bluuebunny/crossref_metadata_2025 huggingface dataset:
Inhibitory Effects of Ginsenoside Compound K on Lipopolysaccharide-Stimulated Inflammatory Responses in Macrophages by Regulating Sirtuin 1 and Histone Deacetylase 4
Authors: Kang Hyunju , Kim Shin , Lee Jin-Young , Kim Bohkyung
Published: March 2023

Inflammation, an innate immune response mediated by macrophages, has been a hallmark leading to the pathophysiology of diseases. In this study, we examined the inhibitory effects of ginsenoside compound K (CK) on lipopolysaccharide (LPS)-induced inflammation and metabolic alteration in RAW 264.7 macrophages by regulating sirtuin 1 (SIRT1) and histone deacetylase 4 (HDAC4). LPS suppressed SIRT1 while promoting HDAC4 expression, accompanied by increases in cellular reactive oxygen species accumulation and pro-inflammatory gene expression; however, the addition of CK elicited the opposite effects. CK ameliorated the LPS-induced increase in glycolytic genes and abrogated the LPS-altered genes engaged in the NAD+ salvage pathway. LPS decreased basal, maximal, and non-mitochondrial respiration, reducing ATP production and proton leak in macrophages, which were abolished by CK. SIRT1 inhibition augmented Hdac4 expression along with increased LPS-induced inflammatory and glycolytic gene expression, while decreasing genes that regulate mitochondrial biogenesis; however, its activation resulted in the opposite effects. Inhibition of HDAC4 enhanced Sirt1 expression and attenuated the LPS-induced inflammatory gene expression. In conclusion, CK exerted anti-inflammatory and antioxidant properties with the potential to counteract the alterations of energy metabolism, including glycolysis and mitochondrial respiration, through activating SIRT1 and repressing HDAC4 in LPS-stimulated macrophages.
Sex-Specific Effects on Total Body Fat Gain with 4-Week Daily Dosing of Raspberry Ketone [4-(4-Hydroxyphenyl)-2-butanone] and Ketogenic Diet in Mice
Authors: Hao Lihong , Bello Nicholas T.
Published: March 2023

Background: Raspberry ketone (RK: [4-(4-Hydroxyphenyl)-2-butanone]) is a dietary supplement marketed for weight control. RK is structurally unrelated to the ketone bodies elevated with a ketogenic diet (KD). This study aims to determine whether RK oral supplementation with KD improves the weight loss outcomes in high-fat diet (HFD; 45% fat)-fed mice. Methods: Male and female C57BL/6J mice were HFD-fed for 9 weeks and switched to KD (80% fat) or a control diet (CD; 10% fat) or continued with the HFD for 4 weeks. Coincident with the diet switch, each diet group received oral RK (200 mg/kg/day) or a vehicle. Results: In male KD-fed mice, oral RK reduced body weight by ~6% (KD_Veh: −9.2 ± 1% vs. KD_RK: −15.1 ± 1%) and fat composition by ~18% (KD_Veh: −16.0 ± 4% vs. KD_RK: −34.2 ± 5%). HFD and KD feeding induced glucose intolerance in both male and female mice. Oral RK decreased the glucose area under the curve in female mice by ~6% (KD_Veh: 44,877 ± 957 vs. KD_RK: 42,040 ± 675 mg*min/dl). KD also had gut microbiota alterations with higher alpha diversity in males and more beta diversity with RK. These findings suggest sex-specific weight loss effects with RK and KD in mice.
Novel Therapeutic Combination Targets the Growth of Letrozole-Resistant Breast Cancer through Decreased Cyclin B1
Authors: Patel Jankiben R. , Banjara Bipika , Ohemeng Afia , Davidson A. Michael , Boué Stephen M. , Burow Matthew E. , Tilghman Syreeta L.
Published: March 2023

As breast cancer cells transition from letrozole-sensitive to letrozole-resistant, they over-express epidermal growth factor receptor (EGFR), mitogen-activated protein kinase (MAPK), and human epidermal growth factor receptor 2 (HER2) while acquiring enhanced motility and epithelial-to-mesenchymal transition (EMT)-like characteristics that are attenuated and reversed by glyceollin treatment, respectively. Interestingly, glyceollin inhibits the proliferation and tumor progression of triple-negative breast cancer (TNBC) and estrogen-independent breast cancer cells; however, it is unlikely that a single phytochemical would effectively target aromatase-inhibitor (AI)-resistant metastatic breast cancer in the clinical setting. Since our previous report indicated that the combination of lapatinib and glyceollin induced apoptosis in hormone-dependent AI-resistant breast cancer cells, we hypothesized that combination therapy would also be beneficial for hormone independent letrozole-resistant breast cancer cells (LTLT-Ca) compared to AI-sensitive breast cancer cells (AC-1) by decreasing the expression of proteins associated with proliferation and cell cycle progression. While glyceollin + lapatinib treatment caused comparable inhibitory effects on the proliferation and migration in both cell lines, combination treatment selectively induced S and G2/M phase cell cycle arrest of the LTLT-Ca cells, which was mediated by decreased cyclin B1. This phenomenon may represent a unique opportunity to design novel combinatorial therapeutic approaches to target hormone-refractory breast tumors.
Increased Fruit and Vegetable Consumption Mitigates Oxidative Damage and Associated Inflammatory Response in Obese Subjects Independent of Body Weight Change
Authors: Gariballa Salah , Al-Bluwi Ghada S. M. , Yasin Javed
Published: March 2023

