Search results for: vision impairment

Authors: Boxiang Zhuang

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This study analyzes the clinical manifestations, hearing rehabilitation methods and outcomes of a complex case of neurofibromatosis type II (NF2). Methods: The clinical manifestations, medical history, clinical data, surgical methods and postoperative hearing rehabilitation outcomes of an NF2 patient were analyzed to determine the hearing reconstruction method and postoperative effect for a special type of NF2 acoustic neuroma. Results: The patient had bilateral acoustic neuromas with profound sensorineural hearing loss in both ears. Peripheral blood genetic testing did not reveal pathogenic gene mutations, suggesting mosaicism. The patient had an intracochlear schwannoma in the right ear and severely impaired vision in both eyes. Cochlear implantation with tumor retention was performed in the right ear. After 2 months of family-based auditory and speech rehabilitation, the Categories of Auditory Performance (CAP) score improved from 0 to 5. Conclusion: NF2 has complex clinical manifestations and poor prognosis. For NF2 patients with intracochlear tumors, cochlear implantation with tumor retention can be used to reconstruct hearing.

Keywords: NF2, intracochlear schwannoma, hearing reconstruction, cochlear implantation

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Authors: Yu Chen

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In line with existing philosophical approaches, this research proposes a conceptual model with an innovative spatial vision and aesthetic principles for Artificial Intelligence (AI) application in brand advertising. The model first identifies the major constituencies in contemporary advertising on three spatial levels—physical, psychological, and symbolic. The model further incorporates the relationships among AI, aesthetics, branding, and advertising and their interactions with the major actors in all spaces. It illustrates that AI may follow the aesthetic principles-- beauty, elegance, and simplicity-- to reinforce brand identity and consistency in advertising, to collaborate with stakeholders, and to satisfy different advertising objectives on each level. It proposes that, with aesthetic guidelines, AI may assist consumers to emerge into the physical, psychological, and symbolic advertising spaces and helps transcend the tangible advertising messages to meaningful brand symbols. Conceptually, the research illustrates that even though consumers’ engagement with brand mostly begins with physical advertising and later moves to psychological-symbolic, AI-assisted advertising should start with the understanding of brand symbolic-psychological and consumer aesthetic preferences before the physical design to better resonate. Limits of AI and future AI functions in advertising are discussed.

Keywords: AI, spatial, aesthetic, brand advertising

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Authors: Alexandra Steed

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Alexandra Steed URBAN was commissioned to undertake the South Essex Green and Blue Infrastructure Study (SEGBI) on behalf of the Association of South Essex Local Authorities (ASELA): a partnership of seven neighboring councils within the Thames Estuary. Located on London’s doorstep, the 70,000-hectare region is under extraordinary pressure for regeneration, further development, and economic expansion, yet faces extreme challenges: sea-level rise and inadequate flood defenses, stormwater flooding and threatened infrastructure, loss of internationally important habitats, significant existing community deprivation, and lack of connectivity and access to green space. The brief was to embrace these challenges in the creation of a document that would form a key part of ASELA’s Joint Strategic Framework and feed into local plans and master plans. Thus, helping to tackle climate change, ecological collapse, and social inequity at a regional scale whilst creating a relationship and awareness between urban communities and the surrounding landscapes and nature. The SEGBI project applied a ‘land-based’ methodology, combined with a co-design approach involving numerous stakeholders, to explore how living infrastructure can address these significant issues, reshape future planning and development, and create thriving places for the whole community of life. It comprised three key stages, including Baseline Review; Green and Blue Infrastructure Assessment; and the final Green and Blue Infrastructure Report. The resulting proposals frame an ambitious vision for the delivery of a new regional South Essex Estuary (SEE) Park – 24,000 hectares of protected and connected landscapes. This unified parkland system will drive effective place-shaping and “leveling up” for the most deprived communities while providing large-scale nature recovery and biodiversity net gain. Comprehensive analysis and policy recommendations ensure best practices will be embedded within planning documents and decisions guiding future development. Furthermore, a Natural Capital Account was undertaken as part of the strategy showing the tremendous economic value of the natural assets. This strategy sets a pioneering precedent that demonstrates how the prioritisation of living infrastructure has the capacity to address climate change and ecological collapse, while also supporting sustainable housing, healthier communities, and resilient infrastructures. It was only achievable through a collaborative and cross-boundary approach to strategic planning and growth, with a shared vision of place, and a strong commitment to delivery. With joined-up thinking and a joined-up region, a more impactful plan for South Essex was developed that will lead to numerous environmental, social, and economic benefits across the region, and enhancing the landscape and natural environs on the periphery of one of the largest cities in the world.

