bluuebunny/crossref_metadata_2025 huggingface dataset:
Pied-piping in Russian relative clauses: A microdiachronic analysis
Authors: Pekelis Olga
Published: September 2021

This paper presents an analysis of the pied-piping phenomenon in Russian relative clauses in the 18th–19th centuries and in present-day Russian. As is well-known, the relative pronoun kotoryj ‘which’ tended to precede its pied-piped head in the 18th–19th centuries and tends to follow it today. This difference, which has mainly been investigated for relativization on genitives, is demonstrated to be valid for a number of heterogeneous syntactic contexts. I propose to account for the syntactic shift undergone by the Russian relative clauses since the 19th century in terms of a more general shift in information structure: I argue that the linear order of the relative pronoun and its head that was acceptable in Russian two centuries ago, is now in contradiction with the modern inventory of felicitous information structure patterns.
Australia – Latin America: Opportunities and Challenges of Cooperation in the 21st Century
Authors: Andreev Anton
Published: September 2021

In the first quarter of the XXI century there the system of international relations was changed. Bipolar and unipolar systems have been replaced by multipolarity - the coexistence of different centers of power, when developing countries and regions find their place in the global world. Under these conditions, interregional dialogue began to acquire special significance. Australia and Latin America are looking for the new political partners and new markets. This article shows the evolution of relations between regions in the 2000s and 2010s. Based on the analysis of official state documents, statistics, documents of non-profit organizations, expert assessments, the article considers new mechanisms of cooperation and identifies the main problems and challenges of interaction between the two regions.
The Bolivian puzzle. Why did MAS win the elections again one year after the overthrow?
Authors: Chernyshev Alexey
Published: September 2021

The Luis Arce’s victory in the elections of the 2020 in Bolivia, on one hand, could be perceived as an unexpected one due to an extremely adverse political situation for the Movement toward the Socialism (Movimiento al Socialismo, MAS), but on the other hand it’s still understandable and attributable to some circumstances of the moment, as well as to some fundamental characteristics of the Bolivian society with its political culture peculiarities, complex social structure and the factor of the indigenous ethnic voting. The indigenous ethnic voting factor seems to gain more importance in the Andean region, if we consider the recent elections in Ecuador and Peru in the 2021. Moreover, the return of the MAS to power in Bolivia shall be analysed within the other regional phenomenon which is the strengthening of the left forces positions, contrary to the mid-2010s forecasts about the “right turn” in the Latin America.
Brazilian historiography on the participation of the USSR in the Second World War
Authors: Martynov Boris
Published: September 2021

The article deals with the evolution of views of the Brazilian authors on the role, played by the Soviet Union in the WWII and its contribution to the victory of the anti-Hitlerian coalition. It contains a historiographical review of the works, written by the Brazilian authors on the theme, beginning from 2004. One follows the process of their growing interest towards clarifying the real contribution of the Soviet part to the common victory, along with the rise of the international authority of Brazil and strengthening of the Russo – Brazilian ties. One reveals the modern attitude of Brazilian authors towards such dubious or scarcely known themes as the Molotov – Ribbentrop pact, the battles for Smolensk and Rhzev, town–bound fights in Stalingrad, liberation of the Baltic republics, the Soviet war with Japan, etc. The author comes to conclusion, that in spite of the Western efforts to infuse the people`s conscience with the elements of the “post – truth” in this respect, the correct treatment of those events acquires priority even in such a far off from Russia state, as Brazil.
How do Environmental Factors Affect Drivers’ Gaze and Head Movements?
Authors: Tavakoli Arash , Balali Vahid , Heydarian Arsalan
Published: September 2021

Studies have shown that environmental factors affect driving behaviors. For instance, weather conditions and the presence of a passenger have been shown to significantly affect the speed of the driver. As one of the important measures of driving behavior is the gaze and head movements of the driver, such metrics can be potentially used towards understanding the effects of environmental factors on the driver’s behavior in real-time. In this study, using a naturalistic study platform, videos have been collected from six participants for more than four weeks of a fully naturalistic driving scenario. The videos of both the participants’ faces and roads have been cleaned and manually categorized depending on weather, road type, and passenger conditions. Facial videos have been analyzed using OpenFace to retrieve the gaze direction and head movements of the driver. Results, overall, suggest that the gaze direction and head movements of the driver are affected by a combination of environmental factors and individual differences. Specifically, results depict the distracting effect of the passenger on some individuals. In addition, it shows that highways and city streets are the cause for maximum distraction on the driver’s gaze.
Development and optimization of headspace and headspace-solid phase microextraction for the determination of volatile fuel compounds in environmental sampless
Authors: Balseiro-Romero María , Chaves-Padín Raquel , Monterroso Carmen
Published: September 2021

