Miracle-dz/UniFAR-FTUs huggingface dataset:
The Effective Factors on Time to Pregnancy In Reproductive Age Women, West of Iran

1 Emam Ali Hospital, Kermanshah University of Medical Sciences, Kermanshah, Iran. 2 Department of Midwifery, Kermanshah university of Medical sciences, Kermanshah, Iran. 3 Associate Professor, Department of Epidemiology and Biostatistics, school of public Health, Kermanshah university of Medical sciences, Kermanshah, Iran. 4 Professor, Department of Epidemiology and Biostatistics, school of public Health, Tehran university of Medical sciences, Tehran, Iran.
NOTCH1, HIF1A and Other Cancer-Related Proteins in Lung Tissue from Uranium Miners—Variation by Occupational Exposure and Subtype of Lung Cancer

Background Radon and arsenic are established pulmonary carcinogens. We investigated the association of cumulative exposure to these carcinogens with NOTCH1, HIF1A and other cancer-specific proteins in lung tissue from uranium miners. Methodology/Principal Findings Paraffin-embedded tissue of 147 miners was randomly selected from an autopsy repository by type of lung tissue, comprising adenocarcinoma (AdCa), squamous cell carcinoma (SqCC), small cell lung cancer (SCLC), and cancer-free tissue. Within each stratum, we additionally stratified by low or high level of exposure to radon or arsenic. Lifetime exposure to radon and arsenic was estimated using a quantitative job-exposure matrix developed for uranium mining. For 22 cancer-related proteins, immunohistochemical scores were calculated from the intensity and percentage of stained cells. We explored the associations of these scores with cumulative exposure to radon and arsenic with Spearman rank correlation coefficients (rs). Occupational exposure was associated with an up-regulation of NOTCH1 (radon rs = 0.18, 95% CI 0.02–0.33; arsenic: rs = 0.23, 95% CI 0.07–0.38). Moreover, we investigated whether these cancer-related proteins can classify lung cancer using supervised and unsupervised classification. MUC1 classified lung cancer from cancer-free tissue with a failure rate of 2.1%. A two-protein signature discriminated SCLC (HIF1A low), AdCa (NKX2-1 high), and SqCC (NKX2-1 low) with a failure rate of 8.4%. Conclusions/Significance These results suggest that the radiation-sensitive protein NOTCH1 can be up-regulated in lung tissue from uranium miners by level of exposure to pulmonary carcinogens. We evaluated a three-protein signature consisting of a physiological protein (MUC1), a cancer-specific protein (HIF1A), and a lineage-specific protein (NKX2-1) that could discriminate lung cancer and its major subtypes with a low failure rate.
Exploring neural network architectures for acoustic modeling

Deep neural network (DNN)-based acoustic models (AMs) have significantly improved automatic speech recognition (ASR) on many tasks. However, ASR performance still suffers from speaker and environment variability, especially under low-resource, distant microphone, noisy, and reverberant conditions. The goal of this thesis is to explore novel neural architectures that can effectively improve ASR performance. In the first part of the thesis, we present a well-engineered, efficient open-source framework to enable the creation of arbitrary neural networks for speech recognition. We first design essential components to simplify the creation of a neural network with recurrent loops. Next, we propose several algorithms to speed up neural network training based on this framework. We demonstrate the flexibility and scalability of the toolkit across different benchmarks. In the second part of the thesis, we propose several new neural models to reduce ASR word error rates (WERs) using the toolkit we created. First, we formulate a new neural architecture loosely inspired by humans to process low-resource languages. Second, we demonstrate a way to enable very deep neural network models by adding more non-linearities and expressive power while keeping the model optimizable and generalizable. Experimental results demonstrate that our approach outperforms several ASR baselines and model variants, yielding a 10% relative WER gain. Third, we incorporate these techniques into an end-to-end recognition model. We experiment with the Wall Street Journal ASR task and achieve 10.5% WER without any dictionary or language model, an 8.5% absolute improvement over the best published result. Thesis Supervisor: James R. Glass Title: Senior Research Scientist
Reduced-Complexity ML Detection and Capacity-Optimized Training for Spatial Modulation Systems

