Search results for: recurrent chest pain

Authors: Thomas E. Portegys

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An animal behavior problem is presented in the form of a nest-building task that involves two cooperating virtual birds, a male and female. The female builds a nest into which she lays an egg. The male's job is to forage in a forest for food for both himself and the female. In addition, the male must fetch stones from a nearby desert for the female to use as nesting material. The task is completed when the nest is built, and an egg is laid in it. A goal-seeking neural network and a recurrent neural network were trained and tested with little success. The goal-seeking network was then enhanced with “place cells”, allowing the birds to spatially navigate the world, building the nest while keeping themselves fed. Place cells are neurons in the hippocampus that map space.

Keywords: artificial animal intelligence, artificial life, goal-seeking neural network, nest-building, place cells, spatial navigation

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Authors: Khaled Selatnia

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Nowadays, the traffic congestion becomes increasingly a chronic problem. Sometimes, the cause is attributed to the recurrent road works that create barriers to the efficient movement. But congestion, which usually occurs in cities, can take diverse forms and magnitudes. The case study of Biskra city in Algeria and the diagnosis of its road network show that throughout all the micro regional system, the road network seems at first quite dense. However, this density although it is important, does not cover all areas. A major flow is concentrated in the axis Sidi Okba – Biskra – Tolga. The largest movement of people in the Wilaya (prefecture) revolves around these three centers and their areas of influence. Centers farthest from the trio are very poorly served. This fact leads us to ask questions about the extent of congestion in Biskra city and its relationship to the imbalance of the urban framework. The objective of this paper is to highlight the impact of the urban fact on the traffic congestion.

Keywords: congestion, urban framework, regional, urban and regional studies

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Authors: Bubai Maji, Monorama Swain

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Speech is considered an essential and most natural medium for the interaction between machines and humans. However, extracting effective features for speech emotion recognition (SER) is remains challenging. The present studies show that the temporal information captured but high-level temporal-feature learning is yet to be investigated. In this paper, we present an efficient novel method using the Self-attention (SA) mechanism in a combination of Convolutional Neural Network (CNN) and Bi-directional Gated Recurrent Unit (Bi-GRU) network to learn high-level temporal-feature. In order to further enhance the representation of the high-level temporal-feature, we integrate a Bi-GRU output with learnable weights features by SA, and improve the performance. We evaluate our proposed method on our created SITB-OSED and IEMOCAP databases. We report that the experimental results of our proposed method achieve state-of-the-art performance on both databases.

Keywords: Bi-GRU, 1D-CNNs, self-attention, speech emotion recognition

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Authors: Mohammad Zavid Parvez, Manoranjan Paul

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Epilepsy is a common neurological disorders characterized by sudden recurrent seizures. Electroencephalogram (EEG) is widely used to diagnose possible epileptic seizure. Many research works have been devoted to predict epileptic seizure by analyzing EEG signal. Seizure prediction by analyzing EEG signals are challenging task due to variations of brain signals of different patients. In this paper, we propose a new approach for feature extraction based on phase correlation in EEG signals. In phase correlation, we calculate relative change between two consecutive segments of an EEG signal and then combine the changes with neighboring signals to extract features. These features are then used to classify preictal/ictal and interictal EEG signals for seizure prediction. Experiment results show that the proposed method carries good prediction rate with greater consistence for the benchmark data set in different brain locations compared to the existing state-of-the-art methods.

Keywords: EEG, epilepsy, phase correlation, seizure

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Authors: Ruqayya Naheed Khan, Romaisa Shamim, Awais Amjad Malik, Awais Naeem, Amina Iqbal Khan, Asad Parvaiz

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Objective: Patients undergoing axillary lymph node dissection (ALND) for metastatic lymph nodes in our hospital usually have drains placed in their axilla for a period of 6-10 days. We evaluated the post-op course of patients who underwent breast conservation surgery (BCS) along with ALND. Methods: A prospective cohort study was conducted at Shaukat Khanam Memorial Cancer Hospital from April 2017 to August 2017 including all lymph node positive breast cancer patients undergoing BCS with ALND. Patients were divided into two groups. Group A had no axillary drain while in Group B a drain was placed in axilla. Results: A total of 76 patients were included. 41 patients were included in group A and 35 patients in Group B. Median number of LNs dissected in group A was 17 and in group B was 15 (p value 0.443). Median operative time in group A was 84 min and in group B was 79 min (p value 0.223). Median hospital stay in both groups was 1 day (p value 0.78). At 2 weeks all patients in group A developed seroma as compared to none in group B (p value < 0.001). 3 of these patients in group A required aspiration of seroma due to pressure effects. Rest were managed conservatively. At 6 weeks only 50% patients had a seroma radiologically in Group A as compared to 33% in group B (p value 0.023). No intervention was required in any patients at week 6. QOL at 2 weeks was much better in Group A (7/41 patients had unsatisfactory response) as compared to group B (10/31 had unsatisfactory response). Results were statistically significant (p value 0.045). However, there wasn’t much difference in QOL at 6 weeks. Only 1 patient in group A had an unsatisfactory response. Average pain score at 2 weeks was similar in both groups (4.2 v/s 4.1 p value 0.73). Infection was seen in 1 patient in each group at 2 weeks (p value 0.668) and in only 1 patient in group A at 6 weeks (p value 0.067). Conclusion: We conclude from our study that there isn’t much difference in drain and no drain group in terms of wound infection and pain scores. No drain group is however associated with a better QOL in early post-op period.

Keywords: axillary drainage, axillary lymph node dissection, breast cancer, no drain in axilla

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Authors: Nicola Milani, Carla Bellissimo, Davide Pogliana, Davide Panzin, Luca Garlaschelli, Giulia Facchinetti, Claudia Casson, Luca Marazzina, Andrea Sartori, Simone Rivaroli, Jeff Konin

