Search results for: clinical error

Authors: Bersufekad Wubie

Abstract:

Introduction: Near visual impairment is presenting near visual acuity of the eye worse than N6 at a 40 cm distance. Teachers' regular duties, such as reading books, writing on the blackboard, and recognizing students' faces, need good near vision. If a teacher has near-visual impairment, the work output is unsatisfactory. Objective: The study was aimed to assess the prevalence and associated factors near vision impairment among school teachers at Gondar city Northwest Ethiopia, August 2022. Methods: To select 567 teachers in Gondar city schools, an institutional-based cross-sectional study design with a multistage sampling technique were used. The study was conducted in selected schools from May 1 to May 30, 2022. Trained data collectors used well-structured Amharic and English language questionnaires and ophthalmic instruments for examination. The collected data were checked for completeness and entered into Epi data version 4.6, then exported to SPSS version 26 for further analysis. A binary and multivariate logistic regression model was fitted. And associated factors of the outcome variable. Result: The prevalence of near visual impairment was 64.6%, with a confidence interval of 60.3%–68.4%. Near visual impairment was significantly associated with age >= 35 years (AOR: 4.90 at 95% CI: 3.15, 7.65), having prolonged years of teaching experience (AOR: 3.29 at 95% CI: 1.70, 4.62), having a history of ocular surgery (AOR: 1.96 at 95% CI: 1.10, 4.62), smokers (AOR: 2.21 at 95% CI: 1.22, 4.07), history of ocular trauma (AOR : 1.80 at 95%CI:1.11,3.18 and uncorrected refractive error (AOR:2.01 at 95%CI:1.13,4.03). Conclusion and recommendations: This study showed the prevalence of near vision impairment among school teachers was high, and it is not a problem of the presbyopia age group alone; it also happens at a young age. So teachers' ocular health should be well accommodated in the school's eye health.

Keywords: Gondar, near visual impairment, school, teachers

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Authors: Panprapa Yongtrakul, Punyaphat Sirithanabadeekul, Pakjira Siriphan

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Background: The thread lift technique has become popular because it is less invasive, requires a shorter operation, less downtime, and results in fewer postoperative complications. The advantage of the technique is that the thread can be inserted under the skin without the need for long incisions. Currently, there are a lot of thread lift techniques with respect to the specific types of thread used on specific areas, such as the mid-face, lower face, or neck area. Objective: To review the thread lift technique for specific areas according to type of thread, patient selection, and how to match the most appropriate to the patient. Materials and Methods: A literature review technique was conducted by searching PubMed and MEDLINE, then compiled and summarized. Result: We have divided our protocols into two sections: Protocols for short suture, and protocols for long suture techniques. We also created 3D pictures for each technique to enhance understanding and application in a clinical setting. Conclusion: There are advantages and disadvantages to short suture and long suture techniques. The best outcome for each patient depends on appropriate patient selection and determining the most suitable technique for the defect and area of patient concern.

Keywords: thread lift, thread lift method, thread lift technique, thread lift procedure, threading

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Authors: Yunwei Zhang, Na Li, Yuhong Niu

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Bone tissue engineering scaffold was regarded as an important clinical technology of curing bony defect. The patent protection of bone tissue engineering scaffold had been paid more attention and strengthened all over the world. This study analyzed the future development trends of international technologies in the field of bone tissue engineering scaffold and its patent protection. This study used the methods of data classification and classification indexing to analyze 2718 patents retrieved in the patent database. Results showed that the patents coming from United States had a competitive advantage over other countiries in the field of bone tissue engineering scaffold. The number of patent applications by a single company in U.S. was a quarter of that of the world. However, the capability of R&D in China was obviously weaker than global level, patents mainly coming from universities and scientific research institutions. Moreover, it would be predicted that synthetic organic materials as new materials would be gradually replaced by composite materials. The patent technology protections of composite materials would be more strengthened in the future.

Keywords: bone tissue engineering, patent analysis, Scaffold material, patent protection

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Authors: Fangzheng Li, Xiong Li

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Significant differences in urban greening have occurred in Chinese cities, which accompanied with China's rapid urbanization. However, few studies focused on the spatial differentiation of urban greening in China with large amounts of data. The spatial differentiation pattern, spatial correlation characteristics and the distribution shape of urban green space ratio, urban green coverage rate and public green area per capita were calculated and analyzed, using Global and Local Moran's I using data from 289 cities in 2014. We employed Spatial Lag Model and Spatial Error Model to assess the impacts of urbanization process on urban greening of China. Then we used Geographically Weighted Regression to estimate the spatial variations of the impacts. The results showed: 1. a significant spatial dependence and heterogeneity existed in urban greening values, and the differentiation patterns were featured by the administrative grade and the spatial agglomeration simultaneously; 2. it revealed that urbanization has a negative correlation with urban greening in Chinese cities. Among the indices, the the proportion of secondary industry, urbanization rate, population and the scale of urban land use has significant negative correlation with the urban greening of China. Automobile density and per capita Gross Domestic Product has no significant impact. The results of GWR modeling showed that the relationship between urbanization and urban greening was not constant in space. Further, the local parameter estimates suggested significant spatial variation in the impacts of various urbanization factors on urban greening.