Spatial Modulation (SM) is a recently developed low-complexity Multiple-Input Multiple-Output scheme that jointly uses antenna indices and a conventional signal set to convey information. It has been shown that the Maximum-Likelihood (ML) detector of an SM system involves joint detection of the transmit antenna index and of the transmitted symbol, hence, the ML search complexity grows linearly with the number of transmit antennas and the size of the signal set. To circumvent the problem, we show that the ML search complexity of an SM system may be rendered independent of the constellation size, provided that the signal set employed is a square- or a rectangular-QAM. Furthermore, we derive bounds for the capacity of the SM system and derive the optimal power allocation between the data and the training sequences by maximizing the worst-case capacity bound of the SM system operating with imperfect channel state information. We show, with the aid of our simulation results, that the proposed detector is ML-optimal, despite its lowest complexity amongst the existing detectors. Furthermore, we show that employing the proposed optimal power allocation provides a substantial gain in terms of the SM system's capacity as well as signal-to-noise ratio compared to its equal-power-allocation counterpart. Finally, we compare the performance of the SM system to that of the conventional Multiple-Input Multiple-Output (MIMO) system and show that the SM system is capable of outperforming the conventional MIMO system by a significant margin, when both the systems are employing optimal power splitting.
Are Automatic Methods for Cognate Detection Good Enough for Phylogenetic Reconstruction in Historical Linguistics?

We evaluate the performance of state-of-the-art algorithms for automatic cognate detection by comparing how useful automatically inferred cognates are for the task of phylogenetic inference compared to classical manually annotated cognate sets. Our findings suggest that phylogenies inferred from automated cognate sets come close to phylogenies inferred from expert-annotated ones, although on average, the latter are still superior. We conclude that future work on phylogenetic reconstruction can profit much from automatic cognate detection. Especially where scholars are merely interested in exploring the bigger picture of a language family’s phylogeny, algorithms for automatic cognate detection are a useful complement for current research on language phylogenies.
Study of P, Ca, Sr, Ba and Pb Levels in Enamel and Dentine of Human Third Molars for Environmental and Archaeological Research

Elemental determination of 80 third molars, collected from local dental clinics in Hsinchu City, Taiwan during 2009 to 2010, was conducted using inductively coupled plasma—mass spectrometry (ICP-MS). Results show that the mean concentrations of P, Ca, Sr, Ba and Pb in enamel are respectively 14.63% ± 2.19%, 27.91% ± 4.03%, 108.31 ± 35.71 ppm, 1.96 ± 1.01 ppm, and 0.72 ± 0.49 ppm. The concentrations of P, Ca and Sr are higher in enamel than in dentine, on the other hand, the concentrations of Ba and Pb are higher in dentine than in enamel. In enamel and dentine the concentrations of P, Ca and Ca/P ratio are kept constant. In enamelthe concentrations of Sr and Sr/Ca increase by age statistically but the concentrations of Ba and Ba/Ca are not. Pb concentrations in both enamel and dentine increase by age and also increase with significant differences among each birth era. This may indicate the dates of environmental exposure. The levels of Pb in this study are lower than the previous published findings before 1979. The concentrations and distribution of elements in enamel and dentine of third molars other than deciduous or permanent teeth can provide reliable base references to past and future studies.
The aqueous extract of Glycyrrhiza inflata can upregulate unfolded protein response-mediated chaperones to reduce tau misfolding in cell models of Alzheimer’s disease