The application of an effective and sensitive analytical method to determine soil contaminants is a crucial step in the monitoring and remediation processes. In the present work, we optimized the analysis of volatile organic compounds (VFOC) commonly present in fuel: oxygenates (FO-MTBE and ETBE-) and monoaromatic hydrocarbons such as benzene, toluene, ethylbenzene and xylene (BTEX). Headspace (HS) and headspace-solid phase microextraction (HS-SPME) were optimized in water samples, and validated for contaminated soils, using artificially spiked soils. Contaminants were identified and quantified by gas chromatography coupled to mass spectrometry (GC/MS). Matrix effect correction with surrogate standards resulted essential when analyzing soil samples, especially when the sample exerted a strong sorption on the contaminants.
Dietary Selenium reduces the toxic effect of Mercury on different organs (Brain, Gills, Kidney and Liver) of Rohu fish (Labeo rohita)
Authors: Khan Muhammad Xaaceph , Anum Beenish , Bibi Ruqia , Babar Masroor Ellahi , Ashraf Muhammad , Ramzan Amera , Aihetasham Ayesha , Abbas Syed Hassan
Published: September 2021

Because of improbably high partiality with antioxidant selenium to mercury, selenium isolates mercury and reduces its biological handiness to organisms. The present study investigates the effect of mercury (Hg) and selenium (Se) on the fingerling of Labeo rohita. The various sub-lethal concentrations of Hg i.e. 0.125µg/g, 0.250µg/g, and 0.500µg/g was used and incorporated in diet with a commercial diet (fish meal 40%, soya bean 33%, 3 % of vitamins premix, mineral premix and oil each and rice polish 18%). To understand how selenium reduces the toxic effect of mercury, fingerlings were exposed with 6ug/g Se singly and combined with doses of Hg. The effect of these heavy metals was observed after 24, 48, 72, and 96 hours in different organs of (Brain, Gills, Kidney and Liver) of Labeo rohita. The organs of exposed rohu showed significant changes in their microscopic anatomy in comparison to control. Prominent changes were observed in Hg treatments and found embody shrinkage of capillary, and dilation of the hollow lumen. In addition to the aforementioned changes vacuolation, peeling, hydropic swelling, and hyaline degeneration of hollow epithelium were also observed. Cysts and hamorrhage developed additionally seem in the organs of fish. Length of exposure seems to own a profound impact on organs because the increase in length of exposure enhanced the severity of histopathological damages. However, combined doses of metals cause reduction in the toxicity of mercury results in decrease damage in the shrinkage of capillary and dilation of the hollow lumen. During histological study vacuolation, hydropic swelling, and hyaline degeneration of hollow epithelium were also reduced. In Hg, the lethal concentration (LC50) was 0.374ug/g while when Hg and Se were combined, LC50 drops to 0.491ug/g. Results of this study suggest that exposure to Se helps to scale back the impact of mercury on mortality and different organs of Labeo rohita fingerling.
Diketopyrrolopyrrole based highly conjugated small molecules for organic solar cells
Authors: Sana Akram  , Quraishi Azra , Abid Hussain  , Zulfiqar Nadia , Akbar Madiha
Published: September 2021

A series of three donor molecules (DPP-B, DPP-N and DPP-P) based on diketopyrrolopyrrole (DPP) sharing the similar backbone of D-π-A-π-D have been investigated. In these molecules, substituents such as pyrene, naphthalene and benzene act as the electron donating end groups, DPP as the central core unit and thiophene has been used as a bridge between donor and acceptor fragments. Theoretical calculations have been carried out with the help of density functional theory (DFT) and time-dependent functional theory (TD-DFT). For the optimization of geometry of investigated molecules, DFT functional B3LYP/6-31g(d) has been used and TD-B3LYP/6-31g(d) has been used to obtain the best results of calculations inexcited state. DPP-P has been considered a suitable donor molecule among all investigated molecules as it manifests the suitable value of Eg of 2.24 eV and showed the stronger absorption λmaxof 611 nm. Hence, this study reveals that investigated donor molecules are suitable for high performance organic solar cell devices
Šíření salafismu v Africe: mechanismy, strategie a nástroje zahraniční politiky Saúdské Arábie
Authors: Svoboda Daniel
Published: September 2021

The role and importance of religion in many countries' foreign policy seem to be rising again. Many scholars have shown that Saudi Arabia uses the spread of religion, specifically Salafi Islam, as a tool for its foreign policy and to strengthen its influence. Saudi Arabia is a crucial player in the MENA region and the entire Islamic world, and its regional and international importance is constantly increasing. The author considers understanding Saudi Arabia’s activities and its foreign policy strategies, mechanisms, and tools in Africa as very important, as Africa is becoming an arena for new powers once again. The article aims to identify how Saudi Arabia penetrates African states and spreads Salafism. It focuses on analyzing Saudi foreign policy, emphasizing the role of religion and its export. The author analyzes Saudi Arabia's relations with five selected African states, where Salafism is spreading, in the period from 2015 to the present.
Nearly Extinct in the Wild: The Vulnerable Transparency of the Endangered Species List
Authors: Cramer Benjamin W.
Published: September 2021

