Miracle-dz/UniFAR-FTUs huggingface dataset:
Relationship between self-reported listening and communication difficulties and executive function: a protocol for a systematic review and meta-analysis

Introduction Listening and communication difficulties can limit people’s participation in activity and adversely affect their quality of life. Hearing, as well as listening and communication difficulties, can be measured either by using behavioural tests or self-report measures, and the outcomes are not always closely linked. The association between behaviourally measured and self-reported hearing is strong, whereas the association between behavioural and self-reported measures of listening and communication difficulties is much weaker, suggesting they assess different aspects of listening. While behavioural measures of listening and communication difficulties have been associated with poorer cognitive performance including executive functions, the same association has not always been shown for self-report measures. The objective of this systematic review and meta-analysis is to understand the relationship between executive function and self-reported listening and communication difficulties in adults with hearing loss, and where possible, potential covariates of age and pure-tone audiometric thresholds. Methods and analysis Studies will be eligible for inclusion if they report data from both a self-report measure of listening difficulties and a behavioural measure of executive function. Eight databases are to be searched: MEDLINE (via Ovid SP), EMBASE (via Ovid SP), PsycINFO (via Ovid SP), ASSIA (via ProQuest), Cumulative Index to Nursing and Allied Health Literature or CINAHL (via EBSCO Host), Scopus, PubMed and Web of Science (Science and Social Science Citation Index). The JBI critical appraisal tool will be used to assess risk of bias for included studies. Results will be synthesised primarily using a meta-analysis, and where sufficient quantitative data are not available, a narrative synthesis will be carried out to describe key results. Ethics and dissemination No ethical issues are foreseen. Data will be disseminated via academic publication and conference presentations. Findings may also be published in scientific newsletters and magazines. PROSPERO registration number CRD42022293546.
Monocular Depth Estimation: A Thorough Review

Estimation of depth in two-dimensional images is among the challenging topics in Computer Vision. This is a well-studied but also an ill-posed problem, which has long been the focus of intense research. This paper is an in-depth review of the topic, presenting two aspects, one that considers the mechanisms of human depth perception, and another that includes the various Deep Learning approaches. The methods are presented in a compact and structured way that outlines the topic and categorizes the approaches according to the line of research followed in the recent decade. Although there has been significant advancement in the topic, it was without any connection with human depth perception and the potential benefits from this sector.
Short Note Sequential H-κ Stacking to Obtain Accurate Crustal Thicknesses beneath Sedimentary Basins

Low-velocity sedimentary basins introduce error in many standard receiver-function (RF) analysis techniques including common conversion point (Dueker and Sheehan, 1997) and crustal thickness-VP=VS ratio (H-κ )s tacking (Zhu and Ka- namori, 2000). We describe a simple RF analysis method for obtaining accurate crustal thickness below seismic stations located in sedimentary basins. The method extends the methods of Zhu and Kanamori (2000). It employs an iterative two-layer depth-VP=VS stacking approach that first characterizes sediment properties (thickness and VP=VS) allowing for the accurate interpretation of Moho conversions. Without accounting for sedimentary layers, standard-RFanalysis can mischaracterize crustal thickness based on Ps-phase delay by >10 km beneath deep basins. We test the technique with syn- thetic seismograms and with data from US Array Transportable Array (TA )s tations from regions with sediment thicknesses that are well determined through other means. We find sequential H-κ stacking for sediment properties to be a simple technique that can benefit many RF-analysis studies and can play an important role in crustal seismic studies in areas with thick or variable sediments.
Effects of positive affect and positive emotions on executive functions: a systematic review and meta-analysis

ABSTRACT Positive emotions (PEs) impact cognitive processes, including executive functions (EFs; i.e. inhibition, working memory, cognitive flexibility). However, previous reviews and meta-analyses report contradicting results. Thus, this review takes a novel approach to overcome conflicting findings by clearly conceptualising PE induction and by providing a detailed description of the tasks used to assess EFs, as well as by exclusively focusing on EFs. A systematic literature review and meta-analysis was performed. Study inclusion criteria required that subjects were healthy individuals over 18 years, PEs were induced in a controlled laboratory setting, a baseline measurement and a control condition was required, and finally, EFs were measured as a dependent variable using valid measurement instruments. The literature search was performed on PRIMUS, including relevant databases such as ERIC, MEDLINE, Psych ARTICLES, Psych INFO or SocINDEX. From a total of 6,661 identified articles, only 13, which featured 20 experimental studies, were included. Results show that the overall induction of PEs successfully caused an increase in valence and/or positive emotions. However, no significant effects of PE on EFs were detected (d = −0.051, p = .405). Reasons and future research will be discussed.
Phenotyping patients with ischaemic heart disease at risk of developing heart failure: an analysis of the HOMAGE trial

