bluuebunny/crossref_metadata_2025 huggingface dataset:
Prevalence, Determinants, and Consumer Stance towards Dietary Supplements According to Sex in a Large Greek Sample: A Cross-Sectional Study
Authors: Soukiasian Panagiotis-David , Kyrana Zacharenia , Gerothanasi Konstantina , Kiranas Efstratios , Kokokiris Lambros E.
Published: December 2022

A stratified random sampling technique was used in order to explore the prevalence of and the factors influencing dietary supplement (DS) use and the consumer stance towards DS by Greeks (n = 28,491, ≥15 years) according to sex. Additionally, we performed a Pearson’s chi-square to test within DS users for the dependence between sex and the examined factors, and binary logistic regression to create predictive DS user profiles. A history of DS use accounted for 55.5% and was more prevalent in women (58.4% vs. 52.3%, p < 0.001); multivitamins were the most popular DS used. The significant predictors for DS use for both sexes were age, education, employment status, exercise, and following a special diet, while BMI and monthly income were significant for women and men, respectively. The women and men DS users had mostly illness-health and fitness-related goals, respectively. Substantial proportions of the respondents had false beliefs about DS. A noticeable percentage of DS users displayed imprudent behavior regarding DS use, e.g., one out of five did not know the definition or did not take into consideration the recommended daily allowance. While several factors seemed to impact DS use, with certain differences between the sexes, the considerable lack of knowledgeable and responsible use of DS, with few differences between the sexes, observed can point state authorities and health professionals towards appropriate countermeasures.
Primary Healthcare Nurses’ Views on Digital Healthcare Communication and Continuity of Care: A Deductive and Inductive Content Analysis
Authors: Hellzén Ove , Kjällman Alm Annika , Holmström Rising Malin
Published: December 2022

Primary healthcare in the Western world faces significant functional challenges, resulting in the implementation of digital communication tools. Nurses are key professionals in primary care and focusing on the impact of digital communication and continuity of care in primary care organisations is important. This qualitative descriptive study explores digital communication and continuity of care from primary healthcare nurses’ perspective. Data from individual semi-structured interviews with 12 nurses were collected; deductive and inductive content analyses were performed. Three descriptive categories emerged from the deductive (digital communication as interpersonal, information, and management continuities) and inductive (‘digital care does not suit everyone’, ‘new technology is contextually intertwined with daily work’, and ‘patient-positive aspects of digital information’) phases. Additionally, a structural risk of obscuration of patients’ needs by the contextual conditions emerged. To ensure digital communication-aligned continuity of care, compatible information technology systems should be developed. Allowing nurses to provide high-quality care based on their own values would enhance person-centred patient care.
Tracing the Genetic Evolution of Canine Parvovirus Type 2 (CPV-2) in Thailand
Authors: Jantafong Tippawan , Ruenphet Sakchai , Garner Harold R. , Ritthipichai Krit
Published: December 2022

Canine parvovirus type 2 (CPV-2) is responsible for hemorrhagic gastroenteritis in dogs worldwide. High genomic substitution rates in CPV-2 contribute to the progressive emergence of novel variants with increased ability to evade the host immune response. Three studies have analyzed the genomic mutations of CPV-2 variants in Thailand. These investigations were independently conducted at different timepoints. Thus, a retrospective integrated analysis of CPV-2 genomic mutations has not been fully performed. Our study aimed at evaluating the evolutionary changes in CPV-2 in Thailand from 2003 to 2019. Two hundred and sixty-eight Thai CPV-2 nucleotide sequences were used for multiple amino acid sequence alignment and phylogenetic analyses. From 2003 to 2010, CPV-2a and -2b were the only variants detected. CPV-2c, emerged in 2014, replacing CPV-2a and -2b, and has become a major variant in 2019. Phylogenetic analysis revealed that the proposed mutation pattern of VP2 amino acid residues could help distinguish Thai CPV-2 variants. This comprehensive examination provides insight into the genomic evolution of CPV-2 in Thailand since its first reporting in 2003, which may facilitate the surveillance of the potential genetic alteration of emergent CPV-2 variants.
Combined Photothermal Therapy and Lycium barbarum Polysaccharide for Topical Administration to Improve the Efficacy of Doxorubicin in the Treatment of Breast Cancer
Authors: Sun Lina , Zuo Cuiling , Liu Xinxin , Guo Yifei , Wang Xiangtao , Dong Zhengqi , Han Meihua
Published: December 2022