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The patient is a 26 year-old male amateur football player from Milan, Italy; (81kg; 185cm; BMI 23.6 kg/m²). He sustained a non-contact anterior cruciate ligament tear to his right knee in June 2021. In September 2021, his right knee ligament was reconstructed using a semitendinosus graft. The injury occurred during a football match on natural grass with typical shoes on a warm day (32 degrees celsius). Playing as a defender he sustained the injury during a change of direction, where the foot was fixated on the grass. He felt pain and was unable to continue playing the match. The surgeon approved his rehabilitation to begin two weeks post-operative. The initial physiotherapist assessment determined performing two training sessions per day within the first three months. In the first three weeks, the pain was 4/10 on Numerical Rating Scale (NRS), no swelling, a range of motion was 0-110°, with difficulty fully extending his knee and minimal quadriceps activation. Crutches were discontinued at four weeks with improved walking. Active exercise, electrostimulator, physical therapy, massages, osteopathy, and passive motion were initiated. At week 6, he completed his first functional movement screen; the score was 16/21 with no pain and no swelling. At week 8, the isokinetic test showed a 23% differential deficit between the two legs in maximum strength (at 90°/s). At week 10, he improved to 15% of injury-induced deficit which suggested he was ready to start running. At week 12, the athlete sustained his first threshold test. At week 16, he performed his first return to sports movement assessment, which revealed a 10% stronger difference between the legs. At week 16, he had his second threshold test. At week 17, his first on-field test revealed a 5% differential deficit between the two legs in the hop test. At week 18, isokinetic test demonstrates that the uninjured leg was 7% stronger than the recovering leg in maximum strength (at 90°/s). At week 20, his second on-field test revealed a 2% difference in hop test; at week 21, his third isokinetic test demonstrated a difference of 5% in maximum strength (at 90°/s). At week 21, he performed his second return to sports movement assessment which revealed a 2% difference between the limbs. Since it was the end of the championship, the team asked him to partake in the playoffs; moreover the player was very motivated to participate in the playoffs also because he was the captain of the team. Together with the player and the team, we decided to let him play even though we were aware of a heightened risk of injury than what is reported in the literature because of two factors: biological recovery times and the results of the tests we performed. In the decision making process about the athlete’s recovery time, it is important to balance the information available from the literature with the desires of the patient to avoid frustration.

Keywords: ACL, football, rehabilitation, return to play

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Authors: Yen-Fen Shen, Meng-Fan Li

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The study aims to investigate the effect of full-body vertical rhythmic training on fatigue, physical activity, and quality of life among middle-aged and elderly hemodialysis patients. The study adopted a quasi-experimental research method and recruited 43 long-term hemodialysis patients from a medical center in northern Taiwan, with 23 and 20 participants in the experimental and control groups, respectively. The experimental group received full-body vertical rhythmic training as an intervention, while the control group received standard hemodialysis care without any intervention. Both groups completed the measurements by using "Fatigue Scale", "Physical Activity Scale" and "Chinese version of the Kidney Disease Quality of Life Questionnaire" before and after the study. The experimental group underwent a 10-minute full-body vertical rhythmic training three times per week, which lasted for eight weeks before receiving regular hemodialysis treatment. The data were analyzed by SPSS 25 software, including descriptive statistics such as frequency distribution, percentages, means, and standard deviations, as well as inferential statistics, including chi-square, independent samples t-test, and paired samples t-test. The study results are summarized as follows: 1. There were no significant differences in demographic variables, fatigue, physical activity, and quality of life between the experimental and control groups in the pre-test. 2. After the intervention of the “full-body vertical rhythmic training,” the experimental group showed significantly better results in the category of "feeling tired and fatigued in the lower back", "physical functioning role limitation", "bodily pain", "social functioning", "mental health", and "impact of kidney disease on life quality." 3. The paired samples t-test results revealed that the control group experienced significant differences between the pre-test and post-test in the categories of feeling tired and fatigued in the lower back, bodily pain, social functioning mental health, and impact of kidney disease on life quality, with scores indicating a decline in life quality. Conversely, the experimental group only showed a significant worsening in bodily pain" and the impact of kidney disease on life quality, with lower change values compared to the control group. Additionally, there was an improvement in the condition of "feeling tired and fatigued in the lower back" for the experimental group. Conclusion: The intervention of the “full-body vertical rhythmic training” had a certain positive effect on the quality of life of the experimental group. While it may not entirely enhance patients' quality of life, it can mitigate the negative impact of kidney disease on certain aspects of the body. The study provides clinical practice, nursing education, and research recommendations based on the results and discusses the limitations of the research.

Keywords: hemodialysis, full-body vertical rhythmic training, fatigue, physical activity, quality of life

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Authors: Lateef Bamidele

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Over the years, radiographic examinations are the most used diagnostic tools in the Nigerian health care system, but most diagnostic examinations carried out do not have records of patient doses. Lack of adequate information on patient doses has been a major hindrance in quantifying the radiological risk associated with radiographic examinations. This study aimed at estimating dose–area product (DAP) of patient examined in X-Ray units in selected hospitals in Southern Nigeria. The standard projections selected are chest posterior-anterior (PA), abdomen anterior-posterior (AP), pelvis AP, pelvis lateral (LAT), skull AP/PA, skull LAT, lumbar spine AP, lumbar spine, LAT. Measurement of entrance surface dose (ESD) was carried out using thermoluminescent dosimeter (TLD). Measured ESDs were converted into DAP using the beam area of patients. The results show that the mean DAP ranged from 0.17 to 18.35 Gycm². The results obtained in this study when compared with those of NRPB-HPE were found to be higher. These are an indication of non optimization of operational conditions.

Keywords: dose–area product, radiographic examinations, patient doses, optimization

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Authors: F. Fatoye, C. E. Mbada, T. Gebrye, A. O. Ogunsola, C. Fatoye, O. Oyewole

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Musculoskeletal disorders (MSDs) such as low back pain (LBP), cervical spondylosis (CSPD), sprain, osteoarthritis (OA), and post immobilization stiffness (PIS) have a major impact on individuals, health systems and society in terms of morbidity, long-term disability, and economics. This study estimated the direct and indirect costs of common MSDs in Osun State, Nigeria. A review of medical charts for adult patients attending Physiotherapy Outpatient Clinic at the Obafemi Awolowo University Teaching Hospitals Complex, Osun State, Nigeria between 2009 and 2018 was carried out. The occupational class of the patients was determined using the International Labour Classification (ILO). The direct and indirect costs were estimated using a cost-of-illness approach. Physiotherapy related health resource use, and costs of the common MSDs, including consultation fee, total fee charge per session, costs of consumables were estimated. Data were summarised using descriptive statistics mean and standard deviation (SD). Overall, 1582 (Male = 47.5%, Female = 52.5%) patients with MSDs population with a mean age of 47.8 ± 25.7 years participated in this study. The mean (SD) direct costs estimate for LBP, CSPD, PIS, sprain, OA, and other conditions were $18.35 ($17.33), $34.76 ($17.33), $32.13 ($28.37), $35.14 ($44.16), $37.19 ($41.68), and $15.74 ($13.96), respectively. The mean (SD) indirect costs estimate of LBP, CSPD, PIS, sprain, OA, and other MSD conditions were $73.42 ($43.54), $140.57 ($69.31), $128.52 ($113.46), sprain $140.57 ($69.31), $148.77 ($166.71), and $62.98 ($55.84), respectively. Musculoskeletal disorders contribute a substantial economic burden to individuals with the condition and society. The unacceptable economic loss of MSDs should be reduced using appropriate strategies. Further research is required to determine the clinical and cost effectiveness of strategies to improve health outcomes of patients with MSDs. The findings of the present study may assist health policy and decision makers to understand the economic burden of MSDs and facilitate efficient allocation of healthcare resources to alleviate the burden associated with these conditions in Nigeria.

