bluuebunny/crossref_metadata_2025 huggingface dataset:
Image Classification: A Survey
Authors:   Department of Computer Science and Engineering, Amity University Uttar Pradesh Lucknow Campus, India, Singh Ankita , Singh Pawan ,   Department of Computer Science and Engineering, Amity University Uttar Pradesh Lucknow Campus, India
Published: September 2021

The Classification of images is a paramount topic in artificial vision systems which have drawn a notable amount of interest over the past years. This field aims to classify an image, which is an input, based on its visual content. Currently, most people relied on hand-crafted features to describe an image in a particular way. Then, using classifiers that are learnable, such as random forest, and decision tree was applied to the extract features to come to a final decision. The problem arises when large numbers of photos are concerned. It becomes a too difficult problem to find features from them. This is one of the reasons that the deep neural network model has been introduced. Owing to the existence of Deep learning, it can become feasible to represent the hierarchical nature of features using a various number of layers and corresponding weight with them. The existing image classification methods have been gradually applied in real-world problems, but then there are various problems in its application processes, such as unsatisfactory effect and extremely low classification accuracy or then and weak adaptive ability. Models using deep learning concepts have robust learning ability, which combines the feature extraction and the process of classification into a whole which then completes an image classification task, which can improve the image classification accuracy effectively. Convolutional Neural Networks are a powerful deep neural network technique. These networks preserve the spatial structure of a problem and were built for object recognition tasks such as classifying an image into respective classes. Neural networks are much known because people are getting a state-of-the-art outcome on complex computer vision and natural language processing tasks. Convolutional neural networks have been extensively used.
Study on Design and Simulation of Temperature Control System
Authors:   Department of ECE, ASET, Amity University Lucknow Campus, India, Yadav Rahul , Singh Kamlesh Kumar ,   Department of ECE, ASET, Amity University Lucknow Campus, India
Published: September 2021

Temperature control system is nothing but a complicated process which is aimed to maintain the temperature in a particular defined area to a certain maxima or minima level or say defined in a range which is quite certain. We can witness this process commonly used in many parts of the India and many other countries. In recent times, we are witnessing a rapid growth in industries at global level which has led to globalization and industrialization which further has led the necessary use of the temperature control system and its application in these industries at day-to-day level in manufacturing and maintenance with the increase in the greenhouse effect and depletion of ozone layer. Many factories both at small scale as well as at large scale always maintain a certain area or say a section of operation in their infrastructure that must maintain a range of temperature for process to work successfully. The laboratories of research uncertainly sometimes lack in the use of temperature control system which has further necessitated the use of large chambers of different sizes to perform specific temperature related re-search work which further led to the increase in the cost of research work. In certain specific areas there are lot of electronic activities happening or some machinery function like in the server rooms or the area where production plant is, so basically these places work constantly for 24hrs and during the whole day the temperature has to be monitored precisely and frequently so that it can be ensured that the temperature do not instantly rise or fall below the marked temperature which may lead to the acceleration of wearing and tearing of whole system. Living rooms, hospitals, malls, aircrafts etc., are also one of the most important places where monitoring of temperature is required so as to ensure that the thermal comfort is ensured, and thermal comfort here means that the state of mind which feels satisfied with the temperature in the present environment. This is important because if there will be any dissatisfaction with the thermal environment then it can cause the body to be too warm or too by unwanted heating and unwanted cooling of the equipment may further lead to the functional disbalance.
A Putative Inter-Generic Hybrid Between Conomurex Fischer and Gibberulus Jousseaume (Gastropoda: Strombidae) from South Africa
Authors: Dekkers Aart , Maxwell Stephen
Published: September 2021

This paper highlights a putative inter-generic Conomurex x Gibberulus hybrid from the Sodwana Bay area, North Natal, Republic of South Africa. Putative hybridisation in the Strombidae is becoming ever more recognised at the intra-generic level. Much rarer are the inter- generic hybrids. The new putative hybrid indicates that inter-generic hybridisation may well be an evolutionary force in the radiation of Strombidae, facilitating both rapid reticulation and speciation.
Two new subspecies of Amphidromus from Indonesia (Mollusca: Gastropoda: Camaenidae)
Authors: Thach Nguyen
Published: September 2021

Two new subspecies of the genus Amphidromus Albers, 1850 are described from Indonesia and compared to five other species and subspecies of this genus: Amphidromus berschaueri Thach, 2018, Amphidromus reflexilabris Schepman, 1892, Amphidromus laevus janetabbasae Parsons, 2014, Amphidromus laevus kissuensis Rolle, 1903 and Amphidromus laevus nusteli Parsons, 2014.
Predicting The Number of Passengers on CV. MAKMUR Using The Backpropagation Method
Authors: Wahyuni Dewi
Published: September 2021

Often, the number of passengers up and down at the CV company. Backpropagation is one solution to the problem. The number of passengers can be predicted so that the company CV. Prosperous have a large income. Based on the research, it was stated that MSE at the time of training predicted the number of passengers on CV. Makmur Medan was 0.000999. Based on the coefficient value in the training process, it can be concluded that ANN can predict the number of passengers well.
Transducer Function In Vending Machine Simulation Design
Authors: Andriani Tuti , Pristiwanto
Published: September 2021

