bluuebunny/crossref_metadata_2025 huggingface dataset:
Assessment of the Influence of Storage Conditions and Time on Red Currants (Ribes rubrum L.) Using Image Processing and Traditional Machine Learning
Authors: Ropelewska Ewa
Published: October 2022

This study was aimed at revealing the usefulness of the combination of image analysis and artificial intelligence in assessing the quality of red currants in terms of external structure changes under the influence of different storage conditions. Red currants after harvest were subjected to storage at room temperature and at a lower temperature in the refrigerator for one week and two weeks. The statistically significant differences in selected image textures as a result of prolonged storage were determined for both samples stored in the room and the refrigerator. However, the changes in the structure of the red currant samples stored at room temperature were greater than for storage in the refrigerator. Distinguishing samples using models built using machine learning algorithms confirmed the usefulness of selected textures to assess the influence of storage conditions and time on red currants. Unstored red currants, samples stored at room temperature for one week, and those stored at room temperature for two weeks were classified with an accuracy of 99–100%, and unstored samples, fruit stored in the refrigerator for one week, and that stored in the refrigerator for two weeks were correctly distinguished at an accuracy of 97–100%, depending on the algorithm. Models developed for distinguishing red currants stored at room temperature and in the refrigerator for one week provided an accuracy of 99–100%, and for the classification of red currants stored at room temperature and in the refrigerator for two weeks, an accuracy equal to 100% for all used algorithms was determined.
Soil Properties of Different Planting Combinations of Zanthoxylum planispinum var. dintanensis Plantations and Their Effect on Stoichiometry
Authors: Li Yitong , Yu Yanghua , Song Yanping
Published: October 2022

The soil quality of plantations with different planting patterns and the effect of soil quality on stoichiometry provide a theoretical basis for the selection of Zanthoxylum planispinum var. dintanensis (hereafter Z. planispinum) planting patterns and nutrient management. Four mixed plantations: Z. planispinum + Prunus salicina, Z. planispinum + Sophora tonkinensis, Z. planispinum + Arachis hypogaea, and Z. planispinum + Lonicera japonica, and a monoculture Z. planispinum plantation were selected to clarify the effect of soil quality on stoichiometry. The results showed that the soil quality index (SQI) of Z. planispinum + L. japonica (1.678) was the highest, indicating that it was the preferred planting combination and that it was significantly limited by soil water content (SWC). The nutrient forms, SWC, and pH all have significant effects on processes such as nutrient transformation and cycling. The contributions of total Ca and total Mg in soil nutrients to stoichiometry were relatively high, while the effect of SQI on stoichiometry was not significant. The microbial stoichiometry ratio was mainly influenced by microbial biomass phosphorus, reflecting that microorganisms have strong internal stability. Strong interactions among soil factors occur, affecting elemental geochemical processes. The regulatory effects of different soil factors on their stoichiometry should be emphasized.
Epidemiology of Nocardia Species at a Tertiary Hospital in Southern Taiwan, 2012 to 2020: MLSA Phylogeny and Antimicrobial Susceptibility
Authors: Kuo Shu-Fang , Chen Fang-Ju , Lan I-Chia , Chien Chun-Chih , Lee Chen-Hsiang
Published: October 2022

The identification and antimicrobial susceptibility of Nocardia spp. are essential for guiding antibiotic treatment. We investigated the species distribution and evaluated the antimicrobial susceptibility of Nocardia species collected in southern Taiwan from 2012 to 2020. A total of 77 Nocardia isolates were collected and identified to the species level using multi-locus sequence analysis (MLSA). The susceptibilities to 15 antibiotics for Nocardia isolates were determined by the broth microdilution method, and the MIC50 and MIC90 for each antibiotic against different species were analyzed. N. cyriacigeorgica was the leading isolate, accounting for 32.5% of all Nocardia isolates, and the prevalence of Nocardia isolates decreased in summer. All of the isolates were susceptible to trimethoprim/sulfamethoxazole, amikacin, and linezolid, whereas 90.9% were non-susceptible to cefepime and imipenem. The phylogenic tree by MLSA showed that the similarity between N. beijingensis and N. asiatica was as high as 99%, 73% between N. niigatensis and N. crassostreae, and 86% between N. cerradoensis and N. cyriacigeorgica. While trimethoprim/sulfamethoxazole, amikacin, and linezolid remained fully active against all of the Nocardia isolates tested, 90.9% of the isolates were non-susceptible to cefepime and imipenem.
Emergence of Cfr-Mediated Linezolid Resistance among Livestock-Associated Methicillin-Resistant Staphylococcus aureus (LA-MRSA) from Healthy Pigs in Portugal
Authors: Leão Célia , Clemente Lurdes , Cara d’Anjo Maria , Albuquerque Teresa , Amaro Ana
Published: October 2022

