary habits, e.g., coffee consumption. Here, we propose the roast coffee compound N-methylpyridinium (NMP) as a promising biomarker of pragmatic use to distinguish a coffee drinker from a non-coffee drinker. NMP is an easily accessible analytical target from the plasma and urine matrix that can help determine precedent exposure to roasted coffee products. We review the published information on the coffee compound N-methylpyridinium in foods, coffee, and plasma/urine after coffee consumption, and evaluate the data in the context of the proposed food biomarker criteria “plausibility”, “time- and dose–response”, “robustness”, “reliability”, “stability”, “analytical performance”, and “reproducibility”. An additional data set is acquired to fill the gaps in the literature. In summary, we conclude that the abundance of NMP can serve as a reliable analytical tool to verify recent consumption of roasted coffee. The use of NMP appears limited to being qualitative, as NMP abundance in coffee and human biosamples is affected by several parameters, e.g., the roasting conditions and the volume and time of coffee consumed.
The Evolution of Spinal Endoscopy: Design and Image Analysis of a Single-Use Digital Endoscope Versus Traditional Optic Endoscope
Authors: Cheng Shih-Hao , Lin Yen-Tsung , Lu Hsin-Tzu , Tsuei Yu-Chuan , Chu William , Chu Woei-Chyn
Published: January 2024

Spinal endoscopy has evolved significantly since its inception, offering minimally invasive solutions for various spinal pathologies. This study introduces a promising innovation in spinal endoscopy—a single-use digital endoscope designed to overcome the drawbacks of traditional optic endoscopes. Traditional endoscopes, despite their utility, present challenges such as fragility, complex disinfection processes, weight issues, and susceptibility to mechanical malfunctions. The digital endoscope, with its disposable nature, lighter weight, and improved image quality, aims to enhance surgical procedures and patient safety. The digital endoscope system comprises a 30-degree 1000 × 1000 pixel resolution camera sensor with a 4.3 mm working channel, and LED light sources replacing optical fibers. The all-in-one touch screen tablet serves as the host computer, providing portability and simplified operation. Image comparisons between the digital and optic endoscopes revealed advantages in the form of increased field of view, lesser distortion, greater close-range resolution, and enhanced luminance. The single-use digital endoscope demonstrates great potential for revolutionizing spine endoscopic surgeries, offering convenience, safety, and superior imaging capabilities compared to traditional optic endoscopes.
Label-Free Optical Technologies for Middle-Ear Diseases
Authors: Zhou Zeyi , Pandey Rishikesh , Valdez Tulio A.
Published: January 2024

Medical applications of optical technology have increased tremendously in recent decades. Label-free techniques have the unique advantage of investigating biological samples in vivo without introducing exogenous agents. This is especially beneficial for a rapid clinical translation as it reduces the need for toxicity studies and regulatory approval for exogenous labels. Emerging applications have utilized label-free optical technology for screening, diagnosis, and surgical guidance. Advancements in detection technology and rapid improvements in artificial intelligence have expedited the clinical implementation of some optical technologies. Among numerous biomedical application areas, middle-ear disease is a unique space where label-free technology has great potential. The middle ear has a unique anatomical location that can be accessed through a dark channel, the external auditory canal; it can be sampled through a tympanic membrane of approximately 100 microns in thickness. The tympanic membrane is the only membrane in the body that is surrounded by air on both sides, under normal conditions. Despite these favorable characteristics, current examination modalities for middle-ear space utilize century-old technology such as white-light otoscopy. This paper reviews existing label-free imaging technologies and their current progress in visualizing middle-ear diseases. We discuss potential opportunities, barriers, and practical considerations when transitioning label-free technology to clinical applications.