bluuebunny/crossref_metadata_2025 huggingface dataset:
Microneedle Array Technique for the Longitudinal Extraction of Interstitial Fluid without Hair Removal
Authors: Taylor Robert M. , Ali Abdul-Mehdi S. , Zhu Yiliang , Bolt Alicia M. , Baca Justin T.
Published: June 2022

Interstitial fluid (ISF) bathes the cells and tissues and is in constant exchange with blood. As an exchange medium for waste, nutrients, exosomes, and signaling molecules, ISF is recognized as a plentiful source of biomolecules. Many basic and pre-clinical small animal studies could benefit from an inexpensive and efficient technique that allows for the in vivo extraction of ISF for the subsequent quantification of molecules in the interstitial space. We have previously reported on a minimally invasive technique for the extraction of ISF using a 3D-printed microneedle array (MA) platform for comprehensive biomedical applications. Previously, hairless animal models were utilized, and euthanasia was performed immediately following the procedure. Here, we demonstrate the technique in Sprague Dawley rats, without the need for hair removal, over multiple extractions and weeks. As an example of this technique, we report simultaneous quantification of the heavy metals Copper (Cu), Lead (Pb), Lithium (Li), and Nickel (Ni) within the ISF, compared with whole blood. These results demonstrate the MA technique applicability to a broader range of species and studies and the reuse of animals, leading to a reduction in number of animals needed to successfully complete ISF extraction experiments.
Intranasal Methylprednisolone Ameliorates Neuroinflammation Induced by Chronic Toluene Exposure
Authors: Giraldo-Velásquez Manuel F. , Pérez-Osorio Iván N. , Espinosa-Cerón Alejandro , Bárcena Brandon M. , Calderón-Gallegos Arturo , Fragoso Gladis , Torres-Ramos Mónica , Páez-Martínez Nayeli , Sciutto Edda
Published: June 2022

Inhalants are chemical substances that induce intoxication, and toluene is the main component of them. Increasing evidence indicates that a dependence on inhalants involves a state of chronic stress associated to the activation of immune cells in the central nervous system and release of proinflammatory mediators, especially in some brain areas such as the nucleus accumbens and frontal cortex, where the circuits of pleasure and reward are. In this study, anti-neuroinflammatory treatment based on a single dose of intranasal methylprednisolone was assessed in a murine model of chronic toluene exposure. The levels of proinflammatory mediators, expression levels of Iba-1 and GFAP, and histological changes in the frontal cortex and nucleus accumbens were evaluated after the treatment. The chronic exposure to toluene significantly increased the levels of TNF-α, IL-6, and NO, the expression of GFAP, and induced histological alterations in mouse brains. The treatment with intranasally administered MP significantly reduced the expression of TNF-α and NO and the expression of GFAP (p < 0.05); additionally, it reversed the central histological damage. These results indicate that intranasally administered methylprednisolone could be considered as a treatment to reverse neuroinflammation and histological damages associated with the use of inhalants.
Oxidized Chitosan-Tobramycin (OCS-TOB) Submicro-Fibers for Biomedical Applications
Authors: Li Zhen , Mei Shunqi , Dong Yajie , She Fenghua , Li Chengpeng , Li Yongzhen , Kong Lingxue
Published: June 2022

Chitosan (CS) is a biodegradable, biocompatible, and non-toxic natural amino-poly-saccharide with antibacterial ability, owing to its positively charged amino groups. However, the low charge density leads to poor antibacterial efficiency which cannot meet the biomedical application requirements. In this study, Tobramycin (TOB) was grafted onto the backbone of oxidized chitosan (OCS) to synthesize oxidized chitosan-tobramycin (OCS-TOB). FTIR, 1H NMR and elemental analysis results demonstrated that OCS-TOB was successfully synthesized. OCS-TOB/PEO composite fibrous materials were produced by a self-made centrifugal spinning machine. In vitro experiments showed that cells proliferated on the submicro-fibrous OCS-TOB/PEO of appropriate concentration, and the antibacterial ability of OCS-TOB was much improved, compared with pristine CS. The results demonstrated that OCS-TOB/PEO nanofibrous materials could potentially be used for biomedical applications.
Pendulum-Based River Current Energy Converter for Hydrometric Monitoring Systems
Authors: Naifar Slim , Grimmeisen Felix , Viehweger Christian , Hu Zheng , Bauer Arthur , Hörschelmann Peter , Kanoun Olfa
Published: June 2022

Energy harvesting from flowing water is important for supplying hydrometric monitoring systems. Nevertheless, it is challenging due to the chaotic water flow in only one main direction and the relatively weak energy profile. In this paper, a novel energy harvester has been proposed, designed, and validated. The converter consists of a pendulum, a gearbox, two overrunning clutches, a spiral spring, and a generator. By coupling the kinetic energy via an oscillating mass equipped with a magnetic spring, it is possible to accommodate the power supply, electronics, and sensors with data transmission in a completely closed, encapsulated, stable housing without an interface to the outside. In addition, an energy management circuit and a battery charging circuit were developed that could be housed in the sealed enclosure. The pendulum transducer prototype was tested with the developed online hydrometric measurement station, which consists of a multi-channel data logger with a cellular modem and a tipping bucket rain gauge sensor. The overall system was successfully validated by experimental studies in a river.
Monitoring the Early Strength Development of Cement Mortar with Piezoelectric Transducers Based on Eigenfrequency Analysis Method
Authors: Wang Guocheng , Qiu Wenying , Wang Dongkai , Chen Huimin , Wang Xiaohao , Zhang Min
Published: June 2022