Livestock-associated methicillin-resistant Staphylococcus aureus (LA-MRSA) ST398 is mainly found in Europe and North America, colonizing the nasal cavity of pigs. This study characterized the MRSA isolates recovered from pig nasal swabs (n = 171) by evaluating the antimicrobial susceptibility profile by broth microdilution and characterizing the genetic lineages by spa-typing. Three linezolid-resistant isolates were subjected to Whole-Genome Sequencing (WGS). All strains harbored the mecA gene and were resistant to tetracycline and susceptible to vancomycin. A high frequency of multidrug resistance (97.6%) was evidenced, with 55 different multidrug resistance profiles identified. The MRSA strains were found to belong to 17 spa-types, three being novel. The linezolid-resistant strains appeared to belong to the ST398 type, spa-type t011, and SCCmec_type_Vc and to harbor the cfr, fexA, blaZ, mecA, tetM, and tetK genes. The cfr gene was predicted to be carried in the plasmid, flanked by ISSau9 and the transposon TnpR. MRSA from Portuguese fattening pigs present a high diversity of genetic lineages. The presence of cfr-positive LA-MRSA may represent a risk of transmission to humans, mainly to those in contact with livestock.
Combination Regimens with Colistin Sulfate versus Colistin Sulfate Monotherapy in the Treatment of Infections Caused by Carbapenem-Resistant Gram-Negative Bacilli
Authors: Hao Min , Yang Yang , Guo Yan , Wu Shi , Hu Fupin , Qin Xiaohua
Published: October 2022

Carbapenem-resistant organisms (CRO) have become a global concern because of the limited antibiotic treatment options for CRO infections. Colistin sulfate is a type of polymyxin approved for the treatment of CRO in China. To date, studies on polymyxin have mainly focused on in vitro antibacterial activity or pharmacokinetics/pharmacodynamics, and few have evaluated its clinical efficacy. We aimed to compare the clinical efficacy and safety of colistin sulfate monotherapy and its combination with other antimicrobials in the treatment of carbapenem-resistant Gram-negative bacilli (CR-GNB) infections in adults. This retrospective study included adult patients with CR-GNB infections treated with colistin sulfate by intravenous drip between January and June 2020. The patients were divided into two groups, according to the administration of colistin sulfate alone or in combination with other antibiotics. Group-wise demographic data, comorbidities, clinical efficacy, prognosis, and adverse events were analyzed and compared. In total, 26 patients in the colistin sulfate monotherapy group and 54 patients in the combined therapy group were recruited. The clinical efficacy in the combined therapy group (94.4%) was significantly higher than that in the colistin monotherapy group (73.1%) (p = 0.007); however, the 28-day mortality and length of hospital stay were not significantly different between groups. The incidence of adverse events (including elevated aminotransferase, bilirubin, serum creatinine, and decreased platelet) was not significantly different between the groups. Combination therapies with colistin sulfate are recommended for the treatment of CR-GNB infections, over colistin sulfate alone.
A Chlorophyll-Derived Phylloxanthobilin Is a Potent Antioxidant That Modulates Immunometabolism in Human PBMC
Authors: Karg Cornelia A. , Parráková Lucia , Fuchs Dietmar , Schennach Harald , Kräutler Bernhard , Moser Simone , Gostner Johanna M.
Published: October 2022

Phyllobilins are natural products derived from the degradation of chlorophyll, which proceeds via a common and strictly controlled pathway in higher plants. The resulting tetrapyrrolic catabolites—the phyllobilins—are ubiquitous in nature; despite their high abundance, there is still a lack of knowledge about their physiological properties. Phyllobilins are part of human nutrition and were shown to be potent antioxidants accounting with interesting physiological properties. Three different naturally occurring types of phyllobilins—a phylloleucobilin, a dioxobilin-type phylloleucobilin and a phylloxanthobilin (PxB)—were compared regarding potential antioxidative properties in a cell-free and in a cell-based antioxidant activity test system, demonstrating the strongest effect for the PxB. Moreover, the PxB was investigated for its capacity to interfere with immunoregulatory metabolic pathways of tryptophan breakdown in human blood peripheral mononuclear cells. A dose-dependent inhibition of tryptophan catabolism to kynurenine was observed, suggesting a suppressive effect on pathways of cellular immune activation. Although the exact mechanisms of immunomodulatory effects are yet unknown, these prominent bioactivities point towards health-relevant effects, which warrant further mechanistic investigations and the assessment of the in vivo extrapolatability of results. Thus, phyllobilins are a still surprisingly unexplored family of natural products that merit further investigation.
Fermented Ginger Extract in Natural Deep Eutectic Solvent Enhances Cytotoxicity by Inhibiting NF-κB Mediated CXC Chemokine Receptor 4 Expression in Oxaliplatin-Resistant Human Colorectal Cancer Cells
Authors: Lee Ko-Chao , Wu Kuen-Lin , Chang Shun-Fu , Chang Hsin-I , Chen Cheng-Nan , Chen Yih-Yuan
Published: October 2022

