bluuebunny/crossref_metadata_2025 huggingface dataset:
Study on Quantity Analysis of Chloride Presence in Ganga Basin
Authors: Kumar Mayank
Published: May 2023

Water pollution and its consequences for humans and agriculture compelled us to examine a variety of water quality indicators. We used a variety of water quality testing methods, including the Wrinkler's method, the EDTA procedure, a pH meter, and others. Ganges water samples are analyzed for their physicochemical properties. Throughout the months of April and May of 2010, water samples were taken from several locations in and around Kanpur. To determine the importance of water quality indicators, a correlation analysis was done between a wide range of properties, including pH, temperature, turbidity, total hardness (TH), metal, total alkalinity (TA), dissolved oxygen (DO), and suspended solids (SS) and Chloride(Cl). It was found that, with the exception of turbidity, all of the properties are well within the WHO-recommended ranges. Several negatively charged species, as NO3 - and Cland Fare, were also discovered to be beyond of acceptable ranges.
The Economic Value of Plastic Waste Used as Paving Aggregate
Authors: Negi Ankit
Published: May 2023

Solid waste, of which plastic waste is a significant part, is plentiful and often gets thrown away without being properly processed into a usable resource. Municipal plastic garbage disposal has increased dramatically, particularly in metropolitan areas, and this has a negative effect on the aesthetic quality of the environment. As a binding agent, plastic proved to be quite useful  pliable asphalt mixtures made from bitumen. By limiting fracture formation and decreasing rainfall penetration, this effective strategy helps pavements tolerate greater temperatures, which would otherwise contribute to the development of potholes. Water seepage is decreased and crushing and abrasion parameters are increased in these pavements. Roads made of plastic would be a great solution to the problem of potholes caused by India's hot and humid environment, where temperatures often exceed 50°C and heavy rains cause havoc, leaving most roads in terrible condition.

Road paving, airport runways, parking garage floors, and other related construction applications often employ a composite material called bituminous concrete (BC). The final product is made by layering mineral aggregate with asphalt or bitumen (used as a binder), and then crushing the resulting mixture. The substantial distinction in daily and seasonal temperature, coupled with the ever-increasing volume of traffic comprised primarily of commercial vehicles, has put us in a precarious position that necessitates creative solutions for enhancing the characteristics and quality of the pavement through the implementation of some necessary modifications that must therefore satisfy the both strength and economic aspects.

When viewed from an environmental point of view, it is apparent that polythenes are a major contributor to air pollution. As it has been shown that polythenes are not biodegradable, finding a solution for waste polyethene has become an essential issue.
Corrosion Behavior and Internal Pressure Capacity of a Composite System Used to Connect Metallic Pipes
Authors: Kumar Mayank
Published: May 2023

This research aims over how different kinds of fiber-reinforced plastic (FRP) may change the internal pressure capacity and corrosion behavior of linked metal pipes. Hence, aluminum pipes have been fabricated for further usage in wrapping with various FRP and welding. Used FRP materials include carbon fiber/epoxy (CFRP) and kevlar fiber/epoxy (KFRP) (CFRP). These fibers have been slit into narrow strips for use in the fabric-winding technique of connecting. Four-layer KFRP pipes and eight-layer KFRP-CFRP pipes are also viable options that have been investigated. On the other hand, comparisons have been made using pipes that have two different kinds of welding. The findings demonstrated an increase in the internal pressure capacity of the pipe compared to welding. The corrosion test was finally performed. The findings demonstrated that FRP connecting methods outperformed both welded and unjoined pipes in terms of corrosion resistance. These findings indicate that FRP composites have a bright future for use in pipe joining.
An Implementation of Deep Wavelet Auto Encoder-Based Deep Neural Network Brain MRI Image Classification for Cancer Detection
Authors: Garg Navin
Published: May 2023

Both computational intelligence and pattern recognition depend on Brain lesion segmentation and classification. In this procedure, an effective algorithm was used to segment the lesion, and its characteristics, including LBP, were paired with the GLCM to extract the data from the picture. A morphologically based fuzzy C-means clustering technique (M-FCM) is suggested for clustering in segmentation. The severity of the information from the brain is then classified using CNN utilising the procedure used in the medical profession to detect brain lesions. The major goals of this procedure are to locate the malignant area on an MRI of the brain and to categorise the severity of that brain in order to increase process effectiveness.
Design of Convolutional Neural Networks Model for Fine-Grained Classification of Cervical Cells
Authors: Chattopadhyay Saumitra
Published: May 2023

One of the most prevalent cancers in the world and one of the most harmful to human life is cervical cancer (CC). This procedure was created to increase the diagnostic accuracy of CC in such dataset pictures in order to better detect and forecast illness. Therefore, we attempted to demonstrate a convolution neural network-based classification framework for CC that is intelligent and effective and has a comparatively basic architecture in comparison to others. Additionally, we offered a simple and useful technique for CC classification from cytological pictures using effective feature extraction or accurate cell image segmentation effort. The outcomes of automatic cell detection are contrasted with those of other cutting-edge cell detection methods as well as hand annotation of the underlying data. Many of the procedures for cell detection and categorization are still being worked on. This procedure's primary goals are to pinpoint the cell area and increase segmentation precision. With an F1 score of 0.96, the suggested approach has the highest cell detection accuracy.
Face Sketch to Photo Matching Through Dynamic Local Feature Extractions and Cascaded Static
Authors: Pandey Chetan
Published: May 2023

