Miracle-dz/UniFAR-FTUs huggingface dataset:
Optical Microphone-Based Speech Reconstruction System With Deep Learning for Individuals With Hearing Loss

Objective: Although many speech enhancement (SE) algorithms have been proposed to promote speech perception in hearing-impaired patients, the conventional SE approaches that perform well under quiet and/or stationary noises fail under nonstationary noises and/or when the speaker is at a considerable distance. Therefore, the objective of this study is to overcome the limitations of the conventional speech enhancement approaches. Method: This study proposes a speaker-closed deep learning-based SE method together with an optical microphone to acquire and enhance the speech of a target speaker. Results: The objective evaluation scores achieved by the proposed method outperformed the baseline methods by a margin of 0.21–0.27 and 0.34–0.64 in speech quality (HASQI) and speech comprehension/intelligibility (HASPI), respectively, for seven typical hearing loss types. Conclusion: The results suggest that the proposed method can enhance speech perception by cutting off noise from speech signals and mitigating interference caused by distance. Significance: The results of this study show a potential way that can help improve the listening experience in enhancing speech quality and speech comprehension/intelligibility for hearing-impaired people.
Neural Signatures of Hierarchical Linguistic Structures in Second Language Listening Comprehension

Abstract Native speakers excel at parsing continuous speech into smaller elements and entraining their neural activities to the linguistic hierarchy at different levels (e.g., syllables, phrases, and sentences) to achieve speech comprehension. However, how a nonnative brain tracks hierarchical linguistic structures in second language (L2) speech comprehension and whether it relates to top-down attention and language proficiency remains elusive. Here, we applied a frequency-tagging paradigm in human adults and investigated the neural tracking responses to hierarchically organized linguistic structures (i.e., the syllabic rate of 4 Hz, the phrasal rate of 2 Hz, and the sentential rate of 1 Hz) in both first language (L1) and L2 listeners when they attended to a speech stream or ignored it. We revealed disrupted neural responses to higher-order linguistic structures (i.e., phrases and sentences) for L2 listeners in which the phrasal-level tracking was functionally related to an L2 subject’s language proficiency. We also observed less efficient top-down modulation of attention in L2 speech comprehension than in L1 speech comprehension. Our results indicate that the reduced δ-band neuronal oscillations that subserve the internal construction of higher-order linguistic structures may compromise listening comprehension in a nonnative language.
Leveraging Cell Painting Images to Expand the Applicability Domain and Actively Improve Deep Learning Quantitative Structure–Activity Relationship Models

The search for chemical hit material is a lengthy and increasingly expensive drug discovery process. To improve it, ligand-based quantitative structure–activity relationship models have been broadly applied to optimize primary and secondary compound properties. Although these models can be deployed as early as the stage of molecule design, they have a limited applicability domain—if the structures of interest differ substantially from the chemical space on which the model was trained, a reliable prediction will not be possible. Image-informed ligand-based models partly solve this shortcoming by focusing on the phenotype of a cell caused by small molecules, rather than on their structure. While this enables chemical diversity expansion, it limits the application to compounds physically available and imaged. Here, we employ an active learning approach to capitalize on both of these methods’ strengths and boost the model performance of a mitochondrial toxicity assay (Glu/Gal). Specifically, we used a phenotypic Cell Painting screen to build a chemistry-independent model and adopted the results as the main factor in selecting compounds for experimental testing. With the additional Glu/Gal annotation for selected compounds we were able to dramatically improve the chemistry-informed ligand-based model with respect to the increased recognition of compounds from a 10% broader chemical space.
Implicit Monte Carlo with a Linear Discontinuous Finite Element Material Solution and Piecewise Non-Constant Opacity