Keywords: climate change, green and blue infrastructure, landscape architecture, master planning, regional planning, social equity

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Authors: Suhathai Tosangwarn, Philip Clissett, Holly Blake

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Background: High prevalence of depression has been reported among older adults living in care homes in Thailand, associated with physical impairment, low social support, low self-esteem and particularly stigma associated with living in a care home. However, little is understood about how such stigma is experienced among Thai care home residents. This study examines residents’ perceptions of stigma and their strategies for coping with stigma. Method/Design: Case study research was used to gain an in-depth view about the stigma of residents’ perspectives and experiences from two care homes in the northeast of Thailand by conducting an in-depth interview and non-participant observation. Qualitative interviews were conducted with 30 older residents (aged >60 years), purposively sampled from both care homes. Non-participant observation was conducted in various public spaces of the care homes, including the dining room, corridors, and activities areas for approximately one to two hours per day at different times; morning and afternoon including weekdays and weekend in both care homes for one month. Thematic analysis was used to analyse the data. Results: The study identified three major themes related to the causes of stigma, the reactions towards stigma and the mitigating factors. Negative beliefs about care homes, negative attitudes, and stereotypes toward the elderly and perceptions of unequal power relations between staff and residents were the main factors precipitating stigma. Consequently, residents exhibited negative emotions and behaviours, including depressive symptoms, while living in care homes. Residents reported the use of particular coping strategies, including accessing support from the public and staff and engaging in care home activities which these helped them to cope with their perception of stigma. Conclusion: Improved understanding of the underlying factors behind perceived stigma in care home residents may help to prevent depression and reduce perceptions of stigma associated with living in a care home, by informing strategy, supportive intervention and guidelines for appropriate care for older Thai residents.

Keywords: care home, depression, older adult, stigma, Thailand

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Authors: Yaser Riki

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There are plenty of considerations about the Third World and developing countries, but one of the main issues regarding these areas is how we can study them. This article makes attention to a fundamental way of approaching this subject through the convergence of history, philosophy, and sociology in order to understand the complexity of the Third World countries. These three disciplines are naturally connected and integrated, but they have gradually separated. While sociology has originated from philosophy, this work is an attempt to generate a sociology that incorporates philosophy as well as history at its heart. This is descriptive-analytical research that searches the history of sociology to find works and theories that provide ideas for this purpose, including the sociology of knowledge and science, The German Ideology (Karl Marx and Friedrich Engels), The Protestant Ethic (Max Weber), Ideology and Utopia (Karl Mannheim) and Dialectic of Enlightenment (Horkheimer and Adorno) provide ideas needed for this purpose. The paper offers a methodological and theoretical vision (historical-philosophical sociology) to identify a few factors, such as the system of thought, that are usually invisible and cause problems in societies, especially third-world counties. This is similar to what some of the founders of sociology did in the first world.

Keywords: the third world, methodology, sociology, philosophy, history, social change, development, social movements

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Authors: Arben Murtezani, Shefqet Mrasori, Vančo Spirov, Bukurije Rama, Oliver Dimitrovski, Visar Bunjaku

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Overview: Temporomandibular disorders (TMDs) are chronic musculoskeletal pain conditions. Clinical indicators of discomfort are related to the use of the joint stiffness during first motions after extended rest and restricted joint range of motion can cause substantial pain and disability. There is little evidence that physical therapy methods of management cause long-lasting reduction in signs and symptoms. Exercise programs premeditated to improve physical fitness have beneficial effects on chronic pain and disability of the musculoskeletal system. Objective: The aim of this study was to assess the effectiveness of physical therapy interventions in the management of temporomandibular disorders. Materials and Methods: A prospective comparative study with a 2-month follow-up period was conducted between April 2016 and June 2016 at the Physical Medicine and Rehabilitation Clinic in Prishtina. Forty six patients with TMDs, (more than three months duration of symptoms) were randomized into two groups: the TENS therapy group (n=24) and combination of active exercise and manual therapy group (n=22). The TENS therapy group patients were treated with twelve sessions of TENS. The treatment period of both groups was 3 weeks at an outpatient clinic. Following main outcome measures were evaluated: (1) pain at rest (2) pain at stress (3) impairment (4) mouth opening at base-line, before and after treatment and at 3 month follow-up. Results: Significant reduction in pain was observed in both treatment groups. In the TENS group 73% (16/22) achieved at least 80% improvement from baseline in TMJ pain at 2 months compared with 54% (13/24) in the exercise group (difference of 19%; 95% confidence interval 220 to 30%). Active and passive maximum mouth opening has been greater in the TENS group (p < 0.05). Conclusion: Exercise therapy in combination with TENS seems to be useful in the treatment of temporomandibular disorders.

Keywords: temporomandibular joint disorders, TENS, manual therapy, exercise

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Authors: Sahar M. El-Gowilly, Mai M. Helmy, Hanan M. El-Gowelli

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Methotrexate (MTX) is widely used in treatment of cancers and autoimmune diseases. However, nephrotoxicity is one of its most important side effects. The peroxisome proliferator-activated receptor gamma agonist, pioglitazone, is known to exert antiinflammatory and reno-protective effects in various kidney injuries. The purpose of this study was to investigate the potential involvement of endothelial damage in MTX-induced renal injury and to elaborate the possible protective effect of pioglitazone against MTX-induced endothelial impairment. Compared with saline-treated rats, treatment with MTX (7 mg/kg for 3 day) caused significant elevations in serum levels of urea and creatinine, increased renal nitrate/nitrite level and impaired renovascular responsiveness of isolated perfused kidney to endothelium-dependent vasodilations induced by acetylcholine (0.01-2.43 nmol) and isoprenaline (1µmol). These effects were abolished by concurrent treatment with pioglitazone (2.5 mg/kg, for 5 days starting two days before MTX). Alternatively, MTX treatment did not affect endothelium-independent renovascular relaxation induced by sodium nitroprusside (0.001-10 μmole). The possibility that alterations in renal antioxidants, circulating cytokine and apoptotic factor (Fas) levels contributed to MTX-pioglitazone interaction was assessed. Pioglitazone treatment abrogated renal oxidative stress (decreased reduced glutathione and catalase activity and increased malondialdehyde), elevated serum cytokine (interleukin-6, interleukin-10, tumor necrosis factor-alpha and transforming growth factor-beta1) and Fas induced by MTX. Histologically, MTX caused defused tubular cells swelling and vacuolization associated with endothelial damage in renal arterioles. These effects disappeared upon co-treated with pioglitazone. Collectively, pioglitazone abolished MTX-induced endothelium dysfunction and nephrotoxicity via ameliorating oxidative stress and rectifying cytokines and Fas abnormalities caused by MTX.