This article reconstructs the Endangered Species Act as a government information statute. That Act makes use of an official list of vulnerable creatures that is used for agency action to save them from extinction. This article argues that the official list of species is not sufficiently accurate or transparent to citizens, so the compilation of that list does not satisfy the public interest goals of American environmental law or government transparency policy.
Blended Amendments: A Sustainable Approach for Managing Nutrient Deficiency in Rice Fields
Authors:   Department of Environmental Science, Tezpur University, Napaam, Sonitpur, Assam, India, Datta Madhumita Ghosh
Published: September 2021

The application of chemical fertilizer provides absorbable soluble macronutrients for increasing rice yield while reducing the availability of micronutrients and occasionally halting nitrogen mineralisation in the soil. To lessen some of these undesirable effects of chemical fertilization, an effort has been made to prepare blended soil organic amendments by mixing organic materials like rice straw, dried cow-dung and compost prepared from eco-friendly wastes from the kitchen, backyard garden and dried cow-dung mixed in the ratio 1:2:2. Such prepared amendments were applied in the rice field by growing three high-yielding rice cultivars Dikhow, Chandrama and Naveen, in three different rice cropping seasons, pre-monsoon (Ahu), monsoon (Sali) and summer (Boro) during 2015-2016 and 2016-2017 for studying soil properties, crop growth and yield. The key finding of the investigation was that the soil amended with chemical fertilizer showed improvement in soil moisture compared to unamended soil in all three rice fields. However, chemically fertilized soil exhibited lower amounts of available phosphorus, available potassium, diethylenetriaminepentaacetic acid (DTPA) extracted iron and copper in Ahu field, DTPA extracted iron, copper and zinc in Sali field and immobilizing nitrogen in Boro field than blended amendments. Overall, chemical fertilizer + rice straw displayed more available nitrogen and yield in Ahu field, whereas, chemical fertilizer + dried cow dung showed the highest amount of zinc and copper along with the highest yield in Sali rice field and chemical fertilizer+compost had better moisture and soil organic carbon amounts with an ideal acidic pH supporting maximum yield in Boro rice field.
Detection of Planar Defects in Multilayered GFRP Composite Structures Using Low-Field Nuclear Magnetic Resonance
Authors: Sahoo Sanjaya , Kuchipudi Srinivas , Rao R. Narasimha , Buragohain Manoj , Chaitanya Ch. Sri
Published: September 2021

Adhesively bonded interfaces of glass fiber– reinforced plastics (GFRP) composite to rubber and rubber to propellant were investigated for planar interfacial defects with a spatial resolution of 100 μm. Single-sided low-field nuclear magnetic resonance (NMR) with a magnetic field strength of 0.3 T (12.88 MHz proton frequency) has been used for noninvasive inspection of planar defects in GFRP-based multilayered composite structures. Further, in this paper, the application of low-field NMR for adhesive liner thickness measurement is also demonstrated. The investigation revealed applicability of single-sided low-field NMR for onsite field applications. Results were compared with other nondestructive evaluation (NDE) techniques: acousto-ultrasonic and radiographic testing (RT). It is observed that single-sided low-field NMR is an excellent NDE tool to study adhesive bonds and defects such as debonding, variations in thickness to accuracies ranging from 50 to 200 μm, and degradation. In comparison with the acousto-ultrasonic technique and RT, single-sided low-field NMR is observed to be more sensitive.
IMMINNENT ECLAMPSIA AND ECLAMPSIA- RISKS FACTORS AND CLINICAL PRESENTATION, 2 YEARS STUDY
Authors: Gupta Vishnu Kumar , Jasoria Lalima
Published: September 2021

Background: The anatomical, Physiological and biochemical adaptations to Pregnancy are well orchestrated. In certain cases departure from this normal course leads to the pregnancy being complicated. Complications that so develop, endanger the life of both mother and her unborn child. One such dreaded complication is pregnancy induced hypertension. Eclampsia is defined as the pre- eclampsia when complicated with convulsion and/ or coma. However, eclampsia usually proceeds pre-eclampsia. It is one of the leading causes of maternal and perinatal mortality as well as morbidity, throughout the world. Approximately 50000 women die worldwide each year from eclampsia. The reported mortality rate ranges from 1-20%. The perinatal mortality rate of neonates born to eclamptic mothers ranges form 1.3-3%.

Aims: 1.To evaluates the risk factors and clinical presentation in women with imminent eclampsia preoperatively.

To evaluate the risk factors and clinical presentation in women with eclampsia.

Materials and Methods

The present study will be carried out in department of Obstetrics & Gynecology and MEDICINE of National institute of medical sciences (NIMS), Jaipur from October 2012 to September 2014. The study will be conducted on the antenatal and postnatal women admitted in the in patient department of NIMS, Jaipur Study Design: Prospective and retrospective observational study. Study Period October 2012 to September 2014. All the women are evaluated for demographic data, antenatal history, obstetric history, menstrual history, medical and surgical history, mode of delivery, onset of eclampsia, treatment received and maternal and fetal complications.

