bluuebunny/crossref_metadata_2025 huggingface dataset:
Thiazole: A Versatile Standalone Moiety Contributing to the Development of Various Drugs and Biologically Active Agents
Authors: Arshad Mohammed F. , Alam Aftab , Alshammari Abdullah Ayed , Alhazza Mohammed Bader , Alzimam Ibrahim Mohammed , Alam Md Anish , Mustafa Gulam , Ansari Md Salahuddin , Alotaibi Abdulelah M. , Alotaibi Abdullah A. , Kumar Suresh , Asdaq Syed Mohammed Basheeruddin , Imran Mohd. , Deb Pran Kishore , Venugopala Katharigatta N. , Jomah Shahamah
Published: June 2022

For many decades, the thiazole moiety has been an important heterocycle in the world of chemistry. The thiazole ring consists of sulfur and nitrogen in such a fashion that the pi (π) electrons are free to move from one bond to other bonds rendering aromatic ring properties. On account of its aromaticity, the ring has many reactive positions where donor–acceptor, nucleophilic, oxidation reactions, etc., may take place. Molecules containing a thiazole ring, when entering physiological systems, behave unpredictably and reset the system differently. These molecules may activate/stop the biochemical pathways and enzymes or stimulate/block the receptors in the biological systems. Therefore, medicinal chemists have been focusing their efforts on thiazole-bearing compounds in order to develop novel therapeutic agents for a variety of pathological conditions. This review attempts to inform the readers on three major classes of thiazole-bearing molecules: Thiazoles as treatment drugs, thiazoles in clinical trials, and thiazoles in preclinical and developmental stages. A compilation of preclinical and developmental thiazole-bearing molecules is presented, focusing on their brief synthetic description and preclinical studies relating to structure-based activity analysis. The authors expect that the current review may succeed in drawing the attention of medicinal chemists to finding new leads, which may later be translated into new drugs.
Physiologic Transdermal Estradiol Replacement Mimics Effects of Endogenous Estrogen on Bone Outcomes in Hypoestrogenic Women with Anorexia Nervosa
Authors: Singhal Vibha , Nimmala Supritha , Slattery Meghan , Eddy Kamryn T. , Miller Karen K. , Klibanski Anne , Misra Madhusmita
Published: June 2022

Background: While physiologic estrogen replacement results in increases in areal bone mineral density (aBMD) in hypoestrogenic adolescent girls and young adult women with AN, data are lacking regarding its impact on measures of volumetric BMD (vBMD), bone geometry, and structure. Methods: 23 young women with anorexia nervosa (AN) and 27 normal-weight healthy controls (HC) between 14–25 years old were followed for 12 months. AN participants received transdermal 17β-estradiol (continuously) with 10 days of cyclic oral progesterone (100 mg daily) every month for the study duration (AN-E+). DXA was used to measure aBMD and body composition, high resolution peripheral quantitative CT (HRpQCT) to assess vBMD, bone geometry and structure at the distal radius and tibia, and microfinite element analysis to estimate strength. Results: Groups did not differ for age. Median baseline BMI z-scores were −1.13 (−1.58, −0.38) in AN-E+ vs. 0.08 (−0.40, 0.84) in HC (p < 0.0001). For most HRpQCT parameters and strength estimates, young women with AN receiving physiologic estrogen replacement demonstrated similar changes over 12 months as did normoestrogenic HC. Additionally, radial cortical tissue mineral density, cortical vBMD, and failure load increased (p = 0.01; p = 0.02; p = 0.004 respectively) over 12 months in AN-E+ compared to HC. Conclusions: With physiologic estrogen replacement, bone accrual improved in AN to approximate changes observed in normoestrogenic controls followed without any intervention, with additional benefits observed for cortical tissue mineral density, cortical vBMD, and failure load at the radius in AN vs. controls. Thus, this strategy for estrogen replacement effectively mimics the effects of endogenous estrogen on bone structure and estimated strength.
Effects of Dietary Fibers on Short-Chain Fatty Acids and Gut Microbiota Composition in Healthy Adults: A Systematic Review
Authors: Vinelli Valentina , Biscotti Paola , Martini Daniela , Del Bo’ Cristian , Marino Mirko , Meroño Tomás , Nikoloudaki Olga , Calabrese Francesco Maria , Turroni Silvia , Taverniti Valentina , Unión Caballero Andrea , Andrés-Lacueva Cristina , Porrini Marisa , Gobbetti Marco , De Angelis Maria , Brigidi Patrizia , Pinart Mariona , Nimptsch Katharina , Guglielmetti Simone , Riso Patrizia
Published: June 2022