Keywords: methotrexate, pioglitazone, endothelium, kidney

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Authors: Abe D. Desta

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This study suggests a deep learning-based method for identifying and following moving objects in surveillance video. The proposed method uses a fast regional convolution neural network (F-RCNN) trained on a substantial dataset of vehicle images to first detect vehicles. A Kalman filter and a data association technique based on a Hungarian algorithm are then used to monitor the observed vehicles throughout time. However, in general, F-RCNN algorithms have been shown to be effective in achieving high detection accuracy and robustness in this research study. For example, in one study The study has shown that the vehicle detection and tracking, the system was able to achieve an accuracy of 97.4%. In this study, the F-RCNN algorithm was compared to other popular object detection algorithms and was found to outperform them in terms of both detection accuracy and speed. The presented system, which has application potential in actual surveillance systems, shows the usefulness of deep learning approaches in vehicle detection and tracking.

Keywords: artificial intelligence, computer vision, deep learning, fast-regional convolutional neural networks, feature extraction, vehicle tracking

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Authors: Bin Ji, Kai Xu, Shunyu Yao, Jingjing Liu, Ye Pan

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Human pose estimation is a popular research area in computer vision for its important application in human-machine interface. In recent years, 2D human pose estimation based on convolution neural network has got great progress and development. However, in more and more practical applications, people often need to deal with tasks based on video. It’s not far-fetched for us to consider how to combine the spatial and temporal information together to achieve a balance between computing cost and accuracy. To address this issue, this study proposes a new spatiotemporal model, namely Spatiotemporal Net (STNet) to combine both temporal and spatial information more rationally. As a result, the predicted keypoints heatmap is potentially more accurate and spatially more precise. Under the condition of ensuring the recognition accuracy, the algorithm deal with spatiotemporal series in a decoupled way, which greatly reduces the computation of the model, thus reducing the resource consumption. This study demonstrate the effectiveness of our network over the Penn Action Dataset, and the results indicate superior performance of our network over the existing methods.

Keywords: convolutional long short-term memory, deep learning, human pose estimation, spatiotemporal series

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Authors: Lai Junzhe, Wang Lihao, Burra Venkata Durga Kumar

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In recent years, due to today's global technological advances, big data and artificial intelligence technologies have been widely used in various industries and fields, playing an important role in reducing costs and increasing efficiency. Among them, artificial intelligence has derived another branch in its own continuous progress and the continuous development of computer personnel, namely distributed artificial intelligence computing systems. Distributed AI is a method for solving complex learning, decision-making, and planning problems, characterized by the ability to take advantage of large-scale computation and the spatial distribution of resources, and accordingly, it can handle problems with large data sets. Nowadays, distributed AI is widely used in military, medical, and human daily life and brings great convenience and efficient operation to life. In this paper, we will discuss three areas of distributed AI computing systems in vision processing, blockchain, and smart home to introduce the performance of distributed systems and the role of AI in distributed systems.

Keywords: distributed system, artificial intelligence, blockchain, IoT, visual information processing, smart home

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Authors: Anoop T. R., Otman Basir, Robert F. Hess, Ben Thompson

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Strabismus refers to a misalignment of the eyes. Early detection and treatment of strabismus in childhood can prevent the development of permanent vision loss due to abnormal development of visual brain areas. Currently, many children with strabismus remain undiagnosed until school entry because current automated screening methods have limited success in the preschool age range. A method for strabismus detection using eye alignment stability (EAS) is proposed. This method starts with face detection, followed by facial landmark detection, eye region segmentation, eye gaze extraction, and eye alignment stability estimation. Binarization and morphological operations are performed for segmenting the pupil region from the eye. After finding the EAS, its absolute value is used to differentiate the strabismic eye from the non-strabismic eye. If the value of the eye alignment stability is greater than a particular threshold, then the eyes are misaligned, and if its value is less than the threshold, the eyes are aligned. The method was tested on 175 strabismic and non-strabismic images obtained from Kaggle and Google Photos. The strabismic eye is taken as a positive class, and the non-strabismic eye is taken as a negative class. The test produced a true positive rate of 100% and a false positive rate of 7.69%.