By using a method of cascading static and dynamic local feature extraction, we attempt to deal with the identification of a photo from a face sketch effect of these effects in this process. To ensure that the feature vectors created are depending upon the appropriate patches. Along with that approach, we include the closest neighbours technique for matching sketches and photos, which concatenates the feature vectors obtained from local static extraction. Following the extraction of the image's characteristics, the most comparable images are narrowed down based on their closes neighbours. Eventually, feature vectors from the local dynamic extraction approach are used to rematch these images. The closest neighbours technique is used to match the feature vectors. The major goal of this technique is to increase the detection system's precision while simultaneously increasing recognition rates and feature stability.
Designing Of Efficient Model for Facial Feature Identification and Classification Using a Sparse Fingerprint Algorithm
Authors: Gupta Sonali
Published: May 2023

By leveraging the geometrical and textural data of the retrieved local characteristics to align the probing partial face to gallery faces throughout this process, we present a novel partial face identification technique. Our fundamental assumption is that the cost function of our alignment approach ought to be reduced if the probing partial face patch and the gallery face picture are using the exact same individual. The similarity between the partial probing patch also the gallery photos across the identified facial feature points is also computed using a point-set distance metric that we provide. The usefulness of the suggested technique is demonstrated by experimental findings on four popular face datasets. This method focuses on choosing localised features from facial detection photos to distinguish between classes depending upon regression results, or partial F-test. The results demonstrate that traditional procedures are more resilient in terms of appropriate feature selection and categorization. The most noticeable characteristics were chosen by introducing a reliable method termed stepwise linear discriminant analysis, which concentrates on choosing the localised features from the face frames and classifying them relied upon regression values. A feature extraction procedure's goal is to extract the localised characteristics from faces that the earlier feature extraction methods were unable to analyse.
Urban Land Chang Detection on Remote Sensing Images Based on Local Similarity Siamese Network
Authors: Gupta Amit
Published: May 2023

Lloyd created the well-known signal quantization issue. We define a different, related problem: The best translation of digital fine grayscale images to a coarser scale (for example, medical imaging with 9–13 bits per pixel) (for instance, 8 bits per pixel on standard computer displays). Although the latter pertains to a mostly digital domain, the former problem is specified primarily in the actual signal domain with smoothly distributed noise. The conventional quantization methods are essentially inapplicable non typical scenarios of quantization of the previously digitised pictures, as we demonstrate in this study, due to this discrepancy. Through experimentation, we discovered that Lloyd's technique is greatly outperformed by a dynamic programming-based solution. The maintenance of any picture database must have two fundamental elements: data representation and content description. In this study, a wavelet-based system called the Waveguide is suggested, which unifies these two elements into a single framework. In this study, a unique way of rating the differences between two satellite photos obtained at various times is presented by this system for unsupervised change analysis. Change Vector Analysis Technique was employed in the current system of change analysis. The polar CVA representation serves as the foundation for this system. In the suggested method of change analysis, the Hamming distance, which is predicated upon binary descriptors, is utilised as a similarity metric.
5G Networks: Technologies, Applications and Challenges
Authors: Gupta Amit
Published: May 2023

The rollout of 5G networks is gaining momentum rapidly around the globe, and it holds the promise of delivering incredibly high data transfer rates, minimal latency, and huge interconnectedness. This article provides an overview of 5G networks, including a discussion of the technology, applications, and issues involved. First, we will discuss the technical features of 5G networks. These aspects include the spectrum, radio access methods, network design, and upcoming technologies such as network slicing and edge computing. After that, we will talk about a variety of applications, such as the Internet of Things, virtual reality, and autonomous cars, that have the potential to benefit from the capabilities of 5G networks. In conclusion, we investigate the primary obstacles that need to be conquered in order to fully fulfil the potential of 5G networks. These obstacles include concerns over regulation, privacy, and security. In addition, we give an overview of the present state of 5G networks and finish up with potential future research and development possibilities. The study is based on a survey of the relevant literature, and its primary objective is to deliver a full comprehension of the current state of the art regarding 5G networks.
A Machine Learning-based Framework for Medical Decision Support Systems
Authors: Sejwal Lakshita
Published: May 2023

Due to the complexity of clinical decision-making and the necessity for patient-specific suggestions, medical decision support systems (MDSS) are becoming more significant in healthcare. Machine learning (ML) can analyze and learn from vast volumes of patient data, making it a strong tool for MDSS development. Domain specialists, data scientists, and software engineers must work together to produce MDSS. This study provides a Machine Learning-based MDSS development approach that prioritizes stakeholder collaboration. Medical Decision Support Systems (MDSS) provide tailored recommendations based on clinical guidelines, medical expertise, and patient data to improve patient outcomes and healthcare delivery. Machine learning (ML) can analyze and learn from vast volumes of patient data, making it a strong tool for MDSS development. This study provides a Machine Learning-based MDSS development framework with data preparation, feature selection and extraction, model training and evaluation, and integration and deployment. To ensure MDSS accuracy and efficacy, domain experts, data scientists, and software engineers collaborate.
Forecast of Stock Market using Machine Learning Strategies
Authors: Dubey Bhanu Prakash
Published: May 2023

