bluuebunny/crossref_metadata_2025 huggingface dataset:
Genetic Inhibition of Mitochondrial Permeability Transition Pore Exacerbates Ryanodine Receptor 2 Dysfunction in Arrhythmic Disease
Authors: Deb Arpita , Tow Brian D. , Qing You , Walker Madelyn , Hodges Emmanuel R. , Stewart James A. , Knollmann Björn C. , Zheng Yi , Wang Ying , Liu Bin
Published: January 2023

The brief opening mode of the mitochondrial permeability transition pore (mPTP) serves as a calcium (Ca2+) release valve to prevent mitochondrial Ca2+ (mCa2+) overload. Catecholaminergic polymorphic ventricular tachycardia (CPVT) is a stress-induced arrhythmic syndrome due to mutations in the Ca2+ release channel complex of ryanodine receptor 2 (RyR2). We hypothesize that inhibiting the mPTP opening in CPVT exacerbates the disease phenotype. By crossbreeding a CPVT model of CASQ2 knockout (KO) with a mouse missing CypD, an activator of mPTP, a double KO model (DKO) was generated. Echocardiography, cardiac histology, and live-cell imaging were employed to assess the severity of cardiac pathology. Western blot and RNAseq were performed to evaluate the contribution of various signaling pathways. Although exacerbated arrhythmias were reported, the DKO model did not exhibit pathological remodeling. Myocyte Ca2+ handling was similar to that of the CASQ2 KO mouse at a low pacing frequency. However, increased ROS production, activation of the CaMKII pathway, and hyperphosphorylation of RyR2 were detected in DKO. Transcriptome analysis identified altered gene expression profiles associated with electrical instability in DKO. Our study provides evidence that genetic inhibition of mPTP exacerbates RyR2 dysfunction in CPVT by increasing activation of the CaMKII pathway and subsequent hyperphosphorylation of RyR2.
New Insights into the Basic and Translational Aspects of AMPK Signaling
Authors: Ladilov Yury , Aslam Muhammad
Published: January 2023

5′-adenosine monophosphate (AMP)-activated protein kinase (AMPK) is an enzyme regulating numerous cellular processes involved in cell survival as well as health- and lifespan [...]
Inflammatory Molecules Responsible for Length Shortening and Preterm Birth
Authors: Fasoulakis Zacharias , Koutras Antonios , Ntounis Thomas , Antsaklis Panos , Theodora Marianna , Valsamaki Asimina , Daskalakis George , Kontomanolis Emmanuel N.
Published: January 2023

It is estimated that inflammation at the placental–maternal interface is directly responsible for or contributes to the development of 50% of all premature deliveries. Chorioamnionitis, also known as the premature rupture of the amniotic membrane in the mother, is the root cause of persistent inflammation that preterm newborns experience. Beyond contributing to the onset of early labor, inflammation is a critical element in advancing several conditions in neonates, including necrotizing enterocolitis, retinopathy of prematurity, bronchopulmonary dysplasia, intraventricular hemorrhage, retinopathy of prematurity and periventricular leukomalacia. Notably, the immune systems of preterm infants are not fully developed; immune defense mechanisms and immunosuppression (tolerance) have a delicate balance that is easily upset in this patient category. As a result, premature infants are exposed to different antigens from elements such as hospital-specific microbes, artificial devices, medications, food antigens and hypoxia/hyperoxia. This has detrimental implications for preterm deliveries of less than 28 weeks because they have not yet evolved the mechanisms to tolerate maternal and self-antigens.
Recognizing the Differentiation Degree of Human Induced Pluripotent Stem Cell-Derived Retinal Pigment Epithelium Cells Using Machine Learning and Deep Learning-Based Approaches
Authors: Lien Chung-Yueh , Chen Tseng-Tse , Tsai En-Tung , Hsiao Yu-Jer , Lee Ni , Gao Chong-En , Yang Yi-Ping , Chen Shih-Jen , Yarmishyn Aliaksandr A. , Hwang De-Kuang , Chou Shih-Jie , Chu Woei-Chyn , Chiou Shih-Hwa , Chien Yueh
Published: January 2023

Induced pluripotent stem cells (iPSCs) can be differentiated into mesenchymal stem cells (iPSC-MSCs), retinal ganglion cells (iPSC-RGCs), and retinal pigmental epithelium cells (iPSC-RPEs) to meet the demand of regeneration medicine. Since the production of iPSCs and iPSC-derived cell lineages generally requires massive and time-consuming laboratory work, artificial intelligence (AI)-assisted approach that can facilitate the cell classification and recognize the cell differentiation degree is of critical demand. In this study, we propose the multi-slice tensor model, a modified convolutional neural network (CNN) designed to classify iPSC-derived cells and evaluate the differentiation efficiency of iPSC-RPEs. We removed the fully connected layers and projected the features using principle component analysis (PCA), and subsequently classified iPSC-RPEs according to various differentiation degree. With the assistance of the support vector machine (SVM), this model further showed capabilities to classify iPSCs, iPSC-MSCs, iPSC-RPEs, and iPSC-RGCs with an accuracy of 97.8%. In addition, the proposed model accurately recognized the differentiation of iPSC-RPEs and showed the potential to identify the candidate cells with ideal features and simultaneously exclude cells with immature/abnormal phenotypes. This rapid screening/classification system may facilitate the translation of iPSC-based technologies into clinical uses, such as cell transplantation therapy.
The Fibrotic Effects of LINC00663 in Human Hepatic Stellate LX-2 Cells and in Bile Duct-Ligated Cholestasis Mice Are Mediated through the Splicing Factor 2-Fibronectin
Authors: Chu Yang , Bao Linan , Teng Yun , Yuan Bo , Ma Lijie , Liu Ying , Kang Hui
Published: January 2023

