bluuebunny/crossref_metadata_2025 huggingface dataset:
A Walkway from Crayfish to Oligochitosan
Authors: Bezrodnykh Evgeniya A. , Vyshivannaya Oxana V. , Berezin Boris B. , Blagodatskikh Inesa V. , Tikhonov Vladimir E.
Published: March 2023

Edible crayfish are an object of local fishing and artificial breeding in many countries. This industry is very promising in terms of production of healthy foods and byproducts, such as biologically active polyaminosaccharide—chitosan and its derivatives. However, crayfishing is far from being at the level at which it could be. This laboratory scale protocol describes a walkway from crayfish Actacus leptodactylus to chitin, chitosan, and oligochitosan hydrochloride, with the main emphasis on the way of getting rid of the impurities (residual heavy metals, proteins and other residues) commonly present in commercial chitosan and its derivatives, as well as the characterization of the products by means of inductively-coupled plasma mass spectrometry (ICP-MS), energy-dispersive X-ray spectroscopy (EDXS), protein and elemental analysis, proton magnetic resonance spectroscopy (1H NMR), and chromatography methods. The protocol includes the preparation of crude shell waste; the extraction of proteins from crude shell waste and preparation of deproteinated shell waste, demineralization and decolorization of the deproteinated crayfish shell waste, deacetylation of chitin, and depolymerization of chitosan. EDXS shows the presence of Al and Si residues in chitin is found when the deproteination of crayfish waste is carried out in an alumosilicate glass vessel. In contrast, these residues are absent when deproteination is carried out in the borosilicate glass flask. Analytical data show that the content of residues in chitosan and oligochitosan hydrochloride meets pharmaceutical requirements. The study demonstrates crayfish waste a promising for the purification of chitosan, for the preparation of pharmaceutical grade oligochitosan hydrochloride, and can improve commercialization of crayfishes.
Antibacterial Activity of Tanacetum vulgare L. Extracts against Clinical Isolates of Bovine Mastitis
Authors: Šukele Renāte , Bārzdiņa Ance , Koka Rudīte , Skadins Ingus , Lauberte Līga , Brangule Agnese , Kovalcuka Liga , Bandere Dace
Published: March 2023

A bovine mastitis is an infectious disease, which is usually treated with antibiotics. Alternatively, herbal medicine has been proposed due to bacterial resistance. The aim of this study was to determine the antibacterial activity of the acetonic and ethanolic extracts of dried flowers and leaves of Tanacetum vulgare L. against bovine mastitis-inducing clinical isolates such as Escherichia coli, Streptococcus agalactiae, Streptococcus uberis, Serratia liquefaciens, Staphylococcus aureus, and reference cultures of S. aureus and E. coli. The extracts of T. vulgare showed partial antibacterial activity against tested strains of S. aureus. The MIC and MBC values of a 70% ethanol extract of flowers (MIC = 3.4 mg/mL, MBC = 3.4–6.8 mg/mL) were lower than for the 70% ethanol extract of leaves (MIC = 15.7–31.4 mg/mL, MBC = 62.9–125.9 mg/mL). The flower extracts showed low activity against E. coli (MIC = 53.9 mg/mL, MBC = 53.9–107.8 mg/mL) and S. agalactiae (MIC, MBC = 53.9 mg/mL). T. vulgare leaf extracts had minimal antibacterial effects against Streptococcus strains (MIC = 31.4–62.9 mg/mL, MBC = 53.9–125.9 mg/mL) and Serratia liquefaciens (MIC, MBC = 125.9 mg/mL). However, flower extracts had a higher phenolic content that did not correlate with antibacterial effects. T. vulgare flower and leaf extracts could be combined to obtain broader antibacterial effects.
Microstructure and Fracture Behaviors of Oscillating Laser Welded 5A06 Aluminum Alloy Lock Butt Joint
Authors: Lu Yang , Lai Jian , Pang Junping , Li Xin , Zhang Chen , Gao Ming
Published: March 2023

Oscillating laser welding is potential to improve the quality of aluminum alloy joints, but has been seldom addressed on lock butt joint. In this paper, the effects of beam oscillation frequencies (f) on the properties of laser-welded 5A06 aluminum alloy lock butt joints were investigated, especially those at the lock step. In the microstructure, the columnar grain zone (CGZ) near the fusion line narrowed, the porosity was reduced, and the angle between lock step and fusion line increased with the increase of f. Correspondingly, the fracture changed from equiaxed grain zone to heat affected zone (HAZ), and the fracture angle between lock step and crack propagation line from 90° to 45°. The maximum ultimate tensile strength and elongation of oscillating weld reached 308 MPa and 18.2%, respectively, 36.3% and 203.3% higher than non-oscillating weld. The fracture behaviors indicated that the crack always initiated at the lock step, and then preferably propagated to the pores, followed closely by the weaker CGZ, and then the stronger HAZ when CGZ was narrowed enough. Notably, when the pore size was small (<0.39 mm) and located below the lock step, the pore was not on the crack propagation path. The crack tended to propagate towards the weaker CGZ. Finally, the fracture mechanism was discussed. The results clarify the fracture mechanism of oscillating laser-welded lock butt joints and contribute to the development of oscillating laser welding.
Probabilistic Coarsening for Knowledge Graph Embeddings
Authors: Pietrasik Marcin , Reformat Marek Z.
Published: March 2023

