Search results for: deep brain stimulation (DBS)
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3539

Search results for: deep brain stimulation (DBS)

809 Physics-Informed Convolutional Neural Networks for Reservoir Simulation

Authors: Jiangxia Han, Liang Xue, Keda Chen

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Despite the significant progress over the last decades in reservoir simulation using numerical discretization, meshing is complex. Moreover, the high degree of freedom of the space-time flow field makes the solution process very time-consuming. Therefore, we present Physics-Informed Convolutional Neural Networks(PICNN) as a hybrid scientific theory and data method for reservoir modeling. Besides labeled data, the model is driven by the scientific theories of the underlying problem, such as governing equations, boundary conditions, and initial conditions. PICNN integrates governing equations and boundary conditions into the network architecture in the form of a customized convolution kernel. The loss function is composed of data matching, initial conditions, and other measurable prior knowledge. By customizing the convolution kernel and minimizing the loss function, the neural network parameters not only fit the data but also honor the governing equation. The PICNN provides a methodology to model and history-match flow and transport problems in porous media. Numerical results demonstrate that the proposed PICNN can provide an accurate physical solution from a limited dataset. We show how this method can be applied in the context of a forward simulation for continuous problems. Furthermore, several complex scenarios are tested, including the existence of data noise, different work schedules, and different good patterns.

Keywords: convolutional neural networks, deep learning, flow and transport in porous media, physics-informed neural networks, reservoir simulation

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808 Improved Approach to the Treatment of Resistant Breast Cancer

Authors: Lola T. Alimkhodjaeva, Lola T. Zakirova, Soniya S. Ziyavidenova

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Background: Breast cancer (BC) is still one of the urgent oncology problems. The essential obstacle to the full anti-tumor therapy implementation is drug resistance development. Taking into account the fact that chemotherapy is main antitumor treatment in BC patients, the important task is to improve treatment results. Certain success in overcoming this situation has been associated with the use of methods of extracorporeal blood treatment (ECBT), plasmapheresis. Materials and Methods: We examined 129 women with resistant BC stages 3-4, aged between 56 to 62 years who had previously received 2 courses of CAF chemotherapy. All patients additionally underwent 2 courses of CAF chemotherapy but against the background ECBT with ultrasonic exposure. We studied the following parameters: 1. The highlights of peripheral blood before and after therapy. 2. The state of cellular immunity and identification of activation markers CD23 +, CD25 +, CD38 +, CD95 + on lymphocytes was performed using monoclonal antibodies. Evaluation of humoral immunity was determined by the level of main classes of immunoglobulins IgG, IgA, IgM in serum. 3. The degree of tumor regression was assessed by WHO recommended 4 gradations. (complete - 100%, partial - more than 50% of initial size, process stabilization–regression is less than 50% of initial size and tumor advance progressing). 4. Medical pathomorphism in the tumor was determined by Lavnikova. 5. The study of immediate and remote results, up to 3 years and more. Results and Discussion: After performing extracorporeal blood treatment anemia occurred in 38.9%, leukopenia in 36.8%, thrombocytopenia in 34.6%, hypolymphemia in 26.8%. Studies of immunoglobulin fractions in blood serum were able to establish a certain relationship between the classes of immunoglobulin A, G, M and their functions. The results showed that after treatment the values of main immunoglobulins in patients’ serum approximated to normal. Analysis of expression of activation markers CD25 + cells bearing receptors for IL-2 (IL-2Rα chain) and CD95 + lymphocytes that were mediated physiological apoptosis showed the tendency to increase, which apparently was due to activation of cellular immunity cytokines allocated by ultrasonic treatment. To carry out ECBT on the background of ultrasonic treatment improved the parameters of the immune system, which were expressed in stimulation of cellular immunity and correcting imbalances in humoral immunity. The key indicator of conducted treatment efficiency is the immediate result measured by the degree of tumor regression. After ECBT performance the complete regression was 10.3%, partial response - 55.5%, process stabilization - 34.5%, tumor advance progressing no observed. Morphological investigations of tumor determined therapeutic pathomorphism grade 2 in 15%, in 25% - grade 3 and therapeutic pathomorphism grade 4 in 60% of patients. One of the main criteria for the effect of conducted treatment is to study the remission terms in the postoperative period (up to 3 years or more). The remission terms up to 3 years with ECBT was 34.5%, 5-year survival was 54%. Carried out research suggests that a comprehensive study of immunological and clinical course of breast cancer allows the differentiated approach to the choice of methods for effective treatment.

Keywords: breast cancer, immunoglobulins, extracorporeal blood treatment, chemotherapy

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807 Comprehensive Framework for Pandemic-Resilient Cities to Avert Future Migrant Crisis: A Case of Mumbai

Authors: Vasudha Thapa, Kiran Chappa

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There is a pressing need to prepare cities in the developing countries of the global south such as India against the chaos created by COVID 19 pandemic and future disaster risks. This pandemic posed the nation with an unprecedented challenge of dealing with a wave of stranded migrant workers. These workers comprise the most vulnerable section of the society in case of any pandemic or disaster risks. The COVID 19 pandemic exposed the vulnerability of migrant workers in the urban form and the need for capacity-building strategies against future pandemics. This paper highlights the challenges of these migrant workers in the case of Mumbai city in lockdown, post lockdown, and the current uncertain scenarios. The paper deals with a thorough investigation of the existing and the recent policies and strategies taken by the Urban Local Bodies (ULBs), state, and central government to assist these migrants in the city during this mayhem of uncertainties. The paper looks further deep into the challenges and opportunities presented in the current scenario through the assessment of existing data and response to policy measures taken by the government organizations. The ULBs are at the forefront in the response to any disaster risk, hence the paper assesses the capacity gaps of the Urban local bodies in mitigating the risks posed by any pandemic-like situation. The study further recommends capacity-building strategies at various levels of governance and uniform policy measures to assist the migrant population of the city.