Hepatic fibrosis can develop into cirrhosis or even cancer without active therapy at an early stage. Long non-coding RNAs (lncRNAs) have been shown to be involved in the regulation of a wide variety of important biological processes. However, lncRNA mechanism(s) involved in cholestatic liver fibrosis remain unclear. RNA sequence data of hepatic stellate cells from bile duct ligation (BDL) mice or controls were analyzed by weighted gene co-expression network analysis (WGCNA). Based on WGCNA analysis, a competing endogenous RNA network was constructed. We identified LINC00663 and evaluated its function using a panel of assays, including a wound healing assay, a dual-luciferase reporter assay, RNA binding protein immunoprecipitation and chromatin immunoprecipitation. Functional research showed that LINC00663 promoted the activation, migration and epithelial–mesenchymal transition (EMT) of LX-2 cells and liver fibrosis in BDL mice. Mechanistically, LINC00663 regulated splicing factor 2 (SF2)-fibronectin (FN) alternative splicing through the sponging of hsa-miR-3916. Moreover, forkhead box A1 (FOXA1) specifically interacted with the promoter of LINC00663. In summary, we elaborated the fibrotic effects of LINC00663 in human hepatic stellate LX-2 cells and in bile duct-ligated cholestasis mice. We established a FOXA1/LINC00663/hsa-miR-3916/SF2-FN axis that provided a potential target for the diagnosis and targeted therapy of cholestatic liver fibrosis.
Idiopathic Scoliosis: Novel Challenges for Researchers and Clinicians
Authors: Zaina Fabio , Donzelli Sabrina , Negrini Stefano
Published: January 2023

Scoliosis is a three-dimensional deformity of the spine and trunk [...]
Lavender Essential Oil Modulates Hepatic Cholesterol Metabolism in HepG2 Cells
Authors: Martella Noemi , Colardo Mayra , Sergio William , Petraroia Michele , Varone Michela , Pensabene Daniele , Russo Miriam , Di Bartolomeo Sabrina , Ranalli Giancarlo , Saviano Gabriella , Segatto Marco
Published: January 2023

Cholesterol is an essential lipid that guarantees several biological processes in eukaryotic cells. Its metabolism is regulated by a complex protein network that could be significantly influenced by numerous exogenous sources, such as essential oils (EOs). For instance, it has been speculated that monoterpenoid and sesquiterpenoid compounds contained in lavender essential oil (LEO) may exert important hypocholesterolemic activities. However, the molecular mechanisms by which LEO influences cholesterol homeostasis are not characterized. In this work, we evaluated the ability of LEO to regulate the protein network that controls cholesterol metabolism in the HepG2 cell line. The main findings indicate that LEO administration increases intracellular cholesterol content. Concurrently, LEO affects the expression of proteins involved in cholesterol uptake, biosynthesis, and trafficking. These effects are partially mediated by terpinene-4-ol, one of the most abundant compounds in LEO. These results demonstrate that LEO modulates cholesterol metabolism in hepatic cells.
Spectral Characteristics of Biomimetic Micro-Nano Structures Derived from Saharan Silver Ants—A Simulation Study
Authors: Liu Mingyue , Chen Bo , Zhang Dehai , Chen Jian
Published: January 2023

Proper selections of microwave-transmitting thermal control materials play key roles in the orbit operations of aerospace microwave detectors. Currently, white paint and germanium-coated polyimide film are common choices for microwave-transmitting thermal control, which have been extensively studied from the perspective of material compositions, ignoring the influence of the micro-nano structure on the surface of the material. Inspired by Saharan silver ants relying on micro-nano structures of hairs for heat protection and dissipation, in this paper, based on finite element simulation, spectral characteristics (e.g., solar absorptance and infrared emissivity) of three types of biomimetic micro-nano structures (e.g., including pyramid, tetrahedron, and triangular prism) were studied and compared. Simulation results revealed that spectral characteristics of these biomimetic micro-nano structures were mainly regulated by the tip height and the air gap; the decrease of the tip height led to the decrease in the solar absorptance and the infrared emissivity; the solar absorptance was decreased, and the infrared emissivity was increased with the increase of the air gap. When these biomimetic structures were compared with flat surfaces without micro-nano topographies, a decrease of the solar absorptance to block the incidence of heat flow from the sun and an increase of the infrared emissivity to dissipate its own heat to the space were located, which may give suggestions on the adjustment of spectral characteristics of aerospace microwave-transmitting thermal control materials.
Thymol-Functionalized Silica Nanomaterials Prepared by Post-Grafting Method: Preparation, Characterization, Bactericidal Activity and Mechanism Research
Authors: Wang Liang , Ni Tianjun , Wei Shiqin
Published: January 2023