In order to improve the efficacy of doxorubicin in the treatment of breast cancer, we constructed a drug delivery system combined with local administration of Lycium barbarum polysaccharides (LBP) and photothermal-material polypyrrole nanoparticles (PPY NPs). In vitro cytotoxicity experiments showed that the inhibitory effect of DOX + LBP + PPY NPs on 4T1 cells under NIR (near infrared) laser was eight times that of DOX at the same concentration (64% vs. 8%). In vivo antitumor experiments showed that the tumor inhibition rate of LBP + DOX + PPY NPs + NIR reached 87.86%. The results of the H&E staining and biochemical assays showed that the systemic toxicity of LBP + DOX + PPY NPs + NIR group was reduced, and liver damage was significantly lower in the combined topical administration group (ALT 54 ± 14.44 vs. 28 ± 3.56; AST 158 ± 16.39 vs. 111 ± 20.85) (p < 0.05). The results of the Elisa assay showed that LBP + DOX + PPY NPs + NIR can enhance efficacy and reduce toxicity (IL-10, IFN-γ, TNF-α, IgA, ROS). In conclusion, LBP + DOX + PPY NPs combined with photothermal therapy can improve the therapeutic effect of DOX on breast cancer and reduce its toxic side effects.
Hyper-Branched Cationic Cyclodextrin Polymers for Improving Plasmid Transfection in 2D and 3D Spheroid Cells
Authors: Monfared Yousef Khazaei , Mahmoudian Mohammad , Cecone Claudio , Caldera Fabrizio , Haiaty Sanya , Heidari Hamid Reza , Rahbarghazi Reza , Matencio Adrián , Zakeri-Milani Parvin , Trotta Francesco
Published: December 2022

In this article, we used monolayer two dimensional (2D) and 3D multicellular spheroid models to improve our understanding of the gene delivery process of a new modified cationic hyper-branched cyclodextrin-based polymer (Ppoly)-loaded plasmid encoding Enhanced Green Fluorescent Protein (EGFP). A comparison between the cytotoxicity effect and transfection efficiency of the plasmid DNA (pDNA)-loaded Ppoly system in 2D and 3D spheroid cells determined that the transfection efficiency and cytotoxicity of Ppoly–pDNA nanocomplexes were lower in 3D spheroids than in 2D monolayer cells. Furthermore, histopathology visualization of Ppoly–pDNA complex cellular uptake in 3D spheroids demonstrated that Ppoly penetrated into the inner layers. This study indicated that the Ppoly, as a non-viral gene delivery system in complex with pDNA, is hemocompatible, non-toxic, high in encapsulation efficiency, and has good transfection efficiency in both 2D and 3D cell cultures compared to free pDNA and lipofectamine (as the control).
Non-Adherence to Antidepressant Treatment and Related Factors in a Region of Spain: A Population-Based Registry Study
Authors: Pedrosa-Naudín M. Aránzazu , Gutiérrez-Abejón Eduardo , Herrera-Gómez Francisco , Fernández-Lázaro Diego , Álvarez F. Javier
Published: December 2022

Antidepressants are a commonly prescribed psychotropic medication, and their use has increased in recent years. Medication non-adherence in patients with mental disorders is associated with worse health outcomes. A population-based registry study to assess antidepressant non-adherence during 2021 has been carried out. An indirect method based on the medication possession ratio (MPR) has been utilized. Patients with a MPR under 80% were classified as non-adherent. A multivariate logistic regression to identify non-adherence predictors has been used, considering sociodemographic (age, sex, institutionalization and urbanicity) and health related variables (diagnostics, antidepressant class, multiple prescribers, and polypharmacy). In 2021, 10.6% of the Castile and Leon population used antidepressants. These patients were institutionalized (7.29%), living in urban areas (63.44%), polymedicated with multiple prescribers (57.07%), and using serotonin selective reuptake inhibitors (SSRIs) (54.77%), other antidepressants (46.82%) or tricyclic antidepressants (TCAs) (13.76%). Antidepressants were prescribed mainly for depression (36.73%) and anxiety (29.24%). Non-adherence to antidepressants was more frequent in men (20.56%) than in woman (19.59%) and decreased with increasing age (32% up to 17 years old vs. 13.76% over 80 years old). TCAs were associated with the highest prevalence of non-adherence (23.99%), followed by SSRIs (20.19%) and other antidepressants (18.5%). Predictors of non-adherence in patients on antidepressants were: living in urban areas, using TCAs, and pain occurrence. Non-adherence to antidepressants decreases with aging. Being female, institutionalization, being polymedicated and having depression/anxiety alongside another psychiatric diagnosis are protective factors against non-adherence. The MPR is a robust indicator for the clinician to identify non-adherent patients for monitoring, and adopt any necessary corrective actions.
Challenges Inherent in Controlling Prickly Pear Species; a Global Review of the Properties of Opuntia stricta, Opuntia ficus-indica and Opuntia monacantha
Authors: Humphries Talia , Campbell Shane , Florentine Singarayer
Published: December 2022

Opuntia species (prickly pear) were deliberately introduced to many countries around the world for fruit, cochineal dye production, living fencing or as ornamentals. They are now some of the world’s most significant weeds, particularly in regions with warm and or dry climates, as they pose threats to economic and environmental assets. In addition, they can cause considerable health issues for humans and animals. Opuntia spp. have prolific reproduction abilities, being able to reproduce both vegetatively and by seed. They have generalist pollination and dispersal requirements, which promotes their establishment and spread. Opuntia stricta, O. monacantha and O. ficus-indica are the most globally widespread of the Opuntia spp. In many countries, biological control agents, particularly the cactus moth (Cactoblastis cactorum) and various cochineal insects from the Dactylopius genus, have successfully reduced land-scape scale populations. On a smaller scale, controlling these weeds by either injecting or spraying the cladodes with herbicides can provide effective control. Care must be taken during herbicide treatments as any untreated areas will regenerate. While biological control is the most cost and time effective control method for landscape-scale infestations, further research into the combined efficacy of herbicides, fire, grubbing and pre-burial techniques would be beneficial for land managers to control small-scale and establishing populations. It would also be useful to have greater knowledge of the potential seedbank longevity and seed ecology of these species so that integrated management strategies can be developed to not only deal with initial populations but also the subsequent seedling regrowth.
On-Farm Multi-Environment Evaluation of Selected Cassava (Manihot esculenta Crantz) Cultivars in South Africa
Authors: Amelework Assefa B. , Bairu Michael W. , Marx Roelene , Owoeye Lawrence , Laing Mark , Venter Sonja L.
Published: December 2022

