Search results for: deep brain stimulation

Authors: Neeraj Malhotra

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Background: Bioreactors in tissue engineering are used as devices that apply mechanical means to influence biological processes. They are commonly employed for stem cell culturing, growth and expansion as well as in 3D tissue culture. Contemporarily there use is well established and is tested extensively in the medical sciences, for tissue-regeneration and tissue engineering of organs like bone, cartilage, blood vessels, skin grafts, cardiac muscle etc. Methodology: Literature search, both electronic and hand search, was done using the following MeSH and keywords: bioreactors, bioreactors and dentistry, bioreactors & dental tissue engineering, bioreactors and regenerative dentistry. Articles published only in English language were included for review. Results: Bioreactors like, spinner flask-, rotating wall-, flow perfusion-, and micro-bioreactors and in-vivo bioreactor have been employed and tested for the regeneration of dental and like-tissues. These include gingival tissue, periodontal ligament, alveolar bone, mucosa, cementum and blood vessels. Based on their working dynamics they can be customized in future for regeneration of pulp tissue and whole tooth regeneration. Apart from this, they have been successfully used in testing the clinical efficacy and biological safety of dental biomaterials. Conclusion: Bioreactors have potential use in testing dental biomaterials and tissue engineering approaches aimed at regenerative dentistry.

Keywords: bioreactors, biological process, mechanical stimulation, regenerative dentistry, stem cells

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Authors: Zdravko Trivic, John Chye Fung, Ruzica Bozovic-Stamenovic

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Within the context of rapidly ageing population in Singapore and the pressing demands on both caregivers and care providers, an integrated approach to ageing-friendly and ability-sensitive enabling environment becomes an imperative. This particularly applies to nursing home environments and their immediate surroundings, as they are becoming one of the main available options of long-term care for many senior adults who are unable to age at home. Yet, despite the considerable efforts to break the still predominant clinical approach to eldercare and to introduce more home-like design and person-centric care model, nursing homes keep being stigmatised and perceived as not so desirable environments to grow old in. The challenges are further emphasised by the associated physical, sensorial, psychological and cognitive declines that are the common consequences of ageing. Such declines have an immense impact on almost all aspects of older adults’ daily functioning, including problems with mobility and spatial orientation, difficulties in communication, withdrawal from social interaction, higher level of depression and decreased sense of independence and autonomy. However, typical nursing home designs tend to neglect the full capacities of balanced and carefully integrated multisensory stimuli as active component of care and ability building. This paper outlines part of a larger multi-disciplinary study of six nursing homes in Singapore, with overarching objectives to create new models of supportive nursing home environments that go beyond the clinical care model and encourage community integration with the nursing home settings. The paper focuses on the largely neglected aspects of sensorial comfort and multi-sensorial properties of nursing homes, including both indoor and immediate outdoor spaces (boundaries). The objective was to investigate the sensory rhythms and explore their role in nursing home users’ daily routine and therapeutic capacities. Socio-sensory rhythms were captured and analysed through a combination of on-site sensory recordings of “objective” quantitative sensory data (air temperature and humidity, sound level and luminance) using multi-function environment meter, perceived experienced data, spatial mapping, first-person observations of nursing home users’ activity patterns, and interviews. This was done in addition to employment of available assessment tools, such as Wisconsin Person Directed Care assessment tool, Dementia Quality of Life [DQoL] instrument, and Resident Environment Impact Scale [REIS], as these tools address the issues of sensorial experience insufficiently and selectively. Key findings indicate varied levels of sensory comfort, as well as diversity, intensity, and customisation of multi-sensory conditions within different nursing home spaces. Sensory stimulation is typically concentrated in communal living areas of the nursing homes or in the areas that often provide controlled or limited access, including specifically designed sensory rooms and outdoor green spaces (gardens and terraces). Opportunities for sensory stimulation are particularly limited for bed-bound senior residents and within more functional areas, such as corridors. This suggests that the capacities of nursing home designs to provide more diverse and better integrated pleasant sensory conditions as integrated “therapeutic devices” to build nursing home residents’ physical and mental abilities, encourage activity and improve wellbeing are far from exhausted.

Keywords: ageing-supportive environment, enabling design, multi-sensory assessment, nursing home environment

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Authors: Irina M. Kolesnikova, Andrey M. Gaponov, Sergey A. Roumiantsev, Tatiana V. Grigoryeva, Alexander V. Laikov, Alexander V. Shestopalov

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Background. Neuropathy is a common complication of obesity. In this regard, the content of neurotrophins in such patients is of particular interest. Neurotrophins are the proteins that regulate neuron survival and neuroplasticity and include brain-derived neurotrophic factor (BDNF) and nerve growth factor (NGF). However, the risk of complications depends on the metabolic type of obesity. Metabolically unhealthy obesity (MUHO) is associated with a high risk of complications, while this is not the case with metabolically healthy obesity (MHO). Therefore, the aim of our work was to study the effect of the obesity metabolic type on serum neurotrophins levels. Patients, materials, methods. The study included 134 healthy donors and 104 obese patients. Depending on the metabolic type of obesity, the obese patients were divided into subgroups with MHO (n=40) and MUHO (n=55). In the blood serum, the concentration of BDNF and NGF was determined. In addition, the content of adipokines (leptin, asprosin, resistin, adiponectin), myokines (irisin, myostatin, osteocrin), indicators of carbohydrate, and lipid metabolism were measured. Correlation analysis revealed the relationship between the studied parameters. Results. We found that serum BDNF concentration was not different between obese patients and healthy donors, regardless of obesity metabolic type. At the same time, in obese patients, there was a decrease in serum NGF level versus control. A similar trend was characteristic of both MHO and MUHO. However, MUHO patients had a higher NGF level than MHO patients. The literature indicates that obesity is associated with an increase in the plasma concentration of NGF. It can be assumed that in obesity, there is a violation of NGF storage in platelets, which accelerates neurotrophin degradation. We found that BDNF concentration correlated with irisin levels in MUHO patients. Healthy donors had a weak association between NGF and VEGF levels. No such association was found in obese patients, but there was an association between NGF and leptin concentrations. In MHO, the concentration of NHF correlated with the content of leptin, irisin, osteocrin, insulin, and the HOMA-IR index. But in MUHO patients, we found only the relationship between NGF and adipokines (leptin, asprosin). It can be assumed that in patients with MHO, the replenishment of serum NGF occurs under the influence of muscle and adipose tissue. In the MUHO patients only the effect of adipose tissue on NGF was observed. Conclusion. Obesity, regardless of metabolic type, is associated with a decrease in serum NGF concentration. We showed that muscle and adipose tissues make a significant contribution to the serum NGF pool in the MHO patients. In MUHO there is no effect of muscle on the NGF level, but the effect of adipose tissue remains.