There is an increasing interest in investigating dietary strategies able to modulate the gut microbial ecosystem which, in turn, may play a key role in human health. Dietary fibers (DFs) are widely recognized as molecules with prebiotic effects. The main objective of this systematic review was to: (i) analyze the results available on the impact of DF intervention on short chain fatty acids (SCFAs) production; (ii) evaluate the interplay between the type of DF intervention, the gut microbiota composition and its metabolic activities, and any other health associated outcome evaluated in the host. To this aim, initially, a comprehensive database of literature on human intervention studies assessing the effect of confirmed and candidate prebiotics on the microbial ecosystem was developed. Subsequently, studies performed on DFs and analyzing at least the impact on SCFA levels were extracted from the database. A total of 44 studies from 42 manuscripts were selected for the analysis. Among the different types of fiber, inulin was the DF investigated the most (n = 11). Regarding the results obtained on the ability of fiber to modulate total SCFAs, seven studies reported a significant increase, while no significant changes were reported in five studies, depending on the analytical methodology used. A total of 26 studies did not show significant differences in individual SCFAs, while the others reported significant differences for one or more SCFAs. The effect of DF interventions on the SCFA profile seemed to be strictly dependent on the dose and the type and structure of DFs. Overall, these results underline that, although affecting microbiota composition and derived metabolites, DFs do not produce univocal significant increase in SCFA levels in apparently healthy adults. In this regard, several factors (i.e., related to the study protocols and analytical methods) have been identified that could have affected the results obtained in the studies evaluated. Future studies are needed to better elucidate the relationship between DFs and gut microbiota in terms of SCFA production and impact on health-related markers.
Food Environments and Their Influence on Food Choices: A Case Study in Informal Settlements in Nairobi, Kenya
Authors: Downs Shauna M. , Fox Elizabeth L. , Mutuku Vincent , Muindi Zacharia , Fatima Tasneem , Pavlovic Irena , Husain Sana , Sabbahi Minna , Kimenju Simon , Ahmed Selena
Published: June 2022

The food environments that people have access to shape their food choices. The purpose of this study was to use mixed methods to characterize the external food environment in informal settlements in Nairobi, Kenya and to examine the individual factors that influence the way in which women interact with those environments to make food choices. We used a combination of food environment assessments (vendor mapping, collection of food prices, food quality assessments) and five focus group discussions with women (n = 26) in four villages within two informal settlements in Nairobi (Mukuru and Kibera) to better understand the drivers of food choice. We found a large number (n = 1163) of vendors selling a variety of food within the settlements. The highest number of vendors were selling fruits and/or vegetables; however, there was limited diversity of fruits available. Animal-source foods were considered relatively expensive as compared to plant-based foods, including prepared fried snacks. We found that the way women interacted with their food environments was influenced by individual factors such as income, time, convenience, and preferences. Our findings suggest that interventions targeting both the external food environment as well as individual factors such as income will be necessary to support healthy diets among low-income populations living in informal settlements in Kenya.
Placenta-Derived Mesenchymal-like Adherent Stromal Cells as an Effective Cell Therapy for Cocaine Addiction in a Rat Model
Authors: Pe’er-Nissan Hilla , Ahdoot-Levi Hadas , Betzer Oshra , Itzhak Pnina Shirel , Shraga-Heled Niva , Gispan Iris , Motiei Menachem , Doroshev Arthur , Anker Yaakov , Popovtzer Rachela , Ofir Racheli , Yadid Gal
Published: June 2022

Recent research points to mesenchymal stem cells’ potential for treating neurological disorders, especially drug addiction. We examined the longitudinal effect of placenta-derived mesenchymal stromal-like cells (PLX-PAD) in a rat model for cocaine addiction. Sprague–Dawley male rats were trained to self-administer cocaine or saline daily until stable maintenance. Before the extinction phase, PLX-PAD cells were administered by intracerebroventricular or intranasal routes. Neurogenesis was evaluated, as was behavioral monitoring for craving. We labeled the PLX-PAD cells with gold nanoparticles and followed their longitudinal migration in the brain parallel to their infiltration of essential peripheral organs both by micro-CT and by inductively coupled plasma-optical emission spectrometry. Cell locations in the brain were confirmed by immunohistochemistry. We found that PLX-PAD cells attenuated cocaine-seeking behavior through their capacity to migrate to specific mesolimbic regions, homed on the parenchyma in the dentate gyrus of the hippocampus, and restored neurogenesis. We believe that intranasal cell therapy is a safe and effective approach to treating addiction and may offer a novel and efficient approach to rehabilitation.
Assessing Drug-Induced Mitochondrial Toxicity in Cardiomyocytes: Implications for Preclinical Cardiac Safety Evaluation
Authors: Tang Xiaoli , Wang Zengwu , Hu Shengshou , Zhou Bingying
Published: June 2022

Drug-induced cardiotoxicity not only leads to the attrition of drugs during development, but also contributes to the high morbidity and mortality rates of cardiovascular diseases. Comprehensive testing for proarrhythmic risks of drugs has been applied in preclinical cardiac safety assessment for over 15 years. However, other mechanisms of cardiac toxicity have not received such attention. Of them, mitochondrial impairment is a common form of cardiotoxicity and is known to account for over half of cardiovascular adverse-event-related black box warnings imposed by the U.S. Food and Drug Administration. Although it has been studied in great depth, mitochondrial toxicity assessment has not yet been incorporated into routine safety tests for cardiotoxicity at the preclinical stage. This review discusses the main characteristics of mitochondria in cardiomyocytes, drug-induced mitochondrial toxicities, and high-throughput screening strategies for cardiomyocytes, as well as their proposed integration into preclinical safety pharmacology. We emphasize the advantages of using adult human primary cardiomyocytes for the evaluation of mitochondrial morphology and function, and the need for a novel cardiac safety testing platform integrating mitochondrial toxicity and proarrhythmic risk assessments in cardiac safety evaluation.
Galactosed and Reduction-Responsive Nanoparticles Assembled from Trimethylchitosan–Camptothecin Conjugates for Enhanced Hepatocellular Carcinoma Therapy
Authors: Fu Chen , Qin Jingcan , Liu Xinlong , Kong Fei
Published: June 2022

