Search results for: threshold correction

Authors: Gerhard Gritsch, Ana Skupch, Manfred Hartmann, Wolfgang Frühwirt, Hannes Perko, Dieter Grossegger, Tilmann Kluge

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Rehabilitation of stroke patients is dominated by classical physiotherapy. Nowadays, a field of research is the application of neurofeedback techniques in order to help stroke patients to get rid of their motor impairments. Especially, if a certain limb is completely paralyzed, neurofeedback is often the last option to cure the patient. Certain exercises, like the imagination of the impaired motor function, have to be performed to stimulate the neuroplasticity of the brain, such that in the neighboring parts of the injured cortex the corresponding activity takes place. During the exercises, it is very important to keep the motivation of the patient at a high level. For this reason, the missing natural feedback due to a movement of the effected limb may be replaced by a synthetic feedback based on the motor-related brain function. To generate such a synthetic feedback a system is needed which measures, detects, localizes and visualizes the motor related µ-rhythm. Fast therapeutic success can only be achieved if the feedback features high specificity, comes in real-time and without large delay. We describe such an approach that offers a 3D visualization of µ-rhythms in real time with a delay of 500ms. This is accomplished by combining smart EEG preprocessing in the frequency domain with source localization techniques. The algorithm first selects the EEG channel featuring the most prominent rhythm in the alpha frequency band from a so-called motor channel set (C4, CZ, C3; CP6, CP4, CP2, CP1, CP3, CP5). If the amplitude in the alpha frequency band of this certain electrode exceeds a threshold, a µ-rhythm is detected. To prevent detection of a mixture of posterior alpha activity and µ-activity, the amplitudes in the alpha band outside the motor channel set are not allowed to be in the same range as the main channel. The EEG signal of the main channel is used as template for calculating the spatial distribution of the µ - rhythm over all electrodes. This spatial distribution is the input for a inverse method which provides the 3D distribution of the µ - activity within the brain which is visualized in 3D as color coded activity map. This approach mitigates the influence of lid artifacts on the localization performance. The first results of several healthy subjects show that the system is capable of detecting and localizing the rarely appearing µ-rhythm. In most cases the results match with findings from visual EEG analysis. Frequent eye-lid artifacts have no influence on the system performance. Furthermore, the system will be able to run in real-time. Due to the design of the frequency transformation the processing delay is 500ms. First results are promising and we plan to extend the test data set to further evaluate the performance of the system. The relevance of the system with respect to the therapy of stroke patients has to be shown in studies with real patients after CE certification of the system. This work was performed within the project ‘LiveSolo’ funded by the Austrian Research Promotion Agency (FFG) (project number: 853263).

Keywords: real-time EEG neuroimaging, neurofeedback, stroke, EEG–signal processing, rehabilitation

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Authors: V. Saccà, A. Sarica, F. Novellino, S. Barone, T. Tallarico, E. Filippelli, A. Granata, P. Valentino, A. Quattrone

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The work aim was to evaluate how well Random Forest (RF) and Support Vector Machine (SVM) algorithms could support the early diagnosis of Multiple Sclerosis (MS) from resting-state functional connectivity data. In particular, we wanted to explore the ability in distinguishing between controls and patients of mean signals extracted from ICA components corresponding to 15 well-known networks. Eighteen patients with early-MS (mean-age 37.42±8.11, 9 females) were recruited according to McDonald and Polman, and matched for demographic variables with 19 healthy controls (mean-age 37.55±14.76, 10 females). MRI was acquired by a 3T scanner with 8-channel head coil: (a)whole-brain T1-weighted; (b)conventional T2-weighted; (c)resting-state functional MRI (rsFMRI), 200 volumes. Estimated total lesion load (ml) and number of lesions were calculated using LST-toolbox from the corrected T1 and FLAIR. All rsFMRIs were pre-processed using tools from the FMRIB's Software Library as follows: (1) discarding of the first 5 volumes to remove T1 equilibrium effects, (2) skull-stripping of images, (3) motion and slice-time correction, (4) denoising with high-pass temporal filter (128s), (5) spatial smoothing with a Gaussian kernel of FWHM 8mm. No statistical significant differences (t-test, p < 0.05) were found between the two groups in the mean Euclidian distance and the mean Euler angle. WM and CSF signal together with 6 motion parameters were regressed out from the time series. We applied an independent component analysis (ICA) with the GIFT-toolbox using the Infomax approach with number of components=21. Fifteen mean components were visually identified by two experts. The resulting z-score maps were thresholded and binarized to extract the mean signal of the 15 networks for each subject. Statistical and machine learning analysis were then conducted on this dataset composed of 37 rows (subjects) and 15 features (mean signal in the network) with R language. The dataset was randomly splitted into training (75%) and test sets and two different classifiers were trained: RF and RBF-SVM. We used the intrinsic feature selection of RF, based on the Gini index, and recursive feature elimination (rfe) for the SVM, to obtain a rank of the most predictive variables. Thus, we built two new classifiers only on the most important features and we evaluated the accuracies (with and without feature selection) on test-set. The classifiers, trained on all the features, showed very poor accuracies on training (RF:58.62%, SVM:65.52%) and test sets (RF:62.5%, SVM:50%). Interestingly, when feature selection by RF and rfe-SVM were performed, the most important variable was the sensori-motor network I in both cases. Indeed, with only this network, RF and SVM classifiers reached an accuracy of 87.5% on test-set. More interestingly, the only misclassified patient resulted to have the lowest value of lesion volume. We showed that, with two different classification algorithms and feature selection approaches, the best discriminant network between controls and early MS, was the sensori-motor I. Similar importance values were obtained for the sensori-motor II, cerebellum and working memory networks. These findings, in according to the early manifestation of motor/sensorial deficits in MS, could represent an encouraging step toward the translation to the clinical diagnosis and prognosis.

Keywords: feature selection, machine learning, multiple sclerosis, random forest, support vector machine

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Authors: A. C. Facin, M. C. Maronezi , M. P. Menezes, G. L. Montanhim, L. Pavan, M. A. R. Feliciano, R. P. Nociti, R. A. R. Uscategui, P. C. Moraes

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The incidence of brachycephalic syndrome (BS) in the clinical routine of small animals has increased significantly giving the higher proportion of brachycephalic pets in the last years and has been considered as an animal welfare problem. The treatment of BS is surgical and the clinical signs related can be considerably attenuated. Nevertheless, the systemic effects of the BS are still poorly reported and little is known about these when the surgical correction is not performed early. Affected dogs are more likely to develop cardiopulmonary, gastrointestinal and sleep disorders in which the chronic hypoxemia plays a major role. This syndrome is compared with the obstructive sleep apnea (OSA) in humans, both considered as causes of systemic and metabolic dysfunction. Among the several consequences of the BS little is known if the syndrome also affects the hepatic tissue of brachycephalic patients. Elastography is a promising ultrasound technique that evaluates tissue elasticity and has been recently used with the purpose of diagnosis of liver fibrosis. In medicine, it is a growing concern regarding the hepatic injury of patients affected by OSA. This prospective study hypothesizes if there is any consequence of BS in the hepatic parenchyma of brachycephalic dogs that don’t receive any surgical treatment. This study was conducted following the approval of the Animal Ethics and Welfare Committee of the Faculdade de Ciências Agrárias e Veterinárias, UNESP, Campus Jaboticabal, Brazil (protocol no 17944/2017) and funded by Sao Paulo Research Foundation (FAPESP, process no 2017/24809-4). The methodology was based in ARFI elastography using the ACUSON S2000/SIEMENS device, with convex multifrequential transducer and specific software as well as clinical evaluation of the syndrome, in order to determine if they can be used as a prognostic non-invasive tool. On quantitative elastography, it was collected three measures of shear wave velocity (meters per second) and depth in centimeters in the left lateral, left medial, right lateral, right medial and caudate lobe of the liver. The brachycephalic patients, 16 pugs and 30 french bulldogs, were classified using a previously established 4-point functional grading system based on clinical evaluation before and after a 3-minute exercise tolerance test already established and validated. The control group was based on the same features collected in 22 beagles. The software R version 3.3.0 was used for the analysis and the significance level was set at 0.05. The data were analysed for normality of residuals and homogeneity of variances by Shapiro-Wilks test. Comparisons of parametric continuous variables between breeds were performed by using ANOVA with a post hoc test for pair wise comparison. The preliminary results show significant statistic differences between the brachycephalic groups and the control group in all lobes analysed (p ≤ 0,05), with higher values of shear wave velocities in the hepatic tissue of brachycephalic dogs. In this context, the results obtained in this study contributes to the understanding of BS as well as its consequences in our patients, reflecting in evidence that one more systemic consequence of the syndrome may occur in brachycephalic patients, which was not related in the veterinary literature yet.

Keywords: airway obstruction, brachycephalic airway obstructive syndrome, hepatic injury, obstructive sleep apnea

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Authors: Adrian W. Egger, Savvas P. Triantafyllou, Eleni N. Chatzi

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The scaled boundary finite element method (SBFEM) is a semi-analytical numerical method, which introduces a scaling center in each element’s domain, thus transitioning from a Cartesian reference frame to one resembling polar coordinates. Consequently, an analytical solution is achieved in radial direction, implying that only the boundary need be discretized. The only limitation imposed on the resulting polygonal elements is that they remain star-convex. Further arbitrary p- or h-refinement may be applied locally in a mesh. The polygonal nature of SBFEM elements has been exploited in quadtree meshes to alleviate all issues conventionally associated with hanging nodes. Furthermore, since in 2D this results in only 16 possible cell configurations, these are precomputed in order to accelerate the forward analysis significantly. Any cells, which are clipped to accommodate the domain geometry, must be computed conventionally. However, since SBFEM permits polygonal elements, significantly coarser meshes at comparable accuracy levels are obtained when compared with conventional quadtree analysis, further increasing the computational efficiency of this scheme. The generalized stress intensity factors (gSIFs) are computed by exploiting the semi-analytical solution in radial direction. This is initiated by placing the scaling center of the element containing the crack at the crack tip. Taking an analytical limit of this element’s stress field as it approaches the crack tip, delivers an expression for the singular stress field. By applying the problem specific boundary conditions, the geometry correction factor is obtained, and the gSIFs are then evaluated based on their formal definition. Since the SBFEM solution is constructed as a power series, not unlike mode superposition in FEM, the two modes contributing to the singular response of the element can be easily identified in post-processing. Compared to the extended finite element method (XFEM) this approach is highly convenient, since neither enrichment terms nor a priori knowledge of the singularity is required. Computation of the gSIFs by SBFEM permits exceptional accuracy, however, when combined with hybrid quadtrees employing linear elements, this does not always hold. Nevertheless, it has been shown that crack propagation schemes are highly effective even given very coarse discretization since they only rely on the ratio of mode one to mode two gSIFs. The absolute values of the gSIFs may still be subject to large errors. Hence, we propose a post-processing scheme, which minimizes the error resulting from the approximation space of the cracked element, thus limiting the error in the gSIFs to the discretization error of the quadtree mesh. This is achieved by h- and/or p-refinement of the cracked element, which elevates the amount of modes present in the solution. The resulting numerical description of the element is highly accurate, with the main error source now stemming from its boundary displacement solution. Numerical examples show that this post-processing procedure can significantly improve the accuracy of the computed gSIFs with negligible computational cost even on coarse meshes resulting from hybrid quadtrees.

