bluuebunny/crossref_metadata_2025 huggingface dataset:
Tidal marsh resilience to sea level rise controlled by vertical accretion and landward migration under nature-based human adaptation scenarios
Authors: Ouyang Xiaoguang , Connolly Rod , Lee Shing Yip
Published: October 2021

Tidal marshes are not only lost to human disturbance but also face the threat of sea level rise (SLR). However, current earth system models used to estimate future changes in wetland extent omit wetland’s real responses to SLR without field observations. We synthesised global data on sediment accretion rate (SAR) and surface elevation change (SEC) for tidal marshes and developed a mathematical model to assess their resilience to future SLR. Sediment loadings and precipitation largely explain the variance of marsh SAR and SEC. Human disturbance resulted in less sediment accretion and existing conservation activities were inefficient in promoting sediment accretion. Under the representative concentration pathways and nature-based human adaptation scenarios, tidal marshes will gain up to 63% of the current area by 2100 if sufficient sediment loadings and accommodation space allow landward migration. If current accommodation space maintains, net areal losses of > 30% are possible and hotspots of future marsh loss are largely in North America, Australia and China. Projections for most SLR scenarios see marsh area peaking in the mid rather than late 21st century. This implicates that tidal marshes may contribute to achieve a climate neutral world by 2050. We highlight the importance of nature- based adaptation in enhancing the resilience of tidal marshes to future SLR.
Recursive Processing of Nested Structures in Monkeys? Two alternative accounts
Authors: Lakretz Yair , Dehaene Stanislas
Published: October 2021

Ferrigno et al. [2020] introduced an ingenious task to investigate recursion in human and non-human primates. American adults, Tsimane adults, and 3-5 year-old children successfully performed the task. Macaque monkeys required additional training, but two out of three eventually showed good generalization and scored above many Tsimane and child participants. Moreover, when tested on sequences composed of new bracket signs, the monkeys still showed good performance. The authors thus concluded that recursive nesting is not unique to humans. Here, we dispute the claim by showing that at least two alternative interpretations remain tenable. We first examine this conclusion in light of recent findings from modern artificial recurrent neural networks (RNNs), regarding how these networks encode sequences. We show that although RNNs, like monkeys, succeed on demanding generalization tasks as in Ferrigno et al., the underlying neural mechanisms are not recursive. Moreover, we show that when the networks are tested on sequences with deeper center-embedded structures compared to training, the networks fail to generalize. We then discuss an additional interpretation of the results in light of a simple model of sequence memory.
Encoding of vocal pitch in the dorsal premotor cortex during multi-talker speech recognition
Authors: Venezia Jonathan Henry , Herrera Ortiz Christian , Whittle Nicole , Leek Marjorie R. , Barnes Samuel , Holshouser Barbara , Yi Alex C.
Published: October 2021

In a recent study (Venezia et al., 2021), left dorsal premotor cortex (dPM) responded to vocal pitch during a degraded speech recognition task, but only when speech was rated as unintelligible. Crucially, vocal pitch was not relevant to the task. The present fMRI study (N = 25) tests the hypothesis that left dPM will respond to vocal pitch for increasingly intelligible speech in a multi-talker speech recognition task that emphasizes pitch for talker segregation. We applied spectrotemporal modulation distortion to independently modulate vocal pitch and phonetic content in two-talker (male/female) utterances across two conditions (Competing, Unison), only one of which required pitch-based segregation (Competing). A Bayesian hierarchical drift-diffusion model (HDDM) was used to predict speech recognition performance (3-AFC response times, accuracy coded) from the pattern of spectrotemporal distortion imposed on each trial. The model’s drift rate parameter, a d’-like measure of speech recognition performance, was strongly associated with vocal pitch for Competing but not Unison. In a second, Bayesian hierarchical brain-behavior model, we then regressed the HDDM’s posterior predictions of trial-wise drift rate against trial-wise fMRI activation amplitude. A significant positive association with overall drift rate, reflecting contributions from vocal pitch and/or phonetic content, was observed in left dPM in both conditions. A significant positive association with ‘pitch-restricted’ drift rate, reflecting only contributions from vocal pitch, was observed in left dPM but only in the Competing condition. These findings suggest that left dPM: (i) responds to vocal pitch; and (ii) can operate in an auditory-pitch mode and a phonetic-speech mode.
Populist Democrats? Unpacking the Relationship between Populist and Democratic Attitudes at the Citizen Level
Authors: Zaslove Andrej , Meijers Maurits
Published: October 2021

It is widely feared that the onset of populism poses a threat to democracy, as citizens' support for democracy is essential for its legitimacy and stability. Yet, the relationship between populism and democratic support at the citizen level remains poorly understood, particularly with respect to support for liberal democracy. Data measuring citizens' populist attitudes in conjunction with a comprehensive range of measures of democratic support has been lacking. Using unique data from the Netherlands, we study the relationship between individuals' populist attitudes and their attitudes towards democracy in three studies. We examine the association between populism and support for democracy and satisfaction with democracy (Study 1); populism and support for liberal democracy (Study 2); and populism and support for majoritarian conceptions of democracy (Study 3). We find that while citizens with stronger populist attitudes are dissatisfied with how democracy works, they are no less supportive of the principle of democracy. Contrary to most theorizing, we find that citizens with higher populist attitudes not less supportive of key institutions of liberal democracy, but reject mediated representation through political parties. At the same time, individuals with stronger populist attitudes are highly supportive of forms of unconstrained majoritarian rule. These findings suggest that the relationship between populism and support for (liberal) democracy is more complicated than commonly assumed.
The Sociology of Housing Market Intermediaries
Authors: Korver-Glenn Elizabeth , Bartram Robin , Besbris Max
Published: October 2021

