Miracle-dz/UniFAR-FTUs huggingface dataset:
Using Population-Based Structures to Actively Monitor AEFIs during a Mass Immunization Campaign—A Case of Measles–Rubella and Polio Vaccines

Active vaccine pharmacovigilance complements the standard passive or spontaneous surveillance system, which suffers from low reporting rates. This study aimed at utilizing population-based structures to report and profile adverse events following immunization (AEFI) with the measles and rubella vaccine (MR), or MR in combination with the bivalent oral polio vaccine (bOPV 1&3) (MR & bOPV), during mass vaccination in Uganda. Caretakers of children at home (less than 5 years) and schoolgoing children were followed up on and encouraged to report any AEFIs on day one, 2–3 days, 10 days, and 14 days after vaccination at school by their teachers and at-home, community-based village health teams. Out of 9798 children followed up on, 382 (3.9%) reported at least one AEFI, and in total, 517 AEFIs were reported. For MR, high temperature (21%), general feeling of weakness (19.3%), and headache (13%) were the most reported AEFIs, though there were variations on the days when they were reported. For the combination dose of MR & bOPV, high temperature (44%), rash (17%), general feeling of weakness (13%), and diarrhoea (8%) were the most common adverse events following immunization reported by caretakers. All 382 children cleared the AEFIs within 2 days, with 343 (90%) children reporting mild or moderate AEFIs and only 39 (10%) reporting severe AEFIs. The reported AEFIs are known and are mentioned in the vaccine leaflets with similar severity classification. Rates of AEFIs differed with the number of days after receiving the immunization. Conclusion: Active surveillance for AEFIs provides additional important information to national vaccine regulatory bodies. It reassures the public that vaccines are safe and that their safety is being taken seriously in Uganda, which would improve vaccine acceptability and confidence in the health system. Piggybacking on existing structures such as village health team members (for children at home) and teachers (for schoolgoing children) facilitates reaching vaccine recipients and increases reporting rates. Therefore, studies using active reporting of AEFIs should be conducted at regular intervals to report the overall incidence of AEs and to monitor trends and changes.
Formulating a functional drink with antiosteoporosis effects

Introduction. Osteoporosis is one of the most common diseases of the musculoskeletal system in modern clinical practice. Its prevention and treatment requires a diet with a sufficient intake of calcium, vitamins, and connective tissue proteins that regenerate cartilage and bone tissue. We aimed to formulate a functional product based on collagen fermentolysate to prevent osteoporosis and prove its effects in experiments on laboratory rats. Study objects and methods. Our study objects were collagen fermentolysate obtained from pork ears and legs (1:1) and the functional product based on it. The biological experiment was carried out on Wistar female rats exposed to osteoporosis through complete ovariectomy. Their femurs were analyzed for the contents of phosphorus, magnesium, and calcium, as well as cytometric and biochemical blood parameters. Results and discussion. The formulated functional product based on collagen fermentolysate contained 41% of the most easily assimilable peptide fractions with a low molecular weight of 10 to 20 kDa. Other components included pumpkin powder, dietary fiber, calcium, chondroprotectors, and vitamins E, C, and D3. Compared to the control, the experimental rats that received the functional product had increased contents of calcium and magnesium in the bone tissue (by 25.0 and 3.0%, respectively), a decreased content of phosphorus (by 7.0%), a calcium-to-phosphorus ratio restored to 2.4:1.0, and a higher concentration of osteocalcin in the blood serum (by 15%). Conclusion. The developed functional product based on collagen fermentolysate can be used as an additional source of connective tissue protein, calcium, vitamins C, E, and D3, dietary fiber, and chondroprotectors to prevent osteoporosis.
Anatomical Evaluation of the Foramen Magnum on Cone-Beam Computed Tomography Images and Review of Literature