Keywords: neurotrophins, nerve growth factor, NGF, brain-derived neurotrophic factor, BDNF, obesity, metabolically healthy obesity, metabolically unhealthy obesity

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Authors: Tarandeep Kaur

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Generation Y and Z nursing students have a much higher need for technology-based stimulation than previous generations, as they may find traditional methods of education boring and disinterested. These generations prefer experiential learning and the use of advanced technology for enhanced learning. Therefore, nursing educators must acquire knowledge to make better use of technology and technological tools for instruction. Millennials and generation are digital natives, optimistic, assertive, want engagement, instant feedback, and collaborative approach. The integration of technology and the efficacy of its use can be challenging for nursing educators. The SAMR (substitution, augmentation, modification, and redefinition) model designed and developed by Dr. Ruben Puentedura can help nursing educators to engage their students in different levels of technology integration for effective learning. Nursing educators should understand that technology use in the classroom must be purposeful. The influx of technology in nursing education is ever-changing; therefore, nursing educators have to constantly enhance and develop technical skills to keep up with the emerging technology in the schools as well as hospitals. In the Saskatchewan Collaborative Bachelor of Nursing (SCBSCN) program at Saskatchewan polytechnic, we use technology at various levels using the SAMR model in our program, including low and high-fidelity simulation labs. We are also exploring futuristic options of using virtual reality and gaming in our classrooms as an innovative way to motivate, increase critical thinking, create active learning, provide immediate feedback, improve student retention and create collaboration.

Keywords: generations, nursing, SAMR, technology

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Authors: Muhammad Faisal Khilji, Rana Shoaib Hamid

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Subdural hematoma (SDH) is an extremely rare complication of immune thrombocytopenic purpura (ITP). We present a case of a 34 years old female who presented to the Emergency department of a tertiary care hospital with complaints of headache, on and off gums bleeding and upper respiratory tract symptoms for the last two weeks. Examination was unremarkable except some purpura over limbs. Investigations revealed zero platelets and peripheral film suggestive of ITP. Computerized tomography (CT) brain revealed bilateral SDH in the frontal areas extending into Falx cerebri. Impression of ITP with SDH was made. Patient was treated with intravenous immunoglobulin (IVIg), methyl prednisolone and initial Platelets transfusion. Patient recovered uneventfully with platelets reaching normal levels within a few days and resolution of SDH without surgery.

Keywords: headache, immune thrombocytopenia, purpura, subdural hematoma

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Authors: Franck Kem Acho

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The trends of diseases have been changed from the last few years, now the burden of non-communicable diseases is increasing day by day. In all the non-communicable diseases, Hypertension is one of the leading causes of premature death and morbidity worldwide. This disease is a silent killer, it mostly affects the people with no obvious symptoms. Not only the heart it also increases the risk of brain, kidney and other diseases, now a days it is a serious medical problem. Over a billion people near about 1 in 4 men and 1 in 5 women having hypertension. In this case study men and women of ages between 30-80 years with Hypertension were identified in community remote area with their Health status being checked and monitored for one week and Health Education was provided for the importance of regular Health checkup alongside the continuous taking of medications.

Keywords: hypertension, health status, health check up, health education

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Authors: Netasha Shaikh, Bryony Wood, Demitra Tsivos, Michael Knight, Risto Kauppinen, Elizabeth Coulthard

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Background: Effective treatment of dementia will require early diagnosis, before significant brain damage has accumulated. Memory loss is an early symptom of Alzheimer’s disease (AD). The hippocampus, a brain area critical for memory, degenerates early in the course of AD. The hippocampus comprises several subfields. In contrast to healthy aging where CA3 and dentate gyrus are the hippocampal subfields with most prominent atrophy, in AD the CA1 and subiculum are thought to be affected early. Conventional clinical structural neuroimaging is not sufficiently sensitive to identify preferential atrophy in individual subfields. Here, we will explore the sensitivity of new magnetic resonance imaging (MRI) sequences designed to interrogate medial temporal regions as an early marker of Alzheimer’s. As it is likely a combination of tests may predict early Alzheimer’s disease (AD) better than any single test, we look at the potential efficacy of such imaging alone and in combination with standard and novel cognitive tasks of hippocampal dependent memory. Methods: 20 patients with mild cognitive impairment (MCI), 20 with mild-moderate AD and 20 age-matched healthy elderly controls (HC) are being recruited to undergo 3T MRI (with sequences designed to allow volumetric analysis of hippocampal subfields) and a battery of cognitive tasks (including Paired Associative Learning from CANTAB, Hopkins Verbal Learning Test and a novel hippocampal-dependent abstract word memory task). AD participants and healthy controls are being tested just once whereas patients with MCI will be tested twice a year apart. We will compare subfield size between groups and correlate subfield size with cognitive performance on our tasks. In the MCI group, we will explore the relationship between subfield volume, cognitive test performance and deterioration in clinical condition over a year. Results: Preliminary data (currently on 16 participants: 2 AD; 4 MCI; 9 HC) have revealed subfield size differences between subject groups. Patients with AD perform with less accuracy on tasks of hippocampal-dependent memory, and MCI patient performance and reaction times also differ from healthy controls. With further testing, we hope to delineate how subfield-specific atrophy corresponds with changes in cognitive function, and characterise how this progresses over the time course of the disease. Conclusion: Novel sequences on a MRI scanner such as those in route in clinical use can be used to delineate hippocampal subfields in patients with and without dementia. Preliminary data suggest that such subfield analysis, perhaps in combination with cognitive tasks, may be an early marker of AD.