Result: From the present study, it can be concluded that the age group 21-30 years is most prone for eclampsia and imminent eclampsia and the disease severity is higher in age group less than 30 years. Low socioeconomic status and poor educational status contribute for their increased incidence. These patients generally have higher proteinuria with headache followed by epigastria pain and vomiting. These women are mostly delivered by caesarian section and deliver low birth baby (< 2.5kg), which needs immediate attention and is admitted to nursery.

Conclusion: Eclampsia and imminent eclampsia is a major health problem in pregnant women. And it carries high morbities and mortality. Eclampsia is more complicated than imminent Eclampsia.

Keywords: Eclampsia, hypertension, preeclampsia, proteinuria
Image Classification Between Two Animals
Authors: Tighare Prof. Khemutai , Bhandekar Prof. Rahul , Ragite Harshali
Published: September 2021

We are going to examine the fine-grained object categorization problem of identifying the breed of animal from a picture. To this end we introduce a replacement annotated dataset of pets covering 37 different breeds of cats and dogs. The visual problem is extremely challenging for the cat and dog, particularly cats, are very deformable and there are often exactly subtle differences between their breeds. We make variety of contributions: we first introduce a model to classify cat and dog breed automatically from a picture.
The model adding the shape of the pet animals, captured by a deformable part model detecting the cat and dog face, and appearance, captured by a bag-of-words model that describes the pet fur. Fitting the model involves automatically segmenting the cat and dog within the image. Second, we compare two classification approaches: a hierarchical one, during which a pet animal is first assigned to the cat or dog family then to a breed, and a flat one, during which the breed is obtained directly.
Bearing Fault Detection Using DWT and CNN
Authors: Paranjape Shubham D. , Gaikwad Prof. J. A.
Published: September 2021

Bearing is a key component of satellite inertia actuators such as moment wheel assemblies (MWAs) and control moment gyros (CMGs), and its operating state is directly related to the performance and service life of satellites. However, because of the complexity of the vibration frequency components of satellite bearing assemblies and the small loading, normal running bearings normally present similar fault characteristics in long-term ground life experiments, which makes it difficult to judge the bearing fault status. There are various methods introduced for condition monitoring such as vibration analysis, temperature analysis, wear and debris analysis, image processing etc. Among this image analysis is found to be the most effective method for detection of machine faults. This paper proposes an automatic fault diagnosis method for bearings based on a DWT and CNN.
An analysis of Approaches for Desktop Virtualization and Challenges
Authors: Kumar Rupesh , Yadav Arun Kumar , Verma H N
Published: September 2021

In the Information Technology world, cloud computing technology offering unlimited amount of IT resources and services to end users over the internet on pay-per-use basis. End users are accessing the cloud services on their mobile or personal computers. Service providers are upgrading their services very frequently to enhance the services, and to use their upgraded services, end users are also required to update the specification of their devices. But it will be very costly for the end users to upgrade their devices for high specification to use the enhanced services. Desktop Virtualization is an extensive technology of cloud services. It is the new concept, in which users can access the virtual desktop of required specifications, software and operating system on their old devices anytime and anywhere. With the help of desktop virtualization, users will be benefited by avoiding the cost of frequent upgradation of mobile or personal computer system. Desktop virtualization technology is proving to be a boon for large and small organizations who have to upgrade their computer system with new technology, which is a very costly and challenging process. Desktop virtualization avoids upgrading the hardware of the client machine repeatedly. It allows us to access all applications and data at a low cost on our old machine. This paper presents the comparative analysis of various approaches for desktop virtualization and various challenges which required the solution. Analysis presented in paper has been done based on various performance parameters which will provide the end users low-cost cloud services and best performance on their mobile or personal computers.
Modeling And Simulation for Digital Document Verification Scheme Using Blockchain in P2P Network
Authors: Mahale Miss. Jayashri Rajendra , Chirchi Prof. E. M.
Published: September 2021

Blockchain is very emerging trend in recent years; it is basically decentralized approach which provides transparency to transactional data. Various researchers already introduces blockchain and its state of art, it is too much effective in a large data processing as well as global transactional systems. In this paper we introduce blockchain base E-certificate generation using cloud environment. Basically in real time environment it is hard to carry educational or other important documentaries. Some confidential information should be leak from various centralized systems when any resource has compromised with attackers. In this system we provide drastic supervision base blockchain technique to generate e certificate according to submitted documentary by respective student as well as user. The system illustrates into four different sections. First we defines user can upload his documentary or educational certificates, similarly the middleware authority known as Third Party Auditor (TPA) will verify such documents from authenticated organization. If the entire documents have authorized then it dynamically generate e-certificate with QR code and unique serial identification number. Once this process has done whole information has stored into various data nodes and it returns QR code as well as UID to student. Moreover when any organization wants to verification documentary of respect to student he can submit the QR code or are given Unique Identification number to respective organization. When such organizations will verify the student’s data the blockchain will provide consistent information after the secure authentication. In entire execution we have written open Smart contract, had generation approach using SHA family algorithm, mining algorithm to generator valid hash, in consensus algorithm to evaluate the proof of work.
Handwritten Digit Recognition Using Deep Learning
Authors: M Bhagyashree P , Likhitha L K , Rajesh D S
Published: September 2021