Cassava is an important starchy root crop grown globally in tropical and subtropical regions. The ability of cassava to withstand difficult growing conditions and long-term storability underground makes it a resilient crop, contributing to food and nutrient security. This study was conducted to evaluate the performance and adaptability of exotic cassava cultivars across different environments in South Africa and to recommend genotypes for cultivation. A total of 11 cassava cultivars were evaluated at six on-farm sites, using a randomized complete block design with three replications. There were highly significant (p < 0.001) variations between genotypes, environments, and their interaction for all yield and yield-related traits studied. This indicates the need to test the genotypes in multiple environments before effective selection and commercialization can be undertaken. MSAF2 and UKF4 showed the overall best performances for most of the traits, whilst UKF9 (49.5%) and P1/19 (48.5%) had the highest dry matter yield. UKF4 (102.7 t ha−1) had the highest yield and greatest root yield stability across environments. MSAF2 did not perform consistently across environments because it was highly susceptible to cassava mosaic disease (CMD). MSAF2 could be used as a donor parent to generate novel clones with large numbers of marketable roots, and high fresh root yields, if the other parent can provide effective resistance to CMD. Based on genotype and environmental mean, Mabuyeni (KwaZulu-Natal), Mandlakazi (Limpopo), and Shatale (Mpumalanga) were found to be better environments for cassava cultivation and testing. This study is a pioneer in cassava research using multiple environments in South Africa. It provides baseline information on the performance of currently available cassava clones, their adaptation to multiple sites, the identification of suitable test sites, and information on current genetic resources for a future breeding program.
Water Stress Identification of Winter Wheat Crop with State-of-the-Art AI Techniques and High-Resolution Thermal-RGB Imagery
Authors: Chandel Narendra S. , Rajwade Yogesh A. , Dubey Kumkum , Chandel Abhilash K. , Subeesh A. , Tiwari Mukesh K.
Published: December 2022

Timely crop water stress detection can help precision irrigation management and minimize yield loss. A two-year study was conducted on non-invasive winter wheat water stress monitoring using state-of-the-art computer vision and thermal-RGB imagery inputs. Field treatment plots were irrigated using two irrigation systems (flood and sprinkler) at four rates (100, 75, 50, and 25% of crop evapotranspiration [ETc]). A total of 3200 images under different treatments were captured at critical growth stages, that is, 20, 35, 70, 95, and 108 days after sowing using a custom-developed thermal-RGB imaging system. Crop and soil response measurements of canopy temperature (Tc), relative water content (RWC), soil moisture content (SMC), and relative humidity (RH) were significantly affected by the irrigation treatments showing the lowest Tc (22.5 ± 2 °C), and highest RWC (90%) and SMC (25.7 ± 2.2%) for 100% ETc, and highest Tc (28 ± 3 °C), and lowest RWC (74%) and SMC (20.5 ± 3.1%) for 25% ETc. The RGB and thermal imagery were then used as inputs to feature-extraction-based deep learning models (AlexNet, GoogLeNet, Inception V3, MobileNet V2, ResNet50) while, RWC, SMC, Tc, and RH were the inputs to function-approximation models (Artificial Neural Network (ANN), Kernel Nearest Neighbor (KNN), Logistic Regression (LR), Support Vector Machine (SVM) and Long Short-Term Memory (DL-LSTM)) to classify stressed/non-stressed crops. Among the feature extraction-based models, ResNet50 outperformed other models showing a discriminant accuracy of 96.9% with RGB and 98.4% with thermal imagery inputs. Overall, classification accuracy was higher for thermal imagery compared to RGB imagery inputs. The DL-LSTM had the highest discriminant accuracy of 96.7% and less error among the function approximation-based models for classifying stress/non-stress. The study suggests that computer vision coupled with thermal-RGB imagery can be instrumental in high-throughput mitigation and management of crop water stress.
Impact of Non-Accelerated Aging on the Properties of Parylene C
Authors: Selbmann Franz , Scherf Christina , Langenickel Jörn , Roscher Frank , Wiemer Maik , Kuhn Harald , Joseph Yvonne
Published: December 2022