Keywords: strabismus, face detection, facial landmarks, eye segmentation, eye gaze, binarization

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Authors: Cóndor C. José, Rodrigues E. Camila, Noronha L. Irene, Dos Santos Fernando, Irigoyen M. Claudia, Andrade Lúcia

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Sepsis induces alterations in hemodynamics and autonomic nervous system (ASN). The autonomic activity can be calculated by measuring heart rate variability (HRV) that represents the complex interplay between ASN and cardiac pacemaker cells. Wharton’s jelly mesenchymal stem cells (WJ-MSCs) are known to express genes and secreted factors involved in neuroprotective and immunological effects, also to improve the survival in experimental septic animals. We hypothesized, that WJ-MSCs present an important role in the autonomic activity and in the hemodynamic effects in a cecal ligation and puncture (CLP) model of sepsis. Methods: We used flow cytometry to evaluate WJ-MSCs phenotypes. We divided Wistar rats into groups: sham (shamoperated); CLP; and CLP+MSC (106 WJ-MSCs, i.p., 6 h after CLP). At 24 h post-CLP, we recorded the systolic arterial pressure (SAP) and heart rate (HR) over 20 min. The spectral analysis of HR and SAP; also the spontaneous baroreflex sensitivity (measure by bradycardic and tachycardic responses) were evaluated after recording. The one-way ANOVA and the post hoc Student– Newman– Keuls tests (P< 0.05) were used to data comparison Results: WJ-MSCs were negative for CD3, CD34, CD45 and HLA-DR, whereas they were positive for CD73, CD90 and CD105. The CLP group showed a reduction in variance of overall variability and in high-frequency power of HR (heart parasympathetic activity); furthermore, there is a low-frequency reduction of SAP (blood vessels sympathetic activity). The treatment with WJ-MSCs improved the autonomic activity by increasing the high and lowfrequency power; and restore the baroreflex sensitive. Conclusions: WJ-MSCs attenuate the impairment of autonomic control of the heart and vessels and might therefore play a protective role in sepsis. (Supported by FAPESP).

Keywords: baroreflex response, heart rate variability, sepsis, wharton’s jelly-derived mesenchymal stem cells

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Authors: William Huang

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Retinal prostheses are currently limited to low resolution grayscale images that lack color and spatial information. This study develops a novel real-time image optimization framework and tools to encode maximum information to the prostheses which are constrained by the number of electrodes. One key idea is to localize main objects in images while reducing unnecessary background noise through region-contrast saliency maps. A novel color depth mapping technique was developed through MiniBatchKmeans clustering and color space selection. The resulting image was downsampled using bicubic interpolation to reduce image size while preserving color quality. In comparison to current schemes, the proposed framework demonstrated better visual quality in tested images. The use of the region-contrast saliency map showed improvements in efficacy up to 30%. Finally, the computational speed of this algorithm is less than 380 ms on tested cases, making real-time retinal prostheses feasible.

Keywords: retinal implants, virtual processing unit, computer vision, saliency maps, color quantization

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Authors: Courret Gilles, Pidoux Damien

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Considering that sunshine is the ultimate reference in lighting, we have examined the spectral correlation between a series of electric light sources and sunlight. As the latter is marked by fluctuations, we have taken two spectra of reference: on the one hand, the CIE daylight standard illuminant, and on the other hand, the global illumination by the clear sky with the sun at 30° above the horizon. We determined the coefficients of correlation between the spectra filtered by the sensitivity of the CIE standard observer for photopic vision. We also calculated the luminous efficiency of the radiation in order to compare the ideal energy performances as well as the CIE color indexes Ra, Ra14, and Rf, since the choice of a light source requires a trade-off between color rendering and luminous efficiency. The benchmarking includes the most commonly used bulbs, various white LED (Lighting Emitting Diode) of warm white or cold white types, incandescent halogen as well as two HID lamps (High-Intensity Discharge) and two plasma lamps of different types, a solar simulator and a new version of the sulfur lamp. The latter obtains the best correlation, whether in comparison with the solar spectrum or that of the standard illuminant.

Keywords: electric light sources, plasma lamp, daylighting, sunlight, spectral correlation

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Authors: Redouane Tlemsani, Abdelkader Benyettou

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Work is in on line Arabic character recognition and the principal motivation is to study the Arab manuscript with on line technology. This system is a Markovian system, which one can see as like a Dynamic Bayesian Network (DBN). One of the major interests of these systems resides in the complete models training (topology and parameters) starting from training data. Our approach is based on the dynamic Bayesian Networks formalism. The DBNs theory is a Bayesians networks generalization to the dynamic processes. Among our objective, amounts finding better parameters, which represent the links (dependences) between dynamic network variables. In applications in pattern recognition, one will carry out the fixing of the structure, which obliges us to admit some strong assumptions (for example independence between some variables). Our application will relate to the Arabic isolated characters on line recognition using our laboratory database: NOUN. A neural tester proposed for DBN external optimization. The DBN scores and DBN mixed are respectively 70.24% and 62.50%, which lets predict their further development; other approaches taking account time were considered and implemented until obtaining a significant recognition rate 94.79%.