ABSTRACT The non-linear thermal radiative-transfer equations can be solved in various ways. One popular way is the Fleck and Cummings Implicit Monte Carlo (IMC) method. The IMC method was originally formulated with piecewise-constant material properties. For domains with a coarse spatial grid and large temperature gradients, an error known as numerical teleportation may cause artificially non-causal energy propagation and consequently an inaccurate material temperature. Source tilting is a technique to reduce teleportation error by constructing sub-spatial-cell (or sub-cell) emission profiles from which IMC particles are sampled. Several source tilting schemes exist, but some allow teleportation error to persist. We examine the effect of source tilting in problems with a temperature-dependent opacity. Within each cell, the opacity is evaluated continuously from a temperature profile implied by the source tilt. For IMC, this is a new approach to modeling the opacity. We find that applying both source tilting along with a source tilt-dependent opacity can introduce another dominant error that overly inhibits thermal wavefronts. We show that we can mitigate both teleportation and under-propagation errors if we discretize the temperature equation with a linear discontinuous (LD) trial space. Our method is for opacities ∼ 1/T3, but we formulate and test a slight extension for opacities ∼ 1/T3.5, where T is temperature. We find our method avoids errors that can be incurred by IMC with continuous source tilt constructions and piecewise-constant material temperature updates.
How do disease control measures impact spatial predictions of schistosomiasis and hookworm? The example of predicting school-based prevalence before and after preventive chemotherapy in Ghana

Background Schistosomiasis and soil-transmitted helminth infections are among the neglected tropical diseases (NTDs) affecting primarily marginalized communities in low- and middle-income countries. Surveillance data for NTDs are typically sparse, and hence, geospatial predictive modeling based on remotely sensed (RS) environmental data is widely used to characterize disease transmission and treatment needs. However, as large-scale preventive chemotherapy has become a widespread practice, resulting in reduced prevalence and intensity of infection, the validity and relevance of these models should be re-assessed. Methodology We employed two nationally representative school-based prevalence surveys of Schistosoma haematobium and hookworm infections from Ghana conducted before (2008) and after (2015) the introduction of large-scale preventive chemotherapy. We derived environmental variables from fine-resolution RS data (Landsat 8) and examined a variable distance radius (1–5 km) for aggregating these variables around point-prevalence locations in a non-parametric random forest modeling approach. We used partial dependence and individual conditional expectation plots to improve interpretability of results. Principal findings The average school-level S. haematobium prevalence decreased from 23.8% to 3.6% and that of hookworm from 8.6% to 3.1% between 2008 and 2015. However, hotspots of high-prevalence locations persisted for both infections. The models with environmental data extracted from a buffer radius of 2–3 km around the school location where prevalence was measured had the best performance. Model performance (according to the R2 value) was already low and declined further from approximately 0.4 in 2008 to 0.1 in 2015 for S. haematobium and from approximately 0.3 to 0.2 for hookworm. According to the 2008 models, land surface temperature (LST), modified normalized difference water index, elevation, slope, and streams variables were associated with S. haematobium prevalence. LST, slope, and improved water coverage were associated with hookworm prevalence. Associations with the environment in 2015 could not be evaluated due to low model performance. Conclusions/significance Our study showed that in the era of preventive chemotherapy, associations between S. haematobium and hookworm infections and the environment weakened, and thus predictive power of environmental models declined. In light of these observations, it is timely to develop new cost-effective passive surveillance methods for NTDs as an alternative to costly surveys, and to focus on persisting hotspots of infection with additional interventions to reduce reinfection. We further question the broad application of RS-based modeling for environmental diseases for which large-scale pharmaceutical interventions are in place.
Patient perspectives on consequences of resection for colorectal cancer: A qualitative study

Colorectal cancer is diagnosed in approximately 500,000 patients each year in Europe, leading to a high number of patients having to cope with the consequences of resection for colorectal cancer. As treatment options tend to grow, more information on the effects of these treatments is needed to engage in shared decision‐making. This study aims to explore the impact of resection for colorectal cancer on patients' daily life.
Experiences of Loneliness Across the Lifespan: A Systematic Review and Thematic Synthesis of Qualitative Studies

