Search results for: gender specific data

Authors: Monica Gonzalez Machorro

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Dementia is hard to diagnose because of the lack of early physical symptoms. Early dementia recognition is key to improving the living condition of patients. Speech technology is considered a valuable biomarker for this challenge. Recent works have utilized conventional acoustic features and machine learning methods to detect dementia in speech. BERT-like classifiers have reported the most promising performance. One constraint, nonetheless, is that these studies are either based on human transcripts or on transcripts produced by automatic speech recognition (ASR) systems. This research contribution is to explore a method that does not require transcriptions to detect early Alzheimer’s disease (AD) and mild cognitive impairment (MCI). This is achieved by fine-tuning a pre-trained ASR model for the downstream early AD and MCI tasks. To do so, a subset of the thoroughly studied Pitt Corpus is customized. The subset is balanced for class, age, and gender. Data processing also involves cropping the samples into 10-second segments. For comparison purposes, a baseline model is defined by training and testing a Random Forest with 20 extracted acoustic features using the librosa library implemented in Python. These are: zero-crossing rate, MFCCs, spectral bandwidth, spectral centroid, root mean square, and short-time Fourier transform. The baseline model achieved a 58% accuracy. To fine-tune HuBERT as a classifier, an average pooling strategy is employed to merge the 3D representations from audio into 2D representations, and a linear layer is added. The pre-trained model used is ‘hubert-large-ls960-ft’. Empirically, the number of epochs selected is 5, and the batch size defined is 1. Experiments show that our proposed method reaches a 69% balanced accuracy. This suggests that the linguistic and speech information encoded in the self-supervised ASR-based model is able to learn acoustic cues of AD and MCI.

Keywords: automatic speech recognition, early Alzheimer’s recognition, mild cognitive impairment, speech impairment

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Authors: Swanand Pathak, Kiran R. Giri, Reena R. Giri, Kamlesh Palandurkar, Sangita Totade, Rajesh Jha, S. S. Patel

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Background: Population burden, illiteracy, availability of few doctors for larger group of population leads to many unanswered questions left in a patient’s mind. Incomplete information results into noncompliance, therapeutic failure, and adverse drug reactions (ADR). It is very important to establish a system which will provide noncommercial, independent, unbiased source of medicine information. Medicines Info OPD is a concept and step towards safe and appropriate use of medicines. Objective: (1) to assess the present status of knowledge about the medicines in the patients and its correlation with education; (2) to assess the medicine information dispensing modalities, their use and sufficiency from the patients view point; (3) to assess the overall need for Medicines Information OPD in present scenario. Materials and Methods: A pre-validated questionnaire based study was conducted amongst 500 patients of tertiary health care hospital. The questionnaire consisted of specific questions regarding understanding of prescription, knowledge about adverse drug reaction, view about self-medication and opinion regarding the need of Medicines Info OPD. Results: Significantly large proportion of patients opined that doctors do not have sufficient time in current Indian healthcare to explain the prescription and they are not aware of adverse drug reactions, expiry date or use the package inserts etc. Conclusion: Clinically relevant, up to date, user specific, independent, objective and unbiased Medicines Info OPD is essential for appropriate drug use and can help in a big way to common public to address many problems faced by them.

Keywords: information, prescription, unbiased, clinically relevant

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Authors: Tyler T. Procko, Steve Collins

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New features in .NET (6 and above) permit streamlined access to information residing in JSON-capable relational databases, such as SQL Server (2016 and above). Traditional methods of data access now comparatively involve unnecessary steps which compromise system performance. This work posits that the established ORM (Object Relational Mapping) based methods of data access in applications and APIs result in common issues, e.g., object-relational impedance mismatch. Recent developments in C# and .NET Core combined with a framework of modern SQL Server coding conventions have allowed better technical solutions to the problem. As an amelioration, this work details the language features and coding conventions which enable this streamlined approach, resulting in an open-source .NET library implementation called Codeless Data Access (CODA). Canonical approaches rely on ad-hoc mapping code to perform type conversions between the client and back-end database; with CODA, no mapping code is needed, as JSON is freely mapped to SQL and vice versa. CODA streamlines API data access by improving on three aspects of immediate concern to web developers, database engineers and cybersecurity professionals: Simplicity, Speed and Security. Simplicity is engendered by cutting out the “middleman” steps, effectively making API data access a whitebox, whereas traditional methods are blackbox. Speed is improved because of the fewer translational steps taken, and security is improved as attack surfaces are minimized. An empirical evaluation of the speed of the CODA approach in comparison to ORM approaches ] is provided and demonstrates that the CODA approach is significantly faster. CODA presents substantial benefits for API developer workflows by simplifying data access, resulting in better speed and security and allowing developers to focus on productive development rather than being mired in data access code. Future considerations include a generalization of the CODA method and extension outside of the .NET ecosystem to other programming languages.

Keywords: API data access, database, JSON, .NET core, SQL server

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Authors: Anyeres N. Atehortua Jimenez, J. David Lambraño, Juan Carlos Muñoz

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Navier-Stokes equations (NSE), which describe the dynamics of a fluid, have an important application on modeling waves used for data inversion techniques as full waveform inversion (FWI). In this work a linearized version of NSE and its variables, neglecting deviatoric terms of stress tensor, is presented. In order to get a theoretical modeling of pressure p(x,t) and wave velocity profile c(x,t), a wave equation of visco-acoustic medium (VAE) is written. A change of variables p(x,t)=q(x,t)h(ρ), is made on the equation for the VAE leading to a well known Klein-Gordon equation (KGE) describing waves propagating in variable density medium (ρ) with dispersive term α^2(x). KGE is reduced to a Poisson equation and solved by proposing a specific function for α^2(x) accounting for the energy dissipation and dispersion. Finally, an integral form solution is derived for p(x,t), c(x,t) and kinematics variables like particle velocity v(x,t), displacement u(x,t) and bulk modulus function k_b(x,t). Further, it is compared this visco-acoustic formulation with another form broadly used in the geophysics; it is argued that this formalism is more general and, given its integral form, it may offer several advantages from the modern parallel computing point of view. Applications to minimize the errors in modeling for FWI applied to oils resources in geophysics are discussed.