Keywords: Alzheimer's disease, dementia, memory, cognition, hippocampus

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Authors: G. Nadirova, B. Aktaulova

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The main question of the research is- how did the Kazakhs manage to keep their religious thinking in the period of active propaganda of Soviet atheism, for seventy years of struggle against religion with the involvement of the scientific worldview as the primary means of proving the absence of the divine nature and materiality of the world? Our hypothesis is that In case of Kazakhstan the conservative female religious consciousness seems to have been a factor that helped to preserve the “everyday” religiousness of Kazakhs, which was far from deep theological contents of Islam, but able to revive in a short time after the decennia of proclaimed atheism.

Keywords: woman, religious thinking, Kazakhstan, soviet ideology, rituals, family

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Authors: Youtao Gao, Bingyu Jin, Tanran Zhao, Bo Xu

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The history of satellite navigation can be dated back to the 1960s. From the U.S. Transit system and the Russian Tsikada system to the modern Global Positioning System (GPS) and the Globalnaya Navigatsionnaya Sputnikovaya Sistema (GLONASS), performance of satellite navigation has been greatly improved. Nowadays, the navigation accuracy and coverage of these existing systems have already fully fulfilled the requirement of near-Earth users, but these systems are still beyond the reach of deep space targets. Due to the renewed interest in space exploration, a novel high-precision satellite navigation system is becoming even more important. The increasing demand for such a deep space navigation system has contributed to the emergence of a variety of new constellation architectures, such as the Lunar Global Positioning System. Apart from a Walker constellation which is similar to the one adopted by GPS on Earth, a novel constellation architecture which consists of libration point satellites in the Earth-Moon system is also available to construct the lunar navigation system, which can be called accordingly, the libration point satellite navigation system. The concept of using Earth-Moon libration point satellites for lunar navigation was first proposed by Farquhar and then followed by many other researchers. Moreover, due to the special characteristics of Libration point orbits, an autonomous orbit determination technique, which is called ‘Liaison navigation’, can be adopted by the libration point satellites. Using only scalar satellite-to-satellite tracking data, both the orbits of the user and libration point satellites can be determined autonomously. In this way, the extensive Earth-based tracking measurement can be eliminated, and an autonomous satellite navigation system can be developed for future space exploration missions. The method of state estimate is an unnegligible factor which impacts on the orbit determination accuracy besides type of orbit, initial state accuracy and measurement accuracy. We apply the extended Kalman filter(EKF) and the unscented Kalman filter(UKF) to determinate the orbits of Lagrangian navigation satellites. The autonomous orbit determination errors are compared. The simulation results illustrate that UKF can improve the accuracy and z-axis convergence to some extent.

Keywords: extended Kalman filter, autonomous orbit determination, unscented Kalman filter, navigation constellation

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Authors: Ana Miguel

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Purpose: Glaucoma is the second cause of worldwide blindness and the first cause of irreversible blindness. Trabeculectomy, the standard glaucoma surgery, has a success rate between 36.0% and 98.0% at three years and a high complication rate, leading to the development of different surgeries, micro-invasive glaucoma surgeries (MIGS). MIGS devices are diverse and have various indications, risks, and effectiveness. We intended to review MIGS’ surgical techniques, indications, contra-indications, and IOP effect. Methods: We performed a literature review of MIGS to differentiate the devices and their reported effectiveness compared to traditional surgery (tubes and blebs). We also conducted a video review of the last 1000 glaucoma surgeries of the author (including MIGS, but also trabeculectomy, deep sclerectomy, and tubes of Ahmed and Baerveldt) performed at glaucoma and advanced anterior segment fellowship in Canada and France, to describe preferred surgical techniques for each. Results: We present the videos with surgical techniques and pearls for each surgery. Glaucoma surgeries included: 1- bleb surgery (namely trabeculectomy, with releasable sutures or with slip knots, deep sclerectomy, Ahmed valve, Baerveldt tube), 2- MIGS with bleb, also known as MIBS (including XEN 45, XEN 63, and Preserflo), 3- MIGS increasing supra-choroidal flow (iStar), 4-MIGS increasing trabecular flow (iStent, gonioscopy-assisted transluminal trabeculotomy - GATT, goniotomy, excimer laser trabeculostomy -ELT), and 5-MIGS decreasing aqueous humor production (endocyclophotocoagulation, ECP). There was also needling (ab interno and ab externo) performed at the operating room and irido-zonulo-hyaloïdectomy (IZHV). Each technique had different indications and contra-indications. Conclusion: MIGS are valuable in glaucoma surgery, such as traditional surgery with trabeculectomy and tubes. All glaucoma surgery can be combined with phacoemulsification (there may be a synergistic effect on MIGS + cataract surgery). In addition, some MIGS may be combined for further intraocular pressure lowering effect (for example, iStents with goniotomy and ECP). A good surgical technique and postoperative management are fundamental to increasing success and good practice in all glaucoma surgery.

Keywords: glaucoma, migs, surgery, video, review

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Authors: Thuy Hanh Nguyen Thi

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Since 1940, existentialism has penetrated into China and continued to profoundly influence contemporary Chinese literature. By the method of deep reading and text analysis, this article analyzes the existential feeling in Yan Lianke’s novels through various aspects: the Sisyphus senses, the narrative rationalization and the viewpoint of the dead. In addition to pointing out the characteristics of the existential sensation in the writer’s novels, the analysis of the article also provides an insight into the nature and depth of contemporary Chinese society.