Keywords: Arabic on line character recognition, dynamic Bayesian network, pattern recognition, computer vision

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Authors: Yashaswini Channabasavegowda, Hema Nagaraj

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Aim: The current study aims at discovering word-class deficits concerning the noun-verb ratio in confrontation naming, picture description, and picture-word matching tasks. A total of ten persons with aphasia (PWA) and ten age-matched neurotypical individuals (NTI) were recruited for the study. The research includes both behavioural and objective measures to assess the word class deficits in PWA. Objective: The main objective of the research is to identify word class deficits seen in persons with aphasia, using various speech eliciting tasks. Method: The study was conducted in the L1 of the participants, considered to be Kannada. Action naming test and Boston naming test adapted to the Kannada version are administered to the participants; also, a picture description task is carried out. Picture-word matching task was carried out using e-prime software (version 2) to measure the accuracy and reaction time with respect to identification verbs and nouns. The stimulus was presented through auditory and visual modes. Data were analysed to identify errors noticed in the naming of nouns versus verbs, with respect to the Boston naming test and action naming test and also usage of nouns and verbs in the picture description task. Reaction time and accuracy for picture-word matching were extracted from the software. Results: PWA showed a significant difference in sentence structure compared to age-matched NTI. Also, PWA showed impairment in syntactic measures in the picture description task, with fewer correct grammatical sentences and fewer correct usage of verbs and nouns, and they produced a greater proportion of nouns compared to verbs. PWA had poorer accuracy and lesser reaction time in the picture-word matching task compared to NTI, and accuracy was higher for nouns compared to verbs in PWA. The deficits were noticed irrespective of the cause leading to aphasia.

Keywords: nouns, verbs, aphasia, naming, description

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Authors: S. A. El-Marasy, S. A. El Awdan, R. M. Abd-Elsalam

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This study aimed to investigate the possible neuroprotective effect of chrysin on thioacetamide (TAA)-induced hepatic encephalopathy in rats. Also, the effect of chrysin on motor impairment, cognitive deficits, oxidative stress, neuroinflammation, apoptosis and histopathological damage was assessed. Male Wistar rats were randomly allocated into five groups. The first group received the vehicle (distilled water) for 21 days and is considered as normal group. While the second one received intraperitoneal dose of TAA (200 mg/kg) at three alternative days during the third week of the experiment to induce HE and is considered as control group. The other three groups were orally administered chrysin for 21 days (25, 50, 100 mg/kg) and starting from day 17; rats received intraperitoneal dose of TAA (200 mg/kg) at three alternative days. Then behavioral, biochemical, histopathological and immunohistochemical analyses were assessed. Then behavioral, biochemical, histopathological and immunohistochemical analyses were assessed. Chrysin reversed TAA-induced motor coordination in rotarod test, cognitive deficits in object recognition test (ORT) and attenuated serum ammonia, hepatic liver enzymes, reduced malondialdehyde (MDA), elevated reduced glutathione (GSH), reduced nuclear factor kappa B (NF-κB), tumor necrosis factor-alpha (TNF-α) and Interleukin-6 (IL-6) brain contents. Chrysin administration also reduced Toll-4 receptor (TLR-4) gene expression, caspase-3 protein expression, hepatic necrosis and astrocyte swelling. This study depicts that chrysin exerted neuroprotective effect in TAA-induced HE rats, evidenced by improvement of cognitive deficits, motor incoordination and histopathological changes such as astrocyte swelling and vacuolization; hallmarks in HE, via reducing hyperammonemia, ameliorating hepatic function, in addition to its anti-oxidant, inactivation of TLR-4/NF-κB inflammatory pathway, and anti-apoptotic effects.

Keywords: chrysin, hepatic encephalopathy, oxidative stress, rats, thioacetamide, TLR4/NF-κB pathway

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Authors: Tiago do Carmo Nogueira, Cássio Dener Noronha Vinhal, Gélson da Cruz Júnior, Matheus Rudolfo Diedrich Ullmann

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Generating automatic image descriptions through natural language is a challenging task. Image captioning is a task that consistently describes an image by combining computer vision and natural language processing techniques. To accomplish this task, cutting-edge models use encoder-decoder structures. Thus, Convolutional Neural Networks (CNN) are used to extract the characteristics of the images, and Recurrent Neural Networks (RNN) generate the descriptive sentences of the images. However, cutting-edge approaches still suffer from problems of generating incorrect captions and accumulating errors in the decoders. To solve this problem, we propose a model based on the encoder-decoder structure, introducing a module that generates the weights according to the importance of the word to form the sentence, using the part-of-speech (PoS). Thus, the results demonstrate that our model surpasses state-of-the-art models.

Keywords: gated recurrent units, caption generation, convolutional neural network, part-of-speech

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Authors: Kingston Rajiah, Mari Kannan Maharajan, Si Jen Yeen, Sara Lew