Accurately predicting the stock market is one of the things that investors are most interested in since it may help them make money in the economy. Given that such markets are significantly influenced by volatility and news, it is difficult to predict stock prices, which are solely dependent on market timing. Owing to this difficulty and volatility, it is vital to evaluate stock forecasting using historical data as well as external variables such as investor behaviour, social media, and financial news. Thus, this study recommends using regression and machine learning algorithms to estimate the price of equities on upcoming days based on investor sentiment. The experiment is conducted on Yahoo Finances and combines Twitter repository data on investor sentiment. In the subsequent step, the concept of sentiment analysis is applied to the monitoring of Twitter user tweets. The tweets are then sorted into positive and negative groups based on the sentiment score. In addition, machine learning algorithms are used to forecast Yahoo Finance stock values. To solve this issue, we propose reducing the complexity of time sequence models by employing regression approaches that integrate a hybridized concept of sentiment analysis and machine learning algorithms, which may result in higher accuracy. The testing results validate the best linear regression prediction accuracy and demonstrate an overall system performance enhancement.
Automatic Pneumonia Diagnosis Using Capsule Network Working in Alignment with CNN Model
Authors: Kumar Indrajeet
Published: May 2023

As a result of the COVID-19 pandemic, the populace has seen one of the most drastic periods in human history, and the ailment tends to grow fast across the worldwide. It is believed that the disease primarily causes respiratory issues in humans. Recognising this disease has also tend become a difficult activity due to the fact that both diseases have comparable effects on the lungs. It is believed that pneumonia is an infection raised by bacteria in parts of the alveoli in lungs that, if left untreated, can result in death. Thus, the development of an automated method to diagnose the sickness could be advantageous to the human species. As a result of the ongoing growth of these areas of research, it has been seen that the basics of deep learning and machine learning continue to contribute to the execution and examination of healthcare based images and the performance classification of the same. In this study, we evaluate the CNN model and a CNN based encapsulation featured capsule network for predicting impacted and unaffected chest X-ray images patients.
A Comprehensive Survey of Artificial Intelligence (AI): Principles, Techniques, and Applications
Authors: Rani Poonam
Published: May 2023

AI has emerged as a transformational technology with enormous potential to change a wide range of sectors. Its foundations are founded on robots' capacity to learn and do jobs that would normally need human intellect. AI techniques such as machine learning and deep learning have grown in sophistication, enabling for the development of strong AI applications in fields such as healthcare, finance, and transportation. Yet, the fast development and implementation of AI raises a slew of issues that must be addressed. Ethical issues, data privacy and security, transparency and explainability, legislation and policy, technological hurdles, adoption and acceptability, accessibility, and interaction with current systems are among these challenges. To address these issues, industry, government, and academia must work together to create ethical frameworks, invest in research and development, and encourage openness and accessibility. Notwithstanding these obstacles, the potential advantages of AI are enormous. AI has the ability to improve efficiency, production, and decision-making in a variety of industries. It also has the ability to enhance people's lives and find answers to some of the world's most urgent problems. Overall, the ideas, methodologies, and applications of AI provide great prospects for good change; nevertheless, addressing the issues is critical to ensuring that AI is created and utilised in an ethical and responsible manner.
A Machine Learning-based Approach for Intrusion Detection and Prevention in Computer Networks
Authors: Dubey Bhanu Prakash
Published: May 2023

The potential of cyberattacks and network penetration has increased due to modern enterprises' increasing reliance on computer networks. Such attacks are detected and prevented by intrusion detection and prevention systems (IDPS), although conventional rule-based solutions have difficulties identifying unidentified attacks. Due to its capacity to learn from data and spot patterns of assault that conventional methods could miss, machine learning (ML) techniques have been gaining prominence in IDPS. This article provides a thorough analysis of the several ML methods utilized in IDPS, including supervised, unsupervised, and hybrid techniques. Also, a hybrid ML-based IDPS that combines the advantages of several methodologies for better performance is proposed. Furthermore, covered are the difficulties with ML-based IDPS and potential solutions. It is demonstrated how ML-based IDPS may be applied in real-world situations, emphasizing the advantages of applying ML to intrusion detection and prevention. In conclusion, this study offers insights into the most recent methods for ML-based IDPS and their potential to enhance network security.
Prevalence of Osteoporosis and Its Correlation With Common Secondary Risk Factors in Population from Rural Areas of South India
Authors: Ram Pothuri Rishi , Narayan Praveen , Janardha Pavith , Chintapalli Surya Sri Karun
Published: May 2023