ABSTRACT Purpose Loneliness is a fundamentally subjective experience that is common at various life stages. Studies have qualitatively explored loneliness, but a comprehensive overview is lacking. This research therefore provides a fine-grained review of studies on loneliness experiences across the lifespan. Methods A systematic review and thematic synthesis were performed on studies that qualitatively investigated experiences of loneliness in people of any age from non-clinical populations. Sensitivity analysis assessed the impact of lower-quality studies and specific age groups on the findings. Results Twenty-nine studies of 1,321 participants aged between 7 and 103 were included. Fifteen descriptive themes and three overarching analytical themes were developed: (1) Loneliness is both psychological and contextual, (2) Loneliness centres on feelings of meaningful connection and painful disconnection, and (3) Loneliness can exist in a general, pervasive sense or can relate to specific other people or relationship types. Some features were particularly pertinent to children, younger adults, and older adults, respectively. Conclusions Loneliness involves a primarily aversive psychological experience of perceived disconnection which is linked to physical, personal, and socio-political contexts and can be pervasive or relate to specific relationships or relationship types. An awareness of context, life stage, and personal experiences is essential to understand loneliness.
Measurement of molecular length of self-assembled monolayer probed by localized surface plasmon resonance

We propose a method to measure the variation of the molecular length of self-assembled monolayers (SAMs) when it is exposed to solutions at different pH conditions. The surface immobilized gold nanospheres (SIGNs) shows strong absorption peak at the wavelengths of 600-800 nm when p-polarized light is illuminated. The peak wavelength depends on the length of the gap distance between the SIGNs and the substrate. The gap is supported by the SAM molecules. According to the analytical calculation based on multiple expansion, the relation between the peak wavelength of the SIGN structures and the gap distance is calculated, to evaluate the molecular length of the SAM through the optical absorption spectroscopy for the SIGN structures. The molecular length of the SIGN structure was measured in air, water, acidic, and basic solutions. It was found that the molecular lengths are longer in acidic solutions.
Managing fuels and fluids: Network integration of osmoregulatory and metabolic hormonal circuits in the polymodal control of homeostasis in insects

Osmoregulation in insects is an essential process whereby changes in hemolymph osmotic pressure induce the release of diuretic or antidiuretic hormones to recruit individual osmoregulatory responses in a manner that optimizes overall homeostasis. However, the mechanisms by which different osmoregulatory circuits interact with other homeostatic networks to implement the correct homeostatic program remain largely unexplored. Surprisingly, recent advances in insect genetics have revealed several important metabolic functions are regulated by classic osmoregulatory pathways, suggesting that internal cues related to osmotic and metabolic perturbations are integrated by the same hormonal networks. Here, we review our current knowledge on the network mechanisms that underpin systemic osmoregulation and discuss the remarkable parallels between the hormonal networks that regulate body fluid balance and those involved in energy homeostasis to provide a framework for understanding the polymodal optimization of homeostasis in insects.
Occurrence of tuberculosis among people exposed to cattle in Bangladesh