Background and objective The morphology and morphometry of the foramen magnum (FM), which provides a passageway to vital neurological structures that relay information to and from the brain and spinal cord, are significant for many surgical approaches and applications. It was aimed to investigate the morphometric and morphological features of the FM on the cone-beam computed tomography (CBCT) images and to review the literature in detail. Methods CBCT images of 400 individuals (200 males, 200 females, aged between 18 and 65) were evaluated by Planmeca Romexis Viewer. The length, width, perimeter, and area of the FM were examined and samples were classified according to shape. Also, the FM index (FMI) was calculated. Results The mean values of the length, width, and perimeter were found to be 36.75±2.50 mm, 32.55±2.93 mm, and 108.35±7.50 mm, respectively. The area of FM was found to be 941.81±128.26 mm2, 946.83±127.39 mm2, and 895.76±123.50 mm2 with Planmeca Romexis Viewer, Radinsky formula, and Teixeira formula, respectively. All parameters were significantly larger in males than females. There was no correlation between age and these parameters. Also, seven shapes were determined for FM, and the most common shape was oval. FM index was evaluated according to the Martin and Saller classification. It was found that 16.5% of the cases belonged to the narrow, 16% belonged to the medium, and 67.5% to the large FM index. There was no correlation between age and FM index. Conclusion Morphometric and morphological features of the FM located in the craniovertebral junction (CVJ), which is a highly complex area, are variable. Surgical procedures and approaches in this region are essential due to the high mortality rate. For this reason, anatomical structures in these regions should be well known before surgery. The quantitative data presented in this study, which made a detailed literature comparison, may assist in surgical procedures around the FM and the planning of these procedures.
Prediction of Carbon Monoxide (CO) Atmospheric Pollution Concentrations with Machine Learning and Time Series Analysis in Langkawi, Malaysia

Carbon monoxide (CO) is a non-irritant toxic and odourless gas produced from the incomplete combustion of fossil fuels. Long-term exposures to lower levels of carbon monoxide have wide implications for human health. Thus, an early warning system for CO atmospheric concentration with an accurate and reliable forecasting method is crucial. Studies for predicting CO atmospheric concentration are still limited in Malaysia especially using data science approaches. This study aims to develop and predict future CO concentration for the next few hours by using the statistical time series approach and machine learning approach. The data used for the project is the air quality data of the monitoring station in Langkawi, Malaysia. The data mining tool used for this project is RapidMiner Studio. Based on the results, it showed that Time Series analysis with deep learning gave a reasonably good CO concentration prediction for the next 3 hours with a relative error of approximate 10%. The model developed in this project can be used by authorities as public health’s protection measure to provide an early alarm for alerting the Malaysian populations on the air pollution issue.
Learning Enhanced Acoustic Latent Representation for Small Scale Affective Corpus with Adversarial Cross Corpora Integration

Achieving robust cross contexts speech emotion recognition (SER) has become a critical next direction of research for wide adoption of SER technology. The core challenge is in the large variability of affective speech that is highly contextualized. Prior works have worked on this as a transfer learning problem that mostly focuses on developing domain adaptation strategy. However, many of the existing speech emotion corpora, even those considered as large scale, are still limited in size resulting in an unsatisfactory transfer result. On the other hand, directly collecting context-specific corpus often results in an even smaller data size leading to an inevitably non-robust accuracy. In order to mitigate this issue, we propose the concept of enhancing the affect-related variability when learning the in-context acoustic latent representation by integrating out-of-context emotion data. Specifically, we utilize adversarial autoencoder network as our backbone with multiple out-of-context emotion labels derived for each in-context samples that serve as an auxiliary constraint in learning the latent representation. We extensively evaluate our framework using three in-context databases with three out-of-context databases. In this work, we demonstrate not only an improved recognition accuracy but also a comprehensive analysis on the effectiveness of this representation learning strategy.
Perceiving Surface Roughness Through a Probe: Effects of Applied Force and Probe Diameter

The current paper constitutes a continuation of our psychophysical research on perceiving the surface roughness of raised-dot surfaces via a rigid probe. Here we investigated the perceptual consequences of varying applied force (Experiment 1) and probe diameter (Experiment 2). A passive-touch mode was used to effect contact between probe and surface. All psychophysical roughness functions were best fit by quadratic equations. Increasing force resulted in increased roughness estimates, without a corresponding shift in the peak position of the function along the interelement-spacing axis (Experiment 1). Perceived roughness decreased overall with increasing probe diameter for the narrower interelement spacings; however, perceived roughness increased overall with increasing probe diameter for the wider interelement spacings. This reversal was explained by a corresponding shift in the position of the peaks of the psychophysical functions toward the wider end of the interelement-spacing axis as probe diameter increased (Experiment 2). Implications for the design of haptic interfaces for virtual environments are also considered. In the last couple of years, we have been reporting the results of a comprehensive research program investigating how people perceive surface texture via a rigid probe. The initial and current stage of this research program involves conducting psychophysical experiments to determine a small number of critical parameters that will describe how vibration — induced by the interaction between surface and rigid probe, and passed to the skin — leads to an internal representation of surface roughness. In the second stage of this research program, we intend to develop a model that describes texture perception from a probe as the transition from mechanical interactions between probe tip and surface to perceptual responses. In the third stage of the program, we will use the vibration based model to create virtual textures with a haptic-interface by delivering vibratory forces to the fingertip. We begin by reviewing the psychophysical literature on perceiving roughness via the bare finger versus a rigid probe as intermediary.
A critical note on the scientific conception of economics: claiming for a methodological pluralism

