bluuebunny/crossref_metadata_2025 huggingface dataset:
Association between Iron Deficiency and Survival in Older Patients with Cancer
Authors: Tisserand Julie , Randrian Violaine , Paccalin Marc , Saulnier Pierre-Jean , Arviset Marine , Fourmy Arthur , Arriudarré Victor , Jamet Amélie , Moreno Yvan , Valéro Simon , Liuu Evelyne
Published: March 2023

Background: iron deficiency (ID) is frequent in older patients. Purpose: to evaluate the association between ID and survival in patients ≥ 75 years old with confirmed solid tumors. Methods: a retrospective monocentric study including patients between 2009 and 2018. ID, absolute ID (AID) and functional ID (FID) were defined according to the European Society for Medical Oncology (ESMO) criteria. Severe ID was defined by a ferritin level < 30 µg/L. Results: in total, 556 patients were included, the mean age was 82 (±4.6) years, 56% were male, the most frequent cancer was colon cancer (19%, n = 104), and metastatic cancers were found in 38% (n = 211). Median follow-up time: 484 [190–1377] days. In anemic patients, ID and FID were independently associated with an increased risk of mortality (respectively, HR 1.51; p = 0.0065 and HR 1.73; p = 0.0007). In non-anemic patients, FID was independently associated with better survival (HR 0.65; p = 0.0495). Conclusion: in our study, ID was significantly associated with survival, and with better survival for patients without anemia. These results suggest that attention should be paid to the iron status in older patients with tumors and raise questions about the prognostic value of iron supplementation for iron-deficient patients without anemia.
Merkel Cell Carcinoma: An Update and Review
Authors: Stockfleth Eggert
Published: March 2023

Merkel cell carcinoma (MCC) is a rare, very aggressive skin cancer with a high mortality rate and a high tendency of metastatic spread [...]
Insight on Non-Coding RNAs from Biofluids in Ovarian Tumors
Authors: Dabi Yohann , Favier Amélia , Razakamanantsoa Léo , Delbos Léa , Poilblanc Mathieu , Descamps Philippe , Golfier Francois , Touboul Cyril , Bendifallah Sofiane , Daraï Emile
Published: March 2023

Ovarian tumors are the most frequent adnexal mass, raising diagnostic and therapeutic issues linked to a large spectrum of tumors, with a continuum from benign to malignant. Thus far, none of the available diagnostic tools have proven efficient in deciding strategy, and no consensus exists on the best strategy between “single test”, “dual testing”, “sequential testing”, “multiple testing options” and “no testing”. In addition, there is a need for prognostic tools such as biological markers of recurrence and theragnostic tools to detect women not responding to chemotherapy in order to adapt therapies. Non-coding RNAs are classified as small or long based on their nucleotide count. Non-coding RNAs have multiple biological functions such as a role in tumorigenesis, gene regulation and genome protection. These ncRNAs emerge as new potential tools to differentiate benign from malignant tumors and to evaluate prognostic and theragnostic factors. In the specific setting of ovarian tumors, the goal of the present work is to offer an insight into the contribution of biofluid non-coding RNAs (ncRNA) expression.
The Effectiveness of Fluoroscopy-Guided Manual Lymph Drainage as Part of Decongestive Lymphatic Therapy on the Superficial Lymphatic Architecture in Patients with Breast Cancer-Related Lymphoedema: A Randomised Controlled Trial
Authors: Devoogdt Nele , Thomis Sarah , De Groef An , Heroes An-Kathleen , Nevelsteen Ines , Gebruers Nick , Tjalma Wiebren A. A. , Belgrado Jean-Paul , Monten Chris , Hanssens Marianne , De Vrieze Tessa
Published: March 2023

The objective of this trial was to investigate the effectiveness of fluoroscopy-guided manual lymph drainage (MLD), as part of decongestive lymphatic therapy (DLT), on the superficial lymphatic architecture in patients with chronic mild to moderate breast cancer-related lymphoedema (BCRL). This trial was a multicentre, double-blind, randomised controlled trial involving 194 participants with BCRL. Participants were randomised into (1) DLT with fluoroscopy-guided MLD (intervention group), (2) DLT with traditional MLD (control group), or (3) DLT with placebo MLD (placebo group). Superficial lymphatic architecture was evaluated as a secondary outcome, visualised by ICG lymphofluoroscopy at the baseline (B0), post-intensive (P), and post-maintenance phases (P6). Variables were (1) number of efferent superficial lymphatic vessels leaving the dermal backflow region, (2) total dermal backflow score, and (3) number of superficial lymph nodes. The traditional MLD group showed a significant decrease in the number of efferent superficial lymphatic vessels at P (p = 0.026), and of the total dermal backflow score at P6 (p = 0.042). The fluoroscopy-guided MLD and placebo group showed significant decreases in the total dermal backflow score at P (p < 0.001 and p = 0.044, respectively) and at P6 (p < 0.001 and p = 0.007, respectively); the placebo MLD group showed a significant decrease in the total number of lymph nodes at P (p = 0.008). However, there were no significant between-group differences for the changes in these variables. In conclusion, based on lymphatic architecture outcomes, the added value of MLD, in addition to the other parts of DLT, could not be demonstrated in patients with chronic mild to moderate BCRL.
Long-Term Follow-Up of Lentigo Maligna Patients Treated with Imiquimod 5% Cream
Authors: Seyed Jafari S. Morteza , Folini-Huesser Flavia , Cazzaniga Simone , Hunger Robert E.
Published: March 2023