A vending machine is a substitute for a cashier or admin in the form of a machine so that buyers simply enter coins and the machine will issue them according to the request. Moore machine and mealy machines as a process for processing buyer orders which are translated into machine orders. Based on the test results of coins entered 1000 and 500, the drink can be chosen according to the price of the drink.
A Personalized Recommender System
Authors:   Bharati Vidyapeeth’s College of Engineering, INDIA, admin admin
Published: September 2021

Due to social media, e-commerce, and the broader digitization of businesses, a data surge has occurred during the previous decade. The information is used to make informed decisions, forecast market trends, and identify patterns in consumer preferences. Following the widespread adoption of internet services, recommendation systems have become commonplace. The idea is to use filtering algorithms to recommend products to users who might be interested in them. Users are given recommendations for a media item such as movies by discovering user profiles of people who share similar interests. The preferences of users are first determined by allowing them to rate movies of their choosing. After some time, the recommender system will be able to better understand the user and recommend films that are more likely to get higher ratings. It also considers the impact of personal and situational factors on the user experience. In comparison to previous models, the experimental findings on the TMDB dataset provide a dependable model that is precise and generates more customized movie recommendations.
Neutrosophic Soft Filter Structures Concerning Soft Points
Authors:   Mersin University, Mersin, Turkey, Demirtas Naime , Demirtas Abdullah ,   Anadolu University, Eskis¸ehir, Turkey
Published: September 2021

In this paper, the concept of neutrosophic soft filter (NSF) and its basic properties are introduced. Later, we set up a neutrosophic soft topology with the help of an NSF. We also give the notions of the greatest lower bound and the least upper bound of the family of neutrosophic soft filters (NSFs), NSF subbase, NSF base and explore some basic properties of them.
Leading From Powerlessness: A Third-way Neutrosophic Leadership Model For Developing Countries
Authors:   Malang Institute of Agriculture (IPM), Malang – INDONESIA, Christianto Victor , Smarandache Florentin ,   Dept. Mathematics & Sciences, University of New Mexico, Gallup, USA
Published: September 2021

We argue that there are essentially two chief leadership models: the hard-style and soft-style leadership. From Neutrosophic point of view, there can be a third way, between hard-style leadership and soft-style leadership model, which may be more relevant to many of people in developing countries as well as in developed countries, who feel “powerless” and “hopeless” especially in this pandemic situation. We prefer to call this new approach: leading from powerlessness. The third-way Neutrosophic leadership model may also mean partially hard-style and partially soft-style leadership.
Linear and Non-Linear Decagonal Neutrosophic numbers: Alpha Cuts, Representation, and solution of large MCDM problems
Authors:   Department of Mathematics and Statistics, The University of Lahore,Pakistan, Farooq Sara , Hamza Ali ,   Department of Mathematics and Statistics, The University of Lahore,Pakistan, Smarandache Florentin ,   Dept. Math and Sciences, University of New Mexico, Gallup, NM, USA
Published: September 2021

The postulation of neutrosophic numbers has been analyzed from different angles in this paper. In this current era, our main purpose is to mention Decagonal Neutrosophic numbers. The types of linear and non-linear generalized decagonal neutrosophic numbers play a very critical role in the theory related to uncertainty This approach is helpful in getting a crisp number from a neutrosophic number. The definitions regarding Linear, Non-Linear, symmetry, Asymmetry, alpha cuts have been introduced and large decision-making problems using fuzzy TOPSIS have been solved.
Misconceptions and Myths Regarding Dog Bite In Urban Area of Kancheepuram District, Tamil Nadu
Authors: Ganesh Shobana Priya , Kumar J Krishna , Arun R
Published: September 2021

Background: Dogs are the main source of human rabies, contributing up to 99% of all rabies transmissions to humans. Though dog bite injuries to humans in India have received much attention, there are certain misconceptions.

Methodology: Cross-sectional study was carried out in urban field practice area of Anakaputhur in Kancheepuram district. By purposive sampling method, 285 outpatients visiting the urban health centre during a period of two months were included as study participants. SPSS version 20 used for entering and analysis of data.

Result: Among the study participants, 36.4 % participants believed that vaccine is given in the stomach, many of them followed certain food restrictions among which 65.2% participants avoided non – vegetarian after dog bite. Around 25.6% participants believed rabies is caused only by dogs and 17 % participants were not aware that rabies is caused by animals other than dog. Less than half of them only responded that they will complete the course of anti-rabies vaccine, if there are no symptoms.

