bluuebunny/crossref_metadata_2025_split huggingface dataset:
Support of Cancer Patients at the Stage of Early Rehabilitation: Possibilities of Postural Correction and Art Therapy Techniques
Authors: Nezhivova A. V. , Kapitsa A. A. 
Published: March 2024

Introduction. Early rehabilitation of cancer patients after surgery plays an important role in their recovery and return to normal functioning. One of the tasks of this stage of treatment is to restore physical activity of the body, in particular, through postural correction. The medical aspects of this process are well described in the literature, however, the psychological aspects of the postural correction process are not sufficiently covered. Even fewer studies are devoted to restoring the psychological state of cancer patients. Purpose. Analysis of the possibilities of postural correction of cancer patients and the possibility of using art therapy techniques to normalize the psychological state during early rehabilitation.Theoretical justification. One of the key elements of postural correction is the restoration of the ability to maintain balance. For this purpose, special devices are used – stabilometric platforms. Another important element is the restoration of voluntary movements. For a more effective recovery, it is worth teaching patients the psychological adjustment to exercise movements. When the patient plans a movement, he forms a mental construct “task to be completed”, which promotes more precise movements. Restoration of their stable psychological state of cancer patients is possible, in particular, through art therapy techniques. One of the techniques, coloring mandalas, involves both hemispheres of the patients’ brains, triggering cognitive processes through the activation of fine motor skills. This provides a natural therapeutic process: the brain works initially on simple tasks and gradually moves on to more complex ones. The details of the mandala drawing are thought out in such a way that in the process of working on it, the patient focuses on his inner state – thoughts and feelings.Discussion. The importance of an integrated approach to the rehabilitation of cancer patients is increasingly emphasized in scientific papers. During the early rehabilitation period, the patient is in the most vulnerable state, both physically and psychologically. The use of psychological techniques can ensure that the patient can restore a more holistic image of himself both physically and internally.
Development of Speech Communication of Senior Preschool Children: Application of Correctional and Developmental Pedagogical Technologies in Moderate and Severe Mental Retardation
Authors: Vorobyeva E. V. , Efimeva E. V. 
Published: March 2024

Introduction. The article discusses correctional-developmental pedagogical technologies for the development of speech communication through the prism of speech pathology correction in preschool children with severe and moderate mental retardation. The following methods are described: fairy tale therapy, theatrical activities, mnemotechniques, logorhythmics, and computer technologies.Purpose. The study examines the components of speech communication in preschool-aged children with moderate and severe mental retardation using pedagogical technologies such as logorhythmics, theatrical activities, and computer technologies.Materials and Methods. A study was conducted involving 10 preschool-aged children with moderate and severe mental retardation attending a combined-type kindergarten. The study aimed to assess the development of the motivational, semantic, linguistic, and sensorimotor components of speech communication. Pedagogical technologies such as logorhythmics, theatrical activities, and computer technologies (developing games) were used to evaluate the manifestation of speech communication components in preschool-aged children with moderate and severe mental retardation.Results. The study involved 10 children (6 boys and 4 girls) aged 5–6 years with severe or moderate mental retardation. A confirmatory experiment was conducted to assess the semantic, linguistic, sensorimotor, and motivational components of speech communication in this group of manifestation. The study allowed us to determine that the most preserved components of speech communication in the participants of the experiment are sensorimotor and motivational, while the semantic and linguistic components of speech communication are poorly developed.Discussion. The data obtained in our study is in line with the findings of other researchers who have who have used the information and communication technologies in correctional speech therapy. The authors also emphasize the role of dialogic communication between a child and a teacher in speech development, which we have implemented at all stages of the confirmatory experiment. The results obtained are applied in correctional and developmental work.
Evaluation of remote assistance for point-of-care ultrasonography in a large animal hospital: a controlled randomized trial
Authors: Leduc Laurence , Underwood Claire , Stefanovski Darko , Hurcombe Samuel , Navas de Solis Cristobal 
Published: March 2024

Abstract

OBJECTIVE
To assess whether remote assistance is beneficial to the accuracy of point-of-care ultrasound (POCUS) examinations during equine emergency evaluations.

