Miracle-dz/UniFAR-FTUs huggingface dataset:
Mucosal wave properties of a human vocal fold

The objective of this research was to investigate mucosal wave propagation in laboratory experiments, across a variety of phonatory conditions. In particular, the focus was on the medial and superior surface dynamics of the vocal fold, which quantify mucosal wave propagation, but have been relatively little studied. High-speed, digital imaging of the superior and medial surfaces of the vocal fold was performed using an excised human hemilarynx setup. Surface dynamics were characterized and differentiated across a variety of phonatory conditions. During sustained, flow-induced oscillation, the local maxima of vocal fold mucosal displacements, velocities and acceleration and their particular phase delays in the glottal cycle were investigated. Statistical analysis was performed, examining the influence of induced flow, adductory stimulation, and length of the vocal fold. To give an overview, the grand average values were computed and discussed for the complete series of 24 recordings. Increasing the applied airflow, yielded higher values for lateral displacements as well as higher velocity and acceleration values. Elongating the vocal fold resulted in decreased lateral displacements. The mucosal wave propagation apparently increased for higher flow, elongated folds, and higher adduction forces. Performing grand averages revealed the three-dimensional dynamical behavior over the superior and medial surface of the vocal fold. A significant increase in the amplitudes of the dynamical quantities between inferior and superior regions was detected. The data showed a nearly 180 degree phase delay between inferior and superior regions of the vocal fold with respect to lateral displacements, velocities, and accelerations. Phase delays for the vertical displacements were also present, but less pronounced. Using a hemilarynx methodology, mucosal wave propagation was characterized and differentiated over the superior and medial surfaces of the vocal fold surface across a range of phonatory conditions. While an understanding of the correlation between vocal fold dynamics and phonatory physiology/pathology is still in its infancy, the data presented here help to establish such connections. The data are also useful for the development and evaluation of physical and numerical models of vocal fold vibration. However, since only one larynx has been investigated the results have to be seen as preliminary.
The Roles and Pathogenesis Mechanisms of a Number of Micronutrients in the Prevention and/or Treatment of Chronic Hepatitis, COVID-19 and Type-2 Diabetes Mellitus

A trace element is a chemical element with a concentration (or other measures of an amount) that is very low. The essential TEs, such as copper (Cu), selenium (Se), zinc (Zn), iron (Fe) and the electrolyte magnesium (Mg) are among the most commonly studied micronutrients. Each element has been shown to play a distinctive role in human health, and TEs, such as iron (Fe), zinc (Zn) and copper (Cu), are among the essential elements required for the organisms’ well-being as they play crucial roles in several metabolic pathways where they act as enzyme co-factors, anti-inflammatory and antioxidant agents. Epidemics of infectious diseases are becoming more frequent and spread at a faster pace around the world, which has resulted in major impacts on the economy and health systems. Different trace elements have been reported to have substantial roles in the pathogenesis of viral infections. Micronutrients have been proposed in various studies as determinants of liver disorders, COVID-19 and T2DM risks. This review article sheds light on the roles and mechanisms of micronutrients in the pathogenesis and prevention of chronic hepatitis B, C and E, as well as Coronavirus-19 infection and type-2 diabetes mellitus. An update on the status of the aforementioned micronutrients in pre-clinical and clinical settings is also briefly summarized.
From Feynman-Kac Formulae to Numerical Stochastic Homogenization in Electrical Impedance Tomography

In this paper, we use the theory of symmetric Dirichlet forms to derive Feynman-Kac formulae for the forward problem of electrical impedance tomography with possibly anisotropic, merely measurable conductivities corresponding to different electrode models on bounded Lipschitz domains. Subsequently, we employ these Feynman-Kac formulae to rigorously justify stochastic homogenization in the case of a stochastic boundary value problem arising from an inverse anomaly detection problem. Motivated by this theoretical result, we prove an estimate for the speed of convergence of the projected mean-square displacement of the underlying process which may serve as the theoretical foundation for the development of new scalable stochastic numerical homogenization schemes.
Quantum thermal absorption machines: refrigerators, engines and clocks