Keywords: China’s urbanization, geographically weighted regression, spatial differentiation pattern, urban greening

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Authors: Sahabeh Safarpour, Khiruddin Abdullah, Hwee San Lim, Mohsen Dadras

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Air pollution is a growing problem arising from domestic heating, high density of vehicle traffic, electricity production, and expanding commercial and industrial activities, all increasing in parallel with urban population. Monitoring and forecasting of air quality parameters are important due to health impact. One widely available metric of aerosol abundance is the aerosol optical depth (AOD). The AOD is the integrated light extinction coefficient over a vertical atmospheric column of unit cross section, which represents the extent to which the aerosols in that vertical profile prevent the transmission of light by absorption or scattering. Seasonal aerosol optical depth (AOD) values at 550 nm derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard NASA’s Terra satellites, for the 10 years period of 2000-2010 were used to test 7 different spatial interpolation methods in the present study. The accuracy of estimations was assessed through visual analysis as well as independent validation based on basic statistics, such as root mean square error (RMSE) and correlation coefficient. Based on the RMSE and R values of predictions made using measured values from 2000 to 2010, Radial Basis Functions (RBFs) yielded the best results for spring, summer, and winter and ordinary kriging yielded the best results for fall.

Keywords: aerosol optical depth, MODIS, spatial interpolation techniques, Radial Basis Functions

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Authors: Makhlouf Sandy, Adem Ziad, Taher Fadia, Magnier Sylvie

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The electronic structure of 90ZrS has been investigated using Ab-initio methods based on Complete Active Space Self Consistent Field and Multi-reference Configuration Interaction (CASSCF/MRCI). The number of predicted states has been extended to 14 singlet and 12 triplet lowest-lying states situated below 36000cm-1. The equilibrium energies of these 26 lowest-lying electronic states have been calculated in the 2S+1Λ(±) representation. The potential energy curves have been plotted in function of the inter-nuclear distances in a range of 1.5 to 4.5Å. Spectroscopic constants, permanent electric dipole moments and transition dipole moments between the different electronic states have also been determined. A discrepancy error of utmost 5% for the majority of values shows a good agreement with available experimental data. The ground state is found to be of symmetry X1Σ+ with an equilibrium inter-nuclear distance Re= 2.16Å. However, the (1)3Δ is the closest state to X1Σ+ and is situated at 514 cm-1. To the best of our knowledge, this is the first time that the spin-orbit coupling has been investigated for all the predicted states of ZrS. 52 electronic components in the Ω(±) representation have been predicted. The energies of these components, the spectroscopic constants ωe, ωeχe, βe and the equilibrium inter-nuclear distances have been also obtained. The percentage composition of the Ω state wave-functions in terms of S-Λ states was calculated to identify their corresponding main parents. These (SOC) calculations have determined the shift between (1)3Δ1 and X1Σ+ states and confirmed the ground state type being 1Σ+.

Keywords: CASSCF/MRCI, electronic structure, spin-orbit effect, zirconium monosulfide

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Authors: Euphrasia Susy Suhendra, Lies Handrijaningsih

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The banking sector as an intermediary party or intermediaries occupies a very important position in bridging the needs of working capital investment in the real sector with funds owner. This will certainly make money more effectively to improve the economic value added. As an intermediary, Islamic banks raise funds from the public and then distribute in the form of financing. In practice, the distribution of funding that is run by Islamic Banking is not as easy as, in theory, because, in fact, there are many financing problems; some are caused by lacking the assessment and supervision of banks to customers. This study aims to analyze the influence of the Third Party Funds, Return on Assets (ROA), Non Performing Financing (NPF), and Financing Deposit Ratio (FDR) to Total Financing provided to the Community by Islamic Banks in Indonesia. The data used is monthly data released by Bank of Indonesia in Islamic Banking Statistics in the time period of January 2009 - December 2013. This study uses cointegration test to see the long-term relationship, and use error correction models to examine the relationship of short-term. The results of this study indicate that the Third Party Fund has a short-term effect on total funding, Return on Assets has a long term effect on the total financing, Non Performing Financing has long-term effects of total financing, and Financing deposit ratio has the effect of short-term and long-term of the total financing provided by Islamic Banks in Indonesia.

Keywords: Islamic banking, third party fund, return on asset, non-performing financing, financing deposit ratio

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Authors: Desta Brhanu Gebrehiwot

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The purpose of this review was to analyze the overall or combined effect of scholarly studies conducted on the impacts of Food for work (FFW) and Productive Safety Net Program (PSNP) on farm households’ livelihood (agricultural investment on the adoption of fertilizer, food security, livestock holding, nutrition and its’ disincentive effect) in Ethiopia. In addition, to make a critical assessment of the internal and external validity of the existing studies, the review also indicates the possibility to redesign the program. The method of selecting eligible studies for review was PICOS (Participants, Intervention, Comparison, Outcomes, and Settings) framework. The method of analysis was the fixed effects model under Meta-Analysis. The findings of this systematic review confirm the overall or combined positive significant impact of PSNP on fertilizer adoption (combined point estimate=0.015, standard error=0.005, variance=0.000, lower limit 0.004 up to the upper limit=0.026, z-value=2.726, and p-value=0.006). And the program had a significant positive impact on the child nutrition of rural households and had no significant disincentive effect. However, the program had no significant impact on livestock holdings. Thus, PSNP is important for households whose livelihood depends on rain-fed agriculture and are exposed to rainfall shocks. Thus, better to integrate the program into the national agricultural policy. In addition, most of the studies suggested that PSNP needs more attention to the design and targeting issued in order to be effective and efficient in social protection.