Traditional systems of handwritten Digit Recognition have depended on handcrafted functions and a massive amount of previous knowledge. Training an Optical character recognition (OCR) system primarily based totally on those stipulations is a hard task. Research in the handwriting recognition subject is centered on deep learning strategies and has accomplished breakthrough overall performance in the previous couple of years. Convolutional neural networks (CNNs) are very powerful in perceiving the structure of handwritten digits in ways that assist in automated extraction of features and make CNN the most appropriate technique for solving handwriting recognition problems. Here, our goal is to attain similar accuracy through the use of a pure CNN structure.CNN structure is proposed to be able to attain accuracy even higher than that of ensemble architectures, alongside decreased operational complexity and price. The proposed method gives 99.87 accuracy for real-world handwritten digit prediction with less than 0.1 % loss on training with 60000 digits while 10000 under validation.
Face Expression Recognition using CNN
Authors: Namira Ashna , Naik Aravind , Dsouza Nikhil Floyd
Published: September 2021

The emotions evolved in face have an excellent influence on decisions and arguments about various subjects. In psychological theory, emotional states of an individual are often classified into six main categories: surprise, fear, disgust, anger, happiness and sadness. Automatic extraction of those emotions from the face images can help in human computer interaction also as many other applications. Machine learning algorithms and particularly deep neural network can learn complex features and classify the extracted patterns. In this paper, a deep learning¬based framework is used for human emotion recognition. The proposed framework uses the feature extraction then a Convolutional Neural Network (CNN) for classification. The experimental results show that the proposed methodology increases both of the speed training process of CNN and therefore the recognition accuracy.
IoT Based Hygiene Monitor for Senior Citizens and Mentally Challenged
Authors: B Mounica , S Yashaswini , V Charitha , J Varsha Gowda S , Kennedy Judy
Published: September 2021

Advancements in medical science and technology, medicine and public health coupled with increased consciousness about nutrition and environmental and personal hygiene have paved the way for the dramatic increase in life expectancy globally in the past several decades. However, increased life expectancy has given rise to an increasing aging population, thus jeopardizing the socio-economic structure of many countries in terms of costs associated with elderly health-care and well- being. In order to deal with the growing need for elderly health-care services, it's essential to develop affordable, unobtrusive and easy-to-use health-care solutions. In this paper, we focused on smart diaper-moisture detection system using IOT. It is a paper based expendable dampness initiated Wi-Fi specialized gadget that could be fused into the conventional cellulose-based diaper. The Wi-Fi enabled sensor unit is done for minimal expense producing, low radiation uses Wi-Fi to send notification to authorized person. There are various approaches to distinguish and quantify dampness where a few models already exist, despite the fact that most strategies require dynamic hardware. When the diaper gets genuinely wet, the dampness sensor turns into source that takes care of an oscillator circuit. The power of the transmitted Wi-Fi connection is far below the levels where it could cause any harm to human.
Handwritten Character Recognition Using Neural Network
Authors: Monika  , Ingole Monika , Tighare Khemutai
Published: September 2021

In this paper, an enterprise is made to perceive manually written characters for English letters so as. The precept point of this mission is to plan a master framework for, "HCR(English) utilizing neural community". That could viably understand a particular individual-of-kind layout making use of the artificial neural community approach. The manually written man or woman acknowledgment trouble has grown to be the maximum famous trouble in ai. Handwritten man or woman acknowledgment has been a difficult space of exam, with the execution of gadgets getting to know we suggest a neural network-based methodology. The development is based totally on neural network, that is a subject of look at in artificial intelligence. Distinct strategies and methods are used to broaden a handwriting person recognition system. Acknowledgment, precision fee, execution, and execution time are massive versions on the way to be met through the technique being applied. The purpose is to illustrate the effectiveness of neural networks for handwriting character recognition.
Secure File/Data Transfer Between Airgap Network
Authors: Navaneeth Arathi , P Vignesh P , R Sreehari N , Pramilarani K.
Published: September 2021