Background. Osteoporosis is a common metabolic disorder characterised by decreased bone mass and weakened micro-architecture of bone tissue. After 50 years of age, one in three women and one in five men experience osteoporotic fractures. This is projected to cause a yearly loss of 5.8 million healthy life years to disability. The number of patients who attend the outpatient clinic and emergency department of Sanjay Gandhi Institute of Trauma and Orthopaedics with fragility fractures has been increasing, hence to know the prevalence of osteoporosis in the general population who were asymptomatic, we decided to conduct a study in the rural areas of south India.
Aims: 1) to estimate the prevalence of osteoporosis among the population above 50 years in rural areas of south India; 2) to determine the correlation between common secondary risk factors for osteoporosis like tobacco consumption, alcohol, diabetes, and hypertension.
Results. The prevalence of osteoporosis in the rural population was more in females at 42.2%, whereas the males had a prevalence of 32.5%. Among the population with habits of tobacco consumption and alcohol consumption, the prevalence was 78% and 30.6% respectively. 20.2% of non-smokers and 39.7% of non-alcoholics were osteoporotic. Among the population with comorbidities, 53.6% of diabetes and 55.4% of hypertensives were osteoporotic. 33.7% of non-diabetics were osteoporotic, and 29.5% of hypertensives were osteoporotic. The correlation between osteoporosis and the individual risk factors ranged between weak negative to moderately positive (r = -0.2 to 0.5). The correlation between the combination of all the four risk factors and osteoporosis is weakly positive (r = 0.339), which is highly significant (p0.001).
Conclusion. Overall, the findings of this study suggest that addictive habits such as tobacco and alcohol consumption may have a significant impact on bone health, with a higher prevalence of osteopenia and osteoporosis observed in individuals with these habits. Comorbidities such as diabetes and hypertension were also found to be associated with a higher prevalence of osteoporosis. These findings emphasize the importance of early detection and prevention of addictive habits and comorbidities to reduce the risk of osteopenia and osteoporosis. Furthermore, the study highlights the need for further research to fully understand the complex relationships between sociodemographic factors, addictive habits, comorbidities, and bone health.
Monocyte eosinophil ratio and red blood cell distribution width in the diagnosis of asthma
Authors: KOÇ İbrahim , DOĞAN Serdar
Published: May 2023

Objective: Bronchial asthma is often associated with chronic airway inflammation and airway hyperresponsiveness in which many cells and mediators are involved. Pulmonary function tests (PFTs) are used in the diagnosis of the disease. Yet PFTs are not available in every healthcare institution or some of the patients cannot cooperate with the procedure. The aim of this study was to determine whether mean platelet volume (MPV), platelet distribution width (PDW), monocyte lymphocyte ratio (MLR), monocyte eosinophil ratio (MER), and platelet lymphocyte ratio (PLR) can be used in the diagnosis of bronchial asthma.

Method: Two hundred and twelve patients who were diagnosed with bronchial asthma according to the Global Initiative for Asthma (GINA) criteria and 187 patients who were deemed not to have asthma were included in the study. Two patient groups were compared by examining the hemogram parameters at the time of diagnosis or exclusion of asthma.

Results: The levels of MPV, neutrophil-lymphocyte ratio (NLR), and PLR were significantly lower in the Asthma group (p
Genetic and clinical characteristics of Turkish children with Maturity Onset Diabetes of the Young Type 2 (MODY2): A single center experience
Authors: NALBANTOĞLU Özlem , GÜRSOY Semra , KIRKGÖZ Tarık , HAZAN Filiz , ÖZKAN Behzat
Published: May 2023

Objective: The aim of the study was to investigate the clinical and molecular genetic characteristics of children with maturity-onset diabetes of the youth-glucokinase (MODY-GCK, MODY type 2).

Method: Medical files of 21 patients with suspected MODY-GCK were reviewed retrospectively. The file records of the clinical findings, laboratory results and the suspected clinical diagnoses of MODY were based on (1) asymptomatic fasting hyperglycemia (glucose ≥100mg/dl, HbA1c < 7.5% (at least twice measurement) 2) parents with a history of diabetes without complications or mild fasting hyperglycemia (100-144mg/dL).

Results: The mean age at diagnosis was 11.5±4.3 years (min-max, 1.9-17.2). The mean (SD) fasting blood glucose level was 119.1 (9.8) mg/dL. The mean (SD) fasting C-peptide level was 1.3 (0.7) ng/mL, the mean (SD) insulin level was 5.9 (2.3) IU/ml, and the mean (SD) HbA1c level at diagnosis was 6.2 (0.5) %. Among 12 variants detected in the GCK gene, 8 were missense mutation, 2 were non-sense mutation, 1 of them was splice site and 1 of them was frameshift mutation. Eight of them (p. Val227Met, p. Ser282Ala, p.Val183Met, p.Met239Thr, p.Arg304Gln, p.Thr229Met, p.Gly163Asp, p.Cys130Ter) have been previously reported in the literature and 4 variants (c.582+4delA, p.Glu436Ter, p.His106ThrfsTer11, p.Asp133Gly) were novel.

Conclusion: We found similar phenotype characteristic of children with GCK-MODY among the children with different variants. The most common mutation type was missense and followed by nonsense, splice site and frameshift mutations. Detection of the molecular defect in patients with MODY is vital for the implementation of appropriate treatment approaches.
The effect of Covid-19 anxiety on prenatal distress and prenatal attachment in pregnant women
Authors: KARADEMİR Dilay , AĞADAYI Ezgi , KARAHAN Seher
Published: May 2023

Objective: In this study, we aimed to investigate the effect of Coronavirus Disease 2019 (COVID-19) anxiety on pregnant women, whether it causes prenatal distress and may be changes on mother-infant attachment.