Ginger extracts have been shown to have health-promoting pharmacological activity and beneficial effects, including antioxidant and anticancer properties. The extraction of ginger by natural deep eutectic solvents (NaDES) has been shown to enhance bioactivity, but the cytotoxicity of NaDES extracts needs to be further determined. Signaling through the CXC chemokine receptor 4 (CXCR4) expressed on colorectal cancer (CRC) cells has a pivotal role in tumor cell chemosensitivity. Oxaliplatin is a third-generation platinum compound used as an effective chemotherapeutic drug for CRC treatment. However, whether ginger extract and oxaliplatin could induce a synergistic cytotoxic effect in oxaliplatin-resistant CRC cells through modulating CXCR4 expression is not known. In this study, oxaliplatin-resistant HCT-116 (HCT-116/R) cells were generated first. Ginger was extracted using the NaDES mixture betaine/lactate/water (1:2:2.5). Lactobacillus reuteri fermentation of NaDES-ginger extract increased the total polyphenol content (12.42 mg gallic acid/g in non-fermented NaDES-ginger extract and 23.66 mg gallic acid/g in fermented NaDES-ginger extract). It also increased the antioxidant activity by about 20–30% compared to non-fermented NaDES-ginger extract. In addition, it achieved low cytotoxicity to normal colonic mucosal cells and enhanced the anticancer effect on HCT-116/R cells. On the other hand, the inhibition of NF-κB activation by fermented NaDES-ginger extract significantly decreased the CXCR4 expression (p < 0.05) in HCT-116/R cells. The inactivation of NF-κB by pharmacological inhibitor pyrrolidine dithiocarbamate further enhanced the fermented NaDES-ginger extract-reduced CXCR4 expression levels (p < 0.05). Moreover, fermented NaDES-ginger extract could synergistically increase the cytotoxicity of oxaliplatin by inhibiting CXCR4 expression and inactivating NF-κB, resulting in HCT-116/R cell death. These findings demonstrate that fermented NaDES-ginger extract reduces the NF-kB-mediated activation of CXCR4 and enhances oxaliplatin-induced cytotoxicity in oxaliplatin-resistant CRC cells.
Integrated Physiological, Transcriptomic, and Proteomic Analyses Reveal the Regulatory Role of Melatonin in Tomato Plants’ Response to Low Night Temperature
Authors: Yang Xiaolong , Zhang Yumeng , Liu Ting , Shi Jiali , Qi Mingfang , Liu Yufeng , Li Tianlai
Published: October 2022

Melatonin is a direct free radical scavenger that has been demonstrated to increase plants’ resistance to a variety of stressors. Here, we sought to examine the effect of melatonin on tomato seedlings subjected to low night temperatures using an integrated physiological, transcriptomic, and proteomic approach. We found that a pretreatment with 100 μM melatonin increased photosynthetic and transpiration rates, stomatal apertures, and peroxidase activity, and reduced chloroplast damage of the tomato plant under a low night temperature. The melatonin pretreatment reduced the photoinhibition of photosystem I by regulating the balance of both donor- and acceptor-side restriction of PSI and by increasing electron transport. Furthermore, the melatonin pretreatment improved the photosynthetic performance of proton gradient regulation 5 (SlPGR5) and SlPGR5-like photosynthetic phenotype 1 (SlPGRL1)-suppressed transformants under a low night temperature stress. Transcriptomic and proteomic analyses found that the melatonin pretreatment resulted in the upregulation of genes and proteins related to transcription factors, signal transduction, environmental adaptation, and chloroplast integrity maintenance in low night temperature-stressed tomato plants. Collectively, our results suggest that melatonin can effectively improve the photosynthetic efficiency of tomato plants under a low night temperature and provide novel insights into the molecular mechanism of melatonin-mediated abiotic stress resistance.
Redox Status Is the Mainstay of SARS-CoV-2 and Host for Producing Therapeutic Opportunities
Authors: Thirupathi Anand , Gu Yaodong , Radak Zsolt , Pinho Ricardo A
Published: October 2022

Over hundreds of years, humans have faced multiple pandemics and have overcome many of them with scientific advancements. However, the recent coronavirus disease (COVID-19) has challenged the physical, mental, and socioeconomic aspects of human life, which has introduced a general sense of uncertainty among everyone. Although several risk profiles, such as the severity of the disease, infection rate, and treatment strategy, have been investigated, new variants from different parts of the world put humans at risk and require multiple strategies simultaneously to control the spread. Understanding the entire system with respect to the commonly involved or essential mechanisms may be an effective strategy for successful treatment, particularly for COVID-19. Any treatment for COVID-19 may alter the redox profile, which can be an effective complementary method for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) entry and further replication. Indeed, redox profiles are one of the main barriers that suddenly shift the immune response in favor of COVID-19. Fortunately, several redox components exhibit antiviral and anti-inflammatory activities. However, access to these components as support elements against COVID-19 is limited. Therefore, understanding redox-derived species and their nodes as a common interactome in the system will facilitate the treatment of COVID-19. This review discusses the redox-based perspectives of the entire system during COVID-19 infection, including how redox-based molecules impact the accessibility of SARS-CoV-2 to the host and further replication. Additionally, to demonstrate its feasibility as a viable approach, we discuss the current challenges in redox-based treatment options for COVID-19.
Genetic Mechanism for Antioxidant Activity of Endogenous Enzymes under Salinity and Temperature Stress in Turbot (Scophthalmus maximus)
Authors: Wang Xinan , Ma Aijun , Huang Zhihui , Sun Zhibin , Liu Zhifeng
Published: October 2022