Keywords: meta-analysis, fixed effect model, PSNP, rural-livelihood, Ethiopia

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Authors: Rahul Agarwal, Ashutosh Singh

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Colorectal cancer (CRC) also refers as bowel cancer or colon cancer. It involves the development of abnormal growth of cells in colon or rectum part of the body. This work leads to the development of a miRNA database in colorectal cancer. We named this database- miCoRe. This database comprises of all validated colon-rectal cancer miRNAs information from various published literature with an effectual knowledge based information retrieval system. miRNAs have been collected from various published literature reports. MySQL is used for main-framework of miCoRe while the front-end was developed in PHP script. The aim of developing miCoRe is to create a comprehensive central repository of colorectal carcinoma miRNAs with all germane information of miRNAs and their target genes. The current version of miCoRe consists of 238 miRNAs which are known to be implicated in malignancy of CRC. Alongside with miRNA information, miCoRe also contains the information related to the target genes of these miRNA. miCoRe furnishes the information about the mechanism of incidence and progression of the disease, which would further help the researchers to look for colorectal specific miRNAs therapies and CRC specific targeted drug designing. Moreover, it will also help in development of biomarkers for the better and early detection of CRC and will help in better clinical management of the disease.

Keywords: colorectal cancer, database, miCoRe, miRNAs

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Authors: Badar Dhehawi A. Aldhafeeri

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Objective: To explore the views and experiences of healthcare providers (HCPs) and their expectations toward pharmacists in mental healthcare, in addition to their acceptance of new pharmacist roles. Barriers and facilitators that are emerging in the process of developing enhanced pharmacist-related roles were also explored. Methods: Qualitative semi-structured face-to-face interviews were conducted with HCPs who had worked in mental health services in Saudi Arabia. The data were thematically analysed using a constant comparison with NVivo software to develop a series of key themes from the interviews. Results: Most HCPs indicated that they rarely interacted with pharmacists. They expected pharmacists to educate both patients and other healthcare workers in the future. Concerns were raised regarding inadequate pharmacy education and lack of clinical training for pharmacists. Conclusion: This study revealed that interactions between HCPs and pharmacists concerning mental health are still limited. A communication strategy for addressing mental health issues should be developed among pharmacists and other HCPs.

Keywords: pharmacist, pharmacy student, saudi arabia, qualitative research

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Authors: Joselito Medina-Marin, Maria G. Serna-Diaz, Juan C. Seck-Tuoh-Mora, Norberto Hernandez-Romero, Irving Barragán-Vite

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Wind speed forecasting is an important issue for planning wind power generation facilities. The accuracy in the wind speed prediction allows a good performance of wind turbines for electricity generation. A model based on artificial neural networks is presented in this work. A dataset with atmospheric information about air temperature, atmospheric pressure, wind direction, and wind speed in Pachuca, Hidalgo, México, was used to train the artificial neural network. The data was downloaded from the web page of the National Meteorological Service of the Mexican government. The records were gathered for three months, with time intervals of ten minutes. This dataset was used to develop an iterative algorithm to create 1,110 ANNs, with different configurations, starting from one to three hidden layers and every hidden layer with a number of neurons from 1 to 10. Each ANN was trained with the Levenberg-Marquardt backpropagation algorithm, which is used to learn the relationship between input and output values. The model with the best performance contains three hidden layers and 9, 6, and 5 neurons, respectively; and the coefficient of determination obtained was r²=0.9414, and the Root Mean Squared Error is 1.0559. In summary, the ANN approach is suitable to predict the wind speed in Pachuca City because the r² value denotes a good fitting of gathered records, and the obtained ANN model can be used in the planning of wind power generation grids.

Keywords: wind power generation, artificial neural networks, wind speed, coefficient of determination

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Authors: Sebastian Kölbl, Thomas Reitmaier, Mathias Hartmann

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Trial and error approaches to adapt wearable support structures to human physiology are time consuming and elaborate. However, during preliminary design, the focus lies on understanding the interaction between exoskeleton and the human body in terms of forces and moments, namely body mechanics. For the study at hand, a multi-body simulation approach has been enhanced to evaluate actual forces and moments in a human dummy model with and without a digital mock-up of an active exoskeleton. Therefore, different motion data have been gathered and processed to perform a musculosceletal analysis. The motion data are ground reaction forces, electromyography data (EMG) and human motion data recorded with a marker-based motion capture system. Based on the experimental data, the response of the human dummy model has been calibrated. Subsequently, the scalable human dummy model, in conjunction with the motion data, is connected with the exoskeleton structure. The results of the human-machine interaction (HMI) simulation platform are in particular resulting contact forces and human joint forces to compare with admissible values with regard to the human physiology. Furthermore, it provides feedback for the sizing of the exoskeleton structure in terms of resulting interface forces (stress justification) and the effect of its compliance. A stepwise approach for the setup and validation of the modeling strategy is presented and the potential for a more time and cost-effective development of wearable support structures is outlined.

Keywords: assistive devices, ergonomic design, inverse dynamics, inverse kinematics, multibody simulation

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Authors: Sandeep, A. Joshi, Kamal, Piu Dhibar, Parveen Kumar

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In the present work strong ground motion has been simulated using a modified semi-empirical technique (MSET), with frequency dependent radiation pattern model. Joshi et al. (2014) have modified the semi-empirical technique to incorporate the modeling of strong motion generation areas (SMGAs). A frequency dependent radiation pattern model is applied to simulate high frequency ground motion more precisely. Identified SMGAs (Kurahashi and Irikura 2012) of the 2011 Tohoku earthquake (Mw 9.0) were modeled using this modified technique. Records are simulated for both frequency dependent and constant radiation pattern function. Simulated records for both cases are compared with observed records in terms of peak ground acceleration and pseudo acceleration response spectra at different stations. Comparison of simulated and observed records in terms of root mean square error suggests that the method is capable of simulating record which matches in a wide frequency range for this earthquake and bears realistic appearance in terms of shape and strong motion parameters. The results confirm the efficacy and suitability of rupture model defined by five SMGAs for the developed modified technique.

