Miracle-dz/UniFAR-FTUs huggingface dataset:
Strain effects on three-dimensional, two-dimensional, and one-dimensional silicon logic devices: Predicting the future of strained silicon

Using a classification scheme based on carrier confinement type (electrostatic and spatial) and the degrees of freedom of the mobile carriers (3DOF, 2DOF, and 1DOF), strain effects on 3DOF to 1DOF silicon logic devices are compared from quantum confinement and device geometry perspectives. For these varied device geometries and types, the effects of strain-induced band splitting and band warping on the modification of the average conductivity effective mass and carrier scattering rates are evaluated. It is shown that the beneficial effects of strain-induced band splitting are the most effective for devices with little or no initial band splitting and become less so for devices with already large built-in band splitting. For these devices with large splitting energy, the potential for strain-induced carrier conductivity mass reduction through repopulation of lower energy bands and the suppression of optical intervalley phonon scattering are limited. On the other hand, for all devices without spatial confin.
Weights for the Hellenic Panel study of EES 2014

With poststratification the population is partitioned into subgroups that are called poststrata. The original weights (in our case they are all equal to one) are multiplied by a ratio which is formed by the corresponding population poststratum size in the nominator and the corresponding sample poststratum size in the denominator. (see Lehtonen, R., and Pahkinen, E. (2004) p.88-92; Holt and Smith (1979) ) For instance, this ratio for the male group is: 692.86/984=0.7041, 1.6113, 230.9533. These adjustments to the sampling weights makes the estimated gender distrubution to match the known population gender distribution, making the sample more representative of the population. Thus, after the poststratification adjustment on gender ELNES 2014 using a weight variable that is summarized in Table 3.
Some Properties of Symmetric Stable Distributions

This paper takes a few steps toward alleviating problems of data analysis that arise from the fact that elementary expressions for density and cumulative distribution functions (c.d.f.'s) for most stable distributions are unknown. In section 2 results of Bergstrom [3] are used to develop numerical approximations for the c.d. f. 's and the inverse functions of the c.d. f. 's of symmetric stable distributions. Tables of the c.d. f. 's and their inverse functions are presented for twelve values of the characteristic exponent. In section 3 the usefulness of the numerical c.d. f. 's and their inverse functions in estimating the parameters of stable distributions and testing linear models involving stable variables is discussed. Finally, section 4 presents a Monte Carlo study of truncated means as estimates of location. In every case but the Gaussian, some truncated mean is shown to have smaller sampling dispersion than the full mean.
Single Antenna and No Circulator Full-Duplex With 52 dB Wideband Self-Interference Suppression

Full-duplex (FD) enables high spectrum efficiency and dynamic spectrum accessing, although its application is restricted by significant self-interference. In this work, we present an integrated, single antenna, wideband FD self-interference suppression front-end solution, targeting for short-range wireless communication. Based on the characteristic of bi-directional signal transparency of N-phase passive mixer, a mixer-first active electrical balance self-interference suppression architecture is proposed. As no costly and space-consuming out-of-chip circulator is needed, compared with traditional single antenna suppression solutions, it is attractive for cost and area saving. In addition, to alleviate the multi-path effect, a two-tap baseband self-interference suppression is adopted, which also helps broaden the self-interference suppression bandwidth. The fabricated FD front-end chip, employing 180nm CMOS process, has a noise figure (NF) of 8.6dB, and at the maximum TX power, the NF is degrade by 4.9dB. Test results show the achieved self-interference suppression depth is up to 52dB over 30MHz, with a much smaller antenna interface and chip size which is 0.75 mm2, compared with other dual and signal antenna solutions. The wireless communication function of the propose FD front-end has been verified and the operation carrier frequency range is 0.4-1.2GHz.
Diagnosis of Toxoplasmosis Using Surface Antigen Grade 1 Detection by ELISA, Nano-Gold ELISA, and PCR in Pregnant Women

Introduction The accurate diagnosis of toxoplasmosis has critical importance in pregnant women. Nanotechnology and molecular biology are making possible opportunities for accurate and rapid diagnosis of many infectious diseases. Aim and Methods The aim of our study was to compare nano-gold ELISA with ELISA and PCR for diagnosis of toxoplasmosis using Toxoplasma surface antigen grade 1 (SAG1) in pregnant women seeking antenatal care in outpatient clinics. Results PCR showed the highest diagnostic values than nano-gold ELISA and ELISA regarding sensitivity (97.3% versus 89.2% and 83.8%); specificity (100% versus 94% and 88%); and diagnostic accuracy (98.9% versus 91.95% and 86.2%), respectively. There is no statistical difference between PCR and nanogold ELISA results. Discussion Nano-gold ELISA had a significant improvement in diagnosis than the traditional ELISA method. Most likely with the assistance of nanoparticles, more antibodies enter the antigen–antibody complex because of the considerable improvement in the surface area of nano-gold particles. Conclusion Although PCR had higher diagnostic values than nano ELISA, nano ELISA is cheaper and easier than PCR. We recommend nano-gold ELISA with SAG1 as a promising technique in the diagnosis of toxoplasmosis and survey studies.
The characteristics of soil microbial co-occurrence networks across a high-latitude forested wetland ecotone in China