Background: The study investigated the long-term efficacy of imiquimod 5% cream for LM, with a focus on disease recurrence and the possible prognostic factors of disease-free survival (DFS) in a cohort, with long-term follow-up. Methods: Consecutive patients with histologically confirmed LM were included. Imiquimod 5% cream was applied until weeping erosion appeared on the LM-affected skin. The evaluation was performed through clinical examination and dermoscopy. Results: We analyzed 111 patients with LM (median age: 72 years, 61.3% women) with tumor clearance after imiquimod therapy, with a median follow-up of 8 years. The overall patient survival rates were 85.5% (95% confidence interval (CI): 78.5–92.6) and 70.4% (95% CI: 60.3–80.5) at 5 and 10 years, respectively. Among the 23 patients (20.1%) with relapse at follow-up, 17 (73.9%) were treated with surgery, five (21.7%) continued imiquimod therapy, and one (4.3%) underwent both surgery and radiotherapy. After adjustment for age and LM area in multivariable models, localization of LM in the nasal region was identified as a prognostic factor for DFS (HR = 2.66; 95% CI: 1.06–6.64). Conclusion: If surgical excision is not possible due to the patients’ age/comorbidities or critical cosmetic localization, imiquimod could provide optimal outcomes with an optimal risk of relapse for the management of LM.
Molten Salt-Assisted Catalytic Preparation of MoS2/α-MoO3/Graphene as High-Performance Anode of Li-Ion Battery
Authors: Zhu Wenhui , Kamali Ali Reza
Published: March 2023

We report on the facile and scalable catalytic conversion of natural graphite and MoS2 minerals into α-MoO3 nanoribbons incorporated into hexagonal MoS2 and graphene nanosheets, and evaluate the structural, morphological and electrochemical performances of the hybrid nanostructured material obtained. Mechanochemical treatment of raw materials, followed by catalytic molten salt treatment leads to the formation of nanostructures with promising electrochemical performances. We examined the effect of processing temperature on the electrochemical performance of the products. At 1100 °C, an excellent Li-ion storage capacity of 773.5 mAh g−1 is obtained after 180 cycles, considerably greater than that of MoS2 (176.8 mAh g−1). The enhanced capacity and the rate performance of this electrode are attributed to the well-integrated components, characterized by the formation of interfacial molybdenum oxycarbide layer during the synthesis process, contributing to the reduced electrical/electrochemical resistance of the sample. This unique morphology promotes the charge and ions transfer through the reduction of the Li-ion diffusion coefficient (1.2 × 10−18 cm2 s−1), enhancing the pseudocapacitive performance of the electrode; 59.3% at the scan rate of 0.5 mV s−1. This article provides a green and low-cost route to convert highly available natural graphite and MoS2 minerals into nanostructured hybrid materials with promising Li-ion storage performance.
Green Synthesis and Photocatalytic Dye Degradation Activity of CuO Nanoparticles
Authors: Aroob Sadia , Carabineiro Sónia A. C. , Taj Muhammad Babar , Bibi Ismat , Raheel Ahmad , Javed Tariq , Yahya Rana , Alelwani Walla , Verpoort Francis , Kamwilaisak Khanita , Al-Farraj Saleh , Sillanpää Mika
Published: March 2023

The degradation of dyes is a difficult task due to their persistent and stable nature; therefore, developing materials with desirable properties to degrade dyes is an important area of research. In the present study, we propose a simple, one-pot mechanochemical approach to synthesize CuO nanoparticles (NPs) using the leaf extract of Seriphidium oliverianum, as a reducing and stabilizing agent. The CuO NPs were characterized via X-ray diffraction (XRD), scanning electron microscopy (SEM), photoluminescence (PL) and Fourier-transform infrared spectroscopy (FTIR). The photocatalytic activity of CuO NPs was monitored using ultraviolet-visible (UV-Vis) spectroscopy. The CuO NPs exhibited high potential for the degradation of water-soluble industrial dyes. The degradation rates for methyl green (MG) and methyl orange (MO) were 65.231% ± 0.242 and 65.078% ± 0.392, respectively. Bio-mechanochemically synthesized CuO NPs proved to be good candidates for efficiently removing dyes from water.
Optimizing Al and Fe Load during HTC of Water Hyacinth: Improvement of Induced HC Physicochemical Properties
Authors: Olivares-Marin Mara , Román Silvia , Ledesma Beatriz , Álvarez Alfredo
Published: March 2023

Nowadays, several alternatives have been proposed to increase the porosity and/or modify the surface groups of hydrochars from biomasses as well as to develop additional features on them. These alternatives can include specific modifications for the process, as previous steps or as postreatments, and the wide variety of forms in which they can be made can substantially affect the product distribution and properties. In this study, the hydrothermal carbonization process of an invasive floating plant (Water hyacinth) has been modified by introducing different amounts of iron (FeCl3) and aluminium alloy (shaving scrap waste) during the hydrothermal reaction. The effects on process reactivity, phase distribution, and physicochemical properties of the samples obtained were studied by means of different characterization techniques such as thermogravimetry (TG-DTG), physical adsorption/desorption of N2 at −196 °C, FT-IR spectroscopy, and scanning electron microscopy (SEM). In the case of iron-catalyzed reactions, the magnetite formation and magnetic behavior of the prepared hydrochars after a pyrolytic treatment was also estimated. The results obtained indicate that the porosity of the hydrochars was clearly improved to different extents by the addition of Al or Fe during direct synthesis. In addition, porous carbons with a moderate magnetic character were obtained.
A Rapid Method for Detection of Antigen-Specific B Cells
Authors: Vakhitova Mariia , Myshkin Mikhail , Staroverov Dmitriy , Shagina Irina , Izraelson Mark , Tverdova Nadezhda , Britanova Olga , Merzlyak Ekaterina
Published: March 2023