Keywords: economic burden, low back pain, musculoskeletal disorders, real-world

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Authors: Angely Sim Jia Wun, Sasa Arsovski

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Numerous studies have been conducted on the segmentation of medical images. Segmenting the lungs is one of the common research topics in those studies. Our research stemmed from the lack of solutions for automatic bone, airway, and vessel segmentation, despite the existence of multiple lung segmentation techniques. Consequently, currently, available software tools used for medical image segmentation do not provide automatic lung, bone, airway, and vessel segmentation. This paper presents segmentation techniques along with an interactive software tool architecture for segmenting bone, lung, airway, and vessel tissues. Additionally, we propose a method for creating binary masks from automatically generated segments. The key contribution of our approach is the technique for automatic image thresholding using adjustable Hounsfield values and binary mask extraction. Generated binary masks can be successfully used as a training dataset for deep-learning solutions in medical image segmentation. In this paper, we also examine the current software tools used for medical image segmentation, discuss our approach, and identify its advantages.

Keywords: lung segmentation, binary masks, U-Net, medical software tools

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Authors: Ian O'Loughlin

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Memory networks aim to integrate some of the recent successes in machine learning with a dynamic memory base that can be updated and deployed in artificial reasoning tasks. These models involve training networks to identify, update, and operate over stored elements in a large memory array in order, for example, to ably perform question and answer tasks parsing real-world and simulated discourses. This family of approaches still faces numerous challenges: the performance of these network models in simulated domains remains considerably better than in open, real-world domains, wide-context cues remain elusive in parsing words and sentences, and even moderately complex sentence structures remain problematic. This innovation, employing an array of stored and updatable ‘memory’ elements over which the system operates as it parses text input and develops responses to questions, is a compelling one for at least two reasons: first, it addresses one of the difficulties that standard machine learning techniques face, by providing a way to store a large bank of facts, offering a way forward for the kinds of long-term reasoning that, for example, recurrent neural networks trained on a corpus have difficulty performing. Second, the addition of a stored long-term memory component in artificial reasoning seems psychologically plausible; human reasoning appears replete with invocations of long-term memory, and the stored but dynamic elements in the arrays of memory networks are deeply reminiscent of the way that human memory is readily and often characterized. However, this apparent psychological plausibility is belied by a recent turn in the study of human memory in cognitive science. In recent years, the very notion that there is a stored element which enables remembering, however dynamic or reconstructive it may be, has come under deep suspicion. In the wake of constructive memory studies, amnesia and impairment studies, and studies of implicit memory—as well as following considerations from the cognitive neuroscience of memory and conceptual analyses from the philosophy of mind and cognitive science—researchers are now rejecting storage and retrieval, even in principle, and instead seeking and developing models of human memory wherein plasticity and dynamics are the rule rather than the exception. In these models, storage is entirely avoided by modeling memory using a recurrent neural network designed to fit a preconceived energy function that attains zero values only for desired memory patterns, so that these patterns are the sole stable equilibrium points in the attractor network. So although the array of long-term memory elements in memory networks seem psychologically appropriate for reasoning systems, they may actually be incurring difficulties that are theoretically analogous to those that older, storage-based models of human memory have demonstrated. The kind of emergent stability found in the attractor network models more closely fits our best understanding of human long-term memory than do the memory network arrays, despite appearances to the contrary.

Keywords: artificial reasoning, human memory, machine learning, neural networks

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Authors: J. Lino Alves, L. Lopes

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It is not new that industrial design projects are a result of cooperative work from different areas of knowledge. However, in the academic teaching of Industrial Design and Mechanical Engineering courses, it is not recurrent that those competences are mixed before the professional life arrives. This abstract intends to describe two semester experiences carried out by two professors - a mechanical engineer and an industrial designer - in the last two academic years, for which they created mixed teams of Industrial Design and Mechanical Engineering (UPorto University). The two experiences differ in several factors; the main one is related to the challenges of online education, a constraint that affected the second experience. In the first year, even before foreseeing the effects that the pandemic would reconfigure the education system, a partnership with the Education Service of Águas do Porto was established. The purpose of the exercise was the project development of a game that could be an interaction element oriented to potentiate a positive experience and as an educational contribution to the children. In the second year, already foreseeing that the teaching experience would be carried out online, it was decided to design an open briefing, which allowed the groups to choose among three themes: a hand scale game using additive manufacturing; a modular system for ventilated facade using a parametric design basis; or, a modular system for vertical gardens. In methodological terms, besides the weekly follow-up, with the simultaneous support of the two professors, a group self-evaluation was requested; and a form to be filled individually to evaluate other groups. One of the first conclusions is related to the briefing format. Industrial Design students seem comfortable working on an open briefing that allows them to draw the project on a conceptual basis created for that purpose; on the other hand, Mechanical Engineering students were uncomfortable and insecure in the initial phase due to the absence of concrete, closed "order." In other words, it is not recurrent for Mechanical Engineering students that the creative component is stimulated, seemingly leaving them reserved to the technical solution and execution, depriving them of the co-creation phase during the conceptual construction of the project's own brief. Another fact that was registered is related to the leadership positions in the groups, which alternated according to the state of development of the project: design students took the lead during the ideation/concept phase, while mechanical engineering ones took a greater lead during the intermediate development process, namely in the definition of constructive solutions, mass/volume calculations, manufacturing, and material resistance. Designers' competences were again more evident and assumed in the final phase, especially in communication skills, as well as in simulations in the context of use. However, at some moments, it was visible the capacity for quite balanced leadership between engineering and design, in a constant debate centered on the human factor of the project - evidenced in the final solution, in the compromise and balance between technical constraints, functionality, usability, and aesthetics.

