Miracle-dz/UniFAR-FTUs huggingface dataset:
Trimester-specific reference interval for thyroid hormones during pregnancy at a Tertiary Care Hospital in Haryana, India

Background: Reference intervals for thyroid hormone during pregnancy need to be gestational age, method, and population specific and there is need to establish trimester-specific thyroid levels for the different population across the world. The aim of this study was to establish trimester-specific reference range for thyroid hormone during pregnancy in a tertiary care center in Haryana. Materials and Methods: A total of 1430 pregnant women were recruited for the study. Participants having any history of chronic illness, goiter on physical examination, thyroid illness in the past or present, consuming thyroid medications, family history of thyroid illness, presence of anti-thyroid peroxidase antibody, poor obstetrics history were excluded from the study and reference population was identified to calculate serum free triiodothyronine (FT3), free thyroxine (FT4) and thyrotropin (TSH) for each trimester of pregnancy. Results: The 2.5–97.5th percentiles for FT3, FT4, and TSH obtained in this study were 2.53–4.54 pg/ml, 0.88–1.78 ng/ml and 0.37–3.69 μIU/ml in the first trimester, 2.0–4.73 pg/ml, 0.91–1.78 ng/ml and 0.54–4.47 μIU/ml in the second trimester, 2.01–4.01 pg/ml, 0.83–1.73 ng/ml, and 0.70–4.64 μIU/ml in the third trimester of pregnancy. Mean TSH increased and mean FT3 decreased significantly with the progression of gestational period. FT4 decreased from trimester 1–3rd, but the decrease was nonsignificant from 2nd to 3rd trimester. Conclusions: Existing results for trimester-specific reference intervals for thyroid hormones are inconsistent and cannot be extrapolated due to differences in ethnicity, maternal iodine status, laboratory assay method, and rigor for selection of reference population. Thus, establishment of reference intervals in each region is of great importance.
Southern Ocean deep convection in global climate models: A driver for variability of subpolar gyres and Drake Passage transport on decadal timescales

We investigate the individual and joint decadal variability of Southern Ocean state quantities, such as the strength of the Ross and Weddell Gyres, Drake Passage transport, and sea ice area, using the National Institute of Water and Atmospheric Research UK Chemistry and Aerosols (NIWA-UKCA) model and CMIP5 models. Variability in these quantities is stimulated by strong deep reaching convective events in the Southern Ocean, which produce an Antarctic Bottom Water-like water mass and affect the large-scale meridional density structure in the Southern Ocean. An increase in the (near) surface stratification, due to freshwater forcing, can be a precondition for subsequent strong convection activity. The combination of enhanced-gyre driven sea ice and freshwater export, as well as ongoing subsurface heat accumulation, lead to a time lag between changes in oceanic freshwater and heat content. This causes an ongoing weakening of the stratification until sudden strong mixing events emerge and the heat is released to the atmosphere. We find that strong convection reduces sea ice cover, weakens the subpolar gyres, increases the meridional density gradient and subsequently results in a positive Drake Passage transport anomaly. Results of available CMIP5 models confirm that variability in sea ice, Drake Passage transport, and the Weddell Gyre strength is enhanced if models show strong open ocean convective events. Consistent relationships between convection, sea ice, Drake Passage transport, and Ross Gyre strength variability are evident in most models, whether or not they host open ocean convection.
Microsurgical Procedures for Studying the Developmental Significance of the Proepicardium and Epicardium in Avian Embryos: PE-Blocking, PE-Photoablation, and PE-Grafting