Keywords: urban resilience, covid 19, migrant population, India, capacity building, governance

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806 Microwave Heating and Catalytic Activity of Iron/Carbon Materials for H₂ Production from the Decomposition of Plastic Wastes

Authors: Peng Zhang, Cai Liang

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The non-biodegradable plastic wastes have posed severe environmental and ecological contaminations. Numerous technologies, such as pyrolysis, incineration, and landfilling, have already been employed for the treatment of plastic waste. Compared with conventional methods, microwave has displayed unique advantages in the rapid production of hydrogen from plastic wastes. Understanding the interaction between microwave radiation and materials would promote the optimization of several parameters for the microwave reaction system. In this work, various carbon materials have been investigated to reveal microwave heating performance and the ensuing catalytic activity. Results showed that the diversity in the heating characteristic was mainly due to the dielectric properties and the individual microstructures. Furthermore, the gaps and steps among the surface of carbon materials would lead to the distortion of the electromagnetic field, which correspondingly induced plasma discharging. The intensity and location of local plasma were also studied. For high-yield H₂ production, iron nanoparticles were selected as the active sites, and a series of iron/carbon bifunctional catalysts were synthesized. Apart from the high catalytic activity, the iron particles in nano-size close to the microwave skin depth would transfer microwave irradiation to the heat, intensifying the decomposition of plastics. Under microwave radiation, iron is supported on activated carbon material with 10wt.% loading exhibited the best catalytic activity for H₂ production. Specifically, the plastics were rapidly heated up and subsequently converted into H₂ with a hydrogen efficiency of 85%. This work demonstrated a deep understanding of microwave reaction systems and provided the optimization for plastic treatment.

Keywords: plastic waste, recycling, hydrogen, microwave

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805 Evaluating the Satisfaction of Chinese Consumers toward Influencers at TikTok

Authors: Noriyuki Suyama

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The progress and spread of digitalization have led to the provision of a variety of new services. The recent progress in digitization can be attributed to rapid developments in science and technology. First, the research and diffusion of artificial intelligence (AI) has made dramatic progress. Around 2000, the third wave of AI research, which had been underway for about 50 years, arrived. Specifically, machine learning and deep learning were made possible in AI, and the ability of AI to acquire knowledge, define the knowledge, and update its own knowledge in a quantitative manner made the use of big data practical even for commercial PCs. On the other hand, with the spread of social media, information exchange has become more common in our daily lives, and the lending and borrowing of goods and services, in other words, the sharing economy, has become widespread. The scope of this trend is not limited to any industry, and its momentum is growing as the SDGs take root. In addition, the Social Network Service (SNS), a part of social media, has brought about the evolution of the retail business. In the past few years, social network services (SNS) involving users or companies have especially flourished. The People's Republic of China (hereinafter referred to as "China") is a country that is stimulating enormous consumption through its own unique SNS, which is different from the SNS used in developed countries around the world. This paper focuses on the effectiveness and challenges of influencer marketing by focusing on the influence of influencers on users' behavior and satisfaction with Chinese SNSs. Specifically, Conducted was the quantitative survey of Tik Tok users living in China, with the aim of gaining new insights from the analysis and discussions. As a result, we found several important findings and knowledge.

Keywords: customer satisfaction, social networking services, influencer marketing, Chinese consumers’ behavior

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804 Investigating the Editing's Effect of Advertising Photos on the Virtual Purchase Decision Based on the Quantitative Electroencephalogram (EEG) Parameters

Authors: Parya Tabei, Maryam Habibifar

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Decision-making is an important cognitive function that can be defined as the process of choosing an option among available options to achieve a specific goal. Consumer ‘need’ is the main reason for purchasing decisions. Human decision-making while buying products online is subject to various factors, one of which is the quality and effect of advertising photos. Advertising photo editing can have a significant impact on people's virtual purchase decisions. This technique helps improve the quality and overall appearance of photos by adjusting various aspects such as brightness, contrast, colors, cropping, resizing, and adding filters. This study, by examining the effect of editing advertising photos on the virtual purchase decision using EEG data, tries to investigate the effect of edited images on the decision-making of customers. A group of 30 participants were asked to react to 24 edited and unedited images while their EEG was recorded. Analysis of the EEG data revealed increased alpha wave activity in the occipital regions (O1, O2) for both edited and unedited images, which is related to visual processing and attention. Additionally, there was an increase in beta wave activity in the frontal regions (FP1, FP2, F4, F8) when participants viewed edited images, suggesting involvement in cognitive processes such as decision-making and evaluating advertising content. Gamma wave activity also increased in various regions, especially the frontal and parietal regions, which are associated with higher cognitive functions, such as attention, memory, and perception, when viewing the edited images. While the visual processing reflected by alpha waves remained consistent across different visual conditions, editing advertising photos appeared to boost neural activity in frontal and parietal regions associated with decision-making processes. These Findings suggest that photo editing could potentially influence consumer perceptions during virtual shopping experiences by modulating brain activity related to product assessment and purchase decisions.

Keywords: virtual purchase decision, advertising photo, EEG parameters, decision Making

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803 1-D Convolutional Neural Network Approach for Wheel Flat Detection for Freight Wagons

Authors: Dachuan Shi, M. Hecht, Y. Ye

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With the trend of digitalization in railway freight transport, a large number of freight wagons in Germany have been equipped with telematics devices, commonly placed on the wagon body. A telematics device contains a GPS module for tracking and a 3-axis accelerometer for shock detection. Besides these basic functions, it is desired to use the integrated accelerometer for condition monitoring without any additional sensors. Wheel flats as a common type of failure on wheel tread cause large impacts on wagons and infrastructure as well as impulsive noise. A large wheel flat may even cause safety issues such as derailments. In this sense, this paper proposes a machine learning approach for wheel flat detection by using car body accelerations. Due to suspension systems, impulsive signals caused by wheel flats are damped significantly and thus could be buried in signal noise and disturbances. Therefore, it is very challenging to detect wheel flats using car body accelerations. The proposed algorithm considers the envelope spectrum of car body accelerations to eliminate the effect of noise and disturbances. Subsequently, a 1-D convolutional neural network (CNN), which is well known as a deep learning method, is constructed to automatically extract features in the envelope-frequency domain and conduct classification. The constructed CNN is trained and tested on field test data, which are measured on the underframe of a tank wagon with a wheel flat of 20 mm length in the operational condition. The test results demonstrate the good performance of the proposed algorithm for real-time fault detection.

Keywords: fault detection, wheel flat, convolutional neural network, machine learning

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802 Temperature Susceptibility of Multigrade Bitumen Asphalt and an Approach to Account for Temperature Variation through Deep Pavements

Authors: Brody R. Clark, Chaminda Gallage, John Yeaman

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Multigrade bitumen asphalt is a quality asphalt product that is not utilised in many places globally. Multigrade bitumen is believed to be less sensitive to temperature, which gives it an advantage over conventional binders. Previous testing has shown that asphalt temperature changes greatly with depth, but currently the industry standard is to nominate a single temperature for design. For detailed design of asphalt roads, perhaps asphalt layers should be divided into nominal layer depths and different modulus and fatigue equations/values should be used to reflect the temperatures of each respective layer. A collaboration of previous laboratory testing conducted on multigrade bitumen asphalt beams under a range of temperatures and loading conditions was analysed. The samples tested included 0% or 15% recycled asphalt pavement (RAP) to determine what impact the recycled material has on the fatigue life and stiffness of the pavement. This paper investigated the temperature susceptibility of multigrade bitumen asphalt pavements compared to conventional binders by combining previous testing that included conducting a sweep of fatigue tests, developing complex modulus master curves for each mix and a study on how pavement temperature changes through pavement depth. This investigation found that the final design of the pavement is greatly affected by the nominated pavement temperature and respective material properties. This paper has outlined a potential revision to the current design approach for asphalt pavements and proposes that further investigation is needed into pavement temperature and its incorporation into design.