Three antioxidant properties (corresponding to the enzymes superoxide dismutase (SOD), catalase, and glutathione peroxidase) were measured in the livers of Scophthalmus maximus under different salinities/temperatures (5, 10, 20, 30, and 40‰/17, 20, 23, 25, and 28 °C). Split-plot (SP) analysis, additive main effects, and multiplicative interaction (AMMI) and genotype × environment interaction (GGE) biplots were used to analyze genotype × salinity/temperature interactions for antioxidant properties. The results of the SP analysis show that the activity of the three antioxidant properties was significantly (p < 0.01) affected by salinity/temperature, antioxidant, and salinity/temperature × antioxidant interaction. The results of the AMMI analysis for salinity reveal that the effect of genotype, salinity, and genotype × salinity interaction on antioxidant properties reached a significant level (p < 0.001); 92.1065%, 2.6256%, and 4.4360% of the total sum of squares for antioxidant property activity were attributable to the effects of genotype, salinity, and genotype × salinity interaction, respectively. The results of GGE biplot analysis for salinity reveal differences in the activity ranking of the three antioxidant properties under five salinities; this difference expands with an decrease or increase in salinity from 30‰ (optimum salinity). A salinity of 5‰ had the strongest ability to identify the three antioxidant properties. The five experimental salinities were divided into one region, and SOD activity was the highest in this region. In a comprehensive analysis of stability and activity, SOD had the best activity and stability. The results of AMMI analysis for temperature reveal that genotype, temperature, and genotype × temperature interaction had significant effects on the antioxidant properties (p < 0.001); 82.4720%, 4.0666%, and 12.0968% of the total sum of squares for antioxidant property activity were attributable to the effects of genotype, temperature, and genotype × temperature interaction, respectively. The results of GGE biplot analysis for temperature reveal a large difference in the activity ranking of antioxidant properties between 17 °C and the other four temperatures, while only small differences in the activity rankings were detected among the other four temperatures. The difference in the activity ranking of antioxidant properties was greatest between the temperatures of 17 and 20 °C. A temperature of 17 °C showed the strongest ability to distinguish the three antioxidant properties. Additionally, the five test temperatures were grouped into one region, and comprehensive analysis of activity and stability showed that SOD had the best activity and stability.
Role of Nutrients and Foods in Attenuation of Cardiac Remodeling through Oxidative Stress Pathways
Authors: Lazzarin Taline , Garcia Leonardo Rufino , Martins Danilo , Queiroz Diego Aparecido Rios , Tonon Carolina Rodrigues , Balin Paola da Silva , Polegato Bertha Furlan , Paiva Sergio Alberto Rupp de , Azevedo Paula Schmidt , Minicucci Marcos , Zornoff Leonardo
Published: October 2022

Cardiac remodeling is defined as a group of molecular, cellular, and interstitial changes that manifest clinically as changes in the heart’s size, mass, geometry, and function after different injuries. Importantly, remodeling is associated with increased risk of ventricular dysfunction and heart failure. Therefore, strategies to attenuate this process are critical. Reactive oxygen species and oxidative stress play critical roles in remodeling. Importantly, antioxidative dietary compounds potentially have protective properties against remodeling. Therefore, this review evaluates the role of nutrients and food as modulators of cardiac remodeling.
Research on the Symbolic 3D Route Scene Expression Method Based on the Importance of Objects
Authors: Han Fulin , Huo Liang , Shen Tao , Zhang Xiaoyong , Zhang Tianjia , Ma Na
Published: October 2022

In the study of 3D route scene construction, the expression of key targets needs to be highlighted. This is because compared with the 3D model, the abstract 3D symbols can reflect the number and spatial distribution characteristics of entities more intuitively. Therefore, this research proposes a symbolic 3D route scene representation method based on the importance of the object. The method takes the object importance evaluation model as the theoretical basis, calculates the spatial importance of the same type of objects according to the spatial characteristics of the geographical objects in the 3D route scene, and constructs the object importance evaluation model by combining semantic factors. The 3D symbols are then designed in a hierarchical manner on the basis of the results of the object importance evaluation and the CityGML standard. Finally, the LOD0-LOD4 symbolic 3D railway scene was constructed on the basis of a railroad data to realise the multi-scale expression of symbolic 3D route scene. Compared with the conventional loading method, the real-time frame rate of the scene was improved by 20 fps and was more stable. The scene loading speed was also improved by 5–10 s. The results show that the method can effectively improve the efficiency of the 3D route scene construction and the prominent expression effect of the key objects in the 3D route scene.
Detection and Classification of COVID-19 by Radiological Imaging Modalities Using Deep Learning Techniques: A Literature Review
Authors: Althenayan Albatoul S. , AlSalamah Shada A. , Aly Sherin , Nouh Thamer , Mirza Abdulrahman A.
Published: October 2022