Monitoring the early strength formation process of cement is of great importance for structural construction management and safety. In this study, we investigated the relationship between the eigenfrequency and the early strength development of cement mortar. Embedded piezoceramic-based smart aggregates recorded the early strength of cement mortar. An eigenfrequency analysis model demonstrated the relationship between strength and frequency. Experiments were performed by using piezoelectric transducers to monitor the early strength formation process during the testing period. Three types of specimens with different strength grades were tested, and the early strength formation processes were recorded. The experimental results demonstrate that cement mortar strength has a good linear relationship with the resonance frequency, and the average square of the correlation coefficient is greater than 0.98. The results show that structural health monitoring technology is a feasible method of assessing structural safety conditions and has a broad market in the structural construction industry.
A Novel Machine Learning Approach for Severity Classification of Diabetic Foot Complications Using Thermogram Images
Authors: Khandakar Amith , Chowdhury Muhammad E. H. , Reaz Mamun Bin Ibne , Ali Sawal Hamid Md , Kiranyaz Serkan , Rahman Tawsifur , Chowdhury Moajjem Hossain , Ayari Mohamed Arselene , Alfkey Rashad , Bakar Ahmad Ashrif A. , Malik Rayaz A. , Hasan Anwarul
Published: June 2022

Diabetes mellitus (DM) is one of the most prevalent diseases in the world, and is correlated to a high index of mortality. One of its major complications is diabetic foot, leading to plantar ulcers, amputation, and death. Several studies report that a thermogram helps to detect changes in the plantar temperature of the foot, which may lead to a higher risk of ulceration. However, in diabetic patients, the distribution of plantar temperature does not follow a standard pattern, thereby making it difficult to quantify the changes. The abnormal temperature distribution in infrared (IR) foot thermogram images can be used for the early detection of diabetic foot before ulceration to avoid complications. There is no machine learning-based technique reported in the literature to classify these thermograms based on the severity of diabetic foot complications. This paper uses an available labeled diabetic thermogram dataset and uses the k-mean clustering technique to cluster the severity risk of diabetic foot ulcers using an unsupervised approach. Using the plantar foot temperature, the new clustered dataset is verified by expert medical doctors in terms of risk for the development of foot ulcers. The newly labeled dataset is then investigated in terms of robustness to be classified by any machine learning network. Classical machine learning algorithms with feature engineering and a convolutional neural network (CNN) with image-enhancement techniques are investigated to provide the best-performing network in classifying thermograms based on severity. It is found that the popular VGG 19 CNN model shows an accuracy, precision, sensitivity, F1-score, and specificity of 95.08%, 95.08%, 95.09%, 95.08%, and 97.2%, respectively, in the stratification of severity. A stacking classifier is proposed using extracted features of the thermogram, which is created using the trained gradient boost classifier, XGBoost classifier, and random forest classifier. This provides a comparable performance of 94.47%, 94.45%, 94.47%, 94.43%, and 93.25% for accuracy, precision, sensitivity, F1-score, and specificity, respectively.
A3C-TL-GTO: Alzheimer Automatic Accurate Classification Using Transfer Learning and Artificial Gorilla Troops Optimizer
Authors: Baghdadi Nadiah A. , Malki Amer , Balaha Hossam Magdy , Badawy Mahmoud , Elhosseini Mostafa
Published: June 2022

Alzheimer’s disease (AD) is a chronic disease that affects the elderly. There are many different types of dementia, but Alzheimer’s disease is one of the leading causes of death. AD is a chronic brain disorder that leads to problems with language, disorientation, mood swings, bodily functions, memory loss, cognitive decline, mood or personality changes, and ultimately death due to dementia. Unfortunately, no cure has yet been developed for it, and it has no known causes. Clinically, imaging tools can aid in the diagnosis, and deep learning has recently emerged as an important component of these tools. Deep learning requires little or no image preprocessing and can infer an optimal data representation from raw images without prior feature selection. As a result, they produce a more objective and less biased process. The performance of a convolutional neural network (CNN) is primarily affected by the hyperparameters chosen and the dataset used. A deep learning model for classifying Alzheimer’s patients has been developed using transfer learning and optimized by Gorilla Troops for early diagnosis. This study proposes the A3C-TL-GTO framework for MRI image classification and AD detection. The A3C-TL-GTO is an empirical quantitative framework for accurate and automatic AD classification, developed and evaluated with the Alzheimer’s Dataset (four classes of images) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). The proposed framework reduces the bias and variability of preprocessing steps and hyperparameters optimization to the classifier model and dataset used. Our strategy, evaluated on MRIs, is easily adaptable to other imaging methods. According to our findings, the proposed framework was an excellent instrument for this task, with a significant potential advantage for patient care. The ADNI dataset, an online dataset on Alzheimer’s disease, was used to obtain magnetic resonance imaging (MR) brain images. The experimental results demonstrate that the proposed framework achieves 96.65% accuracy for the Alzheimer’s Dataset and 96.25% accuracy for the ADNI dataset. Moreover, a better performance in terms of accuracy is demonstrated over other state-of-the-art approaches.
Are Smart Homes Adequate for Older Adults with Dementia?
Authors: Chimamiwa Gibson , Giaretta Alberto , Alirezaie Marjan , Pecora Federico , Loutfi Amy
Published: June 2022