The housing market is replete with intermediaries—individuals whose work constructs, maintains, or expands a market. A sociology of housing requires analytic attention to these myriad housing market intermediaries since they affect whether and under what conditions individuals and households can access and maintain access to housing as well as help determine the affordability and quality of that housing. In this chapter we aim to show the utility of intermediaries as a wide category of analysis, particularly for understanding how housing inequality interacts with other forms of social stratification across axes such as gender, class, and race and ethnicity. We summarize recent research and unpack how the work of public and private-sector intermediaries—such as housing developers, building inspectors, real estate agents, mortgage lenders, appraisers, landlords, housing authority case workers, mobile home park operators, and property managers—leads to more or less stratification in the housing market.
Types, Determinants, and Outcomes of Resourceful Behaviours during Crises
Authors: Castellanza Luca , Woywode Michael
Published: October 2021

Entrepreneurs usually have several means at their disposal to deal with and overcome adverse circumstances, ranging from simple non-resourceful coping strategies to more elaborate resourceful behaviours. However, entrepreneurs who find themselves in conditions of prolonged adversity and disadvantage have few effective possibilities to withstand sudden adversity such as crises and income shocks. Based on these premises, we develop theory on the types, antecedents, and outcomes of entrepreneurial responses to adversity by investigating how entrepreneurs living in conditions of extreme poverty may behave resourcefully while facing two major crises in a short timeframe.Through an analysis of entrepreneurship in South-West Cameroon, we identify three behaviours entrepreneurs enact in response to crises: passive, hustling, and future-oriented, which differ with regards to activities, driving motivations, main objectives, approaches towards present and future adversity, and dominant focus concerning the use of resources. We also find that entrepreneurs’ enacted behaviours depend chiefly on the nature of the losses they incur and on the type of social capital they can avail of in the aftermath of a crisis. Lastly, we suggest that the different behaviours result in further changes in the entrepreneurs’ resource levels, which subsequently influence the likelihood that entrepreneurs will shift between behaviours.
Inwolucja poznawcza a procesy adaptacyjne w okresie późnej dorosłości
Authors: Matyjasek Aleksandra
Published: October 2021

Zmiany o charakterze inwolucyjnym są normatywnym skutkiem starzenia się organizmu. Przejawiają się przekształceniami w budowie tkanek i narządów. Zachodząca wraz z wiekiem reorganizacja ogólnoustrojowa przekłada się na funkcje (zmianę aktywności hormonalnej i ilości neurotransmiterów) i strukturę (stopniowy ubytek masy mózgowia) ośrodkowego układu nerwowego. Wykładnikami zmian neurobiologicznych jednostki są jej możliwości kognitywne, które współcześnie rozpatruje się jako wskaźnik potencjału i plastyczności mózgu. Jako teoretyczną podstawę opisu przyjęto model selektywnej optymalizacji i kompensacji oraz koncepcję regulacyjno-adaptacyjną, zgodnie z którymi zmiany zachodzące w okresie senioralnym wynikają z naturalnych przeobrażeń i można je uznać za miarę możliwości przystosowawczych jednostki. Artykuł stanowi propozycję spojrzenia na okres późnej dorosłości z perspektywy posiadanych zasobów, co w wymiarze praktycznym implikuje do prowadzenia działań edukacyjnych i usprawniających, podnoszących jakość życia seniorów.
Genetics, Agriculture, and Biotechnology
Authors: Suza Walter , Lee Donald
Published: October 2021

This textbook provides an introduction to plant genetics and biotechnology for the advancement of agriculture. A clear and structured introduction to the topic for learners new to the field of genetics, the book includes: an introduction to the life cycle of the cell, DNA and how it relates to genes and chromosomes, DNA analysis, recombinant DNA, biotechnology, and transmission genetics.
Apport du numérique dans la prise en charge médicale des patients souffrant de douleurs chroniques
Authors: Kerckhove N. , Corteval A. , Eschalier A.
Published: October 2021

Cet article est un état des lieux des publications ayant évalué l’utilisation et l’impact de la e-santé chez des patients souffrant de douleur chronique. Nous avons évalué les text-message, les carnets électroniques et les applications mobiles. Enfin, les limites et défis futurs de l’intégration de la e-santé dans la prise en charge des douleurs chroniques sont discutés. En conclusion, l’intégration de la e-santé est prometteuse pour la prise en charge des patients, mais il y a une nécessité d’effectuer des études rigoureuses pour valider le réel bénéfice apporté.
La fermeture dans la chirurgie de l’hallux valgus
Authors: Piat C. , Potage D.
Published: October 2021