Coronavirus disease (COVID-19) is a viral pneumonia that originated in China and has rapidly spread around the world. Early diagnosis is important to provide effective and timely treatment. Thus, many studies have attempted to solve the COVID-19 classification problems of workload classification, disease detection, and differentiation from other types of pneumonia and healthy lungs using different radiological imaging modalities. To date, several researchers have investigated the problem of using deep learning methods to detect COVID-19, but there are still unsolved challenges in this field, which this review aims to identify. The existing research on the COVID-19 classification problem suffers from limitations due to the use of the binary or flat multiclass classification, and building classifiers based on only a few classes. Moreover, most prior studies have focused on a single feature modality and evaluated their systems using a small public dataset. These studies also show a reliance on diagnostic processes based on CT as the main imaging modality, ignoring chest X-rays, as explained below. Accordingly, the aim of this review is to examine existing methods and frameworks in the literature that have been used to detect and classify COVID-19, as well as to identify research gaps and highlight the limitations from a critical perspective. The paper concludes with a list of recommendations, which are expected to assist future researchers in improving the diagnostic process for COVID-19 in particular. This should help to develop effective radiological diagnostic data for clinical applications and to open future directions in this area in general.
A Review of Flow Control for Gust Load Alleviation
Authors: Li Yonghong , Qin Ning
Published: October 2022

Effective control of aerodynamic loads, such as maneuvering load and gust load, allows for reduced structural weight and therefore greater aerodynamic efficiency. After a basic introduction in the types of gusts and the current gust load control strategies for aircraft, we outline the conventional gust load alleviation techniques using trailing-edge flaps and spoilers. As these devices also function as high-lift devices or inflight speed brakes, they are often too heavy for high-frequency activations such as control surfaces. Non-conventional active control devices via fluidic actuators have attracted some attention recently from researchers to explore more effective gust load alleviation techniques against traditional flaps for future aircraft design. Research progress of flow control using fluidic actuators, including surface jet blowing and circulation control (CC) for gust load alleviation, is reviewed in detail here. Their load control capabilities in terms of lift force modulations are outlined and compared. Also reviewed are the flow control performances of these fluidic actuators under gust conditions. Experiments and numerical efforts indicated that both CC and surface jet blowing demonstrate fast response characteristics, capable for timely adaptive gust load controls.
Movement-in-a-Video Detection Scheme for Sign Language Gesture Recognition Using Neural Network
Authors: Caliwag Angela C. , Hwang Han-Jeong , Kim Sang-Ho , Lim Wansu
Published: October 2022

Sign language aids in overcoming the communication barrier between hearing-impaired individuals and those with normal hearing. However, not all individuals with normal hearing are skilled at using sign language. Consequently, deaf and hearing-impaired individuals generally encounter the problem of limited communication while interacting with individuals with normal hearing. In this study, a sign language recognition method based on a movement-in-a-video detection scheme is proposed. The proposed scheme is applied to extract unique spatial and temporal features from each gesture. The extracted features are subsequently used to train a neural network to classify the gestures. The proposed movement-in-a-video detection scheme is applied to sign language videos featuring short, medium, and long gestures. The proposed method achieved an accuracy of 90.33% and 40% in classifying short and medium gestures, respectively, compared with 69% and 43.7% achieved using other methods. In addition, the improved accuracies were achieved with less computational complexity and cost. It is anticipated that improvements in the proposed method, for it to achieve high accuracy for long gestures, can enable hearing-impaired individuals to communicate with normal-hearing people who do not have knowledge of sign language.
Application of Laser-Ultrasonics for Evaluating Textures and Anisotropy
Authors: Malmström Mikael , Jansson Anton , Hutchinson Bevis
Published: October 2022

Various approaches are reviewed for determining elastic anisotropy and its coupling to crystallographic texture, with special reference to ultrasonic measurements. Two new methods are described for measuring the anisotropy of P-wave velocity using laser-ultrasonics. Making measurements across the diameter of a cylindrical specimen as it is rotated makes it possible to maintain a very constant known path length. This permits extremely accurate measurements with a precision of better than 0.01%. Results on 316 stainless steel in different conditions are compared with calculated values obtained from EBSD textures together with measured densities and crystalline coefficients from the literature. Excellent agreement is obtained when applying the Hill geometrical average procedure. A similar approach is adopted to measure the variation of wave velocity in a martensitic steel, after tempering at a range of temperatures. Changes in the anisotropy associated with thermal softening are discussed. The second method uses Galvano mirrors to steer the generating laser to different positions over a sheet surface, allowing wave velocities to be determined along different directions in the anisotropic material.
The Use of Phytochemicals to Improve the Efficacy of Immune Checkpoint Inhibitors: Opportunities and Challenges
Authors: Guven Deniz Can , Sahin Taha Koray , Rizzo Alessandro , Ricci Angela Dalia , Aksoy Sercan , Sahin Kazim
Published: October 2022

Immune checkpoint inhibitors (ICIs) have revolutionized cancer therapy and reshaped medical oncology practice over the past decade. However, despite unprecedented and durable clinical responses, most patients eventually fail to respond to ICI therapy due to primary or acquired resistance. There is a great need for complementary alternative medicine, such as botanicals and nutritional supplements, because of their capability to modulate a myriad of molecular mechanisms to prevent immunotherapy resistance and reduce its adverse effects. Mounting evidence suggests that phytochemicals, biologically active compounds derived from plants, can favorably regulate key signaling pathways involved in tumor development and progression. In addition, phytochemicals have been found to exert anticancer effects by altering the expression of checkpoint inhibitors of the immune response. The immunomodulatory activity of phytochemicals in the tumor microenvironment has recently received immense interest. Based on these immunomodulatory activities, phytochemicals could be candidates for combination with ICIs in future clinical studies. The current review focuses on the available evidence for combining phytochemicals with a discussion on the promising opportunities to enhance the efficacy of immune checkpoint inhibitors and potential challenges resulting from these combinations.
Soil Salinity Prediction and Its Severity Mapping Using a Suitable Interpolation Method on Data Collected by Electromagnetic Induction Method
Authors: Jantaravikorn Yuratikan , Ongsomwang Suwit
Published: October 2022