Knowledge graphs have risen in popularity in recent years, demonstrating their utility in applications across the spectrum of computer science. Finding their embedded representations is thus highly desirable as it makes them easily operated on and reasoned with by machines. With this in mind, we propose a simple meta-strategy for embedding knowledge graphs using probabilistic coarsening. In this approach, a knowledge graph is first coarsened before being embedded by an arbitrary embedding method. The resulting coarse embeddings are then extended down as those of the initial knowledge graph. Although straightforward, this allows for faster training by reducing knowledge graph complexity while revealing its higher-order structures. We demonstrate this empirically on four real-world datasets, which show that coarse embeddings are learned faster and are often of higher quality. We conclude that coarsening is a recommended prepossessing step regardless of the underlying embedding method used.
Biomimicry in Architecture: A Review of Definitions, Case Studies, and Design Methods
Authors: Verbrugghe Nathalie , Rubinacci Eleonora , Khan Ahmed Z.
Published: March 2023

Biomimicry, as a field of science, is mainly defined as a solution for design problems inspired by natural models, systems, and elements. For the built environment, using nature as a guide can enhance sustainability or even go beyond that and generate a regenerative approach. This is important in the building sector to evolve towards a sustainable and circular economy and reduce CO2 emissions in terms of energy-use. While several biomimicry-related keywords exist, scholars and practitioners in architecture have given varying interpretations to the term biomimicry depending on the use and goal. There has been increasing interest in biomimicry in architecture (BIA), yet the field has become more fragmented. This study aims to highlight differences and similarities through an extended literature survey and analysis that explores case studies, classification systems, and methodological frameworks related to biomimicry in architecture as a way to contribute to reduce the fragmentation in the field. To provide the necessary context and avoid confusion regarding the many concepts and terms that refer to nature-based design, biomimicry-related keywords and interpretations of the word biomimicry are first clarified. Ultimately, the discussion is an integrative effort at defining the field, and highlights the significance and impact of employing BIA in terms of sustainability and usability, as well as showcasing the opportunities for further research.
Get a New Perspective on EEG: Convolutional Neural Network Encoders for Parametric t-SNE
Authors: Svantesson Mats , Olausson Håkan , Eklund Anders , Thordstein Magnus
Published: March 2023

t-distributed stochastic neighbor embedding (t-SNE) is a method for reducing high-dimensional data to a low-dimensional representation, and is mostly used for visualizing data. In parametric t-SNE, a neural network learns to reproduce this mapping. When used for EEG analysis, the data are usually first transformed into a set of features, but it is not known which features are optimal. The principle of t-SNE was used to train convolutional neural network (CNN) encoders to learn to produce both a high- and a low-dimensional representation, eliminating the need for feature engineering. To evaluate the method, the Temple University EEG Corpus was used to create three datasets with distinct EEG characters: (1) wakefulness and sleep; (2) interictal epileptiform discharges; and (3) seizure activity. The CNN encoders produced low-dimensional representations of the datasets with a structure that conformed well to the EEG characters and generalized to new data. Compared to parametric t-SNE for either a short-time Fourier transform or wavelet representation of the datasets, the developed CNN encoders performed equally well in separating categories, as assessed by support vector machines. The CNN encoders generally produced a higher degree of clustering, both visually and in the number of clusters detected by k-means clustering. The developed principle is promising and could be further developed to create general tools for exploring relations in EEG data.
An Examination of the Relationships between Eating-Disorder Symptoms, Difficulties with Emotion Regulation, and Mental Health in People with Binge Eating Disorder
Authors: da Luz Felipe Q. , Mohsin Mohammed , Jana Tatiana A. , Marinho Leticia S. , Santos Edilaine dos , Lobo Isabella , Pascoareli Luisa , Gaeta Tamiris , Ferrari Silvia , Teixeira Paula C. , Cordás Táki , Hay Phillipa
Published: March 2023

Eating disorders, such as binge eating disorder, are commonly associated with difficulties with emotion regulation and mental-health complications. However, the relationship between eating-disorder symptoms, difficulties with emotion regulation, and mental health in people with binge eating disorder is unclear. Thus, we investigated associations between eating-disorder symptoms, difficulties with emotion regulation, and mental health in 119 adults with binge eating disorder. Participants were assessed with the Eating Disorder Examination Questionnaire, Loss of Control over Eating Scale, Difficulties in Emotion Regulation Scale, Depression Anxiety and Stress Scale, and the 12-Item Short Form Survey at the pre-treatment phase of a randomized controlled trial. Structural-equation-modelling path analysis was used to investigate relationships between variables. We found that (1) eating-disorder behaviors had a direct association with depression, anxiety, and stress; (2) depression, psychological stress, difficulties with emotion regulation, and eating-disorder psychopathology had a direct association with mental-health-related quality of life; and (3) eating-disorder psychopathology/behaviors and stress had a direct association with difficulties with emotion regulation. Our findings show that depression, stress, difficulties with emotion regulation, and eating-disorder psychopathology were related in important ways to mental-health complications in people with binge eating disorder.
Numerical and Analytical Investigations of the Impact Resistance of Partially Precast Concrete Beams Strengthened with Bonded Steel Plates
Authors: Yan Xueyuan , Lin Cihang , Liu Xuhong , Zheng Tianxiao , Shi Shen , Mao Huimin
Published: March 2023

