Miracle-dz/UniFAR-FTUs huggingface dataset:
Fluctuation contrast and speech-on-speech masking: Model midbrain responses to simultaneous speech

At the level of the auditory midbrain, low-frequency fluctuations within each frequency channel drive neurons with band-pass modulation transfer functions (MTFs). The amplitude of low-frequency fluctuations in ascending neural signals is affected by stimulus amplitude due to the gradual saturation of the inner hair cells (IHCs) beginning at moderate sound levels. This level dependence of low-frequency fluctuation amplitudes results in contrast cues at the level of the midbrain: Spectral peaks result in lower responses of cells with bandpass-MTFs, whereas spectral valleys result in higher responses. Here, we focus on model population midbrain responses with different best-modulation frequencies (BMFs) to simultaneous speech. Midbrain responses were simulated for single hearing-in-noise (HINT) sentences and for a pair of simultaneous sentences, spoken by a male and a female. Correlations between population responses to individual male (or female) sentences and responses to simultaneous sentences vary with BMF in the range of the male (or female) fundamental frequencies. The pattern of fluctuation contrast across frequency in the midbrain representation provides a framework for studying speech-on-speech masking for listeners with normal hearing and sensorineural hearing loss.
USE OF TIO 2 AS A REINFORCEMENT OF CASSAVA STARCH/PVA COMPOSITES ON MOISTURE-RESISTANT PROPERTIES OF TRIBOELECTRIC NANOGENERATOR (TENG) FILM

: High humidity environments can accelerate the transmission, neutralization, or dissipation of frictional charges on the frictional surface of solid-solid triboelectric nanogenerator films (TENGs), which can reduce the output power. The moisture resistance properties of the TENG triboelectric film are needed to overcome these problems. Therefore, this study discusses the role of the TiO 2 nanofiller in cassava starch (CS) and polyvinyl alcohol (PVA) nanocomposite matrix that can increase triboelectricity through the formation of hydrogen bonds and the provision of oxygen-free electrons. The research method was to incorporate different concentrations of TiO 2 nanoparticles (0%, 0.5%, 1%, 5%, 10% wt, and 15% wt) into the CS-PVA nanocomposite matrix using the solvent casting method. The results showed an increase in surface polarity which was more triboelectric-positive due to the CS-PVA hydroxyl group interacting with water molecules. Increasing the concentration above 5% wt TiO 2 increases the density of the CS-PVA nanocomposite
The Use of Partial Least Squares to Define the Characteristics in the Environment of Higher Education Institutions and their Effects on Entrepreneurial Academic Education, a Case Study: Torreon, Mexico

Because universities have a favorable effect on student’s entrepreneurial intents, Higher Education Institutions (HEIs) are essential to the delivery entrepreneurship education. By analyzing the perceptions of students who received master diploma in management-business fields in Torreon, Mexico in 2021, the aim of the research is to identify the internal and external aspects of the HEI environment and their impact on entrepreneurial education using Partial Least Squares methodology with the help of the SmartPLS software, 120 responses from the questionnaire. Three of the original hypotheses were confirmed, while four variables—two associated with HEI ecosystem external factors and two with entrepreneurial education elements—had to be removed since they were not accepted. The findings will lead to a better comprehension of the elements influencing master students' entrepreneurial perspective to create stronger relationship with elements of the HEI ecosystem.
Deployable wavelength optimizer for multi-laser sensing and communication undersea