The inexorable miniaturisation of technologies, the relentless drive to improve efficiency and the enticing prospect of boosting performance through quantum effects are all compelling reasons to investigate microscopic machines. Thermal absorption machines are a particularly interesting class of device that operate autonomously and use only heat flows to perform a useful task. In the quantum regime, this provides a natural setting in which to quantify the thermodynamic cost of various operations such as cooling, timekeeping or entanglement generation. This article presents a pedagogical introduction to the physics of quantum absorption machines, covering refrigerators, engines and clocks in detail.
Emerging Approach for Fish Freshness Evaluation: Principle, Application and Challenges

Affected by micro-organisms and endogenous enzymes, fish are highly perishable during storage, processing and transportation. Efficient evaluation of fish freshness to ensure consumer safety and reduce raw material losses has received an increasing amount of attention. Several of the conventional freshness assessment techniques have plenty of shortcomings, such as being destructive, time-consuming and laborious. Recently, various sensors and spectroscopic techniques have shown great potential due to rapid analysis, low sample preparation and cost-effectiveness, and some methods are especially non-destructive and suitable for online or large-scale operations. Non-destructive techniques typically respond to characteristic substances produced by fish during spoilage without destroying the sample. In this review, we summarize, in detail, the principles and applications of emerging approaches for assessing fish freshness including visual indicators derived from intelligent packaging, active sensors, nuclear magnetic resonance (NMR) and optical spectroscopic techniques. Recent developments in emerging technologies have demonstrated their advantages in detecting fish freshness, but some challenges remain in popularization, optimizing sensor selectivity and sensitivity, and the development of algorithms and chemometrics in spectroscopic techniques.
Relaxin Inhibits the Cardiac Myofibroblast NLRP3 Inflammasome as Part of Its Anti-Fibrotic Actions via the Angiotensin Type 2 and ATP (P2X7) Receptors

Chronic NLRP3 inflammasome activation can promote fibrosis through its production of interleukin (IL)-1β and IL-18. Conversely, recombinant human relaxin (RLX) can inhibit the pro-fibrotic interactions between IL-1β, IL-18 and transforming growth factor (TGF)-β1. Here, the broader extent by which RLX targeted the myofibroblast NLRP3 inflammasome to mediate its anti-fibrotic effects was elucidated. Primary human cardiac fibroblasts (HCFs), stimulated with TGF-β1 (to promote myofibroblast (HCMF) differentiation), LPS (to prime the NLRP3 inflammasome) and ATP (to activate the NLRP3 inflammasome) (T+L+A) or benzoylbenzoyl-ATP (to activate the ATP receptor; P2X7R) (T+L+Bz), co-expressed relaxin family peptide receptor-1 (RXFP1), the angiotensin II type 2 receptor (AT2R) and P2X7R, and underwent increased protein expression of toll-like receptor (TLR)-4, NLRP3, caspase-1, IL-1β and IL-18. Whilst RLX co-administration to HCMFs significantly prevented the T+L+A- or T+L+Bz-stimulated increase in these end points, the inhibitory effects of RLX were annulled by the pharmacological antagonism of either RXFP1, AT2R, P2X7R, TLR-4, reactive oxygen species (ROS) or caspase-1. The RLX-induced amelioration of left ventricular inflammation, cardiomyocyte hypertrophy and fibrosis in isoproterenol (ISO)-injured mice, was also attenuated by P2X7R antagonism. Thus, the ability of RLX to ameliorate the myofibroblast NLRP3 inflammasome as part of its anti-fibrotic effects, appeared to involve RXFP1, AT2R, P2X7R and the inhibition of TLR-4, ROS and caspase-1.
The Robustness of Cellular Immunity Determines the Fate of SARS-CoV-2 Infection