The global SARS-CoV-2 pandemic has united the efforts of many scientists all over the world to develop wet-lab techniques and computational approaches aimed at the identification of antigen-specific T and B cells. The latter provide specific humoral immunity that is essential for the survival of COVID-19 patients, and vaccine development has essentially been based on these cells. Here, we implemented an approach that integrates the sorting of antigen-specific B cells and B-cell receptor mRNA sequencing (BCR-seq), followed by computational analysis. This rapid and cost-efficient method allowed us to identify antigen-specific B cells in the peripheral blood of patients with severe COVID-19 disease. Subsequently, specific BCRs were extracted, cloned, and produced as full antibodies. We confirmed their reactivity toward the spike RBD domain. Such an approach can be effective for the monitoring and identification of B cells participating in an individual immune response.
Potential Role of Low-Molecular-Weight Dioxolanes as Adjuvants for Glyphosate-Based Herbicides Using Photosystem II as an Early Post-Treatment Determinant
Authors: Szwajczak Ewa , Sierka Edyta , Ludynia Michał
Published: March 2023

Pesticide use cannot be completely abandoned in modern agriculture. Among agrochemicals, glyphosate is one of the most popular and, at the same time, most divisive herbicide. Since the chemicalization of agriculture is detrimental, various attempts are being made to reduce it. Adjuvants—substances that increase the efficiency of foliar application—can be used to reduce the amount of herbicides used. We propose low-molecular-weight dioxolanes as adjuvants for herbicides. These compounds quickly convert to carbon dioxide and water and do not harm plants. The aim of this study was to evaluate the efficacy of RoundUp® 360 Plus supported by three potential adjuvants: 2,2-dimethyl-1,3-dioxolane (DMD), 2,2,4-trimethyl-1,3-dioxolane (TMD), and (2,2-dimethyl-1,3-dioxan-4-yl)methanol (DDM), on a common weed species Chenopodium album L., under greenhouse conditions. Chlorophyll a fluorescence parameters and analysis of the polyphasic fluorescence (OJIP) curve, which examines changes in the photochemical efficiency of photosystem II, were used to measure plant sensitivity to glyphosate stress and verified the efficacy achieved by tested formulations. The effective dose (ED) values obtained showed that the weed tested was sensitive to reduced doses of glyphosate, with 720 mg/L needed to achieve 100% effectiveness. Compared to the glyphosate assisted with DMD, TMD, and DDM, ED was reduced by 40%, 50%, and 40%, respectively. The application of all dioxolanes at a concentration equal to 1 vol.% significantly enhanced the herbicide’s effect. Our study showed that for C. album there was a correlation between the change in OJIP curve kinetics and the applied dose of glyphosate. By analyzing the discrepancies in the curves, it is possible to show the effect of different herbicide formulations with or without dioxolanes at an early stage of its action, thus minimizing the time for testing new substances as adjuvants.
Rho GTPases in Model Systems
Authors: Filić Vedrana , Weber Igor
Published: March 2023

Since the discovery of their role in the regulation of actin cytoskeleton 30 years ago, Rho GTPases have taken center stage in cell motility research [...]
A Strategy for Differentiating Oak Barrel Aged and Non-Oak Barrel Aged Wines by Using UHPLC–HRMS Combined with Chemometrics
Authors: Lv Yi , Ma Feng-Lian , Wang Jia-Nan , Zhang Yao , Jiang Yuan , Ge Qian , Yu Yong-Jie
Published: March 2023

The time involved and the high economic cost of using oak barrels to age wines have led to a significant price difference compared to non-oak barrel aged wines and may lead to some fraudulent sales in the market. In this study, an untargeted metabolomic strategy was developed to detect the metabolite composition of oak barrel aged and non-oak barrel aged wines in both positive and negative ion modes by using UHPLC–HRMS combined with the recently developed chemometric method AntDAS. The results of partial least squares discrimination analysis (PLS-DA) showed that the samples were characterized into two categories. Finally, 51 compounds were identified in positive ion mode, while 26 compounds were identified in negative ion mode. The results indicate that combining UHPLC–HRMS with AntDAS can reveal the material basis of wines and has excellent potential to differentiate between oak barrel aged and non-oak barrel aged wines.
Physical Activity and Sedentary Behavior in High School Students: A Quasi Experimental Study via Smartphone during the COVID-19 Pandemic
Authors: Ferreira Silva Regina Márcia , Fonseca Terra Lauryane , da Silva Valadão Fernandes Michele , Noll Priscilla Rayanne E. Silva , de Almeida Alexandre Aparecido , Noll Matias
Published: March 2023