Salt mining and shrimp farming have been practiced in the Non Thai district and the surrounding areas for more than 30 years, creating saline soil problems. To solve the soil salinity problem, soil salinity prediction and mapping utilizing the electromagnetic induction method (EMI) and spatial interpolation methods were examined in the Non Thai district, Nakhon Ratchasima province, Thailand. The research objectives were (1) to predict soil salinity using spatial interpolation methods and (2) to identify a suitable spatial interpolation method for soil salinity severity mapping. The research methodology consisted of five steps: apparent electrical conductivity (ECa) measurement using an electromagnetic induction (EMI) method; in situ soil sample collection and electrical conductivity of the saturated soil paste extract (ECe) measurement; soil electrical conductivity estimation using linear regression analysis (LRA); soil salinity prediction and accuracy assessment; and soil salinity severity classification and overlay analysis with relevant data. The result of LRA showed a strong positive relationship between ECe and ECa. The correlation coefficient (R) values of a horizontal measuring mode (HH) and a vertical measuring mode (VV) were 0.873 to 0.861, respectively. Four selected interpolation methods—Inverse Distance Weighting (IDW), Ordinary Kriging (OK), Ordinary CoKriging (OCK) with soil moisture content, and Regression Kriging (RK) without covariable factor—provided slightly different patterns of soil salinity prediction with HH and VV modes. The mean values of the ECe prediction from the four methods at the district level varied from 2156.02 to 2293.25 mS/m for HH mode and from 2377.38 to 2401.41 mS/m for VV mode. Based on the accuracy assessment with the rank-sum technique, the OCK is a suitable interpolation method for soil salinity prediction for HH mode. At the same time, the IDW is suitable for soil salinity prediction for the VV mode. The dominant soil salinity severity classes of the two measuring modes using suitable spatial interpolation methods were strongly and very strongly saline. Consequently, the developed research methodology can be applied to conduct soil salinity surveys to reduce costs and save time in other areas by government agencies in Thailand. Nevertheless, to apply the EMI method for soil salinity survey, the users should understand the principle of EMI and how to calibrate and operate the EM device properly for accurate ECa measurement.
Case Study in Modular Lightweight Steel Frame Construction: Thermal Bridges and Energy Performance Assessment
Authors: Milovanović Bojan , Bagarić Marina , Gaši Mergim , Vezilić Strmo Nikolina
Published: October 2022

This paper proposes an improvement of the conventional Lightweight Steel Frame (LSF) wall structure suitable for the design of high-performance modular buildings. A mobile module, named MUZA, is used as a case study building to analyse the performance of such LSF structures in terms of their thermal bridging effect on the U-value of the opaque envelope elements, linear heat losses at junctions, and moisture condensation risk, as well as thermal bridging effect on the overall energy performance of the building. The study included an additional climate- and orientation-dependent analysis that examined the performance of MUZA under various conditions. The main conclusion is that the steel studs increase the U-value from 28.4% to 41.6% compared to cases without the studs, which consequently increases transmission losses through opaque elements. Thanks to the continuous covering of the metal studs with thermal insulation, the thermal bridges at the element junctions are minimized, and in almost all cases, the Ψ-values are well below 0.1 W/(m·K) and are free from moisture condensation. The overall impact of thermal bridges on heating energy demand is significant, while the impact on cooling energy is less pronounced. The designed module with the proposed LSF wall structure can meet the Croatian requirements for Nearly Zero-Energy Buildings (NZEB), but the shading devices and photovoltaics orientation must be optimized depending on the climatic conditions and the orientation of the large transparent openings. MUZA can be a promising solution for post-disaster housing, providing better indoor environmental quality, healthy living conditions, and low energy bills for the affected people. In addition, it can also be used for permanent housing when a fast and robust modular construction is required which is also energy efficient and sustainable.
Pseudo-3D Receiver Deghosting of Seismic Streamer Data Based on l1 Norm Sparse Inversion
Authors: Wang Rui , Wang Deli , Zhang Weifeng , Liu Yingxin , Hu Bin , Wang Longlong
Published: October 2022

The ghost effect in marine seismic data causes low-frequency suppression and frequency notch, resulting in incomplete frequency information for seismic records, which poses challenges for high-resolution imaging. The deghosting effect depends on the approximation of the ghost delay operator. Due to the strict requirements of dense sampling, the 2D deghosting method for a densely sampled inline dataset is still the mainstream method for marine data processing. As the trade-off, inversion-based methods are widely used in the industry to reduce the influence of the inaccurate ghost delay operator. In order to overcome the sampling limits and improve the 2D deghosting effect, we propose a pseudo-3D deghosting framework based on an l1 norm sparse inversion. In the framework, the inversion problem is divided into two subproblems, i.e., pseudo-3D operator building and optimization inversion. Considering the data coherence along the shot direction, we derive a pseudo-3D ghost delay operator to deghost simultaneously for multi-shot gathers. We then introduce a sparse inversion method in the pseudo-3D radon domain (multi-shot gathers) to further improve the inversion accuracy. The proposed framework is easy to implement, is not sensitive to noise, and shows superior performance in synthetic and field examples.
Synchronization Analysis of a New Four-Dimensional Time-Delay Lorenz System and Its Circuit Experiments
Authors: Cui Zhiyong , Zhong Dongbo , Qiu Xiaohong
Published: October 2022