A building may be subjected to a variety of accidental loads during its service life. Partially precast concrete (PC) beams are a primary structural component. Their impact resistance can have a substantial impact on the overall safety of a structure when it is subjected to an impact load. In this study, numerical analyses were performed on the dynamic response of PC beams strengthened with bonded steel plates subjected to impact loading. The model was verified from four aspects: energy conversion, failure form, impact force–time history curve, and midspan displacement–time history curve. The dynamic response eigenvalues of the peak impact force, peak midspan displacement, and residual midspan displacement were compared between the numerical simulations and experimental tests. The relative inaccuracy of the peak impact force ranged from 9.51% to 14.0%, with an average value of 11.9%. The average relative error for the midspan displacement was −0.09%, with the greatest relative errors varying between −0.64% and 0.3%. The residual value errors of the midspan displacement ranged from −0.95% to 2.38%, with an average relative error of 0.94%. On this basis, the effects of the impact mass, impact height, width, and length of the bonded steel plate on the impact resistance of the components were evaluated. Furthermore, the differences in the equivalent plastic strain contours, impact force–time history curves, and midspan displacement–time history curves under different parameters were compared. The results demonstrated that the failure modes and flexural deformations of the test beams were influenced by the impact mass and impact height. The increase in the length and width of the steel plate had no effect on the impact force response, but the peak and residual values of the midspan displacement decreased, which could significantly increase the impact resistance of the beams. Lastly, the impact mass m, the impact height h, the thickness t of the bonded steel plate, the length of the bonded steel plate hs, and the width of the bonded steel plate bs were all taken into account in the fitting formula. These five parameters were used to predict the peak impact force response, the peak value of the midspan displacement, and the residual value of the midspan displacement. The results demonstrated that the fitting formula had small errors and could accurately reflect the dynamic responses of the PC beams strengthened with bonded steel plates under impact loading.
Cancer-Associated Fibroblasts Exposed to High-Dose Ionizing Radiation Promote M2 Polarization of Macrophages, Which Induce Radiosensitivity in Cervical Cancer
Authors: Sheng Yuhan , Zhang Baofang , Xing Biyuan , Liu Zhao , Chang Yu , Wu Gang , Zhao Yingchao
Published: March 2023

Radiotherapy, including brachytherapy, is a major therapeutic regimen for cervical cancer. Radioresistance is a decisive factor in radiation treatment failure. Tumor-associated macrophages (TAMs) and cancer-associated fibroblasts (CAFs) in the tumor microenvironment are critical factors in the curative effects of cancer therapies. However, the interactions between TAMs and CAFs in the context of ionizing radiation are not fully understood. This study was undertaken to investigate whether M2 macrophages induce radioresistance in cervical cancer and to explore the TAMs’ phenotypic transformation after IR and its underlying mechanisms. The radioresistance of cervical cancer cells was enhanced after being co-cultured with M2 macrophages. TAMs tended to undergo M2 polarization after high-dose irradiation, which was strongly associated with CAFs in both mouse models and patients with cervical cancer. Additionally, cytokine and chemokine analysis was performed to find that high-dose irradiated CAFs promoted macrophage polarization towards the M2 phenotype through chemokine (C-C motif) ligand 2. Collectively, our results highlight the crucial role that high-dose irradiated CAFs play in the regulation of M2 phenotype polarization, which ultimately induces radioresistance in cervical cancer.
Anti-Cancer Stem-Cell-Targeted Therapies in Prostate Cancer
Authors: Gogola Samantha , Rejzer Michael , Bahmad Hisham F. , Alloush Ferial , Omarzai Yumna , Poppiti Robert
Published: March 2023

Prostate cancer (PCa) is the second-most commonly diagnosed cancer in men around the world. It is treated using a risk stratification approach in accordance with the National Comprehensive Cancer Network (NCCN) in the United States. The main treatment options for early PCa include external beam radiation therapy (EBRT), brachytherapy, radical prostatectomy, active surveillance, or a combination approach. In those with advanced disease, androgen deprivation therapy (ADT) is considered as a first-line therapy. However, the majority of cases eventually progress while receiving ADT, leading to castration-resistant prostate cancer (CRPC). The near inevitable progression to CRPC has spurred the recent development of many novel medical treatments using targeted therapies. In this review, we outline the current landscape of stem-cell-targeted therapies for PCa, summarize their mechanisms of action, and discuss avenues of future development.
Pro-Apoptotic and Anti-Cancer Activity of the Vernonanthura Nudiflora Hydroethanolic Extract
Authors: Nadir Almog , Shteinfer-Kuzmine Anna , Pandey Swaroop Kumar , Ortas Juan , Kerekes Daniel , Shoshan-Barmatz Varda
Published: March 2023