Abstract Aims We aim to characterize the clinical and proteomic profiles of patients at risk of developing heart failure (HF), with and without coronary artery disease (CAD) or prior myocardial infarction (MI). Methods and results HOMAGE evaluated the effect of spironolactone on plasma and serum markers of fibrosis over 9 months of follow‐up in participants with (or at risk of having) CAD, and raised natriuretic peptides. In this post hoc analysis, patients were classified as (i) neither CAD nor MI; (ii) CAD; or (iii) MI. Proteomic between‐group differences were evaluated through logistic regression and narrowed using backward stepwise selection and bootstrapping. Among the 527 participants, 28% had neither CAD or MI, 31% had CAD, and 41% had prior MI. Compared with people with neither CAD nor MI, those with CAD had higher baseline plasma concentrations of matrix metalloproteinase‐7 (MMP‐7), galectin‐4 (GAL4), plasminogen activator inhibitor 1 (PAI‐1), and lower plasma peptidoglycan recognition protein 1 (PGLYRP1), whilst those with a history of MI had higher plasma MMP‐7, neurotrophin‐3 (NT3), pulmonary surfactant‐associated protein D (PSPD), and lower plasma tumour necrosis factor‐related activation‐induced cytokine (TRANCE). Proteomic signatures were similar for patients with CAD or prior MI. Treatment with spironolactone was associated with an increase of MMP7, NT3, and PGLYRP1 at 9 months. Conclusions In patients at risk of developing HF, those with CAD or MI had a different proteomic profile regarding inflammatory, immunological, and collagen catabolic processes.
A human urothelial microtissue model reveals shared colonization and survival strategies between uropathogens and commensals

Urinary tract infection is among the most common infections worldwide, typically studied in animals and cell lines with limited uropathogenic strains. Here, we assessed diverse bacterial species in a human urothelial microtissue model exhibiting full stratification, differentiation, innate epithelial responses, and urine tolerance. Several uropathogens invaded intracellularly, but also commensal Escherichia coli, suggesting that invasion is a shared survival strategy, not solely a virulence hallmark. The E. coli adhesin FimH was required for intracellular bacterial community formation, but not for invasion. Other shared lifestyles included filamentation (Gram-negatives), chaining (Gram-positives), and hijacking of exfoliating cells, while biofilm-like aggregates were formed mainly with Pseudomonas and Proteus. Urothelial cells expelled invasive bacteria in Rab-/LC3-decorated structures, while highly cytotoxic/invasive uropathogens, but not commensals, disrupted host barrier function and strongly induced exfoliation and cytokine production. Overall, this work highlights diverse species-/strain-specific infection strategies and corresponding host responses in a human urothelial microenvironment, providing insights at the microtissue, cell, and molecular level.
Clinical Significance of Stiffness during Endoscopic Surgery for Intracerebral Hemorrhage: A Retrospective Study

Studies regarding hematoma stiffness and removal difficulty are scarce. This study explored the association between hematoma stiffness and surgical results of endoscopic hematoma removal for intracerebral hemorrhage. It also aimed to clarify factors associated with hematoma stiffness. We classified intracerebral hematoma as either soft or firm stiffness by retrospectively evaluating operative videos by two neurosurgeons. The interobserver reliability of the classification was assessed by calculating the κ values. We investigated the relationship between hematoma stiffness and surgical results. Favorable hematoma removal (FHR) was defined as a residual hematoma volume of ≤15 mL or removal rate of ≥70%. Furthermore, we compared the background characteristics, imaging findings, and laboratory data between the two groups. Forty patients were included in this study. The mean baseline hematoma volume was 69.9 mL (range, 41.3-97.6 mL). FHR was accomplished in 35 cases (87.5%). Thirty-four patients (85%) were in the soft hematoma group (group S). Six patients (15%) were in the firm hematoma group (group F). Classification of hematoma stiffness demonstrated an excellent degree of interobserver agreement (κ score = 0.91). Patients in group S had a high FHR rate (p = 0.018) and short endoscopic procedure times (p = 0.00034). The island sign was present in group S (p = 0.030). Patients in group F had significantly high fibrinogen levels (p = 0.049) and low serum total calcium (p = 0.032), hemoglobin (p = 0.041), and hematocrit (p = 0.011) levels. Hematoma stiffness during endoscopic surgery for intracerebral hemorrhage correlates with surgical results, including the endoscopic procedure time and accomplishing rate of FHR.
11β-Hydroxysteroid dehydrogenase and the pre-receptor regulation of corticosteroid hormone action