The epicardium is the outer skin of the mature vertebrate heart. Its embryonic origin and its possible roles in the developing and mature heart did not receive much recognition during the 19th and most of the 20th century. During the past 25 years, however, the epicardium came into the focus of developmental biology and regenerative medicine. Clinical researchers usually prefer genetically modified mouse models when they want to gain insight into developmental or pathological processes. The story of research on the embryonic epicardium, however, nicely demonstrates the value of non-mammalian species, namely avian species, for elucidating fundamental processes in embryonic and fetal development. Studies on chick and quail embryos have not only led to the identification of the primarily extracardiac source of the epicardium—presently called the proepicardium (PE)—they have also significantly contributed to our current knowledge about the developmental significance of the embryonic epicardium. In this review article, I describe three “classical” microsurgical experiments that have been developed for studying the developmental significance of the PE/epicardium in avian embryos (mechanical PE-blocking, PE-photoablation, orthotopic PE-grafting). Furthermore, I show how these microsurgical experiments have contributed to our current knowledge about the roles of the PE/epicardium in cardiac development. There are still some unsolved aspects in the physiology of the developing epicardium, which may be clarified with the aid of these “classical” microsurgical experiments.
Adaptive Coverage and Operational Profile-Based Testing for Reliability Improvement

We introduce covrel, an adaptive software testing approach based on the combined use of operational profile and coverage spectrum, with the ultimate goal of improving the delivered reliability of the program under test. Operational profile-based testing is a black-box technique that selects test cases having the largest impact on failure probability in operation, as such, it is considered well suited when reliability is a major concern. Program spectrum is a characterization of a program's behavior in terms of the code entities (e.g., branches, statements, functions) that are covered as the program executes. The driving idea of covrel is to complement operational profile information with white-box coverage measures based on count spectra, so as to dynamically select the most effective test cases for reliability improvement. In particular, we bias operational profile-based test selection towards those entities covered less frequently. We assess the approach by experiments with 18 versions from 4 subjects commonly used in software testing research, comparing results with traditional operational and coverage testing. Results show that exploiting operational and coverage data in a combined adaptive way actually pays in terms of reliability improvement, with covrel overcoming conventional operational testing in more than 80% of the cases.
A 40 nm CMOS analog front end with enhanced audio for HSPA/EDGE multimedia applications

A 40 nm CMOS analog front end (AFE) supporting HSPA/EDGE multimedia and enhanced audio applications is reported. The AFE consists of hi-fi audio and high-performance peripheral and auxiliary subsystems. Circuit techniques that enable a 200 μA audio RX path and a Class-AB driver with -80 dB THD are discussed. Audio playback and capture paths achieve 105 dB and 85 dB SNR, respectively.
Alzheimer's Disease and Non-Demented High Pathology Control Nonagenarians: Comparing and Contrasting the Biochemistry of Cognitively Successful Aging

The amyloid cascade hypothesis provides an economical mechanistic explanation for Alzheimer's disease (AD) dementia and correlated neuropathology. However, some nonagenarian individuals (high pathology controls, HPC) remain cognitively intact while enduring high amyloid plaque loads for decades. If amyloid accumulation is the prime instigator of neurotoxicity and dementia, specific protective mechanisms must enable these HPC to evade cognitive decline. We evaluated the neuropathological and biochemical differences existing between non-demented (ND)-HPC and an age-matched cohort with AD dementia. The ND-HPC selected for our study were clinically assessed as ND and possessed high amyloid plaque burdens. ELISA and Western blot analyses were used to quantify a group of proteins related to APP/Aβ/tau metabolism and other neurotrophic and inflammation-related molecules that have been found to be altered in neurodegenerative disorders and are pivotal to brain homeostasis and mental health. The molecules assumed to be critical in AD dementia, such as soluble or insoluble Aβ40, Aβ42 and tau were quantified by ELISA. Interestingly, only Aβ42 demonstrated a significant increase in ND-HPC when compared to the AD group. The vascular amyloid load which was not used in the selection of cases, was on the average almost 2-fold greater in AD than the ND-HPC, suggesting that a higher degree of microvascular dysfunction and perfusion compromise was present in the demented cohort. Neurofibrillary tangles were less frequent in the frontal cortices of ND-HPC. Biochemical findings included elevated vascular endothelial growth factor, apolipoprotein E and the neuroprotective factor S100B in ND-HPC, while anti-angiogenic pigment epithelium derived factor levels were lower. The lack of clear Aβ-related pathological/biochemical demarcation between AD and ND-HPC suggests that in addition to amyloid plaques other factors, such as neurofibrillary tangle density and vascular integrity, must play important roles in cognitive failure.
Inhibitory Role of Sphingosine 1-Phosphate Receptor 2 in Macrophage Recruitment during Inflammation