Smart home technologies can enable older adults, including those with dementia, to live more independently in their homes for a longer time. Activity recognition, in combination with anomaly detection, has shown the potential to recognise users’ daily activities and detect deviations. However, activity recognition and anomaly detection are not sufficient, as they lack the capacity to capture the progression of patients’ habits across the different stages of dementia. To achieve this, smart homes should be enabled to recognise patients’ habits and changes in habits, including the loss of some habits. In this study, we first present an overview of the stages that characterise dementia, alongside real-world personas that depict users’ behaviours at each stage. Then, we survey the state of the art on activity recognition in smart homes for older adults with dementia, including the literature that combines activity recognition and anomaly detection. We categorise the literature based on goals, stages of dementia, and targeted users. Finally, we justify the necessity for habit recognition in smart homes for older adults with dementia, and we discuss the research challenges related to its implementation.
Enhancing Precision with an Ensemble Generative Adversarial Network for Steel Surface Defect Detectors (EnsGAN-SDD)
Authors: Akhyar Fityanul , Furqon Elvin Nur , Lin Chih-Yang
Published: June 2022

Defects are the primary problem affecting steel product quality in the steel industry. The specific challenges in developing detect defectors involve the vagueness and tiny size of defects. To solve these problems, we propose incorporating super-resolution technique, sequential feature pyramid network, and boundary localization. Initially, the ensemble of enhanced super-resolution generative adversarial networks (ESRGAN) was proposed for the preprocessing stage to generate a more detailed contour of the original steel image. Next, in the detector section, the latest state-of-the-art feature pyramid network, known as De-tectoRS, utilized the recursive feature pyramid network technique to extract deeper multi-scale steel features by learning the feedback from the sequential feature pyramid network. Finally, Side-Aware Boundary Localization was used to precisely generate the output prediction of the defect detectors. We named our approach EnsGAN-SDD. Extensive experimental studies showed that the proposed methods improved the defect detector’s performance, which also surpassed the accuracy of state-of-the-art methods. Moreover, the proposed EnsGAN achieved better performance and effectiveness in processing time compared with the original ESRGAN. We believe our innovation could significantly contribute to improved production quality in the steel industry.
Multi-Integration Time Adaptive Selection Method for Superframe High-Dynamic-Range Infrared Imaging Based on Grayscale Information
Authors: Tao Xingyu , Jin Weiqi , Yang Jianguo , Li Shuo , Su Binghua , Wang Minghe
Published: June 2022

With the development of superframe high-dynamic-range infrared imaging technology that extends the dynamic range of thermal imaging systems, a key issue that has arisen is how to choose different integration times to obtain an HDR fusion image that contains more information. This paper proposes a multi-integration time adaptive method, in order to address the lack of objective evaluation methods for the selection of superframe infrared images, consisting of the following steps: image evaluation indicators are used to obtain the best global exposure image (the optimal integration time); images are segmented by region-growing point to obtain the ambient/high-temperature regions, selecting the local optimum images with grayscale closest to the medium grayscale of the IR imaging system for the two respective regions (lowest and highest integration time); finally, the three images above are fused and enhanced to achieve HDR infrared imaging. By comparing this method with some existing integration time selection methods and applying the proposed method to some typical fusion methods, via subjective and objective evaluation, the proposed method is shown to have obvious advantages over existing algorithms, and it can optimally select the images from different integration time series images to form the best combination that contains full image information, expanding the dynamic range of the IR imaging system.
Implementing a Hand Gesture Recognition System Based on Range-Doppler Map
Authors: Jhaung Yu-Chiao , Lin Yu-Ming , Zha Chiao , Leu Jenq-Shiou , Köppen Mario
Published: June 2022

There have been several studies of hand gesture recognition for human–machine interfaces. In the early work, most solutions were vision-based and usually had privacy problems that make them unusable in some scenarios. To address the privacy issues, more and more research on non-vision-based hand gesture recognition techniques has been proposed. This paper proposes a dynamic hand gesture system based on 60 GHz FMCW radar that can be used for contactless device control. In this paper, we receive the radar signals of hand gestures and transform them into human-understandable domains such as range, velocity, and angle. With these signatures, we can customize our system to different scenarios. We proposed an end-to-end training deep learning model (neural network and long short-term memory), that extracts the transformed radar signals into features and classifies the extracted features into hand gesture labels. In our training data collecting effort, a camera is used only to support labeling hand gesture data. The accuracy of our model can reach 98%.
Upgrading of the L-P Band Cryogenic Receiver of the Sardinia Radio Telescope: A Feasibility Study
Authors: Ladu Adelaide , Schirru Luca , Gaudiomonte Francesco , Marongiu Pasqualino , Angius Gianmarco , Perini Federico , Vargiu Gian Paolo
Published: June 2022