Introduction: The growing prevalence of obesity and related type 2 diabetes is reaching epidemic proportions in the Gulf countries. Oxidative damage and inflammation are possible mechanisms linking obesity to diabetes and other related complications, including cardiovascular disease (CVD). Aims: To measure the effects of increased fruit and vegetable consumption on body weight, waist circumference, oxidative damage, and inflammatory markers. Materials and Methods: We recruited and followed up with 965 community free-living subjects. All recruited subjects had fruit and vegetable intakes, physical activity, antioxidants, and markers of oxidative damage and inflammation measured at baseline and follow up. A validated, semi-quantitative food-frequency questionnaire was used to assess subjects’ fruit and vegetable consumption. We stratified subjects based on their daily fruit and vegetable consumption and compared metabolic risk factors between those with high fruit and vegetable consumption and those with low consumption. A multiple logistic regression analysis was performed to determine the independent effects of fruit and vegetable intake on changes in body weight and waist circumference (WC). Results: A total of 965 community free-living subjects (801 (83%) females, mean (SD) age 39 ± 12 years) were recruited and followed up with for a mean (SD) period of 427 ± 223 days. Using WHO cut-off points for body mass index (BMI), 284 (30%) subjects were overweight and 584 (62%) obese, compared to 69 (8%) at normal body weight. An increased fruit and vegetable consumption was associated with a significant decrease in inflammatory markers (hs CRP, TNF-α) and oxidative damage markers (TBARs) and with increased antioxidant enzymes (catalase, glutathione peroxidase) compared to a low consumption (p < 0.05). The benefits of an increased fruit and vegetable consumption in obese subjects was independent of changes in body weight and WC and was maintained at follow up. Conclusion: Our results support the beneficial role of a higher fruit and vegetable intake in obese subjects independent of changes in body weight and WC.
Assessment of Heme and Non-Heme Iron Intake and Its Dietary Sources among Adults in Armenia
Authors: Pipoyan Davit , Stepanyan Seda , Beglaryan Meline , Mantovani Alberto
Published: March 2023

Adequate dietary iron (Fe) intake is crucial for preventing Fe-deficient anemia, a recognized global public health concern which is important in Armenia. This study aimed to analyze the intake of Fe, both heme (from animal tissues) and non-heme (more prevalent, but less efficiently absorbed), as well as the Fe dietary sources, among adults in a representative national sample in Armenia. The study was conducted on 1400 individuals aged 18–80 and above, who were enrolled from all regions of Armenia. The Fe intake was assessed through a 24 h dietary recall survey, while Fe occurrence was determined through atomic absorption spectrophotometry (AAS). The results showed a high proportion of adults with a Fe intake lower than the average requirements set by EFSA (65%, 80% and 85% of males, total females and females at fertile age, respectively). Main Fe sources were bread, fruits and vegetables; heme Fe accounted only for <5% of total Fe intake. Compared to males, females had a lower intake of all forms of Fe (p < 0.05). Significant differences were observed in the intake of different forms of Fe between regions (p < 0.05), while the age-group 36–55 years had higher intakes of total Fe. Our data call for comprehensive nutritional security strategies in order to reduce iron deficiency in Armenia, that represents a public health concern.
Impact of Co-Occurrence of Obesity and SARS-CoV-2 Infection during Pregnancy on Placental Pathologies and Adverse Birth Outcomes: A Systematic Review and Narrative Synthesis
Authors: Ferraz Thaina , Benton Samantha J. , Zareef Israa , Aribaloye Oluwatomike , Bloise Enrrico , Connor Kristin L.
Published: March 2023

Obesity is a risk factor for severe COVID-19 disease during pregnancy. We hypothesized that the co-occurrence of high maternal body mass index (BMI) and gestational SARS-CoV-2 infection are detrimental to fetoplacental development. We conducted a systematic review following PRISMA/SWiM guidelines and 13 studies were eligible. In the case series studies (n = 7), the most frequent placental lesions reported in SARS-CoV-2(+) pregnancies with high maternal BMI were chronic inflammation (71.4%, 5/7 studies), fetal vascular malperfusion (FVM) (71.4%, 5/7 studies), maternal vascular malperfusion (MVM) (85.7%, 6/7 studies) and fibrinoids (100%, 7/7 studies). In the cohort studies (n = 4), three studies reported higher rates of chronic inflammation, MVM, FVM and fibrinoids in SARS-CoV-2(+) pregnancies with high maternal BMI (72%, n = 107/149; mean BMI of 30 kg/m2) compared to SARS-CoV-2(−) pregnancies with high BMI (7.4%, n = 10/135). In the fourth cohort study, common lesions observed in placentae from SARS-CoV-2(+) pregnancies with high BMI (n = 187 pregnancies; mean BMI of 30 kg/m2) were chronic inflammation (99%, 186/187), MVM (40%, n = 74/187) and FVM (26%, n = 48/187). BMI and SARS-CoV-2 infection had no effect on birth anthropometry. SARS-CoV-2 infection during pregnancy associates with increased prevalence of placental pathologies, and high BMI in these pregnancies could further affect fetoplacental trajectories.
Simulation-Based Considerations on the Rayleigh Criterion in Super-Resolution Techniques Based on Speckle Interferometry
Authors: Arai Yasuhiko , Chen Tong
Published: March 2023