Keywords: Yan Lianke, existentialism, the existential feeling, contemporary Chinese literature

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Authors: Ching-Yuan Huang, Rhay-Hung Weng, Yi-Ting Chen

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Mentoring functions will improve new nurses' job performance, provide support with new nurses, and then reduce the turnover rate of them. This study explored the impact of transformational leadership and interpersonal interaction on mentoring functions. We employed a questionnaire survey to collect data and selected a sample of new nurses from three hospitals in Taiwan. A total of 306 valid surveys were obtained. Multiple regression model analysis was conducted to test the study hypothesis. Inspirational motivation, idealized influence, and individualized consideration had a positive influence on overall mentoring function, but intellectual stimulation had a positive influence on career development function only. Perceived similarity and interaction frequency also had positive influences on mentoring functions. When the shift overlap rate exceeded 80%, mentoring function experienced a negative result. The transformational leadership of mentors actually would improve the mentoring functions among new staff nurses. Perceived similarity and interaction frequency between mentees and mentors also had a positive influence on mentoring functions. Managers should enhance the transformational leadership of mentors by designing leadership training and motivation programs. Furthermore, nursing managers should promote the interaction between new staff nurses and their mentors, but the shift overlap rate should not exceed 80%.

Keywords: interpersonal interaction, mentoring function, mentor, new nurse, transformational leadership

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Authors: Damian Janecki, Anna Jaskólska, Jarosław Marusiak, Artur Jaskólski

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The aim of this study was to assess double to single twitch ratio after two bouts of eccentric exercise of the elbow flexors. Maximal isometric torque, single and double twitch responses and low-frequency fatigue were assessed on the elbow flexors in 19 untrained male volunteers before, immediately after, 24 and 48 hours following two bouts of eccentric exercise consisted of 30 repetitions of lowering a dumbbell adjusted to ~75% of each individual's maximal isometric torque. Maximal isometric torque and electrically evoked responses decreased significantly in all measurements after the first bout of eccentric exercise (P<0.05). In measurements performed at 24 and 48 hours after the second bout both maximal voluntary isometric torque and electrically evoked contractions were significantly higher than in measurements performed after the fist bout (P<0.05). Although low-frequency fatigue significantly increased up to 48 hours after each bout of eccentric exercise, its values at 24 and 48 hours after the second bout were significantly lower than at respective time points after the first bout (P<0.05). Smaller changes in double to single twitch ratio at 24 and 48 hours after the second bout of eccentric exercise reflects repeated bout effect that confers protection against subsequent exercise-induced muscle damage.

Keywords: biceps brachii, electrical stimulation, lenghtening contractions, repeated bout effect

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Authors: Xabier Olaz Moratinos

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Drone navigation is critical, particularly during the initial phases, such as the initial ascension, where pilots may fail due to strong external interferences that could potentially lead to a crash. In this ongoing work, a drone has been successfully trained to perform an ascent of up to 6 meters at speeds with external disturbances pushing it up to 24 mph, with the DQN algorithm managing external forces affecting the system. It has been demonstrated that the system can control its height, position, and stability in all three axes (roll, pitch, and yaw) throughout the process. The learning process is carried out in the Gazebo simulator, which emulates interferences, while ROS is used to communicate with the agent.

Keywords: machine learning, DQN, Gazebo, navigation

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Authors: Alina Muradyan, Lina Babayan, Arsen Nanyan, Gohar Galstyan, Vigen Khachatryan

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We present a photometric method for identifying stars, galaxies and quasars in multi-color surveys, which uses a library of ∼> 65000 color templates for comparison with observed objects. The method aims for extracting the information content of object colors in a statistically correct way, and performs a classification as well as a redshift estimation for galaxies and quasars in a unified approach based on the same probability density functions. For the redshift estimation, we employ an advanced version of the Minimum Error Variance estimator which determines the redshift error from the redshift dependent probability density function itself. The method was originally developed for the Calar Alto Deep Imaging Survey (CADIS), but is now used in a wide variety of survey projects. We checked its performance by spectroscopy of CADIS objects, where the method provides high reliability (6 errors among 151 objects with R < 24), especially for the quasar selection, and redshifts accurate within σz ≈ 0.03 for galaxies and σz ≈ 0.1 for quasars. For an optimization of future survey efforts, a few model surveys are compared, which are designed to use the same total amount of telescope time but different sets of broad-band and medium-band filters. Their performance is investigated by Monte-Carlo simulations as well as by analytic evaluation in terms of classification and redshift estimation. If photon noise were the only error source, broad-band surveys and medium-band surveys should perform equally well, as long as they provide the same spectral coverage. In practice, medium-band surveys show superior performance due to their higher tolerance for calibration errors and cosmic variance. Finally, we discuss the relevance of color calibration and derive important conclusions for the issues of library design and choice of filters. The calibration accuracy poses strong constraints on an accurate classification, which are most critical for surveys with few, broad and deeply exposed filters, but less severe for surveys with many, narrow and less deep filters.

Keywords: VO, ArVO, DFBS, FITS, image processing, data analysis

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Authors: So Youn Park, Yi Sle Lee, Ki Whan Hong, Chi Dae Kim

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The role of metabolism in the pathogenesis of osteoarthritis is an emerging field. Metabolic alterations may be a role in osteoarthritis (OA) pathogenesis, and these changes influence joint destruction via several cytokine. Especially, in OA patients, levels of IL-1β are elevated in the synovial fluid, synovial membrane, subchondral bone, and cartilage. The IL-1β is activated by NLRP3 inflammasomes, and NLRP3 inflammasomes are cytosolic complexes that drive the production of other inflammatory cytokines, including IL-1β. In this study, we examined that SIRT1 suppresses IL-1β through inhibiting NLRP3 inflammasomes and SIRT1 ameliorates osteoarthritis. OA fibroblasts were isolated from synovium of OA patients. IL-1β and NLRP3 were detected in synovium of OA patients by immunohistochemistry. Lipopolysaccharides (LPS) stimulated the expression of active IL-1β mRNA in OA fibroblasts and combination of LPS, and adenosine triphosphate increased more the expression of active IL-1β in OA fibroblasts. The level of IL-1β was measured by western blot and ELISA assay. NLRP3 inflammasomes complex were measured by western blot. SIRT1 did not inhibit expression of NLRP3 inflammasome. So caspase-1, apoptotic speck-like protein containing a caspase recruitment domain (ASC) and NLRP3 protein were expressed in OA fibroblasts. But SIRT1 suppressed activation of IL-1β by inhibiting activity of caspase-1 via NLRP3 inflammasome in OA fibroblasts under LPS plus ATP stimulation. These results suggest that SIRT1 is a modulator of NLRP3 inflammasomes in OA fibroblasts and ameliorate IL-1β, so expression of SIRT1 in OA fibroblast may be a potential strategy for OA inflammation treatment.