Time-delay chaotic systems with multiple positive Lyapunov exponents have been extensively studied in the field of information security. This paper proposes a new four-dimensional time-delay Lorenz system and its chaotic synchronization through the Lyapunov–Krasovskii theory. The sufficient conditions for the stability of the new chaotic system are obtained by the Routh–Hurwitz criterion, and the control parameters are found to have a significant impact on the speed of synchronous convergence. Furthermore, oscillation circuit simulation is essential for contributing the chaotic system to practical applications. Accordingly, the circuits of the chaotic time-delay system and its coupled synchronous control circuit are innovatively designed by Multisim. Experiment results illustrate the behaviors of various attractors in the new time-delay Lorenz system and the effectiveness of the proposed asymptotic synchronous method.
Speed Tracking Control of High-Speed Train Based on Particle Swarm Optimization and Adaptive Linear Active Disturbance Rejection Control
Authors: Xue Jingze , Zhuang Keyu , Zhao Tong , Zhang Miao , Qiao Zheng , Cui Shuai , Gao Yunlong
Published: October 2022

This paper proposes a control scheme combining improved particle swarm optimization (IPSO) and adaptive linear active disturbance rejection control (ALADRC) to solve the high-speed train (HST) speed tracking control problem. Firstly, in order to meet the actual operation of a HST, a multi-mass point dynamic model with time-varying coefficients was established. Secondly, linear active disturbance rejection control (LADRC) was proposed to control the speed of the HST, and the anti-disturbance ability of the system was improved by estimating and compensating for the total disturbance suffered by the carriage during the operation of the HST. Meanwhile, to solve the problem of difficult parameter tuning of the LADRC, IPSO was introduced to optimize the parameters. Thirdly, the adaptive control (APC) was introduced to compensate for the observation error caused by the bandwidth limitation of the linear state expansion observer in LADRC and the tracking error caused by an unknown disturbance during the train’s operation. Additionally, the Lyapunov theory was used to prove the stability of the system. Finally, the simulation results showed that the designed control scheme is more effective in solving the problem of HST speed tracking.
Emerging Biomedical Applications of Carbon Dot and Polymer Composite Materials
Authors: Adam Gareeballah Osman , Sharker Shazid Md. , Ryu Ji Hyun
Published: October 2022

Carbon dot-based composite materials have been extensively developed for versatile biomedical applications, such as drug delivery, tissue engineering, bioimaging, biosensors, and photothermal cancer therapy, owing to their excellent mechanical properties, electrical and thermal conductivity, large surface-to-volume ratio, and biocompatibility. For instance, the hydrophobicity and delocalized π-electrons of carbon dots enable insoluble drug loading in carbon composite-based drug delivery carriers. In addition, carbon dot-based materials are suitable for optical and electrochemical biosensor applications owing to their intrinsic properties. Thus, this review briefly focuses on the following: (1) general aspects, (2) various sources, and (3) versatile biomedical applications of carbon dots and composite materials. More importantly, we present the emerging applications of carbon dot-based materials, such as in agricultural systems, COVID-19 theranostics, counterfeit, and security.
Occurrence of Zearalenone and Enniatin B in Swiss Wheat Grains and Wheat Flours
Authors: André Amandine , Müller Nadina , Chetschik Irene
Published: October 2022

Wheat is one of the world’s key staple foods, but it is often contaminated with mycotoxin-producing microorganisms, resulting in a large amount of food waste every year. The contamination of wheat grains harvested in 2020 and 2021 in Switzerland, as well as of wheat flours bought in local stores with the two mycotoxins zearalenone (ZEA) and enniatin B (ENB) was investigated. The quantification was performed using LC–MS/MS. ZEA, the level in different cereals and food products of which is regulated by law, was detected in half of the grain samples at levels below 100 µg/kg, except for one sample contaminated with 147 µg/kg. No ZEA was detected in the commercial wheat flours. The emerging mycotoxin ENB was detected in all samples of wheat grains and flours, at levels between 3 and 938 µg/kg. The harvest year was shown to affect the ENB content (p value < 0.01), and in particular the humid weather conditions encountered in 2021 during the month of harvest. The refining grade of the flours showed no influence on the contamination by ENB, indicating that the contamination with ENB can occur not only on the surface layers but also on the inner layers on the wheat grain. As chronic exposure to ENB can therefore not be excluded, decontamination solutions are needed to prevent food waste and further improve the food safety of wheat-based products.
Cloud Computing for Big Data Analysis
Authors: Marozzo Fabrizio , Belcastro Loris
Published: October 2022