Conclusion: According to this study myths and misconception regarding dog bite were found to be highly prevalent. These beliefs and practices are of no use and can be harmful at times.
Kidney transplant outcomes after medical assistance in dying
Authors: Luke Patrick P. , Skaro Anton , Sener Alp , Tang Ephraim , Levine Max , Sami Samir , Basmaji John , Ball Ian
Published: September 2021

Introduction: After nearly four years of Canadian experience with medical assistance in dying (MAiD), the clinical volume of organ transplantation following MAiD remains low. This is the first Canadian report evaluating recipient outcomes from kidney transplantation following MAiD.
Methods: This was a retrospective review of the first nine cases of kidney transplants following MAiD at a Canadian transplant center.
Results: Nine patients underwent MAiD followed by kidney retrieval during the study period. Their diagnoses were largely neuromuscular diseases. The mean warm ischemic time was 20 minutes (standard deviation [SD] 7). The nine recipients had a mean age of 60 (SD 19.7). The mean cold ischemic time was 525 minutes (SD 126). Delayed graft function occurred in only one patient out of nine. The mean 30-day creatinine was 124 umol/L (SD 52) . The mean three-month creatinine was 115 umol/L (SD 29).
Conclusions: We report nine cases of kidney transplantation following MAiD. The process minimized warm ischemia, resulting in low delayed graft function rates, and acceptable post-transplant outcomes. Further large-scale research is necessary to optimize processes and outcomes in this novel clinical pathway.
Het rechtsmiddel van verzet is wat waard
Authors: Keuning A. , Stamhuis E.
Published: September 2021

Het rechtsmiddel van verzet is wat waard

In dit artikel reageren de auteurs op de inmiddels aangenomen inkrimping van de reikwijdte van het rechtsmiddel verzet. Daarbij vormde het systematische verband met de regeling van de berechting in afwezigheid van de verdachte de aanzet om ook dat stuk procesrecht in de bespreking te betrekken. Het bestaande en het toekomstige recht van verstek en verzet worden analytisch beschreven en naast de rechtspraak over het aanwezigheidsrecht van het EHRM gehouden. Dat leidde tot een kritische kanttekening ten aanzien van het bestaande Arubaanse recht. Het bekritiseerde deel, de onduidelijkheid over de positie van de tot verdediging gemachtigde raadsman, wordt verbeterd in de nieuwe tekst van de wet.
Cyberpunk 2077 langs de nieuwe conformiteitsmaatstaf
Authors: Vos J.
Published: September 2021

Cyberpunk 2077 langs de nieuwe conformiteitsmaatstaf

Vanaf 1 januari 2022 is de Richtlijn levering digitale inhoud en digitale diensten (‘Richtlijn’) van toepassing op de (meeste) leveringen van digitale inhoud en digitale diensten, waaronder games. De Richtlijn biedt een nieuwe conformiteitsmaatstaf die, aan de hand van de tekst en implementatie van de Richtlijn en de daarop betrekking hebbende literatuur, in het artikel wordt besproken. De ervaringen van recensenten en gebruikers rondom de game Cyberpunk 2077 worden samengevat. De nieuwe conformiteitsmaatstaf wordt vervolgens toegepast op de game Cyberpunk 2077. Cyberpunk 2077 wordt onder de Richtlijn als non-conform beoordeeld wegens gewekte verwachtingen en vergelijking met games van hetzelfde type.
WYKORZYSTANIE OPROGRAMOWANIA
WSPOMAGAJĄCEGO ANALIZĘ SIECIOWĄ
METODĄ „ŚCIEŻKI KRYTYCZNEJ”
W ASPEKCIE OPRACOWYWANIA
PLANU OCHRONY INFRASTRUKTURY
KRYTYCZNEJ W POLSCE
Authors: Bujak Dominika , Gikiewicz Magdalena
Published: September 2021

Artykuł przedstawia możliwości wykorzystania oprogramowania WinQSB wspomagającego
analizę sieciową metodą „ścieżki krytycznej” w aspekcie opracowywania
planu ochrony infrastruktury krytycznej w Polsce. W materiale uwzględniono
najważniejsze definicje oraz podstawy prawne dotyczące infrastruktury krytycznej,
a także odniesiono się do ogólnej charakterystyki ochrony obiektów infrastruktury
krytycznej. W dalszej kolejności opisano optymalizację decyzji w zarządzaniu bezpieczeństwem
poprzez wykorzystanie analizy sieciowej, co pozwoliło na zaprezentowanie wykorzystania oprogramowania wspomagającego analizę sieciową do opracowania Planu Ochrony Infrastruktury Krytycznej w Przedsiębiorstwie Wodociągów i Kanalizacji.
Bad Smells in Javascript - A Mapping Study
Authors: Barros Aryclenio Xavier , Adachi Eiji
Published: September 2021

Javascript is one of the most famous mainstream programming languages nowadays. It has gained considerable practical relevance over the last years, with applications in several areas, such as games, 3D rendering, and, mainly, web development. Like any other software system, systems developed in Javascript need to keep their ability to evolve to remain useful and relevant over time. Empirical evidence has shown that bad smells are possible indicators of problems hindering software evolvability. In this context, this paper presents a mapping study investigating if and to what extent bad smells have been defined for the Javascript language and how the interest in this topic has evolved. Our study identified 26 different types of bad smells investigated in the context of Javascript in 8 different works published between 2013 and 2020. This result suggests that although Javascript has gained practical relevance in recent years, there is still room for further empirical studies defining and evaluating the impact of bad smells on Javascript-based software systems.
Caracterizando a evolução de software de contratos inteligentes: Um estudo exploratório-descritivo utilizando GitHub e Etherscan
Authors: Rodrigues Alan , Araújo Allysson Allex , Paixao Matheus , Soares Pamella
Published: September 2021