La chirurgie de l’hallux valgus (HV) associe des gestes osseux et des parties molles (libération latérale) connus et codifiés. Il n’en va pas de même du temps final de fermeture capsulaire et cutanée, d’importance pourtant certaine. L’objectif de notre étude était de recueillir les pratiques chirurgicales de ce temps final. Une enquête de pratique a été faite entre janvier et février 2017. Les chirurgiens répondaient à un questionnaire en ligne (site de l’AFCP) sur la fermeture. Cent soixante et un chirurgiens ont répondu au questionnaire sur 240 sollicités, soit 67 %. L’activité chirurgicale « pied » représentait 64 % de leur activité globale (10/100) ; opérant en moyenne 231 HV par an (10–1 000). Il était réalisé une chirurgie à ciel ouvert ou mini-invasive (54 % de chevrons, 40 % de Scarf, 3 % de Lapidus et 3 % d’ostéotomies basales), avec fermeture capsulaire et cutanée. Quatre-vingt-douze pour cent des chirurgiens réalisaient eux-mêmes ce temps. Concernant la capsule : 45 % réalisaient systématiquement une résection, 32 % parfois et 23 % n’en réalisaient aucune. Cinquante et un pour cent des chirurgiens pensaient que la fermeture capsulaire avait un impact sur la mobilité articulaire, 32 % que cela apportait un effet correctif supplémentaire et 16%que cela pérennisait la correction. Le critère de résection capsulaire était l’excès tissulaire (69 %), un complément de recentrage des sésamoïdes (14 %), un complément de correction de l’HV (12 %). La résection capsulaire intéressait la capsule dorsale (37 %), la plantaire (29 %) ou les deux (23,5 %). Des lambeaux, plasties étaient réalisés dans 10 % des cas. La fermeture capsulaire était réalisée de façon étanche (83 %), au fil résorbable (90 %) par des points simples (37 %), des points en croix (33 %), en paletot (14 %) ou par surjet (12 %). Cette fermeture capsulaire était faite dans 71 % des cas en position neutre et dans 21 % en flexion plantaire. Concernant la peau, 51 % ne réalisaient jamais de résection cutanée, 20 % systématiquement et 29 % la pratiquaient à la demande (excès de peau, volumineuse bursite). La fermeture cutanée se faisait essentiellement par fil résorbable (77 %) en points séparés (36 %) ou sujet intradermique (39 %). La fermeture d’un HV à ciel ouvert n’est pas codifiée ; pourtant, les chirurgiens reconnaissent son importance. Cette fermeture capsulaire et cutanée est souvent réalisée par le praticien. La fermeture capsulaire est réalisée, dans trois quarts des cas en position neutre, de manière étanche au fil résorbable. Seul un quart des chirurgiens ne réalisent aucune résection capsulaire. La fermeture cutanée, sans résection pour la moitié des praticiens, est majoritairement faite au fil résorbable. C’est dire l’intérêt d’études prospectives sur ce sujet.
Revisiting the Embryology of the Facial Muscles, the Superficial Musculoaponeurotic System, and the Facial Nerve
Authors: Som P.M. , Taub P.J. , Delman B.N.
Published: October 2021

The facial muscles are responsible for nonverbal expression, and the manner by which these muscles function to express various emotions are reviewed. How one recognizes these various facial expressions and how individuals can alter their facial expression are discussed. The methodology
for cataloging facial expressions is also presented. The embryology of the facial muscles; the facial ligaments; and the supporting superficial musculoaponeurotic system, which magnifies the muscle movements, is also reviewed as is the embryology of the facial nerve, which innervates these
muscles. Also, a detailed MR imaging atlas of the facial muscles is presented.Learning Objective: The reader will learn how the facial muscles develop and how they are the means of human nonverbal emotional expression. The anatomy of the facial ligaments and the superficial musculoaponeurotic
system are also discussed
Kemal Atuturk in the art of republican Turkey
Authors: Goroshkov Nikolay P.
Published: October 2021

The article analyzes how the personality of the first president of the Turkish Republic, Mustafa Kemal Ataturk, is reflected in contemporary Turkish art. This year marks exactly 140 years since his birth. To his achievements in the military and political arenas, cultural figures have dedicated many works in the visual arts, architecture, literature and cinema. 
The trace of the first president of the Republic of Turkey remained in the works of both his contemporaries and in the works of authors today. Creativity is multifaceted, inspiration has no boundaries, along with them, culture was freed from prohibitions with the beginning of a new page in the history of the country. Her achievements became available to more people, the opportunity to touch the spiritual life and create it opened up along with the reforms of Mustafa Kemal Pasha to wide layers of the population. Immortal works have preserved for posterity the image of the father of the Turkish nation, and a characteristic feature of these works is the author's personal admiration for the deeds of Gazi. This undoubtedly leaves its mark on the work and the way in which a person is shown in the context of history, who took fate and the entire people into his own hands, mired in political, economic, cultural crises.
But before giving an answer to the question "Who are you, Father of the Turks?", it is important, in our opinion, briefly to draw attention to the historical retrospective of the development of Turkish culture under the influence of the policy of two states that appeared, flourished and fell into decay on the peninsula of Asia Minor. The article briefly examines some of the features of the cultural policy of the last years of the Ottoman Empire and the first years of the republic.
Detection and Classification of Diseases in Cucumber Leaves
Authors: RajaKumar.R  , Pandian.R  , PremJacob.T
Published: October 2021