Keywords: linear elastic fracture mechanics, generalized stress intensity factors, scaled finite element method, hybrid quadtrees

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Authors: Nitika Sharma, Yogesh Jain

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Introduction: An efficient Information System helps in improving the service delivery as well provides the foundation for policy and regulation of other building blocks of Health System. Health care organizations require an integrated working of its various sub-systems. An efficient EMR software boosts the teamwork amongst the various sub-systems thereby resulting in improved service delivery. Although there has been a huge impetus to EMR under the Digital India initiative, it has still not been mandated in India. It is generally implemented in huge funded public or private healthcare organizations only. Objective: The study was conducted to understand the factors that lead to the successful adoption of an affordable EMR in the low level healthcare organization. It intended to understand the design of the EMR and address the solutions to the challenges faced in adoption of the EMR. Methodology: The study was conducted in a non-profit registered Healthcare organization that has been providing healthcare facilities to more than 2500 villages including certain areas that are difficult to access. The data was collected with help of field notes, in-depth interviews and participant observation. A total of 16 participants using the EMR from different departments were enrolled via purposive sampling technique. The participants included in the study were working in the organization before the implementation of the EMR system. The study was conducted in one month period from 25 June-20 July 2018. The Ethical approval was taken from the institute along with prior approval of the participants. Data analysis: A word document of more than 4000 words was obtained after transcribing and translating the answers of respondents. It was further analyzed by focused coding, a line by line review of the transcripts, underlining words, phrases or sentences that might suggest themes to do thematic narrative analysis. Results: Based on the answers the results were thematically grouped under four headings: 1. governance of organization, 2. architecture and design of the software, 3. features of the software, 4. challenges faced in adoption and the solutions to address them. It was inferred that the successful implementation was attributed to the easy and comprehensive design of the system which has facilitated not only easy data storage and retrieval but contributes in constructing a decision support system for the staff. Portability has lead to increased acceptance by physicians. The proper division of labor, increased efficiency of staff, incorporation of auto-correction features and facilitation of task shifting has lead to increased acceptance amongst the users of various departments. Geographical inhibitions, low computer literacy and high patient load were the major challenges faced during its implementation. Despite of dual efforts made both by the architects and administrators to combat these challenges, there are still certain ongoing challenges faced by organization. Conclusion: Whenever any new technology is adopted there are certain innovators, early adopters, late adopters and laggards. The same pattern was followed in adoption of this software. He challenges were overcome with joint efforts of organization administrators and users as well. Thereby this case study provides a framework of implementing similar systems in public sector of countries that are struggling for digitizing the healthcare in presence of crunch of human and financial resources.

Keywords: EMR, healthcare technology, e-health, EHR

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Authors: Khan Farhan Rafat, Riaz Ahmed

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Renowned offshore organizations are drifting towards collaborative exertion to win and implement international projects for business gains. However, devoid of financial constraints, with the availability of skilled professionals, and despite improved project management practices through state-of-the-art tools and techniques, project delays have become a norm these days. This situation calls for exploring the factor(s) affecting the bonding between project management performance and project success. In the context of the well-known 3M’s of project management (that is, manpower, machinery, and materials), machinery and materials are dependent upon manpower. Because the body of knowledge inveterate on the influence of national culture on men, hence, the realization of the impact on the link between project management performance and project success need to be investigated in detail to arrive at the possible cause(s) of project delays. This research initiative was, therefore, undertaken to fill the research gap. The unit of analysis for the proposed research excretion was the individuals who had worked on skyscraper construction projects. In reverent studies, project management is best described using construction examples. It is due to this reason that the project oriented city of Dubai was chosen to reconnoiter on causes of project delays. A structured questionnaire survey was disseminated online with the courtesy of the Project Management Institute local chapter to carry out the cross-sectional study. The Construction Industry Institute, Austin, of the United States of America along with 23 high-rise builders in Dubai were also contacted by email requesting for their contribution to the study and providing them with the online link to the survey questionnaire. The reliability of the instrument was warranted using Cronbach’s alpha coefficient of 0.70. The appropriateness of sampling adequacy and homogeneity in variance was ensured by keeping Kaiser–Meyer–Olkin (KMO) and Bartlett’s test of sphericity in the range ≥ 0.60 and < 0.05, respectively. Factor analysis was used to verify construct validity. During exploratory factor analysis, all items were loaded using a threshold of 0.4. Four hundred and seventeen respondents, including members from top management, project managers, and project staff, contributed to the study. The link between project management performance and project success was significant at 0.01 level (2-tailed), and 0.05 level (2-tailed) for Pearson’s correlation. Before initiating the moderator analysis test for linearity, multicollinearity, outliers, leverage points and influential cases, test for homoscedasticity and normality were carried out which are prerequisites for conducting moderator review. The moderator analysis, using a macro named PROCESS, was performed to verify the hypothesis that national culture has an influence on the said link. The empirical findings, when compared with Hofstede's results, showed high power distance as the cause of construction project delays in Dubai. The research outcome calls for the project sponsors and top management to reshape their project management strategy and allow for low power distance between management and project personnel for timely completion of projects.

Keywords: causes of construction project delays, construction industry, construction management, power distance

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Authors: Yen Yen Tan, Lynn Lam, Cynthia Lam, Angela Koh, Edwin Seng

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Entrepreneurial education plays a crucial role in nurturing future innovators and change-makers. Over time, significant progress has been made in refining instructional approaches to develop the necessary skills among learners effectively. Two highly valuable frameworks, Kearney's "4 Principles of Entrepreneurial Pedagogy" and Bloom's "Three Domains of Learning," serve as guiding principles in entrepreneurial education. Kearney's principles align with experiential and student-centric learning, which are crucial for cultivating an entrepreneurial mindset. The potential synergies between these frameworks hold great promise for enhancing entrepreneurial acumen among students. However, despite this potential, their integration remains largely unexplored. This study aims to bridge this gap by building upon the Business Essentials through Action (BETA) module and investigating its contributions to nurturing the entrepreneurial mindset. This study employs a quasi-experimental mixed-methods approach, combining quantitative and qualitative elements to ensure comprehensive and insightful data. A cohort of 235 students participated, with 118 enrolled in the BETA module and 117 in a traditional curriculum. Their Personal Entrepreneurial Competencies (PECs) were assessed before admission (pre-Y1) and one year into the course (post-Y1) using a comprehensive 55-item PEC questionnaire, enabling measurement of critical traits such as opportunity-seeking, persistence, and risk-taking. Rigorous computations of individual entrepreneurial competencies and overall PEC scores were performed, including a correction factor to mitigate potential self-assessment bias. The orchestration of Kearney's principles and Bloom's domains within the BETA module necessitates a granular examination. Here, qualitative revelations surface, courtesy of structured interviews aligned with contemporary research methodologies. These interviews act as a portal, ushering us into the transformative journey undertaken by students. Meanwhile, the study pivots to explore the BETA module's influence on students' entrepreneurial competencies from the vantage point of faculty members. A symphony of insights emanates from intimate focus group discussions featuring six dedicated lecturers, who share their perceptions, experiences, and reflective narratives, illuminating the profound impact of pedagogical practices embedded within the BETA module. Preliminary findings from ongoing data analysis indicate promising results, showcasing a substantial improvement in entrepreneurial skills among students participating in the BETA module. This study promises not only to elevate students' entrepreneurial competencies but also to illuminate the broader canvas of applicability for Kearney's principles and Bloom's domains. The dynamic interplay of quantitative analyses, proffering precise competency metrics, and qualitative revelations, delving into the nuanced narratives of transformative journeys, engenders a holistic understanding of this educational endeavour. Through a rigorous quasi-experimental mixed-methods approach, this research aims to establish the BETA module's effectiveness in fostering entrepreneurial acumen among students at Singapore Polytechnic, thereby contributing valuable insights to the broader discourse on educational methodologies.