The mitochondrial voltage-dependent anion channel 1 (VDAC1) protein is involved in several essential cancer hallmarks, including energy and metabolism reprogramming and apoptotic cell death evasion. In this study, we demonstrated the ability of hydroethanolic extracts from three different plants, Vernonanthura nudiflora (Vern), Baccharis trimera (Bac), and Plantago major (Pla), to induce cell death. We focused on the most active Vern extract. We demonstrated that it activates multiple pathways that lead to impaired cell energy and metabolism homeostasis, elevated ROS production, increased intracellular Ca2+, and mitochondria-mediated apoptosis. The massive cell death generated by this plant extract’s active compounds involves the induction of VDAC1 overexpression and oligomerization and, thereby, apoptosis. Gas chromatography of the hydroethanolic plant extract identified dozens of compounds, including phytol and ethyl linoleate, with the former producing similar effects as the Vern hydroethanolic extract but at 10-fold higher concentrations than those found in the extract. In a xenograft glioblastoma mouse model, both the Vern extract and phytol strongly inhibited tumor growth and cell proliferation and induced massive tumor cell death, including of cancer stem cells, inhibiting angiogenesis and modulating the tumor microenvironment. Taken together, the multiple effects of Vern extract make it a promising potential cancer therapeutic.
Effect of Pyrolysis Conditions on the MOFs-Derived Zinc-Based Catalysts in Acetylene Acetoxylation
Authors: Shen Guowang , Li Mengli , Chen Yuhao , Xu Zhuang , Wang Xugen , Dai Bin
Published: March 2023

The preparation method and calcination temperature of metal-organic framework (MOFs)-derived materials are critical factors affecting catalytic performance. In this work, the preparation conditions of MOFS precursors were optimized, and zinc-based catalysts with different activities (MOF5-700, MOF5-750, and MOF5-800) were obtained by pyrolysis of MOFS precursors under nitrogen, which were then applied to an acetylene acetoxylation reaction system. According to the results, the conversion rate of acetic acid under catalysis was significantly different. (MOF5-700 (48%), MOF5-750 (62%), and MOF5-800 (22%)). Comparing the activity of the catalyst with the industrial catalyst Zn(OAc)2/AC (20%), MOF5-750 showed higher activity, and the acetic acid conversion rate remained around 60% after 50 h of stability testing. By characterization analysis, MOFs-derived materials were obtained after proper temperature pyrolysis. They have high mesoporous content, defects, and oxygen-containing functional groups and can maintain a good crystal structure, greatly reducing the loss of active components. This is the main reason for the good performance of the MOF5-750 catalyst in acetylene acetoxylation. Thus, the preparation conditions and favorable pyrolysis temperature of MOF derivative catalysts play a key role in the catalytic performance of acetylene acetoxylation.
Superhydrophobic Epoxy/Fluorosilicone/PTFE Coatings Prepared by One-Step Spraying for Enhanced Anti-Icing Performance
Authors: Fan Lei , Li Bo , Wang Yan , He Jinhang , Bai Jie , Zhu Tao , Yuan Yuan
Published: March 2023

The icing of glass insulators is likely to cause faults such as insulator flashover, which poses a serious threat to the power system. Traditional deicing techniques have the disadvantage of being costly and inefficient. Herein, polytetrafluoroethylenes (PTFEs) as nanoparticles and epoxy and fluorosilicone resins as binders were blended to construct an anti-icing coating. The superhydrophobic (SHP) epoxy/fluorosilicone/PTFE coatings for anti-icing were successfully prepared on glass slides through one-step spraying. The effect of PTFE mass fraction on the microstructure, on the wettability and on the anti-icing properties of the coatings was investigated. The results showed that the coatings with different PTFE mass fractions had different microstructures. When the PTFE mass fraction was 47.2%, the SHP coating exhibited a uniform rough structure with an apparent contact angle as high as 164.7° and a sliding angle as low as 3.2°. Moreover, the water droplets can bounce back five times with a contact time of only 9.5 ms and a rebound height of 4.58 mm. In the low-temperature environment (−10 °C), the SHP coating displayed good anti-frosting, anti-icing and icephobic properties. The delayed frosting time (1499 s) and delayed freezing time (1295.3 s) of the SHP coating were three and five times longer than those of the glass, respectively. The SHP coating presented an ice-adhesion strength (39.8 kPa) that was six times lower than that of glass. The prepared SHP coating demonstrated potential applications for the anti-icing of glass insulators.
Vacuum-Filtration-Assisted Ice-Templated Freeze Drying for Preparing Capacitive Graphene Aerogel for Thermal Management
Authors: Xing Yuze , Jia Hui , Wang Zhefan , Xie Lijing , Liu Dong , Wang Zheng , Li Meng , Kong Qingqiang
Published: March 2023

Graphene aerogel (GA) is widely used in electronic devices owing to its light weight, elasticity, and excellent thermal conductivity. GA has been prepared using various methods. However, the preparation process is complex and the thickness is hard to control, which limits its application. There is an urgent need for a new and simple method to fabricate graphene aerogel. Herein, we describe a novel strategy for fabricating GA via a vacuum filtration–ice template freeze-drying method. The stability of graphene oxide slurry (GOS) was changed by using hydrochloric acid (HCl, 0.12 mol/L), and then GA was quickly obtained by vacuum filtration–ice template freeze drying and graphitization. The obtained GA reveals a symmetrical hyperbolic structure in the vertical direction, giving it excellent thermal and electrical conductivity and good compression performance. The electrical conductivity is up to 14.87 S/cm and the thermal conductivity is 1.29 W m−1 K−1 when the density is 36 mg cm−3. The pressure only needs 0.013 MPa when the strain of GA is 50%. GA has considerable potential for the application of supercapacitors owing to the high conductivity and low density.
Predictive Factors for Anastomotic Leakage Following Colorectal Cancer Surgery: Where Are We and Where Are We Going?
Authors: Tsalikidis Christos , Mitsala Athanasia , Mentonis Vasileios I. , Romanidis Konstantinos , Pappas-Gogos George , Tsaroucha Alexandra K. , Pitiakoudis Michail
Published: March 2023

