Aspect construal in Mandarin: a usage-based constructionist perspective on LE

Despite extensive research efforts to explain the Mandarin Chinese particle le, confusion persists in the absence of a unitary theory and sufficient empirical evidence. This study provides a unitary account of le by adopting a usage-based constructionist approach, one that liberates grammatical aspect from, and is able to accommodate, lexical aspect. We argue that le participates in two distinct family resemblance constructions of aspect construal associated with two distinct sentential positions. The clause-internal le construction construes the closing or final boundary of an event and the clause-final le construction construes the opening or initial boundary of an event. Corpus analysis showed that the two aspect constructions have distinct patterns in natural language uses that are consistent with the proposed construals. Results from elicited response data showed that native speakers paid attention to construction-level formal and semantic cues in making family resemblance judgments about tokens of the two constructions. This study has both theoretical and methodological implications for crosslinguistic research on grammatical aspect in relation to lexical aspect and for usage-based constructionist approaches to grammatical categories beyond aspect.

Characteristics of radiative and non-radiative energy fluxes over monsoon trough zone

In order to describe behaviour of radiative and non-radiative erergy fluxes in the surface layer, computation of net radiation, sensible, latent and heat soil flux has been done using hourly global radiation, slow response data of MONTBLEX-90 and surface observation of Varanasi and Jodhpur during rainy and non-rainy days in July 1990. Daily and hourly ground temperature is calculated solving one dimensional heat conduction equation and soil heat flux is computed using force restored method .Outgoing Longwave Radiation (OLR) is calculated by Stefan-Boltzrnann law of radiation and the largest diurnal variability was found over dry convective zone. Results show that OLR from the ground lies in the range 473.0-537.6 Wm-2 at Jodhpur and 497.4 -548.4 Wm-2 at Varanasi during generally cloudy day. The dip in OLR is increascd by 10% with increase of relative humidity and cloudiness. Daily mean of the largest downward soil heat flux are found as 206.4 and 269.4 Wm-2 at Varanasi and Jodhpur respectively during cloudy day. About 40-50% of net radiation is imparted to soil heat flux at Varanasi and Jodhpur. Sum of the hourly non- radiative energy fluxes has not been balanced by net radiation while daily cumulative value of the fluxes balances the net radiation during non-rainy day.

RAD gene family analysis in cotton provides some key genes for flowering and stress tolerance in upland cotton G. hirsutum

Background RADIALIS (RAD), belongs to the MYB gene family and regulates a variety of functions including floral dorsoventral asymmetry in Antirrhinum majus and development of fruit proteins in Solanum lycopersicum. RAD genes contain an SNF2_N superfamily domain. Here, we comprehensively identified 68 RAD genes from six different species including Arabidopsis and five species of cotton. Results Phylogenetic analysis classified RAD genes into five groups. Gene structure, protein motifs and conserved amino acid residues indicated that GhRAD genes were highly conserved during the evolutionary process. Chromosomal location information showed that GhRAD genes were distributed unevenly on different chromosomes. Collinearity and selection pressure analysis indicated RAD gene family expansion in G. hirsutum and G. barbadense with purifying selection pressure. Further, various growth and stress related promotor cis-acting elements were observed. Tissue specific expression level indicated that most GhRAD genes were highly expressed in roots and flowers (GhRAD2, GhRAD3, GhRAD4 and GhRAD11). Next, GhRAD genes were regulated by phytohormonal stresses (JA, BL and IAA). Moreover, Ghi-miRN1496, Ghi-miR1440, Ghi-miR2111b, Ghi-miR2950a, Ghi-miR390a, Ghi-miR390b and Ghi-miR7495 were the miRNAs targeting most of GhRAD genes. Conclusions Our study revealed that RAD genes are evolutionary conserved and might be involved in different developmental processes and hormonal stress response. Data presented in our study could be used as the basis for future studies of RAD genes in cotton.