The Sardinia Radio Telescope is a quasi-Gregorian system with a shaped 64 m diameter primary reflector and a 7.9 m diameter secondary reflector. It was designed to operate with high efficiency across the 0.3–116 GHz frequency range. The telescope is equipped with a cryogenic coaxial dual-frequency L-P band receiver, which covers a portion of the P-band (305–410 MHz) and the L-band (1300–1800 MHz). Although this receiver has been used for years in its original design, with satisfactory results, it presents some parts that could be upgraded in order to improve the performances of the system. With the passing of time and with technology advances, the presence of unwanted human-made signals in the area around the telescope, known as radio frequency interferences, has grown exponentially. In addition, the technology of the receiver electronic control system became obsolete and it could be replaced with next-generation electronic boards, which offer better performances both service reliability and low generation of unwanted radio frequency signals. In this paper, a feasibility study for improving the L-P band receiver is discussed, taking into account the mitigation of the main radio frequency interferences. With this study, it is possible to have a sensitive instrument that can be used for scientific research at low frequencies (P- and L-bands), which are usually populated by signals from civil and military mobile communications, TV broadcasting and remote sensing applications.
Development of an Electronic Stethoscope and a Classification Algorithm for Cardiopulmonary Sounds
Authors: Wu Yu-Chi , Han Chin-Chuan , Chang Chao-Shu , Chang Fu-Lin , Chen Shi-Feng , Shieh Tsu-Yi , Chen Hsian-Min , Lin Jin-Yuan
Published: June 2022

With conventional stethoscopes, the auscultation results may vary from one doctor to another due to a decline in his/her hearing ability with age or his/her different professional training, and the problematic cardiopulmonary sound cannot be recorded for analysis. In this paper, to resolve the above-mentioned issues, an electronic stethoscope was developed consisting of a traditional stethoscope with a condenser microphone embedded in the head to collect cardiopulmonary sounds and an AI-based classifier for cardiopulmonary sounds was proposed. Different deployments of the microphone in the stethoscope head with amplification and filter circuits were explored and analyzed using fast Fourier transform (FFT) to evaluate the effects of noise reduction. After testing, the microphone placed in the stethoscope head surrounded by cork is found to have better noise reduction. For classifying normal (healthy) and abnormal (pathological) cardiopulmonary sounds, each sample of cardiopulmonary sound is first segmented into several small frames and then a principal component analysis is performed on each small frame. The difference signal is obtained by subtracting PCA from the original signal. MFCC (Mel-frequency cepstral coefficients) and statistics are used for feature extraction based on the difference signal, and ensemble learning is used as the classifier. The final results are determined by voting based on the classification results of each small frame. After the testing, two distinct classifiers, one for heart sounds and one for lung sounds, are proposed. The best voting for heart sounds falls at 5–45% and the best voting for lung sounds falls at 5–65%. The best accuracy of 86.9%, sensitivity of 81.9%, specificity of 91.8%, and F1 score of 86.1% are obtained for heart sounds using 2 s frame segmentation with a 20% overlap, whereas the best accuracy of 73.3%, sensitivity of 66.7%, specificity of 80%, and F1 score of 71.5% are yielded for lung sounds using 5 s frame segmentation with a 50% overlap.
Development of a New Integrated System for Vital Sign Monitoring in Small Animals
Authors: Oliveira Regina G. , Correia Pedro M. M. , Silva Ana L. M. , Encarnação Pedro M. C. C. , Ribeiro Fabiana M. , Castro Ismael F. , Veloso João F. C. A.
Published: June 2022

Monitoring the vital signs of mice is an essential practice during imaging procedures to avoid populational losses and improve image quality. For this purpose, a system based on a set of devices (piezoelectric sensor, optical module and thermistor) able to detect the heart rate, respiratory rate, body temperature and arterial blood oxygen saturation (SpO2) in mice anesthetized with sevoflurane was implemented. Results were validated by comparison with the reported literature on similar anesthetics. A new non-invasive electrocardiogram (ECG) module was developed, and its first results reflect the viability of its integration in the system. The sensors were strategically positioned on mice, and the signals were acquired through a custom-made printed circuit board during imaging procedures with a micro-PET (Positron Emission Tomography). For sevoflurane concentration of 1.5%, the average values obtained were: 388 bpm (beats/minute), 124 rpm (respirations/minute) and 88.9% for the heart rate, respiratory rate and SpO2, respectively. From the ECG information, the value obtained for the heart rate was around 352 bpm for injectable anesthesia. The results compare favorably to the ones established in the literature, proving the reliability of the proposed system. The ECG measurements show its potential for mice heart monitoring during imaging acquisitions and thus for integration into the developed system.
Development of Magnetically Levitated Rotary Table for Repetitive Trajectory Tracking
Authors: Xu Fengqiu , Zhang Kaiyang , Xu Xianze
Published: June 2022