Keywords: osteoarthritis, inflammasome, SIRT1, IL-1beta

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Authors: Fakhrosadat Sajjadian

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The majority of deaths in cancer patients are caused by distant metastasis. Breast cancer shows a unique spread pattern, often affecting bone, liver, lung, and brain. Breast cancer can be categorized into various subtypes according to gene expression patterns, and these subtypes exhibit specific preferences for organs where metastasis occurs. Breast tumors with luminal characteristics have a preference for spreading to the bone, whereas basal-like breast cancer (BLBC) shows a tendency to metastasize to the lungs. Still, the mechanisms behind this particular pattern of metastasis in organs have yet to be fully understood. In this evaluation, we will outline the latest progress in molecular signaling pathways and treatment methods for breast cancer lung metastasis.

Keywords: lung cancer, liver cancer, diagnosis, BLBC, metastasis

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Authors: Dhanuj M. Gandikota

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Sensor-derived three-dimensional (3D) point clouds of trees are invaluable in remote sensing analysis for the accurate measurement of key structural metrics, bio-inventory values, spatial planning/visualization, and ecological modeling. Machine learning (ML) holds the potential in addressing the restrictive tradeoffs in cost, spatial coverage, resolution, and information gain that exist in current point cloud sensing methods. Terrestrial laser scanning (TLS) remains the highest fidelity source of both canopy and below-canopy structural features, but usage is limited in both coverage and cost, requiring manual deployment to map out large, forested areas. While aerial laser scanning (ALS) remains a reliable avenue of LIDAR active remote sensing, ALS is also cost-restrictive in deployment methods. Space-borne photogrammetry from high-resolution satellite constellations is an avenue of passive remote sensing with promising viability in research for the accurate construction of vegetation 3-D point clouds. It provides both the lowest comparative cost and the largest spatial coverage across remote sensing methods. However, both space-borne photogrammetry and ALS demonstrate technical limitations in the capture of valuable below-canopy point cloud data. Looking to minimize these tradeoffs, we explored a class of powerful ML algorithms called Deep Learning (DL) that show promise in recent research on 3-D point cloud reconstruction and interpolation. Our research details the efficacy of applying these DL techniques to reconstruct accurate below-canopy point clouds from space-borne and aerial remote sensing through learned patterns of tree species fractal symmetry properties and the supplementation of locally sourced bio-inventory metrics. From our dataset, consisting of tree point clouds obtained from TLS, we deconstructed the point clouds of each tree into those that would be obtained through ALS and satellite photogrammetry of varying resolutions. We fed this ALS/satellite point cloud dataset, along with the simulated local bio-inventory metrics, into the DL point cloud reconstruction architectures to generate the full 3-D tree point clouds (the truth values are denoted by the full TLS tree point clouds containing the below-canopy information). Point cloud reconstruction accuracy was validated both through the measurement of error from the original TLS point clouds as well as the error of extraction of key structural metrics, such as crown base height, diameter above root crown, and leaf/wood volume. The results of this research additionally demonstrate the supplemental performance gain of using minimum locally sourced bio-inventory metric information as an input in ML systems to reach specified accuracy thresholds of tree point cloud reconstruction. This research provides insight into methods for the rapid, cost-effective, and accurate construction of below-canopy tree 3-D point clouds, as well as the supported potential of ML and DL to learn complex, unmodeled patterns of fractal tree growth symmetry.

Keywords: deep learning, machine learning, satellite, photogrammetry, aerial laser scanning, terrestrial laser scanning, point cloud, fractal symmetry

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Authors: Ravid Inbar

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CaMKII (calcium-calmodulin dependent protein kinase II) makes up 2% of the protein in our brain and has a critical role in memory formation and long-term potentiation of neurons. Despite this, research has yet to uncover the role of one of the domains on the activation of this kinase. The following proposes to express the protein without the hub domain in E. coli, leaving only the kinase and regulatory segment of the protein. Next, a series of kinase assays will be conducted to elucidate the role the hub domain plays on CaMKII sensitivity to calcium/calmodulin activation. The hub domain may be important for activation; however, it may also be a variety of domains working together to influence protein activation and not the hub alone. Characterization of a protein is critical to the future understanding of the protein's function, as well as for producing pharmacological targets in cases of patients with diseases.

Keywords: CaMKII, hub domain, kinase assays, kinase + reg seg

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Authors: Priyanka Gupta, Nilanjana Bairagi, Deepti Gupta

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New pathogenic strains of microbes are continually emerging and resistance of bacteria to antibiotics is growing. Hospitals in India have a high burden of infections in their intensive care units and general wards. Rising incidence of hospital infections is a matter of great concern in India. This growth is often attributed to the absence of effective infection control strategies in healthcare facilities. Government, therefore, is looking for cost effective strategies that are effective against HAIs. One possible method is by application of an antimicrobial finish on the uniform. But there are limited studies to show the effect of antimicrobial activity of antimicrobial finish treated nurses’ uniforms in a real hospital set up. This paper proposes a prospective non-destructive sampling technique, based on the use of a detachable fabric patch, to assess the effectiveness of silver based antimicrobial agent across five wards in a tertiary care government hospital in Delhi, India. Fabrics like polyester and polyester cotton blend fabric which are more prevalent for making coats were selected for the study. Polyester and polyester cotton blend fabric was treated with silver based antimicrobial (AM) finish. At the beginning of shift, a composite patch of untreated and treated fabric respectively was stitched on the abdominal region on the left and right side of the washed white coat of participating nurse. At the end of the shift, the patch was removed and taken for bacterial sampling on Brain Heart Infusion (BHI) plates. Microbial contamination on polyester and blend fabrics after 6 hours shift was compared in Brain Heart Infusion broth (BHI). All patches treated with silver based antimicrobial agent showed decreased bacterial counts. Percent reduction in the bacterial colonies after the antimicrobial treatment in both fabrics was 81.0 %. Antimicrobial finish was equally effective in reducing microbial adhesion on both fabric types. White coats of nurses become progressively contaminated during clinical care. Type of fabric used to make the coat can affect the extent of contamination which is higher on polyester cotton blend as compared to 100% polyester. The study highlights the importance of silver based antimicrobial finish in the area of uniform hygiene. Bacterial load can be reduced by using antimicrobial finish on hospital uniforms. Hospital staff uniforms endowed with antimicrobial properties may be of great help in reducing the occurrence and spread of infections.