The objective of this study was to evaluate whether exposure to information about physical activity and its barriers can increase the level of physical activity and reduce the time exposed to sedentary behaviors in high school students involved in integrated professional and technological education during the coronavirus disease 2019 pandemic. This quasi experimental study was conducted with integrated education high school students, divided into two groups: Intervention Group (IG; n = 59) and Control Group (CG; n = 54). Physical activity and sedentary behavior were identified and measured using the International Physical Activity Questionnaire pre-and post-intervention for both groups. IG students received educational material thrice a week for four weeks. The focus of the material was the importance of physical activity and need to reduce the time exposed to sedentary behavior. The results revealed that IG students showed an average daily reduction of 47.14 min in time exposed to sedentary behaviors, while the CG students showed an increase of 31.37 min. Despite this, the intervention was not effective in improving physical activity levels in the IG and the mean reduction in the time exposed to sedentary behavior was not significant (p = 0.556). The intervention was ineffective in increasing the practice of physical activity and reducing the time exposed to sedentary behavior.
Components of Perinatal Palliative Care: An Integrative Review
Authors: Dombrecht Laure , Chambaere Kenneth , Beernaert Kim , Roets Ellen , De Vilder De Keyser Mona , De Smet Gaëlle , Roelens Kristien , Cools Filip
Published: March 2023

When a severe diagnosis is made before or after birth, perinatal palliative care (PPC) can be provided to support the infant, parents and involved healthcare providers. An integrative and systematic overview of effectiveness and working components of existing PPC programs was needed. An integrative search was conducted in MEDLINE, Embase, CENTRAL, CINAHL, PsycInfo and Web of Science. Study designs examining the effect of PPC compared to regular care, and (empirical) articles describing the components of care included in existing PPC initiatives were included. Three independent authors reviewed titles, abstracts and full texts against eligibility criteria. PRISMA guidelines were followed; 21.893 records were identified; 69 publications met inclusion criteria. Twelve publications (17.4%) discussed the effect of a PPC program. Other publications concerned the description of PPC programs, most often by means of a program description (22/69; 31.9%), guidelines (14/769; 20.3%) or case study (10/69; 14.5%). Outcome measures envisioned four main target categories: care coordination, parents and family members, care for the fetus/neonate and healthcare providers. No trials exist to date. Analysis of working components revealed components related to changes directed to the policy of the hospital wards and components involving actual care being provided within the PPC program, directed to the fetus or infant, the family, involved healthcare providers or external actors. PPC is a growing research field where evidence consists mainly of descriptive studies and guidelines. The extensive list of possible PPC components can serve as a checklist for developing future initiatives worldwide. PPC includes several important actors: the fetus/infant and their family and included healthcare providers on both maternity and neonatal wards. This leads to a large variety of possible care components. However, while some studies show proof of concept, an evidence base to determine which components are actually effective is lacking.
Design-Based Approach to Support Sorting Behavior of Food Packaging
Authors: Nemat Babak , Razzaghi Mohammad , Bolton Kim , Rousta Kamran
Published: March 2023

It is widely acknowledged that environmental impacts from packaging waste depend on how consumers sort this waste fraction. In this research, “design for sustainable behavior” (DfSB) strategies are used to improve a cream packaging design that can support proper sorting of packaging waste as a sustainable behavior. The application of three DfSB strategies—“match”, “steer”, and “force”—was examined through circular interviews and practical experience with two groups of participants in Karlskrona, Sweden. Prototyping was used to provide a more realistic experiment and enhance communication during the interviews. The results show that consumer-packaging interaction during the usage phase is important to enhance proper sorting behavior. The results also show the potential of a user-centered design-based approach to study consumer-packaging interaction and to understand the challenges faced by users when sorting packaging waste. It also shows the possibility of packaging design to script consumer behavior and reveals details that are important when designing packaging that was not known. In this vein, packaging form, color, and haptic attributes are the most influential design attributes that can support packaging functionalities and script consumer sorting behavior.
Recent Advances in Surface Functionalisation
Authors: Salguero Jorge , Vazquez Juan Manuel , Batista Moises , del Sol Irene
Published: March 2023

Surfaces and interfaces have become a highly relevant topic in recent years, mainly due to their technological importance in the design and development of high-performance components [...]
High Absorptivity and Ultra-Wideband Solar Absorber Based on Ti-Al2O3 Cross Elliptical Disk Arrays
Authors: Zhang Yuanjian , Yi Yingting , Li Wenxin , Liang Shiri , Ma Jing , Cheng Shubo , Yang Wenxing , Yi Yougen
Published: March 2023

Perfect metamaterial absorbers have attracted researchers’ attention in solar energy harvesting and utilization. An ideal solar absorber should provide high absorption, be ultra-wideband, and be insensitive to polarization and incident angles, which brings challenges to research. In this paper, we proposed and optimized an ultra-wideband solar absorber based on Ti-Al2O3 cross elliptical disk arrays to obtain the ultra-wideband absorption of solar energy. The addition of a cavity greatly improves the energy-absorbing effect in the operating band, which has research value. The absorption spectrum and field distribution were analyzed by the finite difference time domain method. For the physical mechanism, the electric and magnetic field distribution indicates that ultra-wideband absorption is caused by propagation surface plasmon resonance (SPR), localized SPR and Fabry–Perot (F-P) resonance excited between Ti and Al2O3 disks. The results demonstrate that the absorption bandwidth with the absorption rate beyond 90% reaches 1380 nm (385–1765 nm), and the average absorption reaches an astonishing 98.78%. The absorption bandwidth matches the main radiation bandwidth of the solar energy, which is approximately 295–2500 nm according to the data from the literature, and the total thickness of the structure is only 445 nm. Moreover, the ultra-wideband solar absorber is insensitive to the polarization angle and oblique incidence angle. The proposed ultra-wideband solar absorber has research and application value in solar energy harvesting, photothermal conversion and utilization.
Experimental Study on the Impermeability and Micromechanisms of Basalt Fiber-Reinforced Soil-Cement in Marine Environments
Authors: Li Zhiyuan , Chen Feng , Ren Jianhua , Chen Zhibo
Published: March 2023