Keywords: asphalt, complex modulus, fatigue life, flexural stiffness, four point bending, multigrade bitumen, recycled asphalt pavement

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801 An Efficient Machine Learning Model to Detect Metastatic Cancer in Pathology Scans Using Principal Component Analysis Algorithm, Genetic Algorithm, and Classification Algorithms

Authors: Bliss Singhal

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Machine learning (ML) is a branch of Artificial Intelligence (AI) where computers analyze data and find patterns in the data. The study focuses on the detection of metastatic cancer using ML. Metastatic cancer is the stage where cancer has spread to other parts of the body and is the cause of approximately 90% of cancer-related deaths. Normally, pathologists spend hours each day to manually classifying whether tumors are benign or malignant. This tedious task contributes to mislabeling metastasis being over 60% of the time and emphasizes the importance of being aware of human error and other inefficiencies. ML is a good candidate to improve the correct identification of metastatic cancer, saving thousands of lives and can also improve the speed and efficiency of the process, thereby taking fewer resources and time. So far, the deep learning methodology of AI has been used in research to detect cancer. This study is a novel approach to determining the potential of using preprocessing algorithms combined with classification algorithms in detecting metastatic cancer. The study used two preprocessing algorithms: principal component analysis (PCA) and the genetic algorithm, to reduce the dimensionality of the dataset and then used three classification algorithms: logistic regression, decision tree classifier, and k-nearest neighbors to detect metastatic cancer in the pathology scans. The highest accuracy of 71.14% was produced by the ML pipeline comprising of PCA, the genetic algorithm, and the k-nearest neighbor algorithm, suggesting that preprocessing and classification algorithms have great potential for detecting metastatic cancer.

Keywords: breast cancer, principal component analysis, genetic algorithm, k-nearest neighbors, decision tree classifier, logistic regression

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800 Modifying the Electrical Properties of Liquid Crystal Cells by Including TiO₂ Nanoparticles on a Substrate

Authors: V. Marzal, J. C. Torres, B. Garcia-Camara, Manuel Cano-Garcia, Xabier Quintana, I. Perez Garcilopez, J. M. Sanchez-Pena

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At the present time, the use of nanostructures in complex media, like liquid crystals, is widely extended to manipulate their properties, either electrical or optical. In addition, these media can also be used to control the optical properties of the nanoparticles, for instance when they are resonant. In this work, the change on electrical properties of a liquid crystal cell by adding TiO₂ nanoparticles on one of the alignment layers has been analyzed. These nanoparticles, with a diameter of 100 nm and spherical shape, were deposited in one of the substrates (ITO + polyimide) by spin-coating in order to produce a homogeneous layer. These substrates were checked using an optical microscope (objective x100) to avoid potential agglomerates. The liquid crystal cell is then fabricated, using one of these substrates and another without nanoparticles, and filled with E7. The study of the electrical response was done through impedance measurements in a long range of frequencies (3 Hz- 6 MHz) and at ambient temperature. Different nanoparticle concentrations were considered, as well as pure E7 and an empty cell for comparison purposes. Results about the effective dielectric permittivity and conductivity are presented along with models of equivalent electric circuits and its physical interpretation. As a summary, it has been observed the clear influence of the presence of the nanoparticles, strongly modifying the electric response of the device. In particular, a variation of both the effective permittivity and the conductivity of the device have been observed. This result requires a deep analysis of the effect of these nanoparticles on the trapping of free ions in the device, allowing a controlled manipulation and frequency tuning of the electrical response of these devices.

Keywords: alignment layer, electrical behavior, liquid crystal, TiO₂ nanoparticles

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799 Mammographic Multi-View Cancer Identification Using Siamese Neural Networks

Authors: Alisher Ibragimov, Sofya Senotrusova, Aleksandra Beliaeva, Egor Ushakov, Yuri Markin

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Mammography plays a critical role in screening for breast cancer in women, and artificial intelligence has enabled the automatic detection of diseases in medical images. Many of the current techniques used for mammogram analysis focus on a single view (mediolateral or craniocaudal view), while in clinical practice, radiologists consider multiple views of mammograms from both breasts to make a correct decision. Consequently, computer-aided diagnosis (CAD) systems could benefit from incorporating information gathered from multiple views. In this study, the introduce a method based on a Siamese neural network (SNN) model that simultaneously analyzes mammographic images from tri-view: bilateral and ipsilateral. In this way, when a decision is made on a single image of one breast, attention is also paid to two other images – a view of the same breast in a different projection and an image of the other breast as well. Consequently, the algorithm closely mimics the radiologist's practice of paying attention to the entire examination of a patient rather than to a single image. Additionally, to the best of our knowledge, this research represents the first experiments conducted using the recently released Vietnamese dataset of digital mammography (VinDr-Mammo). On an independent test set of images from this dataset, the best model achieved an AUC of 0.87 per image. Therefore, this suggests that there is a valuable automated second opinion in the interpretation of mammograms and breast cancer diagnosis, which in the future may help to alleviate the burden on radiologists and serve as an additional layer of verification.

Keywords: breast cancer, computer-aided diagnosis, deep learning, multi-view mammogram, siamese neural network

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798 To Design an Architectural Model for On-Shore Oil Monitoring Using Wireless Sensor Network System

Authors: Saurabh Shukla, G. N. Pandey

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In recent times, oil exploration and monitoring in on-shore areas have gained much importance considering the fact that in India the oil import is 62 percent of the total imports. Thus, architectural model like wireless sensor network to monitor on-shore deep sea oil well is being developed to get better estimate of the oil prospects. The problem we are facing nowadays that we have very few restricted areas of oil left today. Countries like India don’t have much large areas and resources for oil and this problem with most of the countries that’s why it has become a major problem when we are talking about oil exploration in on-shore areas also the increase of oil prices has further ignited the problem. For this the use of wireless network system having relative simplicity, smallness in size and affordable cost of wireless sensor nodes permit heavy deployment in on-shore places for monitoring oil wells. Deployment of wireless sensor network in large areas will surely reduce the cost it will be very much cost effective. The objective of this system is to send real time information of oil monitoring to the regulatory and welfare authorities so that suitable action could be taken. This system architecture is composed of sensor network, processing/transmission unit and a server. This wireless sensor network system could remotely monitor the real time data of oil exploration and monitoring condition in the identified areas. For wireless sensor networks, the systems are wireless, have scarce power, are real-time, utilize sensors and actuators as interfaces, have dynamically changing sets of resources, aggregate behaviour is important and location is critical. In this system a communication is done between the server and remotely placed sensors. The server gives the real time oil exploration and monitoring conditions to the welfare authorities.