Keywords: education, industrial design, mechanical engineering, teaching ethodologies

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Authors: Mohamed M. Mashaly, Ahmed M. F. El Shiwi

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Background: Shoulder impingement syndrome is an encroachment of subacromial tissues, rotator cuff, subacromial bursa, and the long head of the biceps tendon, as a result of narrowing of the subacromial space. Activities requiring repetitive or sustained use of the arms over head often predispose the rotator cuff tendon to injury. Purpose: To compare between Combined effect therapeutic exercises and Shockwave therapy versus therapeutic exercises and phonophoresis in the treatment of shoulder impingement syndrome. Methods: Thirty patients diagnosed as shoulder impingement syndrome stage II Neer classification due to mechanical causes. Patients were randomly distributed into two equal groups. The first group consisted of 15 patients with a mean age of (45.46+8.64) received therapeutic exercises (stretching exercise of posterior shoulder capsule and strengthening exercises of shoulder muscles) and shockwave therapy (6000 shocks, 2000/session, 3 sessions, 2 weeks apart, 0.22mJ/mm^2) years. The second group consisted of 15 patients with a mean age of 46.26 (+ 8.05) received same therapeutic exercises and phonophoresis (3 times per week, each other day, for 4 consecutive weeks). Patients were evaluated pretreatment and post treatment for shoulder pain severity, shoulder functional disability, shoulder flexion, abduction and internal rotation motions. Results: Patients of both groups showed significant improvement in all the measured variables. In between groups difference the shock wave group showed a significant improvement in all measured variables than phonophoresis group. Interpretation/Conclusion: Combined effect of therapeutic exercises and shock wave were more effective than therapeutic exercises and phonophoresis on decreasing shoulder pain severity, shoulder functional disability, increasing in shoulder flexion, abduction, internal rotation in patients with shoulder impingement syndrome.

Keywords: shoulder impingement syndrome, therapeutic exercises, shockwave, phonophoresis

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Authors: Sonia Butalia, Huong Luu, Alexis Guigue, Karen J. B. Martins, Khanh Vu, Scott W. Klarenbach

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Obesity-related health conditions impose a substantial economic burden on payers due to increased healthcare use. Estimates of healthcare resource use and costs associated with obesity-related comorbidities are needed to inform policies and interventions targeting these conditions. Methods: Adults living with obesity were identified (a procedure-related body mass index code for class 2/3 obesity between 2012 and 2019 in Alberta, Canada; excluding those with bariatric surgery), and outcomes were compared over 1-year (2019/2020) between those who had and did not have specific obesity-related comorbidities. The probability of using a healthcare service (based on the odds ratio of a zero [OR-zero] cost) was compared; 95% confidence intervals (CI) were reported. Logistic regression and a generalized linear model with log link and gamma distribution were used for total healthcare cost comparisons ($CDN); cost ratios and estimated cost differences (95% CI) were reported. Potential socio-demographic and clinical confounders were adjusted for, and incremental cost differences were representative of a referent case. Results: A total of 220,190 adults living with obesity were included; 44% had hypertension, 25% had osteoarthritis, 24% had type-2 diabetes, 17% had cardiovascular disease, 12% had insulin resistance, 9% had chronic back pain, and 4% of females had polycystic ovarian syndrome (PCOS). The probability of hospitalization, ED visit, and ambulatory care was higher in those with a following obesity-related comorbidity versus those without: chronic back pain (hospitalization: 1.8-times [OR-zero: 0.57 [0.55/0.59]] / ED visit: 1.9-times [OR-zero: 0.54 [0.53/0.56]] / ambulatory care visit: 2.4-times [OR-zero: 0.41 [0.40/0.43]]), cardiovascular disease (2.7-times [OR-zero: 0.37 [0.36/0.38]] / 1.9-times [OR-zero: 0.52 [0.51/0.53]] / 2.8-times [OR-zero: 0.36 [0.35/0.36]]), osteoarthritis (2.0-times [OR-zero: 0.51 [0.50/0.53]] / 1.4-times [OR-zero: 0.74 [0.73/0.76]] / 2.5-times [OR-zero: 0.40 [0.40/0.41]]), type-2 diabetes (1.9-times [OR-zero: 0.54 [0.52/0.55]] / 1.4-times [OR-zero: 0.72 [0.70/0.73]] / 2.1-times [OR-zero: 0.47 [0.46/0.47]]), hypertension (1.8-times [OR-zero: 0.56 [0.54/0.57]] / 1.3-times [OR-zero: 0.79 [0.77/0.80]] / 2.2-times [OR-zero: 0.46 [0.45/0.47]]), PCOS (not significant / 1.2-times [OR-zero: 0.83 [0.79/0.88]] / not significant), and insulin resistance (1.1-times [OR-zero: 0.88 [0.84/0.91]] / 1.1-times [OR-zero: 0.92 [0.89/0.94]] / 1.8-times [OR-zero: 0.56 [0.54/0.57]]). After fully adjusting for potential confounders, the total healthcare cost ratio was higher in those with a following obesity-related comorbidity versus those without: chronic back pain (1.54-times [1.51/1.56]), cardiovascular disease (1.45-times [1.43/1.47]), osteoarthritis (1.36-times [1.35/1.38]), type-2 diabetes (1.30-times [1.28/1.31]), hypertension (1.27-times [1.26/1.28]), PCOS (1.08-times [1.05/1.11]), and insulin resistance (1.03-times [1.01/1.04]). Conclusions: Adults with obesity who have specific disease-related health conditions have a higher probability of healthcare use and incur greater costs than those without specific comorbidities; incremental costs are larger when other obesity-related health conditions are not adjusted for. In a specific referent case, hypertension was costliest (44% had this condition with an additional annual cost of $715 [$678/$753]). If these findings hold for the Canadian population, hypertension in persons with obesity represents an estimated additional annual healthcare cost of $2.5 billion among adults living with obesity (based on an adult obesity rate of 26%). Results of this study can inform decision making on investment in interventions that are effective in treating obesity and its complications.

Keywords: administrative data, healthcare cost, obesity-related comorbidities, real world evidence

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Authors: Mary Abigail T. Ty, Mary Jocelyn Yu-Laygo, Jocelyn Z. Mariano

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This is a case of L.S.T., a 61 year old, G6P4 (3124) who presented with a one month history of intermittent, brownish, watery, non foul smelling vaginal discharge. There were no other accompanying symptoms. On rectovaginal examination, a palpable adnexal mass on the left was appreciated, with the lower border measuring 3 cm. The mass was non-tender, had irregular borders and solid areas. On transvaginal sonography, it revealed a left pelvic mass measuring 3 x 4 x 2 cm, with a Sassone score of 9. It had vascularization. The primary consideration was Ovarian Newgrowth, probably malignant in nature. CA-125 results were slightly elevated at 43.2 u/ml (NV: 0-35 u/ml). After intraoperative evaluation, the left fallopian tube was converted into a 9 x 4.5 x 3 cm bulbous cystic mass with solid areas. On cut section, the ampullary portion of the fallopian tube contained necrotic and friable looking tissues. Specimen was sent for frozen section and results revealed adenocarcinoma of the left fallopian tube. Patient subsequently underwent complete surgical staging with unremarkable post-operative course. The Surg Ico pathologic diagnosis was G6P4 (3124) Fallopian tube serous cystadenocarcinoma stage 1. The mean incidence of PFTC is 3.6 per million women yearly. This is associated with a generally low survival rate. The primary diagnosis is very difficult to establish because only 0–10% of patients suffering from PFTC are diagnosed pre-operatively. Symptoms play a very important role in the discovery of this disease, because there will be no presentation to the hospital without symptoms. The most common of which may be vaginal bleeding, abdominal pain, a palpable mass and ascites. A conglomerate of manifestations may be encountered, but not at all times. This is termed hydrops tubae profluens where there is presence of colicky pain with relief from intermittent passage of serosanguinous vaginal discharge. The significance of this report is to emphasize the rarity of the case and how the dilemma in the diagnosis is almost always present despite ancillary procedures.