With the spread of the Internet of Things, large amounts of digital data are generated and collected from different sources, such as sensors, cameras, in-vehicle infotainment, smart meters, mobile devices, applications, and web services [...]
Topology Optimization of Patient-Specific Custom-Fit Distal Tibia Plate: A Spiral Distal Tibia Bone Fracture
Authors: Al-Tamimi Abdulsalam A.
Published: October 2022

Currently, bone fractures are commonly treated with bone fixation plates that present rigid designs and stiff biometals (e.g., Ti-6Al-4V) that increase the probability of stress shielding happening during bone remodeling by shielding the required stress stimuli for adequate healing. This can lead to medical implant loosening, bone resorption and possible bone refracture. In this paper, an initial custom-fit bone plate is designed to be treated based on the computer tomography imaging of a patient suffering from distal tibia spiral fracture. The initial bone plate was redesigned to reduce the risk of bone being stress shielded. Topology optimization were implemented to redesign the bone plates by minimizing the strain energy and reducing the total plate’s volume in three different cases (25%, 50% and 75%). A bone-plate construct was assembled and examined using finite element analysis considering load conditions of the patient’s gait and the tibia bone being loaded with 10% of the bodyweight. The bone stresses were evaluated in order to compare the topology optimized plates with the initial design. The findings show that with higher volume, load transfer reduction increases in the fractured area and reduces the risk of stress shielding. Topology optimization is a viable approach for building custom-fit distal tibia plates for spiral distal tibia fracture.
A Review of Deep Learning Applications for Railway Safety
Authors: Oh Kyuetaek , Yoo Mintaek , Jin Nayoung , Ko Jisu , Seo Jeonguk , Joo Hyojin , Ko Minsam
Published: October 2022

Railways speedily transport many people and goods nationwide, so railway accidents can pose immense damage. However, the infrastructure of railways is so complex that its maintenance is challenging and expensive. Therefore, using artificial intelligence for railway safety has attracted many researchers. This paper examines artificial intelligence applications for railway safety, mainly focusing on deep learning approaches. This paper first introduces deep learning methods widely used for railway safety. Then, we investigated and classified earlier studies into four representative application areas: (1) railway infrastructure (catenary, surface, components, and geometry), (2) train body and bogie (door, wheel, suspension, bearing, etc.), (3) operation (railway detection, railroad trespassing, wind risk, train running safety, etc.), and (4) station (air quality control, accident prevention, etc.). We present fundamental problems and popular approaches for each application area. Finally, based on the literature reviews, we discuss the opportunities and challenges of artificial intelligence for railway safety.
Machine Learning Applications for Jet Tagging in the CMS Experiment
Authors: Cagnotta Antimo , Carnevali Francesco , De Iorio Agostino
Published: October 2022

The fundamental physics research at the frontier accessible by today’s particle accelerators such as the CERN Large Hadron Collider pose unique challenges in terms of complexity and abundance of data to analyse. In this context, it is of paramount importance to develop algorithms capable of dealing with multivariate problems to enhance humans’ ability to interpret data and ultimately increase the discovery potential of the experiments. Machine learning techniques therefore assume an increasingly important role in the experiments at the LHC. In this work, we give an overview of the latest developments in this field, with a particular focus on the algorithms developed and used within the CMS Collaboration. The review follows this structure: (1) Introduction presents the CMS Experiment at LHC and the most common methods used in particle physics; (2) Jet Flavour Tagging briefly describes the main algorithms used to reconstruct heavy-flavour jets; (3) Jet Substructure and Deep Tagging focuses on the identification of heavy-particle decay in boosted jets; (4) Analysis Applications gives examples of applying the algorithm in physics analyses; and (5) Conclusions summarises the state-of-the-art and gives indications for future studies.
Multivariable Characterization of Atmospheric Environment with Data Collected in Flight
Authors: Shakirova Aliia , Nichman Leonid , Belacel Nabil , Nguyen Cuong , Bliankinshtein Natalia , Wolde Mengistu , DiVito Stephanie , Bernstein Ben , Huang Yi
Published: October 2022

The In-Cloud Icing and Large-drop Experiment (ICICLE) flight campaign, led by the United States Federal Aviation Administration, was conducted in the geographical region over US Midwest and Western Great Lakes, between January and March 2019, with the aim to collect atmospheric data and study the aircraft icing hazard. Measurements were taken onboard the National Research Council of Canada (NRC) Convair-580 aircraft, which was equipped with more than 40 in situ probes, sensors, and remote sensing instruments in collaboration with Environment and Climate Change Canada (ECCC). In each flight, aerosol, cloud microphysics, atmospheric and aircraft state data were collected. Atmospheric environment characterization is critical both for cloud studies and for operational decision making in flight. In this study, we use the advantage of multiple input parameters collected in-flight together with machine learning and clustering techniques to characterize the flight environment. Eleven parameters were evaluated for the classification of the sampled environment along the flight path. Namely, aerosol concentration, temperature, hydrometeor concentration, hydrometeor size, liquid water content, total water content, ice accretion rate, and radar parameters in the vicinity of the aircraft. In the analysis of selected flights, we were able to identify periods of supercooled liquid clouds, glaciated clouds, two types of mixed-phase clouds, and clear air conditions. This approach offers an alternative characterization of cloud boundaries and a complementary identification of flight periods with hazardous icing conditions.