Background Alzheimer’s disease (AD) and several neurodegenerative disorders known as tauopathies are characterized by misfolding and aggregation of tau protein. Although several studies have suggested the potential of traditional Chinese medicine (TCM) as treatment for neurodegenerative diseases, the role of TCM in treating AD and tauopathies have not been well explored. Materials and methods Tau protein was coupled to the DsRed fluorophore by fusing a pro-aggregation mutant of repeat domain of tau (ΔK280 tauRD) with DsRed. The ΔK280 tauRD-DsRed fusion gene was then used to generate Tet-On 293 and SH-SY5Y cell clones as platforms to test the efficacy of 39 aqueous extracts of TCM in reducing tau misfolding and in neuroprotection. Results Seven TCM extracts demonstrated a significant reduction in tau misfolding and reactive oxidative species with low cytotoxicity in the ΔK280 tauRD-DsRed 293 cell model. Glycyrrhiza inflata and Panax ginseng also demonstrated the potential to improve neurite outgrowth in the ΔK280 tauRD-DsRed SH-SY5Y neuronal cell model. G. inflata further rescued the upregulation of ERN2 (pro-apoptotic) and downregulation of unfolded-protein-response-mediated chaperones ERP44, DNAJC3, and SERP1 in ΔK280 tauRD-DsRed 293 cells. Conclusion This in vitro study provides evidence that G. inflata may be a novel therapeutic for AD and tauopathies. Future applications of G. inflata on animal models of AD and tauopathies are warranted to corroborate its effect of reducing misfolding and potential disease modification.
Discriminatory Indices of Typing Methods for Epidemiologic Analysis of Contemporary Staphylococcus aureus Strains

Abstract Historically, a number of typing methods have been evaluated for Staphylococcus aureus strain characterization. The emergence of contemporary strains of community-associated S. aureus, and the ensuing epidemic with a predominant strain type (USA300), necessitates re-evaluation of the discriminatory power of these typing methods for discerning molecular epidemiology and transmission dynamics, essential to investigations of hospital and community outbreaks. We compared the discriminatory index of 5 typing methods for contemporary S. aureus strain characterization. Children presenting to St. Louis Children's Hospital and community pediatric practices in St. Louis, Missouri (MO), with community-associated S. aureus infections were enrolled. Repetitive sequence-based PCR (repPCR), pulsed-field gel electrophoresis (PFGE), multilocus sequence typing (MLST), staphylococcal protein A (spa), and staphylococcal cassette chromosome (SCC) mec typing were performed on 200 S. aureus isolates. The discriminatory index of each method was calculated using the standard formula for this metric, where a value of 1 is highly discriminatory and a value of 0 is not discriminatory. Overall, we identified 26 distinct strain types by repPCR, 17 strain types by PFGE, 30 strain types by MLST, 68 strain types by spa typing, and 5 strain types by SCCmec typing. RepPCR had the highest discriminatory index (D) of all methods (D = 0.88), followed by spa typing (D = 0.87), MLST (D = 0.84), PFGE (D = 0.76), and SCCmec typing (D = 0.60). The method with the highest D among MRSA isolates was repPCR (D = 0.64) followed by spa typing (D = 0.45) and MLST (D = 0.44). The method with the highest D among MSSA isolates was spa typing (D = 0.98), followed by MLST (D = 0.93), repPCR (D = 0.92), and PFGE (D = 0.89). Among isolates designated USA300 by PFGE, repPCR was most discriminatory, with 10 distinct strain types identified (D = 0.63). We identified 45 MRSA isolates which were classified as identical by PFGE, MLST, spa typing, and SCCmec typing (USA300, ST8, t008, SCCmec IV, respectively); within this collection, there were 5 distinct strain types identified by repPCR. The typing methods yielded comparable discriminatory power for S. aureus characterization overall; when discriminating among USA300 isolates, repPCR retained the highest discriminatory power. This property is advantageous for investigations conducted in the era of contemporary S. aureus infections.
Novel inter-crystal scattering event identification method for PET detectors