Two years after the appearance of the SARS-CoV-2 virus, the causal agent of the current global pandemic, it is time to analyze the evolution of the immune protection that infection and vaccination provide. Cellular immunity plays an important role in limiting disease severity and the resolution of infection. The early appearance, breadth and magnitude of SARS-CoV-2 specific T cell response has been correlated with disease severity and it has been thought that T cell responses may be sufficient to clear infection with minimal disease in COVID-19 patients with X-linked or autosomal recessive agammaglobulinemia. However, our knowledge of the phenotypic and functional diversity of CD8+ cytotoxic lymphocytes, CD4+ T helper cells, mucosal-associated invariant T (MAIT) cells and CD4+ T follicular helper (Tfh), which play a critical role in infection control as well as long-term protection, is still evolving. It has been described how CD8+ cytotoxic lymphocytes interrupt viral replication by secreting antiviral cytokines (IFN-γ and TNF-α) and directly killing infected cells, negatively correlating with stages of disease progression. In addition, CD4+ T helper cells have been reported to be key pieces, leading, coordinating and ultimately regulating antiviral immunity. For instance, in some more severe COVID-19 cases a dysregulated CD4+ T cell signature may contribute to the greater production of pro-inflammatory cytokines responsible for pathogenic inflammation. Here we discuss how cellular immunity is the axis around which the rest of the immune system components revolve, since it orchestrates and leads antiviral response by regulating the inflammatory cascade and, as a consequence, the innate immune system, as well as promoting a correct humoral response through CD4+ Tfh cells. This review also analyses the critical role of cellular immunity in modulating the development of high-affinity neutralizing antibodies and germinal center B cell differentiation in memory and long-lived antibody secreting cells. Finally, since there is currently a high percentage of vaccinated population and, in some cases, vaccine booster doses are even being administered in certain countries, we have also summarized newer approaches to long-lasting protective immunity and the cross-protection of cellular immune response against SARS-CoV-2.
Modal Diversity for Robust Free-Space Optical Communications

Free-space communication links are severely affected by atmospheric turbulence, which causes degradation in the transmitted signal. One of the most common solutions to overcome this is to exploit diversity. In this approach, information is sent in parallel using two or more transmitters that are spatially separated, with each beam therefore experiencing different atmospheric turbulence, lowering the probability of a receive error. In this work we propose and experimentally demonstrate a generalization of diversity based on spatial modes of light, which we have termed $\textit{modal diversity}$. We remove the need for a physical separation of the transmitters by exploiting the fact that spatial modes of light experience different perturbations, even when travelling along the same path. For this proof-of-principle we selected modes from the Hermite-Gaussian and Laguerre-Gaussian basis sets and demonstrate an improvement in Bit Error Rate by up to 54\%. We outline that modal diversity enables physically compact and longer distance free space optical links without increasing the total transmit power.
Accuracy of calculated free testosterone formulae in men.

BACKGROUND As reference laboratory methods for measuring free testosterone (FT) by equilibrium dialysis (ED) are laborious, costly and nonautomatable, FT levels are often calculated (cFT) rather than measured. However, the predictive accuracy of such estimates in routine use relative to laboratory measurements is not well defined. We provide a large-scale evaluation of the predictive accuracy for different FT formulae compared with laboratory ED measurement and an analysis of clinical factors that may influence accuracy. METHODS The accuracy of five different cFT formulae (two equilibrium binding, three empirical) based on immunoassays of total testosterone (TT) and SHBG was evaluated by comparing those estimates with FT measurement by ED in 2159 serum samples from men at a single research laboratory over several years. RESULTS cFT formulae show systematic discrepancies from the two equilibrium-binding formulae. One empirical formula overestimated FT relative to ED measurements, whereas two newer empirical cFT formulae were more concordant. These discrepancies persisted after correction for serum albumin and were not influenced by obesity, ethnicity or gonadal status. CONCLUSIONS Commonly used cFT formulae significantly overestimate FT relative to laboratory measurement by ED in male serum samples. The accuracy of the formulae is not influenced by correction for serum albumin, obesity, ethnicity or gonadal status. Such inaccuracy relative to the reference method renders some cFT estimates unreliable for evaluating androgen deficiency as recommended by clinical best practice guidelines.
gp96 Expression in Gliomas and Its Association with Tumor Malignancy and T Cell Infiltrating Level