This study sought to explain the physical phenomenon that eludes the constraints of the Rayleigh criterion in the microstructure observation method using speckle interferometry, for which super-resolution has been experimentally proven; the study was conducted using computer simulations. Separating the light from two light sources in close proximity, which exceeded the Rayleigh criterion under incoherent light, was believed to be impossible. The simulation results, however, showed that when coherent light is used, the separation of two close points is not necessarily impossible if the light phases between the two points are different. Furthermore, the resolution of microstructure observation techniques based on speckle interferometry was discussed. A new interpretation of the Rayleigh criterion in super-resolution techniques based on speckle interferometry was reported.
Farm or Lab? A Comparative Study of Oregano’s Leaf and Callus Volatile Isolates Chemistry and Cytotoxicity
Authors: Kakalis Antonis , Tsekouras Vasileios , Mavrikou Sofia , Moschopoulou Georgia , Kintzios Spyridon , Evergetis Epameinondas , Iliopoulos Vasilios , Koulocheri Sofia D. , Haroutounian Serkos A.
Published: March 2023

Oregano (Origanum vulgare, Lamiaceae plant family) is a well-known aromatic herb with great commercial value, thoroughly utilized by food and pharmaceutical industries. The present work regards the comparative assessment of in vitro propagated and commercially available oregano tissue natural products. This study includes their secondary metabolites’ biosynthesis, antioxidant properties, and anticancer activities. The optimization of callus induction from derived oregano leaf explants and excessive oxidative browning was performed using various plant growth regulators, light conditions, and antioxidant compounds. The determination of oregano callus volatiles against the respective molecules in maternal herbal material was performed using gas chromatography–mass spectrometry (GC/MS) analysis. In total, the presence of twenty-seven phytochemicals was revealed in both leaf and callus extracts, from which thirteen molecules were biosynthesized in both tissues studied, seven compounds were present only in callus extracts, and seven metabolites only in leaf extracts. Carvacrol and sabinene hydrate were the prevailing volatiles in all tissues exploited, along with alkanes octacosane and triacontane and the trimethylsilyl (TMS) derivative of carvacrol that were detected in significant amounts only in callus extracts. The MTT assay was employed to assess the in vitro cytotoxic properties of oregano extracts against the epithelial human breast cancer MDA-MB-231 and the human neuroblastoma SK-N-SH cell lines. The extracts displayed concentration and time-dependent responses in cell proliferation rates.
Biological Methanation in an Anaerobic Biofilm Reactor—Trace Element and Mineral Requirements for Stable Operation
Authors: Tauber Joseph , Möstl Daniel , Vierheilig Julia , Saracevic Ernis , Svardal Karl , Krampe Jörg
Published: March 2023

Biological methanation of carbon dioxide using hydrogen makes it possible to improve the methane and energy content of biogas produced from sewage sludge and organic residuals and to reach the requirements for injection into the natural gas network. Biofilm reactors, so-called trickling bed reactors, offer a relatively simple, energy-efficient, and reliable technique for upgrading biogas via ex-situ methanation. A mesophilic lab-scale biofilm reactor was operated continuously for nine months to upgrade biogas from anaerobic sewage sludge digestion to a methane content >98%. To supply essential trace elements to the biomass, a stock solution was fed to the trickling liquid. Besides standard parameters and gas quality, concentrations of Na, K, Ca, Mg, Ni, and Fe were measured in the liquid and the biofilm using ICP-OES (inductively coupled plasma optical emission spectrometry) to examine the biofilms load-dependent uptake rate and to calculate quantities required for a stable operation. Additionally, microbial community dynamics were monitored by amplicon sequencing (16S rRNA gene). It was found that all investigated (trace) elements are taken up by the biomass. Some are absorbed depending on the load, others independently of it. For example, a biomass-specific uptake of 0.13 mg·g−1·d−1 for Ni and up to 50 mg·g−1·d−1 for Mg were measured.
Pilot Study on a New Conveyor Bed Magnetization Roasting Process for Efficient Iron Extraction from Low-Grade Siderite
Authors: Jiu Shaowu , Lin Mingkang , Zhao Bo , Chen Yanxin , Yang Chao
Published: March 2023