To understand the effect of seasonal variations on soil microbial communities in a forested wetland ecotone, here, we investigated the dynamics of the diversities and functions of both soil bacterial and fungal communities inhabiting three wetland types (forested wetland, shrub wetland and herbaceous vegetation wetland) from forest-wetland ecotone of northern Xiaoxing’an Mountains spanning different seasons. β-diversity of soil microbial communities varied significantly among different vegetation types (Betula platyphylla–Larix gmelinii, Alnus sibirica, Betula ovalifolia, and Carex schmidtii wetlands). We totally detected 34 fungal and 14 bacterial indicator taxa among distinctive groups by using Linear discriminant analysis effect size (LEfSe) analysis, and identified nine network hubs as the most important nodes detected in whole fungi, bacteria, and fungi–bacteria networks. At the vegetation type-level, bacterial and fungal microbiome living in C. schmidtii wetland soil possessed fewer positive interactions and lower modularity than those in other types of wetland soil. Furthermore, we also discovered that ectomycorrhizal fungi were dominant in the fungal microbiota existing in forested and shrub wetland soils, whereas arbuscular mycorrhizal fungi were predominated in those residing in herbaceous vegetation wetland soil. The distribution of the predicted bacterial functional enzymes also obviously varied among different vegetation-types. In addition, the correlation analysis further revealed that the key fungal network modules were significantly affected by the contents of total N and soil water-soluble K, whereas most of the bacterial network modules were remarkably positively driven by the contents of total N, soil water-soluble K, Mg and Na. Our study suggested that vegetation type are substantive factors controlling the diversity, composition and functional group of soil microbiomes from forest-wetland ecotone of northern Xiaoxing’an Mountains.
Digital transformation in organizational health and safety to mitigate Burnout Syndrome

In 2000, the World Health Organization (WHO) identified Burnout Syndrome as an occupational risk factor, affecting an estimated 10% of workers, resulting in lost productivity and increased costs due to sick leave. Some claim that Burnout Syndrome has reached epidemic proportions in workplaces around the world. While signs of burnout are not difficult to identify and palliate, its real impact is not easy to measure, generating a number of risks for companies from possible loss of human talent to decreased productivity and diminished quality of life. Given the complexity of Burnout Syndrome, it must be addressed in a creative, innovative and systematic way; traditional approaches cannot be expected to deliver different results. This paper describes the experience where an innovation challenge was launched to collect creative ideas to identify, prevent or mitigate Burnout Syndrome through the use of technological tools and software. The challenge was endowed with an economic award and its guidelines stated that the proposals must be both creative and feasible from an economic and organizational point of view. A total of twelve creative projects were submitted, including each of them, the analysis, design and management plans, to envision an idea that is feasible and with the appropriate budget, implemented. In this paper, we present a summary of these creative projects and how the IRSST (Instituto Regional de Seguridad y Salud en el Trabajo) experts and leaders in OHS in the Madrid Region (Spain) envision their potential impact on improving the OHS landscape.
Stochastic Geometry and Its Applications

Mathematical Foundation. Point Processes I--The Poisson Point Process. Random Closed Sets I--The Boolean Model. Point Processes II--General Theory. Point Processes III--Construction of Models. Random Closed Sets II--The General Case. Random Measures. Random Processes of Geometrical Objects. Fibre and Surface Processes. Random Tessellations. Stereology. References. Indexes.
HIV Tat Expression and Cocaine Exposure Lead to Sex- and Age-Specific Changes of the Microbiota Composition in the Gut