This effort develops and tests algorithms and a user-portable optical system designed to autonomously optimize the laser communication wavelength in open and coastal oceans. In situ optical meteorology and oceanography (METOC) data gathered and analyzed as part of the auto-selection process can be stored and forwarded. The system performs closedloop optimization of three visible-band lasers within one minute by probing the water column via passive retroreflector and polarization optics, selecting the ideal wavelength, and enabling high-speed communication. Backscattered and stray light is selectively blocked by employing polarizers and wave plates, thus increasing the signal-to-noise ratio. As an advancement in instrumentation, we present autonomy software and portable hardware, and demonstrate this new system in two environments: ocean bay seawater and outdoor test pool freshwater. The next generation design is also presented. Once fully miniaturized, the optical payload and software will be ready for deployment on manned and unmanned platforms such as buoys and vehicles. Gathering timely and accurate ocean sensing data in situ will dramatically increase the knowledge base and capabilities for environmental sensing, defense, and industrial applications. Furthermore, communicating on the optimal channel increases transfer rates, propagation range, and mission length, all while reducing power consumption in undersea platforms.
Thinking Like a Machine

As part of ongoing research bridging ethnomethodology and computer science, in this article we offer an alternate reading of Alan Turing’s 1936 paper, “On Computable Numbers”. Following through Turing’s machinic respecification of computation, we hope to contribute to a deflationary position on AI by showing that the activities attributed to AIs are achieved in the course of methodic hands-on work with computational systems and not in isolation by them. Turing’s major innovation was a demonstration that mathematical and logical operations could be broken down into elementary, mechanically executable operations, devoid of intellectual content. Drawing out lessons from a re-enactment of Turing’s methods as a means of reflecting on contemporary artificial intelligence (AI), including the way those methods disappear into the technology, we will suggest the interesting question raised in “On Computable Numbers” is less about the possibilities of designing machines that “can think” (cf. Turing, 1950), but the practical work we do, and which is made possible, when we ourselves set out to think like machines.
Using the visual-world paradigm to explore the meaning of conditionals in natural language

ABSTRACT This paper reports three eye-tracking experiments using the visual world paradigm to explore the meaning of conditionals in Mandarin Chinese. Experiment 1 found that, when all the tokens were actually true in the experimental setting, the conditional connective if … then … didn't elicit significantly more anticipatory fixations than the conjunctive connective … and … on a token that is appropriately to be merged by the sentential connectives. By contrast, Experiments 2 and 3 found that, when a token was designed as hypothetically but not actually true in the experimental setting, the conditional connective elicited significantly more anticipatory fixations than the conjunctive connective on this hypothetical token. The implications of the experimental paradigm and the observed results were then discussed in relation to theories of conditionals, and to models of rationality in general.
“ROBOVID” mobile application about COVID -19 and target population: semantic validation study

Objective: to semantically validate the “ROBOVID” mobile application with the tar get population. Method: methodological study, presenting the seventh stage of the matrix project, developed between October 2021 and January 2022, with 21 adults residing in the state of Rio de Janeiro, using a semi-structured electronic form. The Concordance Index was used in the data analysis, being considered a validated item that presented a value equal to or greater than 80%. Results: the ROBOVID mobile application was validated, reaching satisfactory individual agreement rates ranging from 95% to 100% and global 98.8%. Conclusion: the mobile application “ROBOVID” was semantically validated in terms of content and appearance by the target population, indicating that this educational technology is understandable, relevant and pertinent, and can be used by the population as a tool for the prevention and control of serious sequelae resulting from covid-19
Probabilistic approach spaces

We study a probabilistic generalization of Lowen's approach spaces. Such a probabilistic approach space is defined in terms of a probabilistic distance which assigns to a point and a subset a distance distribution function. We give a suitable axiom scheme and show that the resulting category is isomorphic to the category of left-continuous probabilistic topological convergence spaces and hence is a topological category. We further show that the category of Lowen's approach spaces is isomorphic to a simultaneously bireflective and bicoreflective subcategory and that the category of probabilistic quasi-metric spaces is isomorphic to a bicoreflective subcategory of the category of probabilistic approach spaces.
CSF proteome profiling reveals highly specific biomarkers for dementia with Lewy bodies.