Keywords: sensor, wireless sensor network, oil, sensor, on-shore level

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797 Efficacy of Transcranial Magnetic Therapy on Balance in Patients with Vestibular Dysfunction

Authors: Ibrahim M. I. Hamoda, Ahmed R. Z. Baghdadi, Mohammed K. Mohamed, Nawal A. Abu-Shady

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Background: Most of patients with vestibular dysfunction suffering from balance disorders, Abnormality in balance increase effort and exertion which affect the independency, so this study might be a guide in managing balance problem and consequently improve walking with less exertion and maximum function. Purpose: to analyze and discuss the effect of transcranial magnetic therapy on balance in patients with vestibular dysfunction. Methods: forty subjects from both sexes were classified to divided randomly into two equal groups; Group I study group: this group received transcranial magnetic therapy, with a selected physical therapy program for improving balance and vestibular disorders (Balance training, Cawthorne-Cooksey Exercises) and group II (control group): this group received a selected physical therapy program as group I without transcranial magnetic therapy. This treatment procedure will be applied three times weekly for three months. The mean age was 54.53±3.44 and 55.33±2.32 years and BMI 35.7±3.03 and 35.73±1.03 kg/m2 for group I and II respectively. The Biodex Balance System, Berge balances scale (BBS) and brain MRI were used for assessment. Assessments were conducted before and after treatment. The treatment program for group I included balance training, Cawthorne-Cooksey Exercises and pulsed magnetic therapy (Parameters used in the program of 20 minutes, Intensity 2 gausses, Frequency 1 Hz). This selected program was done in approximately one hour every other day for three month. The treatment program group II Patients received the same program as group A without transcranial magnetic therapy. Results: The One-way ANOVA revealed that there were no significant differences in BBS scores, overall balance index, Anterior / posterior balance index, Medial / lateral balance index and dynamic limits of stability between both groups. Moreover, the BBS scores increased and overall balance index, Anterior / posterior balance index, Medial / lateral balance index and dynamic limits of stability decreased significantly after treatment in group I and II compared with before treatment. Interpretation/Conclusion: Adding pulsed magnetic therapy to balance training, Cawthorne-Cooksey Exercises has no effect on static and dynamic balance in patients with balance problems due to benign positional paroxysmal vertigo.

Keywords: balance, transcranial magnetic therapy, vestibular dysfunction, biomechanic

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796 The Relationship between Amplitude and Stability of Circadian Rhythm with Sleep Quality and Sleepiness: A Population Study, Kerman 2018

Authors: Akram Sadat Jafari Roodbandi, Farzaneh Akbari, Vafa Feyzi, Zahra Zare, Zohreh Foroozanfar

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Introduction: Circadian rhythm or sleep-awake cycle in 24 hours is one of the important factors affecting the physiological and psychological characteristics in humans that contribute to biochemical, physiological and behavioral processes and helps people to set up brain and body for sleep or active awakening during certain hours. The purpose of this study was to investigate the relationship between the characteristics of circadian rhythms on the sleep quality and sleepiness according to their demographic characteristics such as age. Methods: This cross-sectional descriptive-analytic study was carried out among the general population of Kerman, aged 15-84 years. After dividing the age groups into 10-year demographic characteristics questionnaire, the type of circadian questionnaire, Pittsburgh sleep quality questionnaire and Euporth sleepiness questionnaire were completed in equal numbers between men and women of that age group. Using cluster sampling with effect design equal 2, 1300 questionnaires were distributed during the various hours of 24 hours in public places in Kerman city. Data analysis was done using SPSS software and univariate tests and linear regressions at a significance level of 0.05. Results: In this study, 1147 subjects were included in the study, 584 (50.9%) were male and the rest were women. The mean age was 39.50 ± 15.38. 133 (11.60%) subjects from the study participants had sleepiness and 308 (26.90%) subjects had undesirable sleep quality. Using linear regression test, sleep quality was the significant correlation with sex, hours needed for sleep at 24 hours, chronic illness, sleepiness, and circadian rhythm amplitude. Sleepiness was the meaningful relationship with marital status, sleep-wake schedule of other family members and the stability of circadian rhythm. Both women and men, with age, decrease the quality of sleep and increase the rate of sleepiness. Conclusion: Age, sex, and type of circadian people, the need for sleep at 24 hours, marital status, sleep-wake schedule of other family members are significant factors related to the sleep quality and sleepiness and their adaptation to night shift work.

Keywords: circadian type, sleep quality, sleepiness, age, shift work

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795 The Importance of the Fluctuation in Blood Sugar and Blood Pressure of Insulin-Dependent Diabetic Patients with Chronic Kidney Disease

Authors: Hitoshi Minakuchi, Izumi Takei, Shu Wakino, Koichi Hayashi, Hiroshi Itoh

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Objectives: Among type 2 diabetics, patients with CKD(chronic kidney disease), insulin resistance, impaired glyconeogenesis in kidney and reduced degradation of insulin are recognized, and we observed different fluctuational patterns of blood sugar between CKD patients and non-CKD patients. On the other hand, non-dipper type blood pressure change is the risk of organ damage and mortality. We performed cross-sectional study to elucidate the characteristic of the fluctuation of blood glucose and blood pressure at insulin-treated diabetic patients with chronic kidney disease. Methods: From March 2011 to April 2013, at the Ichikawa General Hospital of Tokyo Dental College, we recruited 20 outpatients. All participants are insulin-treated type 2 diabetes with CKD. We collected serum samples, urine samples for several hormone measurements, and performed CGMS(Continuous glucose measurement system), ABPM (ambulatory blood pressure monitoring), brain computed tomography, carotid artery thickness, ankle brachial index, PWV, CVR-R, and analyzed these data statistically. Results: Among all 20 participants, hypoglycemia was decided blood glucose 70mg/dl by CGMS of 9 participants (45.0%). The event of hypoglycemia was recognized lower eGFR (29.8±6.2ml/min:41.3±8.5ml/min, P<0.05), lower HbA1c (6.44±0.57%:7.53±0.49%), higher PWV (1858±97.3cm/s:1665±109.2cm/s), higher serum glucagon (194.2±34.8pg/ml:117.0±37.1pg/ml), higher free cortisol of urine (53.8±12.8μg/day:34.8±7.1μg/day), and higher metanephrin of urine (0.162±0.031mg/day:0.076±0.029mg/day). Non-dipper type blood pressure change in ABPM was detected 8 among 9 participants with hypoglycemia (88.9%), 4 among 11 participants (36.4%) without hypoglycemia. Multiplex logistic-regression analysis revealed that the event of hypoglycemia is the independent factor of non-dipper type blood pressure change. Conclusions: Among insulin-treated type 2 diabetic patients with CKD, the events of hypoglycemia were frequently detected, and can associate with the organ derangements through the medium of non-dipper type blood pressure change.