Anastomotic leakage (AL) remains one of the most severe complications following colorectal cancer (CRC) surgery. Indeed, leaks that may occur after any type of intestinal anastomosis are commonly associated with a higher reoperation rate and an increased risk of postoperative morbidity and mortality. At first, our review aims to identify specific preoperative, intraoperative and perioperative factors that eventually lead to the development of anastomotic dehiscence based on the current literature. We will also investigate the role of several biomarkers in predicting the presence of ALs following colorectal surgery. Despite significant improvements in perioperative care, advances in surgical techniques, and a high index of suspicion of this complication, the incidence of AL remained stable during the last decades. Thus, gaining a better knowledge of the risk factors that influence the AL rates may help identify high-risk surgical patients requiring more intensive perioperative surveillance. Furthermore, prompt diagnosis of this severe complication may help improve patient survival. To date, several studies have identified predictive biomarkers of ALs, which are most commonly associated with the inflammatory response to colorectal surgery. Interestingly, early diagnosis and evaluation of the severity of this complication may offer a significant opportunity to guide clinical judgement and decision-making.
Impact of the COVID-19 Pandemic on Medical Oncology Workload: A Provincial Review
Authors: Sheridan Margaret , Colwell Bruce , Lamond Nathan W. D. , Macfarlane Robyn , Rayson Daniel , Snow Stephanie , Wood Lori A. , Ramjeesingh Ravi
Published: March 2023

(1) Background: Cancer is the leading cause of death in Canada, with significant resource limitation impacting the delivery of cancer care nationwide. The onset of the COVID-19 pandemic forced additional resource restriction and diversion, further impacting care delivery. Our intention is to analyze the impact COVID-19 on a provincial medical oncology workload and bring attention to the limitations of the current workload metric for oncologists. (2) Methods: All medical oncology patient encounters were extracted and compared, collected by year and encounter type, from April 2014 through March 2022. (3) Results: There was an increase in all patient encounters by an average of 9.5% per year, including during the strictest COVID-19 restrictions. There was an increase in virtual care encounters from 37.9% to 52.1%. (4) Conclusions: Medical Oncology workloads have increased over time and estimates suggest growing demand. Little data exist to inform workforce requirements and actual workload is not captured by the current metric. Though volume of new consults continues to increase, COVID-19 has highlighted additional changes in the delivery of care, likely with lasting impact, little of which are included in the current workload metric.
PGT-SR: A Comprehensive Overview and a Requiem for the Interchromosomal Effect
Authors: Griffin Darren K. , Ogur Cagri
Published: March 2023

Preimplantation genetic testing for structural rearrangements (PGT-SR) was one of the first applications of PGT, with initial cases being worked up in the Delhanty lab. It is the least well-known of the various forms of PGT but nonetheless provides effective treatment for many carrier couples. Structural chromosomal rearrangements (SRs) lead to infertility, repeated implantation failure, pregnancy loss, and congenitally affected children, despite the balanced parent carrier having no obvious phenotype. A high risk of generating chromosomally unbalanced gametes and embryos is the rationale for PGT-SR, aiming to select for those that are chromosomally normal, or at least balanced like the carrier parent. PGT-SR largely uses the same technology as PGT-A, i.e., initially FISH, superseded by array CGH, SNP arrays, Karyomapping, and, most recently, next-generation sequencing (NGS). Trophectoderm biopsy is now the most widely used sampling approach of all PGT variants, though there are prospects for non-invasive methods. In PGT-SR, the most significant limiting factor is the availability of normal or balanced embryo(s) for transfer. Factors directly affecting this are rearrangement type, chromosomes involved, and sex of the carrier parent. De novo aneuploidy, especially for older mothers, is a common limiting factor. PGT-SR studies provide a wealth of information, much of which can be useful to genetic counselors and the patients they treat. It is applicable in the fundamental study of basic chromosomal biology, in particular the purported existence of an interchromosomal effect (ICE). An ICE means essentially that the existence of one chromosomal defect (e.g., brought about by malsegregation of translocation chromosomes) can perpetuate the existence of others (e.g., de novo aneuploidy). Recent large cohort studies of PGT-SR patients seem, however, to have laid this notion to rest, at least for human embryonic development. Unless new evidence comes to light, this comprehensive review should serve as a requiem.
Pollution from Highways Detection Using Winter UAV Data
Authors: Baah Gabriel A. , Savin Igor Yu. , Vernyuk Yuri I.
Published: March 2023