In coastal areas, structures such as cement-soil dams are often eroded by seawater, so it is significant to study how to improve the impermeability of cement-soil. Basalt fiber with a strong tensile property, good stability and a high-performance price ratio was selected as the additive to study the influence of the basalt fiber content on the permeability of soil-cement. The permeability test and the chloride ion permeability test were used to evaluate the best mixing amount. The results of the permeability test showed that, although the permeability coefficient of soil-cement decreased with the increase in the basalt fiber content, the decreased rate of the permeability coefficient showed a slowing trend. The results of the chloride ion permeability test indicated that the chloride ion-related impermeability of soil-cement was enhanced with the increase in the basalt content, which was confirmed by the consistent findings of the contrast permeability test. The comprehensive analysis shows that the optimal content ratio of the basalt fiber was 1.5%. Furthermore, a SEM analysis established that the addition of the basalt fiber reduced the soil-cement porosity, improved the structural compactness and formed a more stable whole. This study could serve as a valuable reference for soil-cement used in projects with impermeability requirements.
Enhanced Energy Storage Performance of AgNbO3:xCeO2 by Synergistic Strategies of Tolerance Factor and Density Regulations
Authors: An Ke , Li Gang , Fan Tingting , Huang Feng , Wang Wenlin , Wang Jing
Published: March 2023

AgNbO3-based ceramics have been widely studied as ideal lead-free materials. Herein, AgNbO3:xCeO2 (x = 0, 1, 2 mol%) ceramics were successfully prepared by the conventional solid-state reaction method. The optimization of energy storage properties is ascribed to the enhanced antiferroelectric (AFE) stability and the increased breakdown strength (Eb). The reduction of the tolerance factor leads to the enhancement of AFE stability. In addition, the enhancement of Eb is due to the increase of actual density, which is achieved through the regulation of CeO2 amount and grinding procedure in the experimental process. A high recoverable energy density (Wrec) of 5.04 J/cm3 and an energy efficiency (η) of 46.2% were achieved in AgNbO3:0.01CeO2 ceramics under an applied electric field up to 390 kV/cm. A higher η of 55.4% was obtained in AgNbO3:0.02CeO2 components. This research provides guidance for finding ceramic materials with comprehensive energy storage properties.
Crack Detection in an Aluminium Oxide Grinding Wheel by Impact Hammer Tests
Authors: Lee Yubin , Turcic David , Danks Dan , Wern Chien
Published: March 2023

Grinding is widely used as the last step of the manufacturing process when a good surface finish and precise dimensional tolerances are required. However, if the grinding wheels have cracks, they may lead to a hazardous working environment and produce poor tolerance in machined products. Therefore, grinding wheels should be inspected for cracks before being mounted onto the machine. In this study, a novel method of finding possible internal cracks in the aluminium oxide grinding wheel will be explored by examining the natural frequency and displacement of wheels using an impact hammer testing method. Grinding wheels were cracked into two segments using a three-point bend fixture and then bonded intentionally to simulate cracks. The impact hammer test indicated that cracks in the grinding wheels caused a drop in natural vibration frequency and an increase in the maximum displacement of the accelerometer sensors.
Problem Solving and Budget Allocation of SMEs: Application of NCA Approach
Authors: Bouzari Parisa , Gyenge Balázs , Ebrahimi Pejman , Fekete-Farkas Mária
Published: March 2023

In order to achieve a specific result, a firm’s problem-solving activities can be thought of as a process that combines physical and cognitive actions. Its internal organization determines how information inputs are distributed among different task units and, as a result, how the cognitive workload is distributed. We tested a case study related to Iranian small and medium enterprises (SMEs). We used NCA analysis as a creative and state-of-the-art method with the help of R software to evaluate data. According to the findings, six prerequisites must be met in order to achieve a 50% level of efficient performance: innovation at a minimum of 22.7%, CSR at a minimum of 30.4%, IT investment at a minimum of 56.7%, SMM at a minimum of 38.3%, product differentiation at a minimum of 11.7%, and CRM at a minimum of 38.3%.
Unified Convergence Criteria of Derivative-Free Iterative Methods for Solving Nonlinear Equations
Authors: Regmi Samundra , Argyros Ioannis K. , Shakhno Stepan , Yarmola Halyna
Published: March 2023

A local and semi-local convergence is developed of a class of iterative methods without derivatives for solving nonlinear Banach space valued operator equations under the classical Lipschitz conditions for first-order divided differences. Special cases of this method are well-known iterative algorithms, in particular, the Secant, Kurchatov, and Steffensen methods as well as the Newton method. For the semi-local convergence analysis, we use a technique of recurrent functions and majorizing scalar sequences. First, the convergence of the scalar sequence is proved and its limit is determined. It is then shown that the sequence obtained by the proposed method is bounded by this scalar sequence. In the local convergence analysis, a computable radius of convergence is determined. Finally, the results of the numerical experiments are given that confirm obtained theoretical estimates.
Automated Detection and Classification of Oral Squamous Cell Carcinoma Using Deep Neural Networks
Authors: Ananthakrishnan Balasundaram , Shaik Ayesha , Kumar Soham , Narendran S. O. , Mattu Khushi , Kavitha Muthu Subash
Published: March 2023