ANIMALS
Adult horses presenting to a tertiary care large animal emergency service for respiratory or gastrointestinal clinical signs.

PROCEDURES
Prospective, randomized, controlled, clinical study. Cases were assigned to receive POCUS with remote assistance (“POCUS-R” group) or POCUS with no assistance (“POCUS” group). Accuracy of diagnosis, duration of sonograms and survival to discharge were the objective outcomes compared between groups. Perceptions about the use of teleultrasound were gathered using a survey.

RESULTS
29 cases were enrolled in the study over an 18-month period. Based on Cox regression estimates, sonogram duration was likely to be longer in the POCUS-R group (n = 13) relative to the POCUS group (16) hazard ratio 0.43 (95% CI, 0.9 to 0.2; P = .03). Whether the final diagnosis was included in the differential diagnosis list, number of diagnoses in the differential list and survival were not different between groups. Educational benefits were the most frequently mentioned benefit by clinician users while logistical and technical problems related to the use of the equipment and inconvenience of enrollment in the study was the most common negative aspect.

CLINICAL RELEVANCE
Teleultrasound was generally not well adopted by users likely due to inconvenience and time constraints. Further work is indicated to assess differences in clinical outcomes in a setting that would allow a larger sample size to increase statistical power.
Intranasal and intravenous apomorphine outperform ropinirole ocular drops for induction of emesis in dogs within ten minutes: a randomized, controlled clinical trial
Authors: Manley Sabrina R. , Berg Alexia N. , Rozanski Elizabeth A. , Sweigart Benjamin A. , Lynch Alex M. 
Published: March 2024

Abstract

OBJECTIVE
The primary goal was to compare the efficacy of administration of apomorphine (APO) administered by intranasal (IN), transconjunctival (TC), SC and IV routes with ropinirole eye drops for induction of emesis in dogs with a secondary goal to evaluate the time of emesis as well as difficulty in administration.

ANIMALS
125 client-owned dogs.

METHODS
Dogs were randomly enrolled between October 1, 2021, and March 30, 2022, into groups of 25: IV APO, IN APO, TC APO, SC APO, and ropinirole eye drops. The IV, SC, and TC groups were dosed at 0.03 mg/kg, the IN group was dosed at 0.06 mg/kg, and the ropinirole group was dosed according to manufacturer guidelines. Data collected included success rate of emesis within 600 seconds, time to emesis, time to administer, and difficulty score. Results were compared to IV with P values and CIs being adjusted for multiple comparisons.

RESULTS
Emesis was successful within 600 seconds using IV APO in 22 of 25 dogs. By comparison, IN APO induced emesis in 18 of 25 dogs (P = .63). Ropinirole (14/25), SC APO (6/25), and TC APO (4/25) were significantly less successful (P = .047, P = < .001, and P < 0.001, respectively). When emesis was successful, it occurred most rapidly with TC APO, followed by IN APO and then ropinirole. It was most difficult to administer IV APO and TC APO.

CLINICAL RELEVANCE
Similar to IV APO, IN APO was a rapid, easy, and effective method of inducing emesis in dogs and should be considered when IV administration is not possible. Ropinirole was easy to administer but successfully induced emesis less reliably within a 10-minute timeframe. APO administered TC using the commercially compounded injectable formulation was ineffective.
Extreme erythrocytosis in a cat reverts after short-term treatment with hydroxyurea and the cat remains healthy for years
Authors: Billström-Saxon Jessica , Giger Urs 
Published: March 2024

Abstract

OBJECTIVE
This case report describes a cat with severe erythrocytosis (Hct, 80%), which after initial treatment with hydroxyurea has gone into remission for over 3 years.

ANIMAL
A 1-year-old neutered male American Maine Coon crossbred cat.