Blockchain tem sido enquadrada como uma nova infra-estrutura disruptiva baseada na internet. Parcela desse potencial advém do fortalecimento de plataformas públicas de blockchain, como a Ethereum, as quais viabilizam Aplicações Descentralizadas (dApps). Tais soluções são baseadas em contratos inteligentes (CIs) e lidam com restrições específicas que desafiam a evolução de software, como a imutabilidade de dados e o acesso transparente ao código-fonte. Em particular, a transparência de código pode ser observada através de ferramentas como o Etherscan, a qual provê acesso público a uma vasta quantidade de informações sobre os CIs implantados na Ethereum. Além disso, pode-se observar organizações oriundas desse ecossistema aderindo à prática de desenvolvimento open source dos CIs, incluindo o amplo uso do GitHub. Esse rico cenário motivou a necessidade de conduzir um estudo exploratório-descritivo baseado em mineração de repositórios de software para compreender a evolução de software de CIs através da avaliação de similaridade entre a versão disponível no GitHub e versão utilizada na Ethereum (e auditável via Etherscan). À luz de uma análise quali-quantititativa de 27 CIs, este artigo contribui ao 1) caracterizar quatro padrões que denotam diferentes comportamentos evolutivos dos CIs e 2) abordar um método experimental baseado em string para comparar a similaridade entre diferentes versões de CIs.
Investigating vulnerability datasets
Authors: Andrade Rodrigo , Santos Vinícius
Published: September 2021

Insecure software can cause severe damage to user experience and privacy. Therefore, developers should be able to prevent software vulnerabilities. However, detecting such problems is expensive and time consuming. To mitigate this issue, researchers propose vulnerability datasets to make it easier to investigate its properties. In this work, we investigate one dataset to better understand common vulnerabilities, the authors who introduce them to open-source projects, and commit properties. Thus, we use as case study the Big-Vul dataset to help us answering the six research questions we define for this work. Our preliminary results indicate that the most common vulnerabilities occur in the Chromium project. Furthermore, mostly experienced authors are responsible for introducing these vulnerabilities. Last but not least, we conclude that such findings could help developers on detecting vulnerabilities.
Quantization of Weights of Neural Networks with Negligible Decreasing of Prediction Accuracy
Authors: Peric Zoran , Denic Bojan , Savic Milan , Dincic Milan , Mihajlov Darko
Published: September 2021

Quantization and compression of neural network parameters using the uniform scalar quantization is carried out in this paper. The attractiveness of the uniform scalar quantizer is reflected in a low complexity and relatively good performance, making it the most popular quantization model. We present a design approach for the memoryless Laplacian source with zero-mean and unit variance, which is based on iterative rule and uses the minimal mean-squared error distortion as a performance criterion. In addition, we derive closed-form expressions for SQNR (Signal to Quantization Noise Ratio) in a wide dynamic range of variance of input data. To show effectiveness on real data, the proposed quantizer is used to compress the weights of neural networks using bit rates from 9 to 16 bps (bits/sample) instead of standardly used 32 bps full precision bit rate. The impact of weights compression on the NN (neural network) performance is analyzed, indicating good matching with the theoretical results and showing negligible decreasing of the prediction accuracy of the NN even in the case of high variance-mismatch between the variance of NN weights and the variance used for the design of quantizer, if the value of the bit-rate is properly chosen according to the rule proposed in the paper.
De-Shadowization of Tax Gaps in the System-Compositional Models of State Fiscal Policy: Comparative Analysis of EU Countries and Ukraine
Authors: Trusova Natalia , Hryvkivska Oksana , Polishchuk Nataliia , Skrypnyk Svitlana , Lobacheva Iryna , Kudyrko Olena
Published: September 2021

The purpose of the article is to consider the empirical calculations of the level of de-shadowization of tax gaps in the system-compositional model of the fiscal policy of the state. The methodological approach to cointegration of the level of de-shadowization of tax gaps into the system-compositional model of fiscal policy is substantiated, taking into account the strategic determinants of financial and economic development of the state. The method of calculation of the integrated indicator of strategic alternatives is presented and represents the configuration of the modified system of fiscal innovations in relation to the taxation of economic entities. A methodical approach to estimating the level of de-shadowization of the tax gap on the income tax of economic entities is proposed. The level of unit testing of variables of de-shadowization of tax gaps from indicators of financial and economic development of the EU and Ukraine is analyzed. It is concluded that one of the most influential factors today is the de-shadowization of the economy. The future directions are the research of the ways to improve Ukraine’s fiscal policy.
VASER Liposuction - How to Get Natural Results with Ultrasound Assisted Liposuction?
Authors: Bagatin Dinko , Bagatin Tomica , Deutsch Judith , Sakic Katarina , Nemrava Johann , Isomura Eduardo , Sarec Ivelj Martina
Published: September 2021