The targeted delivery of drugs to tumor cells and prevention of premature release before reaching the target is one of the key challenges to developing nanomedicines. In this paper, galactose decorated trimethyl chitosan (GT)–camptothecin (CPT) prodrug nanoparticles (GT-ss-CPT NPs) were prepared from GT-CPT conjugates linked by dithiodipropionic acid. The obtained GT-ss-CPT NPs were spherical with a particle size of 184.1 nm. GT-ss-CPT NPs displayed low drug release under physiological conditions, whereas efficient drug release was triggered by high GSH concentration. GT-ss-CPT NPs exhibited a higher antitumor effect both in vitro and in vivo than the free drug counterpart. More importantly, GT-ss-CPT NPs reduced the high systematic toxicity of CPT to tumor-bearing mice. In summary, GT-ss-CPT NPs can not only inhibit the premature release of CPT but also have a great potential for targeted hepatocellular carcinoma chemotherapy.
Synthesis and Evaluation of Small Molecule Drug Conjugates Harnessing Thioester-Linked Maytansinoids
Authors: Lo Chen-Fu , Chiu Tai-Yu , Liu Yu-Tzu , Huang Li-Rung , Yeh Teng-Kuang , Huang Kuan-Hsun , Liu Kuan-Liang , Hsu Chia-Yu , Fang Ming-Yu , Huang Yu-Chen , Hsu Tsu-An , Chen Chiung-Tong , Tsou Lun Kelvin
Published: June 2022

Ligand-targeting drug conjugates are a class of clinically validated biopharmaceutical drugs constructed by conjugating cytotoxic drugs with specific disease antigen targeting ligands through appropriate linkers. The integrated linker-drug motif embedded within such a system can prevent the premature release during systemic circulation, thereby allowing the targeting ligand to engage with the disease antigen and selective accumulation. We have designed and synthesized new thioester-linked maytansinoid conjugates. By performing in vitro cytotoxicity, targeting ligand binding assay, and in vivo pharmacokinetic studies, we investigated the utility of this new linker-drug moiety in the small molecule drug conjugate (SMDC) system. In particular, we conjugated the thioester-linked maytansinoids to the phosphatidylserine-targeting small molecule zinc dipicolylamine and showed that Zn8_DM1 induced tumor regression in the HCC1806 triple-negative breast cancer xenograft model. Moreover, in a spontaneous sorafenib-resistant liver cancer model, Zn8_DM1 exhibited potent antitumor growth efficacy. From quantitative mRNA analysis of Zn8_DM1 treated-tumor tissues, we observed the elevation of gene expressions associated with a “hot inflamed tumor” state. With the identification and validation of a plethora of cancer-associated antigens in the “omics” era, this work provided the insight that antibody- or small molecule-based targeting ligands can be conjugated similarly to generate new ligand-targeting drug conjugates.
Correction: Al-Harrasi et al. Development and Characterization of Chitosan and Porphyran Based Composite Edible Films Containing Ginger Essential Oil. Polymers 2022, 14, 1782
Authors: Al-Harrasi Ahmed , Bhtaia Saurabh , Al-Azri Mohammed Said , Makeen Hafiz A. , Albratty Mohammed , Alhazmi Hassan A. , Mohan Syam , Sharma Ajay , Behl Tapan
Published: June 2022

In the original publication [...]
Development and Characterization of Oral Raft Forming In Situ Gelling System of Neratinib Anticancer Drug Using 32 Factorial Design
Authors: Hani Umme , Rahamathulla Mohamed , Osmani Riyaz Ali M. , Begum M.Yasmin , Wahab Shadma , Ghazwani Mohammed , Fatease Adel Al , Alamri Ali H. , Gowda Devegowda V. , Alqahtani Ali
Published: June 2022

Neratinib (NTB) is an irreversible inhibitor of pan-human epidermal growth factor receptor (HER-2) tyrosine kinase and is used in the treatment of breast cancer. It is a poorly aqueous soluble drug and exhibits extremely low oral bioavailability at higher pH, leading to a diminishing of the therapeutic effects in the GIT. The main objective of the research was to formulate an oral raft-forming in situ gelling system of NTB to improve gastric retention and drug release in a controlled manner and remain floating in the stomach for a prolonged time. In this study, NTB solubility was enhanced by polyethylene glycol (PEG)-based solid dispersions (SDs), and an in situ gelling system was developed and optimized by a two-factor at three-level (32) factorial design. It was analyzed to study the impact of two independent variables viz sodium alginate [A] and HPMC K4M [B] on the responses, such as floating lag time, percentage (%) water uptake at 2 h, and % drug release at 6 h and 12 h. Among various SDs prepared using PEG 6000, formulation 1:3 showed the highest drug solubility. FT-IR spectra revealed no interactions between the drug and the polymer. The percentage of drug content in NTB SDs ranged from 96.22 ± 1.67% to 97.70 ± 1.89%. The developed in situ gel formulations exhibited a pH value of approximately 7. An in vitro gelation study of the in situ gel formulation showed immediate gelation and was retained for a longer period. From the obtained results of 32 factorial designs, it was observed that all the selected factors had a significant effect on the chosen response, supporting the precision of design employed for optimization. Thus, the developed oral raft-forming in situ gelling system of NTB can be a promising and alternate approach to enhance retention in the stomach and to attain sustained release of drug by floating, thereby augmenting the therapeutic efficacy of NTB.
A Study on Highly Effective Electromagnetic Wave Shield Textile Shell Fabrics Made of Point Polyester/Metallic Core-Spun Yarns
Authors: Huang Chen-Hung , Hsu Po-Wen , Ke Zhao-We , Lin Jian-Hong , Shiu Bing-Chiuan , Lou Ching-Wen , Lin Jia-Horng
Published: June 2022