The balance of microbial communities in the gut is extremely important for normal physiological function. Disruption of the balance is often associated with various disorders and diseases. Both HIV infection and cocaine use are known to change the gut microbiota and the epithelial barrier integrity, which contribute to inflammation and immune activation. Our recent study shows that Tat expression and cocaine exposure result in changes of genome-wide DNA methylation and gene expression and lead to worsen the learning and memory impairments. In the current study, we extended the study to determine effects of Tat and cocaine on the gut microbiota composition. We found that both Tat expression and cocaine exposure increased Alteromonadaceae in 6-month-old female/male mice. In addition, we found that Tat, cocaine, or both increased Alteromonadaceae, Bacteroidaceae, Cyanobiaceae, Erysipelotrichaceae, and Muribaculaceae but decreased Clostridiales_vadinBB60_group, Desulfovibrionaceae, Helicobacteraceae, Lachnospiraceae, and Ruminococcaceae in 12-month-old female mice. Lastly, we analyzed changes of metabolic pathways and found that Tat decreased energy metabolism and nucleotide metabolism, and increased lipid metabolism and metabolism of other amino acids while cocaine increased lipid metabolism in 12-month-old female mice. These results demonstrated that Tat expression and cocaine exposure resulted in significant changes of the gut microbiota in an age- and sex-dependent manner and provide additional evidence to support the bidirectional gut–brain axis hypothesis.
A discretization method for the numerical solution of Dieudonné–Rashevsky type problems with application to edge detection within noisy image data

The present paper is concerned with the numerical solution of multidimensional control problems of Dieudonné–Rashevsky type by discretization methods and large‐scale optimization techniques. We prove first a convergence theorem wherein the difference of the minimal value and the objective values along a minimizing sequence is estimated by the mesh size of the underlying triangulations. Then we apply the proposed method to the problem of edge detection within raw image data. Instead of using an Ambrosio–Tortorelli type energy functional, we reformulate the problem as a multidimensional control problem. The edge detector can be built immediately from the control variables. The quality of our numerical results competes well with those obtained by applying variational techniques. Copyright © 2011 John Wiley & Sons, Ltd.
When More Satisfying and Supportive Relationships Increase Loneliness: The Social Worlds of People with Lived Experience of Homelessness

People experiencing homelessness can often have small and fragmented social networks, due to the loss and absence of critical connections, leaving them particularly susceptible to loneliness. During the course of homelessness, some people experience a changing profile of networks, transitioning away from family and some friends and forming new/substitute networks, such as service providers or pets. The resulting loneliness can have profound impacts on this group, threatening their physical and mental health and their ability to exit homelessness successfully. This study aimed to understand the social network characteristics and support associated with loneliness. MOS Social Support and social network questionnaire data from 124 participants (either currently or formerly homeless) were used in three hierarchical regression models to predict romantic, social, and family loneliness (SELSA-S), respectively. Findings suggested the more supportive, important, and (often) more satisfying that participants deemed current relationships to be, the lonelier they tended to feel. This occurred even if they were no longer homeless. These findings suggest that loneliness can operate differently in the context of poverty and homelessness. Whilst experiencing homelessness, people may prioritise relationships that provide resources and safety over those that assuage loneliness. Service providers can support people exiting homelessness to (re)connect with important and valued networks to reduce loneliness.
TEMPERATURE-DEPENDENT ABSORPTION MEASUREMENTS OF EXCITONS IN GAN EPILAYERS

Optical absorption measurements were performed on a series of thin GaN epilayers. Sharp spectral features were observed due to the 1s A and B exciton transitions. Using polarization dependent absorption, the C exciton transition was identified. A broad absorption feature was observed at ∼3.6 eV, which is attributed to indirect exciton-phonon absorption. The excitonic structure was found to persist well above room temperature. A fit to the Varshni formula yielded a temperature dependence of E(T)=E(T=0)−11.8×10−4T2(1414+T) eV for the A and B excitons. The exciton absorption linewidth was studied as a function of temperature, indicating that GaN exhibits very large exciton-phonon coupling.
How does the explicit treatment of convection alter the precipitation–soil hydrology interaction in the mid-Holocene African humid period?