In this study, thymol was covalently connected to mesoporous silica nanomaterial by a post-grafting method to obtain a stable antibacterial system, thus overcoming the volatilization of thymol, prolonging the effective time of antibacterial action, and enhancing the antibacterial efficiency of thymol. It was proposed for the first time that such a synthetic route be adopted to synthesize silica-based mesoporous/essential oil antibacterial materials. The post-grafting method could be capable of retaining the mesoporous original structure, which could effectively avoid the porosity reduction and disordered products caused by condensation. Among them, the minimum bactericidal concentration (MBC) of functionalized MCM-41 (silica support) for E. coli and S. aureus were 0.3 mg mL−1 and 0.4 mg mL−1, which were equivalent to 3/4 and 4/5 of free thymol (0.4 mg mL−1 and 0.5 mg mL−1), respectively. Meanwhile, the MBC of functionalized SBA-15 (silica support) for E. coli and S. aureus were both 0.2 mg mL−1, which also reduced the MBC of free thymol. These results revealed thymol-functionalized mesoporous silica nanomaterial could efficiently improve the bactericidal activities of the organic component. Finally, the inhibition mechanism of the post-grafting strategy was also discussed, which referred to how the antibacterial material directly acts on the cell membrane, resulting in cell inactivation.
The Application of Rubber Aggregate-Combined Permeable Concrete Mixture in Sponge City Construction
Authors: Qi Bowen , Gao Shouwu , Xu Peilong
Published: January 2023

Permeable concrete is a new type of pavement material, which can effectively improve the urban flood discharge system, and is of great significance to the construction of sponge city. In order to optimize the use effect of permeable concrete and improve the application value of permeable concrete in permeable road engineering, the combination of rubber aggregate and permeable concrete is proposed, and the mix ratio of rubber permeable concrete mixture material is designed, which is applied to the engineering of pavement in Hunan Province, and its comprehensive pavement performance is analyzed and evaluated. The results show that the rubber permeable concrete has the best performance when the water cement ratio is 0.3, the designed porosity is 15%, the rubber particle size is 16 mesh, the rubber content is 15% and the coarse aggregate ratio is 4:6. The removal rates of suspended solids and metal pollutants are 0.65 and 0.72, respectively, which are increased by 0.23 and 0.19, respectively, compared with ordinary permeable concrete. This shows that rubber permeable concrete improves the ecological benefits of permeable concrete pavement, gives full play to the economic benefits of waste rubber products, reduces the construction cost of permeable concrete pavement, and provides assistance for promoting the construction of sponge city.
The Indentation Size Effect (ISE) of Ag–Cu Alloys
Authors: Šolc Marek , Blaško Peter , Petrík Jozef , Palfy Pavol , Girmanová Lenka
Published: January 2023

The literature regarding the Indentation Size Effect (ISE) in metal alloys is scarce. The content of this article is the study of the relationship between the applied load and the measured values of the Vickers micro-hardness of silver and copper alloys, measured with a Hanemann hardness tester. The load values ranged between 0.09807 N (10 g) and 0.9807 N (100 g). The size and character of the ISE were evaluated using Meyer’s power law (index n), Proportional Specimen Resistance (PSR) and the Hays–Kendall method. Coins and utility objects of Central European provenance with a silver content of 50 to 99.99% were used as samples. All samples showed a reverse effect (RISE) with a value of n > 2, which is typical for plastic materials. The relatively high variability of the measured micro-hardness and consequently of the index n is related to other factors, such as the age of the sample (age hardening by the precipitation of copper), the uneven degree of deformation and microstructure. The analyzed Ag–Cu alloys show a gradual increase in the Meyer index n with the increase in the silver content, while the ISE has a reverse character throughout the range. The obtained data make it possible to determine the approximate age of artifacts from the mentioned alloys.
One-Dimensional Photonic Crystal with a Defect Layer Utilized as an Optical Filter in Narrow Linewidth LED-Based Sources
Authors: Gryga Michal , Ciprian Dalibor , Gembalova Lucie , Hlubina Petr
Published: January 2023

A one-dimensional photonic crystal (1DPhC) with a defect layer is utilized as an optical filter in a simple realization of narrow linewidth LED-based sources. The 1DPhC comprising TiO2 and SiO2 layers is characterized by two narrow defect mode resonances within the 1DPhC band gap, or equivalently, by two peaks in the normal incidence transmittance spectrum at wavelengths of 625.4 nm and 697.7 nm, respectively. By combining the optical filter with LEDs, the optical sources are employed in interferometry experiments, and the defect mode resonances of a Lorentzian profile with linewidths of 1.72 nm and 1.29 nm, respectively, are resolved. In addition, a simple way to tune the resonances by changing the angle of incidence of light on the optical filter is demonstrated. All-dielectric optical filters based on 1DPhCs with a defect layer and combined with LEDs thus represent an effective alternative to standard coherent sources, with advantages including narrow spectral linewidths and variable output power, with an extension to tunable sources.
Haemosporidians in Non-Passerine Birds of Colombia: An Overview of the Last 20 Years of Research
Authors: Lotta-Arévalo Ingrid Astrid , González Angie Daniela , Gamboa-Suárez Brayan Andrés , Pacheco M. Andreína , Escalante Ananías A. , Moreno Carlos , Rodríguez-Fandíño Oscar , Cuervo Andrés , Matta Nubia E.
Published: January 2023