Keywords: Navier-Stokes equations, modeling, visco-acoustic, inversion FWI

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Authors: Umair Shafique, Hafiz Usman Zia, Fiaz Majeed, Samina Naz, Javeria Ahmed, Maleeha Zainab

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The Internet of Things (IoT) has become a hot topic for the last couple of years. This innovative technology has shown promising progress in various areas, and the world has witnessed exponential growth in multiple application domains. Researchers are working to investigate its aptitudes to get the best from it by harnessing its true potential. But at the same time, IoT networks open up a new aspect of vulnerability and physical threats to data integrity, privacy, and confidentiality. It's is due to centralized control, data silos approach for handling information, and a lack of standardization in the IoT networks. As we know, blockchain is a new technology that involves creating secure distributed ledgers to store and communicate data. Some of the benefits include resiliency, integrity, anonymity, decentralization, and autonomous control. The potential for blockchain technology to provide the key to managing and controlling IoT has created a new wave of excitement around the idea of putting that data back into the hands of the end-users. In this manuscript, we have proposed a model that combines blockchain and IoT networks to address potential security and privacy issues in the healthcare domain. Then we try to describe various application areas, challenges, and future directions in the healthcare sector where blockchain platforms merge with IoT networks.

Keywords: IoT, blockchain, cryptocurrency, healthcare, consensus, data

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Authors: Aberdam Edith, Sangari Linda, Petit Isabelle, Aberdam Daniel

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Background and Rationale: Transparent avascularised cornea is essential for normal vision and depends on limbal stem cells (LSC) that reside between the cornea and the conjunctiva. Ocular burns or injuries may destroy the limbus, causing limbal stem cell deficiency (LSCD). The cornea becomes vascularised by invaded conjunctival cells, the stroma is scarring, resulting in corneal opacity and loss of vision. Grafted autologous limbus or cultivated autologous LCS can restore the vision, unless the two eyes are affected. Alternative cellular sources have been tested in the last decades, including oral mucosa or hair follicle epithelial cells. However, only partial success has been achieved by the use of these cells since they were not able to uniformly commit into corneal epithelial cells. Human pluripotent stem cells (iPSC) display both unlimited growth capacity and ability to differentiate into any cell type. Our goal was to design a standardized and reproducible protocol to produce transplantable autologous LSC from patients through cell reprogramming technology. Methodology: First, keratinocyte primary culture was established from a small number of plucked hair follicles of healthy donors. The resulting epithelial cells were reprogrammed into induced pluripotent stem cells (iPSCs) and further differentiate into corneal epithelial cells (CEC), according to a robust protocol that recapitulates the main step of corneal embryonic development. qRT-PCR analysis and immunofluorescent staining during the course of differentiation confirm the expression of stage specific markers of corneal embryonic lineage. First appear ectodermal progenitor-specific cytokeratins K8/K18, followed at day 7 by limbal-specific PAX6, TP63 and cytokeratins K5/K14. At day 15, K3/K12+-corneal cells are present. To amplify the iPSC-derived LSC (named COiPSC), intact small epithelial colonies were detached and cultivated in limbal cell-specific medium. In that culture conditions, the COiPSC can be frozen and thaw at any passage, while retaining their corneal characteristics for at least eight passages. To evaluate the potential of COiPSC as an alternative ocular toxicity model, COiPSC were treated at passage P0 to P4 with increasing amounts of SDS and Benzalkonium. Cell proliferation and apoptosis of treated cells was compared to LSC and the SV40-immortalized human corneal epithelial cell line (HCE) routinely used by cosmetological industrials. Of note, HCE are more resistant to toxicity than LSC. At P0, COiPSC were systematically more resistant to chemical toxicity than LSC and even to HCE. Remarkably, this behavior changed with passage since COiPSC at P2 became identical to LSC and thus closer to physiology than HCE. Comparative transcriptome analysis confirmed that COiPSC from P2 are similar to a mixture of LSC and CEC. Finally, by organotypic reconstitution assay, we demonstrated the ability of COiPSC to produce a 3D corneal epithelium on a stromal equivalent made of keratocytes. Conclusion: COiPSC could become valuable for two main applications: (1) an alternative robust tool to perform, in a reproducible and physiological manner, toxicity assays for cosmetic products and pharmacological tests of drugs. (2). COiPSC could become an alternative autologous source for cornea transplantation for LSCD.

Keywords: Limbal stem cell deficiency, iPSC, cornea, limbal stem cells

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Authors: Bruce X. B. Yu, Yan Liu, Keith C. C. Chan

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We propose to record Activities of Daily Living (ADLs) of elderly people using a vision-based system so as to provide better assistive and personalization technologies. Current ADL-related research is based on data collected with help from non-elderly subjects in laboratory environments and the activities performed are predetermined for the sole purpose of data collection. To obtain more realistic datasets for the application, we recorded ADLs for the elderly with data collected from real-world environment involving real elderly subjects. Motivated by the need to collect data for more effective research related to elderly care, we chose to collect data in the room of an elderly person. Specifically, we installed Kinect, a vision-based sensor on the ceiling, to capture the activities that the elderly subject performs in the morning every day. Based on the data, we identified 12 morning activities that the elderly person performs daily. To recognize these activities, we created a HARELCARE framework to investigate into the effectiveness of existing Human Activity Recognition (HAR) algorithms and propose the use of a transfer learning algorithm for HAR. We compared the performance, in terms of accuracy, and training progress. Although the collected dataset is relatively small, the proposed algorithm has a good potential to be applied to all daily routine activities for healthcare purposes such as evidence-based diagnosis and treatment.