Opponents of mainstream economics have not yet called attention to the lack of in-depth examination of the general scientific conception of modern economics. However, economic science cannot consistently fulfil the epistemological and ontological requirements of the scientific standards underlying this conception. What can be scientifically recognized as true cannot be answered, neither through the actual ontological structure of the object of observation nor through a methodological demarcation. These limitations necessarily lead to the claim for both a pragmatic and a radical methodological pluralism.
What Kind of Electoral Outcome do People Think is Good for Democracy?

There is perennial debate in comparative politics about electoral institutions, but what characterizes this debate is the lack of consideration for citizens’ perspective. In this paper, we report the results of an original survey conducted on representative samples in 15 West European countries (N = 15,414). We implemented an original instrument to elicit respondents’ views by asking them to rate “real but blind” electoral outcomes. With this survey instrument, we aimed to elicit principled rather than partisan preferences regarding the kind of electoral outcomes that citizens think is good for democracy. We find that West Europeans do not clearly endorse a majoritarian or proportional vision of democracy. They tend to focus on aspects of the government rather than parliament when they pass a judgment. They want a majority government that has few parties and enjoys wide popular support. Finally, we find only small differences between citizens of different countries.
On transformative adaptive activation functions in neural networks for gene expression inference

Motivation Gene expression profiling was made cheaper by the NIH LINCS program that profiles only ~1, 000 selected landmark genes and uses them to reconstruct the whole profile. The D–GEX method employs neural networks to infer the whole profile. However, the original D–GEX can be further significantly improved. Results We have analyzed the D–GEX method and determined that the inference can be improved using a logistic sigmoid activation function instead of the hyperbolic tangent. Moreover, we propose a novel transformative adaptive activation function that improves the gene expression inference even further and which generalizes several existing adaptive activation functions. Our improved neural network achieves average mean absolute error of 0.1340 which is a significant improvement over our reimplementation of the original D–GEX which achieves average mean absolute error 0.1637
THE RELATIONSHIP BETWEEN JOB SATISFACTION AND INDIVIDUAL PERFORMANCE OF IT EMPLOYEES

Purpose – The main purpose of this research paper is to investigate the correlation between job satisfaction of employees in the IT sector and their personal performance. Additionally, the study examines the overall level of employee satisfaction, as well as if job satisfaction levels differ significantly among the studied demographic groups. Design/methodology/approach – The research is based on quantitative analysis of data collected through a questionnaire containing answers of 126 international respondents from over 25 different IT companies. The research methods used are one-dimensional methods for preliminary analysis, Cronbach alpha for reliability and consistency, one-way ANOVA for mean values comparison and correlation analysis for examining relationships. Findings – The findings show a moderate statistically significant correlation between job satisfaction and employees’ personal performance, which is bidirectional as influence and presumably depends on other variables like work engagement, motivation, stress or exhaustion, which were not examined in the current study. Additionally, most of the employees in the researched sample define themselves as satisfied with their jobs. Statistically significant variation of the mean job satisfaction levels was observed in two of the examined demographic variables – gender and years in the current position. Practical implications – The research results can be beneficial for different organizations since job satisfaction is important for employees’ long-term retention, for increasing their commitment and loyalty towards the organization, as well as for the creation of a motivating and productive work environment. Employees’ job satisfaction and their personal performance should always be considered main organizational values and key for achieving excellent business results and market leadership. Originality/value – The results of the current research are important for validating the position of these researchers, who claim that a positive correlation between an employees’ job satisfaction and their personal performance in the workplace exists and should not be neglected. Additionally, it contributes towards a better understanding of job satisfaction among IT employees.
Robust stabilization of the Space Station

A robust H-infinity control design methodology and its application to a Space Station Freedom (SSF) attitude and momentum control problem are presented. This approach incorporates nonlinear multi-parameter variations in the state-space formulation of H-infinity control theory. An application of this robust H-infinity control synthesis technique to the SSF control problem yields remarkable results in stability robustness with respect to moments of inertia variation of about 73 percent in one of the structured uncertainty directions. The performance and stability of this robust H-infinity controller for the SSF are compared to those of other controllers designed using a standard linear-quadratic-regulator synthesis technique.
Prospective study on complications using different techniques for parotidectomy for benign tumors