Keywords: chronic kidney disease, hypoglycemia, non-dipper type blood pressure change, diabetic patients

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794 Oi̇l Absorption Behavior and Its Effect on Charpy Impact Test of Glass Reinforced Polyester Composites Used in the Manufacture of Naval Ship Hulls

Authors: Bouhafara Djaber, Menail Younes, Mesrafet Farouk, Aissaoui Mohammed Islem

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This article presents results of experimental investigations of the durability of (GFRP) composite exposed to typical environments of marine industries applications,The use of fiber-glass reinforced polyester composites in marine applications such as Hulls of voyage boats and hulls of small vessels for the military navy , this type of composite is becoming attractive because of their reduced weight and improved corrosion resistance. However,a deep understating of oil ageing effect on composite structures is essential to ensure long-term performance and durability. in this work evaluate the effect of oil ageing on absorptıon behavıor and ımpact properties of glass/polyester composites manufactured with two types of fiber fabrics (fibreglass mat and fiberglass woven roving) and isophthalic polyester resin. The specimens obtained from commercial (GFRP) profiles made of unsaturated polyester resin were subjected to immersion in (i) marine oil for boats and (ii) salt water at ambient temperature for up to 1 month. The effects of such exposure conditions on this types of profile we analysed in what concerns their (i) mass change,(ii) mechanical response in impact, namely on the mechanical response – oil immersion caused a higher level of degradation, compared with salt water immersion;fracture surface examination by scanning electron microscopy revealed delamination, fiber debonding and resin crumbling due to oil effect.

Keywords: Marine Engine Oil, Absorption, Polyester, Glass Fibre

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793 A Review of Research on Pre-training Technology for Natural Language Processing

Authors: Moquan Gong

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In recent years, with the rapid development of deep learning, pre-training technology for natural language processing has made great progress. The early field of natural language processing has long used word vector methods such as Word2Vec to encode text. These word vector methods can also be regarded as static pre-training techniques. However, this context-free text representation brings very limited improvement to subsequent natural language processing tasks and cannot solve the problem of word polysemy. ELMo proposes a context-sensitive text representation method that can effectively handle polysemy problems. Since then, pre-training language models such as GPT and BERT have been proposed one after another. Among them, the BERT model has significantly improved its performance on many typical downstream tasks, greatly promoting the technological development in the field of natural language processing, and has since entered the field of natural language processing. The era of dynamic pre-training technology. Since then, a large number of pre-trained language models based on BERT and XLNet have continued to emerge, and pre-training technology has become an indispensable mainstream technology in the field of natural language processing. This article first gives an overview of pre-training technology and its development history, and introduces in detail the classic pre-training technology in the field of natural language processing, including early static pre-training technology and classic dynamic pre-training technology; and then briefly sorts out a series of enlightening technologies. Pre-training technology, including improved models based on BERT and XLNet; on this basis, analyze the problems faced by current pre-training technology research; finally, look forward to the future development trend of pre-training technology.

Keywords: natural language processing, pre-training, language model, word vectors

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792 Automated Fact-Checking by Incorporating Contextual Knowledge and Multi-Faceted Search

Authors: Wenbo Wang, Yi-Fang Brook Wu

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The spread of misinformation and disinformation has become a major concern, particularly with the rise of social media as a primary source of information for many people. As a means to address this phenomenon, automated fact-checking has emerged as a safeguard against the spread of misinformation and disinformation. Existing fact-checking approaches aim to determine whether a news claim is true or false, and they have achieved decent veracity prediction accuracy. However, the state-of-the-art methods rely on manually verified external information to assist the checking model in making judgments, which requires significant human resources. This study introduces a framework, SAC, which focuses on 1) augmenting the representation of a claim by incorporating additional context using general-purpose, comprehensive, and authoritative data; 2) developing a search function to automatically select relevant, new, and credible references; 3) focusing on the important parts of the representations of a claim and its reference that are most relevant to the fact-checking task. The experimental results demonstrate that 1) Augmenting the representations of claims and references through the use of a knowledge base, combined with the multi-head attention technique, contributes to improved performance of fact-checking. 2) SAC with auto-selected references outperforms existing fact-checking approaches with manual selected references. Future directions of this study include I) exploring knowledge graphs in Wikidata to dynamically augment the representations of claims and references without introducing too much noise, II) exploring semantic relations in claims and references to further enhance fact-checking.

Keywords: fact checking, claim verification, deep learning, natural language processing

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791 Student's Difficulties with Classes That Involve Laboratory Education Approach

Authors: Kayondoamunmose Kamafrika

Abstract:

Experimental based Engineering education approach plays a vital role in the development of student’s deep understanding of both social and physical sciences. Experimental based education approach through laboratory class activities prepare students to meet national demand for high-tech skilled individuals in the government and private sector. However, students across the country are faced with difficulties in classes that involve laboratory activities: poor experimental based exposure in their early development of student’s education-life-cycle, lack of student engagement in scientific method practical thinking approach, lack of communication between students and the instructor during class, a large number of students in one classroom, lack of instruments and improper equipment calibration. The purpose of this paper is to help students develop their own scientific knowledge and understanding, develop their methodologies in the design of experiments, collect and analyze data, write laboratory reports, present and explain their findings. Experimental based laboratory activities allow students to learn with high-level understanding as well as engage in the design processes of constructing knowledge through practical means of doing science. Experimental based education systems approach will act as a catalyst in the development of practical-based-educational methodologies in social and physical science and engineering domain of learning; thereby, converting laboratory classes into pilot industries and students into professional experts in finding a solution for complex problems, research, and development of super high- tech systems.