In this study, stainless steel (SS) filaments are wrapped in Ge fibers to form core-spun yarns. The yarns along with 500 D polyester (PET) fibers undergo weaving, thereby forming functional woven fabrics. The experiment is composed of two parts:yarns and fabrics. The yarns are twisted with TPI of 8, 9, 10, 11, and 12, and then tested for tensile strength and tensile elongation. The yarns possess mechanical properties that are dependent on the TPI—the higher the TPI, the better the mechanical properties. The maximal mechanical properties occur when the core-spun yarns are made of 12 TPI where the maximal tensile strength is 5.26 N and the lowest elongation is 43.2%. As for the functional woven fabrics, they are made of Ge/SS core-spun yarns as the weft yarns and 500 D PET yarns as the warp yarns. The tensile strength, tensile elongation, negative ion release, electromagnetic interference shielding effectiveness (EMI SE), and air permeability tests are conducted, determining the optimal woven fabrics. The 12 TPI core-spun yarns provide the woven fabrics with the maximal tensile strength of 153.6 N and the optimal elongation at break of 10.08%. In addition, the woven fabrics made with 8 or 9 TPI core-spun yarns exhibit an optimal EMI SE of 41 dB, an optimal air permeability of 212 cm3/cm2/s, and an optimal release amount of negative ion of 550–600 ions/cc. The proposed woven fabrics have a broad range of applications, such as functional garments and bedding.
The Distinctive Mindfulness of Dzogchen: Jigme Lingpa’s Advice on Meta-Awareness and Nondual Meditation
Authors: Deroche Marc-Henri , Sheehy Michael R.
Published: June 2022

For Indian Buddhists and their Tibetan successors, the faculty of “mindfulness” (Skt. smṛti, Tib. dran pa) has been interpreted as the foundation of the threefold development of wisdom (study, reflection, cultivation). Such a model was, in Tibet, the hallmark of the gradual approach to awakening, whereas in the simultaneous approach, the state beyond ordinary mindfulness was emphasized. The complementarity of both approaches has been an essential issue, especially for the Nyingma tradition, which holds the direct teaching of Dzogchen to be the penultimate. To elucidate the operations of mindfulness in this context, this paper analyzes two guidance texts on mindfulness by Rigdzin Jigme Lingpa (1730–1798), Ocean of Qualities: Advice on Mindfulness and Cudgel to Discern the Real: Advice that Shines from Mindfulness and Meta-Awareness, the latter translated into English for the first time in this paper. As this study shows, Jigme Lingpa articulates a twofold typology of mindfulness, first a mindfulness that is effortful and conditioned, and secondarily the distinctive mindfulness of Dzogchen that is inseparable from pure awareness or rigpa (rig pa). Jigme Lingpa thus applies mindfulness to integrate Buddhist teachings and make sense of alternative modes of practice along the Dzogchen path.
A Buddhist Biography Project: Story-Telling, Spiritual Connection, and Intergenerational Exchange
Authors: Dhavernas Catherine , Williams Carmel
Published: June 2022

This descriptive article discusses the development, delivery, and impact of the “Biography Project”. The project is a research and teaching initiative focused on both enhancing the quality of life of older persons, and providing university students across diverse degree programs the opportunity to learn about and engage first-hand with the challenges that confront older adults living in residential aged care. In accounting for the project and its objectives, the article explores the Buddhist values that underpin the project’s approach to teaching, and the important role of spirituality in training students to engage older people in telling the stories of their lives.
Unsupervised Insurance Fraud Prediction Based on Anomaly Detector Ensembles
Authors: Vosseler Alexander
Published: June 2022

The detection of anomalous data patterns is one of the most prominent machine learning use cases in industrial applications. Unfortunately very often there are no ground truth labels available and therefore it is good practice to combine different unsupervised base learners with the hope to improve the overall predictive quality. Here one of the challenges is to combine base learners that are accurate and divers at the same time, where another challenge is to enable model explainability. In this paper we present BHAD, a fast unsupervised Bayesian histogram anomaly detector, which scales linearly with the sample size and the number of attributes and is shown to have very competitive accuracy compared to other analyzed anomaly detectors. For the problem of model explainability in unsupervised outlier ensembles we introduce a generic model explanation approach using a supervised surrogate model. For the problem of ensemble construction we propose a greedy model selection approach using the mutual information of two score distributions as a similarity measure. Finally we give a detailed description of a real fraud detection application from the corporate insurance domain using an outlier ensemble, we share various feature engineering ideas as well as discuss practical challenges.
Existence of Glacier Anomaly in the Interior and Northern Tibetan Plateau between 2000 and 2012
Authors: Liu Lin , Jiang Liming , Wang Hansheng , Sun Yafei
Published: June 2022