Keywords: daily activity recognition, healthcare, IoT sensors, transfer learning

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Authors: Hanna Gulema, Meaza Demissie, Alemayehu Worku, Tesfaye Assebe Yadeta, Yemane Berhane

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Background: In patriarchal societies, female caregivers decide on food allocation within a family based on prevailing gender and age norms, which may lead to inequality that does not favor young adolescent girls. This study evaluated the effect of a community-based social norm intervention involving female caregivers in West Hararghe, Ethiopia. The intervention was engaging female caregivers along with other adult influential community members to deliberate and act on food allocation social norms in a process referred to as Social Analysis and Action (SAA). Method: We used data from a large quasi-experimental study to compare family eating practices between those who participated in the Social Analyses and Action intervention and those who did not. The respondents were female caregivers in households with young adolescent girls (ages 13 and 14 years). The study’s outcome was the practice of family eating together from the same dish. The difference in difference (DID) analysis with the Mixed effect logistic regression model was used to examine the effect of the intervention. Result: The results showed improved family eating practices in both groups, but the improvement was greater in the intervention group. The DID analysis showed an 11.99 percentage points greater improvement in the intervention arm than in the control arm. The mixed-effect regression produced an adjusted odds ratio of 2.08 (95% CI [1.06–4.09]) after controlling selected covariates, p-value 0.033. Conclusions: The involvement of influential adult community members significantly improves the family practice of eating together in households where adolescent girls are present in our study. The intervention has great potential to minimize household food allocation inequalities and thus improve the nutritional status of young adolescents. Further studies are necessary to evaluate the effectiveness of the intervention in different social norm contexts to formulate policy and guidelines for scale-up.

Keywords: family eating practice, social norm intervention, adolescence girls, caregiver

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Authors: Othman Maklouf, Matouk Elamari, M. Rgeai, Fateh Alej

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In modern avionics the main fundamental component is the flight management system (FMS). An FMS is a specialized computer system that automates a wide variety of in-flight tasks, reducing the workload on the flight crew to the point that modern civilian aircraft no longer carry flight engineers or navigators. The main function of the FMS is in-flight management of the flight plan using various sensors such as Global Positioning System (GPS) and Inertial Navigation System (INS) to determine the aircraft's position and guide the aircraft along the flight plan. GPS which is satellite based navigation system, and INS which generally consists of inertial sensors (accelerometers and gyroscopes). GPS is used to locate positions anywhere on earth, it consists of satellites, control stations, and receivers. GPS receivers take information transmitted from the satellites and uses triangulation to calculate a user’s exact location. The basic principle of an INS is based on the integration of accelerations observed by the accelerometers on board the moving platform, the system will accomplish this task through appropriate processing of the data obtained from the specific force and angular velocity measurements. Thus, an appropriately initialized inertial navigation system is capable of continuous determination of vehicle position, velocity and attitude without the use of the external information. The main objective of article is to introduce a comparative study between the two systems under different conditions and scenarios using MATLAB with SIMULINK software.

Keywords: flight management system, GPS, IMU, inertial navigation system

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Authors: Bin Mu, Site Li, Shijin Yuan

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Under the circumstance of environment deterioration, people are increasingly concerned about the quality of the environment, especially air quality. As a result, it is of great value to give accurate and timely forecast of AQI (air quality index). In order to simplify influencing factors of air quality in a city, and forecast the city’s AQI tomorrow, this study used MATLAB software and adopted the method of constructing a mathematic model of PCA-GABP to provide a solution. To be specific, this study firstly made principal component analysis (PCA) of influencing factors of AQI tomorrow including aspects of weather, industry waste gas and IAQI data today. Then, we used the back propagation neural network model (BP), which is optimized by genetic algorithm (GA), to give forecast of AQI tomorrow. In order to verify validity and accuracy of PCA-GABP model’s forecast capability. The study uses two statistical indices to evaluate AQI forecast results (normalized mean square error and fractional bias). Eventually, this study reduces mean square error by optimizing individual gene structure in genetic algorithm and adjusting the parameters of back propagation model. To conclude, the performance of the model to forecast AQI is comparatively convincing and the model is expected to take positive effect in AQI forecast in the future.

Keywords: AQI forecast, principal component analysis, genetic algorithm, back propagation neural network model

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Authors: Mayada Al Meghari

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Recently, grid middlewares have provided large integrated use of network resources as the shared data and the CPU to become a virtual supercomputer. In this work, we present the design and implementation of the middleware for Data Warehouse Signature, DWS Framework. The aim of using the middleware in our DWS framework is to achieve the high performance by the parallel computing. This middleware is developed on Alchemi.Net framework to increase the security among the network nodes through the authentication and group-key distribution model. This model achieves the key security and prevents any intermediate attacks in the middleware. This paper presents the flow process structures of the middleware design. In addition, the paper ensures the implementation of security for DWS middleware enhancement with the authentication and group-key distribution model. Finally, from the analysis of other middleware approaches, the developed middleware of DWS framework is the optimal solution of a complete covering of security issues.