Keywords: antimicrobial finish, bacteria, infection control, silver, white coat

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Authors: Raed KOUTA, José-Alcebiades-Ernesto HLUNGUANE, Eric Châtele

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The search for and exploitation of new fossil energy resources is taking place in the context of the gradual depletion of existing deposits. Despite the adoption of international targets to combat global warming, the demand for fuels continues to grow, contradicting the movement towards an energy-efficient society. The increase in the share of offshore in global hydrocarbon production tends to compensate for the depletion of terrestrial reserves, thus constituting a major challenge for the players in the sector. Through the economic potential it represents, and the energy independence it provides, offshore exploitation is also a challenge for States such as Mozambique, which have large maritime areas and whose environmental wealth must be considered. The exploitation of new reserves on economically viable terms depends on available technologies. The development of deep and ultra-deep offshore requires significant research and development efforts. Progress has also been made in managing the multiple risks inherent in this activity. Our study proposes a reliability approach to develop products and processes designed to live at sea. Indeed, the context of an offshore platform requires highly reliable solutions to overcome the difficulties of access to the system for regular maintenance and quick repairs and which must resist deterioration and degradation processes. One of the characteristics of failures that we consider is the actual conditions of use that are considered 'extreme.' These conditions depend on time and the interactions between the different causes. These are the two factors that give the degradation process its dynamic character, hence the need to develop dynamic reliability models. Our work highlights mathematical models that can explicitly manage interactions between components and process variables. These models are accompanied by numerical resolution methods that help to structure a dynamic reliability approach in a physical and probabilistic context. The application developed makes it possible to evaluate the reliability, availability, and maintainability of a floating storage and unloading platform for liquefied natural gas production.

Keywords: dynamic reliability, offshore plateform, stochastic process, uncertainties

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Authors: Yulistiani Yulistiani, Zamrotul Izzah, Lintang Bismantara, Wenny Putri Nilamsari, Arif Bachtiar, Budi Suprapti

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Interferon-gamma (IFN-γ) and interleukin-6 (IL-6) are pro-inflammatory cytokines, which have the protective immune response against Tuberculosis (TB). Indeed, pro-inflammatory cytokines Mycobacterium tuberculosis antigen-specific CD4+ and CD8+ T cells and NK cells increase the level of production of IFN-γ, a cytokine critical for augmenting the microbicidal activity of phagocytes. On the other hand, M. tuberculosis reduces the effects of IFN-γ by inhibiting the transcription of IFN-γ- responsive genes and by inducing the secretion of IL-6, which inhibits IFN-γ signaling. Probiotics Lactobacillus sp. and Bifidobacterium sp. were known to increase IFN-γ production in vivo, while vitamin B1, B6, and B12 worked on macrophages and releasing cytokines. Therefore, the present study was to evaluate the effect of probiotics and vitamin B supplement on changes of plasma cytokine levels in active pulmonary TB. From October to November 2016, twelve M. tuberculosis-infected patients starting anti-TB drugs were recruited, then divided into two groups. Seven patients were given a combination of probiotics and vitamin B, while five patients were in the control group. Plasma IFN-γ and IL-6 levels were measured by the ELISA kit before and a month after treatment. IFN-γ levels raised in four patients receiving the supplement (P = 0.743), while IL-6 increased in three patients in this group until day 30 of treatment (P = 0.298). Taken together, these results show the promising effect of probiotics and vitamin B on stimulation of IFN-γ and IL-6 production during intensive therapy of TB.

Keywords: interferon-gamma, interleukin-6, probiotic, tuberculosis

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Authors: Muhammad Imran Hussain, Ramisha Ibtisam, Tayyaba Fatima, Huba Khalid, Ayesha Aziz, Khansa, Adan Sitara, Anam Shahzad, Aymen Jabeen

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Vitamin D supports the immune system fight TB by inhibiting Interferon-gamma (IFN-γ) and lowering host inflammation. The purpose of the research was to see if giving the vitamin D supplements to TB patients affected their prognosis. A randomized placebo control study of 200 TB patients was performed among which 106 received 400,000 IU of injectable vitamin D3 and 94 received placebo for 2 doses. Assessment was carried out at the end of every month for 3 months. IFN-γ responses to whole blood stimulation generated by the Mycobacterium tuberculosis sonicate (MTBs) antigen and early secreted and T cell activated 6 kDa (ESAT6) were assessed at 0 and 12 weeks. The statistical analysis used descriptive statistics (mean and standard deviation), Friedman's test and Fisher's test. The vitamin D group gained significantly more weight (+3.90 pounds) and had less persistent lung disease on imaging (1.33 zones vs. 1.84 zones). They also had a 50% decrease in cavity size. Additionally, patients with low baseline serum concentrations of 25-(OH)D had a significant increase in MTB-induced IFN-γ production after taking vitamin D supplements. Vitamin D administration in large amounts can hasten the recovery of TB patients. The findings point is a therapeutically useful activity of Vitamin D's in the management for tuberculosis.

Keywords: tuberculosis, vitamin D, interferon gamma, protein, infection

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Authors: Natalia Espinosa, Arthur Amorim, Rudolf Huebner

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Epilepsy is a chronic neural disease and around 50 million people in the world suffer from this disease, however, in many cases, the individual acquires resistance to the medication, which is known as drug-resistant epilepsy, where a detection system is necessary. This paper showed the development of an automatic system for seizure detection based on artificial neural networks (ANN), which are common techniques of machine learning. Discrete Wavelet Transform (DWT) is used for decomposing electroencephalogram (EEG) signal into main brain waves, with these frequency bands is extracted features for training a feedforward neural network with backpropagation, finally made a pattern classification, seizure or non-seizure. Obtaining 95% accuracy in epileptic EEG and 100% in normal EEG.