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Parkinson’s disease (PD) is a progressive neurodegenerative disorder with evolving layers of complexity. Both motor and non-motor symptoms of PD may affect patients’ quality of life (QoL). Life expectancy for an individual with Parkinson’s disease depends on the level of care the individual has access to, can have a direct impact on length of life. Therefore, improvement of the QoL is a significant part of therapeutic plans. Patients with PD, especially those who are in advanced stages, are in great need of assistance, mostly from their family members or caregivers in terms of medical, emotional, and social support. The role of a caregiver becomes increasingly important with the progression of PD, the severity of motor impairment and increasing age of the patient. The nature and symptoms associated with PD can place significant stresses on the caregivers’ burden. As the prevalence of PD is estimated to more than double by 2030, it is important to recognize and alleviate the burden experienced by caregivers. This study focused on the impact of the clinical features on the QoL of PD patients, and of their caregivers. This study included PD patients along with their caregivers and was undertaken at the Malaysian Parkinson's Disease Association from June 2016 to November 2016. Clinical features of PD patients were assessed using the Movement Disorder Society revised Unified Parkinson Disease Rating Scale (MDS-UPDRS); the Hoehn and Yahr Staging of Parkinson's Disease were used to assess the severity and Parkinson's disease activities of daily living scale were used to assess the disability of Parkinson’s disease patients. QoL of PD patients was measured using the Parkinson's Disease Questionnaire-39 (PDQ-39). The revised version of the Zarit Burden Interview assessed caregiver burden. At least one of the clinical features affected PD patients’ QoL, and at least one of the QoL domains affected the caregivers’ burden. Clinical features ‘Saliva and Drooling’, and ‘Dyskinesia’ explained 29% of variance in QoL of PD patients. The QoL domains ‘stigma’, along with ‘emotional wellbeing’ explained 48.6% of variance in caregivers’ burden. Clinical features such as saliva, drooling and dyskinesia affected the QoL of PD patients. The PD patients’ QoL domains such as ‘stigma’ and ‘emotional well-being’ influenced their caregivers’ burden.

Keywords: carers, quality of life, clinical features, Malaysia

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Authors: Naznine Anwar, Kim Cornish, Izelle Labuschagne, Nellie Georgiou-Karistianis

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Falls and subsequent injuries are common features in symptomatic Huntington’s disease (symp-HD) individuals. As part of daily walking, navigating around obstacles may incur a greater risk of falls in symp-HD. We designed obstacle-crossing experiment to examine adaptive gait dynamics and to identify underlying spatiotemporal gait characteristics that could increase the risk of falling in symp-HD. This experiment involved navigating around one or two ground-based obstacles under two conditions (walking while navigating around one obstacle, and walking while navigating around two obstacles). A total of 32 participants were included, 16 symp-HD and 16 healthy controls with age and sex matched. We used a GAITRite electronic walkway to examine the spatiotemporal gait characteristics and inter-trail gait variability when participants walked at their preferable speed. A minimum of six trials were completed which were performed for baseline free walk and also for each and every condition during navigating around the obstacles. For analysis, we separated all walking steps into three phases as approach steps, navigating steps and recovery steps. The mean and inter-trail variability (within participant standard deviation) for each step gait variable was calculated across the six trails. We found symp-HD individuals significantly decreased their gait velocity and step length and increased step duration variability during the navigating steps and recovery steps compared with approach steps. In contrast, HC individuals showed less difference in gait velocity, step time and step length variability from baseline in both respective conditions as well as all three approaches. These findings indicate that increasing spatiotemporal gait variability may be a possible compensatory strategy that is adopted by symp-HD individuals to effectively navigate obstacles during walking. Such findings may offer benefit to clinicians in the development of strategies for HD individuals to improve functional outcomes in the home and hospital based rehabilitation program.

Keywords: Huntington’s disease, gait variables, navigating around obstacle, basal ganglia dysfunction

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Authors: Putri Alya Ramadhani

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This research analysed how women writers represent their beauty in a platform called Magdalene. With the vision “Supporting diversity, empowering minds,” Magdalene is a new media that seeks to represent women's voices rarely heard in mainstream media. This research elaborates further on how women writers, through their writing, use their body politic to subvert patriarchal values. This research used a qualitative method with an explorative design by using text analysis based on the representation theory of Stuart Hall and in-dept-interview with Women Writers in Magdalene. The result illustrated that women writers represent their beauty in Magdalene to subvert body and beauty-representation in mainstream discourse. Furthermore, the authors have identified an identity negotiation as tension from inevitable oppression and power towards and from women’s bodies. In addition, Women Writers showed the power of their bodies through the redefinition of beauty practices and self. Hence, they subvert body dichotomy to redefine body values in society. In conclusion, this study shows various representations of beauty and body that are underrepresented in the mainstream media through the innovative new medium, Magdalena.

Keywords: women writers, beauty-representation, body politic, new media, identity negotiation

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Authors: Caroline Dupre, David Hupin, Christ Goumou, Francois Belan, Frederic Roche, Thomas Celarier, Bienvenu Bongue

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Background: Previous cohorts have been notably criticized for not studying the different type of physical activity and not investigating household activities. The objective of this work was to analyse the relationship between physical activity and cognitive decline in older people living in the community. Impact of type of physical activity on the results has been realised. Methods: The study used data from the longitudinal and observational study , FrèLE (FRagility: Longitudinal Study of Expressions). The collected data included: socio-demographic variables, lifestyle, and health status (frailty, comorbidities, cognitive status, depression). Cognitive decline was assessed by using: Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA). Physical activity was assessed by the Physical Activity Scale for the Elderly (PASE). This tool is structured in three sections: the leisure activity, domestic activity, and professional activity. Logistic regressions and proportional hazards regression models (Cox) were used to estimate the risk of cognitive disorders. Results: At baseline, the prevalence of cognitive disorders was 6.9% according to MMSE. In total, 1167 participants without cognitive disorders were included in the analysis. The mean age was 77.4 years, and 52.1% of the participants were women. After a 2 years long follow-up, we found cognitive disorders on 53 participants (4.5%). Physical activity at baseline is lower in older adults for whom cognitive decline was observed after two years of follow-up. Subclass analyses showed that leisure and domestic activities were associated with cognitive decline, but not professional activities. Conclusions: Analysis showed a relationship between cognitive disorders and type of physical activity. The current study will be completed by the MoCA for mild cognitive impairment. These findings compared to other ongoing studies, will contribute to the debate on the beneficial effects of physical activity on cognition.