Keywords: strong ground motion, semi-empirical, strong motion generation area, frequency dependent radiation pattern, 2011 Tohoku Earthquake

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Authors: Norshima Humaidi, Saif Hussein Abdallah Alghazo

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Cybersecurity threat have become a serious issue recently, and one of the cause is because human error, which is usually constituted by carelessness, ignorance, and failure to practice cybersecurity behaviour adequately. Using a data from a quantitative survey, Partial Least Squares-Structural Equation Modelling (PLS-SEM) analysis was used to determine the factors that affect cybersecurity protective behaviour (CPB). This study adapts cybersecurity protective behaviour model by focusing on two constructs that can enhance CPB: manager’s information security competencies (MISI) and procedural information security countermeasure (PCM) awareness. Theory of leadership competencies were adapted to measure user’s perception towards competencies among security managers/leader in the organization. Confirmatory factor analysis (CFA) testing shows that all the measurement items of each constructs were adequate in their validity individually based on their factor loading value. Moreover, each constructs are valid based on their parameter estimates and statistical significance. The quantitative research findings show that PCM awareness strongly influences CPB compared to MISI. Meanwhile, MISI was significantlyPCM awarenss. This study believes that the research findings can contribute to human behaviour in IS studies and are particularly beneficial to policy makers in improving organizations’ strategic plans in information security, especially in this new era. Most organizations spend time and resources to provide and establish strategic plans of information security; however, if employees are not willing to comply and practice information security behaviour appropriately, then these efforts are in vain.

Keywords: cybersecurity, protection behaviour, information security, information security competencies, countermeasure awareness

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Authors: Miled Amel, Ben Maad Hatem, Askri Faouzi, Ben Nasrallah Sassi

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Metal hydride water pumping system uses hydrogen as working fluid to pump water for low head and high discharge. The principal operation of this pump is based on the desorption of hydrogen at high pressure and its absorption at low pressure by a metal hydride. This work is devoted to study a concept of the dynamic behavior of a metal hydride pump using unsteady model and LaNi5 as hydriding alloy. This study shows that with MHP, it is possible to pump 340l/kg-cycle of water in 15 000s using 1 Kg of LaNi5 at a desorption temperature of 360 K, a pumping head equal to 5 m and a desorption gear ratio equal to 33. This study reveals also that the error given by the steady model, using LaNi5 is about 2%.A dimensional mathematical model and the governing equations of the pump were presented to predict the coupled heat and mass transfer within the MHP. Then, a numerical simulation is carried out to present the time evolution of the specific water discharge and to test the effect of different parameters (desorption temperature, absorption temperature, desorption gear ratio) on the performance of the water pumping system (specific water discharge, pumping efficiency and pumping time). In addition, a comparison between results obtained with steady and unsteady model is performed with different hydride mass. Finally, a geometric configuration of the reactor is simulated to optimize the pumping time.

Keywords: dynamic behavior, LaNi5, performance of water pumping system, unsteady model

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Authors: Iqraq Kamal, Akmal Razif, Sivadas Chandra Sekaran, Ahmad Syazwan Hisaburi

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Painting plays a crucial role in the aerospace manufacturing industry, serving both protective and cosmetic purposes for components. However, the traditional manual painting method is time-consuming and labor-intensive, posing challenges for the sector in achieving higher efficiency. Additionally, the current automated robot path planning has been a bottleneck for spray painting processes, as typical manual teaching methods are time-consuming, error-prone, and skill-dependent. Therefore, it is essential to develop automated tool path planning methods to replace manual ones, reducing costs and improving product quality. Focusing on flat panel painting in aerospace manufacturing, this study aims to address issues related to unreliable part identification techniques caused by the high-mixture, low-volume nature of the industry. The proposed solution involves using a spray gun and a UR10 robotic arm with a vision system that utilizes one-shot object detection (OS2D) to identify parts accurately. Additionally, the research optimizes path planning by concentrating on the region of interest—specifically, the identified part, rather than uniformly covering the entire painting tray.

Keywords: aerospace manufacturing, one-shot object detection, automated spray painting, vision-based path optimization, deep learning, automation, robotic arm

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Authors: Sangbok Lee

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There has been much effort on process improvement for outpatient clinics to provide quality and acute care to patients. One of the efforts is no-show analysis or prediction. This work analyzes patient no-shows along with patient health conditions. The health conditions refer to clinical symptoms that each patient has, out of the followings; hyperlipidemia, diabetes, metastatic solid tumor, dementia, chronic obstructive pulmonary disease, hypertension, coronary artery disease, myocardial infraction, congestive heart failure, atrial fibrillation, stroke, drug dependence abuse, schizophrenia, major depression, and pain. A dataset from a regional hospital is used to find the relationship between the number of the symptoms and no-show probabilities. Additional analysis reveals how each symptom or combination of symptoms affects no-shows. In the above analyses, cross-classification of patients by age and gender is carried out. The findings from the analysis will be used to take extra care to patients with particular health conditions. They will be forced to visit clinics by being informed about their health conditions and possible consequences more clearly. Moreover, this work will be used in the preparation of making institutional guidelines for patient reminder systems.