Macrophage recruitment to sites of inflammation is an essential step in host defense. However, the mechanisms preventing excessive accumulation of macrophages remain relatively unknown. The lysophospholipid sphingosine 1-phosphate (S1P) promotes T and B cell egress from lymphoid organs by acting on S1P receptor 1 (S1P1R). More recently, S1P5R was shown to regulate NK cell mobilization during inflammation, raising the possibility that S1P regulates the trafficking of other leukocyte lineages. In this study, we show that S1P2R inhibits macrophage migration in vitro and that S1P2R-deficient mice have enhanced macrophage recruitment during thioglycollate peritonitis. We identify the signaling mechanisms used by S1P2R in macrophages, involving the second messenger cAMP and inhibition of Akt phosphorylation. In addition, we show that the phosphoinositide phosphatase and tensin homolog deleted on chromosome 10, which has been suggested to mediate S1P2R effects in other cell types, does not mediate S1P2R inhibition in macrophages. Our results suggest that S1P serves as a negative regulator of macrophage recruitment by inhibiting migration in these cells and identify an additional facet to the regulation of leukocyte trafficking by S1P.
Association Mapping for Fruit, Plant and Leaf Morphology Traits in Eggplant

An eggplant (Solanum melongena) association panel of 191 accessions, comprising a mixture of breeding lines, old varieties and landrace selections was SNP genotyped and phenotyped for key breeding fruit and plant traits at two locations over two seasons. A genome-wide association (GWA) analysis was performed using the mixed linear model, which takes into account both a kinship matrix and the sub-population membership of the accessions. Overall, 194 phenotype/genotype associations were uncovered, relating to 30 of the 33 measured traits. These associations involved 79 SNP loci mapping to 39 distinct chromosomal regions distributed over all 12 eggplant chromosomes. A comparison of the map positions of these SNPs with those of loci derived from conventional linkage mapping showed that GWA analysis both validated many of the known controlling loci and detected a large number of new marker/trait associations. Exploiting established syntenic relationships between eggplant chromosomes and those of tomato and pepper recognized orthologous regions in ten eggplant chromosomes harbouring genes influencing breeders’ traits.
Jupiter's unearthly jets: a new turbulent model exhibiting statistical steadiness without large-scale dissipation

A longstanding mystery about Jupiter has been the straightness and steadiness of its weather-layer jets, quite unlike terrestrial strong jets with their characteristic unsteadiness and long-wavelength meandering. The problem is addressed in two steps. The first is to take seriously the classic Dowling-Ingersoll (DI) 1-1/2-layer scenario and its supporting observational evidence, pointing toward deep, massive, zonally-symmetric zonal jets in the underlying dry-convective layer. The second is to improve the realism of the model stochastic forcing used to represent the effects of Jupiter's moist convection as far as possible within the 1-1/2-layer dynamics. The real moist convection should be strongest in the belts where the interface to the deep flow is highest and coldest, and should generate cyclones as well as anticyclones with the anticyclones systematically stronger. The new model forcing reflects these insights. Also, it acts quasifrictionally on large scales to produce statistically steady turbulent weather-layer regimes without any need for explicit large-scale dissipation, and with weather-layer jets that are approximately straight thanks to the influence of the deep jets, allowing shear stability despite nonmonotonic potential-vorticity gradients when the Rossby deformation lengthscale is not too large. Moderately strong forcing produces chaotic vortex dynamics and realistic belt-zone contrasts in the model's convective activity, through an eddy-induced sharpening and strengthening of the weather-layer jets relative to the deep jets, tilting the interface between them. Weak forcing, for which the only jet-sharpening mechanism is the passive (Kelvin) shearing of vortices (as in the "CE2" or "SSST" theories), produces unrealistic belt-zone contrasts.
Application of Neural Networks in Aid for Diagnosis for Patients with Glaucoma