Realizing the large-scale development and utilization of siderite, a difficult iron ore reserve, has great practical significance in ensuring the supply of iron ore resources. Therefore, a new in-house conveyor bed magnetization roasting–dry cooling process was pilot-tested using low-grade siderite from the Daxigou iron ore mine. A two-stage weak magnetic separation method was used for a beneficiation test to investigate the influence of temperature and CO content on the magnetization of siderite. At 600 °C and 800 °C under suspension, iron minerals were converted into magnetite with an effective 3–5 s residence time. Furthermore, at 600 °C and 750 °C, increasing the calcination temperature increased the iron grade and the concentrate recovery rate. However, calcination at temperatures >750 °C resulted in a slight decrease in the iron grade and recovery rate of the concentrate. 61.50% Fe grade and 80.30% concentrate recovery rate were obtained under 750 °C from magnetization roasting. Magnetization roasting in a reducing atmosphere provides mainly magnetite as the roasted ore, and increased CO content can efficiently promote this effect. At 700–780 °C and when the CO content was increased to more than 3 wt.%, the improvement of the roasting effect was very limited. Rapid cooling of the roasted ore using a mixture of circulating exhaust gas and air could prevent considerable oxidation of the magnetic ferrous material. Therefore, the preferred process conditions are 700–780 °C with a CO content range of 1–3%. It provided a concentrate iron grade of 59.27–61.50% and a recovery rate of 78.32–80.30%. The results of this study provide a reference for the development of conveyor bed magnetization technology, process design, and production control.
Economic, Exergoeconomic and Exergoenvironmental Evaluation of Gas Cycle Power Plant Based on Different Compressor Configurations
Authors: Almutairi Hamad H. , Almutairi Abdulrahman S. , Suleiman Suleiman M. , Alenezi Abdulrahman H. , Alkhulaifi Khalid A. , Alhajeri Hamad M.
Published: March 2023

The decision-making process behind the selection of a gas turbine engine (GT) is crucial and must be made in accordance with economic, environmental, and technical requirements. This paper presents the relevant economic, exergoeconomic and exergoenvironmental analyses for four GT engines with different compressor configurations. The GT engine configurations are identified according to the type of compressor: axial, axial-centrifugal, two-stage centrifugal, and centrifugal-centrifugal. The performances of the four GT engines were validated against manufacturer supplied data using specialized software. The economic analysis, a detailed life cycle costing considering the cost to be paid per unit net power obtained from the GT, and subsequent shortest payback period showed that the GT with centrifugal-centrifugal compressor was most economically feasible. This was followed, in order, by the GT-axial, GT-axial-centrifugal, and finally the GT-two-stage centrifugal configuration, where the cost of ownership for a 20 year plan ranges between 8000 USD/kW to about 12,000 USD/kW at different operational scenarios during the life cycle costing. Exergoeconomic assessment provided useful information to enhance the cost-effectiveness of all four systems by evaluating each component separately. The axial-centrifugal configuration registered the lowest CO2 emissions (about 0.7 kg/kWh); all environmental indicators confirmed it is the most environmentally friendly option.
Detecting the Archaeological Traces of Tar Production Kilns in the Northern Boreal Forests Based on Airborne Laser Scanning and Deep Learning
Authors: Anttiroiko Niko , Groesz Floris Jan , Ikäheimo Janne , Kelloniemi Aleksi , Nurmi Risto , Rostad Stian , Seitsonen Oula
Published: March 2023

This paper presents the development and application of a deep learning-based approach for semi-automated detection of tar production kilns using new Finnish high-density Airborne Laser Scanning (ALS) data in the boreal taiga forest zone. The historical significance of tar production, an important livelihood for centuries, has had extensive environmental and ecological impacts, particularly in the thinly inhabited northern and eastern parts of Finland. Despite being one of the most widespread archaeological features in the country, tar kilns have received relatively little attention until recently. The authors employed a Convolutional Neural Networks (CNN) U-Net-based algorithm to detect these features from the ALS data, which proved to be more accurate, faster, and capable of covering systematically larger spatial areas than human actors. It also produces more consistent, replicable, and ethically sustainable results. This semi-automated approach enabled the efficient location of a vast number of previously unknown archaeological features, significantly increasing the number of tar kilns in each study area compared to the previous situation. This has implications also for the cultural resource management in Finland. The authors’ findings have influenced the preparation of the renewal of the Finnish Antiquities Act, raising concerns about the perceived impacts on cultural heritage management and land use sectors due to the projected tenfold increase in archaeological site detection using deep learning algorithms. The use of environmental remote sensing data may provide a means of examining the long-term cultural and ecological impacts of tar production in greater detail. Our pilot studies suggest that artificial intelligence and deep learning techniques have the potential to revolutionize archaeological research and cultural resource management in Finland, offering promising avenues for future exploration.
New Remote Sensing Data on the Potential Presence of Permafrost in the Deosai Plateau in the Himalayan Portion of Pakistan
Authors: Melis Maria Teresa , Dessì Francesco Gabriele , Casu Marco
Published: March 2023

In this study, the presence of permafrost layer and its potential variation in the last three decades will be examined through the multitemporal analysis of satellite data in the area of the Deosai Plateau (Northern Pakistan). In the area, only global maps on the potential presence of permafrost layer are known. The results are based on the evaluation of variation of the number and water levels of the small lakes, and the changes of the extensions of the wetlands. The adopted methodology is based on the use of spectral indices and visual interpretation of a time-series data of Landsat images in the range 1990–2019, and on the processing of radar data from Sentinel 1 satellites, adopting new methods to extract the vertical displacement. The main findings are: (i) a high temporal dynamic of the number and surface areas of small lakes, and (ii) the evidence of a subduction in a wetland area (Black Hole), coherent with its extension, and suggesting the potential presence of a permafrost layer slowly degrading. This analysis can play a useful role on the management of the Deosai National Park (DNP), adopting careful measures for the human activities inside the park.
Coordinated Optimal Control of AFS and DYC for Four-Wheel Independent Drive Electric Vehicles Based on MAS Model
Authors: Zhang Niaona , Wang Jieshu , Li Zonghao , Xu Nan , Ding Haitao , Zhang Zhe , Guo Konghui , Xu Haochen
Published: March 2023