Keywords: entrepreneurial education, experiential learning, pedagogical frameworks, innovative competencies

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Authors: Abdulkadir Sarauta

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Almost every type of industrial process involves the release of trace quantity of toxic organic and inorganic compound that up in receiving water bodies, this study was aimed at assessing the Persistent Organic Pollutant Level in Challawa River Basin of Kano State, Nigeria. And the research formed the basis of identifying the presence of PCBs and PAHs in receiving water bodies in the study area, assessing the PCBs and PAHs concentration in receiving water body of Challawa system, evaluate the concentration level of PCBs and PAHs in fishes in the study area, determine the concentration level of PCBs and PAHs in crops irrigated in the study area as well as compare the concentration of PCBs and PAHs with the acceptable limit set by Nigerian, EU, U.S and WHO standard. Data were collected using reconnaissance survey, site inspection, field survey, laboratory experiment as well as secondary data source. A total of 78 samples were collected through stratified systematic random sampling (i.e., 26 samples for each of water, crops and fish) three sampling points were chosen and designated A, B and C along the stretch of the river (i.e. up, middle, and downstream) from Yan Danko Bridge to Tambirawa bridge. The result shows that the Polychlorinated biphenyls (PCBs) was not detected while, polycyclic aromatic hydrocarbons (PAHs) was detected in the whole samples analysed at the trench of Challawa River basin in order to assess the contribution of human activities to global environmental pollution. The total concentrations of ΣPAH and ΣPCB ranges between 0.001 to 0.087mg/l and 0.00 to 0.00mg/l of water samples While, crops samples ranges between 2.0ppb to 8.1ppb and fish samples ranges from 2.0 to 6.7ppb.The whole samples are polluted because most of the parameters analyzed exceed the threshold limits set by WHO, Nigerian, U.S and EU standard. The analytical results revealed that some chemicals are present in water, crops and fishes are significantly very high at Zamawa village which is very close to Challawa industrial estate and also is main effluent discharge point and drinking water around study area is not potable for consumption. Analysis of Variance was obtained by Bartlett’s test performance. There is only significant difference in water because the P < 0.05 level of significant, But there is no difference in crops concentration they have the same performance, likes wise in the fishes. It is said to be of concern to health hazard which will increase incidence of tumor related diseases such as skin, lungs, bladder, gastrointestinal cancer, this show there is high failure of pollution abatement measures in the area. In conclusion, it can be said that industrial activities and effluent has impact on Challawa River basin and its environs especially those that are living in the immediate surroundings. Arising from the findings of this research some recommendations were made the industries should treat their liquid properly by installing modern treatment plants.

Keywords: Challawa River Basin, organic, persistent, pollutant

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Authors: Tatiana G. Smirnova, Stan G. Benjamin

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Rapid Update Cycle (RUC) land surface model (LSM) was a land-surface component in several generations of operational weather prediction models at the National Center for Environment Prediction (NCEP) at the National Oceanic and Atmospheric Administration (NOAA). It was designed for short-range weather predictions with an emphasis on severe weather and originally was intentionally simple to avoid uncertainties from poorly known parameters. Nevertheless, the RUC LSM, when coupled with the hourly-assimilating atmospheric model, can produce a realistic evolution of time-varying soil moisture and temperature, as well as the evolution of snow cover on the ground surface. This result is possible only if the soil/vegetation/snow component of the coupled weather prediction model has sufficient skill to avoid long-term drift. RUC LSM was first implemented in the operational NCEP Rapid Update Cycle (RUC) weather model in 1998 and later in the Weather Research Forecasting Model (WRF)-based Rapid Refresh (RAP) and High-resolution Rapid Refresh (HRRR). Being available to the international WRF community, it was implemented in operational weather models in Austria, New Zealand, and Switzerland. Based on the feedback from the US weather service offices and the international WRF community and also based on our own validation, RUC LSM has matured over the years. Also, a sea-ice module was added to RUC LSM for surface predictions over the Arctic sea-ice. Other modifications include refinements to the snow model and a more accurate specification of albedo, roughness length, and other surface properties. At present, RUC LSM is being tested in the regional application of the Unified Forecast System (UFS). The next generation UFS-based regional Rapid Refresh FV3 Standalone (RRFS) model will replace operational RAP and HRRR at NCEP. Over time, RUC LSM participated in several international model intercomparison projects to verify its skill using observed atmospheric forcing. The ESM-SnowMIP was the last of these experiments focused on the verification of snow models for open and forested regions. The simulations were performed for ten sites located in different climatic zones of the world forced with observed atmospheric conditions. While most of the 26 participating models have more sophisticated snow parameterizations than in RUC, RUC LSM got a high ranking in simulations of both snow water equivalent and surface temperature. However, ESM-SnowMIP experiment also revealed some issues in the RUC snow model, which will be addressed in this paper. One of them is the treatment of grid cells partially covered with snow. RUC snow module computes energy and moisture budgets of snow-covered and snow-free areas separately by aggregating the solutions at the end of each time step. Such treatment elevates the importance of computing in the model snow cover fraction. Improvements to the original simplistic threshold-based approach have been implemented and tested both offline and in the coupled weather model. The detailed description of changes to the snow cover fraction and other modifications to RUC soil and snow parameterizations will be described in this paper.

Keywords: land-surface models, weather prediction, hydrology, boundary-layer processes

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Authors: Nejmeddine Ouhichi, Fethi Lachaal, Radhouane Hamdi, Olivier Grunberger

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Located in Cap Bon peninsula (Tunisia), the Lebna dam was built in 1987 to balance local water salt intrusion taking place in the coastal aquifer of Korba. The first intention was to reduce coastal groundwater over-pumping by supplying surface water to a large irrigation system. The unpredicted beneficial effect was recorded with the occurrence of a direct localized recharge to the coastal aquifer by leakage through the geological material of the southern bank of the lake. The hydrological balance of the reservoir dam gave an estimation of the annual leakage volume, but dynamic processes and sound quantification of recharge inputs are still required to understand the localized effect of the recharge in terms of piezometry and quality. Present work focused on simulating the recharge process to confirm the hypothesis, and established a sound quantification of the water supply to the coastal aquifer and extend it to multi-annual effects. A spatial frame of 30km² was used for modeling. Intensive outcrops and geophysical surveys based on 68 electrical resistivity soundings were used to characterize the aquifer 3D geometry and the limit of the Plio-quaternary geological material concerned by the underground flow paths. Permeabilities were determined using 17 pumping tests on wells and piezometers. Six seasonal piezometric surveys on 71 wells around southern reservoir dam banks were performed during the 2019-2021 period. Eight monitoring boreholes of high frequency (15min) piezometric data were used to examine dynamical aspects. Model boundary conditions were specified using the geophysics interpretations coupled with the piezometric maps. The dam-groundwater flow model was performed using Visual MODFLOW software. Firstly, permanent state calibration based on the first piezometric map of February 2019 was established to estimate the permanent flow related to the different reservoir levels. Secondly, piezometric data for the 2019-2021 period were used for transient state calibration and to confirm the robustness of the model. Preliminary results confirmed the temporal link between the reservoir level and the localized recharge flow with a strong threshold effect for levels below 16 m.a.s.l. The good agreement of computed flow through recharge cells on the southern banks and hydrological budget of the reservoir open the path to future simulation scenarios of the dilution plume imposed by the localized recharge. The dam reservoir-groundwater flow-model simulation results approve a potential for storage of up to 17mm/year in existing wells, under gravity-feed conditions during level increases on the reservoir into the three years of operation. The Lebna dam groundwater flow model characterized a spatiotemporal relation between groundwater and surface water.

Keywords: leakage, MODFLOW, saltwater intrusion, surface water-groundwater interaction

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Authors: Hong Mengdi, Li Jianan, Ji Fei, Chen Aiting, Wang Qian

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Objective: To overcome the communication barriers that audiologists encounter during cochlear implant mapping, particularly the challenge of eliciting subjective feedback from recipients regarding electrical stimulation, and to enhance the capabilities of existing technologies, we teamed up with software engineers to design an interactive approach for patient-audiologist communication. This approach employs a tablet (PAD) as the interface for a communication and feedback system between patients and audiologists during the mapping process, known as the Cochlear Implant Mapping Assistance System. Methods: Capitalizing on the touchscreen functionality of the PAD, the recipients' subjective feedback during cochlear implant mapping is instantly transmitted to the audiologist's mapping computer. The system acts as a platform for auditory assessment instruments, facilitating immediate evaluation of recipients' post-mapping hearing and speech discrimination capabilities. Furthermore, the system is designed to augment the visual reinforcement audiometry (VRA) process. The system consists of six modules, including three testing projects: loudness testing, hearing threshold testing, and loudness balance testing; two assessment projects: warble tone testing and digit speech testing; and one VRA animation project. It also incorporates speech-to-text and text input display functions tailored to accommodate speech communication difficulties in hearing-impaired individuals, with pre-installed common exchange content between audiologists and recipients. Audiologists can input sentences by selecting options. The system supports switching between Chinese and English versions, suitable for audiologists and recipients who use English, facilitating international application of the system. Results: The Cochlear Implant Mapping Assistance System has been in use for over a year in the Auditory Implant Center of the Department of Otology and Neurotology, Medical Center of Otology and Head & Neck Surgery, Chinese PLA General Hospital, with more than 300 recipients using this mapping system. Currently, the system operates stably, with both audiologists and recipients providing positive feedback, indicating a significant improvement over previous methods. It is particularly well-received by pediatric recipients, significantly enhancing the work efficiency of audiologists and improving the feedback efficiency and accuracy of recipients. The system enhances the comprehensibility for cochlear implant recipients, improves wearing comfort and user experience, facilitates cochlear implant auditory mapping, and increases the collection of previously challenging-to-obtain data during the existing assisted mapping process, such as loudness testing data, electrical stimulation testing data, warble tone testing data, loudness balance testing data, digit speech testing data, and visual reinforcement audiometry testing data. Real-time data recording improves the accuracy of assisted mapping. The interface design is meticulously crafted to accommodate patients of varying ages and cognitive abilities, featuring an intuitive design that allows for effortless, guidance-free use by patients.