Keywords: aging, cognitive function, physical activity, mixed models

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Authors: Sandra Baez, Mariana Pino, Mildred Berrio, Hernando Santamaria-Garcia, Lucas Sedeno, Adolfo Garcia, Sol Fittipaldi, Agustin Ibanez

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Schadenfreude refers to the perceiver’s experience of pleasure at another’s misfortune. This is a multidetermined emotion which can be evoked by hostile feelings and envy. The experience of Schadenfreude engages mechanisms implicated in diverse social cognitive processes. For instance, Schadenfreude involves heightened reward processing, accompanied by increased striatal engagement and it interacts with mentalizing and perspective-taking abilities. Patients with Huntington's disease (HD) exhibit reductions of Schadenfreude experience, suggesting a role of striatal degeneration in such an impairment. However, no study has directly assessed the relationship between regional brain atrophy in HD and reduced Schadenfreude. This study investigated whether gray matter (GM) atrophy in HD patients correlates with ratings of Schadenfreude. First, we compared the performance of 20 HD patients and 23 controls on an experimental task designed to trigger Schadenfreude and envy (another social emotion acting as a control condition). Second, we compared GM volume between groups. Third, we examined brain regions where atrophy might be associated with specific impairments in the patients. Results showed that while both groups showed similar ratings of envy, HD patients reported lower Schadenfreude. The latter pattern was related to atrophy in regions of the reward system (ventral striatum) and the mentalizing network (precuneus and superior parietal lobule). Our results shed light on the intertwining of reward and socioemotional processes in Schadenfreude, while offering novel evidence about their neural correlates. In addition, our results open the door to future studies investigating social emotion processing in other clinical populations characterized by striatal or mentalizing network impairments (e.g., Parkinson’s disease, schizophrenia, autism spectrum disorders).

Keywords: envy, Gray matter atrophy, Huntigton's disease, Schadenfreude, social emotions

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Authors: Ksenia Meshkova

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With increasing amount of multimedia data, it is very important to automate and speed up the process of obtaining meta. This process means not just recognition of some object or its movement, but recognition of the entire scene versus separate frames and having timeline segmentation as a final result. Labeling datasets is time consuming, besides, attributing characteristics to particular scenes is clearly difficult due to their nature. In this article, we will consider autoencoders application to unsupervised scene recognition and clusterization based on interpretable features. Further, we will focus on particular types of auto encoders that relevant to our study. We will take a look at the specificity of deep learning related to information theory and rate-distortion theory and describe the solutions empowering poor interpretability of deep learning in media content processing. As a conclusion, we will present the results of the work of custom framework, based on autoencoders, capable of scene recognition as was deeply studied above, with highlights generation resulted out of this recognition. We will not describe in detail the mathematical description of neural networks work but will clarify the necessary concepts and pay attention to important nuances.

Keywords: neural networks, computer vision, representation learning, autoencoders

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Authors: Su-Lin Yu

Abstract:

In recent years, we have witnessed the growing scholarship on transnational theorizing and activism within disability. In particular, the universalizing discourses of disability formulated in the Global North seem inadequate in engaging the vast diversity of discourses of disability that emerge in global and local policies as well as the everyday experiences of disabled people in the Global South. This study will further consider the future possibilities of how Taiwanese and global disability studies might interchange disability knowledge. First, this study will determine how a local literature of disability can be formed in Taiwan by examining life writings written by Taiwanese disabled women. Both the texts and the personal experiences are treated as social products which can, through their discourses, offer insight into the socio-cultural practices and norms of disability and womanhood in Taiwan. This paper argues that more than by the impairment in itself, the experiences of disabled women are shaped by the social and cultural discourses and practices that define disability and womanhood as well as the normative roles, places, and contexts associated with them. Simultaneous analysis of disability and womanhood exemplifies the way in which disability operates in a complex interaction with the socio-cultural discourses and practices of womanhood, thus producing gender-differentiated disabling obstacles for disabled women. Another purpose of this study is to gain an understanding of the transformative experience of women with disabilities and their perceptions of the self. Designed to provide positive, realistic pictures of the lives of women with disabilities and the social, economic, and political issues they face, their life writings demonstrate how they as disabled women simultaneously struggle with writing a new identity and creating an ethical narrative. These strong and articulate women construct narratives that attempt to recount the remarkable journey that transformed them from dependent women to community activists and writers who speak forcefully about the needs of people with disabilities. More than a story of one woman's struggle for independence, their writing, then, is a testimony to the importance of community building and organizing to enable local people with disabilities to live fulfilling lives.