The magnetic levitation system has been considered as a promising actuator in micromachining areas of study. In order to improve the tracking performance and disturbance rejection of the magnetically levitated rotary table, an iterative learning PID control strategy with disturbance compensation is proposed. The estimated disturbance compensates for the control signals to enhance the active disturbance rejection ability. The iterative learning control is used as a feed-forward unit to further reduce the trajectory tracking error. The convergence and stability of the iterative learning PID with disturbance compensation are analysed. A series of comparative experiments are carried out on the in-house, custom-made, magnetically levitated rotary table, and the experimental results highlight the superiority of the proposed control strategy. The iterative learning PID with disturbance compensation enables the magnetically levitated rotary table to realize good tracking performance with complex external disturbance. The proposed control strategy strengthens the applicability of magnetically levitated systems in the mechanism manufacturing area.
Prediction-Based Human-Robot Collaboration in Assembly Tasks Using a Learning from Demonstration Model
Authors: Zhang Zhujun , Peng Gaoliang , Wang Weitian , Chen Yi , Jia Yunyi , Liu Shaohui
Published: June 2022

Most robots are programmed to carry out specific tasks routinely with minor variations. However, more and more applications from SMEs require robots work alongside their counterpart human workers. To smooth the collaboration task flow and improve the collaboration efficiency, a better way is to formulate the robot to surmise what kind of assistance a human coworker needs and naturally take the right action at the right time. This paper proposes a prediction-based human-robot collaboration model for assembly scenarios. An embedded learning from demonstration technique enables the robot to understand various task descriptions and customized working preferences. A state-enhanced convolutional long short-term memory (ConvLSTM)-based framework is formulated for extracting the high-level spatiotemporal features from the shared workspace and predicting the future actions to facilitate the fluent task transition. This model allows the robot to adapt itself to predicted human actions and enables proactive assistance during collaboration. We applied our model to the seats assembly experiment for a scale model vehicle and it can obtain a human worker’s intentions, predict a coworker’s future actions, and provide assembly parts correspondingly. It has been verified that the proposed framework yields higher smoothness and shorter idle times, and meets more working styles, compared to the state-of-the-art methods without prediction awareness.
Doped Tin Dioxide (d-SnO2) and Its Nanostructures: Review of the Theoretical Aspects, Photocatalytic and Biomedical Applications
Authors: Pinto Alexandre H. , Nogueira Andre E. , Dalmaschio Cleocir J. , Frigini Iago N. , de Almeida Jéssica C. , Ferrer Mateus M. , Berengue Olivia M. , Gonçalves Rosana A. , de Mendonça Vagner R.
Published: June 2022

Nanomaterials based on metal oxides are extensively studied for several applications due to their versatility. Improvements in their performances can be obtained due to specific structural modifications. One possible modification is by doping the crystal structure, which can affect the materials structure and properties, especially in nanosized particles. Electronic features are among the properties that can be modified through the doping process, consequently morphological and optical parameters can also be controlled by this process. In this sense, this review presents some modifications to tin dioxide (SnO2), one the most studied materials, mainly through the doping process and their impact on several properties. The article starts by describing the SnO2 structural features and the computational models used to explain the role of the doping process on these features. Based on those models, some applications of doped SnO2, such as photocatalytic degradation of pollutants, CO2 reduction, and desulfurization of fossil fuels are presented and discussed. Additionally, the review describes many biological applications related to antimicrobial activity for doped SnO2 and its nanostructures. Although most of the examples presented in this article are based on the doped SnO2, it also presents examples related to SnO2 composites with other nanomaterials forming heterojunctions. The metal oxides SnO2, doped-SnO2 and their nanostructures are promising materials, with results reported in many fields presented in this review, such as theoretical and computational chemistry, environmental remediation, nanoparticle morphology control, fossil fuels improvement, and biomedical applications. Although widely explored, there are still fields for innovation and advances with tin dioxide nanostructures, for example, in transparent conducting oxides, in forensics as materials for latent fingerprints visualization, and sensors in medicine for detection of exhaled volatile organic compounds. Therefore, this article aims to be a reference regarding correlating the doping processes and the properties presented by the SnO2 nanostructures.
Scientometric Analysis and AHP for Hierarchizing Criteria Affecting Construction Equipment Operators’ Performance
Authors: Petroutsatou Kleopatra , Ladopoulos Ilias , Tsakelidou Konstantina
Published: June 2022

The construction sector constitutes a significant indicator of a country’s economic growth. Construction equipment is an integral part of every construction project, and its contribution during construction determines any project’s completion. It also represents a significant capital investment for companies in this sector. A major strategic goal for such companies is the increase in the equipment’s productivity, which is affected mostly by its operators. The aim of this research is to recognize and prioritize the criteria affecting the performance of construction equipment operators. Scientometric analysis, using VOSViewer software, was implemented for the formation of different kinds of bibliometric networks, proposing a holistic approach to this research field. Those networks delineated the field with regard to construction equipment operators and revealed the correlations between the network’s items, which were formed because of previous research, and finally, conclusions were drawn. An extensive literature review in conjunction with structured interviews with experts and operators determined the factors affecting the operators’ performance, with a view to creating a hybrid decision model based on the Analytical Hierarchy Process (AHP), as implemented by the Transparent Choice tool. Many experts evaluated the criteria affecting the operators’ performance, leading to remarkable conclusions. Moreover, a few pointers for future research are provided.
Green Bonds and Commodities: A New Asymmetric Sustainable Relationship
Authors: Tsagkanos Athanasios , Sharma Aarzoo , Ghosh Bikramaditya
Published: June 2022