Keywords: audiologist, subjective feedback, mapping, cochlear implant

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Authors: Eiji Nakamachi, Tsuyoshi Eguchi, Sayo Yamamoto, Yusuke Morita, H. Sakamoto

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In this study, we aim to reveal the relationship between the meniscal tearing and the articular cartilage injury of knee joint by using the dynamic explicit finite element (FE) method. Meniscal injuries reduce its functional ability and consequently increase the load on the articular cartilage of knee joint. In order to prevent the induction of osteoarthritis (OA) caused by meniscal injuries, many medical treatment techniques, such as artificial meniscus replacement and meniscal regeneration, have been developed. However, it is reported that these treatments are not the comprehensive methods. In order to reveal the fundamental mechanism of OA induction, the mechanical characterization of meniscus under the condition of normal and injured states is carried out by using FE analyses. At first, a FE model of the human knee joint in the case of normal state – ‘intact’ - was constructed by using the magnetron resonance (MR) tomography images and the image construction code, Materialize Mimics. Next, two types of meniscal injury models with the radial tears of medial and lateral menisci were constructed. In FE analyses, the linear elastic constitutive law was adopted for the femur and tibia bones, the visco-hyperelastic constitutive law for the articular cartilage, and the visco-anisotropic hyperelastic constitutive law for the meniscus, respectively. Material properties of articular cartilage and meniscus were identified using the stress-strain curves obtained by our compressive and the tensile tests. The numerical results under the normal walking condition revealed how and where the maximum compressive stress occurred on the articular cartilage. The maximum compressive stress and its occurrence point were varied in the intact and two meniscal tear models. These compressive stress values can be used to establish the threshold value to cause the pathological change for the diagnosis. In this study, FE analyses of knee joint were carried out to reveal the influence of meniscal injuries on the cartilage injury. The following conclusions are obtained. 1. 3D FE model, which consists femur, tibia, articular cartilage and meniscus was constructed based on MR images of human knee joint. The image processing code, Materialize Mimics was used by using the tetrahedral FE elements. 2. Visco-anisotropic hyperelastic constitutive equation was formulated by adopting the generalized Kelvin model. The material properties of meniscus and articular cartilage were determined by curve fitting with experimental results. 3. Stresses on the articular cartilage and menisci were obtained in cases of the intact and two radial tears of medial and lateral menisci. Through comparison with the case of intact knee joint, two tear models show almost same stress value and higher value than the intact one. It was shown that both meniscal tears induce the stress localization in both medial and lateral regions. It is confirmed that our newly developed FE analysis code has a potential to be a new diagnostic system to evaluate the meniscal damage on the articular cartilage through the mechanical functional assessment.

Keywords: finite element analysis, hyperelastic constitutive law, knee joint injury, meniscal tear, stress concentration

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Authors: Gagandeep Singh Digra, Pawan Kumar, Mandeep Kaur Sidhu

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INTRODUCTION: Chronic Progressive External Ophthalmoplegia (CPEO), also known as Progressive External Ophthalmoplegia (PEO), is a type of eye disorder characterized by a loss of the muscle functions involved in eye and eyelid movement. CPEO can be caused by mutations in mitochondrial DNA. It typically manifests in young adults with bilateral and progressive ptosis as the most common presentation but can also present with difficulty swallowing (dysphagia) and general weakness of the skeletal muscles (myopathy), particularly in the neck, arms, or legs. CASE PRESENTATION: This is a case discussion of 3 cousins who presented to our clinic. A 23-year-old male with past surgical history (PSH) of ptosis repair 2 years ago presented with a chief complaint of nasal intonation for 1.5 years associated with difficulty swallowing. The patient also complained of nasal regurgitation of liquids. He denied any headaches, fever, seizures, weakness of arms or legs, urinary complaints or changes in bowel habits. Physical Examination was positive for facial muscle weakness, including an inability to lift eyebrows (Frontalis), inability to close eyes tightly (Orbicularis Oculi), corneal reflex absent bilaterally, difficulty clenching jaw (Masseter muscle), difficulty smiling (Zygomaticus major), inability to elevate upper lip (Zygomaticus minor). Another cousin of the first patient, a 25-year-old male with no past medical history, presented with complaints of nasal intonation for 2 years associated with difficulty swallowing. He denied a history of nasal regurgitation, headaches, fever, seizures, weakness, urinary complaints or changes in bowel habits. Physical Examination showed facial muscle weakness of the Frontalis muscle, Orbicularis Oculi muscle, Masseter Muscle, Zygomaticus Major, Zygomaticus Minor and absent corneal reflexes. A 28-year-old male, a cousin of the first two patients, presented with chief complaints of ptosis and nasal intonation for the last 8 years. He also complained of difficulty swallowing and nasal regurgitation of liquids. His physical examination showed facial muscle weakness, including frontalis muscle (inability to lift eyebrows), Orbicularis Oculi (inability to close eyes tightly), absent corneal reflexes bilaterally, Zygomaticus Major (difficulty smiling), and Zygomaticus Minor (inability to elevate upper lip). MRI brain and visual field of all the patients were normal. Differential diagnoses, including Grave’s disease, Myasthenia Gravis and Glioma, were ruled out. Due to financial reasons, muscle biopsy could not be pursued. Pedigree analysis revealed only males were affected, likely due to maternal inheritance, so the clinical diagnosis of CPEO was made. The patients underwent symptomatic management, including ptosis surgical correction for the third patient. CONCLUSION: Chronic Progressive External Ophthalmoplegia (CPEO), a rare case entity, occurs in young adults as a manifestation of mitochondrial myopathy. There are three modes of transmission- maternal transmission associated with mitochondrial point mutations, autosomal recessive, and autosomal dominant. CPEO can sometimes be difficult to diagnose, especially in asymmetric presentation. Therefore, it is crucial to keep it in differential diagnosis to avoid delay in diagnosis.

Keywords: neurology, chronic, progressive, ophthalmoplegia

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Authors: Ammar Alali, Mahmoud Abughaban

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Cost reduction and drilling optimization is the goal of many drilling operators. Historically, stuck pipe incidents were a major segment of non-productive time (NPT) associated costs. Traditionally, stuck pipe problems are part of the operations and solved post-sticking. However, the real key to savings and success is in predicting the stuck pipe incidents and avoiding the conditions leading to its occurrences. Previous attempts in stuck-pipe predictions have neglected the local geology of the problem. The proposed predictive tool utilizes geophysical data processing techniques and Machine Learning (ML) algorithms to predict drilling activities events in real-time using surface drilling data with minimum computational power. The method combines two types of analysis: (1) real-time prediction, and (2) cause analysis. Real-time prediction aggregates the input data, including historical drilling surface data, geological formation tops, and petrophysical data, from wells within the same field. The input data are then flattened per the geological formation and stacked per stuck-pipe incidents. The algorithm uses two physical methods (stacking and flattening) to filter any noise in the signature and create a robust pre-determined pilot that adheres to the local geology. Once the drilling operation starts, the Wellsite Information Transfer Standard Markup Language (WITSML) live surface data are fed into a matrix and aggregated in a similar frequency as the pre-determined signature. Then, the matrix is correlated with the pre-determined stuck-pipe signature for this field, in real-time. The correlation used is a machine learning Correlation-based Feature Selection (CFS) algorithm, which selects relevant features from the class and identifying redundant features. The correlation output is interpreted as a probability curve of stuck pipe incidents prediction in real-time. Once this probability passes a fixed-threshold defined by the user, the other component, cause analysis, alerts the user of the expected incident based on set pre-determined signatures. A set of recommendations will be provided to reduce the associated risk. The validation process involved feeding of historical drilling data as live-stream, mimicking actual drilling conditions, of an onshore oil field. Pre-determined signatures were created for three problematic geological formations in this field prior. Three wells were processed as case studies, and the stuck-pipe incidents were predicted successfully, with an accuracy of 76%. This accuracy of detection could have resulted in around 50% reduction in NPT, equivalent to 9% cost saving in comparison with offset wells. The prediction of stuck pipe problem requires a method to capture geological, geophysical and drilling data, and recognize the indicators of this issue at a field and geological formation level. This paper illustrates the efficiency and the robustness of the proposed cross-disciplinary approach in its ability to produce such signatures and predicting this NPT event.

Keywords: drilling optimization, hazard prediction, machine learning, stuck pipe

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Authors: Till Gramberg, Erwin Gross, Christoph Birenbaum

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This paper presents the approach of the Easy2IoT research project. Easy2IoT aims to enable companies in the prefabrication sheet metal and sheet metal processing industry to enter the Industrial Internet of Things (IIoT) with a low-threshold and cost-effective approach. It focuses on the development of physical hardware and software to easily capture machine activities from on a sawing machine, benefiting various stakeholders in the SME value chain, including machine operators, tool manufacturers and service providers. The methodological approach of Easy2IoT includes an in-depth requirements analysis and customer interviews with stakeholders along the value chain. Based on these insights, actions, requirements and potential solutions for smart services are derived. The focus is on providing actionable recommendations, competencies and easy integration through no-/low-code applications to facilitate implementation and connectivity within production networks. At the core of the project is a novel, non-invasive measurement and analysis system that can be easily deployed and made IIoT-ready. This system collects machine data without interfering with the machines themselves. It does this by non-invasively measuring the tension on a sawing machine. The collected data is then connected and analyzed using artificial intelligence (AI) to provide smart services through a platform-based application. Three Smart Services are being developed within Easy2IoT to provide immediate benefits to users: Wear part and product material condition monitoring and predictive maintenance for sawing processes. The non-invasive measurement system enables the monitoring of tool wear, such as saw blades, and the quality of consumables and materials. Service providers and machine operators can use this data to optimize maintenance and reduce downtime and material waste. Optimize Overall Equipment Effectiveness (OEE) by monitoring machine activity. The non-invasive system tracks machining times, setup times and downtime to identify opportunities for OEE improvement and reduce unplanned machine downtime. Estimate CO2 emissions for connected machines. CO2 emissions are calculated for the entire life of the machine and for individual production steps based on captured power consumption data. This information supports energy management and product development decisions. The key to Easy2IoT is its modular and easy-to-use design. The non-invasive measurement system is universally applicable and does not require specialized knowledge to install. The platform application allows easy integration of various smart services and provides a self-service portal for activation and management. Innovative business models will also be developed to promote the sustainable use of the collected machine activity data. The project addresses the digitalization gap between large enterprises and SME. Easy2IoT provides SME with a concrete toolkit for IIoT adoption, facilitating the digital transformation of smaller companies, e.g. through retrofitting of existing machines.