Ultrasound assisted liposuction technology is a selective technique to emulsify fatty tissue and improve the removal of fat. This technique can be used on many areas of the body such as: chin neck, back, buttocks, abdomen, legs, arms. Fatty areas, as well as, skin and cellulite can be molded in a process known as ultrasound cavitation. Results can produce significant skin contraction and smoothing of areas. Using this method reduces the need for surgical intervention and requires less energy to achieve similar results. This method is also good for treatment of fibrous scar tissue, producing less bruising and blood loss. The advantages of the VASER ultrasound prepared liposuction in comparison to the mechanical liposuction method are better with fat extraction, less blood loss, and smoother results. While the disadvantages of VASER ultrasound method are possible thermal injuries, the need for larger incisions for protective ports, increased incidence of seromas, slightly increased cost and longer preparation and operative times. However further presentation will show the benefits of this newer generation of liposuction method. Also, various probes for better fat extraction and specific treatment areas will be discussed.
How Can Flaxseed be Utilized as Functional Food
Authors: Kakkar Shama , Tandon Runjhun , Tandon Nitin
Published: September 2021

Although vegetables and fruits are unquestionably important components of food, incorporating herbs and spices into one’s diet has become a must to improve one’s health in today’s world. Due to rising popularity among health-conscious consumers, studies on functional foods such as herbs are a growing field in food science. Flaxseed (Linum Usitatissimum L.), which comes from the flax plant, an annual herb, is gaining interest as a functional food ingredient due to its high levels of alpha-linolenic acid (ALA), lignans, and fiber. Flaxseed consumption in the diet helps to prevent serious illnesses such as heart disease, cancer, diabetes, obesity, gastrointestinal, renal, and bone problems. Type II diabetes, in particular, is one of the great healthcare challenges of the twenty-first century, as it has engulfed children, adolescents, and young adults alike. While standard risk factors for type II diabetes are genetics, living style, and behavioral aspects, this article focuses on preventing or controlling the disease through dietary changes. To the best of our knowledge, review articles on the commercial use of flaxseed in the formulation of numerous food products with low glycemic index and their impact on diabetes are hardly available. The data from the previous 5 years is used to compile this report.
Knowledge Extraction from Open Data Repository
Authors: Kakulapati Vijayalakshmi
Published: September 2021

The explosion of affluent social networks, online communities, and jointly generated information resources has accelerated the convergence of technological and social networks producing environments that reveal both the framework of the underlying information arrangements and the collective formation of their members. In studying the consequences of these developments, we face the opportunity to analyze the POD repository at unprecedented scale levels and extract useful information from query log data. This chapter aim is to improve the performance of a POD repository from a different point of view. Firstly, we propose a novel query recommender system to help users shorten their query sessions. The idea is to find shortcuts to speed up the user interaction with the open data repository and decrease the number of queries submitted. The proposed model, based on pseudo-relevance feedback, formalizes exploiting the knowledge mined from query logs to help users rapidly satisfy their information need.
Systemic Therapy in Hepatocellular Carcinoma
Authors: Charonpongsuntorn Chanchai
Published: September 2021

Systemic therapy of advanced stage hepatocellular carcinoma (HCC) was limited to the sorafenib in the past decade since 2007. Novel agents including multiple targeting agents, immune checkpoint inhibitors and anti-angiogenesis reported efficacy in treatment. This is the first time, the combination of atezolizumab and bevacizumab as first-line treatment is superior to sorafenib. Standard guideline in advanced HCC was changing. New novel drugs increase in available including multiple targeting agents and immune checkpoint blockade such as Lenvatinib, regorafenib, cabozantinib, ramucirumab and immunotherapy as first line or second line therapy will benefit in term of survival benefit and quality of life in advanced stage or unresectable hepatocellular carcinoma.
Business Process versus Human Resources Performance
Authors: Stašák Jozef , Škorvagová Eva
Published: September 2021

The contribution deals with qualitative and quantitative analysis of relationship between business processes performance to be investigated (hereinafter BP) versus performance of employees who are interested in that BP functionality hereinafter known as Employees). The qualitative analysis deals with human resources performance psychological aspects, while the quantitative analysis is closely related to BP and Employee performance quantification and modelling. On one hand, the qualitative analysis describes psychological aspects concerned to human resources and the investigated BP performance. On the other hand, the contribution deals with quantifying those relationships with use of linguistic sets, which create basis of business process linguistic modelling (BPLM) approach as well. The PBPL (Principle Business Process Linguistic) Equation is applied in order to create a conceptual model of the objective oriented expert system, which operates over the knowledge base, which contains adequate semantic networks (SNWs| and reference databases (RDBs), while an appropriate inference engine is applied for user communication with that expert system too.
Retreatment of Polymer Wastes by Disintegrator Milling
Authors: Kulu Priit , Goljandin Dmitri
Published: September 2021