Leaf diseases in cucumber must be identified early and accurately as it reduces the yield. Disease detection in plants is the important field of Artificial Intelligent in agriculture. This causes a periodic outbreak of plant diseases which leads to crop death. Automatic plant disease detection may be benefits in monitoring large scale cultivation of crops, and detects the disease symptoms at early stage itself. Here to detect the disease present in the cucumber the tensor flow technique is used and then artificial neural network is used to classify these diseases. The common disease like cucumber mosaic virus, leaf miner, bacterial leaf spot, and leaf blight are examined with disease detection accuracy of 98.66%. This image processing techniques and algorithm are designed using python language to segment the diseases and categories them whether infected or healthy with the help of Pycharm software.
Design of Prosthetic Arm
Authors: Swetha R. , NirmalaDevi S.
Published: October 2021

This paper proposes the design of the prosthetic arm by reconstructing the structure and proportions of an amputated arm using high precision methods and dimensions. To achieve this, CT images of the patient’s amputated and non-amputated arm are collected from the Rehabilitation centre. The patient CT data were imported to a 3D modelling software i.e., Mimics Innovation Suite version 22.0 Materialise 3-Matic version 14.0 original licensed software. The exported file is given to the Computer-Aided Design software, the geometry of the socket and the prosthetic arm were designed according to the mirrored geometry of the non-affected arm. 3D rendering for various degrees of movement has been carried out for animation.
Comparative Analysis Among Decision Tree vs. Naive Bayes for Prediction of Weather Prognostication
Authors: Sindhu V. , Prakash M.
Published: October 2021

In the previous era, a computer is programmed for some specific task. An electronic device is programmed to do its function electronically. It was done with a target device, the programming environment and the system. We get the necessary intermediate code by running the program with the above said environment and committed into the target device. Thus the device performs the task it was intended to do. In case if we need to change the functionality of the device by the learning experience of the vendor and users, the vendor will upgrade the product. Nowadays in this machine learning era, the devices are programmed in such a way it can learn by its own experience and with the available data it collected it can even manipulate the algorithm by itself with the provided data set. Thus machine learning is ruling this era. We are going to discuss the machine learning algorithms here which was used to predict by itself with the data set collected. Therefore, machine learning is all about learning about computer algorithms that progress its potential through the experience. Thus, Machine learning is presently highly regarded analysis topic and applied to all told application in day to day life. In this paper we have a tendency to extract the knowledge of machine learning algorithms like decision tree, Naive Bayes and enforce the algorithms with sample dataset of weather prognostication.
A Survey on Sports Video Annotation Frameworks
Authors: Chidambaram N. , Nallavan G.
Published: October 2021

Video annotation technique delivers many additional video processing capabilities for several applications. Sports broadcast video content is unique in regard to wealth of information as compared to any other video. Sports video annotation is becoming popular among researchers in recent times because of wide range of applications and challenges it pose. The demand for optimized design of framework for sports video annotation is at peak. This paper surveys state-of-the-art in annotation framework design, particularly for sports applications and provides insight into future aspects. This survey may help researchers to further conceive and develop advanced universal frameworks applied to all sports.
Feasibility of Infrared Thermography for Health Monitoring of Archeological Structures
Authors: Nandhitha N.M. , Emalda Roslin S. , Chakravarthi Rekha , Sangeetha M.S.
Published: October 2021

Archeological assets of the nation are to be preserved and rejuvenated. Ageing of these sites poses a major challenge in assessing the health of these structures. Hence it necessitates a technique that is non contact non invasive and non hazardous. Passive InfraRed Thermography is one such technique that uses an IR camera to capture the temperature variations. Thermal variations are mapped as thermographs. Interpretation of thermographs provides information about the health of the archeological structures. As the paradigm has shifted to computer aided interpretation, segmentation techniques and line profiling are used for describing the hotspot. Of the various segmentation techniques, morphological image processing provides accurate segmentation of cold spot.
Study on Intelligent Data Algorithms Implemented in Wearable for Sports Applications
Authors: Nithya N. , Nallavan G.
Published: October 2021

Technological transformation is unlocking new opportunities in wearable devices used in sports application. Nowadays training the sports involves the use of integrating smart sensors, cameras, internet of things and intelligent data algorithms into a device which is wearable making the players to achieve their maximum performance. These smart devices replace the coach and manage all aspects of technical training except for the physical training given by the real coach. This paper provides a comprehensive study on the intelligent data analysis made on the data acquired from sensors to give a meaningful sense to it. The smart training methods employed currently in various sports are identified and presented. The future directions in this area of research are also presented.
Facial Expression Recognition Under Occlusion Conditions Using ACNN
Authors: BalasundaramA  , AshokkumarS  , Saravanan A  , Sathish Kumar P J  , BalajiS
Published: October 2021

This work proposes a Convolution Neural Network with attention mechanism (ACNN), resembling that human understanding the emotion. Naturally, human perceives the facial emotions depending on particular parts of the face. Several clues are gathered from different parts of face like mouth, lips, cheeks etc, and these are in turn analyzed by the learning model to decide on the facial expression. This work uses ACNN to handle the scenario of occlusion as well.
Story-Telling for Children in Image Processing Using Deep Learning – A Survey Review
Authors: Haritha P. , Vimala S. , Malathi S.
Published: October 2021