Keywords: healthcare system, no show analysis, process improvment, statistical data analysis

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Authors: Helen Pushkarskaya, Michael Smithson, Jane E. Joseph, Christine Corbly, Ifat Levy

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Studies of decision making under uncertainty generally focus on imprecise information about outcome probabilities (“ambiguity”). It is not clear, however, whether conflicting information about outcome probabilities affects decision making in the same manner as ambiguity does. Here we combine functional Magnetic Resonance Imaging (fMRI) and a simple gamble design to study this question. In this design, the levels of ambiguity and conflict are parametrically varied, and ambiguity and conflict gambles are matched on both expected value and variance. Behaviorally, participants avoided conflict more than ambiguity, and attitudes toward ambiguity and conflict did not correlate across subjects. Neurally, regional brain activation was differentially modulated by ambiguity level and aversion to ambiguity and by conflict level and aversion to conflict. Activation in the medial prefrontal cortex was correlated with the level of ambiguity and with ambiguity aversion, whereas activation in the ventral striatum was correlated with the level of conflict and with conflict aversion. This novel double dissociation indicates that decision makers process imprecise and conflicting information differently, a finding that has important implications for basic and clinical research.

Keywords: decision making, uncertainty, ambiguity, conflict, fMRI

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Authors: Briohny H. Spencer, Russ Chess-Williams, Catherine McDermott, Shailendra Anoopkumar-Dukie, David Christie

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Background: Prostate cancer is the second most common cancer diagnosed in men worldwide and the most prevalent in Australian men. In 2015, it was estimated that approximately 18,000 new cases of prostate cancer were diagnosed in Australia. Currently, for localised disease, androgen depravation therapy (ADT) and radiotherapy are a major part of the curative management of prostate cancer. ADT acts to reduce the levels of circulating androgens, primarily testosterone and the locally produced androgen, dihydrotestosterone (DHT), or by preventing the subsequent activation of the androgen receptor. Thus, the growth of the cancerous cells can be reduced or ceased. Radiation techniques such as brachytherapy (radiation delivered directly to the prostate by transperineal implant) or external beam radiation therapy (exposure to a sufficient dose of radiation aimed at eradicating malignant cells) are also common techniques used in the treatment of this condition. Radiotherapy (RT) has significant limitations, including reduced effectiveness in treating malignant cells present in hypoxic microenvironments leading to radio-resistance and poor clinical outcomes and also the significant side effects for the patients. Alpha1-adrenoceptor antagonists are used for many prostate cancer patients to control lower urinary tract symptoms, due to the progression of the disease itself or may arise as an adverse effect of the radiotherapy treatment. In Australia, a significant number (not a majority) of patients receive a α1-ADR antagonist and four drugs are available including prazosin, terazosin, alfuzosin and tamsulosin. There is currently limited published data on the effects of α1-ADR antagonists during radiotherapy, but it suggests these medications may improve patient outcomes by enhancing the effect of radiotherapy. Aim: To determine the impact of α1-ADR antagonists treatments on time to biochemical relapse following radiotherapy. Methods: A retrospective study of male patients receiving radiotherapy for biopsy-proven localised prostate cancer was undertaken to compare cancer outcomes for drug-naïve patients and those receiving α1-ADR antagonist treatments. Ethical approval for the collection of data at Genesis CancerCare QLD was obtained and biochemical relapse (defined by a PSA rise of >2ng/mL above the nadir) was recorded in months. Rates of biochemical relapse, prostate specific antigen doubling time (PSADT) and Kaplan-Meier survival curves were also compared. Treatment groups were those receiving α1-ADR antagonists treatment before or concurrent with their radiotherapy. Data was statistically analysed using One-way ANOVA and results expressed as mean ± standard deviation. Major findings: The mean time to biochemical relapse for tamsulosin, prazosin, alfuzosin and controls were 45.3±17.4 (n=36), 41.5±19.6 (n=11), 29.3±6.02 (n=6) and 36.5±17.6 (n=16) months respectively. Tamsulosin, prazosin but not alfuzosin delayed time to biochemical relapse although the differences were not statistically significant. Conclusion: Preliminary data for the prior and/or concurrent use of tamsulosin and prazosin showed a positive trend in delaying time to biochemical relapse although no statistical significance was shown. Larger clinical studies are indicated and with thousands of patient records yet to be analysed, it may determine if there is a significant effect of these drugs on control of prostate cancer.

Keywords: alpha1-adrenoceptor antagonists, biochemical relapse, prostate cancer, radiotherapy

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Authors: Pavel V. Balabanov, Daria A. Liubimova, Aleksandr P. Savenkov

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The increase of technogenic and natural accidents, accompanied by air pollution, for example, by combustion products, leads to the necessity of respiratory protection. This work is devoted to the development of a calorimetric method and a device which allow investigating quickly the kinetics of carbon dioxide sorption by chemo-sorbents on the base of potassium superoxide in order to assess the protective properties of respiratory protective closed-circuit apparatus. The features of the traditional approach for determining the sorption properties in a thin layer of chemo-sorbent are described, as well as methods and devices, which can be used for the sorption kinetics study. The authors of the paper developed an approach (as opposed to the traditional approach) based on the power measurement of internal heat sources in the chemo-sorbent layer. The emergence of the heat sources is a result of the exothermic reaction of carbon dioxide sorption. This approach eliminates the necessity of chemical analysis of samples and can significantly reduce the time and material expenses during chemo-sorbents testing. The error of determining the volume fraction of adsorbed carbon dioxide by the developed method does not exceed 12%. Taking into account the efficiency of the method, we consider that it is a good alternative to traditional methods of chemical analysis under the assessment of the protection sorbents quality.