CLINICAL PRESENTATION, PROGRESSION, AND PROCEDURES
A 1-year-old neutered male American Maine Coon crossbred domestic cat was presented with acute neurologic signs, systolic heart murmur, and extreme erythrocytosis (Hct, 80%; normal interval, 30% to 48%). There were no clinical signs of dehydration, and several diagnostic tests for absolute erythrocytosis did not identify an underlying cause. A presumptive diagnosis of primary erythrocytosis (polycythemia vera [P vera], a myeloproliferative disease) was made.

TREATMENT AND OUTCOME
Repeated phlebotomies were declined by the owner, and thus the cat was treated with oral hydroxyurea. The neurologic signs, heart murmur, and erythrocytosis resolved within 2 months (Hct, 41%). Treatment with hydroxyurea was continued for 2 years and then discontinued. The Hct remained in the normal range (between 37% and 44%) during a 3-year observation period.

CLINICAL RELEVANCE
This case illustrates the challenges of determining a precise cause of erythrocytosis. The extreme erythrocytosis reverted after treatment with hydroxyurea and did not recur even after drug withdrawal, suggesting an undefined singular or multifactorial cause of the erythrocytosis rather than a primary absolute erythrocytosis, such as P vera. The reversibility of this cat’s erythrocytosis suggested that in select cases the discontinuation of treatment is warranted.
Blockchain-Based Smart Home Network Security through ML
Authors: Sinha Anurag , Jha Pooja , Kumar Biresh , Mishra Aditya , Ujjwal Vaibhav , Singh Anurag 
Published: March 2024

Abstract
Due in large part to the Internet of Things’ (IoT) anticipated enormous scope and extensive implementation, achieving safe and private communications on the IoT is difficult. Recent initiatives have investigated the use of blockchain technology to enable decentralized protection and privacy. Such methods, however, are prohibitive for the bulk of IoT applications due to their high computational and time requirements. We specifically offer a resource-efficient, blockchain-based IoT security and privacy solution in this study. The approach is made achievable by utilizing Deep Extreme Learning Machine in combination with unique computational resource exploitation in a typical IoT context (such as smart houses) (DELM). In the proposed method, the privacy, integrity, and accessibility of the Blockchain based Architecture of Smart Homes are prudently considered while assessing the reliability of the system. The overheads caused this strategy are negligible with respect to the security and privacy benefits, we further underline by presenting simulated findings.
Distributed Fundamentals based Conducting the Web Crawling Approaches and Types (Focused, Incremental, Distributed, Parallel, Hidden Web, Form Focused and Breadth First) Crawlers
Authors: Mehyadin Aska Ezadeen , Abdulrahman Lozan M. , Ahmed Sarkar Hasan , Qashi Riyadh 
Published: March 2024

Abstract
Over the last several years, there has been a significant rise in the number of people getting online and using the internet. Individual hypertext links are available, and any one of them may be used to get access to the resource. There is a variety of hypertext links available. It has been feasible to construct new websites as a result of the growth of crawlers, which has been facilitated by the rise in the number of people who use the internet. Web crawlers are highly evolved search engines that make it simpler for customers to get the information they are searching for on the internet. Web crawlers are also known as web crawlers. In a similar vein, these web crawlers have the potential to be used for more research endeavours in the months and years to come. Furthermore, the information that has been gathered may be used to detect and uncover any connections that are absent, as well as to assess the possibility for expansion inside complicated networks. This can be done by discovering any connections that are missing. The analysis of web crawlers is the primary topic of this study. Topics covered include the architecture of web crawlers, the many types of web crawlers, and the challenges that search engines have while using web crawlers.
Exploration of Vehicle Target Detection and Classification Method Based on Sea Lion Optimization with Deep Convolutional Neural Network
Authors: Ahmed Zain Jaffer , Mustfai Mohammed Ali 
Published: March 2024