The Neotropics are highly diverse in avian species. Neotropical countries contribute a large part of the estimated diversity of haemosporidian parasites reported for the planet’s tropical zones. However, sampling is limited and biased, illustrated by only 30% of the genetic records (barcodes) from non-passerines, most of them not linked to a nominal species. This paper aimed to perform the molecular and morphological characterization of the haemosporidians that infect non-passerine birds from Colombia deposited in the biological collection named “Grupo de Estudio Relación Parásito Hospedero (GERPH)”. We analyzed 1239 samples from twelve biomes and two animal care facilities. Phylogenetic relationships using barcodes and mitochondrial genomes were estimated. In addition, the reports of haemosporidian infections in non-passerine birds from the Neotropics recorded after 1978 were summarized. We reported the presence of thirteen morphological haemosporidian species, four potential new species deposited in GERPH, a host range expansion for two Plasmodium species, and a barcode sequence for Haemoproteus caprimulgi. We confirmed the species associated with 56 molecular lineages reported in other neotropical countries at the genus level. Thus, biological collections and curated databases such as MalAvi are essential to support integrative approaches demanded in modern taxonomy.
Combining Geographic Distribution and Trait Information to Infer Predator–Prey Species-Level Interaction Properties
Authors: Sánchez-Barradas Alejandro , Dáttilo Wesley , Santiago-Alarcon Diego , Kissling W. Daniel , Villalobos Fabricio
Published: January 2023

Biotic interactions are a key component of the proper functioning of ecosystems. However, information on biotic interactions is spatially and taxonomically biased and limited to several groups. The most efficient strategy to fill these gaps is to combine spatial information (species ranges) with different sources of information (functional and field data) to infer potential interactions. This approach is possible due to the fact that there is a correspondence between the traits of two trophic levels (e.g., predator and prey sizes are correlated). Therefore, our objective was to evaluate the performance of the joint use of spatial, functional and field data to infer properties of the predator–prey interaction for five neotropical cats. To do this, we used presence–absence matrices to obtain lists of potential prey species per grid-cell for each predator range. These lists were filtered according to different criteria (models), and for each model, an interaction property was estimated and compared with field observations. Our results show that the use of functional information and co-occurrence allows us to generate values similar to those observed in the field. We also observed that there were differences in model performance related to the intrinsic characteristics of the predator (body size) and the interaction property being evaluated.
CFD Investigation of Ventilation Strategies to Remove Contaminants from a Hospital Room
Authors: Alkhalaf Mustafa , Ilinca Adrian , Hayyani Mohamed Yasser
Published: January 2023

The primary requirement in designing air conditioning systems in healthcare facilities is eliminating contaminants. It is considered one of the crucial health elements in building design, particularly in the presence of many airborne diseases such as COVID-19. The purpose of this numerical research is to simulate various ventilation designs for a hospital room model by taking into account results obtained by previous researchers. Four designs with three airflows, 9, 12, and 15 ACH (Air Change per Hour), are applied to explore the capacity of the ventilation system to remove contaminants. The objective is to determine the influence of airflow and the diffuser location distribution on the pollutants elimination represented by carbon dioxide. The Reynold Averaged Navier–Stokes (RANS) equations and the k-ε turbulence model were used as the underlying mathematical model for the airflow. In addition, boundary conditions were extracted from ASHRAE (American Society of Heating, Refrigeration, and Air-Conditioning Engineers Society) ventilation publications and relevant literature. Contrary to what was expected, this study’s results demonstrated that increased ventilation alone does not always improve air distribution or remove more contaminants. In addition, pollutant removal was significantly affected by the outlet’s location.
Oncologic Outcome after Pulmonary Metastasectomy as Part of Multidisciplinary Treatment in a Tertiary Oncological Center
Authors: Motas Natalia , Davidescu Mihnea Dan , Tanase Bogdan Cosmin , Rus Ovidiu , Burlacu Alin Ionut , Alexe Vlad , Manolache Veronica , Mizea Madalina Cristiana , Gheorghiu Nicolae , Trifanescu Oana Gabriela , Gales Laurentia Nicoleta , Horvat Teodor , Anghel Rodica Maricela
Published: January 2023

(1) Background: Pulmonary metastases are encountered in approximately one-third of patients with malignancies, especially from colorectal, lung, breast, and renal cancers, and sarcomas. Pulmonary metastasectomy is the ablative approach of choice, when possible, as part of the multidisciplinary effort to integrate and personalize the oncological treatment. (2) Methods: The study includes 58 consecutive cases of pulmonary metastasectomies, retrospectively analyzed, performed in 12 consecutive months, in which the pathology reports confirmed lung metastases. (3) Results: Most frequent pathological types of metastases were: 14 of colorectal cancer, 10 breast, 8 lung, and 8 sarcomas. At the time of primary cancer diagnosis, 14 patients (24.14%) were in the metastatic stage. The surgical approach was minimally invasive through uniportal VATS (Video-Assisted Thoracic Surgery) in 3/4 of cases (43 patients, 74%). Almost 20% of resections were typical (lobectomy, segmentectomy). Lymphadenectomy was associated in almost 1/2 of patients and lymph node metastases were found in 11.11% of cases. The mortality rate (intraoperative and 90 days postoperative) is zero. The OS after pulmonary metastasectomy is 87% at 18 months, and the estimated OS for cancer is 90% at 5 years. The worst outcome presents the patients with sarcomas and the best outcome—colorectal and lung cancer. The patients with 1 or 2 resected metastases presented 96% survival at 24 months. (4) Conclusions: After pulmonary metastasectomy, survival is favored by the small number of metastases resected (1 or 2), and by the dimension of metastases under 20.5 mm. The non-anatomic (wedge) type of lung resection may present a lower risk of death compared to lobectomy. No statistical significance on survival has the presence of lymphadenectomy, the laterality right/left lung, the upper/lower lobes. In the future, longer follow-up and prospective randomized trials are needed for drawing definitive conclusions.
Prognostic Role of Vascular Endothelial Growth Factor and Correlation with Oxidative Stress Markers in Locally Advanced and Metastatic Ovarian Cancer Patients
Authors: Trifanescu Oana Gabriela , Gales Laurentia Nicoleta , Tanase Bogdan Cosmin , Marinescu Serban Andrei , Trifanescu Raluca Alexandra , Gruia Iuliana Maria , Paun Mihai Andrei , Rebegea Laura , Mitrica Radu , Serbanescu Luiza , Anghel Rodica Maricela
Published: January 2023