Keywords: carbon dioxide chemisorption, exothermic reaction, internal heat sources, respiratory protective apparatus

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Authors: G. Shahzadi, A. Soulaimani

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This research work aims to identify the physical parameters of the constitutive soil model in the design of a rockfill dam by inverse analysis. The best parameters of the constitutive soil model, are those that minimize the objective function, defined as the difference between the measured and numerical results. The Finite Element code (Plaxis) has been utilized for numerical simulation. Polynomial and neural network-based response surfaces have been generated to analyze the relationship between soil parameters and displacements. The performance of surrogate models has been analyzed and compared by evaluating the root mean square error. A comparative study has been done based on objective functions and optimization techniques. Objective functions are categorized by considering measured data with and without uncertainty in instruments, defined by the least square method, which estimates the norm between the predicted displacements and the measured values. Hydro Quebec provided data sets for the measured values of the Romaine-2 dam. Stochastic optimization, an approach that can overcome local minima, and solve non-convex and non-differentiable problems with ease, is used to obtain an optimum value. Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Differential Evolution (DE) are compared for the minimization problem, although all these techniques take time to converge to an optimum value; however, PSO provided the better convergence and best soil parameters. Overall, parameter identification analysis could be effectively used for the rockfill dam application and has the potential to become a valuable tool for geotechnical engineers for assessing dam performance and dam safety.

Keywords: Rockfill dam, parameter identification, stochastic analysis, regression, PLAXIS

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Authors: Boda Sreenivas, Lyathakula Ravindranath, Kanugula Srishailam, Byru Venkatram Reddy

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Extensive research into the optimized structure and molecular properties of 3-Flouro-2-methylbenzoicacid(FMB), 3-Chloro-2-methoxybenzoicacid (CMB), and 3-Bromo-2-methylbenzoicacid (BMB) was carried out using FT-IR, FT-Raman and UV-Visible spectra, as well as theoretically using the DFT approach with B3LYPfunctional in conjunction with 6-311++G(d,p) basis set. The optimized structure was determined by evaluating torsional scans about free rotation bonds. Structure parameters, harmonic vibrational frequencies, potential energy distribution(PED), and infrared and Raman intensities were computed. The computational results from the DFT approach, such asFT-IR, FT-Raman, and UV-Visible spectra, were compared with the experimental results and found good agreement. Observed and calculated frequencies agreed with an rms error of 8.42, 6.60, and 6.95 cm-1 for FMB, CMB, and BMB, respectively. Unambiguous vibrational assignments were made for all fundamentals using PED and eigenvectors. The electronic HOMO-LUMO, H-bonding, and strong conjugative interactions across different molecular entities are discussed using experimental and simulated Ultraviolet-Visible spectra. The title molecules' molecular properties such as dipole moment, mean polarizability, and first-order hyperpolarizability, were calculated to study their non-linear optical (NLO) behavior. The chemical reactivity descriptors and mapped electrostatic surface potential (MESP) were also evaluated. Natural bond orbital (NBO) analysis was used to examine the stability of molecules resulting from hyperconjugative interactions and charge delocalization.

Keywords: ftir/raman spectra, DFT, NLO, homo-lumo, NBO, halogenated benzoic acids

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Authors: Kuen Ming Shu, Ren Kai Ho

Abstract:

Ultrasonic horn has the functions of amplifying amplitude and reducing resonant impedance in ultrasonic system. Its primary function is to amplify deformation or velocity during vibration and focus ultrasonic energy on the small area. It is a crucial component in design of ultrasonic vibration system. There are five common design methods for ultrasonic horns: analytical method, equivalent circuit method, equal mechanical impedance, transfer matrix method, finite element method. In addition, the general optimization design process is to change the geometric parameters to improve a single performance. Therefore, in the general optimization design process, we couldn't find the relation of parameter and objective. However, a good optimization design must be able to establish the relationship between input parameters and output parameters so that the designer can choose between parameters according to different performance objectives and obtain the results of the optimization design. In this study, an ultrasonic horn provided by Maxwide Ultrasonic co., Ltd. was used as the contrast of optimized ultrasonic horn. The ANSYS finite element analysis (FEA) software was used to simulate the distribution of the horn amplitudes and the natural frequency value. The results showed that the frequency for the simulation values and actual measurement values were similar, verifying the accuracy of the simulation values. The ANSYS DesignXplorer was used to perform Response Surface optimization, which could shows the relation of parameter and objective. Therefore, this method can be used to substitute the traditional experience method or the trial-and-error method for design to reduce material costs and design cycles.