There was sufficient evidence to indicate a nearly balanced glacier mass change (termed glacier anomaly) for Karakoram Mts. since the 1970s, in contrast to worldwide glacier mass losses caused by climate warming. Recently, this anomalous phenomenon was detected over the neighboring western Kunlun and Pamir Mts. However, the southeastern limit of this glacier anomaly remains uncertain, owing to the paucity of glacier mass balance observations across the interior and northern Tibetan Plateau (INTP). In this study, we presented a decadal glacier mass balance estimation in the INTP by differencing the SRTM DEM with the topographic data produced from TanDEM-X bistatic InSAR images. From 2000 to 2012, decade-average glacier mass balances of between −0.339 ± 0.040 and 0.237 ± 0.078 m w.e. yr−1 were detected over 22 glacierized areas. Significantly, we found a gradient and switch of glacier mass loss over the southeastern portion to glacier mass gain over the northwestern portion. This varying spatial pattern illustrates that glacier anomaly has existed over the northwestern or even central zone of the INTP since the early 21st century. This study provides important evidence for the model simulation of both glacier evolution and atmospheric circulations in investigating the prevailing mechanism of the regional anomalous phenomenon.
An Assessment of the GEDI Lasers’ Capabilities in Detecting Canopy Tops and Their Penetration in a Densely Vegetated, Tropical Area
Authors: Fayad Ibrahim , Baghdadi Nicolas , Lahssini Kamel
Published: June 2022

The Global Ecosystem Dynamics Investigation (GEDI), specifically designed to measure vertical forest structures, has acquired, since April 2019, more than 35 billion waveforms of Earth’s surface on a nearly global scale. GEDI is equipped with 3 identical 1064 nm lasers with a power of 10 mJ per shot, where 1 laser is split into 2 lasers, resulting in two 5 mJ coverage lasers and two 10 mJ full-power lasers. In this study, we evaluate the potential of GEDI’s four lasers to penetrate through canopies and detect the ground, and their capabilities to detect the top of the canopies over a tropical forest (in French Guiana) characterized by a dense canopy cover and tall trees. The accurate detection of both of these surfaces is the first step in characterizing vertical forest structures. The SRTM Digital Elevation Model (DEM) is used as a reference point for elevations while a canopy height model (CHM), derived from airborne and spaceborne LiDAR data, is used as a reference for canopy heights. In addition, the ground and canopy-top elevations estimated from NASA’s Land, Vegetation, and Ice Sensor (LVIS, 1064 nm full-waveform LiDAR, 5 mJ per shot, ~8 km altitude) are used as a benchmark for comparison with GEDI’s lasers. Results indicate that GEDI’s coverage and full-power lasers, even after the application of a preliminary filter that removes around 50% of acquisitions, tend to underestimate tree heights in densely vegetated, tall forests. Moreover, GEDI’s coverage lasers also exhibited a lower level of performance in comparison to both the full-power lasers and LVIS. Overall, the average estimated maximum canopy heights (RH100) for a CHM greater than 30 m was 24.4 m with the coverage lasers, 32.1 m with the full-power lasers, and 36.7 m with LVIS. The analysis of shots with high-beam sensitivity (sensitivity ≥ 98%) showed that they tend to have a better probability of reaching the ground and have better detection of canopy tops for both GEDI laser types. Nonetheless, GEDI’s coverage lasers still showed an underestimation of canopy heights with an average RH100 of 29.8 m, while for GEDI’s full-power lasers and LVIS, the average RH100 was 35.2 m and 37.7 m, respectively. Finally, the assessment of the acquisition time on the detection of the ground return and the top of the canopies showed that, for the coverage lasers, solar noise could affect the detection of the ground return as acquisitions made during early mornings or late afternoons have more penetration than shots acquired between 8 a.m. and 4 p.m. The effect of acquisition time on the detection of the tops of canopies showed that solar noise slightly affected the coverage lasers. Regarding the full-power lasers, the acquisition time of the shots seem to affect neither the penetration of the lasers, nor the detection of the tops of canopies.
Algorithms and Methods for the Fault-Tolerant Design of an Automated Guided Vehicle
Authors: Stetter Ralf
Published: June 2022

Researchers around the globe have contributed for many years to the research field of fault-tolerant control; the importance of this field is ever increasing as a consequence of the rising complexity of technical systems, the enlarging importance of electronics and software as well as the widening share of interconnected and cloud solutions. This field was supplemented in recent years by fault-tolerant design. Two main goals of fault-tolerant design can be distinguished. The first main goal is the improvement of the controllability and diagnosability of technical systems through intelligent design. The second goal is the enhancement of the fault-tolerance of technical systems by means of inherently fault-tolerant design characteristics. Inherently fault-tolerant design characteristics are, for instance, redundancy or over-actuation. This paper describes algorithms, methods and tools of fault-tolerant design and an application of the concept to an automated guided vehicle (AGV). This application took place on different levels ranging from conscious requirements management to redundant elements, which were consciously chosen, on the most concrete level of a technical system, i.e., the product geometry. The main scientific contribution of the paper is a methodical framework for fault-tolerant design, as well as certain algorithms and methods within this framework. The underlying motivation is to support engineers in design and control trough product development process transparency and appropriate algorithms and methods.
Real-Time Sound Source Localization for Low-Power IoT Devices Based on Multi-Stream CNN
Authors: Ko Jungbeom , Kim Hyunchul , Kim Jungsuk
Published: June 2022