Keywords: middleware, parallel computing, data warehouse, security, group-key, high performance

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Authors: Emil Sakharov, Alex Zotov, Ilkin Osmanov, Oleg Shelest, Aleksander Troitskiy, Robert Khabazov

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Objective: Since 2015, our center has been actively implementing methods of surgical correction of atrial fibrillation, in particular, in patients with coronary heart disease. The study presents a comparative analysis of the late postoperative period in patients with coronary artery bypass grafting and atrial fibrillation. Methods: The study included 150 patients with ischemic heart disease and atrial fibrillation for the period from 2015 to 2021. Patients were divided into 2 groups. The first group is represented by patients with ischemic heart disease and atrial fibrillation who underwent coronary bypass surgery and surgical correction of atrial fibrillation (N=50). The second group is represented by patients with ischemic heart disease and atrial fibrillation who underwent only myocardial revascularization (N=100). Patients were comparable in age, gender, and initial severity of the condition. Among the patients in group 1 there were 82% were men, while in the second group, their number was 75%. Among the patients of the first group, there were 36% with persistent atrial fibrillation, 20% with long-term persistent atrial fibrillation. In the second group, 10% with persistent atrial fibrillation and 17% with long-term persistent atrial fibrillation. Results: Average follow-up for groups 1 and 2 amounted to 47 months. There were no complications in group 1, such as bleeding and stroke. There was only 1 patient in group 1, who had died from cardiovascular disease. Freedom of atrial fibrillation was in 82% without AADs therapy. In group 2 there were 8 patients who had died from cardiovascular diseases and total freedom of atrial fibrillation was in 35% of patients, among which 42.8% had additional AADs therapy. Follow-up data are presented in Table 2. Progression of heart failure was observed in 3% in group 1 and 7% in group 2. Combined endpoints (recurrence of AF, stroke, progression of heart failure, myocardial infarction) were achieved in 16% in group 1 and 34% in group 2, respectively. Freedom from atrial fibrillation without antiarrhythmic therapy was 82% for group 1 and 35% for group 2. In the first group, there is a more pronounced decrease in heart failure rates. Deaths from cardiovascular causes were recorded in 2% for group 1 and 7% for group 2. Conclusion: Surgical treatment of atrial fibrillation helps to reduce adverse complications in the late postoperative period and contributes to the regression of heart failure.

Keywords: atrial fibrillation, coronary artery bypass grafting, ischaemic heart disease, heart failure

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Authors: Muhammad Shafi’U Adamu

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This study examined the effects of two groups of Cognitive Behavioral Therapies (CBT) which, includes Cognitive Restructuring (CB) and Rational Emotive Behavioral Therapy (REBT), on the Psychological Distress of awaiting-trial Inmates in Correctional Centers in North-West Nigeria. The study had four specific objectives, four research questions, and four null hypotheses. The study used a quasi-experimental design that involved pre-test and post-test. The population comprised of all 7,962 awaiting-trial inmates in correctional centers in North-west Nigeria. 131 awaiting trial inmates from three intact Correctional Centers were randomly selected using the census technique. The respondents were sampled and randomly put into 3 groups (CR, REBT and Control). Kessler Psychological Distress Scale (K10) was adapted for data collection in the study. The instrument was validated by experts and subjected to a pilot study using Cronbach's Alpha with a reliability coefficient of 0.772. Each group received treatment for 8 consecutive weeks (60 minutes/week). Data collected from the field were subjected to descriptive statistics of mean, standard deviation and mean difference to answer the research questions. Inferential statistics of ANOVA and independent sample t-test were used to test the null hypotheses at P≤ 0.05 level of significance. Results in the study revealed that there was no significant difference among the pre-treatment mean scores of experimental and control groups. Statistical evidence also showed a significant difference among the mean scores of the three groups, and thus, results of the Post Hoc multiple-comparison test indicated the posttreatment reduction of psychological distress in the awaiting-trial inmates. Documented output also showed a significant difference between the post-treatment psychologically distressed mean scores of male and female awaiting-trial inmates, but there was no difference in those exposed to REBT. The research recommends that a standardized structured CBT counseling technique treatment should be designed for correctional centers across Nigeria, and CBT counseling techniques could be used in the treatment of PD in both correctional and clinical settings.

Keywords: awaiting-trial inmates, cognitive restructuring, correctional centers, rational emotive behavioral therapy

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Authors: Rajeev Manhas, M. A. Bhat, A. K. Taku, Dalip Singh, Deep Shikha, Gulzar Bader

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The study was aimed to understand the distribution of various serogroups of Pasteurella multocida in bovines, small ruminants, pig, rabbit, and poultry from Jammu, Jammu and Kashmir and to characterize the isolates with respect to LPS synthesizing genes, dermonecrotic toxin gene (toxA) gene and antibiotic resistance. For isolation, the nasopharyngeal swab procedure appeared to be better than nasal swab procedure, particularly in ovine and swine. Out of 200 samples from different animals, isolation of P. multocida could be achieved from pig and sheep (5 each) and from poultry and buffalo (2 each) samples only, which accounted for 14 isolates. Upon molecular serogrouping, 3 isolates from sheep and 2 isolates from poultry were found as serogroup A, 2 isolates from buffalo were confirmed as serogroup B and 5 isolates from pig were found to belong to serogroup D. However, 2 isolates from sheep could not be typed, hence, untypable. All the 14 isolates were subjected to mPCR genotyping. A total of 10 isolates, 5 each from pig and sheep, generated an amplicon specific to genotype L6 and L6 indicates Heddleston serovars 10, 11, 12 and 15. Similarly, 2 isolates from bovines generated an amplicon of genotype L2 which indicates Heddleston serovar 2/5. However, 2 isolates from poultry generated specific amplicon with L1 signifying Heddleston serovar 1, but these isolates also produced multiple bands with primer L5. Only, one isolate of capsular type A from sheep possessed the structural gene, toxA for dermonecrotoxin. There was variability in the antimicrobial susceptibility pattern in sheep isolates, but overall the rate of tetracycline resistance was relatively high (64.28%) in our strains while all the isolates were sensitive to streptomycin. Except for the swine isolates and one toxigenic sheep isolate, the P. multocida isolates from this study were sensitive to quinolones. Although the level of resistance to commercial antibiotics was generally low, the use of tetracycline and erythromycin was not recommended.