Keywords: horn, natural frequency, response surface optimization, ultrasonic vibration

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Authors: Duchel Jeanedvi Kinouani Kinavouidi, Christian Aimé Kayath, Etienne Nguimbi

Abstract:

Biosurfactants are amphipathic molecules produced by many microorganisms, usually bacteria, fungi, and yeasts. +ey possesses the property of reducing the tension of the membrane interfaces. No studies have been conducted on Shigella species showing the role of biosurfactant-like molecules (BLM) in pathogenicity. +e aim of this study is to assess the ability of Shigella environmental and clinical strains to produce BLM and investigate the involvement of biosurfactants in pathogenicity. Our study has shown that BLM is secreted in the extracellular medium with EI24 ranging from 80% to 100%. +e secretion depends on the type III secretion system (T3SS). Moreover, our results have shown that S. flexneri, S. boydii, and S. sonnei are able to interact with hydrophobic areas with 17.64%, 21.42%, and 22.22% hydrophobicity, respectively. BLM secretion is totally prevented due to the inhibition of T3SS by 100 mM benzoic and 1.5 mg/ml salicylic acids. P. aeruginosa harboring T3SS is able to produce 100% of BLM in the presence or in the absence of both T3SS inhibitors. +e secreted BLM are extractable with an organic solvent such as chloroform, and this could entirely be considered a lipopeptide or polypeptide compound. Secretion of BLM allows some Shigella strains to induce multicellular phenomena like ‘swarming.’

Keywords: shigella flexneri, biosurfactant, T3SS, Lipopeptide

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Authors: Hossain A, Hossain S.

Abstract:

Introduction: In a small cohort, we sought to assess the magnetic resonance spectroscopy's (MRS) ability to predict the presence of metastatic lesions. Method: A Popular Diagnostic Centre Limited enrolled patients with neuroepithelial tumors. The 1H CSI MRS of the brain allows us to detect changes in the concentration of specific metabolites caused by metastatic lesions. Among these metabolites are N-acetyl-aspartate (NNA), creatine (Cr), and choline (Cho). For Cho, NAA, Cr, and Cr₂, the metabolic ratio was calculated using the division method. Results: The NAA values were 0.63 and 5.65 for tumor cells, 1.86 and 5.66 for normal cells, and 1.86 and 5.66 for normal cells 2. NAA values for normal cells 1 were 1.84, 10.6, and 1.86 for normal cells 2, respectively. Cho levels were as low as 0.8 and 10.53 in the tumor cell, compared to 1.12 and 2.7 in the normal cell 1 and 1.24 and 6.36 in the normal cell 2. Cho/Cr₂ barely distinguished itself from the other ratios in terms of significance. For tumor cells, the ratios of Cho/NAA, Cho/Cr₂, NAA/Cho, and NAA/Cr₂ were significant. Normal cell 1 had significant Cho/NAA, Cho/Cr, NAA/Cho, and NAA/Cr ratios. Conclusion: The clinical result can be improved by using 1H-MRSI to guide the size of resection for metastatic lesions. Even though it is non-invasive and doesn't present any difficulties during the procedure, MRS has been shown to predict the detection of metastatic lesions.

Keywords: metabolite ratio, MRI images, metastatic lesion, MR spectroscopy, N-acetyl-aspartate

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Authors: Camilo Cerda Sarabia, Fernanda Bravo Cornejo, Diego Santibanez Oyarce, Hugo Osses Prado, Esteban Gómez Terán, Belén Diaz Diaz, Raúl Caulier-Cisterna, Jorge Vergara-Quezada, Ana Moya-Beltrán

Abstract:

Antimicrobial resistance (AMR) represents a significant and rapidly escalating global health threat. Projections estimate that by 2050, AMR infections could claim up to 10 million lives annually. Respiratory infections, in particular, pose a severe risk not only to individual patients but also to the broader public health system. Despite the alarming rise in resistant respiratory infections, AMR within the lung microbiome (microbial community) remains underexplored and poorly characterized. The lungs, as a complex and dynamic microbial environment, host diverse communities of microorganisms whose interactions and resistance mechanisms are not fully understood. Unlike studies that focus on individual genomes, analyzing the entire microbiome provides a comprehensive perspective on microbial interactions, resistance gene transfer, and community dynamics, which are crucial for understanding AMR. However, this holistic approach introduces significant computational challenges and exposes the limitations of traditional analytical methods such as the difficulty of identifying the AMR. Machine learning has emerged as a powerful tool to overcome these challenges, offering the ability to analyze complex genomic data and uncover novel insights into AMR that might be overlooked by conventional approaches. This study investigates microbial resistance within the lung microbiome using unsupervised machine learning approaches to uncover resistance patterns and potential clinical associations. it downloaded and selected lung microbiome data from HumanMetagenomeDB based on metadata characteristics such as relevant clinical information, patient demographics, environmental factors, and sample collection methods. The metadata was further complemented by details on antibiotic usage, disease status, and other relevant descriptions. The sequencing data underwent stringent quality control, followed by a functional profiling focus on identifying resistance genes through specialized databases like Antibiotic Resistance Database (CARD) which contains sequences of AMR gene sequence and resistance profiles. Subsequent analyses employed unsupervised machine learning techniques to unravel the structure and diversity of resistomes in the microbial community. Some of the methods employed were clustering methods such as K-Means and Hierarchical Clustering enabled the identification of sample groups based on their resistance gene profiles. The work was implemented in python, leveraging a range of libraries such as biopython for biological sequence manipulation, NumPy for numerical operations, Scikit-learn for machine learning, Matplotlib for data visualization and Pandas for data manipulation. The findings from this study provide insights into the distribution and dynamics of antimicrobial resistance within the lung microbiome. By leveraging unsupervised machine learning, we identified novel resistance patterns and potential drivers within the microbial community.