The polymer Parylene combines a variety of excellent properties and, hence, is an object of intensive research for packaging applications, such as the direct encapsulation of medical implants. Moreover, in the past years, an increasing interest for establishing new applications for Parylene is observed. These include the usage of Parylene as a flexible substrate, a dielectric, or a material for MEMS, e.g., a bonding adhesive. The increasing importance of Parylene raises questions regarding the long-term reliability and aging of Parylene as well as the impact of the aging on the Parylene properties. Within this paper, we present the first investigations on non-accelerated Parylene C aging for a period of about five years. Doing so, free-standing Parylene membranes were fabricated to investigate the barrier properties, the chemical stability, as well as the optical properties of Parylene in dependence on different post-treatments to the polymer. These properties were found to be excellent and with only a minor age-related impact. Additionally, the mechanical properties, i.e., the Young’s modulus and the hardness, were investigated via nano-indentation over the same period of time. For both mechanical properties only, minor changes were observed. The results prove that Parylene C is a highly reliable polymer for applications that needs a high long-term stability.
Recent Advances in Stimuli-Responsive Doxorubicin Delivery Systems for Liver Cancer Therapy
Authors: Radu Elena Ruxandra , Semenescu Augustin , Voicu Stefan Ioan
Published: December 2022

Doxorubicin (DOX) is one of the most commonly used drugs in liver cancer. Unfortunately, the traditional chemotherapy with DOX presents many limitations, such as a systematic release of DOX, affecting both tumor tissue and healthy tissue, leading to the apparition of many side effects, multidrug resistance (MDR), and poor water solubility. Furthermore, drug delivery systems’ responsiveness has been intensively studied according to the influence of different internal and external stimuli on the efficiency of therapeutic drugs. In this review, we discuss both internal stimuli-responsive drug-delivery systems, such as redox, pH and temperature variation, and external stimuli-responsive drug-delivery systems, such as the application of magnetic, photo-thermal, and electrical stimuli, for the controlled release of Doxorubicin in liver cancer therapy, along with the future perspectives of these smart delivery systems in liver cancer therapy.
Electrospinning vs. Electro-Assisted Solution Blow Spinning for Fabrication of Fibrous Scaffolds for Tissue Engineering
Authors: Demina Tatiana S. , Bolbasov Evgeniy N. , Peshkova Maria A. , Efremov Yuri M. , Bikmulina Polina Y. , Birdibekova Aisylu V. , Popyrina Tatiana N. , Kosheleva Nastasia V. , Tverdokhlebov Sergei I. , Timashev Peter S. , Akopova Tatiana A.
Published: December 2022

Biodegradable polymeric fibrous non-woven materials are widely used type of scaffolds for tissue engineering. Their morphology and properties could be controlled by composition and fabrication technology. This work is aimed at development of fibrous scaffolds from a multicomponent polymeric system containing biodegradable synthetic (polylactide, polycaprolactone) and natural (gelatin, chitosan) components using different methods of non-woven mats fabrication: electrospinning and electro-assisted solution blow spinning. The effect of the fabrication technique of the fibrous materials onto their morphology and properties, including the ability to support adhesion and growth of cells, was evaluated. The mats fabricated using electrospinning technology consist of randomly oriented monofilament fibers, while application of solution blow spinning gave a rise to chaotically arranged multifilament fibers. Cytocompatibility of all fabricated fibrous mats was confirmed using in vitro analysis of metabolic activity, proliferative capacity and morphology of NIH 3T3 cell line. Live/Dead assay revealed the formation of the highest number of cell–cell contacts in the case of multifilament sample formed by electro-assisted solution blow spinning technology.
Naphthalene-Based Oxime Esters as Type I Photoinitiators for Free Radical Photopolymerization
Authors: Lee Zhong-Han , Yen Shih-Chieh , Hammoud Fatima , Hijazi Akram , Graff Bernadette , Lalevée Jacques , Chen Yung-Chung
Published: December 2022

In order to discuss the polymerization effect from the substituted position and methoxy group of Type I photinitiators, a series of naphthalene-based oxime esters was designed and synthesized. Compared to the 2-naphthalene-substituted compound, the UV absorption region of the 1-naphthalene-based compound was greatly improved. In addition, the methoxy substitution exhibited longer absorption characteristics than did the methoxy-free one. The photochemical reaction behavior of these novel compounds was also studied by photolysis, cyclic voltammetry (CV), and electron spin resonance (ESR) experiments. Finally, the initiation abilities of naphthalene-based oxime esters toward trimethylolpropane triacrylate (TMPTA) monomer were conducted through the photo-DSC instrument under UV and a 405@nm LED lamp. Remarkedly, the naphthalene-based oxime ester (NA-3) that contains 1-naphthalene with o-methoxy substituent showed the rather red-shifted absorption region with the highest final conversion efficiency under UV (46%) and 405@nm LED (41%) lamp irradiation.
Differences in the Elastomeric Behavior of Polyglycine-Rich Regions of Spidroin 1 and 2 Proteins
Authors: Pacios Luis F. , Arguelles Joseph , Hayashi Cheryl Y. , Guinea Gustavo V. , Elices Manuel , Perez-Rigueiro Jose
Published: December 2022