This work aims to classify normal and carcinogenic cells in the oral cavity using two different approaches with an eye towards achieving high accuracy. The first approach extracts local binary patterns and metrics derived from a histogram from the dataset and is fed to several machine-learning models. The second approach uses a combination of neural networks as a backbone feature extractor and a random forest for classification. The results show that information can be learnt effectively from limited training images using these approaches. Some approaches use deep learning algorithms to generate a bounding box that can locate the suspected lesion. Other approaches use handcrafted textural feature extraction techniques and feed the resultant feature vectors to a classification model. The proposed method will extract the features pertaining to the images using pre-trained convolution neural networks (CNN) and train a classification model using the resulting feature vectors. By using the extracted features from a pre-trained CNN model to train a random forest, the problem of requiring a large amount of data to train deep learning models is bypassed. The study selected a dataset consisting of 1224 images, which were divided into two sets with varying resolutions.The performance of the model is calculated based on accuracy, specificity, sensitivity, and the area under curve (AUC). The proposed work is able to produce a highest test accuracy of 96.94% and an AUC of 0.976 using 696 images of 400× magnification and a highest test accuracy of 99.65% and an AUC of 0.9983 using only 528 images of 100× magnification images.
CBCT Images to an STL Model: Exploring the “Critical Factors” to Binarization Thresholds in STL Data Creation
Authors: Kamio Takashi , Kawai Taisuke
Published: March 2023

In-house fabrication of three-dimensional (3D) models for medical use has become easier in recent years. Cone beam computed tomography (CBCT) images are increasingly used as source data for fabricating osseous 3D models. The creation of a 3D CAD model begins with the segmentation of hard and soft tissues of the DICOM images and the creation of an STL model; however, it can be difficult to determine the binarization threshold in CBCT images. In this study, how the different CBCT scanning and imaging conditions of two different CBCT scanners affect the determination of the binarization threshold was evaluated. The key to efficient STL creation through voxel intensity distribution analysis was then explored. It was found that determination of the binarization threshold is easy for image datasets with a large number of voxels, sharp peak shapes, and narrow intensity distributions. Although the intensity distribution of voxels varied greatly among the image datasets, it was difficult to find correlations between different X-ray tube currents or image reconstruction filters that explained the differences. The objective observation of voxel intensity distribution may contribute to the determination of the binarization threshold for 3D model creation.
Diagnostic Algorithm Based on Machine Learning to Predict Complicated Appendicitis in Children Using CT, Laboratory, and Clinical Features
Authors: Byun Jieun , Park Seongkeun , Hwang Sook Min
Published: March 2023

To establish a diagnostic algorithm for predicting complicated appendicitis in children based on CT and clinical features. Methods: This retrospective study included 315 children (<18 years old) who were diagnosed with acute appendicitis and underwent appendectomy between January 2014 and December 2018. A decision tree algorithm was used to identify important features associated with the condition and to develop a diagnostic algorithm for predicting complicated appendicitis, including CT and clinical findings in the development cohort (n = 198). Complicated appendicitis was defined as gangrenous or perforated appendicitis. The diagnostic algorithm was validated using a temporal cohort (n = 117). The sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC) from the receiver operating characteristic curve analysis were calculated to evaluate the diagnostic performance of the algorithm. Results: All patients with periappendiceal abscesses, periappendiceal inflammatory masses, and free air on CT were diagnosed with complicated appendicitis. In addition, intraluminal air, transverse diameter of the appendix, and ascites were identified as important CT findings for predicting complicated appendicitis. C-reactive protein (CRP) level, white blood cell (WBC) count, erythrocyte sedimentation rate (ESR), and body temperature also showed important associations with complicated appendicitis. The AUC, sensitivity, and specificity of the diagnostic algorithm comprising features were 0.91 (95% CI, 0.86–0.95), 91.8% (84.5–96.4), and 90.0% (82.4–95.1) in the development cohort, and 0.7 (0.63–0.84), 85.9% (75.0–93.4), and 58.5% (44.1–71.9) in test cohort, respectively. Conclusion: We propose a diagnostic algorithm based on a decision tree model using CT and clinical findings. This algorithm can be used to differentiate between complicated and noncomplicated appendicitis and to provide an appropriate treatment plan for children with acute appendicitis.
Integration of Interdomain Flow-Rule in Software-Defined Networks for Embedded Internet of Things Devices
Authors: Afridi Sabih Khan , Iqbal Saleem , Qureshi Kashif Naseer , Majeed Saqib , Jeon Gwanggil
Published: March 2023