Keywords: antibiogram, genotyping, Pasteurella multocida, serogrouping, toxA

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Authors: Swarnadip Ghosh

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Sentiment Analysis is the process of detecting the contextual polarity of text. In other words, it determines whether a piece of writing is positive, negative or neutral.Sentiment analysis of documents holds great importance in today's world, when numerous information is stored in databases and in the world wide web. An efficient algorithm to illicit such information, would be beneficial for social, economic as well as medical purposes. In this project, we have developed an algorithm to classify a document into positive or negative. Using our algorithm, we obtained a feature set from the data, and classified the documents based on this feature set. It is important to note that, in the classification, we have not used the independence assumption, which is considered by many procedures like the Naive Bayes. This makes the algorithm more general in scope. Moreover, because of the sparsity and high dimensionality of such data, we did not use empirical distribution for estimation, but developed a method by finding degree of close clustering of the data points. We have applied our algorithm on a movie review data set obtained from IMDb and obtained satisfactory results.

Keywords: sentiment, Run's Test, cross validation, higher dimensional pmf estimation

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Authors: Ayodele Ajayi, John Ajayi

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This paper investigates the effect of corporate governance with a view to determining the relationship between board size and bank performance. Data for the study were obtained from the audited financial statements of five sampled banks listed on the Nigerian Stock Exchange. Panel data technique was adopted and analysis was carried out with the use of multiple regression and pooled ordinary least square. Results from the study show that the larger the board size, the greater the profit implying that corporate governance is positively correlated with bank performance.

Keywords: corporate governance, banks performance, board size, pooled data

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Authors: William Coburn, Dylan Hauchard, Amel Naouali

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Background: The nature of the HIV epidemic in Puerto Rico (PR) is less understood than in the continental U.S. There is evidence to suggest that there are differences in health care access based on geographical location, such that rural areas are less underserved and have less immediate access to HIV prevention resources. Methods: The current study consists of a cross-sectional online survey of self-reporting HIV-negative sexual minority men (SMM) residing in PR. Results: In this sample, there were no differences between urban and rural-based services for SMM. However, more than half of the sample reported that they have never disclosed their gender identity and sexual practices to a physician. Conclusion: HIV is a significant public health concern affecting Latinos/Hispanics in the U.S. Findings in this paper can have implications for HIV prevention services in PR specifically, as few studies have directly focused on the impact of HIV and health care services in PR outside of the continental U.S.

Keywords: HIV, Puerto Rico, infectious diseases , public health

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Authors: Anouar El Younssi

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This study seeks to shed some light on the political and social ramifications and implications of Haifaa al-Mansour’s 2012 film Wadjda. The film made international headlines following its release, and was touted as the first film ever to be shot in its entirety inside the Kingdom of Saudi Arabia, and also the first to be directed by a female (Haifaa al-Mansour). Wadjda revolves around a simple storyline: A teenage Saudi girl living in the capital city Riyadh—named Wadjda—wants to have a bicycle just like her male teenage neighbor and friend Abdullah, but her ultra-conservative Saudi society places so many constraints on its female population—including not allowing girls and women to ride bicycles. Wadjda, who displays a rebellious spirit, takes concrete steps to save money in order to realize her dream of buying a bicycle. For example, she starts making and selling sports bracelets to her school mates, and she decides to participate in a Qur’an competition in hopes of winning a sum of money that comes with the first prize. In the end, Wadjda could not beat the system on her own, but the film reverses course, and the audience gets a happy ending: Wadjda’s mother, whose husband has decided to take a second wife, defies the system and buys her daughter the very bicycle Wadjda has been dreaming of. It is quite significant that the mother takes her daughter’s side on the subject of the bicycle at the end of the film, for this shows that she finally came to the realization that she and her daughter are both oppressed by the cultural norms prevalent in Saudi society. It is no coincidence that this change of heart and action on the part of the mother takes place immediately after the wedding night celebrating her husband’s second marriage. Gender inequality is thus placed front and center in the film. Nevertheless, a major finding of this study is that the film carries out its social critique in a soft and almost covert manner. The female actors in the film never issue a direct criticism of Saudi society or government; the criticism is consistently implied and subtle throughout. It is a criticism that relies more on showing than telling. The film shows us—rather than tells us directly—what is wrong, and lets us, the audience, decide and make a judgment. In fact, showing could arguably be more powerful and impactful than telling. Regarding methodology, this study will focus on and analyze the visuals and a number of key utterances by the main actor Wadjda in order to corroborate the study’s argument about the film’s bent on critiquing patriarchy. This research will attempt to establish a link between the film as an art object and as a social text. Ultimately, Wadjda sends a message of hope, that change is possible and that it is already happening slowly inside the Kingdom. It also sends the message that an insurrectional approach regarding women’s rights in Saudi Arabia is perhaps not the right one, at least at this historical juncture.