Wireless Data communication is fastest growing technology era in which the research society has recently embarked. Today, Computer data can include financial transactions such as electronic payments, M- wallets and sensitive multimedia contents. The explosive volumes of computer devices personal data, bring-up more attention to securely data storage rather than consideration on data privacy and confidentiality levels. In this scenario Air Gap Data Communication, Machine Leaning (ML) and image processing brings an important role in the electronic data management. It is always expensive and hard to manage the data manually without adopting machine learning and image processing techniques using metadata. The contribution of this research article is to demonstrate a securing computer data storage secrecy and privacy in cloud communication framework in terms of automatic data classification using computer training datasets with help of Training dataset which classifies the data based on the confidentiality level of the record with higher accuracy and powerful timelines as compared to the traditional KNN algorithms and RSA algorithm securing such confidential data category afterwards by applying various existing cryptographic solutions to assuring data privacy, confidentiality levels and alerting the use of abusive contents and simulation results demonstrates that reducing the overall cost. Training dataset which classifies the data based on the confidentiality level of the record with higher accuracy and powerful timelines as compared to the traditional KNN algorithms and RSA algorithm securing such confidential data category.
Undergraduates' Perception of (STEM) Education as a Tool for Enhancing Economic Development in Sokoto State, Nigeria
Authors: Matazu Dr. Suleiman Saadu
Published: September 2021

Economic development appears to be a major challenge confronting nations and individuals across the globe in recent times. Economic development is the process by which a nation improves the economic, political, and social well-being of its people. Nigeria which is tagged as the giant of Africa, and also endowed with numerous natural and human resources, is still battling with the menace of economic under development particularly Sokoto state. This paper therefore, examined the perception of undergraduates on (STEM) education as a tool for enhancing economic development. The study employed a quantitative research design, with a sample of 200 undergraduate students of Usmanu Danfodiyo University, Sokoto (UDUS). The sampled students were randomly selected from four programs of study. A questionnaire containing (12) items, entitled Perception of Undergraduates on STEM for Enhancing Economic Development (PUSEEED) was utilized in collecting data for the study. The instrument was content validated by 3 experts. The reliability index of 0.82 was calculated for the instrument using the Cronbach Alpha. The result of the study indicated that the undergraduates appreciated the introduction of STEM education as a tool for enhancing economic development and they looked forward to actively participating in the program once it is practically integrated into their programs. It was recommended among others that STEM education should be incorporated into the entrepreneurial programs of Nigerian universities especially in Sokoto state, Nigeria for meaningful economic development.
Heart Disease Prediction using Machine Learning Techniques
Authors: Ponnala Ramesh , Sowjanya K. Sai
Published: September 2021

Prediction of Cardiovascular ailment is an important task inside the vicinity of clinical facts evaluation. Machine learning knowledge of has been proven to be effective in helping in making selections and predicting from the huge amount of facts produced by using the healthcare enterprise. on this paper, we advocate a unique technique that pursuits via finding good sized functions by means of applying ML strategies ensuing in improving the accuracy inside the prediction of heart ailment. The severity of the heart disease is classified primarily based on diverse methods like KNN, choice timber and so on. The prediction version is added with special combos of capabilities and several known classification techniques. We produce a stronger performance level with an accuracy level of a 100% through the prediction version for heart ailment with the Hybrid Random forest area with a linear model (HRFLM).
Automatic Summarization on Restaurants Opinion Mining
Authors: Rathi Miss Sonal Anil , Chhajed Prof. Krutika K
Published: September 2021

Innovation has been a fundamental piece of our lives. When going bent another cafe/restaurants or bistro, individuals normally use sites or applications to question close by spots and afterward select one hooked in to normal rating. Notwithstanding, the traditional rating is now and again insufficient to foresee the character of the café as individuals have alternate points of view and wishes while assessing an eatery. During this paper, an overview framework for sentiments in eatery audits is proposed. The framework may be a useful device for clients during a hurry to assist them improve decisions about the nature of a restaurant while saving their time. This is often finished via naturally and rapidly furnishing the clients with a synopsis of the sentiments within the café's/restaurants surveys. The proposed synopsis framework has been actualized during a versatile area based application with KNN Algorithm and Multi keyword search it accomplished a high convenience score.
Anonymization Techniques for Privacy Preservation in Social Networks: A Review
Authors: Chavhan Kalpana , Challagidad Dr. Praveen S.
Published: September 2021

Any data that user creates or owns is known as the user's data (For example: Name, USN, Phone number, address, email Id). As the number of users in social networks are increasing day by day the data generated by the user's is also increasing. Network providers will publish the data to others for analysis with hope that mining will provide additional functionality to their users or produce useful results that they can share with others. The analysis of social networks is used in modern sociology, geography, economics and information science as well as in various fields. Publicizing the original data of social networks for analysis raises issues of confidentiality, the adversary can search for documented threats such as identity theft, digital harassment and personalized spam. The published data may contain some sensitive information of individuals which must not be disclosed for this reason social network data must be anonymized before it is published. To do the data in nominate the anonymization technique should be applied, to preserve the privacy of data in the social network in a manner that preserves the privacy of the user whose records are being published while maintaining the published dataset rich enough to allow for the exploration of data. In order to address the issue of privacy protection, we first describe the concept of k-anonymity and illustrate different approaches for its enforcement. We then discuss how the privacy requirements characterized by k-anonymity can be violated in data mining and introduce possible approaches to ensure the satisfaction of k-anonymity in data mining also several attacks on dataset are discussed.
Face Liveness Detection : An Overview
Authors: Policepatil Shweta , Hatture Sanjeevakumar M.
Published: September 2021