Keywords: smart services, IIoT, IIoT-platform, industrie 4.0, big data

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Authors: Diane Ghanem, Arjun Gupta, Rohan Vijayan, Ali Uneri, Babar Shafiq

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Introduction: Ankle sprains and fractures often result in syndesmosis injuries. Unstable syndesmotic injuries result from relative motion between the distal ends of the tibia and fibula, anatomic juncture which should otherwise be rigid, and warrant operative management. Clinical and radiological evaluations of intraoperative syndesmosis stability remain a challenging task as traditional 2D fluoroscopy is limited to a uniplanar translational displacement. The purpose of this pilot cadaveric study is to compare the 2D fluoroscopy and 3D cone beam computed tomography (CBCT) stress-induced syndesmosis displacements. Methods: Three fresh-frozen lower legs underwent 2D fluoroscopy and 3D CIOS CBCT to measure syndesmosis position before dissection. Syndesmotic injury was simulated by resecting the (1) anterior inferior tibiofibular ligament (AITFL), the (2) posterior inferior tibiofibular ligament (PITFL) and the inferior transverse ligament (ITL) simultaneously, followed by the (3) interosseous membrane (IOM). Manual external rotation and Cotton stress test were performed after each of the three resections and 2D and 3D images were acquired. Relevant 2D and 3D parameters included the tibiofibular overlap (TFO), tibiofibular clear space (TCS), relative rotation of the fibula, and anterior-posterior (AP) and medial-lateral (ML) translations of the fibula relative to the tibia. Parameters were measured by two independent observers. Inter-rater reliability was assessed by intraclass correlation coefficient (ICC) to determine measurement precision. Results: Significant mismatches were found in the trends between the 2D and 3D measurements when assessing for TFO, TCS and AP translation across the different resection states. Using 3D CBCT, TFO was inversely proportional to the number of resected ligaments while TCS was directly proportional to the latter across all cadavers and ‘resection + stress’ states. Using 2D fluoroscopy, this trend was not respected under the Cotton stress test. 3D AP translation did not show a reliable trend whereas 2D AP translation of the fibula was positive under the Cotton stress test and negative under the external rotation. 3D relative rotation of the fibula, assessed using the Tang et al. ratio method and Beisemann et al. angular method, suggested slight overall internal rotation with complete resection of the ligaments, with a change < 2mm - threshold which corresponds to the commonly used buffer to account for physiologic laxity as per clinical judgment of the surgeon. Excellent agreement (>0.90) was found between the two independent observers for each of the parameters in both 2D and 3D (overall ICC 0.9968, 95% CI 0.995 - 0.999). Conclusions: The 3D CIOS CBCT appears to reliably depict the trend in TFO and TCS. This might be due to the additional detection of relevant rotational malpositions of the fibula in comparison to the standard 2D fluoroscopy which is limited to a single plane translation. A better understanding of 3D imaging may help surgeons identify the precise measurements planes needed to achieve better syndesmosis repair.

Keywords: 2D fluoroscopy, 3D computed tomography, image processing, syndesmosis injury

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Authors: I. M. K. Ho, S. K. Y. Chan, K. H. P. Lam, G. M. W. Tong, N. C. Y. Yeung, J. T. C. Luk

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Low-dye taping (LDT) is commonly used for treating foot problems, such as plantar fasciitis, and supporting foot arch for runners and non-athletes patients with pes planus. The potential negative impact of pronated feet leading to tibial and femoral internal rotation via the entire kinetic chain reaction was postulated and identified. The changed lower limb biomechanics potentially leading to poor activation of hip and knee stabilizers, such as gluteus maximus and medius, may associate with higher risk of knee injuries including patellofemoral pain syndrome and ligamentous sprain in many team sports players. It is therefore speculated that foot arch correction with LDT might enhance the use of gluteal muscles. The purpose of this study was to investigate the effect of applying LDT on surface electromyographic (sEMG) activity of superior gluteus maximus (SGMax), inferior gluteus maximus (IGMax), gluteus medius (GMed) and tibialis anterior (TA) during double-leg squat. 12 male collegiate basketball players (age: 21.72.5 years; body fat: 12.43.6%; navicular drop: 13.72.7mm) with at least three years regular basketball training experience participated in this study. Participants were excluded if they had recent history of lower limb injuries, over 16.6% body fat and lesser than 10mm drop in navicular drop (ND) test. Recruited subjects visited the laboratory once for the within-subject crossover study. Maximum voluntary isometric contraction (MVIC) tests on all selected muscles were performed in randomized order followed by sEMG test on double-leg squat during LDT and non-LDT conditions in counterbalanced order. SGMax, IGMax, GMed and TA activities during the entire 2-second concentric and 2-second eccentric phases were normalized and interpreted as %MVIC. The magnitude of the difference between taped and non-taped conditions of each muscle was further assessed via standardized effect90% confidence intervals (CI) with non-clinical magnitude-based inference. Paired samples T-test showed a significant decrease (4.71.4mm) in ND (95% CI: 3.8, 5.6; p < 0.05) while no significant difference was observed between taped and non-taped conditions in sEMG tests for all muscles and contractions (p > 0.05). On top of traditional significant testing, magnitude-based inference showed possibly increase in IGMax activity (small standardized effect: 0.270.44), likely increase in GMed activity (small standardized effect: 0.340.34) and possibly increase in TA activity (small standardized effect: 0.220.29) during eccentric phase. It is speculated that the decrease of navicular drop supported by LDT application could potentially enhance the use of inferior gluteus maximus and gluteus medius especially during eccentric phase in this study. As the eccentric phase of double-leg squat is an important component of landing activities in basketball, further studies on the onset and amount of gluteal activation during jumping and landing activities with LDT are recommended. Since both hip and knee kinematics were not measured in this study, the underlying cause of the observed increase in gluteal activation during squat after LDT is inconclusive. In this regard, the investigation of relationships between LDT application, ND, hip and knee kinematics, and gluteal muscle activity during sports specific jumping and landing tasks should be focused in the future.

Keywords: flat foot, gluteus maximus, gluteus medius, injury prevention

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Authors: Anna Mucha, Ewa Wojtyna, Anita Pollak

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The environment in which an individual resides and observes may play a meaningful role in well-being and related constructs. Contact with nature may have a positive influence of natural environments on individuals, impacting mood and psychophysical sensations, such as pain relief. Conversely, urban settings, dominated by concrete elements, might lead to mood decline and heightened stress levels. Similarly, the situation may appear in the case of the perception of virtual environments. However, this is a topic that requires further exploration, especially in the context of relationships with pain. The aforementioned matters served as the basis for formulating and executing the outlined experimental research within the realm of environmental psychology, leveraging new technologies, notably virtual reality (VR), which is progressively gaining prominence in the domain of mental health. The primary objective was to investigate the impact of a simulated virtual environment, mirroring a natural setting abundant in greenery, on the perception of acute pain induced by thermal stimuli (high temperature) – encompassing intensity, unpleasantness, and pain tolerance. Comparative analyses were conducted between the virtual natural environment (intentionally constructed in the likeness of a therapeutic garden), virtual urban environment, and a control group devoid of virtual projections. Secondary objectives aimed to determine the mutual relationships among variables such as positive and negative emotions, preferences regarding virtual environments, sense of presence, and restorative experience in the context of the perception of presented virtual environments and induced thermal pain. The study encompassed 126 physically healthy Polish adults, distributing 42 individuals across each of the three comparative groups. Oculus Rift VR technology and the TSA-II neurosensory analyzer facilitated the experiment. Alongside demographic data, participants' subjective feelings concerning virtual reality and pain were evaluated using the Visual Analogue Scale (VAS), the original Restorative Experience in the Virtual World questionnaire (Doświadczenie Regeneracji w Wirtualnym Świecie), and an adapted Slater-Usoh-Steed (SUS) questionnaire. Results of statistical and psychometric analyses, such as Kruskal-Wallis tests, Wilcoxon tests, and contrast analyses, underscored the positive impact of the virtual natural environment on individual pain perception and mood. The virtual natural environment outperformed the virtual urban environment and the control group without virtual projection, particularly in subjective pain components like intensity and unpleasantness. Variables such as restorative experience, sense of presence and virtual environment preference also proved pivotal in pain perception and pain tolerance threshold alterations, contingent on specific conditions. This implies considerable application potential for virtual natural environments across diverse realms of psychology and related fields, among others as a supportive analgesic approach and a form of relaxation following psychotherapeutic sessions.

Keywords: environmental psychology, nature, acute pain, emotions, vitrual reality, virtual environments

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Authors: Yunwei Tang, Linhai Jing, Hui Li, Qingjie Liu, Xiuxia Li, Qi Yan, Haifeng Ding

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The giant panda (Ailuropoda melanoleuca) is an endangered species, mainly live in central China, where bamboos act as the main food source of wild giant pandas. Knowledge of spatial distribution of bamboos therefore becomes important for identifying the habitat of giant pandas. There have been ongoing studies for mapping bamboos and other tree species using remote sensing. WorldView-2 (WV-2) is the first high resolution commercial satellite with eight Multi-Spectral (MS) bands. Recent studies demonstrated that WV-2 imagery has a high potential in classification of tree species. The advanced classification techniques are important for utilising high spatial resolution imagery. It is generally agreed that object-based image analysis is a more desirable method than pixel-based analysis in processing high spatial resolution remotely sensed data. Classifiers that use spatial information combined with spectral information are known as contextual classifiers. It is suggested that contextual classifiers can achieve greater accuracy than non-contextual classifiers. Thus, spatial correlation can be incorporated into classifiers to improve classification results. The study area is located at Wuyipeng area in Wolong, Sichuan Province. The complex environment makes it difficult for information extraction since bamboos are sparsely distributed, mixed with brushes, and covered by other trees. Extensive fieldworks in Wuyingpeng were carried out twice. The first one was on 11th June, 2014, aiming at sampling feature locations for geometric correction and collecting training samples for classification. The second fieldwork was on 11th September, 2014, for the purposes of testing the classification results. In this study, spectral separability analysis was first performed to select appropriate MS bands for classification. Also, the reflectance analysis provided information for expanding sample points under the circumstance of knowing only a few. Then, a spatially weighted object-based k-nearest neighbour (k-NN) classifier was applied to the selected MS bands to identify seven land cover types (bamboo, conifer, broadleaf, mixed forest, brush, bare land, and shadow), accounting for spatial correlation within classes using geostatistical modelling. The spatially weighted k-NN method was compared with three alternatives: the traditional k-NN classifier, the Support Vector Machine (SVM) method and the Classification and Regression Tree (CART). Through field validation, it was proved that the classification result obtained using the spatially weighted k-NN method has the highest overall classification accuracy (77.61%) and Kappa coefficient (0.729); the producer’s accuracy and user’s accuracy achieve 81.25% and 95.12% for the bamboo class, respectively, also higher than the other methods. Photos of tree crowns were taken at sample locations using a fisheye camera, so the canopy density could be estimated. It is found that it is difficult to identify bamboo in the areas with a large canopy density (over 0.70); it is possible to extract bamboos in the areas with a median canopy density (from 0.2 to 0.7) and in a sparse forest (canopy density is less than 0.2). In summary, this study explores the ability of WV-2 imagery for bamboo extraction in a mountainous region in Sichuan. The study successfully identified the bamboo distribution, providing supporting knowledge for assessing the habitats of giant pandas.