In this paper, a natural approach of the describing for the kids which it is brought into use, by making the image engraving technique of Deep Learning into thought. The previous work opens the technique for a course semantic mix plan (CSF) to mine the specialist features to encode the image content through thought instrument. A CSF benefits by three sorts of visual thought semantics which including the thing level, picture level, and spatial thought features, in three-stage course way. In the viewpoint on the current structure, the model takes the moved picture given by the customer as the information and starts recording the image what a PC find in human standard language with point by point explicit presents in the image appropriately exhibiting the significance of picture captioning. This strategy can be applied to the field of youngster’s tutoring to make them pattern of adapting also entrancing. Fundamentally, we facilitate thought instrument with three kinds of features to orchestrate the setting data about the photos from differentviewpoints.
Efficient Face Mask Recognition System by Using Deep Learning Methodology
Authors: Hari Priya K  , Malathi S
Published: October 2021

In this project, mask Recognition System is presented, that utilizes the prospect of Object Detection, completed the assistance of Deep Learning philosophies. The past work gives the topic of article identification by joining coarse-grained and fine-grained discovery philosophies without precedent for police work the moving items on high goal recordings. Period object location and acknowledgment finds careful applications in various fields like clinical applications, security police examination, and independent vehicles. There unit of estimation a few machine and profound learning procedures that unit utilized for object discovery and acknowledgment. The development of a convolutional neural organization (CNN) has given a major forward leap to protest discovery and acknowledgment. Convolutional Neural Network (CNN) has arrived at the exemplification of picture characterization for different application. Explicitly in 2D-CNN, there’s huge advancement for object discovery, beside 3D-CNN, it’s still toward the start of partner time. Profound CNN’s unit acclimated get extra exact directions and to deal with high goal video outlines. By taking this idea of location on the grounds that the base to our work, the framework includes in perceiving the essence of the individual and checks if the face have mask or not, befittingly guaranteeing the individual complies with the assurance safety measures so as that the unfurl of hepatotoxic infection may be managed. The framework will unpredictably be utilized for future face ID with face mask till the pandemic gets died.
Detection and Identification of Pancreatic Cancer Using Probabilistic Neural Network
Authors: Ramya N  , Manoj Kumar B  , Vijay Balaji B  , Kiruthiga Devi M  , Deepika R
Published: October 2021

The fact that pancreatic cancer has a low life expectancy, that is only 9% of people survive five years, makes a diagnosis catastrophic. The majority of patients are diagnosed late in life, where care choices are minimal. Early diagnosis of pancreatic cancer will greatly increase a person’s chances of survival. Accurate PC staging will help doctors have the right treatment plan for PC patients at different stages, as well as the diagnostic measures needed for a quicker cancer recovery. In this proposed project, ultrasound images will be analyzed. The noise in the image is minimised using the Median Filter. In the next step, Gray Level Co-occurrence Matrix (GLCM) and Discrete Wavelet Transform (DWT)are used to extract related features. Following this extraction step, the refined characteristics are fed into a Probabilistic Neural Network (PNN) neural network classifier, which determines whether or not cancer is present. Metrics such as sensitivity, precision, and specificity are used in experimental computation.
Advanced Eyewear with Embedded Hardware for Woman Safety
Authors: Narendhiran.S  , Radhakrishnan.P  , Elangovan.D
Published: October 2021

Human have always lived for the betterment of themselves but the bitter truth is that the process of modernisation has never focussed on making a safe society for women. The lack of self-reliance in women is one of the shortcomings of modernisation. An Advanced eyewear with an embedded camera will remove the barriers in a woman’s life. The combination of wireless communication with IoT sensors increases its scope of use. The People under threat would be intervened with the security officials or alert the emergency contacts saved previously. This paper introduces a security purpose eyewear with the required embedded technology to enhance the life style of a woman. This would bring in quicker and reliable information to the security officials. This would eventually hamper the victimizer from his cruel intentions by creating a fear of being watched.
Li-Fi & Wi-Fi Based Drone for Weather Monitoring with Data Storage in Cloud Using IoT
Authors: Jayashree T R  , Priyadarshini K  , Sri Harini K.
Published: October 2021

In this paper a Li-Fi and Wi-Fi-based weather monitoring system is built using drone. The atmospheric conditions are monitored using the drone and the gathered information is communicated to the ground station using Li-Fi technology. The process of transfer of information involves gathering data using sensors and transfer of data using Li-Fi technology. Data is processed and sent to the receiving station by using Light Fidelity technology. The received data is uploaded to a cloud data base using Wi-Fi technology. Real time data is displayed in an android device using IOT technology. Increased used of wireless communication which used Radio Frequency leads to RF congestion. Light Fidelity system is a best alternative by using a visible light instead of Radio frequency as used by all wireless communication system.
Smart Industry Monitoring and Controlling System Using IoT
Authors: Elumalai. G  , Nallavan. G  , Ramakrishnan. R
Published: October 2021