Two isozymes of 11-hydroxysteroid dehydrogenase (11-HSD1 and 11-HSD2) catalyse the interconversion of hormonally active cortisol and inactive cortisone. The enzyme evolved from a metabolic pathway to a novel mechanism underpinning human disease with the eluci- dation of the role of the type 2 or 'kidney' isozyme and an inherited form of hypertension, 'apparent mineralocorti- coid excess'. 'Cushing's disease of the kidney' arises because of a failure of 11-HSD2 to inactivate cortisol to cortisone resulting in cortisol-induced mineralocorticoid excess. Conversely, 11-HSD1 has been linked to human obesity and insulin resistance, but also to other diseases in which glucocorticoids have historically been implicated (osteoporosis, glaucoma). Here, the activation of cortisol from cortisone facilitates glucocorticoid hormone action at an autocrine level. The molecular basis for the putative human 11-HSD1 'knockout' - 'cortisone reductase deficiency' - has recently been described, an observation that also answers a long standing conundrum relating to the set-point of 11-HSD1 activity. In each case, these clinical studies have been underpinned by studies in vitro and the manipulation of enzyme expression in vivo using recombinant mouse models.
11β‐Hydroxysteroid dehydrogenase and the brain: Not (yet) lost in translation

11‐beta‐hydroxysteroid dehydrogenases (11β‐HSDs) catalyse the conversion of active 11‐hydroxy glucocorticoids (cortisol, corticosterone) and their inert 11‐keto forms (cortisone, 11‐dehydrocorticosterone). They were first reported in the body and brain 70 years ago, but only recently have they become of interest. 11β‐HSD2 is a dehydrogenase, potently inactivating glucocorticoids. In the kidney, 11β‐HSD2 generates the aldosterone‐specificity of intrinsically non‐selective mineralocorticoid receptors. 11β‐HSD2 also protects the developing foetal brain and body from premature glucocorticoid exposure, which otherwise engenders the programming of neuropsychiatric and cardio‐metabolic disease risks. In the adult CNS, 11β‐HSD2 is confined to a part of the brain stem where it generates aldosterone‐specific central control of salt appetite and perhaps blood pressure. 11β‐HSD1 is a reductase, amplifying active glucocorticoid levels within brain cells, notably in the cortex, hippocampus and amygdala, paralleling its metabolic functions in peripheral tissues. 11β‐HSD1 is elevated in the ageing rodent and, less certainly, human forebrain. Transgenic models show this rise contributes to age‐related cognitive decline, at least in mice. 11β‐HSD1 inhibition robustly improves memory in healthy and pathological ageing rodent models and is showing initial promising results in phase II studies of healthy elderly people. Larger trials are needed to confirm and clarify the magnitude of effect and define target populations. The next decade will be crucial in determining how this tale ends – in new treatments or disappointment.
Sensorslam: an investigation into sensor parameter estimation for slam

Mapping technology is an essential component of autonomous robotic systems. The ability of a vehicle to establish its location with respect to some environmental representation allows the vehicle to navigate and reason about the environment. This process of estimating vehicle motion while fusing sensor data to acquire a map of the environment is called simultaneous localization and mapping or SLAM. Existing SLAM formulations are unable to effectively address the problem of non-stationary sensor noise in the sensor model. Yet orientation or location dependent noise sources are commonplace in real-world scenarios. The use of standard noise models (which assume stationary noise) leads to instability or reduced accuracy of the resulting map within traditional SLAM solutions. By parameterizing the non-stationary aspects of the noise model and estimating these parameters simultaneously with the map and sensor location, a stochastic formulation for SLAM is developed. The general Bayesian framework developed in this dissertation is applicable in many domains, however this work focuses on the underwater environment. Stereo video cameras and inertial sensors are utilized to solve SLAM in the underwater environment. The resulting algorithm is used to recover models of complex underwater structures. Incorporating a non-stationary noise model within a Bayesian SLAM formulation reduces the error in the resulting trajectory and map by simultaneously estimating the location-based (non-stationary) noise in the environment, the trajectory of the sensor, and an accurate map of the environment.
Collagen‐Based Hydrogels for Cartilage Regeneration

Cartilage regeneration remains difficult due to a lack of blood vessels. Degradation of the extracellular matrix (ECM) causes cartilage defects, and the ECM provides the natural environment and nutrition for cartilage regeneration. Until now, collagen hydrogels are considered to be excellent material for cartilage regeneration due to the similar structure to ECM and good biocompatibility. However, collagen hydrogels also have several drawbacks, such as low mechanical strength, limited ability to induce stem cell differentiation, and rapid degradation. Thus, there is a demanding need to optimize collagen hydrogels for cartilage regeneration. In this review, we will first briefly introduce the structure of articular cartilage and cartilage defect classification and collagen, then provide an overview of the progress made in research on collagen hydrogels with chondrocytes or stem cells, comprehensively expound the research progress and clinical applications of collagen‐based hydrogels that integrate inorganic or organic materials, and finally present challenges for further clinical translation.
An Introduction to Adversarially Robust Deep Learning