Background: Vascular endothelial growth factor (VEGF) plays an important role in tumor progression in ovarian cancer, but the complex mechanism and interaction with oxidative stress are not fully understood. Methods: A prospective study included 52 patients with ovarian adenocarcinoma stage IIIA-IV. Serum VEGF and reactive oxygen species (ROS) such as malondialdehyde and ceruloplasmin were measured. Results: VEGF levels were elevated (mean 1014.7 ± 165 pg/mL), especially in patients with macroscopic residual disease (1058 vs. 810 pg/mL, p = 0.0001). Median progression-free survival (PFS) and overall survival (OS) were 6 and 40 months in patients with a very high VEGF (over 1200 pg/mL), 11 and 48 months in patients with VEGF between 1000–1200 pg/mL, 18 and 84 months in patients with VEGF between 800–1000 pg/mL, and not reached in patients with normal VEGF. Increased VEGF values were associated with a 2.6-fold increased risk of disease progression (HR = 2.60, 95% CI 1.69–3.99), and a 1.4-fold increased risk of death (HR = 1.4, 95% CI 1.15–1.91, p = 0.002). Receiver operator characteristic (ROC) curves were used to validate VEGF as a prognostic factor and the area under the curve (AUC) was 0.814, p = 0.036 for PFS and 0.729, p = 0.043, for OS. There was a positive correlation between VEGF and malondialdehyde, Pearson coefficient of 0.35, p = 0.0001. Conclusions: VEGF and malondialdehyde are important prognostic markers in ovarian cancer, especially in macroscopic residual disease, and there is a positive correlation between angiogenesis and oxidative stress.
GabROP: Gabor Wavelets-Based CAD for Retinopathy of Prematurity Diagnosis via Convolutional Neural Networks
Authors: Attallah Omneya
Published: January 2023

One of the most serious and dangerous ocular problems in premature infants is retinopathy of prematurity (ROP), a proliferative vascular disease. Ophthalmologists can use automatic computer-assisted diagnostic (CAD) tools to help them make a safe, accurate, and low-cost diagnosis of ROP. All previous CAD tools for ROP diagnosis use the original fundus images. Unfortunately, learning the discriminative representation from ROP-related fundus images is difficult. Textural analysis techniques, such as Gabor wavelets (GW), can demonstrate significant texture information that can help artificial intelligence (AI) based models to improve diagnostic accuracy. In this paper, an effective and automated CAD tool, namely GabROP, based on GW and multiple deep learning (DL) models is proposed. Initially, GabROP analyzes fundus images using GW and generates several sets of GW images. Next, these sets of images are used to train three convolutional neural networks (CNNs) models independently. Additionally, the actual fundus pictures are used to build these networks. Using the discrete wavelet transform (DWT), texture features retrieved from every CNN trained with various sets of GW images are combined to create a textural-spectral-temporal demonstration. Afterward, for each CNN, these features are concatenated with spatial deep features obtained from the original fundus images. Finally, the previous concatenated features of all three CNN are incorporated using the discrete cosine transform (DCT) to lessen the size of features caused by the fusion process. The outcomes of GabROP show that it is accurate and efficient for ophthalmologists. Additionally, the effectiveness of GabROP is compared to recently developed ROP diagnostic techniques. Due to GabROP’s superior performance compared to competing tools, ophthalmologists may be able to identify ROP more reliably and precisely, which could result in a reduction in diagnostic effort and examination time.
Taking Stock of Fruit and Vegetable Consumption in Canada: Trends and Challenges
Authors: Charlebois Sylvain , Music Janet , Rupasinghe H. P. Vasantha
Published: January 2023