Keywords: experimental, engineering, innovation, practicability

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790 Investigating Visual Statistical Learning during Aging Using the Eye-Tracking Method

Authors: Zahra Kazemi Saleh, Bénédicte Poulin-Charronnat, Annie Vinter

Abstract:

This study examines the effects of aging on visual statistical learning, using eye-tracking techniques to investigate this cognitive phenomenon. Visual statistical learning is a fundamental brain function that enables the automatic and implicit recognition, processing, and internalization of environmental patterns over time. Some previous research has suggested the robustness of this learning mechanism throughout the aging process, underscoring its importance in the context of education and rehabilitation for the elderly. The study included three distinct groups of participants, including 21 young adults (Mage: 19.73), 20 young-old adults (Mage: 67.22), and 17 old-old adults (Mage: 79.34). Participants were exposed to a series of 12 arbitrary black shapes organized into 6 pairs, each with different spatial configurations and orientations (horizontal, vertical, and oblique). These pairs were not explicitly revealed to the participants, who were instructed to passively observe 144 grids presented sequentially on the screen for a total duration of 7 min. In the subsequent test phase, participants performed a two-alternative forced-choice task in which they had to identify the most familiar pair from 48 trials, each consisting of a base pair and a non-base pair. Behavioral analysis using t-tests revealed notable findings. The mean score for the first group was significantly above chance, indicating the presence of visual statistical learning. Similarly, the second group also performed significantly above chance, confirming the persistence of visual statistical learning in young-old adults. Conversely, the third group, consisting of old-old adults, showed a mean score that was not significantly above chance. This lack of statistical learning in the old-old adult group suggests a decline in this cognitive ability with age. Preliminary eye-tracking results showed a decrease in the number and duration of fixations during the exposure phase for all groups. The main difference was that older participants focused more often on empty cases than younger participants, likely due to a decline in the ability to ignore irrelevant information, resulting in a decrease in statistical learning performance.

Keywords: aging, eye tracking, implicit learning, visual statistical learning

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789 The Role of 'Hindu Tantrism' in Conceptualization of the Divine Manifestations in Vajrayana Tradition of Tibetan Buddhism

Authors: Mohammed T. Shabeer

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Hoary moorlands of Tibet bear bundle of religious traditions. Vajrayana tradition of Tibetan Buddhism is one of the deep rooted religious orders of the area. It demands the homage to a variety of gods and diverse worships, especially to manifestations like the Dalai Lamas. This divine diversity has been conceptualized by remoteness of the area and transcontinental intrusion of Asiatic philosophies like Indian Buddhism, Mongolian Shamanism and Hindu Tantrism. This study reveals the role of Hindu Tantrism in conceptualizing the manifestations in Vajrayana Tradition of Tibetan Buddhism in a comparative way. Nowadays, the academic explorations and researches in the field of ‘Tibetology’ are widely tolerable in east and west alike. International community concerns such studies supportive of the restless campaigns for ‘free Tibet’. Moreover, the scientific sources on the topic are rarest and precious in the field of comparative religion. This study reveals a clear account of god concept of Vajrayana tradition and insists that the god concept of the tradition is conceptualized from the amalgamation of Indian Hindu Tantrism, Mongolian Shamanism, and Indian Buddhism. Primly, it sheds the light upon the mysterious similarities between Indian and Tibetan concepts of manifestation of gods. The scientific examination of this problem lasts in the conclusion that the transcontinental transmission of Hindu Tantrism in the special occasion of Buddhist Diaspora of 12th century in consequence of the invasion of Muslim Ghorid Sultanate had paved a vital role in shaping the Vajrayana tradition especially conceptualizing the manifestation of Tibetan gods.

Keywords: Buddhist diaspora, Hindu tantrism, manifestation of god, Vajrayana tradition of Tibetan Buddhism

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788 Political Transition in Nepal: Challenges and Limitations to Post-Conflict Peace-Building

Authors: Sourina Bej

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Since the process of decolonization in 1940, several countries in South Asia have witnessed intra-state conflicts owing to ineffective political governance. The conflicts have remained protracted as the countries have failed to make a holistic transition to a democratic state. Nepal is one such South Asian country facing a turmultous journey from monarchy to republicanism. The paper aims to focus on the democratic transition in the context of Nepal’s political, legal and economic institutions. The presence of autocratic feudalistic and centralised state structure with entrenched socio-economic inequalities has resulted in mass uprising only to see the country slip back to the old order. Even a violent civil war led by the Maoists could not overhaul the political relations or stabilize the democratic space. The paper aims to analyse the multiple political, institutional and operational challenges in the implementation of the peace agreement with the Maoist. Looking at the historical background, the paper will examine the problematic nation-building that lies at the heart of fragile peace process in Nepal. Regional dynamics have played a big role in convoluting the peace-building. The new constitution aimed at conflict resolution brought to the open, deep seated hatred among different ethnic groups in Nepal. Apart from studying the challenges to the peace process and the role of external players like India and China in the political reconstruction, the paper will debate on a viable federal solution to the ethnic conflict in Nepal. If the current government fails to pass a constitution accepted by most ethnic groups, Nepal will remain on the brink of new conflict outbreaks.

Keywords: democratisation, ethnic conflict, Nepal, peace process

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787 Improvement of Microscopic Detection of Acid-Fast Bacilli for Tuberculosis by Artificial Intelligence-Assisted Microscopic Platform and Medical Image Recognition System

Authors: Hsiao-Chuan Huang, King-Lung Kuo, Mei-Hsin Lo, Hsiao-Yun Chou, Yusen Lin

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The most robust and economical method for laboratory diagnosis of TB is to identify mycobacterial bacilli (AFB) under acid-fast staining despite its disadvantages of low sensitivity and labor-intensive. Though digital pathology becomes popular in medicine, an automated microscopic system for microbiology is still not available. A new AI-assisted automated microscopic system, consisting of a microscopic scanner and recognition program powered by big data and deep learning, may significantly increase the sensitivity of TB smear microscopy. Thus, the objective is to evaluate such an automatic system for the identification of AFB. A total of 5,930 smears was enrolled for this study. An intelligent microscope system (TB-Scan, Wellgen Medical, Taiwan) was used for microscopic image scanning and AFB detection. 272 AFB smears were used for transfer learning to increase the accuracy. Referee medical technicians were used as Gold Standard for result discrepancy. Results showed that, under a total of 1726 AFB smears, the automated system's accuracy, sensitivity and specificity were 95.6% (1,650/1,726), 87.7% (57/65), and 95.9% (1,593/1,661), respectively. Compared to culture, the sensitivity for human technicians was only 33.8% (38/142); however, the automated system can achieve 74.6% (106/142), which is significantly higher than human technicians, and this is the first of such an automated microscope system for TB smear testing in a controlled trial. This automated system could achieve higher TB smear sensitivity and laboratory efficiency and may complement molecular methods (eg. GeneXpert) to reduce the total cost for TB control. Furthermore, such an automated system is capable of remote access by the internet and can be deployed in the area with limited medical resources.