In this study we examine the relationship between corporate green bonds and commodities (both perishable & non-perishable) that attracts very little attention in relative literature. For the first time, we investigate a long-term relationship between green bonds and commodities including a significantly higher number of commodities and observations. Furthermore, we adopt a novel methodology, the VaR (value at risk) based copulas, to describe the asymmetric risk spillover between green bonds and commodities by considering the asymmetric tail distribution. Our results reveal an insignificant risk spillover effect from commodity market uncertainty. Further, we found non-perishable commodities are transmitting risk to perishable commodities (barring lead). In addition, in contrast to other similar studies the risk spillover is comparatively higher regarding lead, gold, and agriculture commodities as against copper and silver. On the other hand, energy commodities have the least spillover effect. Finally, these results have several important implications for investors as well as for policymakers.
Effect of Androgen Deprivation Therapy on the Results of PET/CT with 18F-Fluciclovine in Patients with Metastatic Prostate Cancer
Authors: Bach-Gansmo Tore , Korsan Katrine , Bogsrud Trond Velde
Published: June 2022

Background: 18F-fluciclovine is a positron emission tomography (PET) radiotracer approved for the detection of prostate cancer recurrence. No effect of androgen deprivation therapy (ADT) on its performance has been established. Purpose: To study the impact of concurrent ADT on disease detection with 18F-fluciclovine PET in patients with prostate cancer. Materials and Methods: Data from patients with prostate cancer who had been receiving ADT for ≥3 months at the time of undergoing an 18F-fluciclovine PET/CT at our institution were retrospectively reviewed. Seventy-three scans from 71 patients were included. The scans indicated rising prostate-specific antigen (n = 58), staging advanced disease (n = 4) or therapeutic monitoring (n = 9). Patients’ medical records provided baseline clinical data and post-scan outcomes (median follow-up 40 months). Results: Malignant lesions with increased uptake of 18F-fluciclovine were detected in 60/73 (82%) scans; 33 (45%) had lesions in the prostate/bed and 46 (63%) in extraprostatic sites. Patients received ADT for a median of 2 years (range 3 months to >10 years) pre-scan. The time on ADT did not influence detection; the detection rates were 89% for patients who had received ADT for <1 year, 63% for a treatment period of 1–<2 years, 83% for 2–4 years, 78% for >4–10 years, and 67% for a treatment period of >10 years. Conclusion: 18F-fluciclovine detected recurrent or metastatic lesions in 82% of patients with prostate cancer receiving ADT. The rates achieved in the present study are consistent with widely reported data for 18F-fluciclovine PET/CT, suggesting that withdrawal of ADT before scanning is not necessary.
Addressing Negative Externalities of Urban Development: Toward a More Sustainable Approach
Authors: Correia Christopher R. , Roseland Mark
Published: June 2022

The sheer size, growth, and complexity of cities worldwide are creating an ever-increasing burden of negative externalities on society and the environment. This systematic review aims to illuminate the broad range of negative urban development externalities and to analyze them in way that sharpens our ability to perceive, anticipate, and manage them. After finding that negative urban development externalities are more complex and diverse than has been previously articulated in the literature, the paper categorizes a representative sample by type (social, environmental, and economic) and identifies three modes of impact (visibility, emergence, and distribution) that make them extremely challenging to anticipate and mitigate. The most problematic negative externalities are social or environmental, with low visibility, cumulative patterns of emergence, and effects that extend beyond regulating jurisdictions. The analysis then draws on welfare economics to strengthen the case for the proactive management of these negative externalities and analyzes the competencies and capacities of local governments to strategically intervene in order to more effectively achieve sustainable development.
Toward Sustainable Water Resources Management in the Tunisian Citrus Sector: Impact of Pricing Policies on Water Resources Reallocation
Authors: Ajroudi Najla Hajbi , Dhehibi Boubaker , Lasram Asma , Dellagi Hatem , Frija Aymen
Published: June 2022

This study aims to analyse Tunisian farmers’ ability to pay (ATP) in a citrus area and propose a penalising price strategy based on the block-pricing process to decrease over-irrigation without affecting farmers’ incomes. The methodology is based on the residual imputation approach to determine farmers’ ATP, a stochastic production frontier to estimate the technical efficiency to determine optimal water irrigation quantity and calculation of the price elasticity of demand for an effective penalty and the Gini index before and after penalisation to study equity improvement. A survey was carried out on a sample of 147 citrus farms in the Nabeul Governorate, Northeastern Tunisia. The technical efficiency analysis confirms that an optimal quantity of 5000 m3/ha guarantees the maximisation of yields and profits. Above this quantity, the amount of overused water could be penalised without significantly affecting farmers’ incomes. Results also reveal that water overconsumption represents 28% of available resources and the ATP varies according to technical efficiency. Therefore, the proposed penalty system could reduce water overconsumption by 44.56% without deteriorating agricultural welfare. To improve water management as well as farmers’ welfare, this study recommends an increase in the technical efficiency level of farms to optimise all production factors for any implemented pricing policy.
Ecotoxicological Consequences of the Abatement of Contaminants of Emerging Concern by Ozonation—Does Mixture Complexity Matter?
Authors: Jesus Fátima , Bernardo Carla , Martins Rui C. , Gomes João , Pereira Joana Luísa
Published: June 2022