Keywords: fallopian tube carcinoma, prognosis, rare, risk factors

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Authors: Vikrant Gupta, Amrit Goswami

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The fixed income market forms the basis of the modern financial market. All other assets in financial markets derive their value from the bond market. Owing to its over-the-counter nature, corporate bonds have relatively less data publicly available and thus is researched upon far less compared to Equities. Bond price prediction is a complex financial time series forecasting problem and is considered very crucial in the domain of finance. The bond prices are highly volatile and full of noise which makes it very difficult for traditional statistical time-series models to capture the complexity in series patterns which leads to inefficient forecasts. To overcome the inefficiencies of statistical models, various machine learning techniques were initially used in the literature for more accurate forecasting of time-series. However, simple machine learning methods such as linear regression, support vectors, random forests fail to provide efficient results when tested on highly complex sequences such as stock prices and bond prices. hence to capture these intricate sequence patterns, various deep learning-based methodologies have been discussed in the literature. In this study, a recurrent neural network-based deep learning model using long short term networks for prediction of corporate bond prices has been discussed. Long Short Term networks (LSTM) have been widely used in the literature for various sequence learning tasks in various domains such as machine translation, speech recognition, etc. In recent years, various studies have discussed the effectiveness of LSTMs in forecasting complex time-series sequences and have shown promising results when compared to other methodologies. LSTMs are a special kind of recurrent neural networks which are capable of learning long term dependencies due to its memory function which traditional neural networks fail to capture. In this study, a simple LSTM, Stacked LSTM and a Masked LSTM based model has been discussed with respect to varying input sequences (three days, seven days and 14 days). In order to facilitate faster learning and to gradually decompose the complexity of bond price sequence, an Empirical Mode Decomposition (EMD) has been used, which has resulted in accuracy improvement of the standalone LSTM model. With a variety of Technical Indicators and EMD decomposed time series, Masked LSTM outperformed the other two counterparts in terms of prediction accuracy. To benchmark the proposed model, the results have been compared with traditional time series models (ARIMA), shallow neural networks and above discussed three different LSTM models. In summary, our results show that the use of LSTM models provide more accurate results and should be explored more within the asset management industry.

Keywords: bond prices, long short-term memory, time series forecasting, empirical mode decomposition

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Authors: Muhammad Ahnaf Zahin, Yaw Adu-Gyamfi

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Bus transit is a crucial component of transportation networks, especially in urban areas. Any intelligent transportation system must have accurate real-time information on bus travel times since it minimizes waiting times for passengers at different stations along a route, improves service reliability, and significantly optimizes travel patterns. Bus agencies must enhance the quality of their information service to serve their passengers better and draw in more travelers since people waiting at bus stops are frequently anxious about when the bus will arrive at their starting point and when it will reach their destination. For solving this issue, different models have been developed for predicting bus travel times recently, but most of them are focused on smaller road networks due to their relatively subpar performance in high-density urban areas on a vast network. This paper develops a deep learning-based architecture using a single-step multi-station forecasting approach to predict average bus travel times for numerous routes, stops, and trips on a large-scale network using heterogeneous bus transit data collected from the GTFS database. Over one week, data was gathered from multiple bus routes in Saint Louis, Missouri. In this study, Gated Recurrent Unit (GRU) neural network was followed to predict the mean vehicle travel times for different hours of the day for multiple stations along multiple routes. Historical time steps and prediction horizon were set up to 5 and 1, respectively, which means that five hours of historical average travel time data were used to predict average travel time for the following hour. The spatial and temporal information and the historical average travel times were captured from the dataset for model input parameters. As adjacency matrices for the spatial input parameters, the station distances and sequence numbers were used, and the time of day (hour) was considered for the temporal inputs. Other inputs, including volatility information such as standard deviation and variance of journey durations, were also included in the model to make it more robust. The model's performance was evaluated based on a metric called mean absolute percentage error (MAPE). The observed prediction errors for various routes, trips, and stations remained consistent throughout the day. The results showed that the developed model could predict travel times more accurately during peak traffic hours, having a MAPE of around 14%, and performed less accurately during the latter part of the day. In the context of a complicated transportation network in high-density urban areas, the model showed its applicability for real-time travel time prediction of public transportation and ensured the high quality of the predictions generated by the model.

Keywords: gated recurrent unit, mean absolute percentage error, single-step forecasting, travel time prediction.

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Authors: Muhammad Naveed Ali, Hamad Bin Rashid, Muhammad Arif Khan, Abdul Basit, Hafiz Muhammad Arshad

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Abdominal defects are very common in pigeons. A new technique is known as intraabdominal mesh transplant that give better protection for herniorrhaphy. The aim of this study was to determine the performance of hernia mesh. In this study, an efficacy of two synthetic hernia mesh implants viz. conventional Prolene and a lightweight mesh monofilament polyester were assessed for the abdominal wall repair in pigeons. Twenty four healthy pigeons were selected and randomly distributed into three groups, A, B and C (n=8). In all groups, experimental laparotomy was performed; thereafter, abdominal muscles and peritoneum were sutured together, while, a 2 x 2 cm defect was created in the abdominal muscles. For onlay hernioplasty, the hernia mesh (Prolene mesh: group A; Polyester mesh: group B) was implanted over the external oblique muscles of the abdomen. In group C (control), the mesh was not implanted; instead, the laparotomy incision was closed after a herniorrhaphy. Post-operative pain wound healing, adhesion formation, histopathological findings and formation of hematoma, abscess and seroma were assessed as short-term complications. Post-operatively, pain at surgical site was significantly less (P < 0.001) in group B (Polyester mesh); wound healing was also significantly better and rapid in group B (P < 0.05) than in group A (Prolene mesh). Group B (Polyester mesh) also depicted less than 25% adhesions when assessed on the basis of a Quantitative Modified Diamond scale; a Qualitative Adhesion Tenacity scale also depicted either no adhesions or flimsy adhesions (n=2) in group B (Polyester mesh), in contrast to group A (Prolene), which manifested greater adhesion formation and presence of dense adhesions requiring blunt dissection. There were observed hematoma, seroma and abscess formations in birds treated by Prolene mesh only. Conclusively, the polyester mesh proved superior to the Prolene mesh regarding lesser adhesion, better in wound healing, and no short-term follow-up complications.