Keywords: gender, disability, representation, agency

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Authors: Ibrahim Abubakar Mikugi

Abstract:

Nigerian graduates could only be self-employed and marketable if they acquire relevant skills and knowledge for successful establishment in various occupation and gainful employment. Research has shown that entrepreneurship education will be successful through developing individual entrepreneurial attitudes, raising awareness of career options by integrating and inculcating a positive attitude in the mind of students through skill acquisition. This paper examined the student- led entrepreneurship education through skill acquisition with specific emphasis on analysis of David Kolb experiential learning cycle. This Model allows individual to review their experience through reflection and converting ideas into action by doing. The methodology used was theoretical approach through journal, internet and Textbooks. Challenges to entrepreneurship education through skill acquisition were outlined. The paper concludes that entrepreneurship education is recognised by both policy makers and academics; entrepreneurship is more than mere encouraging business start-ups. Recommendations were given which include the need for authorities to have a clear vision towards entrepreneurship education and skill acquisition. Authorities should also emphasise a periodic and appropriate evaluation of entrepreneurship and to also integrate into schools academic curriculum to encourage practical learning by doing.

Keywords: entrepreneurship, entrepreneurship education, active learning, Cefe methodology

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Authors: Gorkem Algan, Ilkay Ulusoy, Saban Gonul, Banu Turgut, Berker Bakbak

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Computer vision systems recently made a big leap thanks to deep neural networks. However, these systems require correctly labeled large datasets in order to be trained properly, which is very difficult to obtain for medical applications. Two main reasons for label noise in medical applications are the high complexity of the data and conflicting opinions of experts. Moreover, medical imaging datasets are commonly tiny, which makes each data very important in learning. As a result, if not handled properly, label noise significantly degrades the performance. Therefore, a label-noise-robust learning algorithm that makes use of the meta-learning paradigm is proposed in this article. The proposed solution is tested on retinopathy of prematurity (ROP) dataset with a very high label noise of 68%. Results show that the proposed algorithm significantly improves the classification algorithm's performance in the presence of noisy labels.

Keywords: deep learning, label noise, robust learning, meta-learning, retinopathy of prematurity

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Authors: Vangelis Drosos, Dimitrios Tsoukalos, Dimitrios Tsolis

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We present a simple algorithm for capturing a 3D scene (focused on the usage of mobile device cameras in the context of augmented/mixed reality) by using a floating origin camera solution and storing the resulting information in a linear voxel octree. Data is derived from cloud points captured by a mobile device camera. For the purposes of this paper, we assume a scene of fixed size (known to us or determined beforehand) and a fixed voxel resolution. The resulting data is stored in a linear voxel octree using a hashtable. We commence by briefly discussing the logic behind floating origin approaches and the usage of linear voxel octrees for efficient storage. Following that, we present the algorithm for translating captured feature points into voxel data in the context of a fixed origin world and storing them. Finally, we discuss potential applications and areas of future development and improvement to the efficiency of our solution.

Keywords: voxel, octree, computer vision, XR, floating origin

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Authors: Kripesh Adhikari, Hamid Bouchachia, Hammadi Nait-Charif

Abstract:

Falls are one of the major causes of injury and death among elderly people aged 65 and above. A support system to identify such kind of abnormal activities have become extremely important with the increase in ageing population. Pose estimation is a challenging task and to add more to this, it is even more challenging when pose estimations are performed on challenging poses that may occur during fall. Location of the body provides a clue where the person is at the time of fall. This paper presents a vision-based tracking strategy where available joints are grouped into three different feature points depending upon the section they are located in the body. The three feature points derived from different joints combinations represents the upper region or head region, mid-region or torso and lower region or leg region. Tracking is always challenging when a motion is involved. Hence the idea is to locate the regions in the body in every frame and consider it as the tracking strategy. Grouping these joints can be beneficial to achieve a stable region for tracking. The location of the body parts provides a crucial information to distinguish normal activities from falls.

Keywords: fall detection, machine learning, deep learning, pose estimation, tracking

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Authors: Afsaneh Mohammadnejad, Marianne Nygaard, Jan Baumbach, Shuxia Li, Weilong Li, Jesper Lund, Jacob v. B. Hjelmborg, Lene Christensen, Qihua Tan

Abstract:

Cognitive impairment in the elderly is a key issue affecting the quality of life. Despite a strong genetic background in cognition, only a limited number of single nucleotide polymorphisms (SNPs) have been found. These explain a small proportion of the genetic component of cognitive function, thus leaving a large proportion unaccounted for. We hypothesize that one reason for this missing heritability is the misspecified modeling in data analysis concerning phenotype distribution as well as the relationship between SNP dosage and the phenotype of interest. In an attempt to overcome these issues, we introduced a model-free method based on the generalized correlation coefficient (GCC) in a genome-wide association study (GWAS) of cognitive function in twin samples and compared its performance with two popular linear regression models. The GCC-based GWAS identified two genome-wide significant (P-value < 5e-8) SNPs; rs2904650 near ZDHHC2 on chromosome 8 and rs111256489 near CD6 on chromosome 11. The kinship model also detected two genome-wide significant SNPs, rs112169253 on chromosome 4 and rs17417920 on chromosome 7, whereas no genome-wide significant SNPs were found by the linear mixed model (LME). Compared to the linear models, more meaningful biological pathways like GABA receptor activation, ion channel transport, neuroactive ligand-receptor interaction, and the renin-angiotensin system were found to be enriched by SNPs from GCC. The GCC model outperformed the linear regression models by identifying more genome-wide significant genetic variants and more meaningful biological pathways related to cognitive function. Moreover, GCC-based GWAS was robust in handling genetically related twin samples, which is an important feature in handling genetic confounding in association studies.

Keywords: cognition, generalized correlation coefficient, GWAS, twins

Procedia PDF Downloads 127