Keywords: antibiotic resistance, microbial community, unsupervised machine learning., sequences of AMR gene

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Authors: U. Datta

Abstract:

The main objective of this study is to find a suitable approach to monitor the land infrastructure growth over a period of time using multispectral satellite images. Bi-temporal change detection method is unable to indicate the continuous change occurring over a long period of time. To achieve this objective, the approach used here estimates a statistical model from series of multispectral image data over a long period of time, assuming there is no considerable change during that time period and then compare it with the multispectral image data obtained at a later time. The change is estimated pixel-wise. Statistical composite hypothesis technique is used for estimating pixel based change detection in a defined region. The generalized likelihood ratio test (GLRT) is used to detect the changed pixel from probabilistic estimated model of the corresponding pixel. The changed pixel is detected assuming that the images have been co-registered prior to estimation. To minimize error due to co-registration, 8-neighborhood pixels around the pixel under test are also considered. The multispectral images from Sentinel-2 and Landsat-8 from 2015 to 2018 are used for this purpose. There are different challenges in this method. First and foremost challenge is to get quite a large number of datasets for multivariate distribution modelling. A large number of images are always discarded due to cloud coverage. Due to imperfect modelling there will be high probability of false alarm. Overall conclusion that can be drawn from this work is that the probabilistic method described in this paper has given some promising results, which need to be pursued further.

Keywords: co-registration, GLRT, infrastructure growth, multispectral, multitemporal, pixel-based change detection

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Authors: Eun Ho Kim

Abstract:

Innovations have conjured up a mode of treating GBM cancer cells in the newly diagnosed patients in a period of 4.9 months at an improved median OS, which brings along only a few minor side effects in the phase III of the clinical trial. This mode has been termed the Alternating Electric Fields (AEF). The study at hand is aimed at determining whether the AEF treatment is beneficial in sensitizing the GBM cancer cells through the process of increasing the AEF –induced senescence. The methodology to obtain the findings for this research ranged across various components, such as obtaining and testing SA-β-gal staining, flow cytometry, Western blotting, morphology, and Positron Emission Tomography (PET) / Computed Tomography (CT), immunohistochemical staining and microarray. The number of cells that displayed a senescence-specific morphology and positive SA-ß-Gal activity gradually increased up to 5 days. These results suggest that p16, p21 and p27 are essential regulators of AEF -induced senescence via NF-κB activation. The results showed that the AEF treatment is functional in enhancing the AEF –induced senescence in the GBM cells via an apoptosis- independent mechanism. This research concludes that this mode of treatment is a trustworthy protocol that can be effectively employed to overcome the limitations of the conventional mode of treatment on GBM.

Keywords: alternating electric fields, senescence, glioblastoma, cell death

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Authors: Ziad Abdeldayem, Jakub Markiewicz, Kunal Kansara, Laura Edwards

Abstract:

Airborne Laser Scanning (ALS) is one of the main technologies for generating high-resolution digital terrain models (DTMs). DTMs are crucial to several applications, such as topographic mapping, flood zone delineation, geographic information systems (GIS), hydrological modelling, spatial analysis, etc. Laser scanning system generates irregularly spaced three-dimensional cloud of points. Raw ALS data are mainly ground points (that represent the bare earth) and non-ground points (that represent buildings, trees, cars, etc.). Removing all the non-ground points from the raw data is referred to as filtering. Filtering heavily forested areas is considered a difficult and challenging task as the canopy stops laser pulses from reaching the terrain surface. This research presents an approach for removing non-ground points from raw ALS data in densely forested areas. Smoothing splines are exploited to interpolate and fit the noisy ALS data. The presented filter utilizes a weight function to allocate weights for each point of the data. Furthermore, unlike most of the methods, the presented filtering algorithm is designed to be automatic. Three different forested areas in the United Kingdom are used to assess the performance of the algorithm. The results show that the generated DTMs from the filtered data are accurate (when compared against reference terrain data) and the performance of the method is stable for all the heavily forested data samples. The average root mean square error (RMSE) value is 0.35 m.

Keywords: airborne laser scanning, digital terrain models, filtering, forested areas

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Authors: M. Yilmaz, I. Yilmaz, M. Uysal

Abstract:

The Earth system generates different phenomena that are observable at the surface of the Earth such as mass deformations and displacements leading to plate tectonics, earthquakes, and volcanism. The dynamic processes associated with the interior, surface, and atmosphere of the Earth affect the three pillars of geodesy: shape of the Earth, its gravity field, and its rotation. Geodesy establishes a characteristic structure in order to define, monitor, and predict of the whole Earth system. The traditional and new instruments, observables, and techniques in geodesy are related to the gravity field. Therefore, the geodesy monitors the gravity field and its temporal variability in order to transform the geodetic observations made on the physical surface of the Earth into the geometrical surface in which positions are mathematically defined. In this paper, the main components of the gravity field modeling, (Free-air and Bouguer) gravity anomalies are calculated via recent global models (EGM2008, EIGEN6C4, and GECO) over a selected study area. The model-based gravity anomalies are compared with the corresponding terrestrial gravity data in terms of standard deviation (SD) and root mean square error (RMSE) for determining the best fit global model in the study area at a regional scale in Turkey. The least SD (13.63 mGal) and RMSE (15.71 mGal) were obtained by EGM2008 for the Free-air gravity anomaly residuals. For the Bouguer gravity anomaly residuals, EIGEN6C4 provides the least SD (8.05 mGal) and RMSE (8.12 mGal). The results indicated that EIGEN6C4 can be a useful tool for modeling the gravity field of the Earth over the study area.

Keywords: free-air gravity anomaly, Bouguer gravity anomaly, global model, land gravity

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