Abstract
Presently, urban environments over the globe are highly employed to obtain solutions for enhancing the quality of the livers and enhance the usage of city infrastructure and resources with minimal operational cost. Urban remote sensing acts as a significant part in the ability of mapping, monitoring, and controlling infrastructure. High-resolution remote sensing data renders worldwide images faster than traditional data collection strategies. Hence, small objects such as cars are easily detected. Vehicle recognition on aerial remote sensing images (RSIs) in the complicated background of urban zones has always gained a lot of interest in the remote sensing field. The automatic vehicles enumeration research domain had a significant contribution in several applications, including traffic management and monitoring. Target detection technology will be a crucial part of computer vision (CV) technology, and target detection techniques were enforced in several domains. Therefore, this study develops a new Vehicle Recognition and Classification using Sea Lion Optimization with Deep Learning (VRC-SLODL) model on RSI. In the presented VRC-SLODL technique, the major intention lies in recognising and classifying vehicles present in the images. The bilateral filtering (BF) technique can initially improve the RSI quality. The VRC-SLODL technique employs a modified residual network (ResNet) model to produce a collection of feature vectors. Eventually, the SLO approach with long short-term memory (LSTM) technique was exploited for vehicle classification, where the SLO algorithm acts as a hyperparameter optimizer. The experiments were performed on a benchmark dataset to examine the better performance of the VRC-SLODL method. The obtained values reported the improved classification performance of the VRC-SLODL technique over other models.
Improved Arithmetic Optimization with Deep Learning Driven Traffic Congestion Control for Intelligent Transportation Systems in Smart Cities
Authors: Almusawy Muntather Hassan 
Published: March 2024

AbstractIn the last few years, some progress had been made in smart cities, and reduction in traffic congestion was the topmost concern in the development of smart cities. Shorter delays in transmission between Roadside Units (RSUs) and vehicles, road safety, and smooth traffic flow are the major difficulties of Intelligent Transportation Systems (ITS). The rapid improvement in automobiles occurs which increased the number of road accidents and traffic congestion. Machine Learning (ML) was an advanced technique to find hidden insights into ITSs without being explicitly programmed by learning from datasets. This article introduces an Improved Arithmetic Optimization with Deep Learning Driven Traffic Congestion Control (IAOADL-TCC) for ITS in Smart Cities. The presented IAOADL-TCC model enables traffic data collection and route traffic on existing routes for avoiding traffic congestion in smart cities. To accomplish this, the IAOADL-TCC model employs hybrid convolution neural network attention long short-term memory (HCNN-ALSTM) method for traffic congestion control. In addition, IAOA based hyperparameter tuning strategy is derived to optimally modify the hyperparameter values of the HCNN-ALSTM model. The presented IAOADL-TCC model effectively enhances the flow of traffic and reduces congestion. The experimental result study of the IAOADL-TCC method can be tested by making use of road traffic dataset from Kaggle repository. The experimental outcome stated the better performance of the IAOADL-TCC model over other DL methods.
Modeling of Optimal Fully Connected Deep Neural Network based Sentiment Analysis on Social Networking Data
Authors: Alsalami Zaid 
Published: March 2024

Abstract
In recent times, the user reviews and opinions postedon social-media like Twitter, Facebook, and Google+, and so on have received considerable attention in the domain of sentiment analysis (SA), offering valued feedback to public as well as private organizations. The examination of reviews roles an essential role for enhancing the product and service qualities. Although numerous SA methods are available in the literature, it is still needed to boost the outcome of the SA for understanding the customer feedbacks and thereby enhances the product quality. The presented article proposesan optimum fully connected deep neural network (OFCDNN) based SA, called OFCDNN-SA technique on social networking data. The OFCDNN-SA technique encompasses distinct procedureslike feature extraction, classification, preprocessing, and parameter optimization. Additionally, Glove technique is applied for the transformation of input data into feature vectors. Moreover, salp swarm optimization (SSO) based hyperparameter optimization technique is derived for maximally selecting the hyperparameters utilized in the DL method. Finally, the FCDNN methodis employed for classification purposes. To investigate the supreme achievement of the OFCDNN-SA method, a wide-ranging simulation assessment is performed and the experimental outputs highlighted the betterment over current methods by means of diverse measures.
Optimal Deep Belief Network Enabled Vulnerability Detection on Smart Environment
Authors: Hussan Bzar Khidir , Rashid Zryan Najat , Zeebaree Subhi R. M. , Zebari Rizgar R. 
Published: March 2024