Keywords: TB smears, automated microscope, artificial intelligence, medical imaging

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786 Influence of Yōmeigaku and Emerson on Meiji Intelligentsia: With Special Reference to Kitamura Tōkoku

Authors: Arpita Paul

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Wang Yang-ming introduced a revolutionary dimension to Japanese thought through his philosophy on intuitive moral consciousness. Post-Meiji Restoration,Emerson struck a chord with the Japanese due to the striking similarities his theories on transcendentalism had with doctrines of Wang Yang-ming'sschool of thought (Yōmeigaku), as pointed out by HomeiIwano (1873-1920). Wang's philosophy, chiefly anchored in the idea of the fundamental unity of thought and action, resembles the non-dualistic aspect of Brahman, a subject of Emerson's deep interest. Kitamura Tōkoku's (1868-1894) ardent reading of Emerson corroborated what he had learned in Wang Yang-ming's philosophy. This essay shall begin with a discussion on Emerson's discoveries of Vedanta that later, on a parallel ground with Yōmeigaku, significantly influenced Tōkoku. This essay will then demonstrate how Tōkokutransforms these philosophies to portray the advent of modern consciousness in Japan in his magnum opus"Naibuseimeiron." In his attempt to undo the blindfold of past feudalism,Tōkoku repeatedly championed the mental process of a self-reliant individual in his essays which showcase the metamorphosis of Japanese individualism in the final decades of the Meiji Period. In seeking to express Japan's budding intellectual enterprise,Tōkoku asserts securing one's vantage point in the world through an awakened consciousness. In his desire to articulate this, Tōkoku becomes, as argued in this paper's penultimate and final sections, a fascinating merging point of the philosophical doctrines of Vedanta, Yōmeigaku, and Emerson, a rare depiction in the existing scholarship.

Keywords: meiji intellengtsia, yomeigaku, vedanta, modern consciousness

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785 Hypolipidemic and Antioxidant Effects of Mycelial Polysaccharides from Calocybe indica in Hyperlipidemic Rats Induced by High-Fat Diet

Authors: Govindan Sudha, Mathumitha Subramaniam, Alamelu Govindasamy, Sasikala Gunasekaran

Abstract:

The aim of this study was to investigate the protective effect of Hypsizygus ulmarius polysaccharides (HUP) on reducing oxidative stress, cognitive impairment and neurotoxicity in D-galactose induced aging mice. Mice were subcutaneously injected with D-galactose (150 mg/kg per day) for 6 weeks and were administered HUP simultaneously. Aged mice receiving vitamin E (100 mg/kg) served as positive control. Chronic administration of D-galactose significantly impaired cognitive performance oxidative defence and mitochondrial enzymes activities as compared to control group. The results showed that HUP (200 and 400 mg/kg) treatment significantly improved the learning and memory ability in Morris water maze test. Biochemical examination revealed that HUP significantly increased the decreased activities of superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GPx), glutathione reductase (GR), glutathione-S-transferase (GST), mitochondrial enzymes-NADH dehydrogenase, malate dehydrogenase (MDH), isocitrate dehydrogenase (ICDH), Na+K+, Ca2+, Mg2+ATPase activities, elevated the lowered total anti-oxidation capability (TAOC), glutathione (GSH), vitamin C and decreased the raised acetylcholinesterase (AChE) activities, malondialdehyde (MDA), hydroperoxide (HPO), protein carbonyls (PCO), advanced oxidation protein products (AOPP) levels in brain of aging mice induced by D-gal in a dose-dependent manner. In conclusion, present study highlights the potential role of HUP against D-galactose induced cognitive impairment, biochemical and mitochondrial dysfunction in mice. In vitro studies on the effect of HUP on scavenging DPPH, ABTS, DMPD, OH radicals, reducing power, B-carotene bleaching and lipid peroxidation inhibition confirmed the free radical scavenging and antioxidant activity of HUP. The results suggest that HUP possesses anti-aging efficacy and may have potential in treatment of neurodegenerative diseases.

Keywords: aging, antioxidants, mushroom, neurotoxicity

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784 Numerical Simulation of Footing on Reinforced Loose Sand

Authors: M. L. Burnwal, P. Raychowdhury

Abstract:

Earthquake leads to adverse effects on buildings resting on soft soils. Mitigating the response of shallow foundations on soft soil with different methods reduces settlement and provides foundation stability. Few methods such as the rocking foundation (used in Performance-based design), deep foundation, prefabricated drain, grouting, and Vibro-compaction are used to control the pore pressure and enhance the strength of the loose soils. One of the problems with these methods is that the settlement is uncontrollable, leading to differential settlement of the footings, further leading to the collapse of buildings. The present study investigates the utility of geosynthetics as a potential improvement of the subsoil to reduce the earthquake-induced settlement of structures. A steel moment-resisting frame building resting on loose liquefiable dry soil, subjected to Uttarkashi 1991 and Chamba 1995 earthquakes, is used for the soil-structure interaction (SSI) analysis. The continuum model can simultaneously simulate structure, soil, interfaces, and geogrids in the OpenSees framework. Soil is modeled with PressureDependentMultiYield (PDMY) material models with Quad element that provides stress-strain at gauss points and is calibrated to predict the behavior of Ganga sand. The model analyzed with a tied degree of freedom contact reveals that the system responses align with the shake table experimental results. An attempt is made to study the responses of footing structure and geosynthetics with unreinforced and reinforced bases with varying parameters. The result shows that geogrid reinforces shallow foundation effectively reduces the settlement by 60%.

Keywords: settlement, shallow foundation, SSI, continuum FEM

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783 Dental Fluorosis in Domestic Animals Inhabiting Industrial Area of Udaipur, Rajasthan, India

Authors: Lalita Panchal, Zulfiya Sheikh

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Fluoride is essential for teeth and bones development not only for human beings but also for animals. But excess intake of fluoride causes harmful effects on health. Fluorosis is a worldwide health hazard and India is also one of the endemic countries. Udaipur district of Rajasthan is also prone to fluorosis and superphosphate industries are aggravating fluoride toxicity in this area. Grazing fields for animals in the close vicinity of the industries, fodder and water are fluoride contaminated. Fluoride toxicity in the form of dental fluorosis was observed in domestic animals, inhabiting industrial area near Udaipur, where superphosphate fertilizer plants are functioning and releasing fluoride and fumes and effluents into the surroundings. These fumes and gases directly affect the vegetation of grazing field, thus allowing entry of fluoride into the food chain. A survey was conducted in this area to assess the severity of fluorosis, in 2015-16. It was a house to house survey and animal owners were asked for their fodder and water supply. Anterior teeth of the animal were observed. Domestic animals exhibited mild to severe signs of dental fluorosis. Teeth showed deep brown staining, patches, lines and abrasions. Even immature animals were affected badly. Most of the domestic animals were affected, but goats of this area showed chronic symptoms of fluorosis. Due to abrasion of teeth and paining teeth their chewing or grazing capacity and appetite reduced. Eventually, it reduced the life span of animals and increased the mortality rate.