Global introduction of waste utilization techniques to the polymer market is currently not fully developed but has enormous potential. Before reintegration of used material into a new product, it normally requires grinding, that is shredding, crushing, or milling. In traditional grinders, the generated stresses in the material to be ground are equal to or less than the strength of the material. If by traditional methods, the stresses generated are compressive + shift, so by milling based on collision are tension + shift. Due to the high stress-material strength ratio at collision, it is possible to crush not only brittle materials but also ductile materials. This process allows easily combining the grinding of composite materials with their separation into individual constituents. In the current study, the mechanical recycling of the following groups of polymer materials was studied: pure brittle and soft polymers (PMMA, HDPE and IER), blends of plastics (ABS+PMMA, PC + ABS), reinforced plastics (PMMA+GFP); elastomers (rubber and tyres), and printed circuit boards (PCB).
Deep Learning Approach for Raman Spectroscopy
Authors: Wathsala N. Jinadasa M.H. , C. Kahawalage Amila , Halstensen Maths , Skeie Nils-Olav , Jens Klaus-Joachim
Published: September 2021

Raman spectroscopy is a widely used technique for organic and inorganic chemical material identification. Throughout the last century, major improvements in lasers, spectrometers, detectors, and holographic optical components have uplifted Raman spectroscopy as an effective device for a variety of different applications including fundamental chemical and material research, medical diagnostics, bio-science, in-situ process monitoring and planetary investigations. Undoubtedly, mathematical data analysis has been playing a vital role to speed up the migration of Raman spectroscopy to explore different applications. It supports researchers to customize spectral interpretation and overcome the limitations of the physical components in the Raman instrument. However, large, and complex datasets, interferences from instrumentation noise and sample properties which mask the true features of samples still make Raman spectroscopy as a challenging tool. Deep learning is a powerful machine learning strategy to build exploratory and predictive models from large raw datasets and has gained more attention in chemical research over recent years. This chapter demonstrates the application of deep learning techniques for Raman signal-extraction, feature-learning and modelling complex relationships as a support to researchers to overcome the challenges in Raman based chemical analysis.
Local Inflammatory Biomarkers and Potential Inflammation-Targeting Therapies in Diabetic Retinopathy
Authors: Damian Ioana , Delia Nicoară Simona
Published: September 2021

Diabetic retinopathy (DR) is one of the most frequent microvascular complications of diabetes. A large body of evidence supports the role of inflammation in the development and progression of DR. Currently, DR is diagnosed based on the presence of morphological lesions detected on fundus examination. Yet, there are other laboratory or imaging biomarker whose alteration precede DR lesions. This chapter will first briefly explain the role of inflammation in DR pathogenesis and will analyze the molecules involved. Further, it will discuss significant and recent studies that analyzed local laboratory or imaging inflammatory biomarkers in different DR stages. It will then focus on several potential inflammation-targeting therapies which proved to be effective in animal or human studies. Validation of these reviewed biomarkers would allow the identification of patients who do not respond to the current available treatment and could benefit from an adjunctive therapy.
Photophysical Detection of Singlet Oxygen
Authors: Maity Arnab
Published: September 2021

The chemical reactivity of singlet oxygen (1O2) (SO) derives from its electronically excited state. Being a unique reactive oxygen species SO takes part in many important atmospheric, biological physical, chemical, and therapeutic process and attracted current research interest. To understand the mechanistic pathways in various process the detection and quantification of SO is very important. The direct method of detection is very challenging due to its highly reactive nature. Only direct method of determination of phosphorescence of SO at 1270 nm has been utilised but that also puts some limitation due to very low luminescence quantum yield. Indirect method using UV–Vis spectrophotometric, fluorescent and chemiluminescent probes has been extensively studied for this purpose. Elucidation of various mechanistic processes improvised the use of sophisticated spectroscopic detection probe for SO have been discussed in a simple and lucid manner in this article through citation of literature examples. Four major spectroscopic methods i.e. spectrophotometry, fluorescence, emission and chemiluminescence are elaborately discussed with special emphasis to chemical probes having high selectivity and sensitivity for SO.
Role of Lipid, Protein-Derived Toxic Molecules, and Deficiency of Antioxidants behind the Pathogenesis of Diabetic Retinopathy (DR) in Type 2 Diabetes Mellitus
Authors: Pramanik Subhasish , Kanta Mondal Lakshmi , Chowdhury Subhankar , Bose Chiranjit , Bera Debgopal , Bhattacharjee Koena
Published: September 2021

To determine the role of NADPH-oxidase mediated formation of different lipid, protein-derived molecules, and depletion of vitamin-C level in vitreous behind the endothelial dysfunction-induced vascular endothelial growth factor secretion and pathogenesis of diabetic retinopathy (DR) in type 2 diabetes mellitus (T2DM). Fourteen T2DM patients with mild non-proliferative diabetic retinopathy (MNPDR), 11 patients without diabetic retinopathy (DNR), 17 T2 DM subjects with high-risk proliferative diabetic retinopathy (HRPDR), and 5 healthy individuals without DM underwent vitreous analysis for estimation NADPH oxidase, lipid peroxide like malondialdehyde (MDA), 4-Hydroxy-noneal (HNE) and advanced lipoxidation end product (ALE) like Hexanoyl-lysine (HLY), protein carbonyl compound (PCC), Vitamin-C and concentration of vascular endothelial growth factor (VEGF) secretion following standard spectrophotometric methods and enzyme-linked immunosorbent assay (ELISA). Vitreous concentration of NADPH-oxidase, different protein and lipid-derived molecule, and VEGF were found to be significantly elevated among DNR and of DR subjects with different grades compared to HC subjects whereasthe vitamin-C level was found to be decreased among different DR subjects and DNR subjects in comparison to healthy individuals. Oxidative stress-mediated lipid and protein-derived biomolecules not only add important mediators in the pathogenesis of DR, but also accelerate the progression and severity of microangiopathy.
Analysis of the Factors That Influence the Clinical Outcome of Severe Acute Respiratory Syndrome Caused by SARS-CoV-2 in Pregnant Women
Authors: de Sousa Cavalcante Yuri , Castelo Branco Chaves Nicolly , Lucas de Sousa Moreira Jorge , de Sá Barreto Lima Samuel , Martins de Freitas Maryana , Gonçalves Júnior Jucier , Lima Cândido Estelita
Published: September 2021