Voice-activated artificial intelligence (AI) technology has advanced rapidly and is being adopted in various devices such as smart speakers and display products, which enable users to multitask without touching the devices. However, most devices equipped with cameras and displays lack mobility; therefore, users cannot avoid touching them for face-to-face interactions, which contradicts the voice-activated AI philosophy. In this paper, we propose a deep neural network-based real-time sound source localization (SSL) model for low-power internet of things (IoT) devices based on microphone arrays and present a prototype implemented on actual IoT devices. The proposed SSL model delivers multi-channel acoustic data to parallel convolutional neural network layers in the form of multiple streams to capture the unique delay patterns for the low-, mid-, and high-frequency ranges, and estimates the fine and coarse location of voices. The model adapted in this study achieved an accuracy of 91.41% on fine location estimation and a direction of arrival error of 7.43° on noisy data. It achieved a processing time of 7.811 ms per 40 ms samples on the Raspberry Pi 4B. The proposed model can be applied to a camera-based humanoid robot that mimics the manner in which humans react to trigger voices in crowded environments.
Machine Learning White-Hat Worm Launcher for Tactical Response by Zoning in Botnet Defense System
Authors: Pan Xiangnan , Yamaguchi Shingo
Published: June 2022

Malicious botnets such as Mirai are a major threat to IoT networks regarding cyber security. The Botnet Defense System (BDS) is a network security system based on the concept of “fight fire with fire”, and it uses white-hat botnets to fight against malicious botnets. However, the existing white-hat Worm Launcher of the BDS decides the number of white-hat worms, but it does not consider the white-hat worms’ placement. This paper proposes a novel machine learning (ML)-based white-hat Worm Launcher for tactical response by zoning in the BDS. The concept of zoning is introduced to grasp the malicious botnet spread with bias over the IoT network. This enables the Launcher to divide the network into zones and make tactical responses for each zone. Three tactics for tactical responses for each zone are also proposed. Then, the BDS with the Launcher is modeled by using agent-oriented Petri nets, and the effect of the proposed Launcher is evaluated. The result shows that the proposed Launcher can reduce the number of infected IoT devices by about 30%.
CNN Architectures and Feature Extraction Methods for EEG Imaginary Speech Recognition
Authors: Rusnac Ana-Luiza , Grigore Ovidiu
Published: June 2022

Speech is a complex mechanism allowing us to communicate our needs, desires and thoughts. In some cases of neural dysfunctions, this ability is highly affected, which makes everyday life activities that require communication a challenge. This paper studies different parameters of an intelligent imaginary speech recognition system to obtain the best performance according to the developed method that can be applied to a low-cost system with limited resources. In developing the system, we used signals from the Kara One database containing recordings acquired for seven phonemes and four words. We used in the feature extraction stage a method based on covariance in the frequency domain that performed better compared to the other time-domain methods. Further, we observed the system performance when using different window lengths for the input signal (0.25 s, 0.5 s and 1 s) to highlight the importance of the short-term analysis of the signals for imaginary speech. The final goal being the development of a low-cost system, we studied several architectures of convolutional neural networks (CNN) and showed that a more complex architecture does not necessarily lead to better results. Our study was conducted on eight different subjects, and it is meant to be a subject’s shared system. The best performance reported in this paper is up to 37% accuracy for all 11 different phonemes and words when using cross-covariance computed over the signal spectrum of a 0.25 s window and a CNN containing two convolutional layers with 64 and 128 filters connected to a dense layer with 64 neurons. The final system qualifies as a low-cost system using limited resources for decision-making and having a running time of 1.8 ms tested on an AMD Ryzen 7 4800HS CPU.
Development of Joint Activity Angle Measurement and Cloud Data Storage System
Authors: Tuan Chiu-Ching , Wu Yi-Chao , Yeh Wen-Ling , Wang Chun-Chieh , Lu Chi-Heng , Wang Shao-Wei , Yang Jack , Lee Tsair-Fwu , Kao Hsuan-Kai
Published: June 2022

In this study, we developed a range of motion sensing system (ROMSS) to simulate the function of the elbow joint, with errors less than 0.76 degrees and 0.87 degrees in static and dynamic verification by the swinging and angle recognition modules, respectively. In the simulation process, the ɣ correlation coefficient of the Pearson difference between the ROMSS and the universal goniometer was 0.90, the standard deviations of the general goniometer measurements were between ±2 degrees and ±2.6 degrees, and the standard deviations between the ROMSS measurements were between ±0.5 degrees and ±1.6 degrees. With the ROMSS, a cloud database was also established; the data measured by the sensor could be uploaded to the cloud database in real-time to provide timely patient information for healthcare professionals. We also developed a mobile app for smartphones to enable patients and healthcare providers to easily trace the data in real-time. Historical data sets with joint activity angles could be retrieved to observe the progress or effectiveness of disease recovery so the quality of care could be properly assessed and maintained.
Artificial Intelligence Algorithm-Based Economic Denial of Sustainability Attack Detection Systems: Cloud Computing Environments
Authors: Aldhyani Theyazn H. H. , Alkahtani Hasan
Published: June 2022