Two different polyglycine-rich fragments were selected as representatives of major ampullate gland spidroins (MaSp) 1 and 2 types, and their behavior in a water-saturated environment was simulated within the framework of molecular dynamics (MD). The selected fragments are found in the sequences of the proteins MaSp1a and MaSp2.2a of Argiope aurantia with respective lengths of 36 amino acids (MaSp1a) and 50 amino acids (MaSp2.2s). The simulation took the fully extended β-pleated conformation as reference, and MD was used to determine the equilibrium configuration in the absence of external forces. Subsequently, MD were employed to calculate the variation in the distance between the ends of the fragments when subjected to an increasing force. Both fragments show an elastomeric behavior that can be modeled as a freely jointed chain with links of comparable length, and a larger number of links in the spidroin 2 fragment. It is found, however, that the maximum recovery force recorded from the spidroin 2 peptide (Fmax ≈ 400 pN) is found to be significantly larger than that of the spidroin 1 (Fmax ≈ 250 pN). The increase in the recovery force of the spidroin 2 polyglycine-rich fragment may be correlated with the larger values observed in the strain at breaking of major ampullate silk fibers spun by Araneoidea species, which contain spidroin 2 proteins, compared to the material produced by spider species that lack these spidroins (RTA-clade).
Capsule-Based Self-Healing and Self-Sensing Composites with Enhanced Mechanical and Electrical Restoration
Authors: Foteinidis Georgios , Kosarli Maria , Nikiphorides Pantelis , Tsirka Kyriaki , Paipetis Alkiviadis S.
Published: December 2022

In this work, we report for the first time the manufacturing and characterization of smart multifunctional, capsule-based self-healing and self-sensing composites. In detail, neat and nanomodified UF microcapsules were synthesized and incorporated into composites with a nanomodified epoxy matrix for the restoration of the mechanical and electrical properties. The electrical properties were evaluated with the use of the impedance spectroscopy method. The self-healing composites were subjected to mode-II fracture toughness tests. Additionally, the lap strap geometry that can simulate the mechanical behavior of a stiffened panel was used. The introduction of the nanomodified self-healing system improved the initial mechanical properties in the mode-II fracture toughness by +29%, while the values after the healing process exceeded the initial one. At lap strap geometry, the incorporation of the self-healing system did not affect the initial mechanical properties that were fully recovered after the healing process.
Analysis Method and Case Study of the Lightweight Design of Automotive Parts and Its Influence on Carbon Emissions
Authors: Li Qiang , Zhang Yu , Zhang Cuixia , Wang Xiang , Chen Jianqing
Published: December 2022

The automobile industry, as a representative in pursuing the goals of “emission peak” and “carbon neutrality”, has made low carbon a new industrial practice. With regard to low carbon, the lightweight design proves to be an effective approach to reducing carbon emissions from automobiles. Given the state of research, in which the existing lightweight design schemes of automobiles seldom consider the impact of the lightweight quality on carbon emissions during the whole life cycle of the automobiles, this paper proposes a more comprehensive lightweight design method for automobiles in regard to carbon emissions. First, the finite element method was adopted to analyze the stress, strain and safety factors of the automobile parts based on their stress, so as to identify the positions where the lightweight design was applicable. Subsequently, a lightweight scheme was designed accordingly. Next, the finite element method was re-applied to the parts whose weights had been reduced. In this way, the feasibility of the lightweight scheme was verified. In addition, a method of calculating the carbon emissions produced by changes in the mass, manufacturing processes, application and recycling of automobile parts after the application of the lightweight design was also presented. The method can be used for evaluating the low carbon benefits of the lightweight design scheme. To prove the feasibility of the method, the ZS061750-152101 wheel hub designed and manufactured by Anhui Axle Co., Ltd. was taken as an example for the case analysis. The lightweight design changes three structures of the wheel hub, reducing its weight by 1.4 kg in total. For a single wheel hub, the carbon emissions are reduced by 51.22 kg altogether. That is to say, if the lightweight scheme were to be applied to all the wheels produced by Anhui Axle Co., Ltd. (about 500,000 per year), the carbon emissions from the wheel production, application and recycling could be cut by 2.56 × 107 kg, marking a favorable emission reduction effect. The proposed method can not only provide insight into the lightweight design of automobiles and other equipment against the background of low carbon but also provide a channel for calculating the carbon emission changes in the whole process after the application of the lightweight design.
Co-Precipitated Mn0.15Ce0.85O2−δ Catalysts for NO Oxidation: Manganese Precursors and Mn-Ce Interactions
Authors: Gao Yuxi , Jin Baofang , Wu Xiaodong , Li Zhenguo , Ran Rui , Weng Duan
Published: December 2022

Two Mn0.15Ce0.85O2−δ mixed oxides were synthesized by a co-precipitation method using Mn(NO3)2 and KMnO4 as the manganese precursors, respectively. Structural analyses by X-ray powder diffraction and Raman spectroscopy reveal the formation of MnOx-CeO2 solid solutions. The Mn0.15Ce0.85O2−δ catalyst prepared from the high-valent manganese precursor exhibits higher activity for the catalytic oxidation of NO. The advantage of KMnO4 is related to the improved redox property of the catalyst as supported by H2 temperature-programmed reduction (TPR) and O2 temperature-programmed desorption (TPD). The Mn-Ce interactions create more Mn4+, Ce3+ and oxygen vacancies on the KMnO4-synthesized mixed oxides based on the Raman and X-ray photoelectron spectra (XPS).
Synthesis and Characterization of Multiple Functionalized Cyclohexanone Using Diels–Alder Reaction of α-Nitrocinnamate
Authors: Hamada Takumi , Iwai Kento , Nishiwaki Nagatoshi
Published: December 2022