Keywords: adhesion, mesh, polyester, prolene

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Authors: Moustafa Ali Elwan, Ibrahim Salem Abdelrafa, Ashraf Moharm

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Nonsteroidal anti-inflammatory drugs (NSAIDs) are among the most commonly prescribed oral and topical drugs worldwide. Moreover, NSAIDs are responsible for most of all adverse drug reactions. For several decades, there are numerous attempts to use the cutaneous layers as a gate into the body for the local delivery of the therapeutic agent. Transdermal drug delivery is a validated technology contributing significantly to global pharmaceutical care. Transdermal Drug Delivery systems can be improved by using therapeutic agents. Moreover, Transdermal Drug Delivery systems can be improved by using chemical enhancers like ultrasound or iontophoresis. Iontophoresis provides a mechanism to enhance the penetration of hydrophilic and charged molecules across the skin. Objective: to compare the drug administration by ‘iontophoresis’ versus the oral rule. Methods: This study was conducted at the Faculty of Physical Therapy, Modern University for technology and information, Cairo, Egypt, on 20 participants (8 female & 12 male) who complained of tennis elbow. Their mean age was (25.45 ± 3.98) years, and all participants were assessed in many aspects: Pain threshold was assessed by algometer. Range of motion was assessed by electro goniometer, and isometric strength was assessed by a portable hand-held dynamometer. Then Participants were randomly assigned into two groups: group A was treated with oral NSAID (diclofenac) while group B was treated via administration of NSAIDs (diclofenac) via an iontophoresis device. All the participants were subjected to blood samples analysis in both pre-administration of the drug and post-administration of the drug for 24 hours (sample/every 6 hours). Results: The results demonstrated that there was a significant improvement in group b, “iontophoresis NSAIDs group,” more than in group B,” oral NSAIDs group,” in all measurements ‘ pain threshold, strength, and range of motion. Also, the iontophoresis method shows higher maximum plasma concentrations (Cmax) and concentration-time curves than the oral method.

Keywords: diclofenac, iontophoresis, NSAIDs, oral, tennis elbow

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Authors: Syed Mahbubuz Zaman, A. B. M. Abrar Haque, Mehedi Hassan Nayeem, Misbah Uddin Sagor

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Everyday e-mails are being used by millions of people as an effective form of communication over the Internet. Although e-mails allow high-speed communication, there is a constant threat known as spam. Spam e-mail is often called junk e-mails which are unsolicited and sent in bulk. These unsolicited emails cause security concerns among internet users because they are being exposed to inappropriate content. There is no guaranteed way to stop spammers who use static filters as they are bypassed very easily. In this paper, a smart system is proposed that will be using neural networks to approach spam in a different way, and meanwhile, this will also detect the most relevant features that will help to design the spam filter. Also, a comparison of different parameters for different neural network models has been shown to determine which model works best within suitable parameters.

Keywords: long short-term memory, bidirectional long short-term memory, gated recurrent unit, natural language processing, natural language processing

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Authors: Masashi Kanazawa, Takaaki Nakano, Masaaki Takemoto, Tomonori Imamura, Mamiko Sugimura, Toshitaka Ito

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Introduction: We experienced a massive disaster due to inhalation of water-soluble paint. Sixteen patients were brought to our emergency room, and pulmonary edema was revealed on the CT images of 12 cases. Purpose: Transition of chest CT-scan findings in cases with pulmonary edema was examined. Method: CT-scans were performed on the 1st, 2nd, 5th, and 19th days after the inhalation event. Patients whose pulmonary edema showed amelioration or exacerbation were classified into the improvement or the exacerbation group, respectively. Those with lung edema findings appearing at different sites after the second day were classified into the changing group. Results: Eight, one and three patients were in the improvement, exacerbation and changing groups, respectively. In all cases, the pulmonary edema had disappeared from CT images on the 19th day after the inhalation event. Conclusion: Inhalation of water-soluble paints is considered to be relatively safe. However, our observations in these emergency cases suggest that, even if pulmonary edema is not severe immediately after the exposure, new lesions may appear later and existing lesions may worsen. Follow-up imaging is thus necessary for about two weeks.

Keywords: CT scan, intoxication, pulmonary edema, water-soluble paint

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Authors: Nanteza Rachel

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Background: Worldwide, there were 36.7 million people living with Human Immunodeficiency Virus (HIV) in 2015, up from 35 million at the end of 2013. Wakiso district is one of the hotspots for the Human Immunodeficiency Virus (HIV)/ Acquired Immune Deficiency Syndrome (AIDS) infection in Uganda, with the prevalence of 8.1 %. Herbal medicine has gained popularity among Human Immunodeficiency Virus (HIV)/ Acquired Immune Deficiency Syndrome (AIDS) patients as adjuvant therapy to reduce the adverse effects of ART. Regardless of the subsidized and physical availability of the Anti-Retroviral Therapy (ART), majority of Africans living with Human Immunodeficiency Virus (HIV)/ Acquired Immune Deficiency Syndrome (AIDS) resort to adding to their ART traditional medicine. Result found out from a pilot observation made by the PI that indicate 13 out of 30 People Living with AIDS(PLWA) who are attending Human Immunodeficiency Virus (HIV) clinics in Wakiso district reported to be using herbal preparations despite the fact that they were taking Anti Retro Viral (ARVs) this prompted this study to be done. Purpose of the study: To determine the prevalence and factors associated with concurrent use of herbal medicine and anti-retroviral therapy among HIV/AIDS patients attending selected HIV clinics in Wakiso district. Methodology: This was a cross sectional study with both quantitative data collection (use of a questionnaire) and qualitative data collection (key informants’ interviews). A mixed method of sampling was used, that is, purposive and random sampling. Purposive sampling was based on the location in the district and used to select 7 health facilities basing on the 7 health sub districts from Wakiso. Simple random sampling was used to select one HIV clinic from each of the 7 health sub districts. Furthermore, the study units were enrolled in to the study as they entered into the HIV clinics, and 105 respondents were interviewed. Both manual and computer packages (SPSS) were used to analyze the data Results: The prevalence of concurrent use of herbal medicine and ART was 38 (36.2%). Commonly HIV symptom treated with herbs was fever 27(71.1%), diarrhea 3(7.9%) and cough 2(5.3%). Commonly used herbs for fever (Omululuza (Vernonica amydalina), Ekigagi (Aloe sp), Nalongo (Justicia betonica Linn) while for diarrhea was Ntwatwa. The side effects also included; too much pain, itchy pain of HIV, aneamia,felt sick, loss/gain appetite, joint pain and bad dreams. Herbs used to sooth the side effects were; for aneamia was avocado leaves Parea Americana mill The significant factors associated with concurrent use of herbal medicine were being familiar with herbs and conventional medicine for management HIV symptoms being expensive. The other significant factor was exhibiting hostility to patients by health personnel providing HIV care. Conclusion: Herbal medicine is widely used by clients in HIV/AIDS care. Patients being familiar with herbs and conventional medicine being expensive were associated with concurrent use of herbal medicine and ART. The exhibition of hostility to the HIV/AIDS patients by the health care providers was also associated with concurrent use of herbal medicine and ART among HIV/AIDS patients.