Keywords: bicycle, gender inequality, social critique, Wadjda, women’s rights

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Authors: Sadia Nasrin Tisha, Mushfika Sharmin Rahman, Javier Orduz

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Machine learning is applied in a variety of fields throughout the world. The healthcare sector has benefited enormously from it. One of the most effective approaches for predicting human heart diseases is to use machine learning applications to classify data and predict the outcome as a classification. However, with the rapid advancement of quantum technology, quantum computing has emerged as a potential game-changer for many applications. Quantum algorithms have the potential to execute substantially faster than their classical equivalents, which can lead to significant improvements in computational performance and efficiency. In this study, we applied quantum machine learning concepts to predict coronary heart diseases from text data. We experimented thrice with three different features; and three feature sets. The data set consisted of 100 data points. We pursue to do a comparative analysis of the two approaches, highlighting the potential benefits of quantum machine learning for predicting heart diseases.

Keywords: quantum machine learning, SVM, QSVM, matrix product state

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Authors: Brenden M. Shutt, Lubjana Beshaj, Paul L. Goethals, Ambrose Kam

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Communication security is of particular interest to military data networks. A relatively novel approach to network security is blockchain, a cryptographically secured distribution ledger with a decentralized consensus mechanism for data transaction processing. Recent advances in blockchain technology have proposed new techniques for both data validation and trust management, as well as different frameworks for managing dataflow. The purpose of this work is to test the feasibility of different blockchain architectures as applied to military command and control networks. Various architectures are tested through discrete-event simulation and the feasibility is determined based upon a blockchain design’s ability to maintain long-term stable performance at industry standards of throughput, network latency, and security. This work proposes a consortium blockchain architecture with a computationally inexpensive consensus mechanism, one that leverages a Proof-of-Identity (PoI) concept and a reputation management mechanism.

Keywords: blockchain, consensus mechanism, discrete-event simulation, fog computing

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Authors: Bin Mohamed Ebrahim, Aminesh Singla, Henry Pleass

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Aim: There is an ongoing gap in renal transplantation between organs available for donation and recipients on the waiting list. Live donors with pre-existing or a history of renal calculi were thought to be a relative contraindication due to safety concerns for donors. We aim to review current literature assessing outcomes of donors who were found to have a history of renal calculi. Methods: Ovid and Embase were searched between 1960 to 2021 using key terms and Medical Subject Headings (MeSH) – nephrolithiasis, renal stones, renal transplantation and renal graft. Articles included conference proceedings and journal articles and were not excluded based on patient numbers. Studies were excluded if the specific organ was not identified, duplicated reports found or if post-transplant outcomes were not recorded. Outcomes were donor’s renal function or renal calculi recurrence postoperatively. Results: Upon reviewing 344 articles, 14 manuscripts met inclusion criteria. A total of 152 live donors were identified as having pre-existing or with a history of renal calculi at pre-operative workup. The mean stone size was 2.6 4mm (1 – 16) with a mean follow-up duration of 31.8 months (1 – 96). Seven studies had both outcomes. None showed renal complications or stone recurrence. The remaining studies contained 2 out of 84 patients having recurrent nephrolithiasis. Conclusion: Data suggests minimal morbidity involved for live renal donors with a history of nephrolithiasis. This should encourage surgeons to continue recruiting such donors for kidney transplantation.

Keywords: renal transplantation, renal graft, nephrolithiasis, renal calculi, live donor

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Authors: Trapti Sharma, Devesh Kumar Srivastava

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This paper is basically a analysis study of above MapReduce implementation and also to verify and validate the MapReduce solution model for Parallel K-Mediod algorithm on Hadoop Cluster. MapReduce is a programming model which authorize the managing of huge amounts of data in parallel, on a large number of devices. It is specially well suited to constant or moderate changing set of data since the implementation point of a position is usually high. MapReduce has slowly become the framework of choice for “big data”. The MapReduce model authorizes for systematic and instant organizing of large scale data with a cluster of evaluate nodes. One of the primary affect in Hadoop is how to minimize the completion length (i.e. makespan) of a set of MapReduce duty. In this paper, we have verified and validated various MapReduce applications like wordcount, grep, terasort and parallel K-Mediod clustering algorithm. We have found that as the amount of nodes increases the completion time decreases.

Keywords: hadoop, mapreduce, k-mediod, validation, verification

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Authors: Mohammadreza Bakhtiari, Mehrdad Maghsoudi, Hamidreza Bakhtiari

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The widespread adoption of laptops has become essential to modern lifestyles, supporting work, education, and entertainment. Social media platforms have emerged as key spaces where users share real-time feedback on laptop performance, providing a valuable source of data for understanding consumer preferences. This study leverages aspect-based sentiment analysis (ABSA) on 1.5 million tweets to examine how users from developed and developing countries perceive and prioritize 16 key laptop features. The analysis reveals that consumers in developing countries express higher satisfaction overall, emphasizing affordability, durability, and reliability. Conversely, users in developed countries demonstrate more critical attitudes, especially toward performance-related aspects such as cooling systems, battery life, and chargers. The study employs a mixed-methods approach, combining ABSA using the PyABSA framework with expert insights gathered through a Delphi panel of ten industry professionals. Data preprocessing included cleaning, filtering, and aspect extraction from tweets. Universal issues such as battery efficiency and fan performance were identified, reflecting shared challenges across markets. However, priorities diverge between regions, while users in developed countries demand high-performance models with advanced features, those in developing countries seek products that offer strong value for money and long-term durability. The findings suggest that laptop manufacturers should adopt a market-specific strategy by developing differentiated product lines. For developed markets, the focus should be on cutting-edge technologies, enhanced cooling solutions, and comprehensive warranty services. In developing markets, emphasis should be placed on affordability, versatile port options, and robust designs. Additionally, the study highlights the importance of universal charging solutions and continuous sentiment monitoring to adapt to evolving consumer needs. This research offers practical insights for manufacturers seeking to optimize product development and marketing strategies for global markets, ensuring enhanced user satisfaction and long-term competitiveness. Future studies could explore multi-source data integration and conduct longitudinal analyses to capture changing trends over time.