As the world becomes more and more digitized, the threat to security grows at an alarming rate. The mass usage of technology has garnered the attention and curiosity of people with foul intentions, whose aim is to exploit this use of technology to commit theft and other heinous crimes. One such technology used for security purposes is “Facial Recognition”. Face recognition is a popular biometric technique. Face recognition technology has advanced fast in recent years, and when compared to other ways, it is more direct, user-friendly, and convenient. Face recognition systems, on the other hand, are vulnerable to spoof assaults by non-real faces. To protect against spoofing, a secure system requires liveness detection. This study examines researchers' attempts to address the problem of spoofing and liveness detection, including mapping the research overview from the literature survey into a suitable taxonomy, exploring the fundamental properties of the field, motivation for using liveness detection methods in face recognition, and problems that may limit the benefits.
Reclamation of Potholes by Utilisation of Plastic
Authors: Saji Nidhi , Khedikar Isha P. , Diwan Seema
Published: September 2021

The rate of accidents caused by potholes is increasing day by day. So, potholes must be repaired as soon as possible. This paper aims to repair potholes by using plastic. The introduction of plastic in bitumen modifies the characteristic of bitumen. Tests were done on aggregate and bitumen to check their quality. Marshall Test on bitumen were done on different percentage of bitumen and plastic. From the result it was observed that as the percentage of plastic is increased the stability value of Marshall test is also increased.
Port Efficiency Assessment for Selecting Transit Port for West African Land Locked Countries
Authors: Miezah Whajah Samuel , Whajah Gifty
Published: September 2021

The fundamental purpose of this paper is to assess the efficiency of port in West Africa and selectively select the best transit port for landlocked West African countries and for that matter data envelopment analysis will be used for this research. Seven (7) ports were selected out of twelve (12) using container throughput level for the basis of their selection, whiles DEA model was used for the determination of their relative efficiencies and their over time efficiencies through window analysis. It is noted that. The study noted that based on the operational efficiency of the port of Tema in Ghana, port Lomé and port of Douala, they should serve and standout as the transit port when it comes to West African landlocked countries selecting of transit port. It is recommended that there should be an expansion in infrastructure which is which should be the target so as to improve operational efficiency in West African port. Ports authorities should look more into that because is the beacon of ports efficiency and performance, because infrastructure propels ports mass production once those infrastructures are properly utilized.
Evaluation and Characterization of Microalgae from Kalaburagi Region as a Potential Source of Biomass Production
Authors: Korban Asha Jagan , Parameshwar A. B. , Sulochana M. B.
Published: September 2021

Microalgaes are considered for a large number of applications such as biomass and energy production due to their increased capability of biomass production. Various biotic and abiotic factors influence the growth of microalgae. Among the abiotic factors include the temperature, light intensity, pH of the medium, salinity, and nutritional conditions play the major role. Ten samples of microalgae were collected from different sites of water bodies from Gulbarga University campus. The microalgae isolated were identified and characterized using light microscope, SEM and PCR based 18s rRNA. Influence of cultural conditions such as carbon and nitrogen sources, pH, temperature and salinity on biomass production were studied and analyzed. Among the strains identified, a novel species was isolated and identified as Scenedesmus vacuolatus AK1. The maximum growth rate and biomass productivity can be achieved by providing glucose as carbon source and urea as nitrogen sources at an optimum of 0.5gm/l and 0.1mg/l irrespectively. It was also observed that the strain showed a good growth profile and increase in biomass production at an optimum alkaline pH of 8. Maximum biomass productivity of 0.6g/l was observed at an optimum temperature of 30˚C in BG-11 medium. Maximum biomass yield of 1.45g/l was observed at 5mM NaCl concentration.
An Experimental Investigation on The Influence of Nano Silica on The Strength and Durability Characteristics of Self Compacting Concrete
Authors: Kumar B. Arun , Begum Shamshad
Published: September 2021