This study identified and evaluated the association between metal content and UAV data to monitor pollution from roadways. A total of 18 mixed snow samples were collected at the end of winter, utilizing a 1 m long and 10 cm wide snow collection tube, from either side of the Caspian Highway (Moscow-Tambo-Astrakhan) in Moscow. Inductively coupled plasma optical emission spectrometry (ICP-OES) was used to examine the chemical composition of the samples, yielding 35 chemical elements (metals). UAV data and laboratory findings were calculated and examined. Regression estimates demonstrated the possibility of using remote sensing data to identify Al, Ba, Fe, K, and Na metals in snow cover near roadways due to dust dispersal. This discovery supports the argument that UAV sensing data can be utilized to monitor air pollution from roadways.
Deep Learning-Based Pine Nematode Trees’ Identification Using Multispectral and Visible UAV Imagery
Authors: Qin Bingxi , Sun Fenggang , Shen Weixing , Dong Bin , Ma Shencheng , Huo Xinyu , Lan Peng
Published: March 2023

Pine wilt disease (PWD) has become increasingly serious recently and causes great damage to the world’s pine forest resources. The use of unmanned aerial vehicle (UAV)-based remote sensing helps to identify pine nematode trees in time and has become a feasible and effective approach to precisely monitor PWD infection. However, a rapid and high-accuracy detection approach has not been well established in a complex terrain environment. To this end, a deep learning-based pine nematode tree identification method is proposed by fusing visible and multispectral imagery. A UAV equipped with a multispectral camera and a visible camera was used to obtain imagery, where multispectral imagery includes six bands, i.e., red, green, blue, near-infrared, red edge and red edge 750 nm. Two vegetation indexes, NDVI (Normalized Difference Vegetation Index) and NDRE (Normalized Difference Red Edge Index) are extracted as a typical feature according to the reflectance of infected trees in different spectral bands. The YOLOv5 (You Only Look Once v5)-based detection algorithm is adopted and optimized from different aspects to realize the identification of infected pine trees with high detection speed and accuracy. e.g., GhostNet is adopted to reduce the number of model parameters and improve the detection speed; a module combining a CBAM (Convolutional Block Attention Module) and a CA (Coordinate Attention) mechanism is designed to improve the feature extraction for small-scale pine nematode trees; Transformer module and BiFPN (Bidirectional Feature Pyramid Network) structure are applied to improve the feature fusion capability. The experiments show that the mAP@0.5 of the improved YOLOv5 model is 98.7%, the precision is 98.1%, the recall is 97.3%, the average detection speed of single imagery is 0.067 s, and the model size is 46.69 MB. All these metrics outperform other comparison methods. Therefore, the proposed method can achieve a fast and accurate detection of pine nematode trees, providing effective technical support for the control of a pine nematode epidemic.
Piecewise Business Bubble System under Classical and Nonsingular Kernel of Mittag–Leffler Law
Authors: Zhang Chao , Li Bo
Published: March 2023

This study aims to investigate the dynamics of three agents in the emerging business bubble model based on the Mittag–Leffler law pertaining to the piecewise classical derivative and non-singular kernel. By generalizing the business bubble dynamics in terms of fractional operators and the piecewise concept, this study presents a new perspective to the field. The entire set of intervals is partitioned into two piecewise intervals to analyse the classical order and conformable order derivatives of an Atangana–Baleanu operator. The subinterval analysis is critical for removing discontinuities in each sub-partition. The existence and uniqueness of the solution based on a piecewise global derivative are tested for the considered model. The approximate root of the system is determined using the piecewise numerically iterative technique of the Newton polynomial. Under the classical order and non-singular law, the approximate root scheme is applied to the piecewise derivative. The curve representation for the piece-wise globalised system is tested by applying the data for the classical and different conformable orders. This establishes the entire density of each compartment and shows a continuous spectrum instead of discrete dynamics. The concept of this study can also be applied to investigate crossover behaviours or abrupt changes in the dynamics of the values of each market.
GLH: From Global to Local Gradient Attacks with High-Frequency Momentum Guidance for Object Detection
Authors: Chen Yuling , Yang Hao , Wang Xuewei , Wang Qi , Zhou Huiyu
Published: March 2023

The adversarial attack is crucial to improving the robustness of deep learning models; they help improve the interpretability of deep learning and also increase the security of the models in real-world applications. However, existing attack algorithms mainly focus on image classification tasks, and they lack research targeting object detection. Adversarial attacks against image classification are global-based with no focus on the intrinsic features of the image. In other words, they generate perturbations that cover the whole image, and each added perturbation is quantitative and undifferentiated. In contrast, we propose a global-to-local adversarial attack based on object detection, which destroys important perceptual features of the object. More specifically, we differentially extract gradient features as a proportion of perturbation additions to generate adversarial samples, as the magnitude of the gradient is highly correlated with the model’s point of interest. In addition, we reduce unnecessary perturbations by dynamically suppressing excessive perturbations to generate high-quality adversarial samples. After that, we improve the effectiveness of the attack using the high-frequency feature gradient as a motivation to guide the next gradient attack. Numerous experiments and evaluations have demonstrated the effectiveness and superior performance of our from global to Local gradient attacks with high-frequency momentum guidance (GLH), which is more effective than previous attacks. Our generated adversarial samples also have excellent black-box attack ability.
Quantum Information and Computation
Authors: Fei Shao-Ming , Li Ming , Luo Shunlong
Published: March 2023

Quantum technology can break through the bottleneck of traditional information technology by ensuring information security, speeding up computation, improving measurement accuracy, and providing revolutionary solutions to some issues of economic and social development [...]
Detecting Human Falls in Poor Lighting: Object Detection and Tracking Approach for Indoor Safety
Authors: Zi Xing , Chaturvedi Kunal , Braytee Ali , Li Jun , Prasad Mukesh
Published: March 2023