Keywords: bamboo mapping, classification, geostatistics, k-NN, worldview-2

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Authors: Khachen Kongpakwattana, Nathorn Chaiyakunapruk

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Background: Decision-analytic models for Alzheimer’s disease (AD) have been advanced to discrete-event simulation (DES), in which individual-level modelling of disease progression across continuous severity spectra and incorporation of key parameters such as treatment persistence into the model become feasible. This study aimed to apply the DES to perform a cost-effectiveness analysis of treatment for AD in Thailand. Methods: A dataset of Thai patients with AD, representing unique demographic and clinical characteristics, was bootstrapped to generate a baseline cohort of patients. Each patient was cloned and assigned to donepezil, galantamine, rivastigmine, memantine or no treatment. Throughout the simulation period, the model randomly assigned each patient to discrete events including hospital visits, treatment discontinuation and death. Correlated changes in cognitive and behavioral status over time were developed using patient-level data. Treatment effects were obtained from the most recent network meta-analysis. Treatment persistence, mortality and predictive equations for functional status, costs (Thai baht (THB) in 2017) and quality-adjusted life year (QALY) were derived from country-specific real-world data. The time horizon was 10 years, with a discount rate of 3% per annum. Cost-effectiveness was evaluated based on the willingness-to-pay (WTP) threshold of 160,000 THB/QALY gained (4,994 US$/QALY gained) in Thailand. Results: Under a societal perspective, only was the prescription of donepezil to AD patients with all disease-severity levels found to be cost-effective. Compared to untreated patients, although the patients receiving donepezil incurred a discounted additional costs of 2,161 THB, they experienced a discounted gain in QALY of 0.021, resulting in an incremental cost-effectiveness ratio (ICER) of 138,524 THB/QALY (4,062 US$/QALY). Besides, providing early treatment with donepezil to mild AD patients further reduced the ICER to 61,652 THB/QALY (1,808 US$/QALY). However, the dominance of donepezil appeared to wane when delayed treatment was given to a subgroup of moderate and severe AD patients [ICER: 284,388 THB/QALY (8,340 US$/QALY)]. Introduction of a treatment stopping rule when the Mini-Mental State Exam (MMSE) score goes below 10 to a mild AD cohort did not deteriorate the cost-effectiveness of donepezil at the current treatment persistence level. On the other hand, none of the AD medications was cost-effective when being considered under a healthcare perspective. Conclusions: The DES greatly enhances real-world representativeness of decision-analytic models for AD. Under a societal perspective, treatment with donepezil improves patient’s quality of life and is considered cost-effective when used to treat AD patients with all disease-severity levels in Thailand. The optimal treatment benefits are observed when donepezil is prescribed since the early course of AD. With healthcare budget constraints in Thailand, the implementation of donepezil coverage may be most likely possible when being considered starting with mild AD patients, along with the stopping rule introduced.

Keywords: Alzheimer's disease, cost-effectiveness analysis, discrete event simulation, health technology assessment

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Authors: Maari Sugawara

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This arts-based research is about "self-torture": the interplay of seemingly opposing elements of pain, pleasure, submission, and power. It asserts that "self-torture" can be considered a nontrivial mediation between the aesthetic and the sociopolitical. It explores what the author calls queered self-torture; "self-torture" marked by an ambivalence that allows the oppressed to resist, and their counter-valorization occasionally functions as therapeutic solutions to the problems they highlight and condense. The research goal is to deconstruct normative self-torture and propose queered self-torture as a fertile ground for considering the complexities of desire that allow the oppressed to practice freedom. While “self-torture” manifests in many societies, this research focuses on cultural and national identity in post-WWII Japan using this lens of self-torture, as masochism functions as the very basis for Japanese cultural and national identity to ensure self-preservation. This masochism is defined as an impulse to realize a sense of pride and construct an identity through the acceptance of subordination, shame, and humiliation in the face of an all-powerful Other; the dominant Euro-America. It could be argued that this self-torture is a result of Japanese cultural annihilation and the trauma of the nation's defeat to the US. This is the definition of "self-torturous thresholds," the author’s post-WWII Japan psycho-historical diagnosis; when this threshold is crossed, the oppressed begin to torture themselves; the oppressors no longer need to do anything to maintain their power. The oppressed are already oppressing themselves. The term "oppressed" here refers to Japanese individuals and residents of Japan who are subjected to oppressive “white” heteropatriarchal supremacist structures and values that serve colonialist interests. There are three stages in "self-torturous thresholds": (1) the oppressors no longer need to oppress because the oppressed voluntarily commit to self-torture; (2) the oppressed find pleasure in self-torture; and (3) the oppressed achieve queered self-torture, to achieve alternative futures. Using the conceptualization of "self-torture," this research examines and critiques pleasure, desire, capital, and power in postwar Japan, which enables the discussion of the data-colonizing “Moonshot Research and Development program”. If the oppressed want to divest from the habits of normative self-torture, which shape what is possible in both our present and future, we need methods to feel and know that the alternative results of self-torture are possible. Phase three will be enacted using Sarah Ahmed's queer methodology to reorient national and cultural identity away from heteronormativity. Through theoretical analysis, textual analysis, archival research, ethnographic interviews, and digital art projects, including experimental documentary as a method to capture the realities of the individuals who are practicing self-torture, this research seeks to reveal how self-torture may become not just a vehicle of pleasure but also a mode of critiquing power and achieving freedom. It seeks to encourage the imaginings of queer Japanese futures, where the marginalized survive Japan’s natural and man-made disasters and Japan’s Imperialist past and present rather than submitting to the country’s continued violence.

Keywords: arts-based research, Japanese studies, interdisciplinary arts, queer studies, cultural studies, popular culture, BDSM, sadomasochism, sexuality, VR, AR, digital art, visual arts, speculative fiction

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Authors: Hirseland Andreas, Kerschbaumer Lukas

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In the case of Germany, there are about one million long-term unemployed – a figure that did not vary much during the past years. These long-term unemployed did not benefit from the prospering labor market while most short-term unemployed did. Instead, they are continuously dependent on welfare and sometimes precarious short-term employment, experiencing work poverty. Long-term unemployment thus turns into a main obstacle to become employed again, especially if it is accompanied by other impediments such as low-level education (school/vocational), poor health (especially chronical illness), advanced age (older than fifty), immigrant status, motherhood or engagement in care for other relatives. As can be shown by this current research project, in these cases the chance to regain employment decreases to near nil. Almost two-thirds of all welfare recipients have multiple impediments which hinder a successful transition from welfare back to sustainable and sufficient employment. Prospective employers are unlikely to hire long-term unemployed with additional impediments because they evaluate potential employees on their negative signaling (e.g. low-level education) and the implicit assumption of unproductiveness (e.g. poor health, age). Some findings of the panel survey “Labor market and social security” (PASS) carried out by the Institute of Employment Research (the research institute of the German Federal Labor Agency) spread a ray of hope, showing that unlikely does not necessarily mean impossible. The presentation reports on current research on these very scarce “success stories” of unlikely transitions from long-term unemployment to work and how these cases were able to perform this switch against all odds. The study is based on a mixed-method design. Within the panel survey (~15,000 respondents in ~10,000 households), only 66 cases of such unlikely transitions were observed. These cases have been explored by qualitative inquiry – in depth-interviews and qualitative network techniques. There is strong evidence that sustainable transitions are influenced by certain biographical resources like habits of network use, a set of informal skills and particularly a resilient way of dealing with obstacles, combined with contextual factors rather than by job-placement procedures promoted by Job-Centers according to activation rules or by following formal paths of application. On the employer’s side small and medium-sized enterprises are often found to give job opportunities to a wider variety of applicants, often based on a slow but steadily increasing relationship leading to employment. According to these results it is possible to show and discuss some limitations of (German) activation policies targeting the labor market and their impact on welfare dependency and long-term unemployment. Based on these findings, indications for more supportive small-scale measures in the field of labor-market policies are suggested to help long-term unemployed with multiple impediments to overcome their situation (e.g. organizing small-scale-structures and low-threshold services to encounter possible employers on a more informal basis like “meet and greet”).

Keywords: against-all-odds, mixed-methods, Welfare State, long-term unemployment

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Authors: Patrick Cormier, Cesar Meylan, Matt Jensen, Dana Agar-Newman, Chloe Werle, Ming-Chang Tsai, Marc Klimstra

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Sprint-derived horizontal force-velocity-power (FVP) profiles can be developed with adequate validity and reliability with satellite (GPS/GNSS) systems. However, FVP metrics are sensitive to small nuances in data processing procedures such that minor differences in defining the onset and end of the sprint could result in different FVP metric outcomes. Furthermore, in team-sports, there is a requirement for rapid analysis and feedback of results from multiple athletes, therefore developing standardized and automated methods to improve the speed, efficiency and reliability of this process are warranted. Thus, the purpose of this study was to compare different methods of sprint end detection on the development of FVP profiles from 10Hz GPS/GNSS data through goodness-of-fit and intertrial reliability statistics. Seventeen national team female soccer players participated in the FVP protocol which consisted of 2x40m maximal sprints performed towards the end of a soccer specific warm-up in a training session (1020 hPa, wind = 0, temperature = 30°C) on an open grass field. Each player wore a 10Hz Catapult system unit (Vector S7, Catapult Innovations) inserted in a vest in a pouch between the scapulae. All data were analyzed following common procedures. Variables computed and assessed were the model parameters, estimated maximal sprint speed (MSS) and the acceleration constant τ, in addition to horizontal relative force (F₀), velocity at zero (V₀), and relative mechanical power (Pmax). The onset of the sprints was standardized with an acceleration threshold of 0.1 m/s². The sprint end detection methods were: 1. Time when peak velocity (MSS) was achieved (zero acceleration), 2. Time after peak velocity drops by -0.4 m/s, 3. Time after peak velocity drops by -0.6 m/s, and 4. When the integrated distance from the GPS/GNSS signal achieves 40-m. Goodness-of-fit of each sprint end detection method was determined using the residual sum of squares (RSS) to demonstrate the error of the FVP modeling with the sprint data from the GPS/GNSS system. Inter-trial reliability (from 2 trials) was assessed utilizing intraclass correlation coefficients (ICC). For goodness-of-fit results, the end detection technique that used the time when peak velocity was achieved (zero acceleration) had the lowest RSS values, followed by -0.4 and -0.6 velocity decay, and 40-m end had the highest RSS values. For intertrial reliability, the end of sprint detection techniques that were defined as the time at (method 1) or shortly after (method 2 and 3) when MSS was achieved had very large to near perfect ICC and the time at the 40 m integrated distance (method 4) had large to very large ICCs. Peak velocity was reached at 29.52 ± 4.02-m. Therefore, sport scientists should implement end of sprint detection either when peak velocity is determined or shortly after to improve goodness of fit to achieve reliable between trial FVP profile metrics. Although, more robust processing and modeling procedures should be developed in future research to improve sprint model fitting. This protocol was seamlessly integrated into the usual training which shows promise for sprint monitoring in the field with this technology.