Keywords: consumer behavior, durability, laptop industry, sentiment analysis, social media analytics

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Authors: Billel Kenidra, Mohamed Benmohammed

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Data mining technique used in the field of clustering is a subject of active research and assists in biological pattern recognition and extraction of new knowledge from raw data. Clustering means the act of partitioning an unlabeled dataset into groups of similar objects. Each group, called a cluster, consists of objects that are similar between themselves and dissimilar to objects of other groups. Several clustering methods are based on partitional clustering. This category attempts to directly decompose the dataset into a set of disjoint clusters leading to an integer number of clusters that optimizes a given criterion function. The criterion function may emphasize a local or a global structure of the data, and its optimization is an iterative relocation procedure. The K-Means algorithm is one of the most widely used partitional clustering techniques. Since K-Means is extremely sensitive to the initial choice of centers and a poor choice of centers may lead to a local optimum that is quite inferior to the global optimum, we propose a strategy to initiate K-Means centers. The improved K-Means algorithm is compared with the original K-Means, and the results prove how the efficiency has been significantly improved.

Keywords: microarray data mining, biological pattern recognition, partitional clustering, k-means algorithm, centroid initialization

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Authors: Lyne Chantal Boudreau, Claudine Auger, Arline Laforest

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As an English-speaking country, Canada faces challenges in French-language education. During both editions of a provincial congress on education planned and conducted under shared cultural leadership, three organizers created a Francophone space where, for the first time in the province of New Brunswick (the only officially bilingual province in Canada), a group of stakeholders from the school, post-secondary and community sectors have succeeded in contributing to reflections on specific topics by sharing winning practices to meet the challenges of learning in a minority Francophone environment. Shared cultural leadership is a hybrid between theories of leadership styles in minority communities and theories of shared leadership. Through shared cultural leadership, the goal is simply to guide leadership and to set up all minority leaderships in minority context through shared leadership. This leadership style requires leaders to transition from a hierarchical to a horizontal approach, that is, to an approach where each individual is at the same level. In this exploratory research, it has been demonstrated that shared leadership exercised under the T-learning model best fosters the mobilization of all partners in advancing in-depth knowledge in a particular field while simultaneously allowing learning of the elements related to the domain in question. This session will present how it is possible to mobilize the whole community through leaders who continually develop their knowledge and skills in their specific field but also in related fields. Leaders in this style of management associated to shared cultural leadership acquire the ability to consider solutions to problems from a holistic perspective and to develop a collective power derived from the leadership of each and everyone in a space where all are rallied to promote the ultimate advancement of society.

Keywords: education, minority context, shared leadership, t-leaning

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Authors: Nishita Jaiswal, Apoorv Mohan Satpute

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The increasing demand for efficient, cost-effective motor control systems in the automotive industry has driven the need for advanced, highly optimized control algorithms. Field-Oriented Control (FOC) has established itself as the leading approach for motor control, offering precise and dynamic regulation of torque, speed, and position. However, as energy efficiency becomes more critical in modern applications, implementing FOC on low-power, cost-sensitive microcontrollers pose significant challenges due to the limited availability of computational and hardware resources. Currently, most solutions rely on high-performance 32-bit microcontrollers or Application-Specific Integrated Circuits (ASICs) equipped with Floating Point Units (FPUs) and Hardware Accelerated Units (HAUs). These advanced platforms enable rapid computation and simplify the execution of complex control algorithms like FOC. However, these benefits come at the expense of higher costs, increased power consumption, and added system complexity. These drawbacks limit their suitability for embedded systems with strict power and budget constraints, where achieving energy and execution efficiency without compromising performance is essential. In this paper, we present an alternative approach that utilizes optimized data representation and computation techniques on a 16-bit microcontroller without FPUs or HAUs. By carefully optimizing data point formats and employing fixed-point arithmetic, we demonstrate how the precision and computational efficiency required for FOC can be maintained in resource-constrained environments. This approach eliminates the overhead performance associated with floating-point operations and hardware acceleration, providing a more practical solution in terms of cost, scalability and improved execution time efficiency, allowing faster response in motor control applications. Furthermore, it enhances system design flexibility, making it particularly well-suited for applications that demand stringent control over power consumption and costs.

Keywords: field-oriented control, fixed-point arithmetic, floating point unit, hardware accelerator unit, motor control systems

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Authors: Young Gyu Kim, Sangguk Ahn, Gyoutae Park, Hiesik Kim

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In the gas industrial fields, there are many problems to detect extremely small amounts of combustible gas (CH₄) if a conventional semiconductor is used. Those reasons are that measuring is difficult at the low concentration level, the stabilization time is long, and an initial response time is slow. In this study, we propose a method to solve these issues using two specific sensors to overcome the circumstances of temperature and humidity. This idea is to combine a catalytic and a semiconductor type sensor and to utilize every advantage from every sensor’s characteristic. In order to achieve the goal, we reduced fluctuations of a gas sensor for temperature and humidity by applying designed circuits for sensing temperature and humidity. And we induced the best calibration line of gas sensors through adjusting a weight value corresponding to changeable patterns of temperature and humidity after their data are previously acquired and stored. We proposed and developed the gas leak detector using two sensor modules, which is first operated by a semiconductor sensor for measuring small gas quantities and second a catalytic type sensor is detected if measuring range of the first sensor is beyond. We conclusively verified characteristics of sharp sensitivity and fast response time against even at lower gas concentration level through experiments other than a conventional gas sensor. We think that our proposed idea is very useful if another gas leak is developed to enable measuring extremely small quantities of toxic and flammable gases.