Method: The research population consists of pregnant women in all trimesters. Exclusion criteria from the study; anomaly risk in the fetus, abnormal examination findings, systemic chronic disease and drug use, presence of diagnosed psychiatric disease, consanguineous marriage between the pregnant woman and her spouse. 323 pregnant women who did not meet these exclusion criteria and agreed to participate in the study were included in this study. In the study data form: Income status, education level, age, gravidity, parity, presence and number of miscarriages, gestational week, smoking status, history of COVID-19 infection, if yes, in which week of pregnancy she had, history of COVID-19 infection in her close family, planned pregnancy, in vitro fertilization-intrauterine insemination (IVF-IUI) or a spontaneous pregnancy status were questionnaired. The patients included in the study were administered the Coronavirus Anxiety Scale (CAS), Revised Prenatal Distress Questionnaire (NuPDQ), Prenatal Attachment Scale (PAS).

Results: COVID-19 anxiety increases more if close relatives have coronavirus rather than participants themselves. We detected that high coronavirus anxiety also caused an increase in the sub-dimensions of prenatal distress. We also found that high COVID-19 anxiety negatively affects prenatal attachment.

Conclusion: Pregnant women should be given information and education about the possible effects of coronavirus on their pregnancy during their routine follow-up during the pandemic period. Otherwise, both psychologically and physically unhealthy generations await the whole world.
Evaluation of notifiable infectious diseases between 2018 and 2021 in Van province: A descriptive study
Authors: TEKİN Ömer Faruk , ÇAKICI TOSUN Müberra
Published: May 2023

Objective: In this study, it was aimed to examine the infectious diseases reported in Van province between 2018 and 2021 in terms of various characteristics.

Method: It is a descriptive study that was conducted between January 1 and January 31, 2022. Necessary permissions and an ethics committee were obtained for the study. Infectious diseases reported in Van province between January 1, 2018 and September 30, 2021 were examined using the Infectious Diseases Surveillance and Early Warning System (IZCI) of the Ministry of Health. It was examined in terms of various variables. The study’s data were analysed with the Jamovi 2.2 statistical program. Descriptive data were given as numbers and percentages. The Pearson Chi-square test was used for comparisons between categorical variables.

Results: There were 16778 notifications between 01.01.2018-30.09.2021. Of the people with the reported disease, 59.5% were men and 40.5% were women. The mean age was 23.3±19.0 (min: 0-max: 99). The 3 most frequently reported diseases/conditions were 32.51% (n=5455) Brucellosis, 31.07% (n=5212) Rabies-risk contact, and 12.70% (n=2131) Rotavirus. There were 5555 (33.1%) disease reports in 2018, 4769 (28.4%) in 2019, 3411 (20.3%) in 2020, and 3043 (18.1%) in the first nine months of 2021. The incidence of Brucellosis, Rabies Risky Contact, Echinococcosis, and Anthrax diseases was found to be higher in rural districts than in urban districts (for each p
The application and prospects of 3D printable microgel in biomedical science and engineering
Authors: Du Chengcheng , Huang Wei , Lei Yiting
Published: May 2023

Three-dimensional (3D) bioprinting technology is one of the most advanced techniques currently applied in tissue engineering and regenerative medicine and has developed rapidly in the past few years. Despite many breakthroughs, there are still several challenges of 3D bioprinting technology awaiting to be addressed, and one of them is the urgency of optimizing bioinks (natural or synthetic hydrogel), which are critical elements in 3D bioprinting, for specific properties. Different from traditional hydrogels, microgels, which are a new type of bioink, are micron-sized gels with excellent mechanical and biological properties, which make them great candidates for applications in 3D bioprinting. Different from the dense and limited pore size of traditional hydrogels, the pore structure of microgel is adjustable, enabling better cell loading before 3D bioprinting, and the printed pores are conducive to the exchange of metabolic substances and cell migration. The “bottom-up” modular microgel has stronger customizable characteristics, and it can freely adjust its mechanical properties, such as hardness, toughness, and rheological properties. In this review, we review the application of microgels in the field of biomedicine and discuss the future development of microgels in 3D bioprinting.
Hydrogels for 3D bioprinting in tissue engineering and regenerative medicine: Current progress and challenges
Authors: Fang Wenzhuo , Yang Ming , Wang Liyang , Li Wenyao , Liu Meng , Jin Yangwang , Wang Yuhui , Yang Ranxing , Wang Ying , Zhang Kaile , Fu Qiang
Published: May 2023

Three-dimensional (3D) bioprinting is a promising and innovative biomanufacturing technology, which can achieve precise position controlling of cells and extracellular matrix components, and further create complex and functional multi-cellular tissues or organs in a 3D environment. Bioink in the form of the cell-loaded hydrogel is most commonly used in bioprinting, and it is vital to the process of bioprinting. The bionic scaffold should possess suitable mechanical strength, biocompatibility, cell proliferation, survival, and other biological characteristics. The disadvantages of natural polymer hydrogel materials include poor mechanical properties as well as low printing performance and shape fidelity. Over the past years, a series of synthetic, modified, and nanocomposite hydrogels have been developed, which can interact through physical interactions, chemical covalent bond crosslinking, and bioconjugation reactions to change the characteristics to satisfy the requirements. In this review, a comprehensive summary is provided on recent research regarding the unique properties of hydrogel bioinks for bioprinting, with optimized methods and technologies highlighted, which have both high-value research significance and potential clinical applications. A critical analysis of the strengths and weaknesses of each hydrogel-based biomaterial ink is presented at the beginning or end of each section, alongside the latest improvement strategies employed by current researchers to address their respective shortcomings. Furthermore, we propose potential repair sites for each hydrogel-based ink based on their distinctive repair features, while reflecting on current research limitations. Finally, we synthesize and analyze expert opinions on the future of these hydrogel-based bioinks in the broader context of tissue engineering and regenerative medicine, offering valuable insights for future investigations.
Advances in 3D printing techniques for cartilage regeneration of temporomandibular joint disc and mandibular condyle
Authors: Hu Shoushan , Yi Yating , Ye Chengxinyue , Liu Jin , Wang Jun
Published: May 2023