Glaucoma is an ophthalmologic disease very difficult to diagnose in the earlier phase. Additionally, exams and methods used to give reliable information for correct diagnosis are usually very expensive. Therefore, other methods less expensive and also reliable must be proposed as an auxiliary tool to Glaucoma diagnosis. This paper analyzes the performance of neural networks as an auxiliary tool for the diagnosis of patients with glaucoma, avoiding the use of data only available in expensive exams. The analysis considers two different kinds of neural networks (Multi-Layer Perceptron (MLP) and Probabilistic Neural Networks (PNN)) and two different methods variable selection: a random and iterative method; and the Least Square Extrapolation (LSE) method. The paper also evaluates the benefits of applying principal components analysis (PCA) to the database. The results obtained were very good, attaining an accuracy of more than 90% of correct classification of all cases present in our database. It confirms the real possibility of using neural networks as an auxiliary and inexpensive tool to help in Glaucoma diagnosis.
Unattended words are not identified

A stand for bicycles or other two wheel vehicles includes a base unit with two staggered wheel supporting cradles and a plurality of add-on units. Vertical uprights for each cradle define spaces or slots for the front wheels of two bicycles extending in opposed directions. Each base unit supports four bicycles and each add-on unit, two bicycles. When the base and add-on units are connected the uprights which define the wheel receiving slots are located along two parallel spaced axes. Such an arrangement provides good stability, utilizes a minimum amount of framing material and provides a compact arrangement for closely locating bicycles in a relatively small storage space.
A concrete approach to teaching symbolic algebra

Student difficulties with the study of algebra have been well documented. The inability of many students to understand variables and formal symbolic manipulation act as a barrier to success in mathematics study. This report documents an intervention that uses a concrete approach to teaching algebra in a Year 9 class. Results indicate that much of the student struggle was associated with a lack of understanding of arithmetic concepts including those associated with equivalence, operations with negative integers, and the distributive law and fraction concepts. Once these difficulties were addressed through the explicit teaching of the links between materials and symbols, materials and language, language and symbols, students made considerable progress in writing, simplifying expressions, and solving equations with variables on both sides.
Using Model Reduction techniques for simulating the heat transfer in electronic systems

There is an increasing need for quicker heat transfer simulations of electronic systems during its design process. Typically, FEM simulations require a lot of computational time and memory. Our work focuses on creating reduced order models of the thermal models of such systems. More specifically, Krylov subspace and Proper Orthogonal Decomposition methods are being used to create such reduced order models. Eventually, we are aiming to create a library of reduced order models of different components of electronic systems so that the heat transfer simulation of the entire system can be obtained when we interconnect several such reduced order models. This paper proposes a method for applying model reduction techniques to heat transfer problems in electronic systems and we state the initial results of our study and the main problems that have to be dealt with in our future work. Introduction: There is a great need for quick and accurate heat transfer simulations in the micro-packaging community. This is especially true in today's world where packages are getting smaller and problems of inefficient heat dissipation are beginning to affect the performance of micro-devices. Hence, searching a larger part of the micro-packaging design space has become very important. The bottlenecks which prevents one from exploring larger parts of the design space are the increased computational costs and storage. In this regard, apart from further improvements in machine speed and numerical algorithm accuracy, one would definitely like to reduce the size of the heat transfer models as much as possible without unduly compromising on accuracy. Currently, the electronic thermal design community uses very large numerical simulations (involving thousands of states) to model multi-mode heat transfer and fluid flow in packaged electronics [1]. This results in enormous computational costs. Previous efforts included compact modeling [2], which aimed at simulating steady state heat conduction within geometrically complex structures subject to convective and/or radiative surface conditions. We propose to use model reduction techniques like krylov subspace methods [3] and proper orthogonal decomposition [4] in order to reduce the size of the models. The structure of this paper is as follows. We explain our solution technique, i.e. the way we discretized the original heat transfer model and the various model reduction techniques that we considered (along with their brief descriptions) and the reasons why we chose the krylov subspace based model reduction technique for solving the heat conduction problem and the proper orthogonal decomposition method for …
Detecting shadows in image sequences