Ozonation has been used to degrade persistent water contaminants, namely, pharmaceuticals and personal care products (PPCPs). However, ozonation can lead to by-products that can be more toxic than the parent compounds. This work aims to assess whether the ecotoxicological effects of ozonation are modified as the initial matrix being treated increases in complexity, considering mixtures of 2, 3, 4 and 5 PPCPs. The following PPCPs were used: two parabens (metylparaben (MP) and propylparaben (PP)), paracetamol (PCT), sulfamethoxazole (SMX) and carbamazepine (CBZ). The following model species were used to assess toxicity: the crustacean Daphnia magna, the microalgae Raphidocelis subcapitata, the macrophyte Lemna minor and the watercress Lepidium sativum. There was a trend of increased toxicity with increasing mixture complexity of the untreated samples, except for D. magna. The same was observed after ozonation with the exception of the mixture MP+PP, which showed high toxicity to all the tested species, namely 100% immobilization of D. magna. The toxicity of SMX to the primary producers decreased pronouncedly after ozonation, except for L. minor. This study highlights the importance of considering the complexity of the matrix being treated and of using an ecotoxicological test battery with a wide diversity of species for assessing ozonation efficiency.
Ideas of evolution and transformation of culture in the concept of Leslie White and their reflection in the socio-cultural processes of modernity
Authors:   Samara National Research University named after academician S.P. Korolev, Zhigalov A.V.
Published: June 2022

The article analyzes the dynamics of culture in our country and its influence on demographic processes expressed in statistical data. The basis of the analysis is the theoretical development of the concept of Leslie White.
Pedagogical conditions for the development of the technical creativity of students in college
Authors:   St. Petersburg “Automechanical College”, Verkhoturtsev D.E.
Published: June 2022

The article tells about the results of an investigation of the problem of the development of technical creativity of college students as a significant part of modern life. Particularly the pedagogical conditions which determine the effectiveness of such development are scientifically proved, the experimental base of the investigation on which they have been tested is given, guidances are given on their use in the broad educational practice of the domestic vocational education.
Communication culture of the Khmer ethnicity in Vietnam (Case: communication in family and community phum, soc)
Authors:   Socialist Republic of Vietnam, Tra Vinh University, Pham Tiét Khanh , Nguyen Thi Kieu Tien ,   Socialist Republic of Vietnam, Tra Vinh University
Published: June 2022

Communicative culture is one of the elements of culture. It bears the mark of the way of thinking, the way of education, the behavior of each person, the humanity of the community. Therefore, in each ethnic group, each country in general, and the Khmer people in Vietnam in particular, there are social codes of conduct suitable to cultural conditions, showing humanity through the behavior of each person. individuals in families and communities. The article approaches to study the communication culture of the Khmer in different languages, and the behavior between relationships within the family, phum, and squirrels of the Khmer. Since then, the study wishes to contribute to the development of behavioral culture, building a solid cultural foundation for individuals and ethnic Khmer people from the traditional cultural background and the development of Vietnamese society today.
Religion and the Great Silk Road: means of communication, contours of interaction, trade
Authors:   Kazakh Ablai Khan University of International Relations and World Languages, Doszhanova Akmaral Ivanovna
Published: June 2022

The article discusses the historical aspects of the functioning of the Great Silk Road from the point of view of the formation of world religions. The study of the formation of world religions is impossible without taking into account the study of the Great Silk Road as one of the factors of their spread. Religious topics themselves are quite difficult for objective scientific research, however, without the appropriate knowledge, religion today is perceived as a factor of fundamentalism that carries a potential danger. This perspective today dominates the mass consciousness and complicates the topic of interfaith relations, while during the period of the Great Silk Road, religion played a fundamental role and often served as a bridge between different cultures. The existing configuration along the entire length of the trade route of the Great Silk Road, i.e. China - Central Asia - the Eastern Mediterranean, continued to work according to the scheme where religion dictated its rules to politics, politics — to the economy, and the economy, in turn, strengthened or weakened religion. This closed cycle remained stable until and after the era of the Crusades and the Mongol conquests.
Science in public consciousness and spiritual culture
Authors:   Institute for Fundamental and Applied Research, Moscow University for the Humanities, Voskoboinikov Anatoliy Emmanuilovich
Published: June 2022