Keywords: HIV patients, herbal medicine, antiretroviral therapy, factors associated

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Authors: Ashan Wijekoon, Abi Beane, Subashini Jayawardana

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Background: Civil war in Sri Lanka ended a decade ago, leaving thousands of army veterans permanently disabled following lower-limb amputations. Quantifying long-term functional health and psychological wellbeing will inform the development of tailored home-based rehabilitation intervention. Objectives: To assess the long-term health and quality of life of Sri Lankan soldiers with traumatic lower-limb amputation.Methods and Materials: A comparative cross-sectional study was conducted in five districts of Sri Lanka. Using stratified random sample technique, two groups of 85 participants were selected; group 1, community re-integrated male army veterans with unilateral lower-limb amputation, and group 2, age and sex matched normal healthy individuals. Long-term health and quality of life (QoL) outcomes were assessed and compared between the two groups using self-administered Short-Form Health Survey-36 questionnaire (SF-36) previously validated for use in Sri Lanka. Results: Group 1 were active prosthetic users who had undergone amputation > ten years ago (Mean±SD: 21.7±5.9). The most prevalent comorbidities for group 1 and 2 were hypertension and diabetes (22.4% and 30.6% and 9.4% and 9.8%, respectively). In group 1, injury-associated long-term health outcomes included knee osteoarthritis (18.8%), knee pain (20.0%), and back pain (69.4%). Scores of physical health and psychological wellbeing were 53.1 (IQR 64.4- 43.8) and 63.5 (IQR 73.3- 51.4) for each group, respectively. Scores revealed the highest QoL related to social functioning (75 (IQR 87.5- 62.5)) and the poorest aspects of QoL related to general health (40 (IQR 50- 35)). Prevalence of comorbidities was significantly higher, and QoL outcomes were significantly lower among soldiers compared to normal healthy individuals (p<0.05).Conclusion: Higher prevalence of comorbidities, poor physical health, and lower QoL outcomes were more prevalent in soldiers with lower-limb amputation when compared to healthy counterparts.

Keywords: community-based, disability, health outcomes, quality of life, soldiers

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Authors: Richa Shri, Varinder Singh, Kundan Singh Bora, Abhishek Bhanot, Rahul Kumar, Amit Kumar, Ravinder Kaur

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The term ‘neuroprotection’ means preserving/salvaging function and structure of neurons. Neuroprotection is an adjunctive treatment option for neurodegenerative disorders. Oxidative stress is considered a major culprit in neurodegenerative disorders; hence, management strategies include use of antioxidants. Our search for a neuroprotective agent began with Allium cepa L. or onions, (family Amaryllidaceae) - a potent antioxidant. We have investigated the neuroprotective potential of onions in experimental models of ischemic stroke, diabetic neuropathy, neuropathic pain, and dementia. In pre and post-ischemic stroke model, the methanol extract of outer scales of onion bulbs (MEOS) prevented memory loss and motor in-coordination; reduced oxidative stress and cerebral infarct size. This also prevented and ameliorated diabetic neuropathy in mice. The MEOS was fractionated to yield a flavonoid rich fraction (FRF) that successfully reversed ischemia-reperfusion induced neuronal damage, thereby demonstrating that the flavonoids are responsible for the activity. The FRF effectively ameliorated chronic constriction induced neuropathic pain in rats. The FRF was subjected to bioactivity-guided fractionated. It was seen that FRF is more effective as compared to the isolated components probably due to synergism among the constituents (i.e., quercetin and quercetin glucosides) in the FRF. The outer scales of onion bulbs have great potential for prevention as well as for treatment of neuronal disorders. Red onions, with higher amounts of flavonoids as compared to the white onions, produced more significant neuroprotection. Thus, the standardized FRF from the waste material of a commonly used vegetable, especially the red variety, may be developed as a valuable neuroprotective agent.

Keywords: Allium cepa, antioxidant activity, flavonoid rich fraction, neuroprotection

Procedia PDF Downloads 144

Authors: Dila Ram Bhandari

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Throughout the 20th century, new governments were created where identities such as ethnic, religious, linguistic, caste, communal, tribal, and others played a part in the development of constitutions and the legal system of victim and criminal justice. Acute issues with extremism, poverty, environmental degradation, cybercrimes, human rights violations, crime against, and victimization of both individuals and groups have recently plagued South Asian nations. Everyday massive number of crimes are steadfast, these frequent crimes have made the lives of common citizens restless. Crimes are one of the major threats to society and also for civilization. Crime is a bone of contention that can create a societal disturbance. The old-style crime solving practices are unable to live up to the requirement of existing crime situations. Crime analysis is one of the most important activities of the majority of intelligent and law enforcement organizations all over the world. The South Asia region lacks such a regional coordination mechanism, unlike central Asia of Asia Pacific regions, to facilitate criminal intelligence sharing and operational coordination related to organized crime, including illicit drug trafficking and money laundering. There have been numerous conversations in recent years about using data mining technology to combat crime and terrorism. The Data Detective program from Sentient as a software company, uses data mining techniques to support the police (Sentient, 2017). The goals of this internship are to test out several predictive model solutions and choose the most effective and promising one. First, extensive literature reviews on data mining, crime analysis, and crime data mining were conducted. Sentient offered a 7-year archive of crime statistics that were daily aggregated to produce a univariate dataset. Moreover, a daily incidence type aggregation was performed to produce a multivariate dataset. Each solution's forecast period lasted seven days. Statistical models and neural network models were the two main groups into which the experiments were split. For the crime data, neural networks fared better than statistical models. This study gives a general review of the applied statistics and neural network models. A detailed image of each model's performance on the available data and generalizability is provided by a comparative analysis of all the models on a comparable dataset. Obviously, the studies demonstrated that, in comparison to other models, Gated Recurrent Units (GRU) produced greater prediction. The crime records of 2005-2019 which was collected from Nepal Police headquarter and analysed by R programming. In conclusion, gated recurrent unit implementation could give benefit to police in predicting crime. Hence, time series analysis using GRU could be a prospective additional feature in Data Detective.