Cloud computing is currently the most cost-effective means of providing commercial and consumer IT services online. However, it is prone to new flaws. An economic denial of sustainability attack (EDoS) specifically leverages the pay-per-use paradigm in building up resource demands over time, culminating in unanticipated usage charges to the cloud customer. We present an effective approach to mitigating EDoS attacks in cloud computing. To mitigate such distributed attacks, methods for detecting them on different cloud computing smart grids have been suggested. These include hard-threshold, machine, and deep learning, support vector machine (SVM), K-nearest neighbors (KNN), random forest (RF) tree algorithms, namely convolutional neural network (CNN), and long short-term memory (LSTM). These algorithms have greater accuracies and lower false alarm rates and are essential for improving the cloud computing service provider security system. The dataset of nine injection attacks for testing machine and deep learning algorithms was obtained from the Cyber Range Lab at the University of New South Wales (UNSW), Canberra. The experiments were conducted in two categories: binary classification, which included normal and attack datasets, and multi-classification, which included nine classes of attack data. The results of the proposed algorithms showed that the RF approach achieved accuracy of 98% with binary classification, whereas the SVM model achieved accuracy of 97.54% with multi-classification. Moreover, statistical analyses, such as mean square error (MSE), Pearson correlation coefficient (R), and the root mean square error (RMSE), were applied in evaluating the prediction errors between the input data and the prediction values from different machine and deep learning algorithms. The RF tree algorithm achieved a very low prediction level (MSE = 0.01465) and a correlation R2 (R squared) level of 92.02% with the binary classification dataset, whereas the algorithm attained an R2 level of 89.35% with a multi-classification dataset. The findings of the proposed system were compared with different existing EDoS attack detection systems. The proposed attack mitigation algorithms, which were developed based on artificial intelligence, outperformed the few existing systems. The goal of this research is to enable the detection and effective mitigation of EDoS attacks.
Accounting for fixed assets and depreciable property: changes in 2022
Authors:   Department audit and corporate reporting, Faculty of taxes, audit and business analysis, Financial University under the Government of the Russian Federation, Moscow, Sotnikova L.V.
Published: June 2022

The article discusses, using numerous examples, changes in the accounting of fixed assets in connection with the entry into force from January 1, 2022 for the mandatory application of FSBU 6/2020 “Fixed Assets”: under the influence of changes in the useful life; under the influence of a change in the method of depreciation; when exchanging items of fixed assets. Significant changes have occurred in the tax accounting of fixed assets recognized as depreciable property: transfer and removal of fixed assets from conservation, introduction of depreciation rates into tax accounting to fully transfer the cost of fixed assets to tax expenses even when the useful life corresponding to the depreciable group of To the classifier, has already expired.
Control of the customer in the field of procurement over the fulfillment of obligations by the supplier (contractor, performers)
Authors:   Plekhanov Russian University of Economics, Titova E.I. , Prodanova N.A. ,   basic department Financial Control, Analysis and Audit of Moscow GKU, Plekhanov Russian University of Economics
Published: June 2022

The article discusses the main aspects devoted to the control carried out by the customer in the field of procurement. Control in procurement activities is an important component of the contract system of the Russian Federation. Customers, as well as suppliers (contractors, performers), are the main participants in the public procurement system. To ensure the proper operation of this system, customers are authorized to monitor the fulfillment of contract terms by suppliers. The customer is interested in timely and accurate execution of the terms of the contract, so this topic is very relevant.
Legal means of minimizing risks in labor relations: a note to the accountant
Authors:   Training and Design Laboratory for Interdisciplinary Development of IT Competencies, Plekhanov Russian University of Economics, Lebedev V.A. , Lebedeva E.I. ,   Non-profit Partnership “Institute of Professional Accountants and Auditors of Russia”
Published: June 2022

The legal means of reducing the risks of the employer in labor relations are considered, in particular, the use of the test period when hiring, the mechanism for verifying the employee’s compliance with the position assigned to the work; a comparative analysis of the features of the conclusion of a fixed-term employment contract and the test period for checking an employee entering into work is carried out; the consequences of the expiration of the labor contract and the test period when employment; the ratio of general and special provisions concerning the procedure and conditions for setting deadlines. The article considers the grounds for excluding the establishment of a test period when applying for a job, as well as cases when an employment contract can or should be concluded for a certain period.
Diplomacy of force and special military operation of the Russian Armed Forces in Ukraine: general and special
Authors:   Diplomatic Academy of the Ministry of Foreign Affairs of Russia, Vinokurov Vladimir I.
Published: June 2022

Russia's conduct of a special military operation in Ukraine has brought back to the agenda a long-known discussion among experts in the fi eld of foreign policy and diplomacy about the role of force in international relations. Claims about the possibility of using force in our time arose as a result of the appearance of nuclear weapons. Today, US politicians continue to assert that war will remain an acceptable instrument of national policy of states at the level of international subsystems, that is, in various regions. In their opinion, the power of a major power is capable of exerting an effective psychological influence on how often such conflicts will arise and what their outcome will be. At one time, Russia clearly outlined the "red line" in connection with attempts to integrate Ukraine into NATO and repeatedly and unequivocally warned that it would take active actions in response to this, i. e. use "hard force". In response to this, the United States and NATO have been fueling anti-Russian sentiments in Ukraine for a long time, considering it as a tool to deter Moscow and turning it into antiRussia. One of the components of this policy was the reckless expansion of NATO to the east, despite the obligations of non-expansion of the alliance. All this forced Russia to announce the conduct of a special military operation in Ukraine, the purpose of which is the de–Nazification and demilitarization of the neighboring state.
The history of the emergence and development of marketing
Authors:   Russian Academy of National Economy and Public Administration under the President of the Russian Federation, Nikolaeva M. A.
Published: June 2022

The article presents the author's view on the history of the emergence and development of marketing. In its essence, it does not differ significantly from the generally accepted history. The main difference is systematization by dividing the story into two stages and several stages. In addition, this systematization is based not on marketing concepts, but on its functions.
Modern retail trade in Russia: trends and trends of development, directions of innovative updating of business models
Authors:   Department of Enterprise Economics and Personnel Management, Donetsk National University of Economics and Trade named after M. Tugan-Baranovsky, Candidate of Economics, Kravchenko Elena Sergeevna , Karashchuk Oksana Sergeevna ,   Basic Department of Trade Policy, Plekhanov Russian University of Economics
Published: June 2022