Purpose: A diet rich in fruits and vegetables is vital for prolonged health and wellness. Yet, the consumption of fruits and vegetables remains low in some regions. Methodology: This exploratory quantitative study utilized a web-based survey instrument to probe the likelihood of consumption by Canadian consumers. Canadians who have lived in the country for 12 months or more and were 18 years of age or older were surveyed. Care was given to get a representative sample from all Canadian regions. Findings: Barriers to produce consumption include cost (39.5%), lack of knowledge and preparation skills (38.5%), and confusion surrounding health benefits (6.3%). There is further confusion surrounding the nutrition of frozen vs. fresh vegetables. Finally, respondents were concerned about pesticide residue on imported produce (63.4%). Originality: Although evidence that fruits and vegetables can mitigate disease and that promotion of fruit and vegetable consumption has been a key policy area for the Canadian government, consumers still fail to integrate sufficient fruits and vegetables into their diets. To our knowledge, this is the only study probing consumers on their fresh produce intake in the Canadian context. Public awareness and education about the regular consumption of fruits and vegetables and their nutritional value and health-promoting benefits can increase consumption in many Canadian regions and demographics.
Invariant-Parameterized Exact Evolution Operator for SU(2) Systems with Time-Dependent Hamiltonian
Authors: Nakazato Hiromichi , Sergi Alessandro , Migliore Agostino , Messina Antonino
Published: January 2023

We report the step-by-step construction of the exact, closed and explicit expression for the evolution operator U(t) of a localized and isolated qubit in an arbitrary time-dependent field, which for concreteness we assume to be a magnetic field. Our approach is based on the existence of two independent dynamical invariants that enter the expression of SU(2) by means of two strictly related time-dependent, real or complex, parameters. The usefulness of our approach is demonstrated by exactly solving the quantum dynamics of a qubit subject to a controllable time-dependent field that can be realized in the laboratory. We further discuss possible applications to any SU(2) model, as well as the applicability of our method to realistic physical scenarios with different symmetry properties.
Resource Concentration and Clustering in Replicator Dynamics with Stochastic Reset Events
Authors: Gómez Garay Ignacio T. , Zanette Damián H.
Published: January 2023

As a model for economic and ecological systems, replicator dynamics represent a basic form of agent competition for finite resources. Here, we investigate the effects of stochastic resetting in this kind of processes. Random reset events abruptly lead individual resources to a small value from which dynamics must start anew. Numerical results show that resource distribution over the population of competing agents develops highly nonuniform profiles, exhibiting clustering and fluctuations with anomalous dependence on the population size. This non-standard statistical behavior jeopardizes an analytical treatment based on mean-field assumptions. We propose alternative simplified analytical approaches which provide a stylized description of entropy evolution for the clustered distribution of resources and explain the unusually slow decrease of fluctuations.
The Complexity Behavior of Big and Small Trading Orders in the Chinese Stock Market
Authors: Zhu Yu , Fang Wen
Published: January 2023

The Chinese stock market exhibits many characteristics that deviate from the efficient market hypothesis and the trading volume contains a great deal of complexity information that the price cannot reflect. Do small or big orders drive trading volume? We studied the complex behavior of different orders from a microstructure perspective. We used ETF data of the CSI300, SSE50, and CSI500 indices and divided transactions into big and small orders. A multifractal detrended fluctuation analysis (MFDFA) method was used to study persistence. It was found that the persistence of small orders was stronger than that of big orders, which was caused by correlation with time. A multiscale composite complexity synchronization (MCCS) method was used to study the synchronization of orders and total volume. It was found that small orders drove selling-out transactions in the CSI300 market and that big orders drove selling-out transactions in the CSI500 market. Our findings are useful for understanding the microstructure of the trading volume in the Chinese market.
Observations on the Lovász θ-Function, Graph Capacity, Eigenvalues, and Strong Products †
Authors: Sason Igal
Published: January 2023

This paper provides new observations on the Lovász θ-function of graphs. These include a simple closed-form expression of that function for all strongly regular graphs, together with upper and lower bounds on that function for all regular graphs. These bounds are expressed in terms of the second-largest and smallest eigenvalues of the adjacency matrix of the regular graph, together with sufficient conditions for equalities (the upper bound is due to Lovász, followed by a new sufficient condition for its tightness). These results are shown to be useful in many ways, leading to the determination of the exact value of the Shannon capacity of various graphs, eigenvalue inequalities, and bounds on the clique and chromatic numbers of graphs. Since the Lovász θ-function factorizes for the strong product of graphs, the results are also particularly useful for parameters of strong products or strong powers of graphs. Bounds on the smallest and second-largest eigenvalues of strong products of regular graphs are consequently derived, expressed as functions of the Lovász θ-function (or the smallest eigenvalue) of each factor. The resulting lower bound on the second-largest eigenvalue of a k-fold strong power of a regular graph is compared to the Alon–Boppana bound; under a certain condition, the new bound is superior in its exponential growth rate (in k). Lower bounds on the chromatic number of strong products of graphs are expressed in terms of the order and the Lovász θ-function of each factor. The utility of these bounds is exemplified, leading in some cases to an exact determination of the chromatic numbers of strong products or strong powers of graphs. The present research paper is aimed to have tutorial value as well.
GCM-SIV1.5: Optimal Tradeoff between GCM-SIV1 and GCM-SIV2
Authors: Zhang Ping
Published: January 2023

GCM-SIV2 is a nonce-based beyond-birthday-bound (BBB)-secure authenticated encryption (AE) mode introduced by Iwata and Minematsu at FSE 2017. However, it is built by combining two instances of GCM-SIV1 and needs eight keys, which increases the costs of hardware and software implementation. This paper aims to reduce these costs by optimizing components (such as key materials, hash calls, and block cipher calls) and proposes an optimal tradeoff between GCM-SIV1 and GCM-SIV2 called GCM-SIV1.5. Moreover, we introduce the faulty nonce setting to AE and prove the BBB security of GCM-SIV1.5 with graceful security degradation in the faulty nonce setting by mirror theory. Finally, we discuss advantages of GCM-SIV1.5.
Intelligent Computer Vision System for Analysis and Characterization of Yarn Quality
Authors: Pereira Filipe , Macedo Alexandre , Pinto Leandro , Soares Filomena , Vasconcelos Rosa , Machado José , Carvalho Vítor
Published: January 2023