Air pollution in an ecosystem has proliferated industrial automation. This dissertation concentrates more on industrial automation and has design an embedded device with sensors to monitor and control the toxic gases in industries. This entire prototype is an excellent result for observing the toxic gases in industry and generates information by using data acquisition and transmission of data. “Internet of Things (IoT)” is a important technology behind this and it provide platform to bring together all the devices in the world to the internet. In this dissertation, the parameters monitored are temperature, humidity and gas leakages in industries. The sensor senses the parameters and uploads these data to the cloud with the help of NodeMCU. If observed gas level is above the threshold which is the safety limit of operation, the first alert is intimated from the Google cloud and the controlling action carried out (ie) automatically close gas leakage valves and then industry will take immediate step to control pollution. Or else, the second alert message is sent through Electronic mail (e-mail) to restore the safe limit, as government play role to power outage in the industries. Cloud is used to store the sensed data, which is then transmitted and processed.
APMFT: Anamoly Prediction Model for Financial Transactions Using Learning Methods in Machine Learning and Deep Learning
Authors: Priyadarshini R. , Anuratha K. , Rajendran N. , Sujeetha S.
Published: October 2021

Anamoly is an uncommon and it represents an outlier i.e, a nonconforming case. According to Oxford Dictionary of Mathematics anamoly is defined as an unusal and erroneous observation that usually doesn’t follow the general pattern of drawn population. The process of detecting the anmolies is a process of data mining and it aims at finding the data points or patterns that do not adapt with the actual complete pattern of the data.The study on anamoly behavior and its impact has been done on areas such as Network Security, Finance, Healthcare and Earth Sciences etc. The proper detection and prediction of anamolies are of great importance as these rare observations may carry siginificant information. In today’s finanicial world, the enterprise data is digitized and stored in the cloudand so there is a significant need to detect the anaomalies in financial data which will help the enterprises to deal with the huge amount of auditing The corporate and enterprise is conducting auidts on large number of ledgers and journal entries. The monitoring of those kinds of auidts is performed manually most of the times. There should be proper anamoly detection in the high dimensional data published in the ledger format for auditing purpose. This work aims at analyzing and predicting unusal fraudulent financial transations by emplyoing few Machine Learning and Deep Learning Methods. Even if any of the anamoly like manipulation or tampering of data detected, such anamolies and errors can be identified and marked with proper proof with the help of the machine learning based algorithms. The accuracy of the prediction is increased by 7% by implementing the proposed prediction models.
An Analysis of the Applications of Natural Language Processing in Various Sectors
Authors: Priya B  , Nandhini J.M  , Gnanasekaran T
Published: October 2021

Natural Language processing (NLP) dealing with Artificial Intelligence concept is a subfield of Computer Science, enabling computers to understand and process human language. Natural Language Processing being a part of artificial intelligence provides understanding of human language by computers for the purpose of extracting information or insights and create meaningful response. It involves creating algorithms that transform text in to words labeling With the emerging advancements in Machine learning and Deep Learning, NLP can contributed a lot towards health sector, education, agriculture and so on. This paper summarizes the various aspects of NLP along with case studies associated with Health Sector for Voice Automated System, prediction of Diabetes Millets, Crop Detection technique in Agriculture Sector.
Malicious Attack Identification Using Deep Non Linear Bag-of-Words (FAI-DLB)
Authors: Arul E. , Punidha A. , Gunasekaran K. , Radhakrishnan P , Ashok Kumar VD
Published: October 2021

Online media have flourished in modern years to connect with the world. Most of those stuff users share on blogs like facebook, twitter and many other are pessimistic or just middle spirited. Further, an increasingly professional anti - spyware technologies are dependent on Machine Learning(ML) technology to secure malicious consumers. Over the past few years, revolutionary learning approaches have yielded remarkable outcomes and have immediately generated photos, characters and text interpretations of dynamic weak points. The Purple consumer frequency makes the troll and attacker aim an enticing one. The users will learn the controversial topics and techniques used by malware from articles with ties to harmful material and bogus applications. It is essential to build and customize a lot of potential functionality in vulnerability and application developers around the world. To represent a public web firmware assault with deep logistic inference using Extreme Spontaneous Tree (FAI-DLB). A corresponding output device is named harmful or benign by training an FAI-DLB with different modulation clustered with such a normal or anomalous API. It was therefore equipped to locate a suspicious sequence in unidentified firmware of FAI Deep LB. The outcome demonstrates a good actual meaning of 96.25% and a low spyware assault of 0.03%.
Comparison of core stabilization techniques on ultrasound imaging of the diaphragm, and core muscle thickness and external abdominal oblique muscle electromyography activity
Authors: Lee Jaejin , Kim Dohyun , Shin Yoonkyum , Yi Chunghwi , Jeon Hyeseon , You Sung (Joshua) Hyun , Park Chanhee
Published: October 2021

BACKGROUND: To restore core stability, abdominal drawing-in maneuver (ADIM), abdominal bracing (AB), and dynamic neuromuscular stabilization (DNS) have been employed but outcome measures varied and one intervention was not superior over another. OBJECTIVE: The purpose of this study was to compare the differential effects of ADIM, AB, and DNS on diaphragm movement, abdominal muscle thickness difference, and external abdominal oblique (EO) electromyography (EMG) amplitude. METHODS: Forty-one participants with core instability participated in this study. The subjects performed ADIM, AB, and DNS in random order. A Simi Aktisys and Pressure Biofeedback Unit (PBU) were utilized to measure core stability, an ultrasound was utilized to measure diaphragm movement and measure abdominal muscles thickness and EMG was utilized to measure EO amplitude. Analysis of variance (ANOVA) was conducted at P< 0.05. RESULTS: Diaphragm descending movement and transverse abdominis (TrA) and internal abdominal oblique (IO) thickness differences were significantly increased in DNS compared to ADIM and AB (P< 0.05). EO amplitude was significantly increased in AB compared to ADIM, and DNS. CONCLUSIONS: DNS was the best technique to provide balanced co-activation of the diaphragm and TrA with relatively less contraction of EO and subsequently producing motor control for efficient core stabilization.
Arabic version of the International Knee Documentation Committee Subjective Knee Form (IKDC): Translation and validation
Authors: Almalki Husam , Herrington Lee , Jones Richard
Published: October 2021