The problem that it is difficult to balance vehicle stability and economy at the same time under the starting steering condition of a four-wheel independent drive electric vehicle (4WIDEV) is addressed. In this paper, we propose a coordinated optimal control method of AFS and DYC for a four-wheel independent drive electric vehicle based on the MAS model. Firstly, the angular velocity of the transverse pendulum at the center of mass and the lateral deflection angle of the center of mass are decoupled by vector transformation, and the two-degree-of-freedom eight-input model of the vehicle is transformed into four two-degree-of-freedom two-input models, and the reduced-dimensional system is regarded as four agents. Based on the hardware connection structure and communication topology of the four-wheel independent drive electric vehicle, the reduced-dimensional model of 4WIDEV AFS and DYC coordinated optimal control is established based on graph theory. Secondly, the deviation of the vehicle transverse swing angular velocity and mass lateral deflection angle from their ideal values is oriented by combining sliding mode variable structure control (SMC) with distributed model predictive control (DMPC). A discrete dynamic sliding mode surface function is proposed for the ith agent to improve the robustness of the system in response to parameter variations and disturbances. Considering the stability and economy of the ith agent, an active front wheel steering and drive torque optimization control method based on SMC and DMPC is proposed for engineering applications. Finally, a hardware-in-the-loop (HIL) test bench is built for experimental verification, and the results show that the steering angle is in the range of 0–5°, and the proposed method effectively weighs the system dynamic performance, computational efficiency, and the economy of the whole vehicle. Compared with the conventional centralized control method, the torque-solving speed is improved by 32.33 times, and the electrical consumption of the wheel motor is reduced by 16.6%.
Reduced-Parameter YOLO-like Object Detector Oriented to Resource-Constrained Platform
Authors: Zheng Xianbin , He Tian
Published: March 2023

Deep learning-based target detectors are in demand for a wide range of applications, often in areas such as robotics and the automotive industry. The high computational requirements of deep learning severely limit its ability to be deployed on resource-constrained and energy-first devices. To address this problem, we propose a class YOLO target detection algorithm and deploy it to an FPGA platform. Based on the FPGA platform, we can make full use of its computational features of parallel computing, and the computational units such as convolution, pooling and Concat layers in the model can be accelerated for inference.To enable our algorithm to run efficiently on FPGAs, we quantized the model and wrote the corresponding hardware operators based on the model units. The proposed object detection accelerator has been implemented and verified on the Xilinx ZYNQ platform. Experimental results show that the detection accuracy of the algorithm model is comparable to that of common algorithms, and the power consumption is much lower than that of the CPU and GPU. After deployment, the accelerator has a fast inference speed and is suitable for deployment on mobile devices to detect the surrounding environment.
Transformers for Multi-Horizon Forecasting in an Industry 4.0 Use Case
Authors: Vakaruk Stanislav , Karamchandani Amit , Sierra-García Jesús Enrique , Mozo Alberto , Gómez-Canaval Sandra , Pastor Antonio
Published: March 2023

Recently, a novel approach in the field of Industry 4.0 factory operations was proposed for a new generation of automated guided vehicles (AGVs) that are connected to a virtualized programmable logic controller (PLC) via a 5G multi-access edge-computing (MEC) platform to enable remote control. However, this approach faces a critical challenge as the 5G network may encounter communication disruptions that can lead to AGV deviations and, with this, potential safety risks and workplace issues. To mitigate this problem, several works have proposed the use of fixed-horizon forecasting techniques based on deep-learning models that can anticipate AGV trajectory deviations and take corrective maneuvers accordingly. However, these methods have limited prediction flexibility for the AGV operator and are not robust against network instability. To address this limitation, this study proposes a novel approach based on multi-horizon forecasting techniques to predict the deviation of remotely controlled AGVs. As its primary contribution, the work presents two new versions of the state-of-the-art transformer architecture that are well-suited to the multi-horizon prediction problem. We conduct a comprehensive comparison between the proposed models and traditional deep-learning models, such as the long short-term memory (LSTM) neural network, to evaluate the performance and capabilities of the proposed models in relation to traditional deep-learning architectures. The results indicate that (i) the transformer-based models outperform LSTM in both multi-horizon and fixed-horizon scenarios, (ii) the prediction accuracy at a specific time-step of the best multi-horizon forecasting model is very close to that obtained by the best fixed-horizon forecasting model at the same step, (iii) models that use a time-sequence structure in their inputs tend to perform better in multi-horizon scenarios compared to their fixed horizon counterparts and other multi-horizon models that do not consider a time topology in their inputs, and (iv) our experiments showed that the proposed models can perform inference within the required time constraints for real-time decision making.
Machine Learning Analysis of Hyperspectral Images of Damaged Wheat Kernels
Authors: Dhakal Kshitiz , Sivaramakrishnan Upasana , Zhang Xuemei , Belay Kassaye , Oakes Joseph , Wei Xing , Li Song
Published: March 2023