Temporomandibular joint (TMJ) osteoarthritis causes fibrocartilage damage to the TMJ disc and mandibular condyle, resulting in local pain and functional impairment that further reduces patients’ quality of life. Tissue engineering offers a potential treatment for fibrocartilage regeneration of the TMJ disc and mandibular condyle. However, the heterogeneous structure of TMJ fibrocartilage tissue poses significant challenges for the fabrication of biomimetic scaffolds. Over the past two decades, some researchers have attempted to adopt three-dimensional (3D) printing techniques to fabricate biomimetic scaffolds for TMJ fibrocartilage regeneration, but publications on such attempts are limited and rarely report satisfactory results, indicating an urgent need for further development. This review outlines several popular 3D printing techniques and the significant elements of tissue-engineered scaffolds: seed cells, scaffold materials, and bioactive factors. Current research progress on 3D-printed scaffolds for fibrocartilage regeneration of the TMJ disc and mandibular condyle is reviewed. The current challenges in TMJ tissue engineering are mentioned along with some emerging tissue-engineering strategies, such as machine learning, stimuli-responsive delivery systems, and extracellular vesicles, which are considered as potential approaches to improve the performance of 3D-printed scaffolds for TMJ fibrocartilage regeneration. This review is expected to inspire the further development of 3D printing techniques for TMJ fibrocartilage regeneration.
Longstanding giant frontoethmoidal mucocele with orbital and intracranial extension: challenges of surgical approach in a developing nation
Authors: Aliyu Daniel , Adeyeye Foluso M. , Mohammed Adamu D. , Iseh Kufre R. , Lasseini Ali
Published: May 2023

Mucoceles of the paranasal sinuses are expansile, benign mucus filled epithelial lined cystic-like lesion resulting from chronic obstruction to sinus ostia. They erode bony walls by pressure and bony resorption with the frontal and ethmoid sinuses predominately affected. The expansile lesion can involve surrounding structures like the orbit, intracranium or nasopharynx. Diagnosis is based on history, examination and radiological assessment with Computerized tomography scan   being the imaging of choice. Surgery is the mainstay of treatment and would require collaboration with the neurosurgeons or the ophthalmologist when it extends to the brain or orbit respectively. It can be done via an external approach, endoscopic approach or a combination of both.  If left without intervention, it may cause morbidity and potential mortality due to its proximity to the brain and orbit.  We report a rare case in our setting of a 65-year-old male farmer with a painless huge left sided cystic fronto-orbital swelling of 8 years that mimicked a benign orbital tumor. The mass was non-tender and not pulsatile measuring about 20×18 cm with normal visual acuity. Computed tomography (CT) scans of the brain and paranasal sinus revealed a large well-defined non-contrast enhancing homogenous lesion involving the left fronto-ethmoidal sinuses with orbital and intracranial extension as well as inferolateral displacement of the left eye globe. He was reviewed by the ENT surgeons, neurosurgeons and ophthalmologists and subsequently had frontoethmoidectomy via an external approach.
Unusual sinonasal mass clinically mimicking malignancy
Authors: Hajare Shalvi N. , Purohit Gautam S. , Magdum Vishal K. , Nilakhe Sachin S.
Published: May 2023

Central giant cell lesion is a non-neoplastic proliferation, usually asymptomatic, of unknown aetiology. This case report describes the diagnosis and treatment for a maxillary central giant cell lesion. We report a case of a 30-year-old lady with a central giant cell granuloma (CGCG) who presented with a history of right-side nasal blockage, swelling and pain in the right side of the cheek, proptosis of the right eye, occasional blurred vision for one month. Images and histopathology examinations confirmed the diagnosis. The patient underwent tumour resection through the endoscopic endonasal approach successfully without any postoperative complication, there was no recurrence within a year of follow up and its histopathological analysis was consistent with a CGCG. Histopathological examination of the mass confirmed as CGCG. Complete excision of right sinonasal mass achieved by right endoscopic sinus surgery through modified Denker’s approach. As CGCG is a non-neoplastic lesion of unknown aetiology, histopathology is necessary for definitive diagnosis. Treatment can vary depending on the extension of the tumour.
Efficacy of pre-operative submucosal injection of dexamethasone and triamcinolone acetonide on post-operative pain following endodontic treatment of teeth with irreversible pulpitis: A randomised clinical trial
Authors: Anand Pari , T Jaykumar , A Srirekha , C Champa , Shetty Ashwija , S Archana
Published: May 2023

Post-endodontic pain is a challenge to clinicians. In this context the evidence for use of preoperative medication is not consistent.