BACKGROUND: In order to administer the International Knee Documentation Committee Subjective Knee Form (IKDC) questionnaire to Arabic speakers, a rigorous process of cross-cultural adaptation and validation is required in order to reach equivalence between the original publication and target version of the questionnaire. OBJECTIVES: The main aim of this study is to translate and culturally adapt the IKDC into Arabic to suit the Arabic population. The secondary aim is to assess the Arabic version of the IKDC in order to test the psychometric characteristics (reliability, validity and dimensionality). METHODS: The translation process has been carried out according to cross-cultural adaptation guidelines in accordance with the American Orthopaedic Society for Sports Medicine guidelines with forward/backward translations and pre-testing. The Arabic IKDC, Knee injury and Osteoarthritis Outcome Score (KOOS), RAND-36-Item Health Survey (RAND-36) questionnaire, and visual analogue scales (VAS) of pain were tested in 105 ACLR patients. Test-retest reliability, internal consistency, construct validity and content validity were evaluated. RESULTS: The test-retest reliability proved excellent with a high value for the intraclass correlation coefficient (r= 0.95). The internal consistency was strong (Cronbach’s α= 0.91). Good construct validity by the strong correlations between similar component of the KOOS subscales, Rand-36 subscales and VAS, and good content validity with absence of floor and ceiling effects. CONCLUSIONS: The Arabic version of the IKDC is a valid and reliable instrument for Arabic patients with ACLR. However, further research is required with a more varied knee sample in order to enable generalisation to a wider population.
Does mobilisation of the thoracic spine using mechanical massage affect diaphragmatic excursion in individuals with thoracic hyperkyphosis?
Authors: Jung Sung-Hoon , Hwang Ui-Jae , Ahn Sun-Hee , Kim Jun-Hee , Kwon Oh-Yun
Published: October 2021

BACKGROUND: Thoracic mobilisation improves thoracic hyperkyphosis and respiratory function. Diaphragmatic excursion is associated with respiratory function; however, limited studies have assessed the effect of thoracic mobilisation on diaphragmatic excursion. OBJECTIVE: This study aimed to investigate the effects of thoracic mobilisation on diaphragmatic excursion and respiratory function in individuals with thoracic hyperkyphosis. METHODS: Participants were recruited through Internet advertising and participated voluntarily. Nineteen healthy participants (age: 33.37 ± 6.56 years; height: 170.32 ± 7.92 cm; weight: 69.77 ± 14.70 kg) with thoracic hyperkyphosis underwent thoracic mobilisation for 8 weeks. Diaphragmatic excursion, thoracic kyphosis, and respiratory function were measured. Thoracic mobilisation was provided using a mechanical massage device. RESULTS: Thoracic mobilisation for 8 weeks significantly improved diaphragmatic excursion during deep breathing (p= 0.015), forced vital capacity (p< 0.01), and thoracic hyperkyphosis (p< 0.01). CONCLUSIONS: Thoracic mobilisation can be recommended in respiratory rehabilitation programs to increase diaphragmatic excursion and respiratory function for the management and prevention of respiratory dysfunction in individuals with thoracic hyperkyphosis.
Decreased serum levels of glycerol-3- phosphate dehydrogenase 1 and monoacylglycerol lipase act as diagnostic biomarkers for breast cancer
Authors: Karaosmanoglu Yoneten Kubra , Kasap Murat , Arga Kazim Yalcin , Akpinar Gurler , Utkan Nihat Zafer
Published: October 2021

BACKGROUND: Breast cancer (BC) is one of the most life-threatening cancer types among women. Despite major developments in medical sciences and technologies, the incidence and mortality rates of BC cases are still increasing. One of the reasons for this increase is the absence of an easy to perform early-diagnostic tool. Although there are defined BC biomarkers routinely used for diagnostic and prognostic purposes, none of these biomarkers is useful for early diagnosis. Therefore, early diagnosis of BC remains an important challenge and there is a great need for the early-diagnostic biomarker(s). OBJECTIVE: In this study, we aimed to evaluate the diagnostic and prognostic values of glycerol-3-phosphate dehydrogenase (GPD1) and monoacylglycerol lipase (MAGL) proteins as non-invasive serum biomarkers. METHODS: GPD1 and MAGL serum levels were determined by ELISA for BC patients (n= 100) from five different subtypes, and healthy controls (n= 20), and a comparative analysis was performed to determine statistically significant expression differences among the groups. RESULTS: The results provided evidence that GPD1 acted as a diagnostic biomarker in distinguishing triple-negative breast cancer (TNBC) patients from other subtypes, and MAGL acted as a diagnostic biomarker in distinguishing healthy individuals from BC patients. CONCLUSION: GPD1 and MAGL might be proposed as non-invasive diagnostic biomarkers for BC with high sensitivity and specificity.
Dubai and Barcelona as Smart Cities: Some Reflections on Data Protection Law and Privacy
Authors: Eskhita Radwan , Manda Vijaya Kittu , Hlali Arbia
Published: October 2021