A systematic study of the Diels–Alder reaction of α-nitrocinnamate was performed. The reaction of p-substituted α-nitrocinnamate with 2,3-dimethyl-1,3-butadienes smoothly proceeded regardless of the p-substituent, which was either an electron-donating or -withdrawing group. A control reaction revealed that α-nitrocinnamate isomerized during the reaction. Danishefsly’s diene (1-methoxy-3-trimethylsiloxy-1,3-butadiene) facilitated cycloaddition under mild conditions to afford a cycloadduct without the alternation of the diastereomeric ratio. Moreover, the desilylation of the cycloadduct furnished multiple functionalized cyclohexanones.
Hearing Voices: Reapproaching Medieval Inquisition Records
Authors: Zbíral David , Shaw Robert L. J.
Published: December 2022

The records of medieval heresy inquisitions have been a subject of controversy ever since their rediscovery by historians. The detail they convey of specific social interactions has continued to inspire generations of scholars, while the coercive conditions of their production have placed strong caveats over their interpretation. This article offers a comprehensive review of the debate on the uses of inquisition records, encompassing scholarship across multiple languages and schools of thought. It also highlights some shortcomings in that debate, e.g., the overrepresentation of inquisitors’ choices; the claim that the use of torture led automatically to reproducing outlandish inquisitorial fears; and the idea that exceptional detail correlates with reliability. The article concludes with the proposal of the Dissident Networks Project (DISSINET) to use structured data within a new variety of quantitative history. This method, founded on the Computer-Assisted Semantic Text Modelling approach that DISSINET has pioneered, is well-suited to addressing the biases of inquisition documents and opening them to scrutiny, thus providing a significant complement to close reading.
The Dissemination of Laozi’s Text and Thought in the Arab World
Authors: Hadhri Sana , Liu Zixiao , Wu Zhiyong
Published: December 2022

Based on Chinese and Arabic literature, this paper summarizes the spread of Laozi’s text and thought in the Arab world. The specific course of dissemination can be divided into two stages: from 1966 to 2000, the Dao De Jing was disseminated on the basis of indirect translations; from 2000 to today, the spread of the Dao De Jing in the Arab world reached a climax when the first direct translation was published. Laozi’s text and thought have gained acceptance and popularity largely because of their soothing function and similarity to the Sufi spirit found in Arab culture. The spread of Laozi’s text and thought in the Arab world presents three features: a long and friendly history of cultural exchange has served as a foundation; languages such as English and French have functioned as intermediaries; and similarities between Sufism and Daoism have provided points of connection.
What Can God Do? What Should God Do?
Authors: Horowitz Amir
Published: December 2022

The aim of this paper is to defend James Sterba’s version (2019) of the logical argument from evil against the existence of God from two objections that have been raised against it: that God cannot “logically” prevent all evils and that the moral requirements that the argument poses for God may not apply to God. I argue that these objections do not refute the claim that God can prevent and should prevent any evil and do not undermine Sterba’s argument from evil to the effect that God does not exist.
Explainable Artificial Intelligence (XAI) in Insurance
Authors: Owens Emer , Sheehan Barry , Mullins Martin , Cunneen Martin , Ressel Juliane , Castignani German
Published: December 2022

Explainable Artificial Intelligence (XAI) models allow for a more transparent and understandable relationship between humans and machines. The insurance industry represents a fundamental opportunity to demonstrate the potential of XAI, with the industry’s vast stores of sensitive data on policyholders and centrality in societal progress and innovation. This paper analyses current Artificial Intelligence (AI) applications in insurance industry practices and insurance research to assess their degree of explainability. Using search terms representative of (X)AI applications in insurance, 419 original research articles were screened from IEEE Xplore, ACM Digital Library, Scopus, Web of Science and Business Source Complete and EconLit. The resulting 103 articles (between the years 2000–2021) representing the current state-of-the-art of XAI in insurance literature are analysed and classified, highlighting the prevalence of XAI methods at the various stages of the insurance value chain. The study finds that XAI methods are particularly prevalent in claims management, underwriting and actuarial pricing practices. Simplification methods, called knowledge distillation and rule extraction, are identified as the primary XAI technique used within the insurance value chain. This is important as the combination of large models to create a smaller, more manageable model with distinct association rules aids in building XAI models which are regularly understandable. XAI is an important evolution of AI to ensure trust, transparency and moral values are embedded within the system’s ecosystem. The assessment of these XAI foci in the context of the insurance industry proves a worthwhile exploration into the unique advantages of XAI, highlighting to industry professionals, regulators and XAI developers where particular focus should be directed in the further development of XAI. This is the first study to analyse XAI’s current applications within the insurance industry, while simultaneously contributing to the interdisciplinary understanding of applied XAI. Advancing the literature on adequate XAI definitions, the authors propose an adapted definition of XAI informed by the systematic review of XAI literature in insurance.
Feedback-Assisted Automatic Target and Clutter Discrimination Using a Bayesian Convolutional Neural Network for Improved Explainability in SAR Applications
Authors: Blomerus Nicholas , Cilliers Jacques , Nel Willie , Blasch Erik , de Villiers Pieter
Published: December 2022