Diagnosis of dementia with Lewy bodies (DLB) is challenging and biofluid biomarkers specific for DLB are highly needed. Here we use proximity extension-based multiplex assays to establish the specific cerebrospinal fluid (CSF) proteomic changes that underlie DLB in an unprecedented well-characterized cohort of 109 DLB patients, 235 patients with Alzheimers disease (AD) and 190 controls. We identified more than 50 CSF proteins dysregulated in DLB, which were especially related to myelination processes. An enzyme involved in dopamine biosynthesis (L-amino acid decarboxylase, DDC) was the strongest dysregulated protein in DLB (>1.5 fold-change vs.CON or AD; q<1E-16) and could discriminate DLB from controls and AD patients with high accuracy (AUC: 0.91 and 0.81 respectively). We modelled a CSF protein panel containing only seven of these markers, which discriminate DLB from AD with higher performance (AUC: 0.93, 95%CI: 0.86-0.98). We developed custom multiplex assays for six of these markers (DDC, CRH, MMP-3, ABL1, MMP-10 and THOP1); and validated their performance in independent cohorts (n=329; AUCs: 0.68-0.90), including an autopsy cohort (n=76; AUCs: 0.90-0.95). This extensive and unique DLB CSF proteome study depicts specific protein changes underlying DLB pathophysiology. It translates these findings into a custom CSF biomarker panel able to identify DLB patients with high accuracy in different independent cohorts, providing new testing opportunities for diagnostic settings and clinical trials.
Strategies for Improving the Performance of Prediction Models for Response to Immune Checkpoint Blockade Therapy in Cancer

Immune checkpoint blockade (ICB) therapy holds promise for bringing long-lasting clinical gains for the treatment of cancer. However, studies show that only a fraction of patients respond to the treatment. In this regard, it is valuable to develop gene expression signatures based on RNA sequencing (RNAseq) data and machine learning methods to predict patients' response to the ICB therapy, which contributes to more personalized treatment strategy and better management of cancer patients. However, due to the limited sample size of ICB trials with RNAseq data available and the vast number of candidate gene expression features, it is challenging to develop well-performed gene expression signatures. In this study, we used several published melanoma datasets and investigated approaches that can improve the construction of gene expression-based prediction models. We found that merging datasets from multiple studies and incorporating prior biological knowledge yielded prediction models with higher predictive accuracies. Our finding suggests that these two strategies are of high value to identify ICB response biomarkers in future studies.
Impact of COVID-19 on the cascade of care for tuberculosis: A systematic review

Abstract Objectives To describe the impact of the COVID-19 pandemic on the TB care cascade. Methods In this systematic review, the Cochrane library, Scopus, CINAHL, Ebscohost, and PubMed databases were comprehensively searched from the onset of the pandemic, till May 5th, 2022. Eligible studies were those reporting on changes in the TB cascade of care one year before and one year during the COVID-19 pandemic. Due to the expected differences in the contexts of the included studies, a narrative synthesis was conducted. Results Twenty-seven studies, from Asia, North America, Africa, South America, and Europe were included. TB screening decreased by between 1% - 50%, and multidrug resistance tuberculosis (MDR-TB) screening decreased by between 15%-17%. Diagnostic delay increased by between 35 - 45 days, contact tracing decreased by up to 36.1%, and case notification decreased by between 3%-63%. TB treatment enrolment decreased by between 16%-35.0%, treatment completion decreased by around 8.0% and treatment success decreased by up to 17.0%. Conclusion COVID-19 had a detrimental impact on the TB care cascade and these findings suggest a need for policies to protect healthcare systems for TB and other communicable diseases in future health emergencies.
Species distribution modeling for disease ecology: a multi-scale case study for schistosomiasis host snails in Brazil