The study's objective is to assess the effects of dexamethasone and triamcinolone acetonide administered submucosally in single doses on postoperative pain following single-visit root canal treatment for teeth with symptomatic irreversible pulpitis.

Thirty patients were randomly allocated in three groups. Group I received saline (control), Group II received dexamethasone (8mg) and Group III received triamcinolone acetonide (40mg) before endodontic treatment was initiated. Root canal treatment was performed in a single appointment for all the participants. Post-operative pain was assessed using Heft-Parker visual analogue scale (HP VAS).

Comparison of HP VAS scores was done using Kruskal Wallis Test and Mann Whitney Test.

There was no significant difference in the mean HP VAS scores between 3 groups at pre-op period (P=0.74). At 6,12 and 24h post-operative period the mean HP VAS scores in Group 2 and 3 was significantly lesser as compared to Group 1.

Corticosteroid preoperative dosages led to a reduction in post endodontic pain after single visit root canal treatment of teeth with symptomatic irreversible pulpitis.
Occular manifestation of a case of lamellar ichthyosis
Authors: Nayak Dhruvil V , Trivedi Harish , Rathod Prapti
Published: May 2023

A baby full term born of LSCS to a otherwise healthy mother was referred for ophthalmology department. On ophthalmological torch light examination, the patient had equal upper and lower lid bilateral ectropion. There was missing eye lashes noted. The anterior segment evaluation was found to be within normal limit without evidence of corneal opacities. Lamellar ichthyosis otherwise termed as Collodion baby is a infrequent disease; and there is no well-known management protocol. The Patient was managed conservatively by the use of Hydroxy propyl methyl cellulose (2% w/v) eye ointment and lubricant (Carboxy methyl cellulose 0.5%) eye drops. Thus, surgical intervention was avoided and patient was managed medically on ointments and drops
Algorithm for stable solution of inverse problem of magnetotelluric sounding
Authors: Plotkin V. V.
Published: May 2023

When solving inverse problems of magnetotelluric sounding (MTS), equivalent solutions appear, noticeably different from each other. But the solution of a direct problem under a given medium model and boundary conditions is the only one, the response of the medium to the source of the electromagnetic field is unique. An algorithm is considered that leads to an accurate solution of the test problem when striving for zero inconsistencies in input and model data. Several starting medium models and two optimization methods are used: a nonlinear least squares method with calculations of the sensitivity matrix and a method based on metaheuristic algorithms used when target functions have several local minima. Using numerical calculations, a stable solution of the inverse MTS problem for the 3D-medium model was obtained.
Increasing the Accuracy of Orientation Determination Based on Auto-compensation of Errors
Authors: Ryzhkov Lev , Chernyak Mykola
Published: May 2023

An increasing the accuracy of orientation determination of strapdown system based on the spatial rotation of gyroscopes relative to an object is considered. The subject of analysis is a mathematical model of the measurement errors of orientation angles, taking into account the constant biases of gyroscopes. The proposed error model makes it quite easy to evaluate the efficiency of auto-compensation. It is shown that the problem may be reduced to integrating the direction cosine matrix that determine the position of the sensitive elements in the reference coordinate system. The results of theoretical analysis and simulation confirm the high efficiency of this method for increasing the accuracy of measuring kinematic parameters.
Значимость актуализации Единой Информационной Системы в сфере закупок
Authors: Басикова Ч.Ф. , Шобухова А.Н.
Published: May 2023

На сегодняшний день развитие государственных информационных систем является актуальной темой, способствующей развитию равного доступа граждан к сведениям, уменьшению коррупции и улучшения систем. В данной статье рассматривается проблема недоработки системы, несмотря на длительность ее развития. В статье затрагивается тема регулирования ЕИС в нормативно-правовом аспекте, в принципе эффективного делегирования полномочий по ее ведению и развитию.
Влияние экономических санкций на развитие контейнерных перевозок
Authors: Бондарь С.Г. , Гарбар А.В. , Чеменцова А.А.
Published: May 2023

В статье анализируется ситуация на рынке контейнерных перевозок. Приведены проблемы, существующие на рынке перевозок. Оценена возможность дальнейшего развития грузовых перевозок между Россией и Китаем.
Склонность российских потребителей к использованию электрической коммерческой автотехники
Authors: Тихонов М.С. , Макарова О.Ю.
Published: May 2023

Цель данной статьи выявить потенциал использования электрической коммерческой автотехники на российском рынке. Были рассмотрены основные тренды развития автоиндустрии в целом и их влияние на исследуемый сегмент, проведен анализ предложения и спроса на коммерческие электромобили в России. Обобщение проблем, с которыми сталкиваются пользователи коммерческого электротранспорта, приводит к неоднозначным выводам. Возможно данный вид техники представляет некий переходный вариант от транспортных средств с ДВС к более экологичным и эффективным вариантам.
Адаптация предприятий к изменениям внешней среды при оценке операционной эффективности
Authors: Честнов А.В.
Published: May 2023

В статье рассмотрены вопросы факторов внешней среды функционирования предприятия и влияния их на деятельность хозяйственных объектов.
Генетические основы морозоустойчивости озимой пшеницы. Последние исследования.
Authors: Димитриенко О.В. , Колесниченко Т.В.
Published: May 2023