Evaluation of Calibration Equations by Using Regression Analysis: An Example of Chemical Analysis

A calibration curve is used to express the relationship between the response of the measuring technique and the standard concentration of the target analyst. The calibration equation verifies the response of a chemical instrument to the known properties of materials and is established using regression analysis. An adequate calibration equation ensures the performance of these instruments. Most studies use linear and polynomial equations. This study uses data sets from previous studies. Four types of calibration equations are proposed: linear, higher-order polynomial, exponential rise to maximum and power equations. A constant variance test was performed to assess the suitability of calibration equations for this dataset. Suspected outliers in the data sets are verified. The standard error of the estimate errors, s, was used as criteria to determine the fitting performance. The Prediction Sum of Squares (PRESS) statistic is used to compare the prediction ability. Residual plots are used as quantitative criteria. Suspected outliers in the data sets are checked. The results of this study show that linear and higher order polynomial equations do not allow accurate calibration equations for many data sets. Nonlinear equations are suited to most of the data sets. Different forms of calibration equations are proposed. The logarithmic transformation of the response is used to stabilize non-constant variance in the response data. When outliers are removed, this calibration equation’s fit and prediction ability is significantly increased. The adequate calibration equations with the data sets obtained with the same equipment and laboratory indicated that the adequate calibration equations differed. No universe calibration equation could be found for these data sets. The method for this study can be used for other chemical instruments to establish an adequate calibration equation and ensure the best performance.

Study on the Behavior of Helmholtz Resonance in Different Size Bottles

The resonance is the specific response of system which is capable to vibrate with certain frequency to an external force acting with the same frequency. When air is blown across the open mouth of different bottles then air vibrate in a neck at resonant frequency. In this study we consider 5-5 bottles of different five types bottles having different of length of neck, radius of port, cross-sectional area of port and same volume (250ml). Resonance in different bottles was studied to determine how the volume of air cavity of different bottle affects the resonance. From calculated and experimental data, we found that the Helmholtz resonance frequency decreases with increase in volume and vice versa in each case of different bottles. From graph we also found that the calculated and experimental model are about 100% and 99% variability of the response data around its mean. The practical range for these different bottles is from about 256 to 512 Hz. This is about an octave plus a musical fifth near the middle of the musical instrument, so most simple musical tunes can be produced with such bottles.

Transportation barriers to care among frequent health care users during the COVID pandemic

Objective: To investigate transportation barriers to accessing health care services during the COVID-19 pandemic among high-frequency health care users.Data Sources: Between June 21 and July 23, 2021, primary survey data were collected for a sample of patients in North Carolina.Study Design: The study analyzed the prevalence of arriving late to, delaying, or missing medical care and examined how transportation barriers contributed to negative health care outcomes. Data Collection Methods: A web-based survey was administered to North Carolina residents aged 18 and older in the UNC Health system who were enrolled in Medicaid or Medicare and had at least six outpatient medical appointments in the past year. 323 complete responses were analyzed to investigate the prevalence of reporting transportation barriers that resulted in having arrived late to, delayed, or missed care, as well as relationships between demographic and other independent variables and transportation barriers. Qualitative analyses were performed on text response data to explain transportation barriers.Principal Findings: Approximately 1 in 3 respondents experienced transportation barriers to health care between June 2020 and June 2021. Multivariate logistic regressions indicate individuals aged 18–64 were significantly more likely to encounter transportation barriers. Costs of traveling for medical appointments and a lack of driver or car availability emerged as major transportation barriers; however, respondents explained that barriers were often complex, involving circumstantial problems related to one’s ability to access and pay for transportation as well as to personal health.Conclusions: To address transportation barriers, we recommend more coordination between transportation and health professionals and the implementation of programs that expand access to and improve patient awareness of health care mobility services. We also recommend transportation and health entities direct resources to address transportation barriers equitably, as barriers disproportionately burden younger adults under age 65 enrolled in public insurance programs.

Functional response regression model on correlated longitudinal microbiome sequencing data

Functional regression has been widely used on longitudinal data, but it is not clear how to apply functional regression to microbiome sequencing data. We propose a novel functional response regression model analyzing correlated longitudinal microbiome sequencing data, which extends the classic functional response regression model only working for independent functional responses. We derive the theory of generalized least squares estimators for predictors’ effects when functional responses are correlated, and develop a data transformation technique to solve the computational challenge for analyzing correlated functional response data using existing functional regression method. We show by extensive simulations that our proposed method provides unbiased estimations for predictors’ effect, and our model has accurate type I error and power performance for correlated functional response data, compared with classic functional response regression model. Finally we implement our method to a real infant gut microbiome study to evaluate the relationship of clinical factors to predominant taxa along time.