Species distribution models (SDMs) are increasingly popular tools for profiling disease risk in ecology, particularly for infectious diseases of public health importance that include an obligate non-human host in their transmission cycle. SDMs can create high-resolution maps of host distribution across geographical scales, reflecting baseline risk of disease. However, as SDM computational methods have rapidly expanded, there are many outstanding methodological questions. Here we address key questions about SDM application, using schistosomiasis risk in Brazil as a case study. Schistosomiasis--a debilitating parasitic disease of poverty affecting over 200 million people across Africa, Asia, and South America--is transmitted to humans through contact with the free-living infectious stage of Schistosoma spp. parasites released from freshwater snails, the parasites obligate intermediate hosts. In this study, we compared snail SDM performance across machine learning (ML) approaches (MaxEnt, Random Forest, and Boosted Regression Trees), geographic extents (national, regional, and state), types of presence data (expert-collected and publicly-available), and snail species (Biomphalaria glabrata, B. tenagophila and B. straminea). We used high-resolution (1km) climate, hydrology, land-use/land-cover (LULC), and soil property data to describe the snails ecological niche and evaluated models on multiple criteria. Although all ML approaches produced comparable spatially cross-validated performance metrics, their suitability maps showed major qualitative differences that required validation based on local expert knowledge. Additionally, our findings revealed varying importance of LULC and bioclimatic variables for different snail species at different spatial scales. Finally, we found that models using publicly-available data predicted snail distribution with comparable AUC values to models using expert-collected data. This work serves as an instructional guide to SDM methods that can be applied to a range of vector-borne and zoonotic diseases. In addition, it advances our understanding of the relevant environment and bioclimatic determinants of schistosomiasis risk in Brazil.
Examination of Influenza A Infection Rate, Its Determinants, and Seasonal Influenza Vaccine Effectiveness in the Post-COVID-19 Pandemic Era

Background In the context of the COVID-19 pandemic, a pronounced wave of Influenza A occurred in the 2022/23 winter season under generally relaxed post-pandemic non-pharmaceutical preventive measures. Aim This study aimed to investigate the Influenza A infection rate, factors influencing its occurrence and seasonal Influenza vaccine effectiveness on seroconversion in the post-COVID-19 pandemic era. Methods The seroconversion of Anti-Influenza-A-Nucleoprotein/Matrix IgG was investigated in 402 healthcare workers (HCWs) during the winter season of 2022/2023 (23 May 2022 to 11 May 2023). The participants provided a serum sample and completed a study questionnaire both before and after the seasonal Influenza A wave (24 October 2022 to 8 January 2023). The levels of a vaccine-independent Anti-Influenza-A-Nucleoprotein/Matrix IgG were measured using the SERION ELISA classic Influenza A IgG assay, with a 2-fold increase as indicative of seroconversion after asymptomatic or symptomatic influenza infection. Results Out of the 402 study participants, 20.6% (95% CI 17.0-24.9%; 83/402) showed seroconversion. The multivariate logistic regression analysis revealed that the age category of [≥]45 years (p=0.03) and regular patient contact (p=0.02) significantly influenced seroconversion. However, the factors male gender, BMI, smoking, household size, seasonal Influenza vaccination, and SARS-CoV-2 infection during the Influenza A season were not significantly associated with seroconversion. The vaccine effectiveness of the 2022/23 seasonal Influenza vaccination on seroconversion was 22.6% (95% CI -17.1-50.6%). Conclusion During the initial Influenza A season following the COVID-19 pandemic, approximately 20% of HCWs contracted an Influenza A infection. This highlights a potential risk and a significant asymptomatic or symptomatic infection rate posing a theoretical risk for intrahospital transmission chains and nosocomial infections.
Power Saving Approach of a Smart Watch for Monitoring the Heart Rate of a Runner

Heart Rate (HR) monitoring in a smart watch is a battery consuming process. Therefore, some smart watches prevent continuous HR sampling during low-level physical activities for improving the power usage of batteries. However, high acceleration events like running require continuous HR sampling for recording the varying HR readings, which consumes a lot of battery power. Therefore, the challenge is to reduce the sampling during running while recording an individual’s HR variation (HRV). Our approach prevents continuous HR sampling for long-running events without missing important HR information. In this context, we analyze the existing real-life HRs and acceleration datasets recorded on humans during long runs. We design an adaptive HR sampling algorithm, A-HeaRing, from the extracted HR variation details. A-HeaRing reduces the battery power consumption of a smart watch by more than 50% while recording a running event. Additionally, we design a data regeneration system for missing HR readings. The regeneration system provides a minimum of 90% accuracy in the HR zone estimation.
Performance Analysis of a Dynamic Test Bench Based on a Linear Direct Drive