The quality of yarn is essential in the control of the fabrics processes. There is some commercial equipment that measures the quality of yarn based on sensors, of different types, used for collecting data about some textile yarn characteristic parameters. The irregularity of the textile thread influences its physical properties/characteristics and there may be a possibility of a break in the textile thread during the fabric manufacturing process. This can contribute to the occurrence of unwanted patterns in fabrics that deteriorate their quality. The existing equipment, for the above-mentioned purpose, is characterized by its high size and cost, and for allowing the analysis of only few yarn quality parameters. The main findings/results of the study are the yarn analysis method as well as the developed algorithm, which allows the analysis of defects in a more precise way. Thus, this paper presents the development and results obtained with the design of a mechatronic prototype integrating a computer vision system that allows, among other parameters, the analysis and classification, in real time, of the hairs of the yarn using artificial intelligence techniques. The system also determines other characteristics inherent to the yarn quality analysis, such as: linear mass, diameter, volume, twist orientation, twist step, average mass deviation, coefficient of variation, hairiness coefficient, average hairiness deviation, and standard hairiness deviation, as well as performing spectral analysis. A comparison of the obtained results with the designed system and a commercial equipment was performed validating the undertaken methodology.
HetSev: Exploiting Heterogeneity-Aware Autoscaling and Resource-Efficient Scheduling for Cost-Effective Machine-Learning Model Serving
Authors: Mo Hao , Zhu Ligu , Shi Lei , Tan Songfu , Wang Suping
Published: January 2023

To accelerate the inference of machine-learning (ML) model serving, clusters of machines require the use of expensive hardware accelerators (e.g., GPUs) to reduce execution time. Advanced inference serving systems are needed to satisfy latency service-level objectives (SLOs) in a cost-effective manner. Novel autoscaling mechanisms that greedily minimize the number of service instances while ensuring SLO compliance are helpful. However, we find that it is not adequate to guarantee cost effectiveness across heterogeneous GPU hardware, and this does not maximize resource utilization. In this paper, we propose HetSev to address these challenges by incorporating heterogeneity-aware autoscaling and resource-efficient scheduling to achieve cost effectiveness. We develop an autoscaling mechanism which accounts for SLO compliance and GPU heterogeneity, thus provisioning the appropriate type and number of instances to guarantee cost effectiveness. We leverage multi-tenant inference to improve GPU resource utilization, while alleviating inter-tenant interference by avoiding the co-location of identical ML instances on the same GPU during placement decisions. HetSev is integrated into Kubernetes and deployed onto a heterogeneous GPU cluster. We evaluated the performance of HetSev using several representative ML models. Compared with default Kubernetes, HetSev reduces resource cost by up to 2.15× while meeting SLO requirements.
Analysis of Challenges and Solutions of IoT in Smart Grids Using AI and Machine Learning Techniques: A Review
Authors: Mazhar Tehseen , Irfan Hafiz Muhammad , Haq Inayatul , Ullah Inam , Ashraf Madiha , Shloul Tamara Al , Ghadi Yazeed Yasin , Imran  , Elkamchouchi Dalia H.
Published: January 2023

With the assistance of machine learning, difficult tasks can be completed entirely on their own. In a smart grid (SG), computers and mobile devices may make it easier to control the interior temperature, monitor security, and perform routine maintenance. The Internet of Things (IoT) is used to connect the various components of smart buildings. As the IoT concept spreads, SGs are being integrated into larger networks. The IoT is an important part of SGs because it provides services that improve everyone’s lives. It has been established that the current life support systems are safe and effective at sustaining life. The primary goal of this research is to determine the motivation for IoT device installation in smart buildings and the grid. From this vantage point, the infrastructure that supports IoT devices and the components that comprise them is critical. The remote configuration of smart grid monitoring systems can improve the security and comfort of building occupants. Sensors are required to operate and monitor everything from consumer electronics to SGs. Network-connected devices should consume less energy and be remotely monitorable. The authors’ goal is to aid in the development of solutions based on AI, IoT, and SGs. Furthermore, the authors investigate networking, machine intelligence, and SG. Finally, we examine research on SG and IoT. Several IoT platform components are subject to debate. The first section of this paper discusses the most common machine learning methods for forecasting building energy demand. The authors then discuss IoT and how it works, in addition to the SG and smart meters, which are required for receiving real-time energy data. Then, we investigate how the various SG, IoT, and ML components integrate and operate using a simple architecture with layers organized into entities that communicate with one another via connections.
An Improved VLSI Algorithm for an Efficient VLSI Implementation of a Type IV DCT That Allows an Efficient Incorporation of Hardware Security with a Low Overhead
Authors: Chiper Doru Florin
Published: January 2023