Heat shock protein glycoprotein 96 kDa (gp96) implicates in glioma invasiveness and engages antitumor immune response, representing a potential target for glioma treatment. However, its expression in different types of gliomas, its association with glioma-infiltrating T cells (GITs), and their clinical significance remain unknown. Herein, we utilized multiplex immunofluorescence staining (MIS) to detect gp96 expression and GIT levels on a tissue microarray (TMA), that comprises 234 glioma cases. We then validated the TMA results and explored possible mechanisms by investigating the RNA-seq data from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). We observed that gp96 was ubiquitously expressed in all types of gliomas whereas overexpressed in grade IV gliomas. Also, high gp96 expression predicted unfavorable outcomes independent of the malignancy grade. Meanwhile, gp96 expression positively correlated CD8+, CD4+, and PD-1+ cell densities, and especially associated with increased infiltration of CD4+ PD-1+ GITs. Clinically, the gp96-immune cell score (GI score), by summing the values measuring gp96 expression and immune cell densities, is capable of stratifying patients into four outcome-distinct groups (hazard ratio, 1.945; 95% CI, 1.521–2.486; P < 0.0001). Mechanistically, the interferon-γ/α response pathways were revealed to engage in the association between gp96 and GITs. Taken together, gp96 was ubiquitously expressed in gliomas, overexpressed in grade IV gliomas, and increased with GIT infiltrative levels. The GI score, that integrates levels of gp96 expression and GIT infiltration, is a potential prognostic classification system for gliomas.
POSET-RL: Phase ordering for Optimizing Size and Execution Time using Reinforcement Learning

The ever increasing memory requirements of several applications has led to increased demands which might not be met by embedded devices. Constraining the usage of memory in such cases is of paramount importance. It is important that such code size improvements should not have a negative impact on the runtime. Improving the execution time while optimizing for code size is a non-trivial but a significant task.The ordering of standard optimization sequences in modern compilers is fixed, and are heuristically created by the compiler domain experts based on their expertise. However, this ordering is sub-optimal, and does not generalize well across all the cases.We present a reinforcement learning based solution to the phase ordering problem, where the ordering improves both the execution time and code size. We propose two different approaches to model the sequences: one by manual ordering, and other based on a graph called Oz Dependence Graph (ODG). Our approach uses minimal data as training set, and is integrated with LLVM.We show results on x86 and AArch64 architectures on the benchmarks from SPEC-CPU 2006, SPEC-CPU 2017 and MiBench. We observe that the proposed model based on ODG outperforms the current Oz sequence both in terms of size and execution time by 6.19% and 11.99% in SPEC 2017 benchmarks, on an average.
Computational Analysis Identifies Novel Biomarkers for High-Risk Bladder Cancer Patients

In the case of bladder cancer, carcinoma in situ (CIS) is known to have poor diagnosis. However, there are not enough studies that examine the biomarkers relevant to CIS development. Omics experiments generate data with tens of thousands of descriptive variables, e.g., gene expression levels. Often, many of these descriptive variables are identified as somehow relevant, resulting in hundreds or thousands of relevant variables for building models or for further data analysis. We analyze one such dataset describing patients with bladder cancer, mostly non-muscle-invasive (NMIBC), and propose a novel approach to feature selection. This approach returns high-quality features for prediction and yet allows interpretability as well as a certain level of insight into the analyzed data. As a result, we obtain a small set of seven of the most-useful biomarkers for diagnostics. They can also be used to build tests that avoid the costly and time-consuming existing methods. We summarize the current biological knowledge of the chosen biomarkers and contrast it with our findings.
Scalar sigma meson effects in radiative rho0 meson decays

We study the radiative $\rho^0\to \pi^+\pi^-\gamma$ and $\rho^0\to \pi^0\pi^0\gamma$ decays and we calculate their branching ratios using a phenomenological approach by adding to the amplitude calculated within the framework of chiral perturbation theory and vector meson dominance the amplitude of $\sigma$-meson intermediate state. Our results for the branching ratios are in good agreement with the experimental values.
Detection of Escherichia coli O157: H7 and Non-O157 Strains in Meat, Human Stool, Abattoir Wastewater and Hygiene Practices among Meat Peddlers in Port Harcourt, Nigeria