Here, we propose a novel method to identify inter-crystal scattering (ICS) events from a PET detector that is even applicable to light-sharing designs. In the proposed method, the detector observation was considered as a linear problem and ICS events were identified by solving this problem. Two ICS identification methods were suggested for solving the linear problem, pseudoinverse matrix calculation and convex constrained optimization. The proposed method was evaluated based on simulation and experimental studies. For the simulation study, an 8 × 8 photo sensor was coupled to 8 × 8, 10 × 10 and 12 × 12 crystal arrays to simulate a one-to-one coupling and two light-sharing detectors, respectively. The identification rate, the rate that the identified ICS events correctly include the true first interaction position and the energy linearity were evaluated for the proposed ICS identification methods. For the experimental study, a digital silicon photomultiplier was coupled with 8 × 8 and 10 × 10 arrays of 3 × 3 × 20 mm3 LGSO crystals to construct the one-to-one coupling and light-sharing detectors, respectively. Intrinsic spatial resolutions were measured for two detector types. The proposed ICS identification methods were implemented, and intrinsic resolutions were compared with and without ICS recovery. As a result, the simulation study showed that the proposed convex optimization method yielded robust energy estimation and high ICS identification rates of 0.93 and 0.87 for the one-to-one and light-sharing detectors, respectively. The experimental study showed a resolution improvement after recovering the identified ICS events into the first interaction position. The average intrinsic spatial resolutions for the one-to-one and light-sharing detector were 1.95 and 2.25 mm in the FWHM without ICS recovery, respectively. These values improved to 1.72 and 1.83 mm after ICS recovery, respectively. In conclusion, our proposed method showed good ICS identification in both one-to-one coupling and light-sharing detectors. We experimentally validated that the ICS recovery based on the proposed identification method led to an improved resolution.
Optimization of analytical methods to improve detection of erythromycin from water and sediment

Analytical methods to improve the detection of erythromycin in water and sediment were developed to optimize for erythromycin's recovery of extractable and bound residues from the aquatic environment. The objective of this study was to determine optimal recovery of erythromycin from water and sediment to improve its detection in environmental samples through solid-phase extraction (SPE) and sediment-extraction methods. SPE methods examined included previously reported methods for macrolide and sulfonamide antibiotics with erythromycin recoveries ranging from 75.5 % to 94.7 %. Extraction of erythromycin was performed from sand employing various solvents and buffers to determine the best method for extraction from two sandy loam pond sediments. Various extraction times were also examined, and all extraction procedures were performed in duplicate. The greatest recovery of 14C-erythromycin in the Iowa sediment was 84 % using 0.3 M ammonium acetate at pH 4.2: acetonitrile (15:85, v/v) solution. The Oklahoma sediment yielded the greatest recovery of 14C-erythromycin at 86.7 % with 0.3 M ammonium acetate at pH 7: acetonitrile (30:70, v/v) with a 60-minute shake time. The present results demonstrate improved extraction methods for enhancing the accuracy of erythromycin detection from environmental samples.
Prognostic score to predict mortality during TB treatment in TB/HIV co-infected patients

Background Estimating mortality risk during TB treatment in HIV co-infected patients is challenging for health professionals, especially in a low TB prevalence population, due to the lack of a standardized prognostic system. The current study aimed to develop and validate a simple mortality prognostic scoring system for TB/HIV co-infected patients. Methods Using data from the CDC’s Tuberculosis Genotyping Information Management System of TB patients in Texas reported from 01/2010 through 12/2016, age ≥15 years, HIV(+), and outcome being “completed” or “died”, we developed and internally validated a mortality prognostic score using multiple logistic regression. Model discrimination was determined by the area under the receiver operating characteristic (ROC) curve (AUC). The model’s good calibration was determined by a non-significant Hosmer-Lemeshow’s goodness of fit test. Results Among the 450 patients included in the analysis, 57 (12.7%) died during TB treatment. The final prognostic score used six characteristics (age, residence in long-term care facility, meningeal TB, chest x-ray, culture positive, and culture not converted/unknown), which are routinely collected by TB programs. Prognostic scores were categorized into three groups that predicted mortality: low-risk (<20 points), medium-risk (20–25 points) and high-risk (>25 points). The model had good discrimination and calibration (AUC = 0.82; 0.80 in bootstrap validation), and a non-significant Hosmer-Lemeshow test p = 0.71. Conclusion Our simple validated mortality prognostic scoring system can be a practical tool for health professionals in identifying TB/HIV co-infected patients with high mortality risk.
Surgical Reconstruction of Interdental Papilla using Subepithelial Connective Tissue Graft by Microsurgical Technique: A Clinical Study