Fusarium head blight (FHB) is a disease of small grains caused by the fungus Fusarium graminearum. In this study, we explored the use of hyperspectral imaging (HSI) to evaluate the damage caused by FHB in wheat kernels. We evaluated the use of HSI for disease classification and correlated the damage with the mycotoxin deoxynivalenol (DON) content. Computational analyses were carried out to determine which machine learning methods had the best accuracy to classify different levels of damage in wheat kernel samples. The classes of samples were based on the DON content obtained from Gas Chromatography–Mass Spectrometry (GC-MS). We found that G-Boost, an ensemble method, showed the best performance with 97% accuracy in classifying wheat kernels into different severity levels. Mask R-CNN, an instance segmentation method, was used to segment the wheat kernels from HSI data. The regions of interest (ROIs) obtained from Mask R-CNN achieved a high mAP of 0.97. The results from Mask R-CNN, when combined with the classification method, were able to correlate HSI data with the DON concentration in small grains with an R2 of 0.75. Our results show the potential of HSI to quantify DON in wheat kernels in commercial settings such as elevators or mills.
Semi-Supervised Behavior Labeling Using Multimodal Data during Virtual Teamwork-Based Collaborative Activities
Authors: Plunk Abigale , Amat Ashwaq Zaini , Tauseef Mahrukh , Peters Richard Alan , Sarkar Nilanjan
Published: March 2023

Adaptive human–computer systems require the recognition of human behavior states to provide real-time feedback to scaffold skill learning. These systems are being researched extensively for intervention and training in individuals with autism spectrum disorder (ASD). Autistic individuals are prone to social communication and behavioral differences that contribute to their high rate of unemployment. Teamwork training, which is beneficial for all people, can be a pivotal step in securing employment for these individuals. To broaden the reach of the training, virtual reality is a good option. However, adaptive virtual reality systems require real-time detection of behavior. Manual labeling of data is time-consuming and resource-intensive, making automated data annotation essential. In this paper, we propose a semi-supervised machine learning method to supplement manual data labeling of multimodal data in a collaborative virtual environment (CVE) used to train teamwork skills. With as little as 2.5% of the data manually labeled, the proposed semi-supervised learning model predicted labels for the remaining unlabeled data with an average accuracy of 81.3%, validating the use of semi-supervised learning to predict human behavior.
Multi-Boundary Empirical Path Loss Model for 433 MHz WSN in Agriculture Areas Using Fuzzy Linear Regression
Authors: Phaiboon Supachai , Phokharatkul Pisit
Published: March 2023

Path loss models are essential tools for estimating expected large-scale signal fading in a specific propagation environment during wireless sensor network (WSN) design and optimization. However, variations in the environment may result in prediction errors due to uncertainty caused by vegetation growth, random obstruction or climate change. This study explores the capability of multi-boundary fuzzy linear regression (MBFLR) to establish uncertainty relationships between related variables for path loss predictions of WSN in agricultural farming. Measurement campaigns along various routes in an agricultural area are conducted to obtain terrain profile data and path losses of radio signals transmitted at 433 MHz. Proposed models are fitted using measured data with “initial membership level” (μAI). The boundaries are extended to cover the uncertainty of the received signal strength indicator (RSSI) and distance relationship. The uncertainty not captured in normal measurement datasets between transmitter and receiving nodes (e.g., tall grass, weed, and moving humans and/or animals) may cause low-quality signal or disconnectivity. The results show the possibility of RSSI data in MBFLR supported at an μAI of 0.4 with root mean square error (RMSE) of 0.8, 1.2, and 2.6 for short grass, tall grass, and people motion, respectively. Breakpoint optimization helps provide prediction accuracy when uncertainty occurs. The proposed model determines the suitable coverage for acceptable signal quality in all environmental situations.
Navigation with Polytopes: A Toolbox for Optimal Path Planning with Polytope Maps and B-spline Curves
Authors: Nguyen Ngoc Thinh , Gangavarapu Pranav Tej , Kompe Niklas Fin , Schildbach Georg , Ernst Floris
Published: March 2023

To deal with the problem of optimal path planning in 2D space, this paper introduces a new toolbox named "Navigation with Polytopes" and explains the algorithms behind it. The toolbox allows one to create a polytopic map from a standard grid map, search for an optimal corridor, and plan a safe B-spline reference path used for mobile robot navigation. Specifically, the B-spline path is converted into its equivalent Bézier representation via a novel calculation method in order to reduce the conservativeness of the constrained path planning problem. The conversion can handle the differences between the curve intervals and allows for efficient computation. Furthermore, two different constraint formulations used for enforcing a B-spline path to stay within the sequence of connected polytopes are proposed, one with a guaranteed solution. The toolbox was extensively validated through simulations and experiments.
Weibull Tone Mapping (WTM) for the Enhancement of Underwater Imagery
Authors: Game Chloe Amanda , Thompson Michael Barry , Finlayson Graham David
Published: March 2023