The paper assesses the contribution of the retail sector to the socio-economic development of the state, examines the main development trends and examines trends in the structural transformation of trade formats. The main motivational factors of buying goods online and offline are analyzed. The expediency is reasoned and the key dominants of innovative renewal of business models of retail enterprises are substantiated.
Kentsel Dönüşüm Uygulaması Sonrası Suç Korkusu Üzerine Bir Değerlendirme: Denizli Aktepe Mahallesi Örneği
Authors: SAVAŞ YAVUZÇEHRE Pınar
Published: June 2022

Son dönemde özellikle gecekondu mahallelerinde uygulanan kentsel dönüşüm projelerinin fiziki hedefleri dışında mekânda yapılacak düzenlemeler sonrası suç unsurunu azaltmak da amaçları arasındadır. 2000’li yıllar sonrası hemen her Anadolu kentinde uygulanan kentsel dönüşüm projelerinin suç unsuruna etkileri de artık tartışılmaktadır. Denizli’de 2005-2009 yıllarında gerçekleştirilen kentsel dönüşüm projesi ile 2000 konut dönüşüme uğramıştır. Bu makalenin amacı Denizli Aktepe Mahallesinde gerçekleşen kentsel dönüşüm projesi sonrası mahallede yaşayanların suç korkusundaki değişimi ortaya koymaktır. 2019 yılında, mahallede 125 kişi ile anket yapılmıştır. Sonuç olarak; ankete katılanların kenti ve mahalleyi güvenli buldukları, komşularına güvendikleri, gece dışarı çıkmayı güvenli bulmadıkları, en çok evden hırsızlık suçu ile karşılaştıkları ve en fazla öldürülmekten korktukları bulgularına ulaşılmıştır. Kentsel dönüşüm projesi sonrası mahallede suç unsuru ve korkusu azalmış ancak yok olmamıştır.
Eski Anadolu Türkçesi Metinlerine Göre Bitkilerde İşaret Teorisi
Authors: DOĞAN Hüseyin
Published: June 2022

Bu çalışmada, bitkiler (Regnum: Plantae) özelinde 13. ve 15. yüzyıllar arasında Anadolu’da Türkçe yazınında İşaret Teorisi’nin yansımalarını göstermeye çalışacağız. İşaret Teorisi basitçe, (çalışmamız özelinde) bitkilerin bir parçası ya da tamamının insanın bir organına benzemesinin, söz konusu bitkinin ilgili organ üzerinde tedavi edici özellikler taşıdığına dair doğal bir kod olduğuna dair bir inanıştır. Bu inanışa göre, bir bitkinin kökleri ya da yaprakları saça benziyorsa, bu bitkinin saçla ilgili rahatsızlıklarda (dökülmesi, kırılması, erken ağarması, geç uzaması, vb.) faydalı olması beklenmektedir. İşaret Teorisi ayrıca, süte benzer bir usaresi olan bitkinin süt salgısını arttırdığı, bitkinin bir parçasının muayyen bir hayvanın organına benzemesi halinde o hayvandan gelecek zararlara karşı etkili olduğu, nemli bölgelerde yetişen bitkilerin rutubet kaynaklı hastalıklara iyi geleceği, vb. gibi geniş bir algı çerçevesine sahiptir. Benzeri, benzer özellikleri olması nedeniyle tedavi eden benzer’e, örneğin kokusu ile benzeyen başka bir bitki de zaman zaman benzer’in ikamesi olarak kullanılmıştır ve bu kullanım da teorinin kapsamı içinde değerlendirilmelidir. Bu anlayışa dair görüşlere Hint, Çin, Yunan ve Roma uygarlıklarının yazınlarında rastlanmaktadır. Bu görüş daha sonra mezkûr uygarlıkların metinlerinin Süryanice, Farsça, Arapça ve Türkçeye tercüme edilmeleri ile İslâm uygarlığında da karşılık bulmuştur.
Comparison of Indonesian and Finnish Education Curriculum
Authors:   Universitas Negeri Padang, Indonesia, Sunarti Vevi , Hafizah Hafizah ,   STKIP Ahlusunnah Bukitinggi, Indonesia, Rusdinal Rusdinal ,   Universitas Negeri Padang, Indonesia, Ananda Azwar ,   Universitas Negeri Padang, Indonesia, Gistituati Nurhizrah ,   Universitas Negeri Padang, Indonesia
Published: June 2022

Abstract: Purpose: This study aims at describing the planning of the education system that will be adapted that it is necessary to make comparisons in order to improve the quality of the education system and contribute to the government in considering making policies to improve the Indonesian education system. Research methodology: The research design is used a case study to compare the education system between Indonesia and Finnish and literature review to collect relevant research. Results: The results of the study indicated that the Indonesian education curriculum is classified as low because it is based on five curriculum components, namely objectives, contents-materials, media, learning strategies, and learning process. Limitations: This study focuses on the five curriculum components in the Indonesian education system generally, so that there is a gap that can be filled by future researchers by discussing more deeply along with examples from other countries. Contribution: This research contributes to curriculum policyholders in the Indonesian education system because it can be a reference for improving the quality of the Indonesian education system. Keywords: 1. Curriculum 2. Indonesia 3. Finnish