In this paper, we present an algorithm for the detection of local illumination changes due to shadows in real world sequences. The algorithm is designed to be able to work when camera, illumination and scene’s characteristics are unknown. This feature is highly desirable for a wide range of applications, such as video production, immersive gaming, and visual surveillance. The algorithm operates as follows. First colour information is exploited, then multiple constraints from physical knowledge are embedded to define the shadow detection algorithm. Colour information is exploited by means of the RGB colour space and by means of photometric invariant features. After colour analysis, a spatio-temporal verification stage is introduced to refine the results. Experimental results show that the proposed algorithm outperforms state-of-the-art methods and can be applied on both indoor and outdoor image sequences
Prediction of Drug Clearance and Drug-Drug Interactions in Microscale Cultures of Human Hepatocytes

Accurate prediction of in vivo hepatic drug clearance using in vitro assays is important to properly estimate clinical dosing regimens. Clearance of low-turnover compounds is especially difficult to predict using short-lived suspensions of unpooled primary human hepatocytes (PHHs) and functionally declining PHH monolayers. Micropatterned cocultures (MPCCs) of PHHs and 3T3-J2 fibroblasts have been shown previously to display major liver functions for several weeks in vitro. In this study, we first characterized long-term activities of major cytochrome P450 enzymes in MPCCs created from unpooled cryopreserved PHH donors. MPCCs were then used to predict the clearance of 26 drugs that exhibit a wide range of turnover rates in vivo (0.05–19.5 ml/min per kilogram). MPCCs predicted 73, 92, and 96% of drug clearance values for all tested drugs within 2-fold, 3-fold, and 4-fold of in vivo values, respectively. There was good correlation (R2 = 0.94, slope = 1.05) of predictions between the two PHH donors. On the other hand, suspension hepatocytes and conventional monolayers created from the same donor had significantly reduced predictive capacity (i.e., 30–50% clearance values within 4-fold of in vivo), and were not able to metabolize several drugs. Finally, we modulated drug clearance in MPCCs by inducing or inhibiting P450s. Rifampin-mediated CYP3A4 induction increased midazolam clearance by 73%, while CYP3A4 inhibition with ritonavir decreased midazolam clearance by 79%. Similarly, quinidine-mediated CYP2D6 inhibition reduced clearance of dextromethorphan and desipramine by 71 and 22%, respectively. In conclusion, MPCCs created using cryopreserved unpooled PHHs can be used for drug clearance predictions and to model drug-drug interactions.
Predicting Conscientiousness through Semantic Analysis of Facebook Posts

Here we present a method for detecting an individual's level of conscientiousness based on an analysis of the content of their Facebook status updates. Our model is based on the identification of semantic evidence of facets related to conscientiousness; an individual's belief of their control over events around them and their goal orientation. The model achieves a correlation of r=. 27 on a subset of the Facebook data published for the myPersonality workshop, with an accuracy of 58.13% for detecting if an individual is above or below the median and 68.03% for those outside of one standard deviation. While we take a narrow approach and identify only one personality trait, the general methodology of directly looking for evidence of traits in an individual's utterances is applicable to discovering models for all of the personality traits.