The widespread success of deep learning in solving machine learning problems has fueled its adoption in many fields, from speech recognition to drug discovery and medical imaging. However, deep learning systems are extremely fragile: imperceptibly small modifications to their input data can cause the models to produce erroneous output. It is very easy to generate such adversarial perturbations even for state-of-the-art models, yet immunization against them has proven exceptionally challenging. Despite over a decade of research on this problem, our solutions are still far from satisfactory and many open problems remain. In this work, we survey some of the most important contributions in the field of adversarial robustness. We pay particular attention to the reasons why past attempts at improving robustness have been insufficient, and we identify several promising areas for future research.
Strategic Pauses Relieve Listeners from the Effort of Listening to Fast Speech: Data Limited and Resource Limited Processes in Narrative Recall by Adult Users of Cochlear Implants

Speech that has been artificially accelerated through time compression produces a notable deficit in recall of the speech content. This is especially so for adults with cochlear implants (CI). At the perceptual level, this deficit may be due to the sharply degraded CI signal, combined with the reduced richness of compressed speech. At the cognitive level, the rapidity of time-compressed speech can deprive the listener of the ordinarily available processing time present when speech is delivered at a normal speech rate. Two experiments are reported. Experiment 1 was conducted with 27 normal-hearing young adults as a proof-of-concept demonstration that restoring lost processing time by inserting silent pauses at linguistically salient points within a time-compressed narrative (“time-restoration”) returns recall accuracy to a level approximating that for a normal speech rate. Noise vocoder conditions with 10 and 6 channels reduced the effectiveness of time-restoration. Pupil dilation indicated that additional effort was expended by participants while attempting to process the time-compressed narratives, with the effortful demand on resources reduced with time restoration. In Experiment 2, 15 adult CI users tested with the same (unvocoded) materials showed a similar pattern of behavioral and pupillary responses, but with the notable exception that meaningful recovery of recall accuracy with time-restoration was limited to a subgroup of CI users identified by better working memory spans, and better word and sentence recognition scores. Results are discussed in terms of sensory-cognitive interactions in data-limited and resource-limited processes among adult users of cochlear implants.
Environmental force sensing helps robots traverse cluttered large obstacles

Robots can traverse sparse obstacles by sensing environmental geometry and avoiding contact with obstacles. However, for search and rescue in rubble, environmental monitoring through dense vegetation, and planetary exploration over Martian and lunar rocks, robots must traverse cluttered obstacles as large as themselves by physically interacting with them. Previous work discovered that the forest floor-dwelling discoid cockroach and a sensor-less minimalistic robot can traverse cluttered grass-like beam obstacles of various stiffness by transitioning across different locomotor modes. Yet the animal was better at traversal than the sensor-less robot, likely by sensing forces during obstacle interaction to control its locomotor transitions. Inspired by this, here we demonstrated in simulation that environmental force sensing helps robots traverse cluttered large obstacles. First, we developed a multi-body dynamics simulation and a physics model of the minimalistic robot interacting with beams to estimate beam stiffness from the sensed contact forces. Then, we developed a force feedback strategy for the robot to use the sensed beam stiffness to choose the locomotor mode with a lower mechanical energy cost. With feedforward pushing, the robot was stuck in front of stiff beams if it has a limited force capacity; without force limit, it traversed but suffered a high energy cost. Using obstacle avoidance, the robot traversed beams by avoiding beam contact regardless of beam stiffness, resulting in a high energy cost for flimsy beams. With force feedback, the robot determined beam stiffness, then traversed flimsy beams by pushing them over and stiff beams by rolling through the gap between them with a low energy cost. Stiffness estimation based on force sensing was accurate across varied body oscillation amplitude and frequency and position sensing uncertainty. Mechanical energy cost of traversal increased with sensorimotor delay. Future work should demonstrate cluttered large obstacle traversal using force feedback in a physical robot.
Improving the RNA velocity approach with single-cell RNA lifecycle (nascent, mature and degrading RNAs) sequencing technologies

Abstract We presented an experimental method called FLOUR-seq, which combines BD Rhapsody and nanopore sequencing to detect the RNA lifecycle (including nascent, mature, and degrading RNAs) in cells. Additionally, we updated our HIT-scISOseq V2 to discover a more accurate RNA lifecycle using 10x Chromium and Pacbio sequencing. Most importantly, to explore how single-cell full-length RNA sequencing technologies could help improve the RNA velocity approach, we introduced a new algorithm called ‘Region Velocity’ to more accurately configure cellular RNA velocity. We applied this algorithm to study spermiogenesis and compared the performance of FLOUR-seq with Pacbio-based HIT-scISOseq V2. Our findings demonstrated that ‘Region Velocity’ is more suitable for analyzing single-cell full-length RNA data than traditional RNA velocity approaches. These novel methods could be useful for researchers looking to discover full-length RNAs in single cells and comprehensively monitor RNA lifecycle in cells.