В данной статье рассматриваются основные исследования в области морозоустойчивости озимой пшеницы, затрагиваются ключевые аспекты влияющие на гены обуславливающие этот фактор.
Мелиссопалинологический анализ при оценке качества мѐда
Authors: Елькина Н.А.
Published: May 2023

Изучена возможность использования показателей морфологического строения пыльцевых зерен для оценки качества продуктов пчеловодства. Мелиссопалинологический анализ позволяет судить о географическом и ботаническом происхождении мѐда, возможной фальсификации продукта и об экологическом состоянии территории, на которой находится пасека. Исследован образец мѐда с частной пасеки, расположенной на территории с низкой антропогенной нагрузкой. Получены данные о качественном и количественном составе пыльцевой компоненты мѐда. Обнаружено менее 2 % тератоморфных пыльцевых зерен, что свидетельствует о высоком качестве пыльцы растений-медоносов и отсутствии загрязнения территории и самого мѐда гаметопатогенными соединениями.
Современные методы преподавания физической культуры в вузах
Authors: Азнабаев О.Ф. , Алгушаев Ф.Н.
Published: May 2023

В данной статье рассматривается важность усовершенствования новых методов преподавания физической культуры в российских университетах, более того, раскрываются причины, по которым совершенствуются подходы к обучению. Научная работа посвящена поиску современных методов преподавания физической культуры и поиску мотивации обучающихся вузов к изучению данной дисциплины. Указываются образцы и примеры здоровья, личностно-ориентированных коммуникативных технологий, а также технологий, сберегающих здоровье.
Применение теории массового обслуживания при автоматизации предприятий доставки
Authors: Золотарев С.А. , Фешина Е.В.
Published: May 2023

Статья посвящена раскрытию возможностей теории массового обслуживания при автоматизации предприятий доставки.
Об оценке среднего ускорения параллельной композиции конвейерных систем с ограничениями
Authors: Трещев И.А.
Published: May 2023

В работе рассмотрены конвейерные системы, для которых введена операция параллельной композиции. Для конвейерных систем с ограничениями приводится среднее ускорение вычислений. Доказана теорема для оценки максимально достижимого ускорения параллельной композиции группы конвейерных систем.
Автоматизированные системы патентного поиска
Authors: Смолова Е.А.
Published: May 2023

В работе выполнен анализ известных автоматизированных систем поиска патентов для проверки релевантности подаваемых в патентные бюро заявок для подтверждения их новизны. Были рассмотрены наиболее известные и применяемые для поиска патентов автоматизированные системы: Espacenet, Patentscope, USPTO, Google Patent Search, ФИПС, Роспатент, Free Patents Online и SIPO; проведен их сравнительный анализ, который показал, что для поиска релевантных тексов в них слабо автоматизирован процесс построения запросов.
Полиамиды в качестве перспективного изоляционного материала
Authors: Афанасьева В.В. , Мифтахов А.Р.
Published: May 2023

В данной статье мы рассматриваем новый вид изоляции – полиимиды. Обращено внимание на их электрофизические характеристики, модель поведения при изменении параметров температуры и внутреннего строения
Триинги в полимерной изоляции кабелей
Authors: Афанасьева В.В. , Мифтахов А.Р.
Published: May 2023

Наличие неоднородностей и пустот приводит к разрушению изоляции. В данной статье мы рассматриваем следствие этих явлений – триинги, их влияние и процесс возникновения.
Индивидуальные средства обогрева для использования в зонах с пониженной температурой
Authors: Шелехов И.Ю. , Салишев И.Р. , Лысенко Д.О.
Published: May 2023

В статье приводится анализ технических средств, предназначенных для защиты частей тела от переохлаждения, представлены электронагревательные приборы, представлены их технические характеристики. Показано, что при использовании индивидуальных средств защиты частей тела от переохлаждения повышается работоспособность, снижается риск обморожения при длительном нахождении в зоне отрицательных температур. Так же в статье показано, что при использовании новых нагревательных элементов с распределенным греющим слоем снижается энергопотребление и увеличивается срок работы данных приборов.
Обзор работы автотранспортных средств по вывозу ТКО
Authors: Давыдова Е.А. , Ефимов Р.А.
Published: May 2023

В статье рассмотрены вопросы влияния типа транспортных средств по вывозу ТКО из населенных пунктов для построения модели рациональной маршрутной сети и определения потребного парка автомобилей. Необходимость создания подобной модели обусловлена экологическими факторами с учетом увеличения соотношения объемов образования ТКО и вместимости действующих мест утилизации или переработки.
Структурные особенности перлитного превращения в магнитном поле
Authors: Долгачев Ю.В. , Пустовойт В.Н. , Лукушина М.С.
Published: May 2023

Рассмотрены особенности структурного превращения в магнитном поле. Выполнено сопоставление структуры и свойств стали после термической обработки на структуру перлита в магнитном поле и без поля. Основываясь на полученных экспериментальных данных, можно прийти к выводу, что в магнитном поле оказывается возможным мультипликативное зарождение центров феррита, что связано с преимуществами ферромагнитного состояния феррита и термодинамической невыгодностью образования неферромагнитных фаз