Keywords: gas sensor, leak detector, lower concentration, and calibration

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Authors: Mumtaz Ali Baloch

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This article aims at to review the policies and gaps including the socioeconomic and institutional factors that affected the enrollment of disabled children and caused drop-outs. It provides insights to scrutinize the gaps in policies, socioeconomic, and institutional factors with the specific concern in enrollment and drop out of disabled children in Pakistan, and Balochistan in particular. The findings of this study revealed that the old-age centralized policies and a number of socio-economic and institutional factors seemed to have significantly affected the enrollment and quality education in the case of physically disabled children. There were only a few schools functional in entire Balochistan. For example, an entire province (Balochistan) there are only two schools for disabled children, established in Quetta city. In the other 31 districts, an estimated population of 300,000 people of each district there were no schools for the disabled children. The findings of this study revealed that there is a great distinction between the policy and practice in the case of physically disabled children in Quetta, Balochistan. Consequently, such children seemed to have been out of schools. Dropout after the class eighth grade is almost 100%, as there are no high schools available for physically/disabled children, in Balochistan. The concerned organizations and authorities need to develop and ratify specific policies, provide required) facilities to the schools including sufficient budget, streamline the academic planning, and an effective monitoring and evaluation system. Only awareness and motivation could not help in improving the enrollment rate and decreasing the dropout in the case of physically disabled children. There is an urgent need to provide the required facilities to the schools. Almost all students needed assistive equipment, effective physical therapy as well as regular medical facilities. Such measures can improve the enrolment and rehabilitation of children.

Keywords: education policy, practices, physically disabled children, challenges, Balochistan, Pakistan

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Authors: Jing Zhao, Dayong Liu, Shihao Wang, Xinghua Zhu, Delong Li

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Uhumanned Underwater Vehicles generally operate in the deep sea, which has its own unique working conditions. Lithium-ion power batteries should have the necessary stability and endurance for use as an underwater vehicle’s power source. Therefore, it is essential to accurately forecast how long lithium-ion batteries will last in order to maintain the system’s reliability and safety. In order to model and forecast lithium battery Remaining Useful Life (RUL), this research suggests a model based on Complete Ensemble Empirical Mode Decomposition with Adaptive noise-Temporal Convolutional Net (CEEMDAN-TCN). In this study, two datasets, NASA and CALCE, which have a specific gap in capacity data fluctuation, are used to verify the model and examine the experimental results in order to demonstrate the generalizability of the concept. The experiments demonstrate the network structure’s strong universality and ability to achieve good fitting outcomes on the test set for various battery dataset types. The evaluation metrics reveal that the CEEMDAN-TCN prediction performance of TCN is 25% to 35% better than that of a single neural network, proving that feature expansion and modal decomposition can both enhance the model’s generalizability and be extremely useful in industrial settings.

Keywords: lithium-ion battery, remaining useful life, complete EEMD with adaptive noise, temporal convolutional net

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Authors: Muhammad Umer Mehmood, Muhammad Luqman, Muhammad Yaseen, Imtiaz Hussain

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Climate change is an arduous fact, which could not be unheeded easily. It is a phenomenon which has brought a collection of challenges for the mankind. Scientists have found many of its negative impacts on the life of human being and the resources on which the life of humanity is dependent. There are many issues which are associated with the factor of prime importance in this study, 'climate change'. Whenever changes happen in nature, they strike the whole globe. Effects of these changes vary from region to region. Climate of every region of this globe is different from the other. Even within a state, country or the province has different climatic conditions. So it is mandatory that the response in that specific region and the coping strategy of this specific region should be according to the prevailing risk. In the present study, the objective was to assess the coping strategies and vulnerability of small landholders. So that a professional suggestion could be made to cope with the vulnerability factor of small farmers. The cross-sectional research design was used with the intervention of quantitative approach. The study was conducted in the Khanewal district, of Punjab, Pakistan. 120 small farmers were interviewed after randomized sampling from the population of respective area. All respondents were above the age of 15 years. A questionnaire was developed after keen observation of facts in the respective area. Content and face validity of the instrument was assessed with SPSS and experts in the field. Data were analyzed through SPSS using descriptive statistics. From the sample of 120, 81.67% of the respondents claimed that the environment is getting warmer and not fit for their present agricultural practices. 84.17% of the sample expressed serious concern that they are disturbed due to change in rainfall pattern and vulnerability towards the climatic effects. On the other hand, they expressed that they are not good at tackling the effects of climate change. Adaptation of coping strategies like change in cropping pattern, use of resistant varieties, varieties with minimum water requirement, intercropping and tree planting was low by more than half of the sample. From the sample 63.33% small farmers said that the coping strategies they adopt are not effective enough. The present study showed that subsistence farming, lack of marketing and overall infrastructure, lack of access to social security networks, limited access to agriculture extension services, inappropriate access to agrometeorological system, unawareness and access to scientific development and low crop yield are the prominent factors which are responsible for the vulnerability of small farmers. A comprehensive study should be conducted at national level so that a national policy could be formulated to cope with the dilemma in future with relevance to climate change. Mainstreaming and collaboration among the researchers and academicians could prove beneficiary in this regard the interest of national leaders’ does matter. Proper policies to avoid the vulnerability factors should be the top priority. The world is taking up this issue with full responsibility as should we, keeping in view the local situation.

Keywords: adaptation, coping strategies, climate change, Pakistan, small farmers, vulnerability

Procedia PDF Downloads 147