Falls are one the leading causes of accidental death for all people, but the elderly are at particularly high risk. Falls are severe issue in the care of those elderly people who live alone and have limited access to health aides and skilled nursing care. Conventional vision-based systems for fall detection are prone to failure in conditions with low illumination. Therefore, an automated system that detects falls in low-light conditions has become an urgent need for protecting vulnerable people. This paper proposes a novel vision-based fall detection system that uses object tracking and image enhancement techniques. The proposed approach is divided into two parts. First, the captured frames are optimized using a dual illumination estimation algorithm. Next, a deep-learning-based tracking framework that includes detection by YOLOv7 and tracking by the Deep SORT algorithm is proposed to perform fall detection. On the Le2i fall and UR fall detection (URFD) datasets, we evaluate the proposed method and demonstrate the effectiveness of fall detection in dark night environments with obstacles.
Statistical Study on the Time Characteristics of the Transient EMD Excitation Current from the Pantograph–Catenary Arcing Discharge
Authors: Jin Mengzhe , Wang Shaoqian , Liu Shanghe , Fang Qingyuan , Liu Weidong
Published: March 2023

Electromagnetic disturbances (EMDs) resulting from arcing discharge between the pantograph and catenary pose a serious threat to the electromagnetic safety of electrified trains. The time characteristic of EMD excitation current has a significant impact on the generation mechanism and characteristics of electromagnetic emission from pantograph–catenary discharge, but there have been few studies on the topic. In this paper, a large sample of time-domain waveform parameters were collected through laboratory measurements considering the high randomness nature of the arcing discharge. The reference distributions of the waveform parameters were selected using the Kolmogorov–Smirnov test, and the probability density function parameters that vary with applied voltages and discharge gap spacings were examined. Then, a stochastic model for the derivation of the discharge current waveform was proposed based on statistical results using a modified double exponential function whose parameters can be derived from physical properties. Waveforms of the excitation currents representing different EMD severities were generated by adjusting the quantiles of the fitting distributions. The validity of the stochastic model was demonstrated by comparing the measured and simulated waveforms for both single pulses and pulse trains. The proposed method and generated waveforms can help recreate the electromagnetic environment of pantograph–catenary arcing.
A New Hybrid Fault Diagnosis Method for Wind Energy Converters
Authors: Liang Jinping , Zhang Ke
Published: March 2023

Fault diagnostic techniques can reduce the requirements for the experience of maintenance crews, accelerate maintenance speed, reduce maintenance cost, and increase electric energy production profitability. In this paper, a new hybrid fault diagnosis method based on multivariate empirical mode decomposition (MEMD), fuzzy entropy (FE), and an artificial fish swarm algorithm (AFSA)-support vector machine (SVM) is proposed to identify the faults of a wind energy converter. Firstly, the measured three-phase output voltage signals are processed by MEMD to obtain three sets of intrinsic mode functions (IMFs). The multi-scale analysis tool MEMD is used to extract the common modes matching the timescale. It studies the multi-scale relationship between three-phase voltages, realizes their synchronous analysis, and ensures that the number and frequency of the modes match and align. Then, FE is calculated to describe the IMFs’ complexity, and the IMFs-FE information is taken as fault feature to increase the robustness to working conditions and noise. Finally, the AFSA algorithm is used to optimize SVM parameters, solving the difficulty in selecting the penalty factor and radial basis function kernel. The effectiveness of the proposed method is verified in a simulated wind energy system, and the results show that the diagnostic accuracy for 22 fault modes is 98.7% under different wind speeds, and the average accuracy of 30 running can be maintained above 84% for different noise levels. The maximum, minimum, average, and standard deviation are provided to prove the robust and stable performance. Compared with the other methods, the proposed hybrid method shows excellent performance in terms of high accuracy, strong robustness, and computational efficiency.
A Quantitative Analysis of Fuel Break Effectiveness Drivers in Southern California National Forests
Authors: Gannon Benjamin , Wei Yu , Belval Erin , Young Jesse , Thompson Matthew , O’Connor Christopher , Calkin David , Dunn Christopher
Published: March 2023

Fuel and wildfire management decisions related to fuel break construction, maintenance, and use in fire suppression suffer from limited information on fuel break success rates and drivers of effectiveness. We built a dataset of fuel break encounters with recent large wildfires in Southern California and their associated biophysical, suppression, weather, and fire behavior characteristics to develop statistical models of fuel break effectiveness with boosted regression. Our results suggest that the dominant influences on fuel break effectiveness are suppression, weather, and fire behavior. Variables related to fuel break placement, design, and maintenance were less important but aligned with manager expectations for higher success with wider and better maintained fuel breaks, and prior research findings that fuel break success increases with accessibility. Fuel breaks also held more often if burned by a wildfire during the previous decade, supporting the idea that fuel breaks may be most effective if combined with broader fuel reduction efforts.
A Genome-Wide Association Study to Identify Novel Candidate Genes Related to Low-Nitrogen Tolerance in Cucumber (Cucumis sativus L.)
Authors: Li Bowen , Wei Aimin , Tong Xueqiang , Han Yike , Liu Nan , Chen Zhengwu , Yang Hongyu , Wu Huaxiang , Lv Mingjie , Wang Ning Ning , Du Shengli
Published: March 2023