This study introduces a descriptive analysis to carry out the transformation of the Dubai smart city as a case study in the GCC region with reference to the Barcelona smart city. Furthermore, to investigate how the Dubai smart city will deal with the huge amount of the collected personal data through Internet of Things devices and applications. The theoretical analysis shows that the Barcelona smart city can be represented as an effective model, its innovations recommends to be used in Dubai smart city. The analysis founds that the classification of the collected data inside smart city to open and shared data did not provide sufficient privacy for personal data. Therefore, the personal data should be classified explicitly in order to be processed separately under the rules of the data protection law.
Inhalational Anesthetics Do Not Deteriorate Amyloid-β-Derived Pathophysiology in Alzheimer’s Disease: Investigations on the Molecular, Neuronal, and Behavioral Level
Authors: Hofmann Carolin , Sander Annika , Wang Xing Xing , Buerge Martina , Jungwirth Bettina , Borgstedt Laura , Kreuzer Matthias , Kopp Claudia , Schorpp Kenji , Hadian Kamyar , Wotjak Carsten T. , Ebert Tim , Ruitenberg Maarten , Parsons Christopher G. , Rammes Gerhard
Published: October 2021

Background: Studies suggest that general anesthetics like isoflurane and sevoflurane may aggravate Alzheimer’s disease (AD) neuropathogenesis, e.g., increased amyloid-β (Aβ) protein aggregation resulting in synaptotoxicity and cognitive dysfunction. Other studies showed neuroprotective effects, e.g., with xenon. Objective: In the present study, we want to detail the interactions of inhalational anesthetics with Aβ-derived pathology. We hypothesize xenon-mediated beneficial mechanisms regarding Aβ oligomerization and Aβ-mediated neurotoxicity on processes related to cognition. Methods: Oligomerization of Aβ1–42 in the presence of anesthetics has been analyzed by means of TR-FRET and silver staining. For monitoring changes in neuronal plasticity due to anesthetics and Aβ1–42, Aβ1–40, pyroglutamate-modified amyloid-(AβpE3), and nitrated Aβ (3NTyrAβ), we quantified long-term potentiation (LTP) and spine density. We analyzed network activity in the hippocampus via voltage-sensitive dye imaging (VSDI) and cognitive performance and Aβ plaque burden in transgenic AD mice (ArcAβ) after anesthesia. Results: Whereas isoflurane and sevoflurane did not affect Aβ1–42 aggregation, xenon alleviated the propensity for aggregation and partially reversed AβpE3 induced synaptotoxic effects on LTP. Xenon and sevoflurane reversed Aβ1–42-induced spine density attenuation. In the presence of Aβ1–40 and AβpE3, anesthetic-induced depression of VSDI-monitored signaling recovered after xenon, but not isoflurane and sevoflurane removal. In slices pretreated with Aβ1–42 or 3NTyrAβ, activity did not recover after washout. Cognitive performance and plaque burden were unaffected after anesthetizing WT and ArcAβ mice. Conclusion: None of the anesthetics aggravated Aβ-derived AD pathology in vivo. However, Aβ and anesthetics affected neuronal activity in vitro, whereby xenon showed beneficial effects on Aβ1–42 aggregation, LTP, and spine density.
Minimal solutions of fuzzy relation inequalities with addition-min composition1
Authors: Mi Xiao , Wang Xue-ping
Published: October 2021

This paper investigates minimal solutions of fuzzy relation inequalities with addition-min composition. It first shows the conditions that an element is a minimal solution of the inequalities, and presents the conditions that the inequalities have a unique minimal solution. It then proves that every solution of the inequalities has a minimal one and proposes an algorithm to searching for a minimal solution with computational complexity O (n2) where n is the number of unknown variables of the inequalities. This paper finally describes all minimal solutions of the inequalities.
Computational analyses of Fe-Chelation by thiofavipiravir
Authors: Rajabzadeh Halimeh , Abbasi Maryam , Tohoidian Mostafa
Published: October 2021

Existence of iron (Fe) is important for cells of living systems; however, its level of magnitude for those patients infected by novel coronavirus disease (COVID-19) is still a challenging issue. Therefore, such mechanism of function was investigated in this work by assistance of thiofavipiravir (TFav) compounds generated by the well-known favipiravir (Fav) drug used for medication of COVID-19 patents. To this aim, sulfur-substitutions of oxygen atoms of Fav were done and the obtained parent structures were prepared for participating in Fe-chelation function. The results indicated that the modes were suitable for running such Fe-chelation processes, in which favorability and strength the models were ranged in this order: 1O2S-Fe > 1S2S-Fe > 1O2O-Fe > 1S2O-Fe. As a consequence, such idea of sulfur-substitution of Fav drug for more appropriate favorability of participating in Fe-chelation process was sensed by results of this work proposing 1O2S compound as the most favorable one for doing the function. Hence, information about capability of TFav compounds for participating in Fe-chelation processes were provided in this work regarding the challenging issue of Fe-chelation in medication of COVID-19 patients. All results of this work were obtained by performing computations using the density functional theory (DFT) approach