Keywords: domestic animals, fluoride toxicity, industrial fluorosis, superphosphate fertilizers

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782 Examining the Effects of Increasing Lexical Retrieval Attempts in Tablet-Based Naming Therapy for Aphasia

Authors: Jeanne Gallee, Sofia Vallila-Rohter

Abstract:

Technology-based applications are increasingly being utilized in aphasia rehabilitation as a means of increasing intensity of treatment and improving accessibility to treatment. These interactive therapies, often available on tablets, lead individuals to complete language and cognitive rehabilitation tasks that draw upon skills such as the ability to name items, recognize semantic features, count syllables, rhyme, and categorize objects. Tasks involve visual and auditory stimulus cues and provide feedback about the accuracy of a person’s response. Research has begun to examine the efficacy of tablet-based therapies for aphasia, yet much remains unknown about how individuals interact with these therapy applications. Thus, the current study aims to examine the efficacy of a tablet-based therapy program for anomia, further examining how strategy training might influence the way that individuals with aphasia engage with and benefit from therapy. Individuals with aphasia are enrolled in one of two treatment paradigms: traditional therapy or strategy therapy. For ten weeks, all participants receive 2 hours of weekly in-house therapy using Constant Therapy, a tablet-based therapy application. Participants are provided with iPads and are additionally encouraged to work on therapy tasks for one hour a day at home (home logins). For those enrolled in traditional therapy, in-house sessions involve completing therapy tasks while a clinician researcher is present. For those enrolled in the strategy training group, in-house sessions focus on limiting cue use in order to maximize lexical retrieval attempts and naming opportunities. The strategy paradigm is based on the principle that retrieval attempts may foster long-term naming gains. Data have been collected from 7 participants with aphasia (3 in the traditional therapy group, 4 in the strategy training group). We examine cue use, latency of responses and accuracy through the course of therapy, comparing results across group and setting (in-house sessions vs. home logins).

Keywords: aphasia, speech-language pathology, traumatic brain injury, language

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781 Applications of Polyvagal Theory for Trauma in Clinical Practice: Auricular Acupuncture and Herbology

Authors: Aurora Sheehy, Caitlin Prince

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Within current orthodox medical protocols, trauma and mental health issues are deemed to reside within the realm of cognitive or psychological therapists and are marginalised in these areas, in part due to limited drugs option available, mostly manipulating neurotransmitters or sedating patients to reduce symptoms. By contrast, this research presents examples from the clinical practice of how trauma can be assessed and treated physiologically. Adverse Childhood Experiences (ACEs) are a tally of different types of abuse and neglect. It has been used as a measurable and reliable predictor of the likelihood of the development of autoimmune disease. It is a direct way to demonstrate reliably the health impact of traumatic life experiences. A second assessment tool is Allostatic Load, which refers to the cumulative effects that chronic stress has on mental and physical health. It records the decline of an individual’s physiological capacity to cope with their experience. It uses a specific grouping of serum testing and physical measures. It includes an assessment of neuroendocrine, cardiovascular, immune and metabolic systems. Allostatic load demonstrates the health impact that trauma has throughout the body. It forms part of an initial intake assessment in clinical practice and could also be used in research to evaluate treatment. Examining medicinal plants for their physiological, neurological and somatic effects through the lens of Polyvagal theory offers new opportunities for trauma treatments. In situations where Polyvagal theory recommends activities and exercises to enable parasympathetic activation, many herbs that affect Effector Memory T (TEM) cells also enact these responses. Traditional or Indigenous European herbs show the potential to support the polyvagal tone, through multiple mechanisms. As the ventral vagal nerve reaches almost every major organ, plants that have actions on these tissues can be understood via their polyvagal actions, such as monoterpenes as agents to improve respiratory vagal tone, cyanogenic glycosides to reset polyvagal tone, volatile oils rich in phenyl methyl esters improve both sympathetic and parasympathetic tone, bitters activate gut function and can strongly promote parasympathetic regulation. Auricular Acupuncture uses a system of somatotopic mapping of the auricular surface overlaid with an image of an inverted foetus with each body organ and system featured. Given that the concha of the auricle is the only place on the body where the Vagus Nerve neurons reach the surface of the skin, several investigators have evaluated non-invasive, transcutaneous electrical nerve stimulation (TENS) at auricular points. Drawn from an interdisciplinary evidence base and developed through clinical practice, these assessment and treatment tools are examples of practitioners in the field innovating out of necessity for the best outcomes for patients. This paper draws on case studies to direct future research.

Keywords: polyvagal, auricular acupuncture, trauma, herbs

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780 Responsive Integrative Therapeutic Method: Paradigm for Addressing Core Deficits in Autism by Balkibekova

Authors: Balkibekova Venera Serikpaevna

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Background: Autism Spectrum Disorder (ASD) poses significant challenges in both diagnosis and treatment. Existing therapeutic interventions often target specific symptoms, necessitating the exploration of alternative approaches. This study investigates the RITM (Rhythm Integration Tapping Music) developed by Balkibekova, aiming to create imitation, social engagement and a wide range of emotions through brain development. Methods: A randomized controlled trial was conducted with 100 participants diagnosed with ASD, aged 1 to 4 years. Participants were randomly assigned to either the RITM therapy group or a control group receiving standard care. The RITM therapy, rooted in tapping rhythm to music such as: marche on the drums, waltz on bells, lullaby on musical triangle, dancing on tambourine, polka on wooden spoons. Therapy sessions were conducted over a 3 year period, with assessments at baseline, midpoint, and post-intervention. Results: Preliminary analyses reveal promising outcomes in the RITM therapy group. Participants demonstrated significant improvements in social interactions, speech understanding, birth of speech, and adaptive behaviors compared to the control group. Careful examination of subgroup analyses provides insights into the differential effectiveness of the RITM approach across various ASD profiles. Conclusions: The findings suggest that RITM therapy, as developed by Balkibekova, holds promise as intervention for ASD. The integrative nature of the approach, addressing multiple domains simultaneously, may contribute to its efficacy. Further research is warranted to validate these preliminary results and explore the long-term impact of RITM therapy on individuals with ASD. This abstract presents a snapshot of the research, emphasizing the significance, methodology, key findings, and implications of the RITM therapy method for consideration in an autism conference.

Keywords: RITM therapy, tapping rhythm, autism, mirror neurons, bright emotions, social interactions, communications

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