Aim: To determine the prevalent rates of Escherichia coli O157: H7 and non-O157 strains in of isolates from meat, human stool and abattoir waste water, collected from selected sources in Port Harcourt, Nigeria. Study Design: Case-controlled study. Place and Duration of Study: Selected places in Port Harcourt, Rivers State, Nigeria, between November, 2020 to November, 2021. Methodology: Three hundred and forty -nine (349) samples were analyzed, 80 meat and 63 waste waters from five abattoirs cited in the city, 46 meat samples from five selected sites sold by roadside butchers, 109 patient stool samples and 30 stool samples from food sellers, in addition to 20 stool samples from healthy subjects and 1 commercial bottled water which served as control samples. Tryptone soya broth (TSB) as an enrichment media, selective agar media namely; Eosin methylene blue agar, cefixime tellurite-sorbitol MacConkey agar (CT-SMAC), Chromagar STEC were used to isolate STEC from the samples and serology done with O157 latex agglutinating kit to confirm E. coli O157:H7 serogroup. Results: The results showed that Isolation rates obtained for E. coli O157:H7 and non O157 respectively were: abattoir meat 11(13.8%);13(16.3%), roadside meat 5(10.9%); 10(21.7%), clinical stool 7(6.4%); 27(24.7%), food sellers’ stool 4(13.3%);6(20%), waste abattoir water 2(3%); 14(22.2%). Food sellers and abattoir effluents were found to be potential sources of STEC dissemination in Port Harcourt. The data obtained were statistically analyzed using chi- square which showed that there was no significant difference (p < 0.05) in the rate of isolation of E. coli O157: H7 and non- O157 strain from the samples. Conclusion: The detection of E.coli O157:H7 and non-O157 strains in raw meat (food), environment and clinical samples in Port Harcourt may give rise to a potential widespread public health hazard if strict adherence to proper hygiene management are not place to regulate food processing in other to reduce contamination and foodborne infections.
The prehospital time impact on traffic injury from hospital fatality and inpatient recovery perspectives

Abstract A solid emergency medical service response is important to saving lives. Most past studies are however focused on the effect of response time on fatalities resulting from cardiac arrest and fewer from traffic crash. The present study aims to present an extensive analysis of the impact of prehospital time on traffic injuries covering two perspectives: hospital fatalities and victims recovery. The former is described by the probability of death, and the second is measured by two proxy variables named “length of hospital stay” (LHS) and “health care costs” (HCC). A binary model was used to analyze the probability of death and generalized linear models were applied separately to the LHS and HCC continuous variables. The random-parameter approach was considered. A linked data set, resulting from a linkage process between hospital and police data sets, was used. The results showed that the effect of prehospital time varies across observations and is positively correlated to LHS and HCC. Control variables such as age and sex of the victim, type of crash, hospital and injury severity classified by maximum abbreviated injury scale showed impact on the probability of death and on the inpatient recovery. The study results suggest the importance of actions to improve emergency service.
Using Cognitive Modeling to Understand the Roles of Prefrontal and Posterior Parietal Cortex in Algebra Problem Solving

• Why did our manipulations fail to isolate the activity in these regions? • Explanation 1: These regions are not functionally distinct as characterized by ACT-R • Explanation 2: Our task manipulations failed to properly isolate retrieval and transformation • We designed two ACT-R models to determine the plausibility of Explanation 2 • Pure Model: Encompassed our initial assumptions about the design but failed to fit the RT data (R2 = .50) • Mixed Model: Assumed that both manipulations had retrieval and transformation components and fit the RT data well (R2 = .94) Using Cognitive Modeling to Understand the Roles of Prefrontal and Posterior Parietal Cortex in Algebra Problem Solving Jared F. Danker & John R. Anderson Department of Psychology and Center for the Neural Basis of Cognition, Carnegie Mellon University