Domain experts prefer interactive and targeted control-point tone mapping operations (TMOs) to enhance underwater image quality and feature visibility; though this comes at the expense of time and training. In this paper, we provide end-users with a simpler and faster interactive tone-mapping approach. This is built upon Weibull Tone Mapping (WTM) theory; introduced in previous work as a preferred tool to describe and improve domain expert TMOs. We allow end-users to easily shape brightness distributions according to the Weibull distribution, using two parameter sliders which modify the distribution peak and spread. Our experiments showed that 10 domain experts found the two-slider Weibull manipulation sufficed to make a desired adjustment in >80% of images in a large dataset. For the remaining ∼20%, observers opted for a control-point TMO which can, broadly, encompass many global tone mapping algorithms. Importantly, 91% of these control-point TMOs can actually be visually well-approximated by our Weibull slider manipulation, despite users not identifying slider parameters themselves. Our work stresses the benefit of the Weibull distribution and significance of image purpose in underwater image enhancement.
Physiological and Biomechanical Monitoring in American Football Players: A Scoping Review
Authors: Nocera Antonio , Sbrollini Agnese , Romagnoli Sofia , Morettini Micaela , Gambi Ennio , Burattini Laura
Published: March 2023

American football is the sport with the highest rates of concussion injuries. Biomedical engineering applications may support athletes in monitoring their injuries, evaluating the effectiveness of their equipment, and leading industrial research in this sport. This literature review aims to report on the applications of biomedical engineering research in American football, highlighting the main trends and gaps. The review followed the PRISMA guidelines and gathered a total of 1629 records from PubMed (n = 368), Web of Science (n = 665), and Scopus (n = 596). The records were analyzed, tabulated, and clustered in topics. In total, 112 studies were selected and divided by topic in the biomechanics of concussion (n = 55), biomechanics of footwear (n = 6), biomechanics of sport-related movements (n = 6), the aerodynamics of football and catch (n = 3), injury prediction (n = 8), heat monitoring of physiological parameters (n = 8), and monitoring of the training load (n = 25). The safety of players has fueled most of the research that has led to innovations in helmet and footwear design, as well as improvements in the understanding and prevention of injuries and heat monitoring. The other important motivator for research is the improvement of performance, which has led to the monitoring of training loads and catches, and studies on the aerodynamics of football. The main gaps found in the literature were regarding the monitoring of internal loads and the innovation of shoulder pads.
Medicinal Chemistry of Quinazolines as Anticancer Agents Targeting Tyrosine Kinases
Authors: Zayed Mohamed F.
Published: March 2023

Cancer is a large group of diseases that can affect any organ or body tissue due to the abnormal cellular growth with the unknown reasons. Many of the existing chemotherapeutic agents are highly toxic with a low level of selectivity. Additionally, they lead to development of therapeutic resistance. Hence, the development of targeted chemotherapeutic agents with low side effects and high selectivity is required for cancer treatment. Quinazoline is a vital scaffold well-known to be linked with several biological activities. The anticancer activity is one of the prominent biological activities of this scaffold. Several established anticancer quinazolines work by different mechanisms on the various molecular targets. The aim of this review is to present different features of medicinal chemistry as drug design, structure activity relationship, and mode of action of some targeted anticancer quinazoline derivatives. It gives comprehensive attention on the chemotherapeutic activity of quinazolines in the viewpoint of drug discovery and its development. This review provides panoramic view to the medicinal chemists for supporting their efforts to design and synthesize novel quinazolines as targeted chemotherapeutic agents.
A Method to Determine an Equity Score for Transportation Systems in the Cities
Authors: Nadimi Navid , Camporeale Rosalia , Khaleghi Mostafa , Haghani Mohamadreza , Sheykhfard Abbas , Shaaban Khaled
Published: March 2023

Transportation equity is vital for the fulfillment of citizens’ activities. To make better decisions for transportation planning, it is appropriate to have a method to evaluate each mode and assign an equity score to it. This paper aims to propose a method to assess the level of equity using different transportation modes in each zone of a city. Here, the equity level takes into account on one side the proportion between the frequency of long and short-distance trips, the volume-to-capacity ratio of streets, the air quality, and the parking availability. On the other side, the ratio of costs associated with using passenger cars, the average income of the residents, and transit and cycling infrastructure quality is used in a zone of a city. In this regard, at first, indicators are considered to assess the condition of buses, cycling, and passenger cars. Then, the Fuzzy Inference System (FIS) is used to determine the level of equity for each mode. The method has been applied to regular buses, cycling, and passenger cars in Kerman, Iran, as a case study. The results indicate a significant difference between the equity levels perceived by citizens and the performed calculations. The citizens’ perceptions about the equity of regular buses and cycling seem to be more pessimistic than what the FIS model shows. Based on the model outputs, more restrictions must be established about using passenger cars in most of the zones. Nevertheless, in this regard, citizens have stated that the current situation is fair. We believe this method can be a helpful way to quantitatively assess the equity level of transportation systems in each zone.
Supplementary Cementitious Materials in Building Blocks—Diagnosing Opportunities in Sub-Saharan Africa
Authors: Isaksson Raine , Rosvall Max , Babaahmadi Arezou , Buregyeya Apollo , Hazarika Amrita , Marangu Joseph Mwiti , Olonade Kolawole , Ramanathan Swaminathan , Rucukye Anthony , Valentini Luca
Published: March 2023