This paper describes the design and performance of a dynamic test bench used for dynamic testing of special sensor systems intended for use in vehicle chassis. In order to economically meet all requirements of a dynamic driving simulation, the dynamic test bench is being developed on the basis of a linear direct drive. The test bench has a modular design and can be used flexibly, i.e. vertically or horizontally. No ferromagnetic material is used in the measuring range of the sensor to minimize measurement inaccuracies. The performance requirements to be met are to the achievable acceleration and frequency, the stroke distance and the positioning accuracy. The test bench must be capable of accelerating at a minimum of 30 g while realizing an oscillation of at least 12 Hz. Regardless of the dynamic requirements, a minimum stroke distance of 500 mm is required. The required positioning accuracy is 1 mm. To ensure that all requirements are met, the performance limits of the test bench are determined experimentally and validated mathematically. In addition to the maximum acceleration and the maximum realizable frequency, the maximum stroke speed of the test rig is determined. Furthermore, the critical resonance frequencies of the test bench, which can lead to disturbances, are determined. As a result, all required performance values are exceeded by the dynamic test bench.
Newborn Screening Program for Cystic Fibrosis in Cuba: Three Years’ Experience

In Cuba, newborn screening (NBS) for cystic fibrosis (CF) was introduced in January 2019. The results from the first three years of the CF NBS program are presented. An IRT/IRT protocol was followed using a cut-off value of 50 ng/mL. In this period 281,717 neonates were screened, 2,197 samples had increased IRT values, and a second sample was necessary (recall rate=0.78%). In 686 (0.24%) neonates, IRT was still elevated, and they were referred for clinical evaluation. Twenty-one children were confirmed by sweat test and molecular biology. Eighteen newborns presented variant F508del. A false negative case was reported. Demographic data of 32,764 neonates were collected. The average age of sampling was six days with results available at 11 days of life, but 1.7% of the samples were collected 20 days after birth. The mean IRT value was 12.7±11.7 ng/mL (ranging 0–283 ng/mL) with a calculated 98.5 percentile value of 42.4 ng/mL. On average, the samples were processed five days after collection and two days after they were received at the laboratory. Although CF NBS program in Cuba is just beginning, it can be predicted that CF will be one of the most frequent inherited-metabolic diseases in the Cuban population.
Employability Capital for Tour Guides at a World Heritage Site

Aim. Employability has gained increased interest after the respective global shocks of 2008 and 2020. The study deepens the theory of employability in relation to a globally significant tourism industry. The aim of the study is to identify the core dimensions of the employability of tour-guides. Method. The study adopted a qualitatively intrinsic case study at a world heritage site (WHS), namely the Maropeng Visitor Centre. The researcher focused on the notion of employability for tour-guides, based on existing research gaps regarding those two central concepts. Results. The study determines the roles and responsibilities of tour-guides so as to align these to the notion of employability capital of tour-guides. Secondly, the study probed how higher education institutions (HEIs) should contribute to tour-guides’ employability particularly, and their employability capital, generally. Moreover, misconceptions emerged about HEIs’ offerings concerning employability and tour-guides’ education. Conclusions. Employability capital has become a factor influencing success in the work environment. This study revealed the importance of practical courses in tourism education (tour guiding, first aid, and additional languages) and highlighted the imperative to understand students’ skills and capabilities within the scope of practical training courses. Originality. The study advances knowledge on employability capital in relation to tour guiding at WHS. This would help to develop a better system that would increase employability capital in the tour-guiding sector.