This paper aims to solve one of the most challenging problems in designing VLSI chips for common goods, namely an efficient incorporation of security techniques while maintaining high performances of the VLSI implementation with a reduced hardware complexity. In this case, it is very important to maintain high performance at a low hardware complexity and the overheads introduced by the security techniques should be as low as possible. This paper proposes an improved approach based on a new VLSI algorithm for including the obfuscation technique in the VLSI implementation of one important DSP algorithm used in multimedia applications. The proposed approach is based on a new VLSI algorithm that decomposes type IV DCT into six quasi-cycle convolutions and allows an efficient incorporation of the obfuscation technique. The proposed method uses a regular and modular structure called quasi-cyclic convolution and the obtained architecture is based on the architectural paradigm of systolic arrays. In this way we can obtain the advantages introduced by systolic arrays, especially high speed, with an efficient utilization of the hardware structure. Moreover, using the proposed VLSI algorithm, we can obtain the important benefit of attaining hardware security. Thus, a more efficient VLSI architecture for type IV DCT can be obtained, with a significant reduction of the hardware complexity, and an efficient incorporation of an improved hardware security mechanism with low overheads. These features are very important for resource-constrained common goods.
Magnetic Design Aspects of Coupled-Inductor Topologies for Transient Suppression
Authors: Silva Thotabaddadurage Sadeeshvara , Kularatna Nihal , Steyn-Ross D. Alistair
Published: January 2023

Based on the discovery of the surge absorption capability of supercapacitors, a transient protector named supercapacitor-assisted surge absorber (SCASA) was designed and implemented in a commercial device. Despite its simplicity, the circuit topology consisted of a coupled inductor wound around a specially selected magnetic core. This paper elucidates the design aspects of SCASA coupled-inductor topologies with a special focus on the magnetic action of core windings during transient propagation. The non-ideal operation of the SCASA transformer was studied based on a semi-empirical approach with predictions made by using magnetizing and leakage permeances. The toroidal flux distribution through the transformer was also determined for a 6 kV/3 kA combinational surge, and these findings were validated by using a lightning surge simulator. In predicting the possible effects of magnetic saturation, the hysteresis properties of different powdered-iron and ferrite core types were considered to select the optimal design for surge absorption. The test results presented in this research revealed that X-Flux powdered-iron toroid and air-gapped EER ferrite yielded exceptional performance with ∼10% and ∼20% lower load–voltage clamping compared to that of the existing Kool μu design. These prototypes further demonstrated a remarkable surge endurance, withstanding over 250 consecutive transients. This paper also covers details of three-winding design optimizations of SCASA and LTSpice simulations under the IEC 61000/IEEE C62.45 standard transient conditions.
Development of Non-Destructive Testing Device for Plant Leaf Expansion Monitoring
Authors: Meng Xianchang , Zheng Yili , Liu Weiping
Published: January 2023

This paper designs a plant leaf expansion pressure non-destructive detection device, aiming to promote plant leaf expansion pressure research and achieve precision irrigation. The design is based on leaf expansion pressure probe technology, which can effectively monitor the plant leaf expansion pressure by detecting the feedback of the leaf under constant pressure. In this paper, the stability of the sensor and the calibration model is tested. The calibration experiments showed that the coefficient of determination R2 of the sensor was over 0.99, the static test results showed that the range of the sensor was 0–300 kPa, and the fluctuation of the sensor was less than 0.2 kPa during the long-term stability test. The indoor comparison tests showed that there was a significant difference in the variation of leaf expansion pressure data between plants under drought conditions and normal conditions. The irrigation experiments showed that the leaf expansion pressure was very sensitive to irrigation. The correlation between the expansion pressure data and the environmental factors was analyzed. The correlation coefficient between expansion pressure and light intensity was found to be 0.817. The results of the outdoor experiments showed that there was a significant difference in the expansion pressure of plants under different weather conditions. The data show that the plant leaf expansion pressure non-destructive detection device designed in this paper can be used both as an effective means of detecting plant leaf expansion pressure and promoting the research of plant physiological feedback mechanisms and precision irrigation.
A 100-Gb/s PAM-4 DSP in 28-nm CMOS for Serdes Receiver
Authors: Li Weijie , Liu Min , Zheng Xuqiang , Xiao Guangxing , Yuan Guojun , Hao Qinfen , Jin Zhi
Published: January 2023

This paper presents a dedicated digital signal process (DSP) for four pulse amplitude modulation (PAM4) SerDes receivers. It is targeted to implement data recovery and adaptive equalization under ultra-high-speed and large channel attenuation with a small area and high power efficiency. The DSP consists of a clock data recovery (CDR), a 16-tap feed forward equalizer (FFE), a 1-tap decision feedback equalizer (DFE), and an automatic adaptation engine. An adaptive least mean square (LMS) algorithm is utilized to make the system more intelligent in calculating tap coefficients of the FFE and DFE. To address the timing limitation associated with traditional digital DFE that cannot handle large amounts of parallel data at a high speed, speculative techniques and a customized 4-to-1 multiplexer (MUX) unit are employed to remove the summation time and reduce the selection time, respectively. A first-order sigma-delta modulator is used to replace the traditional moving average to calculate average voltages, which could prominently save the hardware resources and power consumption. Additionally, the influence of input quantization resolution on the equalization ability is analyzed. Implemented in a 28-nm CMOS, the DSP could compensate for up to 33-dB loss at 100 Gb/s with a power consumption of 7.22 pJ/bit.