Keywords: Artificial Neural Network (ANN), Discrete Wavelet Transform (DWT), Epilepsy Detection , Seizure.

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Authors: Denis Jordan, Daniel Golkowski, Mathias Lukas, Katharina Merz, Caroline Mlynarcik, Max Maurer, Valentin Riedl, Stefan Foerster, Eberhard F. Kochs, Andreas Bender, Ruediger Ilg

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Introduction: So far, clinical assessments that rely on behavioral responses to differentiate coma states or even predict outcome in coma patients are unreliable, e.g. because of some patients’ motor disabilities. The present study was aimed to provide prognosis in coma patients using markers from electroencephalogram (EEG), blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) and [18F]-fluorodeoxyglucose (FDG) positron emission tomography (PET). Unsuperwised principal component analysis (PCA) was used for multimodal integration of markers. Methods: Approved by the local ethics committee of the Technical University of Munich (Germany) 20 patients (aged 18-89) with severe brain damage were acquired through intensive care units at the Klinikum rechts der Isar in Munich and at the Therapiezentrum Burgau (Germany). At the day of EEG/fMRI/PET measurement (date I) patients (<3.5 month in coma) were grouped in the minimal conscious state (MCS) or vegetative state (VS) on the basis of their clinical presentation (coma recovery scale-revised, CRS-R). Follow-up assessment (date II) was also based on CRS-R in a period of 8 to 24 month after date I. At date I, 63 channel EEG (Brain Products, Gilching, Germany) was recorded outside the scanner, and subsequently simultaneous FDG-PET/fMRI was acquired on an integrated Siemens Biograph mMR 3T scanner (Siemens Healthineers, Erlangen Germany). Power spectral densities, permutation entropy (PE) and symbolic transfer entropy (STE) were calculated in/between frontal, temporal, parietal and occipital EEG channels. PE and STE are based on symbolic time series analysis and were already introduced as robust markers separating wakefulness from unconsciousness in EEG during general anesthesia. While PE quantifies the regularity structure of the neighboring order of signal values (a surrogate of cortical information processing), STE reflects information transfer between two signals (a surrogate of directed connectivity in cortical networks). fMRI was carried out using SPM12 (Wellcome Trust Center for Neuroimaging, University of London, UK). Functional images were realigned, segmented, normalized and smoothed. PET was acquired for 45 minutes in list-mode. For absolute quantification of brain’s glucose consumption rate in FDG-PET, kinetic modelling was performed with Patlak’s plot method. BOLD signal intensity in fMRI and glucose uptake in PET was calculated in 8 distinct cortical areas. PCA was performed over all markers from EEG/fMRI/PET. Prognosis (persistent VS and deceased patients vs. recovery to MCS/awake from date I to date II) was evaluated using the area under the curve (AUC) including bootstrap confidence intervals (CI, *: p<0.05). Results: Prognosis was reliably indicated by the first component of PCA (AUC=0.99*, CI=0.92-1.00) showing a higher AUC when compared to the best single markers (EEG: AUC<0.96*, fMRI: AUC<0.86*, PET: AUC<0.60). CRS-R did not show prediction (AUC=0.51, CI=0.29-0.78). Conclusion: In a multimodal analysis of EEG/fMRI/PET in coma patients, PCA lead to a reliable prognosis. The impact of this result is evident, as clinical estimates of prognosis are inapt at time and could be supported by quantitative biomarkers from EEG, fMRI and PET. Due to the small sample size, further investigations are required, in particular allowing superwised learning instead of the basic approach of unsuperwised PCA.

Keywords: coma states and prognosis, electroencephalogram, entropy, functional magnetic resonance imaging, machine learning, positron emission tomography, principal component analysis

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Authors: K. Julia Rose Mary, Victor Arokia Doss

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Electrical and chemical stimulations up-regulate phosphorylaion of CREB, a transcriptional factor that induces its target gene production for memory consolidation and Late Long-Term Potentiation (L-LTP) in CA1 region of the hippocampus. L-LTP requires complex interactions among second-messenger signaling cascade molecules such as cAMP, CAMKII, CAMKIV, MAPK, RSK, PKA, all of which converge to phosphorylate CREB which along with CBP induces the transcription of target genes involved in memory consolidation. A differential equation based model for L-LTP representing stimulus-mediated activation of downstream mediators which confirms the steep, supralinear stimulus-response effects of activation and inhibition was used. The same was extended to accommodate the inhibitory effect of the Inducible cAMP Early Repressor (ICER). ICER is the natural inducible CREB antagonist represses CRE-Mediated gene transcription involved in long-term plasticity for learning and memory. After verifying the sensitivity and robustness of the model, we had simulated it with various empirical levels of repressor concentration to analyse their effect on the gene induction. The model appears to predict the regulatory dynamics of repression on the L-LTP and agrees with the experimental values. The flux data obtained in the simulations demonstrate various aspects of equilibrium between the gene induction and repression.

Keywords: CREB, L-LTP, mathematical modeling, simulation

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Authors: Fagner Luiz P. Salles, Janaina C. Oliveira, Ivair P. Cesar

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Statement of the Problem: Auriculotherapy (AT) is a TCM technique, which uses seeds instead of needles, based physiologically on the mechanical stimulation of the cranial nerves. In the context of understanding the new concept of health of the WHO, the AT is an integrative approach for achieving Global Health Care so as to achieve the global health care concerns. This study aimed to evaluate the effect of auriculotherapy on pain and sleep quality in patients with chronic pain. Methodology and Theoretical Orientation: This study was performed between February and March 2017 at the Faculdade Estácio de Sá de Vitória, Brazil. The pain evaluation was through VAS in 4 periods: maximum, minimum, average and at the time of evaluation; the evaluation of sleep quality was used the Pittsburgh Sleep Quality Index. Socio-demographic data included: gender, age, use of medication and BMI. All data are presented as mean (standard deviation), Teste Mann-Whitney and T-student with P-values < 0.05 were regarded as significant. Findings: Participated in this study thirty-two individuals with age (M = 43.18, SD = 17.86), the time with pain in years (M = 3.67, SD = 3.68), 81.7% were female, 75% of the individuals used medication and BMI (M = 26.67; SD = 6.20). The pain presented improvement in the maximum level and the average of the pain and sleep quality before did not have statistically significant results. Conclusion and Significance: This study showed that TA is efficacy for reduction levels of pain. However, AT was not effective in improving sleep quality.