Abstract Background Tuberculosis (TB) has been an important public health concern in Bangladesh. The most common cause of human TB is Mycobacterium tuberculosis, while bovine TB is caused by Mycobacterium bovis. Objective The objective of this study was to determine the frequency of TB in individuals with occupational exposure to cattle and to detect Mycobacterium bovis among cattle in slaughterhouses in Bangladesh. Methods Between August 2014 and September 2015, an observational study was conducted in two government chest disease hospitals, one cattle market, and two slaughterhouses. [Correction added on 27 June 2023, after first online publication: In the preceding sentence, the year “2014” has been added after the word “August”. ] Sputum samples were collected from individuals who met the criteria for suspected TB and had been exposed to cattle. Tissue samples were collected from cattle that had low body condition score(s). Both humans and cattle samples were screened for acid‐fast bacilli (AFB) by Ziehl–Neelsen (Z‐N) staining and cultured for Mycobacterium tuberculosis complex (MTC). Region of difference (RD) 9‐based polymerase chain reaction (PCR) was also performed to identify Mycobacterium spp. We also conducted Spoligotyping to identify the specific strain of Mycobacterium spp. Results Sputum was collected from a total of 412 humans. The median age of human participants was 35 (IQR: 25–50) years. Twenty‐five (6%) human sputum specimens were positive for AFB, and 44 (11%) were positive for MTC by subsequent culture. All (N = 44) culture‐positive isolates were confirmed as Mycobacterium tuberculosis by RD9 PCR. Besides, 10% of cattle workers were infected with Mycobacterium tuberculosis in the cattle market. Of all TB (caused by Mycobacterium tuberculosis) infected individuals, 6.8% of individuals were resistant to one or two anti‐TB drugs. The majority of the sampled cattle (67%) were indigenous breeds. No Mycobacterium bovis was detected in cattle. Conclusions We did not detect any TB cases caused by Mycobacterium bovis in humans during the study. However, we detected TB cases caused by Mycobacterium tuberculosis in all humans, including cattle market workers.
A hypothesis - generating Swedish extended national cross-sectional family study of multimorbidity severity and venous thromboembolism

Objectives Venous thromboembolism (VTE) is a common worldwide disease. The burden of multimorbidity, that is, two or more chronic diseases, has increased. Whether multimorbidity is associated with VTE risk remains to be studied. Our aim was to determine any association between multimorbidity and VTE and any possible shared familial susceptibility. Design A nationwide extended cross-sectional hypothesis - generating family study between 1997 and 2015. Setting The Swedish Multigeneration Register, the National Patient Register, the Total Population Register and the Swedish cause of death register were linked. Participants 2 694 442 unique individuals were analysed for VTE and multimorbidity. Main outcomes and measures Multimorbidity was determined by a counting method using 45 non-communicable diseases. Multimorbidity was defined by the occurrence of ≥2 diseases. A multimorbidity score was constructed defined by 0, 1, 2, 3, 4 or 5 or more diseases. Results Sixteen percent (n=440 742) of the study population was multimorbid. Of the multimorbid patients, 58% were females. There was an association between multimorbidity and VTE. The adjusted odds ratio (OR) for VTE in individuals with multimorbidity (2 ≥ diagnoses) was 3.16 (95% CI: 3.06 to 3.27) compared with individuals without multimorbidity. There was an association between number of diseases and VTE. The adjusted OR was 1.94 (95% CI: 1.86 to 2.02) for one disease, 2.93 (95% CI: 2.80 to 3.08) for two diseases, 4.07 (95% CI: 3.85 to 4.31) for three diseases, 5.46 (95% CI: 5.10 to 5.85) for four diseases and 9.08 (95% CI: 8.56 to 9.64) for 5 ≥ diseases. The association between multimorbidity and VTE was stronger in males OR 3.45 (3.29 to 3.62) than in females OR 2.91 (2.77 to 3.04). There were significant but mostly weak familial associations between multimorbidity in relatives and VTE. Conclusions Increasing multimorbidity exhibits a strong and increasing association with VTE. Familial associations suggest a weak shared familial susceptibility. The association between multimorbidity and VTE suggests that future cohort studies where multimorbidity is used to predict VTE might be worthwhile.
Instability Of Flows

A large body of published work on the instability of laminar flows is available in the open literature. The purpose of this chapter is to present the basic equations and the mathematical techniques in a systematic manner to study the instability of both the viscous and inviscid flows. The chapter begins with the consideration of the Lorenz equations to show the dependency of instabilities on some parameters for dissipative dynamical systems. Failure of the eigenvalue analysis in some important cases, e.g., flow in a circular pipe, has been highlighted in view of the research carried out in the last ten years.
Numerical solution of a two-dimensional IHCP based on Duhamel's principle