In this paper, a feedback training approach for efficiently dealing with distribution shift in synthetic aperture radar target detection using a Bayesian convolutional neural network is proposed. After training the network on in-distribution data, it is tested on out-of-distribution data. Samples that are classified incorrectly with high certainty are fed back for a second round of training. This results in the reduction of false positives in the out-of-distribution dataset. False positive target detections challenge human attention, sensor resource management, and mission engagement. In these types of applications, a reduction in false positives thus often takes precedence over target detection and classification performance. The classifier is used to discriminate the targets from the clutter and to classify the target type in a single step as opposed to the traditional approach of having a sequential chain of functions for target detection and localisation before the machine learning algorithm. Another aspect of automated synthetic aperture radar detection and recognition problems addressed here is the fact that human users of the output of traditional classification systems are presented with decisions made by “black box” algorithms. Consequently, the decisions are not explainable, even to an expert in the sensor domain. This paper makes use of the concept of explainable artificial intelligence via uncertainty heat maps that are overlaid onto synthetic aperture radar imagery to furnish the user with additional information about classification decisions. These uncertainty heat maps facilitate trust in the machine learning algorithm and are derived from the uncertainty estimates of the classifications from the Bayesian convolutional neural network. These uncertainty overlays further enhance the users’ ability to interpret the reasons why certain decisions were made by the algorithm. Further, it is demonstrated that feeding back the high-certainty, incorrectly classified out-of-distribution data results in an average improvement in detection performance and a reduction in uncertainty for all synthetic aperture radar images processed. Compared to the baseline method, an improvement in recall of 11.8%, and a reduction in the false positive rate of 7.08% were demonstrated using the Feedback-assisted Bayesian Convolutional Neural Network or FaBCNN.
Automatic Detection of Marine Litter: A General Framework to Leverage Synthetic Data
Authors: Nagy Manon , Istrate Luca , Simtinică Matei , Travadel Sébastien , Blanc Philippe
Published: December 2022

The spatial and temporal coverage of spaceborne optical imaging systems are well suited for automated marine litter monitoring. However, developing machine learning-based detection and identification algorithms requires large amounts of data. Indeed, when it comes to marine debris, ground validated data is scarce. In this study, we propose a general methodology that leverages synthetic data in order to avoid overfitting and generalizes well. The idea is to utilize realistic models of spaceborne optical image acquisition and marine litter to generate large amounts of data to train the machine learning algorithms. These can then be used to detect marine pollution automatically on real satellite images. The main contribution of our study is showing that algorithms trained on simulated data can be successfully transferred to real-life situations. We present the general components of our framework, our modeling of satellites and marine debris and a proof of concept implementation for macro-plastic detection with Sentinel-2 images. In this case study, we generated a large dataset (more than 16,000 pixels of marine debris) composed of seawater, plastic, and wood and trained a Random Forest classifier on it. This classifier, when tested on real satellite images, successfully discriminates marine litter from seawater, thus proving the effectiveness of our approach and paving the way for machine learning-based marine litter detection with even more representative simulation models.
Real-Time Measurement of Refractive Index Using 3D-Printed Optofluidic Fiber Sensor
Authors: Leça João M. , Magalhães Yannis , Antunes Paulo , Pereira Vanda , Ferreira Marta S.
Published: December 2022

This work describes a 3D-printed optofluidic fiber sensor to measure refractive index in real time, combining a microfluidic system with an optical fiber extrinsic Fabry–Perot interferometer. The microfluidic chip platform was developed for this purpose through 3D printing. The Fabry–Perot cavity was incorporated in the microfluidic chip perpendicularly to the sample flow, which was of approximately 3.7 µL/s. The optofluidic fiber sensor platform coupled with a low-cost optical power meter detector was characterized using different concentrations of glucose solutions. In the linear regression analysis, the optical power shift was correlated with the refractive index and a sensitivity of −86.6 dB/RIU (r2 = 0.996) was obtained. Good results were obtained in terms of stability with a maximum standard deviation of 0.03 dB and a sensor resolution of 5.2 × 10−4 RIU. The feasibility of the optofluidic fiber sensor for dynamic analyses of refractive index with low sample usage was confirmed through real-time measurements.
Evidence of Nonlinear Seismic Effects in the Earth from Downhole Distributed Acoustic Sensors
Authors: Yurikov Alexey , Gurevich Boris , Tertyshnikov Konstantin , Lebedev Maxim , Isaenkov Roman , Sidenko Evgenii , Yavuz Sinem , Glubokovskikh Stanislav , Shulakova Valeriya , Freifeld Barry , Correa Julia , Wood Todd J. , Beresnev Igor A. , Pevzner Roman
Published: December 2022