Self-compacting concrete (SCC) is also considered as a concrete which can be placed and compacted under its own weight with little or no vibration without segregation or bleeding. The use of SCC with its improving productions techniques is increasing everyday in concrete production. It is used to facilitate and ensure proper filling and good structural performance of heavily reinforced structural members. Recently, nano particles have been gaining increasing attention and have been applied in many fields to fabricate new materials with novel functions due to their unique physical and chemical properties. Degradation of concrete members exposed to aggressive sulphuric acid environments is a key durability issue that affects the life cycle performance and maintenance costs of vital civil infrastructure. Sulphuric acid in groundwater, chemical waste or generated from the oxidation of sulphur bearing compounds in backfill can attack substructure concrete members. Moreover, concrete structures in industrial zones are susceptible to deterioration due to acid rain of which sulphuric acid is a chief component. In this work 40Mpa self-compacting concrete is developed using modified Nan-Su method of mix design. Slump flow, J-Ring, V-funnel tests are conducted to justify the fresh properties of SCC and are checked against EFNARC (2005) specifications. Specimens of dimensions 150x150x150mm were cast without nano silica and with two nano silica are added in different percentages(1%, 1.5% and 2% by weight of cement) to SCC. To justify the compressive strength for 7 and 28days, specimens are tested under axial compression. Durability properties were also studied by immersing the specimensin5% HCl and5% H2SO4. The particle packing in concrete can be improved by using Nano-silica which leads to densifying of the micro and nanostructure resulting in improved mechanical properties. Nano-silica addition to cement based materials can also control the degradation of the fundamental C-S-H (calcium-silicate-hydrate) reaction of concrete caused by calcium leaching in water as well as block water penetration and therefore lead to improvements in durability.
Investigation of the Effect of the Use of Bamboo and Silver Yarn on Antibacterial Activity in Towel Fabric
Authors: PAKSOY Navruz , KONUKOĞLU Seval , AYAR Levent , BATÇIK Cansu , AYDIN Hüseyin
Published: September 2021

Towels in home textile products are textile surfaces that are frequently used in daily life. Towel products are generally used to remove moisture and water from the body. In this context, the main performance feature expected from terry fabric due to the contact of the product with the skin is softness, fast drying and antibacterial properties. Due to the moisture on the towel fabrics, it provides a suitable environment for bacterial growth. For this reason, studies are carried out on the antibacterial properties of the towel. In this study, it is aimed to conduct research activities within the scope of developing antibacterial terry fabric. For this purpose, different terry fabric productions were made using silver yarn, bamboo and antibacterial chemicals, and their antibacterial properties were examined. In this context, the antibacterial chemical finishing process, known as the classical method, was applied to the towels, which were first woven from 100% cotton yarn. In addition, towel fabrics were produced by using 70% bamboo-30% cotton yarn and 92% cotton-8% silver yarn. Antibacterial activities of the obtained fabric samples against S.aureus and K. pneumonie bacteria according to AATCC 100 standard were examined. According to the obtained test results, the antibacterial activity level of bamboo blended towels close to the antibacterial activity level obtained with chemical finishing was observed in the trials.
Bloqueo auriculoventricular completo en paciente tratada con rivastigmina transcutánea
Authors: Carranza-Urones Julia , Grocin-Vidaondo Ana Isabel , Vals-Casulá Vanessa , Bernad-Barcos Maia , Iribar-Diéguez Ion Koldobika
Published: September 2021

Usar fármacos con múltiples efectos secundarios e interacciones medicamentosas posibles es muy común en una población cada vez más envejecida y polimedicada. Esto pasa con la rivastigmina, utilizada como tratamiento de la demencia. Entre sus posibles efectos secundarios encontramos alteraciones graves del ritmo cardíaco. El antídoto es la atropina, pero ocasionalmente el paciente precisa de la implantación de un marcapasos porque los efectos persisten. Por ello, preventivamente, antes de iniciar un tratamiento con este tipo de fármacos, es imprescindible realizar un electrocardiograma al paciente y, en caso de existir trastornos del ritmo o de la conducción, valorar el riesgo/beneficio del mismo.
Encefalopatía de Hashimoto resistente a corticoides: reporte de caso y revisión bibliográfica
Authors: García-Gili Manuel , Reynoso Aldana
Published: September 2021

Varón de 46 años con antecedente de hipotiroidismo que ingresa con un cuadro de agitación psicomotriz, alteración del lenguaje y convulsiones, con requerimiento de ventilación mecánica. Presentaba títulos séricos elevados de anticuerpos antitiroideos con detección de anticuerpos anti-tiroglobulina en el líquido cefalorraquídeo. Se realizó tratamiento endovenoso con inmunoglobulinas, alcanzando recuperación completa sin recaídas. Nuestro objetivo es explicar la utilidad de la terapia endovenosa con inmunoglobulinas en pacientes con encefalopatía de Hashimoto que no responden a la terapia inicial con corticoides.
A A Survey of the Link Prediction on Static and Temporal Knowledge Graph
Authors: Le Thanh , Nguyen Hoang , Le Bac
Published: September 2021

Link prediction in knowledge graphs gradually plays an essential role in the field of research and application. Through detecting latent connections, we can refine the knowledge in the graph, discover interesting relationships, answer user questions or make item suggestions. In this paper, we conduct a survey of the methods that are currently achieving good results in link prediction. Specially, we perform surveys on both static and temporal graphs. First, we divide the algorithms into groups based on the characteristic representation of entities and relations. After that, we describe the original idea and analyze the key improvements. In each group, comparisons and investigation on the pros and cons of each method as well as their applications are made. Based on that, the correlation of the two graph types in link prediction is drawn. Finally, from the overview of the link prediction problem, we propose some directions to improve the models for future studies.