In this paper, we will first study the existence and uniqueness of the solu- tion for a two-dimensional inverse heat conduction problem (IHCP). Furthermore, the estimate of an unknown boundary condition by a numerical algorithm in this IHCP based on Duhamel's principle, is the topic of this paper. The stability and accuracy of the scheme presented is evaluated by comparison with the Singular Value Decom- position method. Some numerical experiments confirm the utility of this algorithm as the results are in good agreement with the exact data.
‘Specific Normalization’ method for NIRS calibrations

In this study, we present a chemometric procedure called ‘Specific Normalization’. It upgrades the calibration for use in a specific set of new samples by normalizing together the spectra of both the calibration set and a new measured sample set. The proposed procedure is shown for near infra-red spectroscopy measurement of olive oil acidity, as an example. This procedure would need its integration as software application for routine analysis.
Objective measures of speech quality (subjective)

This thesis investigates objective measures of speech quality, or measures which can be computed from properties of an original and a distorted speech waveform. Two sets of objective measures are investigated. The first set is designed to estimate the specific types of perceived distortions specified by the 'parametric' subjective quality scales of the Diagnostic Acceptability Measure (DAM), a subjective speech quality test. The narrow scope of these parametric scales promotes a close coupling between physical quantities and their associated perceptual qualities, resulting in quite accurate measures. The second set of objective measures estimate the composite acceptability scale of the DAM, a scale measuring overall speech acceptability. The first set of measures are used as a foundation for designing the second set of measures. The speech quality data base used in this research is quite extensive. It consists of a total of 1056 examples of distorted speech produced by various speech coder and other speech distorting systems and their associated subjective quality ratings as produced by the Diagnostic Acceptability Measure. The thesis research can be divided into three parts. In the first part, the relationship between the scales of the Diagnostic Acceptability Measure and several of the best available objective speech quality measures is analyzed. It is demonstrated, using Multidimensional Scaling, that current objective measures produce poor estimates of composite acceptability because they incorporate little of the information provided by the parametric subjective measures. Multiple linear regression is used to find a linear relationship between the parametric subjective quality scales and the composite acceptability scale. The resulting regression model produces very good estimates of composite acceptability using only a subset of the parametric qualities. Because of this relationship, objective measures of parametric quality can be used as the basis for a measure of composite acceptability. In the second part, a set of objective measures is designed which provide dramatically improved estimates of the parametric qualities of the Diagnostic Acceptability Measure. Performance is measured in terms of the correlation between actual and estimated subjective quality. Multidimensional scaling graphically shows the remarkable ability of these measures to estimate the parametric subjective qualities. And finally, in the third part, the parametric objective measures are combined into a single composite measure for estimating subjective composite acceptability. Several measures are presented, with correlations to composite acceptability ranging from 0.81 to 0.85.
From supergiant stars to galaxies: The path to extragalactic distances

Abstract The spectroscopic study of blue supergiants in nearby galaxies can yield crucial information about the spatial distribution of extinction by dust, and can be successfully used to measure the metal content, abundance patterns, and distances of galaxies out to ~8 Mpc with current telescopes and instrumentation. We briefly review the results of an ongoing project in which the quantitative analysis of B- and A-type supergiants is used to independently test widely used metallicity diagnostics for star-forming galaxies and derive reddening-free extragalactic distances.
In The Name of GOD Approximated Type-2 Fuzzy Set Operations

Type-2 fuzzy sets, an elaboration over type-1 fuzzy sets, are an interesting method for handling uncertainty in rules and parameters in fuzzy systems. However, their adoption has not been as wide as one could have expected. In this paper we provide a simple introduction to type-2 fuzzy sets; then we propose a novel method for calculating operations on type-2 fuzzy sets with normal type-1 membership values, for which we redefine set ordering. Finally, based on the max ordering of fuzzy set and highest degree of separation, we propose an approximation for performing the operations, which ensures that the calculation is accurate for the most important parts of the membership values.