The article shows that an individual lives in culture and is a socio-cultural being, which means that one of the crucial parts of spiritual culture is social consciousness. It includes such components as science, philosophy, morality, art, religion, modern mythology and some others. The author shows how they coexist in a single social consciousness and integral culture and reveals their specifics. Philosophy embodies reality and the era in its deep and holistic worldview, religion - in faith, art - in experienced artistic images, morality - in a conscious moral duty, a sense of justice and responsibility. All these areas are clearly marked by human subjectivity, as they are associated with experiences, but the most objective one is science, the features of which are disclosed in the article. The materials of the article can be used in the educational process within the framework of the disciplines "Concepts of Modern Natural Science", "Science Theory and Methodology" and others.
Artificial intelligence in the context of the transhumanism concept: an ethical approach
Authors:   Moscow University for the Humanities, Gordeev Roman Mikhailovich
Published: June 2022

The author reveals the features of artificial intelligence, reflecting on the problem of machine achieving an ability to act and think within the framework of ethics. This is all the more important since investments in artificial intelligence (AI) systems are constantly growing, AI is becoming a strategically important area for all developed countries, and the impact of AI systems on society is rapidly increasing - if two decades ago, the field of machine ethics seemed interesting only to a small number of scientists as a field for theoretical research, today questions about methods and approaches to computability and algorithmization of moral judgments are becoming an essential applied area of knowledge.
The Place and Importance of the Imam in the Ottoman Local Administration: The Case of Bolu (the 19th and 20th centuries)
Authors: SÜME Mehmet
Published: June 2022

İmam, günümüzde cemaate namaz kıldıran kimse olarak tanımlanmaktadır. Osmanlı toplumu söz konusu olduğunda ise imam çok daha geniş anlamları ifade eder. Bunlar; kendine uyulan, önder, devlet başkanı, halife, sevk ve idare eden şeklinde sıralanabilir. Bu çalışmada imam kavramının “sevk ve idare eden” anlamından yola çıkarak, Osmanlı yerel yönetiminde üstlendiği görevler, Bolu örneği üzerinden açıklanmaya çalışılacaktır. Osmanlı taşra teşkilatı, eyalet, sancak, kaza, nahiye ve köy/mahalle gibi idarî birimlerinden meydana gelir. Bu teşkilatın alt birimleri olan köy ve mahallenin yönetiminden imam sorumlu olmuştur. İmamın Osmanlı yerel yönetiminde aldığı görevlerin başlangıcını devletin kuruluş aşamasına kadar götürebiliriz. İdarî, malî ve beledî alanlarda bu zaman diliminde pek çok görevi imam ifa etmiştir. 19. yüzyılın ilk yarısında muhtarlık teşkilatının kurulması, resmi olarak imamın görev ve sorumlulukları açısından bir kırılma noktası olmuştur. İmamın yürüttüğü pek çok görev muhtara devredildi. Ancak imam uygulamada, geçmişte yürüttüğü görevleri devletin yıkılışına kadar sürdürdü. Hatta özellikle kırsal kesim söz konusu olduğunda bu sürecin yakın zamanlara kadar devam ettiğini söyleyebiliriz. Bu çalışmada ağırlıklı olarak 19. yüzyıldaki geçiş süreci ve 20. yüzyılın başında meydana gelen gelişmeler ele alınacaktır.
Bionic Microbubble Neutrophil Composite for Inflammation-Responsive Atherosclerotic Vulnerable Plaque Pluripotent Intervention
Authors: Liu Fangfang , Mao Yang , Yan Jiaqi , Sun Yu , Xie Zhihua , Li Fei , Yan Fei , Zhang Hongbo , Zhang Pengfei
Published: June 2022

Rupture or erosion of inflammatory atherosclerotic vulnerable plaque is essential to acute coronary events, while the target intervene of vulnerable plaque is very challenging, due to the relatively small volume, high hemodynamic shear stress, and multifactorial nature of the lesion foci. Herein, we utilize the biological functionality of neutrophil and the versatility of microbubble in the acoustic field, to form Neu-balloon through CD11b antibody binding. The Neu-balloon inherits the advantage of neutrophils on firming the endothelium adhesion even at shear stress up to 16 dyne/cm
2
and also maintains the acoustic enhancement property from the microbubble, to accumulate at atherosclerotic lesions under acoustic in an atherosclerotic Apo E
-/-
mice model. Interestingly, Neo-balloon also has high and broad drug loading capacity, which enables the delivery of indocyanine green and miR-126a-5p into vulnerable plagues
in vivo
. Overall, the bionic Neu-balloon holds great potential to boost on-demand drug transportation into plaques
in vivo
.
Ensuring Global Health Equity in a Post-pandemic Economy
Authors: Labonté Ronald
Published: June 2022

With coronavirus disease 2019 (COVID-19) receding, many countries are pondering what a post-pandemic economy should look like. Some advocate a more inclusive stakeholder model of capitalism. Others caution that this would be insufficient to deal with our pre-pandemic crises of income inequality and climate change. Many countries emphasize a ‘green recovery’ with improved funding for health and social protection. Progressive tax reform and fiscal policy innovations are needed, but there is concern that the world is already tilting towards a new round of austerity. Fundamentally, the capitalist growth economy rests on levels of material consumption that are unsustainable and inequitable. More radical proposals thus urge ‘degrowth’ policies to reduce consumption levels while redistributing wealth and income to allow the poorer half of humanity to achieve an ethical life expectancy. We have the policy tools to do so. We need an activist public health movement to ensure there is sufficient political will to adopt them.