Seismic velocities and elastic moduli of rocks are known to vary significantly with applied stress, which indicates that these materials exhibit nonlinear elasticity. Monochromatic waves in nonlinear elastic media are known to generate higher harmonics and combinational frequencies. Such effects have the potential to be used for broadening the frequency band of seismic sources, characterization of the subsurface, and safety monitoring of civil engineering infrastructure. However, knowledge on nonlinear seismic effects is still scarce, which impedes the development of their practical applications. To explore the potential of nonlinear seismology, we performed three experiments: two in the field and one in the laboratory. The first field experiment used two vibroseis sources generating signals with two different monochromatic frequencies. The second field experiment used a surface orbital vibrator with two eccentric motors working at different frequencies. In both experiments, the generated wavefield was recorded in a borehole using a fiber-optic distributed acoustic sensing cable. Both experiments showed combinational frequencies, harmonics, and other intermodulation products of the fundamental frequencies both on the surface and at depth. Laboratory experiments replicated the setup of the field test with vibroseis sources and showed similar nonlinear combinations of fundamental frequencies. Amplitudes of the nonlinear signals observed in the laboratory showed variation with the saturating fluid. These results confirm that nonlinear components of the wavefield propagate as body waves, are likely to generate within rock formations, and can be potentially used for reservoir fluid characterization.
The Effect of Geometrical Overlap between Giant Magnetoresistance Sensor and Magnetic Flux Concentrators: A Novel Comb-Shaped Sensor for Improved Sensitivity
Authors: Kulkarni Prabhanjan D. , Iwasaki Hitoshi , Nakatani Tomoya
Published: December 2022

The combination of magnetoresistive (MR) element and magnetic flux concentrators (MFCs) offers highly sensitive magnetic field sensors. To maximize the effect of MFC, the geometrical design between the MR element and MFCs is critical. In this paper, we present simulation and experimental studies on the effect of the geometrical relationship between current-in-plane giant magnetoresistive (GMR) element and MFCs made of a NiFeCuMo film. Finite element method (FEM) simulations showed that although an overlap between the MFCs and GMR element enhances their magneto-static coupling, it can lead to a loss of magnetoresistance ratio due to a magnetic shielding effect by the MFCs. Therefore, we propose a comb-shaped GMR element with alternate notches and fins. The FEM simulations showed that the fins of the comb-shaped GMR element provide a strong magneto-static coupling with the MFCs, whereas the electric current is confined within the main body of the comb-shaped GMR element, resulting in improved sensitivity. We experimentally demonstrated a higher sensitivity of the comb-shaped GMR sensor (36.5 %/mT) than that of a conventional rectangular GMR sensor (28 %/mT).
Joint Cross-Consistency Learning and Multi-Feature Fusion for Person Re-Identification
Authors: Ren Danping , He Tingting , Dong Huisheng
Published: December 2022

To solve the problem of inadequate feature extraction by the model due to factors such as occlusion and illumination in person re-identification tasks, this paper proposed a model with a joint cross-consistency learning and multi-feature fusion person re-identification. The attention mechanism and the mixed pooling module were first embedded in the residual network so that the model adaptively focuses on the more valid information in the person images. Secondly, the dataset was randomly divided into two categories according to the camera perspective, and a feature classifier was trained for the two types of datasets respectively. Then, two classifiers with specific knowledge were used to guide the model to extract features unrelated to the camera perspective for the two types of datasets so that the obtained image features were endowed with domain invariance by the model, and the differences in the perspective, attitude, background, and other related information of different images were alleviated. Then, the multi-level features were fused through the feature pyramid to concern the more critical information of the image. Finally, a combination of Cosine Softmax loss, triplet loss, and cluster center loss was proposed to train the model to address the differences of multiple losses in the optimization space. The first accuracy of the proposed model reached 95.9% and 89.7% on the datasets Market-1501 and DukeMTMC-reID, respectively. The results indicated that the proposed model has good feature extraction capability.
Plane Fitting in 3D Reconstruction to Preserve Smooth Homogeneous Surfaces
Authors: Xu Yanan , So Yohwan , Woo Sanghyuk
Published: December 2022

Photogrammetric techniques for weakly-textured surfaces without sufficient information about the R (red), G (green) and B (blue) primary colors of light are challenging. Considering that most urban or indoor object surfaces follow simple geometric shapes, a novel method for reconstructing smooth homogeneous planar surfaces based on MVS (Multi-View Stereo) is proposed. The idea behind it is to extract enough features for the image description, and to refine the dense points generated by the depth values of pixels with plane fitting, to favor the alignment of the surface to the detected planes. The SIFT (Scale Invariant Feature Transform) and AKAZE (Accelerated-KAZE) feature extraction algorithms are combined to ensure robustness and help retrieve connections in small samples. The smoothness of the enclosed watertight Poisson surface can be enhanced by enforcing the 3D points to be projected onto the absolute planes detected by a RANSAC (Random Sample Consensus)-based approach. Experimental evaluations of both cloud-to-mesh comparisons in the per-vertex distances with the ground truth models and visual comparisons with a popular mesh filtering based post-processing method indicate that the proposed method can considerably retain the integrity and smoothness of the reconstruction results. Combined with other primitive fittings, the reconstruction extent of homogeneous surfaces can be further extended, serving as primitive models for 3D building reconstruction, and providing guidance for future works in photogrammetry and 3D surface reconstruction.