Introduction: The new coronavirus (SARS-CoV-2) pandemic has shown to cause even more severe problems among pregnant women, increasing the incidence of complications before and after childbirth, especially cardiorespiratory problems, such as the Severe Acute Respiratory Syndrome (SARS). Objectives: To describe the clinical outcome of SARS caused by SARS-CoV-2 in Brazilian pregnant women and to compare the rates of morbidity and mortality from other causes in this group, stratified by the following variables: gestational age and age group. Methodology: Observational, analytical study based on documents whose data were collected from the 2020 Epidemiological Report No. 40 in the database of the Brazilian Department of Health, from which morbidity and mortality data were extracted to calculate the lethality rate and compare rates using a binomial test with a significance level of 0.05. Results: Of the total number of pregnant women hospitalized for SARS, 4,467 (46.6%) were confirmed for COVID-19 and, of these, 233 died, corresponding to a lethality rate of 5.2%. Morbidity was higher in the third trimester of pregnancy, but the disease was more severe in the second trimester (7%), being worse in women aged 40 years and older (40–49; 8.7% and 50–59; 15.3%). A significant difference was observed in the rate of cases between the COVID-19 SARS group and the group with other causes in all gestational strata and age groups. As for deaths, a significant difference was found in the rates between the first and third trimesters, and in pregnant women aged 10 to 19 years. Conclusion: Considering the variables under analysis, evidence shows that pregnant women at an advanced age and in the second trimester of pregnancy contribute to the lethal outcome of the disease. Other variables associated with the presence of comorbidities and quality of care for pregnant women should be considered in the model in future studies.
Surgical Treatment of Esophageal Advanced Achalasia
Authors: Luis Braga de Aquino José , Aparecida Leandro-Merhi Vânia
Published: September 2021

Of the several procedures that has to treat esophageal achalasia, the esophagectomy is to be the most indicated in advanced disease, which prompted Pinotti the disseminate the transmediastinal esophagectomy technique in the 1970s, with the advantage of avoiding thoracotomy. Nevertheless, several series demonstrated that this technique was not exempt from complications one of which could lead to massive hemopneumothorax due to injury to the trachea- bronchial tree and vessels due the periesophagitis that may be present with consequent adherence of the esophagus to these noble organs. Thus, Aquino in 1996 introduced the esophageal mucosectomy technique with preservation of the esophageal muscle tunic at the level of mediastinum as well as the transposition of the stomach to the cervical region inside in this tunic for the reconstruction of digestive tract. The advantage of this procedure is to avoid transgression of the mediastinum. This author describes in details this procedure, and shows early results and late evaluation using the ECKARDT score in a series of patients showing the advantages of the esophageal mucosectomy due the low incidence of immediate postoperative complications and good resolution in long term due the absence of symptoms in most patients.
Design and Analysis of Robust Deep Learning Models for Stock Price Prediction
Authors: Sen Jaydip , Mehtab Sidra
Published: September 2021

Building predictive models for robust and accurate prediction of stock prices and stock price movement is a challenging research problem to solve. The well-known efficient market hypothesis believes in the impossibility of accurate prediction of future stock prices in an efficient stock market as the stock prices are assumed to be purely stochastic. However, numerous works proposed by researchers have demonstrated that it is possible to predict future stock prices with a high level of precision using sophisticated algorithms, model architectures, and the selection of appropriate variables in the models. This chapter proposes a collection of predictive regression models built on deep learning architecture for robust and precise prediction of the future prices of a stock listed in the diversified sectors in the National Stock Exchange (NSE) of India. The Metastock tool is used to download the historical stock prices over a period of two years (2013–2014) at 5 minutes intervals. While the records for the first year are used to train the models, the testing is carried out using the remaining records. The design approaches of all the models and their performance results are presented in detail. The models are also compared based on their execution time and accuracy of prediction.
The Frequency and Causes of Subepidermal Gaps or Blisters and the Compliance Rate Between Clinical Diagnosis and Pathology Reports from 2015 to 2019
Authors: Darjani Abbas , Eftekhari Hojat , Amini Rad Seyedeh Rojin , Alizadeh Narges , Rafiee Rana , Gharaei Nejad Kaveh
Published: September 2021