Software-defined networking (SDN) is an evolving technology providing proper segregation between the control part and data-forwarding domain of network devices. The expansion of the Internet of Things (IoTs) and embedded mobile devices increases the volume of traffic at the network backbone and causes processing costs in the control plane. This directly affects the Ternary Content Addressable Memory (TCAM) of the switches because insufficient space makes it more challenging to manage the flow-entries. In this situation, providing services to specific users who newly authenticate after the successful handoff from the previous SDN domain is challenging. This paper proposes a method for implanting the users’ primary domain’s flow-rules in the serving SDN domain. As the TCAM is already suffering from a short space, it is hard to handle the flow-tables of multiple SDN domains in limited TCAM storage. The SDN-based Integration of the Interdomain Flow-rule in the SDN (IIF-SDN) scheme maximizes the proficiency of the switches by effectively storing flow-table and flow-entries. The effectiveness of the proposed scheme is benchmarked with proactive and reactive SDN approaches.
ITSS: An Intelligent Traffic Signaling System Based on an IoT Infrastructure
Authors: Rai Satyananda Champati , Nayak Samaleswari Pr , Acharya Biswaranjan , Gerogiannis Vassilis C. , Kanavos Andreas , Panagiotakopoulos Theodor
Published: March 2023

Recently, there has been a huge spike in the number of automobiles in the urban areas of many countries, particularly in India. The number of vehicles are increasing rapidly and with the existing infrastructure, the traffic systems stand still during peak hours. Some of the main challenges for traffic management are the movement of overloaded vehicles beyond their restricted zone and time, reckless driving, and overlooking road safety rules. This paper proposes an Internet of Things (IoT)-based real-time Intelligent Traffic Signal System (ITSS), which consists of inductive loops and a programmable micro-controller to determine traffic density. Inter-communication in the centralized control unit sets the timer of the traffic light and synchronizes with the traffic density in real-time for smooth mobility of vehicles with less delay. Additionally, to prioritize emergency vehicles over other vehicles in the same lane, a pre-emption mechanism has been integrated through infrared sensors. The result of traffic density determines the timer of the light post in real-time, which in result enhances the smooth flow of vehicles with reduced delay for travelers. Using its automatic on-demand traffic signaling system, the presented solution has advantages over fixed systems.
Efficient Reachability Ratio Computation for 2-Hop Labeling Scheme
Authors: Tang Xian , Zhou Junfeng , Shi Yunyu , Liu Xiang , Kong Lihong
Published: March 2023

Reachability queries processing has been extensively studied during the past decades. Many approaches have followed the line of designing 2-hop labels to ensure acceleration. Considering its index size cannot be bounded, researchers have proposed to use a part of nodes to construct partial 2-hop labels (p2HLs) to cover as much reachability information as possible. We achieved better query performance using p2HLs with a limited index size and index construction time. However, the adoption of p2HLs was based on intuition, and the number of nodes used to generate p2HLs was fixed in advance blindly, without knowing its applicability. In this paper, we focused on the problem of efficiently computing a reachability ratio (RR) in order to obtain RR-aware p2HLs. Here, RR denoted the ratio of the number of reachable queries that could be answered by p2HLs over the total number of reachable queries involved in a given graph. Based on the RR, users could determine whether p2HLs should be used to answer the reachability queries for a given graph and how many nodes should be chosen to generate p2HLs. We discussed the difficulties of RR computation and propose an incremental-partition algorithm for RR computation. Our rich experimental results showed that our algorithm could efficiently obtain the RR and the overall effects on query performance by different p2HLs. Based on the experimental results, we provide our findings on the use p2HLs for a given graph for processing reachability queries.
Material-Aware Path Aggregation Network and Shape Decoupled SIoU for X-ray Contraband Detection
Authors: Xiang Nan , Gong Zehao , Xu Yi , Xiong Lili
Published: March 2023

X-ray contraband detection plays an important role in the field of public safety. To solve the multi-scale and obscuration problem in X-ray contraband detection, we propose a material-aware path aggregation network to detect and classify contraband in X-ray baggage images. Based on YoloX, our network integrates two new modules: multi-scale smoothed atrous convolution (SCA) and material-aware coordinate attention modules (MCA). In SAC, an improved receptive field-enhanced network structure is proposed by combining smoothed atrous convolution, using separate shared convolution, with a parallel branching structure, which allows for the acquisition of multi-scale receptive fields while reducing grid effects. In the MCA, we incorporate a spatial coordinate separation material perception module with a coordinated attention mechanism. A material perception module can extract the material information features in X and Y dimensions, respectively, which alleviates the obscuring problem by focusing on the distinctive material characteristics. Finally, we design the shape-decoupled SIoU loss function (SD-SIoU) for the shape characteristics of the X-ray contraband. The category decoupling module and the long–short side decoupling module are integrated to the shape loss. It can effectively balance the effect of the long–short side. We evaluate our approach on the public X-ray contraband SIXray and OPIXray datasets, and the results show that our approach is competitive with other X-ray baggage inspection approaches.
HRFP: Highly Relevant Frequent Patterns-Based Prefetching and Caching Algorithms for Distributed File Systems
Authors: Nalajala Anusha , Ragunathan T. , Naha Ranesh , Battula Sudheer Kumar
Published: March 2023

Data-intensive applications are generating massive amounts of data which is stored on cloud computing platforms where distributed file systems are utilized for storage at the back end. Most users of those applications deployed on cloud computing systems read data more often than they write. Hence, enhancing the performance of read operations is an important research issue. Prefetching and caching are used as important techniques in the context of distributed file systems to improve the performance of read operations. In this research, we introduced a novel highly relevant frequent patterns (HRFP)-based algorithm that prefetches content from the distributed file system environment and stores it in the client-side caches that are present in the same environment. We have also introduced a new replacement policy and an efficient migration technique for moving the patterns from the main memory caches to the caches present in the solid-state devices based on a new metric namely the relevancy of the patterns. According to the simulation results, the proposed approach outperformed other algorithms that have been suggested in the literature by a minimum of 15% and a maximum of 53%.
A Novel Word Line Driver Circuit for Compute-in-Memory Based on the Floating Gate Devices
Authors: Gu Xiaofeng , Che Rao , Dong Yating , Yu Zhiguo
Published: March 2023