Long‐term prospective studies on procedure‐related complications after parotid surgery for benign neoplasms (BNs) are scarce. This is the first prospective study on the use of extracapsular dissection (ECD) for BNs, and it aimed to examine the incidence of postoperative complications after parotid surgery for BN.
Design and Analysis of Modern Tracking Systems

The Basics of Target Tracking. Sensor and Source Characteristics. Kinematic State Estimation: Filtering and Prediction. Modelling and Tracking Dynamic Targets. Passive Sensor Tracking. Basic Methods for Data Association. Advanced Methods for MTT Data Association. Attribute Data Fusion. Multiple Sensor Tracking -- Issues and Methods. Multiple Sensor Tracking -- System Implementation and Applications. Reasoning Schemes for Situation Assessment and Sensor Management. Situation Assessment. Tracking System Performance Prediction, and Evaluation. Multi Target Tracking with an Agile Beam Radar. Sensor Management. Multiple Hypothesis Tracking System Design and Application. Detection and Tracking of Dim Targets in Clutter.
Effects of Metallic and Carbon-Based Nanomaterials on Human Pancreatic Cancer Cell Lines AsPC-1 and BxPC-3

Pancreatic cancer, due to its asymptomatic development and drug-resistance, is difficult to cure. As many metallic and carbon-based nanomaterials have shown anticancer properties, we decided to investigate their potential use as anticancer agents against human pancreatic adenocarcinoma. The objective of the study was to evaluate the toxic properties of the following nanomaterials: silver (Ag), gold (Au), platinum (Pt), graphene oxide (GO), diamond (ND), and fullerenol (C60(OH)40) against the cell lines BxPC-3, AsPC-1, HFFF-2, and HS-5. The potential cytotoxic properties were evaluated by the assessment of the cell morphology, cell viability, and cell membrane damage. The cancer cell responses to GO and ND were analysed by determination of changes in the levels of 40 different pro-inflammatory proteins. Our studies revealed that the highest cytotoxicity was obtained after the ND treatment. Moreover, BxPC-3 cells were more sensitive to ND than AsPC-1 cells due to the ND-induced ROS production. Furthermore, in both of the cancer cell lines, ND caused an increased level of IL-8 and a decreased level of TIMP-2, whereas GO caused only decreased levels of TIMP-2 and ICAM-1 proteins. This work provides important data on the toxicity of various nanoparticles against pancreatic adenocarcinoma cell lines.
Building cultural intelligence: insights from project management job advertisements

Abstract This paper examines how organisations that conduct worldwide recruitment of project management professionals can derive insight from the cultural preferences stated within project management job advertisements. Drawing on project management practitioner job advertisements placed by 2040 organisations across seven countries and seven industries, we employ Hofstede’s national cultural framework to categorise cultural preferences which the organisations persistently replicate in their specifications of desired candidate project management practitioner competency. To map global trends and national variations, data analysis is undertaking and utilising exploratory data analysis, Poisson regression and negative binomial regression are used. The paper finds that specific national cultural dimensions – ‘Collectivism’, ‘Uncertainty Avoidance’ and, to a lesser extent, ‘Power Distance’ – are the most salient cultural denominators for advertised project management positions, while this is not the case with ‘Masculinity’ and ‘Individualism’. The findings raise issues about which organisations should seek to become more culturally intelligent, and which relate to the adaptiveness of the cultural preferences that they articulate through their job advertisements, both to project tasks and to cultural contexts for projects.
Beyond the shared frailty model

This thesis deals with frailty modelling, a framework devised to analyse clustered survival data. The main focus is on modelling the frailty term. The frailty term captures the dependence of survival times within a cluster and the heterogeneity between clusters. Typical is that the frailty term is treated as a random effect. Different distributions have been proposed to model the frailty term. Contributions of this thesis include a unified framework for fitting the frailty model with different frailty distributions, a new diagnostic plot to evaluate the frailty distribution assumption, a simulation study to assess robustness of regression inference against frailty misspecification, and a method to test for decreasing cluster heterogeneity in a new time-varying frailty model. Also presented is a first step towards modelling spatial dependence in survival data by means of spatially correlated frailties.