Background: Skin diseases are the fourth most common cause of human illness, and blisters with different clinical manifestations make a diagnostic challenge. Objectives: This study aimed to evaluate the frequency and causes of subepidermal gaps or blisters, as well as the compliance rate between the initial and final clinical diagnoses based on pathology reports. Methods: In this cross-sectional study, pathology reports of subepidermal blisters or gaps were evaluated in the patients referred to the Razi Laboratory of Rasht from 2015 to 2019. The samples were examined by a pathologist after hematoxylin and eosin staining. The reports included demographic information, clinical differential diagnoses, final diagnosis, direct immunofluorescence findings, and salt split results. Finally, the compliance rate of clinical diagnosis with pathology reports was determined. Results: A total of 183 pathology reports were evaluated, 170 of which contained the final diagnosis. Females were more frequently affected by the disease, and pemphigoid bolus and lichen planus were the most prevalent final diagnoses. The compliance rate between the initial and final diagnoses was 94%. About 37.2% of the reports lacked direct immunofluorescence (DIF) and salt split, and only 42.6% of the samples had undergone DIF examination, while 20.2% had both DIF and salt split. There was no significant association between the compliance rate of the final diagnosis with age, sex, and undergoing diagnostic tests. Conclusions: A high incidence of subepidermal gaps or blisters was seen in middle-aged individuals and females. The compliance rate of the initial clinical diagnosis with the final diagnosis based on pathological reports was high. Our findings emphasize the importance of histopathological examination and the complementary role of direct immunofluorescence and salt split in diagnosis.
What is the Relation between Semantic and Substantive Epistemic Contextualism?
Authors: Wilburn Ron ,   Romanian Academy - Iasi Branch
Published: September 2021

Epistemic Contextualism is generally treated as a semantic thesis that may or may not have epistemological consequences. It is sometimes taken to concern only knowledge claims (as the assertion that the word “know” means different things in different contexts of use). Still, at other times it is taken to regard the knowledge relation itself (as the assertion that knowledge itself has no single univocal nature). Call the former view Semantic EC, the latter view Substantive EC, and the idea that the plausibility of Semantic EC presupposes that of Substantive EC, the “Presupposition Thesis.” Numerous authors argue against the Presupposition Thesis on the grounds that an understanding of the nature of knowledge is no more required to understand the meaning of knowledge assertions than an understanding of the self, for instance, is needed to understand the meaning of sentences containing “I.” These authors then offer additional arguments for the same conclusion, using further comparisons between “know” and other indexicals, as well as between “know” and quantifiers, gradable and modal adjectives. Herein, I defend the Presupposition Thesis by arguing against these authors’ claims (based as they are on these types of comparisons) that Semantic EC is plausible without the supposition of Substantive EC.
Policies for professionalisation in adult learning and education: A comparative study from India, Colombia and Denmark
Authors: Singh Shalini , Molina-Naar Mario , Ehlers Søren
Published: September 2021

This paper discusses the role of policies in promoting or hindering professionalisation in adult education in different contexts. The paper draws generalisations based on three case studies: India, Colombia and Denmark, where professionalisation of adult education is negligible. The methodology includes case studies, policy analysis and a comparative perspective. The paper concludes that the professionalisation of adult education has diminished with the emergence of lifelong learning because the focus of policies has shifted to learning outcomes rather than educators. Stakeholders who favour the professionalisation of adult education and learning, therefore need to ensure the development of distinctive offers, create a market for them and get them acknowledged to convince policy makers for investment.
Her majesty the transaction
Authors: Gaćeša Radmila
Published: September 2021

The transaction is one of the unavoidable phenomena of the modern world. The transaction is accessible, ubiquitous, global, and necessary, hence the number of transactions and the number of users is constantly increasing, as statistics regularly confirm. Generators of further development of transactions in the world of financial and especially banking services are certainly ICT companies together with numerous providers that develop and improve information and communication technologies, and make available reliable information transmission systems without which the world of transactions we know today would not be possible. Banks pay special attention to the further development and improvement of each individual type of transaction. In doing so, banks actively cooperate with ICT companies, sending initiatives and giving ratings, and appropriate support, as they are vitally interested in providing innovative services and types of transactions to their existing and potential clients.
Sociološke marginalije na savremene teme (ogledi) - Ljubiša Mitrović: Sociološke marginalije na savremene teme, Prometej, Novi Sad, 2019
Authors: Nastić Nevena
Published: September 2021

Osvrt na ovu monografiju ogleda se u analizi društava koja su u tranziciji, kao i pokušajima da se čitavo društvo izvuče iz ralja neoliberalizma. U njoj je zapravo reč o ideji da se savremeno društvo mora konačno posvetiti očuvanju nauke i obrazovanja ili će propasti. Kao što ćemo dalje videti, Mitrović se zalaže za stvaranje socijaldemokratskog modela razvoja koji će se afirmisati kroz jačanje sindikata i novih pokreta, gde civilno društvo mora odigrati glavnu ulogu. Takođe, na više mesta provlači se ideja o borbi mladih obrazovanih ljudi u osvešćivanju javnosti.