Keywords: automated, biomechanics, team-sports, sprint

Procedia PDF Downloads 119

Authors: Jara Kaye S. Villanueva, M. Rosario Concepcion O. Ang

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For the past few years, Philippines has depended most of its energy source on oil, coal, and fossil fuel. According to the Department of Energy (DOE), the dominance of coal in the energy mix will continue until the year 2020. The expanding energy needs in the country have led to increasing efforts to promote and develop renewable energy. This research is a part of the government initiative in preparation for renewable energy development and expansion in the country. The Philippine Renewable Energy Resource Mapping from Light Detection and Ranging (LiDAR) Surveys is a three-year government project which aims to assess and quantify the renewable energy potential of the country and to put them into usable maps. This study focuses on the site suitability analysis of the four renewable energy sources – biomass (coconut, corn, rice, and sugarcane), hydro, solar, and wind energy. The site assessment is a key component in determining and assessing the most suitable locations for the construction of renewable energy power plants. This method maximizes the use of both the technical methods in resource assessment, as well as taking into account the environmental, social, and accessibility aspect in identifying potential sites by utilizing and integrating two different methods: the Multi-Criteria Decision Analysis (MCDA) method and Geographic Information System (GIS) tools. For the MCDA, Analytical Hierarchy Processing (AHP) is employed to determine the parameters needed for the suitability analysis. To structure these site suitability parameters, various experts from different fields were consulted – scientists, policy makers, environmentalists, and industrialists. The need to have a well-represented group of people to consult with is relevant to avoid bias in the output parameter of hierarchy levels and weight matrices. AHP pairwise matrix computation is utilized to derive weights per level out of the expert’s gathered feedback. Whereas from the threshold values derived from related literature, international studies, and government laws, the output values were then consulted with energy specialists from the DOE. Geospatial analysis using GIS tools translate this decision support outputs into visual maps. Particularly, this study uses Euclidean distance to compute for the distance values of each parameter, Fuzzy Membership algorithm which normalizes the output from the Euclidean Distance, and the Weighted Overlay tool for the aggregation of the layers. Using the Natural Breaks algorithm, the suitability ratings of each of the map are classified into 5 discrete categories of suitability index: (1) not suitable (2) least suitable, (3) suitable, (4) moderately suitable, and (5) highly suitable. In this method, the classes are grouped based on the best groups similar values wherein each subdivision are set from the rest based on the big difference in boundary values. Results show that in the entire Philippine area of responsibility, biomass has the highest suitability rating with rice as the most suitable at 75.76% suitability percentage, whereas wind has the least suitability percentage with score 10.28%. Solar and Hydro fall in the middle of the two, with suitability values 28.77% and 21.27%.

Keywords: site suitability, biomass energy, hydro energy, solar energy, wind energy, GIS

Procedia PDF Downloads 149

Authors: Stefan W. Kienzle

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The increasing number of occurrences of extreme weather and climate events have significant impacts on society and are the cause of continued and increasing loss of human and animal lives, loss or damage to property (houses, cars), and associated stresses to the public in coping with a changing climate. A climate index breaks down daily climate time series into meaningful derivatives, such as the annual number of frost days. Climate indices allow for the spatially consistent analysis of a wide range of climate-dependent variables, which enables the quantification and mapping of historical and future climate change across regions. As trends of phenomena such as the length of the growing season change differently in different hydro-climatological regions, mapping needs to be carried out at a high spatial resolution, such as the 10km by 10km Canadian Climate Grid, which has interpolated daily values from 1950 to 2017 for minimum and maximum temperature and precipitation. Climate indices form the basis for the analysis and comparison of means, extremes, trends, the quantification of changes, and their respective confidence levels. A total of 39 temperature indices and 16 precipitation indices were computed for the period 1951 to 2017 for the Province of Alberta. Temperature indices include the annual number of days with temperatures above or below certain threshold temperatures (0, +-10, +-20, +25, +30ºC), frost days, and timing of frost days, freeze-thaw days, growing or degree days, and energy demands for air conditioning and heating. Precipitation indices include daily and accumulated 3- and 5-day extremes, days with precipitation, period of days without precipitation, and snow and potential evapotranspiration. The rank-based nonparametric Mann-Kendall statistical test was used to determine the existence and significant levels of all associated trends. The slope of the trends was determined using the non-parametric Sen’s slope test. The Google mapping interface was developed to create the website albertaclimaterecords.com, from which beach of the 55 climate indices can be queried for any of the 6833 grid cells that make up Alberta. In addition to the climate indices, climate normals were calculated and mapped for four historical 30-year periods and one future period (1951-1980, 1961-1990, 1971-2000, 1981-2017, 2041-2070). While winters have warmed since the 1950s by between 4 - 5°C in the South and 6 - 7°C in the North, summers are showing the weakest warming during the same period, ranging from about 0.5 - 1.5°C. New agricultural opportunities exist in central regions where the number of heat units and growing degree days are increasing, and the number of frost days is decreasing. While the number of days below -20ºC has about halved across Alberta, the growing season has expanded by between two and five weeks since the 1950s. Interestingly, both the number of days with heat waves and cold spells have doubled to four-folded during the same period. This research demonstrates the enormous potential of using climate indices at the best regional spatial resolution possible to enable society to understand historical and future climate changes of their region.

Keywords: climate change, climate indices, habitat risk, regional, mapping, extremes

Procedia PDF Downloads 92

Authors: Xingyu Gao, Qiang Wu, Yuanyuan Liu, Yue Yang

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In the era of the knowledge economy, the relationship between scientific knowledge and patents has garnered significant attention. Understanding the intricate interplay between the foundations of science and technological innovation has emerged as a pivotal challenge for both researchers and policymakers. This study establishes a coupled network of artificial intelligence patents based on co-cited scientific papers. Leveraging centrality metrics from network analysis offers a fresh perspective on understanding the influence of information flow and knowledge sharing within the network on patent impact. The study initially obtained patent numbers for 446,890 granted US AI patents from the United States Patent and Trademark Office’s artificial intelligence patent database for the years 2002-2020. Subsequently, specific information regarding these patents was acquired using the Lens patent retrieval platform. Additionally, a search and deduplication process was performed on scientific non-patent references (SNPRs) using the Web of Science database, resulting in the selection of 184,603 patents that cited 37,467 unique SNPRs. Finally, this study constructs a coupled network comprising 59,379 artificial intelligence patents by utilizing scientific papers co-cited in patent backward citations. In this network, nodes represent patents, and if patents reference the same scientific papers, connections are established between them, serving as edges within the network. Nodes and edges collectively constitute the patent coupling network. Structural characteristics such as node degree centrality, betweenness centrality, and closeness centrality are employed to assess the scientific connections between patents, while citation count is utilized as a quantitative metric for patent influence. Finally, a negative binomial model is employed to test the nonlinear relationship between these network structural features and patent influence. The research findings indicate that network structural features such as node degree centrality, betweenness centrality, and closeness centrality exhibit inverted U-shaped relationships with patent influence. Specifically, as these centrality metrics increase, patent influence initially shows an upward trend, but once these features reach a certain threshold, patent influence starts to decline. This discovery suggests that moderate network centrality is beneficial for enhancing patent influence, while excessively high centrality may have a detrimental effect on patent influence. This finding offers crucial insights for policymakers, emphasizing the importance of encouraging moderate knowledge flow and sharing to promote innovation when formulating technology policies. It suggests that in certain situations, data sharing and integration can contribute to innovation. Consequently, policymakers can take measures to promote data-sharing policies, such as open data initiatives, to facilitate the flow of knowledge and the generation of innovation. Additionally, governments and relevant agencies can achieve broader knowledge dissemination by supporting collaborative research projects, adjusting intellectual property policies to enhance flexibility, or nurturing technology entrepreneurship ecosystems.

Keywords: centrality, patent coupling network, patent influence, social network analysis

Procedia PDF Downloads 54

Authors: Óscar Muñoz Garrigós, José Manuel Bernabeu Aubán

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Time-sensitive services are the base of the cloud services industry. Keeping low service saturation is essential for controlling response time. All auto-scalable services make use of reactive auto-scaling. However, reactive auto-scaling has few in-depth studies. This presentation shows a model for reactive auto-scaling methodologies with a MAPE-k architecture. Queuing theory can compute different properties of static services but lacks some parameters related to the transition between models. Our model uses queuing theory parameters to relate the transition between models. It associates MAPE-k related times, the sampling frequency, the cooldown period, the number of requests that an instance can handle per unit of time, the number of incoming requests at a time instant, and a function that describes the acceleration in the service's ability to handle more requests. This model is later used as a solution to horizontally auto-scale time-sensitive services composed of microservices, reevaluating the model’s parameters periodically to allocate resources. The solution requires limiting the acceleration of the growth in the number of incoming requests to keep a constrained response time. Business benefits determine such limits. The solution can add a dynamic number of instances and remains valid under different system sizes. The study includes performance recommendations to improve results according to the incoming load shape and business benefits. The exposed methodology is tested in a simulation. The simulator contains a load generator and a service composed of two microservices, where the frontend microservice depends on a backend microservice with a 1:1 request relation ratio. A common request takes 2.3 seconds to be computed by the service and is discarded if it takes more than 7 seconds. Both microservices contain a load balancer that assigns requests to the less loaded instance and preemptively discards requests if they are not finished in time to prevent resource saturation. When load decreases, instances with lower load are kept in the backlog where no more requests are assigned. If the load grows and an instance in the backlog is required, it returns to the running state, but if it finishes the computation of all requests and is no longer required, it is permanently deallocated. A few load patterns are required to represent the worst-case scenario for reactive systems: the following scenarios test response times, resource consumption and business costs. The first scenario is a burst-load scenario. All methodologies will discard requests if the rapidness of the burst is high enough. This scenario focuses on the number of discarded requests and the variance of the response time. The second scenario contains sudden load drops followed by bursts to observe how the methodology behaves when releasing resources that are lately required. The third scenario contains diverse growth accelerations in the number of incoming requests to observe how approaches that add a different number of instances can handle the load with less business cost. The exposed methodology is compared against a multiple threshold CPU methodology allocating/deallocating 10 or 20 instances, outperforming the competitor in all studied metrics.