Cucumber is one of the most important vegetables, and nitrogen is essential for the growth and fruit production of cucumbers. It is crucial to develop cultivars with nitrogen limitation tolerance or high nitrogen efficiency for green and efficient development in cucumber industry. To reveal the genetic basis of cucumber response to nitrogen starvation, a genome-wide association study (GWAS) was conducted on a collection of a genetically diverse population of cucumber (Cucumis sativus L.) comprising 88 inbred and DH accessions including the North China type, the Eurasian type, the Japanese and South China type mixed subtype, and the South China type subtype. Phenotypic evaluation of six traits under control (14 mM) and treatment (3.5 mM) N conditions depicted the presence of broad natural variation in the studied population. The GWAS results showed that there were significant differences in the population for nitrogen limitation treatment. Nine significant loci were identified corresponding to six LD blocks, three of which overlapped. Sixteen genes were selected by GO annotation associated with nitrogen. Five low-nitrogen stress tolerance genes were finally identified by gene haplotype analysis: CsaV3_3G003630 (CsNRPD1), CsaV3_3G002970 (CsNRT1.1), CsaV3_4G030260 (CsSnRK2.5), CsaV3_4G026940, and CsaV3_3G011820 (CsNPF5.2). Taken together, the experimental data and identification of candidate genes presented in this study offer valuable insights and serve as a useful reference for the genetic enhancement of nitrogen limitation tolerance in cucumbers.
MicroRNA Target Identification: Revisiting Accessibility and Seed Anchoring
Authors: Homberg Nicolas , Galvão Ferrarini Mariana , Gaspin Christine , Sagot Marie-France
Published: March 2023

By pairing to messenger RNAs (mRNAs for short), microRNAs (miRNAs) regulate gene expression in animals and plants. Accurately identifying which mRNAs interact with a given miRNA and the precise location of the interaction sites is crucial to reaching a more complete view of the regulatory network of an organism. Only a few experimental approaches, however, allow the identification of both within a single experiment. Computational predictions of miRNA–mRNA interactions thus remain generally the first step used, despite their drawback of a high rate of false-positive predictions. The major computational approaches available rely on a diversity of features, among which anchoring the miRNA seed and measuring mRNA accessibility are the key ones, with the first being universally used, while the use of the second remains controversial. Revisiting the importance of each is the aim of this paper, which uses Cross-Linking, Ligation, And Sequencing of Hybrids (CLASH) datasets to achieve this goal. Contrary to what might be expected, the results are more ambiguous regarding the use of the seed match as a feature, while accessibility appears to be a feature worth considering, indicating that, at least under some conditions, it may favour anchoring by miRNAs.
Special Issue: “Seismotectonics, Active Deformation, and Structure of the Crust”
Authors: Kassaras Ioannis , Ganas Athanassios , Pace Paolo
Published: March 2023

Knowledge of seismotectonics, active deformation, and the structure of Earth’s crust is key for the first-order perception and assessment of the seismic hazard, and consequently the seismic risk, of an area [...]
Voices from the Patients: A Qualitative Study of the Integration of Tuberculosis, Human Immunodeficiency Virus and Primary Healthcare Services in O.R. Tambo District, Eastern Cape, South Africa
Authors: Dlatu Ntandazo , Oladimeji Kelechi Elizabeth , Apalata Teke
Published: March 2023

Tuberculosis (TB), a disease of poverty and inequality, is a leading cause of severe illness and death among people with human immunodeficiency virus (HIV). In South Africa, both TB and HIV epidemics have been closely related and persistent, posing a significant burden for healthcare provision. Studies have observed that TB-HIV integration reduces mortality. The operational implementation of integrated services is still challenging. This study aimed to describe patients’ perceptions on barriers to scaling up of TB-HIV integration services at selected health facilities (study sites) in Oliver Reginald (O.R) Tambo Municipality, Eastern Cape province, South Africa. We purposely recruited twenty-nine (29) patients accessing TB and HIV services at the study sites. Data were analyzed using qualitative content analysis and presented as emerging themes. Barriers identified included a lack of health education about TB and HIV; an inadequate counselling for HIV and the antiretroviral drugs (ARVs); and poor quality of services provided by the healthcare facilities. These findings suggest that the O.R. Tambo district needs to strengthen its TB-HIV integration immediately.
The Functions of TRIM56 in Antiviral Innate Immunity and Tumorigenesis
Authors: Fu Lin , Zhou Xiaotong , Jiao Qian , Chen Xi
Published: March 2023

As a member of the TRIM (tripartite motif) protein family, TRIM56 can function as an E3 ubiquitin ligase. In addition, TRIM56 has been shown to possess deubiquitinase activity and the ability to bind RNA. This adds to the complexity of the regulatory mechanism of TRIM56. TRIM56 was initially found to be able to regulate the innate immune response. In recent years, its role in direct antiviral and tumor development has also attracted the interest of researchers, but there is no systematic review on TRIM56. Here, we first summarize the structural features and expression of TRIM56. Then, we review the functions of TRIM56 in TLR and cGAS-STING pathways of innate immune response, the mechanisms and structural specificity of TRIM56 against different types of viruses, and the dual roles of TRIM56 in tumorigenesis. Finally, we discuss the future research directions regarding TRIM56.