Background: Loss of interdental papilla is one of the most concerning esthetic problem for the patient and equally challenging for the clinician. Management of papillary loss has shown limited success and is limited to case reports with lack of long-term follow-up.Method: Surgical microscope was used at 6X magnification in this study to enhance the visual acuity in the narrow interdental space. 13 cases with 20 sites in the maxillary anterior region were selected for surgical reconstruction. Tunnelling was performed under the deficient papillae and connective tissue graft used to fill the space created.Results: Among 20 sites, 5 sites showed complete papillary fill, while 3 sites were 1 mm deficient. The mean vertical gain achieved was 1.63 mm which was statistically significant at P value <0.01. A significant adverse surgical outcome was diastema formation within 4 weeks postoperatively.Conclusion: Microsurgery enhances the surgeon’s ability to handle delicate papillary tissue and hence more predictable. Splinting of teeth prior to papillary reconstruction may be considered to prevent diastema formation.
ANISOTROPY AS A PROBE OF THE GALACTIC COSMIC-RAY PROPAGATION AND HALO MAGNETIC FIELD

The anisotropy of cosmic rays (CRs) in the solar vicinity is generally attributed to CR streaming due to the discrete distribution of CR sources or local magnetic field modulation. Recently, the two-dimensional large-scale CR anisotropy has been measured by many experiments in the TeV–PeV energy range in both hemispheres. The tail-in excess along the tangential direction of the local spiral arm and the loss cone deficit pointing to the north Galactic pole direction agree with what have been obtained in tens to hundreds of GeV. The persistence of the two large-scale anisotropy structures in such a wide energy range suggests that the anisotropy might be due to global streaming of the Galactic CRs (GCRs). This work tries to extend the observed CR anisotropy picture from the solar system to the whole galaxy. In such a case, we can find a new interesting signature, a loop of GCR streaming, of the GCR propagation. We further calculate the overall GCR streaming induced magnetic field, and find a qualitative consistency with the observed structure of the halo magnetic field.
End-to-End Deep Learning for Robotic Following

Robotic following has many practical applications and involves several cognitive sub-tasks including object identification, localization, tracking, path planning, and motion control. We propose a system that uses a single deep neural network (DNN), with video camera pixels as the only input, to handle all the cognitive perception and visuomotor control functions needed to perform robotic following behaviors. Our approach combines 1) end-to-end deep learning for inferring motion control outputs from visual inputs, 2) multi-task learning for simultaneously producing multiple outputs with the same DNN, and 3) spatio-temporal deep learning for perceiving motion across multiple video frames. We use simulations of truck platooning to quantitatively show that spatio-temporal DNNs increase driving accuracy and improve machine perception of scene kinematics. Experiments conducted with mobile robots in a laboratory test track show real-time embedded systems performance and indicate that an end-to-end deep learning robot is able to follow its leader for long periods of time, while keeping within lanes and avoiding obstacles.
Aluminum‐enhanced alkali diffusion from float glass to PVD‐sputtered silica thin films

Interdiffusion processes between aluminum enriched PVD-sputtered silica thin films and industrial float soda-lime silicate glass substrates are quantitatively studied using SIMS analysis. Heat treatments are performed at temperatures close or above the glass transition temperature of the float glass. Aluminum doping of the film is shown to strongly increase the migration of alkali from the glass substrate to the silica thin film. In particular the final alkali content in the film exhibits a linear scaling with the aluminum concentration. An interdiffusion process is evidenced between bulk alkali ions and protons originating from a significant water content in the as-deposited silica film. Experimental measurements of sodium concentration are shown to be consistent with a simple thermodynamic model based on the equilibration of the activity of sodium between the film and the glass substrate. This article is protected by copyright. All rights reserved.