Keywords: reactive auto-scaling, auto-scaling, microservices, cloud computing

Procedia PDF Downloads 93

Authors: Zahirah Dhurmeea, Iker Zudaire, Heidi Pethybridge, Emmanuel Chassot, Maria Cedras, Natacha Nikolic, Jerome Bourjea, Wendy West, Chandani Appadoo, Nathalie Bodin

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Scientific advice on the status of fish stocks relies on indicators that are based on strong assumptions on biological parameters such as condition, maturity and fecundity. Currently, information on the biology of albacore tuna, Thunnus alalunga, in the Indian Ocean is scarce. Consequently, many parameters used in stock assessment models for Indian Ocean albacore originate largely from other studied stocks or species of tuna. Inclusion of incorrect biological data in stock assessment models would lead to inappropriate estimates of stock status used by fisheries manager’s to establish future catch allowances. The reproductive biology of albacore tuna in the western Indian Ocean was examined through analysis of the sex ratio, spawning season, length-at-maturity (L50), spawning frequency, fecundity and fish condition. In addition, the total lipid content (TL) and lipid class composition in the gonads, liver and muscle tissues of female albacore during the reproductive cycle was investigated. A total of 923 female and 867 male albacore were sampled from 2013 to 2015. A bias in sex-ratio was found in favour of females with fork length (LF) <100 cm. Using histological analyses and gonadosomatic index, spawning was found to occur between 10°S and 30°S, mainly to the east of Madagascar from October to January. Large females contributed more to reproduction through their longer spawning period compared to small individuals. The L50 (mean ± standard error) of female albacore was estimated at 85.3 ± 0.7 cm LF at the vitellogenic 3 oocyte stage maturity threshold. Albacore spawn on average every 2.2 days within the spawning region and spawning months from November to January. Batch fecundity varied between 0.26 and 2.09 million eggs and the relative batch fecundity (mean  standard deviation) was estimated at 53.4 ± 23.2 oocytes g-1 of somatic-gutted weight. Depending on the maturity stage, TL in ovaries ranged from 7.5 to 577.8 mg g-1 of wet weight (ww) with different proportions of phospholipids (PL), wax esters (WE), triacylglycerol (TAG) and sterol (ST). The highest TL were observed in immature (mostly TAG and PL) and spawning capable ovaries (mostly PL, WE and TAG). Liver TL varied from 21.1 to 294.8 mg g-1 (ww) and acted as an energy (mainly TAG and PL) storage prior to reproduction when the lowest TL was observed. Muscle TL varied from 2.0 to 71.7 g-1 (ww) in mature females without a clear pattern between maturity stages, although higher values of up to 117.3 g-1 (ww) was found in immature females. TL results suggest that albacore could be viewed predominantly as a capital breeder relying mostly on lipids stored before the onset of reproduction and with little additional energy derived from feeding. This study is the first one to provide new information on the reproductive development and classification of albacore in the western Indian Ocean. The reproductive parameters will reduce uncertainty in current stock assessment models which will eventually promote sustainability of the fishery.

Keywords: condition, size-at-maturity, spawning behaviour, temperate tuna, total lipid content

Procedia PDF Downloads 260

Authors: Vittorio Astarita, Giuseppe Guido, Vincenzo Pasquale Giofre, Alessandro Vitale

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Traffic microsimulation has been used extensively to evaluate consequences of different traffic planning and control policies in terms of travel time delays, queues, pollutant emissions, and every other common measured performance while at the same time traffic safety has not been considered in common traffic microsimulation packages as a measure of performance for different traffic scenarios. Vehicle conflict techniques that were introduced at intersections in the early traffic researches carried out at the General Motor laboratory in the USA and in the Swedish traffic conflict manual have been applied to vehicles trajectories simulated in microscopic traffic simulators. The concept is that microsimulation can be used as a base for calculating the number of conflicts that will define the safety level of a traffic scenario. This allows engineers to identify unsafe road traffic maneuvers and helps in finding the right countermeasures that can improve safety. Unfortunately, most commonly used indicators do not consider conflicts between single vehicles and roadside obstacles and barriers. A great number of vehicle crashes take place with roadside objects or obstacles. Only some recent proposed indicators have been trying to address this issue. This paper introduces a new procedure based on the simulation of potential crash events for the evaluation of safety levels in microsimulation traffic scenarios, which takes into account also potential crashes with roadside objects and barriers. The procedure can be used to define new conflict indicators. The proposed simulation procedure generates with the random perturbation of vehicle trajectories a set of potential crashes which can be evaluated accurately in terms of DeltaV, the energy of the impact, and/or expected number of injuries or casualties. The procedure can also be applied to real trajectories giving birth to new surrogate safety performance indicators, which can be considered as “simulation-based”. The methodology and a specific safety performance indicator are described and applied to a simulated test traffic scenario. Results indicate that the procedure is able to evaluate safety levels both at the intersection level and in the presence of roadside obstacles. The procedure produces results that are expressed in the same unity of measure for both vehicle to vehicle and vehicle to roadside object conflicts. The total energy for a square meter of all generated crash can be used and is shown on the map, for the test network, after the application of a threshold to evidence the most dangerous points. Without any detailed calibration of the microsimulation model and without any calibration of the parameters of the procedure (standard values have been used), it is possible to identify dangerous points. A preliminary sensitivity analysis has shown that results are not dependent on the different energy thresholds and different parameters of the procedure. This paper introduces a specific new procedure and the implementation in the form of a software package that is able to assess road safety, also considering potential conflicts with roadside objects. Some of the principles that are at the base of this specific model are discussed. The procedure can be applied on common microsimulation packages once vehicle trajectories and the positions of roadside barriers and obstacles are known. The procedure has many calibration parameters and research efforts will have to be devoted to make confrontations with real crash data in order to obtain the best parameters that have the potential of giving an accurate evaluation of the risk of any traffic scenario.

Keywords: road safety, traffic, traffic safety, traffic simulation

Procedia PDF Downloads 135

Authors: Lynn Sheridan, Dennis Alonzo, Hoa Nguyen, Andy Gao, Tracy Durksen

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Disruptions to teaching (e.g., COVID-related) have increased work demands for teachers. There is an opportunity for research to explore evidence-informed steps to support teachers. Collective evidence informs data on teachers’ personal attributes (e.g., self-efficacy beliefs) in the workplace are seen to promote success in teaching and support teacher engagement. Teacher engagement plays a role in students’ learning and teachers’ effectiveness. Engaged teachers are better at overcoming work-related stress, burnout and are more likely to take on active roles. Teachers’ commitment is influenced by a host of personal (e.g., teacher well-being) and environmental factors (e.g., job stresses). The job demands-resources model provided a conceptual basis for examining how teachers’ well-being, and is influenced by job demands and job resources. Job demands potentially evoke strain and exceed the employee’s capability to adapt. Job resources entail what the job offers to individual teachers (e.g., organisational support), helping to reduce job demands. The application of the job demands-resources model involves gathering an evidence-base of and connection to personal attributes (job resources). The study explored the association between constructs (resilience, adaptability, commitment, self/collective efficacy) and a teacher’s engagement with the job. The paper sought to elaborate on the model and determine the associations between key constructs of well-being (resilience, adaptability), commitment, and motivation (self and collective-efficacy beliefs) to teachers’ engagement in teaching. Data collection involved online a multi-dimensional instrument using validated items distributed from 2020-2022. The instrument was designed to identify construct relationships. The participant number was 170. Data Analysis: The reliability coefficients, means, standard deviations, skewness, and kurtosis statistics for the six variables were completed. All scales have good reliability coefficients (.72-.96). A confirmatory factor analysis (CFA) and structural equation model (SEM) were performed to provide measurement support and to obtain latent correlations among factors. The final analysis was performed using structural equation modelling. Several fit indices were used to evaluate the model fit, including chi-square statistics and root mean square error of approximation. The CFA and SEM analysis was performed. The correlations of constructs indicated positive correlations exist, with the highest found between teacher engagement and resilience (r=.80) and the lowest between teacher adaptability and collective teacher efficacy (r=.22). Given the associations; we proceeded with CFA. The CFA yielded adequate fit: CFA fit: X (270, 1019) = 1836.79, p < .001, RMSEA = .04, and CFI = .94, TLI = .93 and SRMR = .04. All values were within the threshold values, indicating a good model fit. Results indicate that increasing teacher self-efficacy beliefs will increase a teacher’s level of engagement; that teacher ‘adaptability and resilience are positively associated with self-efficacy beliefs, as are collective teacher efficacy beliefs. Implications for school leaders and school systems: 1. investing in increasing teachers’ sense of efficacy beliefs to manage work demands; 2. leadership approaches can enhance teachers' adaptability and resilience; and 3. a culture of collective efficacy support. Preparing teachers for now and in the future offers an important reminder to policymakers and school leaders on the importance of supporting teachers’ personal attributes when faced with the challenging demands of the job.

Keywords: collective teacher efficacy, teacher self-efficacy, job demands, teacher engagement

Procedia PDF Downloads 124