Sustainable building should at least be affordable and carbon neutral. Sub-Saharan Africa (SSA) is a region struggling with housing affordability. Residential buildings are often constructed using block-based materials. These are increasingly produced using ordinary Portland cement (PC), which has a high carbon footprint. Using alternative Supplementary Cementitious Materials (SCMs) for block production might reduce the footprint and price. The purpose is to assess the level of information for SCM use in blocks in SSA and to use this information for Diagnosing the improvement potential as part of an Opportunity Study. Results from the scoping review show that aggregated information on SCMs and the quantities available is limited. Diagnosing the theoretical improvement potential in using cassava peel ash, rice husk ash, corn cob ash, volcanic ash and calcined clays, indicates that SCMs could represent a yearly value of approximately USD 400 million, which could be transferred from buying cement to local production. The use of SCMs could save 1.7 million tonnes of CO2 per year and create some 50,000 jobs. About 5% of the PC used for block production could be substituted, indicating that, in addition to using SCMs, other solutions are needed to secure production of sustainable blocks.
The ISO/IEC 27001 Information Security Management Standard: How to Extract Value from Data in the IT Sector
Authors: Kitsios Fotis , Chatzidimitriou Elpiniki , Kamariotou Maria
Published: March 2023

In order to handle their regulatory and legal responsibilities and to retain trustworthy strategic partnerships, enterprises need to be dedicated to guaranteeing the privacy, accessibility, and authenticity of the data at their disposal. Companies can become more resilient in the face of information security threats and cyberattacks by effectively integrating security strategies. The goal of this article is to describe a plan that a corporation has implemented in the information technology industry in order to ensure compliance with International Organization for Standardization (ISO) 27001. This research demonstrates an examination of the reasons that force enterprises to make a investment in ISO 27001 in addition to the incentives that might be acquired from having undergone this process. In addition, the research examines the reasons that push firms to make an investment in ISO 27001. More particularly, the research investigates an international IT consulting services institution that is responsible for the implementation of large-scale business assistance insertion and projects. It demonstrates the risk management framework and the administrative structure of the appropriate situations so that its procedures are adequate and also in line with the guidelines founded by ISO 27001. In conclusion, it discusses the problems and difficulties that were experienced.
Spatiotemporal Evolution of Wind Erosion and Ecological Service Assessments in Northern Songnen Plain, China
Authors: Mo Jixian , Li Jie , Wang Ziying , Song Ziwei , Feng Jingyi , Che Yanjing , Rong Jiandong , Gu Siyu
Published: March 2023

The northern Songnen Plain in China is one of the most important areas for grain production in China, which has been increasingly affected by wind erosion in recent years. This study analyzed the dynamic spatiotemporal distribution of wind erosion in the northern Songnen Plain from 2010 to 2018 using the Revised Wind Erosion Equation model. The ecological service function of the study area was evaluated by constructing a spatial visualization map of windbreak and sand-fixation service flow. Wind erosion worsened from 2010 to 2018. The gravity center of different categories of wind erosion intensity moved to the northeast, indicating a risk of spreading from south to north. The amount of wind erosion in 2018 increased by 50.78% compared with 2010. The increase of wind force and temperature and the decrease of precipitation may have contributed to these trends. Long-term wind erosion led to soil coarsening, decreased soil organic matter, soil organic carbon, and total nitrogen contents, and increased soil CaCO3 and pH, which may be one reason for slight soil salinization observed in some regions. Therefore, windbreak and sand-fixation management and eco-environmental protection are urgently required. This study is the first detailed assessment of wind erosion in the northern Songnen Plain on a regional scale and the first to propose measures for ecological restoration and desertification control.
Maintenance Policies and Practices on Resilient Houses: Case Study from a Coastal Resilience Project in Vietnam
Authors: Tuan Hai Dinh , Kim Hoang Nguyen
Published: March 2023

Vietnam is a country that experiences extreme climate conditions and annual accumulated damage due to typhoons and floods, which seriously destroy houses and cause many deaths. Approximately half a million people currently living within 200 m from the coastline live in unsafe houses. Therefore, the Coastal Resilience Project (the project) was implemented to build 4000 storm- and flood-resistant houses for five coastal provinces in Central Vietnam. The paper is carried out to review existing policies and practices related to the maintenance of resilient houses, as well as to propose feasible maintenance solutions for houses to ensure the sustainability of the project. The result shows that currently, there are no technical instructions or manuals on the maintenance and repair of individual houses in general, or the project houses in particular. Most of the households in the project also have very low and unstable incomes. In addition, as they lack knowledge of how construction works, they know little to nothing about the maintenance of a house. From these findings, the authors recommend several solutions for better maintenance policies and practices on the resilient houses of the project in Vietnam. The project provides several lessons in terms of the maintenance of the resilient houses of future projects in Vietnam and elsewhere, by reviewing existing policies and current practices, as well as proposing feasible measures to ensure the sustainability of the project. The findings in this paper provide valuable information for better maintenance policies and practices of resilient houses for other vulnerable coastal provinces in Vietnam and similar contexts elsewhere.