Keywords: auriculotherapy, chronic pain, sleep quality, integrative approach

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Authors: Rajish Shil, Amal Alduhoori, Vipin Thomachan, Jamal Teir, Radhakrishnan Renganathan

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Background: Antiphospholipid antibody syndrome (APS) has a broad spectrum of thrombotic and non-thrombotic clinical manifestations. We present a case of APS presenting with seizure, stroke, and atrial mass. Case Description: A 38-year-old male presented with headache of 10 days duration and tonic-clonic seizure. The neurological examination was normal. Magnetic resonance imaging of brain showed small acute right cerebellar infarct. Magnetic resonance angiography of brain and neck showed a focal narrowing in the origin of the internal carotid artery bilaterally. Electroencephalogram was normal. He was started on aspirin, atorvastatin, and carbamazepine. Transthoracic and trans-esophageal echocardiography showed a pedunculated and lobular atrial mass, measuring 1 X 1.5 cm, which was freely mobile across mitral valve opening across the left ventricular inflow. Autoimmune screening showed positive Antiphospholipid antibodies in high titer (Cardiolipin IgG > 120 units/ml, B2 glycoprotein IgG 90 units/mL). Anti-nuclear antibody was negative. Erythrocyte sedimentation rate and C-reactive protein levels were normal. Platelet count was low (111 x 109/L). The patient underwent successful surgical removal of the mass, which looked like a thrombotic clot, and Histopathological analysis confirmed it as a fibrinous clot, with no evidence of tumor cells. The patient was started on full anticoagulation treatment and was followed up regularly in the clinic, where our patient did not have any further complications from the disease. Discussion: Our patient was diagnosed to have APS based on the features of high positive anticardiolipin antibody IgG and B2 glycoprotein IgG levels, Stroke, thrombocytopenia, and abnormal echo findings. Thrombotic vegetation can mimic an atrial myxoma on echo. Conclusion: APS can present with neurological and cardiac manifestations, and therefore a high index of suspicion is necessary for a diagnosis of the disease as it can affect both short and long term treatment plans and prognosis. Therefore, in patients presenting with neurological symptoms like seizures, weakness and radiological diagnosis of stroke in a young patient, where atrial masses could be thought to be the cause of stroke, they should be screened for any concomitant findings of thrombocytopenia and/or activated partial thromboplastin time prolongation, which should raise the suspicion of vasculitis, specifically APS to be the primary cause of the clinical presentation.

Keywords: antiphospholipid syndrome, seizures, atrial mass, stroke

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Authors: Metin Kömsöken, Ayşe Güneş Tanır, Onur Karaman

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Usage of high energy charged particles for diagnosis and treatment has been widespread in medicine. The main purpose is to investigate that Bremsstrahlung which occurs by tissue interactions with charged particles should not be neglected. Nuclear stopping power (Bremsstrahlung) was calculated for lung, brain, skin, muscle, bone (cortical) and water targets for the energies of electrons obtained from LINAC used in radiotherapy and of β+ sources used in positron emission tomography (PET). These calculations were done by using the four different analytical functions including classical Bethe-Bloch, Tsoulfanidis, modified Bethe-Bloch and modified Tsoulfanidis equations. It was concluded that obtained results were compatible with that of National Institute of Standards and Technology (NIST-ESTAR).

Keywords: β- emitting source, bremsstrahlung, therapeutic radionuclides, LINAC

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Authors: Armin Nabaei, M. Omair Ahmad, M. N. S. Swamy

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Many facial expression and emotion recognition methods in the traditional approaches of using LDA, PCA, and EBGM have been proposed. In recent years deep learning models have provided a unique platform addressing by automatically extracting the features for the detection of facial expression and emotions. However, deep networks require large training datasets to extract automatic features effectively. In this work, we propose an efficient emotion detection algorithm using face images when only small datasets are available for training. We design a deep network whose feature extraction capability is enhanced by utilizing several parallel modules between the input and output of the network, each focusing on the extraction of different types of coarse features with fined grained details to break the symmetry of produced information. In fact, we leverage long range dependencies, which is one of the main drawback of CNNs. We develop this work by introducing a Dynamic Soft-Margin SoftMax.The conventional SoftMax suffers from reaching to gold labels very soon, which take the model to over-fitting. Because it’s not able to determine adequately discriminant feature vectors for some variant class labels. We reduced the risk of over-fitting by using a dynamic shape of input tensor instead of static in SoftMax layer with specifying a desired Soft- Margin. In fact, it acts as a controller to how hard the model should work to push dissimilar embedding vectors apart. For the proposed Categorical Loss, by the objective of compacting the same class labels and separating different class labels in the normalized log domain.We select penalty for those predictions with high divergence from ground-truth labels.So, we shorten correct feature vectors and enlarge false prediction tensors, it means we assign more weights for those classes with conjunction to each other (namely, “hard labels to learn”). By doing this work, we constrain the model to generate more discriminate feature vectors for variant class labels. Finally, for the proposed optimizer, our focus is on solving weak convergence of Adam optimizer for a non-convex problem. Our noteworthy optimizer is working by an alternative updating gradient procedure with an exponential weighted moving average function for faster convergence and exploiting a weight decay method to help drastically reducing the learning rate near optima to reach the dominant local minimum. We demonstrate the superiority of our proposed work by surpassing the first rank of three widely used Facial Expression Recognition datasets with 93.30% on FER-2013, and 16% improvement compare to the first rank after 10 years, reaching to 90.73% on RAF-DB, and 100% k-fold average accuracy for CK+ dataset, and shown to provide a top performance to that provided by other networks, which require much larger training datasets.

Keywords: computer vision, facial expression recognition, machine learning, algorithms, depp learning, neural networks

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