Abstract
Cyborgs invoke visions of super-humans intertwined with innovative technologies able to surpass the restrictions of the human body. Conventional vulnerability detection models sustain maximum false positive rates and depend upon manual participation. Machine learning (ML) and Artificial intelligence (AI) technologies are exploited in several real-time applications, like vulnerability, malware, and software function detection, for high-quality feature representation learning. In this aspect, this study introduces a hyperparameter-optimized deep belief network-enabled vulnerability and classification (HOSDBN-VC) technique on cyborgs. The presented HOSDBN-VC model aims to detect and classify the existence of vulnerabilities. The presented HOSDBN-VC model involves a Z-score normalization approach to transform the input data into a useful format. In addition, the Hypercube Optimization Search Algorithm-based feature selection (HOS-FS) method is employed for selecting feature subsets. Moreover, a flower pollination algorithm (FPA) with a deep belief network (DBN) paradigm is applied for vulnerability and classification. The metaheuristics-based FPA is exploited to choose the hyperparameters related to the DBN paradigm appropriately. A wide-ranging experiment has been conducted to investigate the results of the HOSDBN-VD model under two databases, FFmpeg and LibPNG. The experimental outcomes implied the betterment of the HOSDBN-VD algorithm over recent approaches.
Immunohistochemical Detection of CD3 and MAC387 Antibodies in the Mesenteric Lymph Nodes and the Small Intestine of 20 Dogs that Died of Canine Parvoviral Enteritis
Authors: Novakov Todor , Gjurovski Ivica , Bozinovski Spiro , Janevski Aleksandar , Adamov Nikola , Ristoski Trpe 
Published: March 2024

Abstract
There is little data on the use of the immunohistochemical method in the observation of the T lymphocytes and macrophages distribution within the mesenteric lymph nodes in canine parvovirus (CPV) enteritis. The virus initially replicates in the systemic lymphoid tissue and causes highest changes in the small intestine. This current study aimed to demonstrate the CD3 and MAC387 antibodies detection and distribution in mesenteric lymph nodes and small intestines in dogs which had positive clinical, pathological, and histological findings of CPV. Twenty dogs that were clinically confirmed on CPV, had been autopsied following onset of death. Tissue samples (lymph nodes and small intestines) from each dog was processed for histology and immunohistochemistry utilizing hematoxylin-eosin and peroxidase/DAB (3,3′-diaminobenzidine) staining methods, respectively. The virus distribution was greatest in the tissue areas of the small intestine and the lymph nodes where the virus had made the most severe tissue damage. The distribution of macrophage was highest in the necrotic areas of the small intestine and the mesenteric lymph nodes. The amount of CD3 positive lymphocytes was greatly reduced in the mesenteric lymph nodes and the lymphoid tissue of the small intestine.
Optimization of Component Assembly in Automotive Industry
Authors: Křepelka Jaromír , Schovánek Petr , Tuček Pavel , Hrabovský Miroslav , Jáně František 
Published: March 2024

Abstract
This article is devoted to the positioning of glued parts by robots in the process of manufacturing automotive headlights, with the possibility of generalization to the mutual positioning of any 3D object. The authors focused on the description of the mathematical method that leads to the optimization of the robot arm setting and ensures the closest contact of the glued parts. The contact surfaces of the two joined parts are, in the ideal case, identical in shape and their optimal alignment is considered to best align the position of the nominal points on the base part with the position of the control (measured) points on the part manipulated by the robot.