In floating gate compute-in-memory (CIM) chips, due to the gate equivalent capacitance of the large-scale array and the parasitic capacitance of the long-distance transmission wire, it is difficult to balance the switching speed and area of the word line driver circuit (WLDC). The difference among multiple voltage domains required for floating gate CIM devices has also far exceeded the withstand voltage range of a single transistor in the WLDC. This paper proposes a novel WLDC based on the working principle of the CIM array. A multi-level pre-processing voltage control method is adopted to carry out an optional hierarchical transmission of multiple high voltages, significantly reducing the propagation delay. The proposed WLDC is based on the Wilson current mirror structure, which substantially reduces the physical design area. The simulation results show that the circuit can convert a 1.2 V low-voltage domain input signal with a frequency of 10 MHz into a high-voltage domain output voltage, and the output voltage range of a single WLDC can reach −10 V to 10 V. With a capacitive load within 5 pF, the transmission delay is less than 10 ns. The layout area is 594.88 µm2, which is suitable for a large-scale CIM array.
Transcriptome Analysis of Biochemistry Responses to Low-Temperature Stress in the Flower Organs of Five Pear Varieties
Authors: Lin Shun , Li Yongtan , Zhao Jingxian , Guo Weizhen , Jiang Min , Li Xinman , Liu Weiping , Zhang Jun , Yang Minsheng
Published: March 2023

Using floral organs of five pear cultivars as materials, this study determined and compared physiological indices such as relative conductivity, superoxide dismutase (SOD), and malondialdehyde (MDA) of each cultivar’s floral organs under different low-temperature stress treatments, and evaluated the cold resistance of the five pear cultivars. Transcriptome sequencing analysis was performed on the floral organs of a new early-ripening pear cultivar called “Jinguang”, and 259 differentially expressed genes (DEGs) were identified, which were mainly enriched in pathways related to circadian rhythm and flavonoid biosynthesis. Weighted gene co-expression network analysis (WGCNA) showed that specific gene modules were significantly associated with MDA and soluble protein. Key enzymes such as NPC1(non-specific PLC, NPC), transcription factor MYB102, BBX19, and LHY (Late elongated hypocotyl) genes were located at the core of the constructed network, and may have important potential roles under low-temperature stress.
Lignocellulosic Biorefinery Technologies: A Perception into Recent Advances in Biomass Fractionation, Biorefineries, Economic Hurdles and Market Outlook
Authors: K.N Yogalakshmi , T.M Mohamed Usman , S Kavitha , Sachdeva Saloni , Thakur Shivani , S Adish Kumar , J Rajesh Banu
Published: March 2023

Lignocellulosic biomasses (LCB) are sustainable and abundantly available feedstocks for the production of biofuel and biochemicals via suitable bioconversion processing. The main aim of this review is to focus on strategies needed for the progression of viable lignocellulosic biomass-based biorefineries (integrated approaches) to generate biofuels and biochemicals. Processing biomass in a sustainable manner is a major challenge that demands the accomplishment of basic requirements relating to cost effectiveness and environmental sustainability. The challenges associated with biomass availability and the bioconversion process have been explained in detail in this review. Limitations associated with biomass structural composition can obstruct the feasibility of biofuel production, especially in mono-process approaches. In such cases, biorefinery approaches and integrated systems certainly lead to improved biofuel conversion. This review paper provides a summary of mono and integrated approaches, their limitations and advantages in LCB bioconversion to biofuel and biochemicals.
Synthesis of Cationic Quaternized Nanolevan Derivative for Small Molecule and Nucleic Acid Delivery
Authors: Charoenwongphaibun Chonnipha , Lorthongpanich Chanchao , Septham Prapasri , Wangpaiboon Karan , Panpetch Pawinee , Pichyangkura Rath , Charoenwongpaiboon Thanapon , Kuttiyawong Kamontip
Published: March 2023

Levan is a biopolymer composed of fructose chains covalently linked by β−2,6 glycosidic linkages. This polymer self−assembles into a nanoparticle of uniform size, making it useful for a wide range of applications. Also, levan exhibits various biological activities such as antioxidants, anti-inflammatory, and anti-tumor, that make this polymer very attractive for biomedical application. In this study, levan synthesized from Erwinia tasmaniensis was chemically modified by glycidyl trimethylammonium chloride (GTMAC) to produce cationized nanolevan (QA-levan). The structure of the obtained GTMAC−modified levan was determined by FT-IR, 1H-NMR and elemental (CHN) analyzer. The size of the nanoparticle was calculated using the dynamic light scattering method (DLS). The formation of DNA/QA-levan polyplex was then investigated by gel electrophoresis. The modified levan was able to increase the solubility of quercetin and curcumin by 11-folds and 205-folds, respectively, compared to free compounds. Cytotoxicity of levan and QA−levan was also investigated in HEK293 cells. This finding suggests that GTMAC−modified levan should have a potential application for drug and nucleic acid delivery.