Who Drops out? A Study of Secondary School Dropouts in Connecticut

The purpose of the study was to investigate the relationships between the dropout pattern and student characteristics such as gender, ethnicity and grade level among exited students from grade 7 to grade 12. The study included 57,709 students from grades 7-12 in the 2006-2007 school year in Connecticut. A logistic regression analysis was conducted to examine demographic factors related to student dropout pattern. This study provides empirical evidence of identifying secondary school students in Connecticut who were more likely to drop out. Identifying the groups of high risk students would help practitioners and policy makers to develop prevention programs or make interventions to reduce student attrition at the early stage, and thus, to close the achievement gap among these groups

Improving gas sensing properties of graphene by introducing dopants and defects: a first-principles study

The interactions between four different graphenes (including pristine, B- or N-doped and defective graphenes) and small gas molecules (CO, NO, NO2 and NH3) were investigated by using density functional computations to exploit their potential applications as gas sensors. The structural and electronic properties of the graphene-molecule adsorption adducts are strongly dependent on the graphene structure and the molecular adsorption configuration. All four gas molecules show much stronger adsorption on the doped or defective graphenes than that on the pristine graphene. The defective graphene shows the highest adsorption energy with CO, NO and NO2 molecules, while the B- doped graphene gives the tightest binding with NH3. Meanwhile, the strong interactions between the adsorbed molecules and the modified graphenes induce dramatic changes to graphene's electronic properties. The transport behavior of a gas sensor using B- doped graphene shows a sensitivity two orders of magnitude higher than that of pristine graphene. This work reveals that the sensitivity of graphene-based chemical gas sensors could be drastically improved by introducing the appropriate dopant or defect

A Review on 3D Printing for Customized Food Fabrication

AbstractThis study introduces the first generation food printer concept designs and workable prototypes that target to revolutionize customized food fabrication by 3D printing (3DP). Different from robotics-based food manufacturing technologies designed to automate manual processes for mass production, 3D food printing integrates 3DP and digital gastronomy technique to manufacture food products with customization in shape, colour, flavor, texture and even nutrition. This introduces artistic capabilities to fine dining, and extend customization capabilities to industrial culinary sector.The selected prototypes are reviewed based on fabrication platforms and printing materials. A detailed discussion on specific 3DP technologies and their associate dispensing/printing process for 3D customized food fabrication are reported for single and multi-material applications. Eventually, impacts of food printing on personalized nutrition, on-demand food fabrication, food processing technologies and process design are reported. Their applications in domestic cooking or catering services can not only provide an engineering solution for customized food design and personalized nutrition control, but also a potential machine to reconfigure a customized food supply chain

Identification of rice chromosome segment substitution line Z322-1-10 and mapping QTLs for agronomic traits from the F₃ population

Chromosome segment substitution lines (CSSLs) are powerful tools to combine naturally occurring genetic variants with favorable alleles in the same genetic backgrounds of elite cultivars. An elite CSSL Z322-1-10 was identified from advanced backcrosses between a japonica cultivar Nipponbare and an elite indica restorer Xihui 18 by SSR marker-assisted selection (MAS). The Z322-1-10 line carries five substitution segments distributed on chromosomes 1, 2, 5, 6 and 10 with an average length of 4.80 Mb. Spikilets per panicle, 1000-grain weight, grain length in the Z322-1-10 line are significantly higher than those in Nipponbare. Quantitative trait loci (QTLs) were identified and mapped for nine agronomic traits in an F3 population derived from the cross between Nipponbare and Z322-1-10 using the restricted maximum likelihood (REML) method in the HPMIXED procedure of SAS. We detected 13 QTLs whose effect ranging from 2.45% to 44.17% in terms of phenotypic variance explained. Of the 13 loci detected, three are major QTL (qGL1, qGW5-1 and qRLW5-1) and they explain 34.68%, 44.17% and 33.05% of the phenotypic variance. The qGL1 locus controls grain length with a typical Mendelian dominance inheritance of 3:1 ratio for long grain to short grain. The already cloned QTL qGW5-1 is linked with a minor QTL for grain width qGW5-2 (13.01%) in the same substitution segment. Similarly, the previously reported qRLW5-1 is also linked with a minor QTL qRLW5-2. Not only the study is important for fine mapping and cloning of the gene qGL1, but also has a great potential for molecular breeding

In-plane and Out-of-plane Plasma Resonances in Optimally Doped La1.84Sr0.16CuO4

We addressed the inconsistency between the electron mass anisotropy ratios determined by the far-infrared experiments and DC conductivity measurements. By eliminating possible sources of error and increasing the sensitivity and resolution in the far-infrared reflectivity measurement on the single crystalline and on the polycrystalline La1.84Sr0.16CuO4, we have unambiguously identified that the source of the mass anisotropy problem is in the estimation of the free electron density involved in the charge transport and superconductivity. In this study we found that only 2.8 % of the total doping-induced charge density is itinerant at optimal doping. Our result not only resolves the mass anisotropy puzzle but also points to a novel electronic structure formed by the rest of the electrons that sets the stage for the high temperature superconductivity

Probing the nature of the conjectured low-spin wobbling bands in atomic nuclei

The precession of an atomic nucleus can be approximately described as wobbling motion, arising from the coupling of a rotation and a harmonic vibration. Recently, a number of wobbling bands were reported at low spin, which violate the wobbling approximation that can be valid only at high spin. In the present work, we explore the nature of the reported low-spin wobbling bands. Via a new experiment including both angular correlation and linear polarization measurements, we demonstrate that one such band in 187Au is generated by dominant single-particle excitation rather than by the excitation of a wobbling phonon. Assessing the experimental proofs and discussions to assign the reported low-spin wobbling bands, we further point out that the imperfect research paradigm used previously would lead to unreliable identification of low-spin wobbling bands

Detection of herb-symptom associations from traditional chinese medicine clinical data

YesTraditional Chinese medicine (TCM) is an individualized medicine by observing the symptoms and signs (symptoms in brief) of patients. We aim to extract the meaningful herb-symptom relationships from large scale TCM clinical data. To investigate the correlations between symptoms and herbs held for patients, we use four clinical data sets collected from TCM outpatient clinical settings and calculate the similarities between patient pairs in terms of the herb constituents of their prescriptions and their manifesting symptoms by cosine measure. To address the large-scale multiple testing problems for the detection of herb-symptom associations and the dependence between herbs involving similar efficacies, we propose a network-based correlation analysis (NetCorrA) method to detect the herb-symptom associations. The results show that there are strong positive correlations between symptom similarity and herb similarity, which indicates that herb-symptom correspondence is a clinical principle adhered to by most TCM physicians. Furthermore, the NetCorrA method obtains meaningful herb-symptom associations and performs better than the chi-square correlation method by filtering the false positive associations. Symptoms play significant roles for the prescriptions of herb treatment. The herb-symptom correspondence principle indicates that clinical phenotypic targets (i.e., symptoms) of herbs exist and would be valuable for further investigations