Keywords: time series analysis, forecasting, ARIMA, machine learning

Procedia PDF Downloads 156

Authors: Nabil A. A. Mohamed, Alaa A. A. Balbaa, Khaled E. Ayad

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Osteoarthritis (OA) of the knee is the most common form of arthritis and leads to more activity limitations (e.g., disability in walking and stair climbing) than any other disease, especially in the elderly. Recently, impaired proprioceptive accuracy of the knee has been proposed as a local factor in the onset and progression of radiographic knee OA (ROA). Purpose: To compare the clinical and radiological findings in healthy with that of knee OA. Also, to determine if there is a correlation between the clinical and radiological findings in patients with knee OA. Subjects: Fifty one patients diagnosed as unilateral or bilateral knee OA with age ranged between 35-70 years, from both gender without any previous history of knee trauma or surgery, and twenty one normal subjects with age ranged from 35 - 68 years. METHODS: peak torque/body weight (PT/BW) was recorded from knee extensors at isokinetic isometric mode at angle of 45 degree. Also, the Absolute Angular Error was recorded at 45O and 30O to measure joint position sense (JPS). They made anteroposterior (AP) plain X-rays from standing semiflexed knee position and their average score of Timed Up and Go test(TUG) and WOMAC were recorded as a measure of knee pain, stiffness and function. Comparison between the mean values of different variables in the two groups was performed using unpaired student t test. The P value less or equal to 0.05 was considered significant. Results: There were significant differences between the studied variables between the experimental and control groups except the values of AAE at 30O. Also, there were no significant correlation between the clinical findings (pain, function, muscle strength and proprioception) and the severity of arthritic changes in X-rays. CONCLUSION: From the finding of the current study we can conclude that there were a significant difference between the both groups in all studied parameters (the WOMAC, functional level, quadriceps muscle strength and the joint proprioception). Also this study did not support the dependency on radiological findings in management of knee OA as the radiological features did not necessarily indicate the level of structural damage of patients with knee OA and we should consider the clinical features in our treatment plan.

Keywords: joint position sense, peak torque, proprioception, radiological knee osteoarthritis

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Authors: Leena Korpinen, Rauno Pääkkönen, Fabriziomaria Gobba

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This paper is based on a large questionnaire study. The paper presents how all participants and subgroups (upper- and lower-level white-collar workers) answered the question, “Have you had an ache, pain, or numbness, which you associate with desktop computer use, in the different body parts during the last 12 months?’ 14.6% of participants (19.4% of women and 8.2% of men) reported that they had often or very often physical symptoms in the neck. Even if our results cannot prove a causal relation of symptoms with computer use, show that workers believe that computer use can influence their wellbeing: This is important when devising treatment modalities to decrease these physical symptoms.

Keywords: ergonomics, work, computer, symptoms

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Authors: Ibragim Issabekov, Byron Crape, Lyazzat Toleubekova

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Background: Palliative care substantially improves the quality of life of terminally-ill patients. Symptom control is one of the keystones in the management of patients in palliative care settings, lowering distress as well as improving the quality of life of patients with end-stage diseases. The most common symptoms causing significant distress for patients are pain, nausea and vomiting, increased respiratory secretions and mental health issues like depression. Aims are: 1. to identify best practices in symptom management in palliative patients in accordance with internationally approved guidelines and compare aforementioned with actual practices in Kazakhstan; to evaluate the criteria for assessing symptoms in terminally-ill patients, 2. to review the availability and utilization of pharmaceutical agents for pain control, management of excessive respiratory secretions, nausea, and vomiting, and delirium and 3. to develop recommendations for the systematic approach to end-of-life symptom management in Kazakhstan. Methods: The use of qualitative research methods together with systematic literature review have been employed to provide a rigorous research process to evaluate current approaches for symptom management of palliative patients in Kazakhstan. Qualitative methods include in-depth semi-structured interviews of the healthcare professionals involved in palliative care provision. Results: Obstacles were found in appropriate provision of palliative care. Inadequate education and training to manage severe symptoms, poorly defined laws and regulations for palliative care provision, and a lack of algorithms and guidelines for care were major barriers in the effective provision of palliative care. Conclusion: Assessment of palliative care in this medium-income transitional-economy country is one of the first steps in the initiation of integration of palliative care into the existing health system. Achieving this requires identifying obstacles and resolving these issues.

Keywords: end-of-life care, middle income country, palliative care, symptom control

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Authors: Slimani Halima

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One of the main problems of degradation of arid steppe rangelands in the southern Mediterranean is the loss of plant diversity and changes in soil properties. During the last decades, these rangelands faced two main driving forces: climate through more or less lasting and recurrent droughts and overgrazing by sheep. In the present work, the preexisting system was an arid steppe with alfa grass (Stipa tenacissima L.) as the dominant plant, which was considered to be the "keystone" species toward the whole ecosystem structure and functioning. Vegetation and soil change was monitored for 45 years along a grazing intensity gradient. Changes in species richness and diversity, in the vegetation and in the soil, enabled to better understand climate fluctuations effects in comparison to overgrazing ones. The aim is to assess the impacts of grazing and climatic variability and change on biodiversity,vegetation and soil over a period of 45 years, based on data from seven reference years.

Keywords: biodiversity, desertification, droughts, el bayadh, overgrazing, soil, steppe

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Authors: Pingping Lin, Xudong Luo, Yifan Fan

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Sentiment analysis is a very active research topic. Every day, Facebook, Twitter, Weibo, and other social media, as well as significant e-commerce websites, generate a massive amount of comments, which can be used to analyse peoples opinions or emotions. The existing methods for sentiment analysis are based mainly on sentiment dictionaries, machine learning, and deep learning. The first two kinds of methods rely on heavily sentiment dictionaries or large amounts of labelled data. The third one overcomes these two problems. So, in this paper, we focus on the third one. Specifically, we survey various sentiment analysis methods based on convolutional neural network, recurrent neural network, long short-term memory, deep neural network, deep belief network, and memory network. We compare their futures, advantages, and disadvantages. Also, we point out the main problems of these methods, which may be worthy of careful studies in the future. Finally, we also examine the application of deep learning in multimodal sentiment analysis and aspect-level sentiment analysis.

Keywords: document analysis, deep learning, multimodal sentiment analysis, natural language processing

Procedia PDF Downloads 155