Abstract. Global climate models with coarse horizontal resolution are largely unable to reproduce the monsoonal precipitation pattern over North Africa during the mid-Holocene. Here we present the first regional, storm-resolving simulations with an idealized but reasonable mid-Holocene vegetation cover. In these simulations, the West African monsoon expands farther north by about 4–5∘, and the precipitation gradient between the Guinea coast and the Sahara decreases compared to simulations with a barren Sahara as it is today. The northward shift of monsoonal precipitation is caused by land surface–atmosphere interaction, i.e., the coupling of soil moisture and precipitation, as well as interactions of the land surface with the large-scale monsoon circulation (e.g., the African easterly jet). The response of the monsoon circulation to an increased vegetation cover is qualitatively similar but more pronounced in parameterized convection simulations. We attribute the differences in monsoonal precipitation to differences in soil moisture that are strongly controlled by runoff and precipitation characteristics. If precipitation is intense and falls over a spatially small region, as in our storm-resolving simulations, about 35 % of all precipitation water goes into runoff instead of filling soil moisture storage. In contrast, in light and spatially more homogeneous precipitation, as produced in our parameterized convection simulations, only some 20 % leaves the grid cell as runoff. Therefore, much more water is available to maintain high soil moisture content. We confirm the significant role of soil moisture and runoff by performing simulations with the same constant soil moisture field in both storm-resolving and parameterized convection simulations. These constant soil moisture simulations cancel the effect of lower soil moisture on the land–atmosphere feedback cycle in our storm-resolving simulations. We show that precipitation strongly increases in the storm-resolving simulations, especially in moisture-controlled regions, such as the northern Sahel and Sahara, and reaches equally high values as in parameterized convection simulations. Our study highlights how the type of rainfall (e.g., local and intense or widespread and light) impacts soil moisture and thus land–atmosphere feedbacks. This is contrary to many studies that focus mainly on the amount of rainfall and how it modifies land–atmosphere feedbacks. Moreover, this study suggests that comprehensive land-surface schemes, which appropriately respond to varying precipitation characteristics, are needed for studying land surface–atmosphere interaction.
Alignment scores in a regularized support vector classification method for fold recognition of remote protein families

One of fundamental principles of molecular biology says that the primary structure of a protein, i.e. sequence of amino acid residues forming its polypeptide chain, carries an essential amount of information for unambiguous establishing its spatial structure. Despite the fact that each protein has its own spatial structure, it is typical phenomenon that the fold pattern remains basically the same within large groups of evolutionarily allied proteins, so that the "number" of essentially different spatial structures is much less than that of known proteins. Since spatial structures are classified in that or other manner, the estimation of the spatial structure of a given protein reduces to its allocating over a finite set of classes, i.e. the problem falls into the competence area of pattern recognition. The traditional methodology of pattern recognition presupposes that the object whose class-membership is to be recognized is represented by vector of some numerical features and is considered as a point in the respective linear vector space. However, the actual diversity of amino acid properties that may play an important part in forming the spatial structure of a protein is so immensely rich, that the choice of suitable numerical properties makes a special problem which is the key one here. We consider here an alternative featureless approach to recognition of spatial structure of proteins. It is proposed to judge about the membership of a protein in one of the classes of spatial structures immediately on the basis of measuring the proximity of its amino acid chain to those of some other proteins whose spatial structure is known. To infer the decision rule of recognition from a training sample of proteins of known structure, we apply the traditional support vector method of machine learning on the basis of treating amino acid chains as elements of a Hilbert space, i.e. linear space with inner product, in what role the pairwise alignment scores are used. The inevitable difficulty of the small size of training samples is overcome by a special regularization technique that makes use of some available a priori information on the sought-for decision rule. The proposed approach to the problem of fold class recognition illustrated by results of processing a collection of 396 mutually distant protein domains of 51 fold classes chosen from the SCOP database.
Direct numerical simulation of high-speed transition due to an isolated roughness element

Abstract We study the transition of a Mach 6 laminar boundary layer due to an isolated cylindrical roughness element using large-scale direct numerical simulations (DNS). Three flow conditions, corresponding to experiments conducted at the Purdue Mach 6 quiet wind tunnel are simulated. Solutions are obtained using a high-order, low-dissipation scheme for the convection terms in the Navier–Stokes equations. The lowest Reynolds number ( $Re$ ) case is steady, whereas the two higher $Re$ cases break down to a quasi-turbulent state. Statistics from the highest $Re$ case show the presence of a wedge of fully developed turbulent flow towards the end of the domain. The simulations do not employ forcing of any kind, apart from the roughness element itself, and the results suggest a self-sustaining mechanism that causes the flow to transition at a sufficiently large Reynolds number. Statistics, including spectra, are compared with available experimental data. Visualizations of the flow explore the dominant and dynamically significant flow structures: the upstream shock system, the horseshoe vortices formed in the upstream separated boundary layer and the shear layer that separates from the top and sides of the cylindrical roughness element. Streamwise and spanwise planes of data were used to perform a dynamic mode decomposition (DMD) (Rowley et al., J. Fluid Mech., vol. 641, 2009, pp. 115–127; Schmid, J. Fluid Mech., vol. 656, 2010, pp. 5–28).
ESTIMATION OF THE MEMORY PARAMETER FOR NONSTATIONARY OR NONINVERTIBLE FRACTIONALLY INTEGRATED PROCESSES

We consider the asymptotic characteristics of the periodogram ordinates of a fractionally integrated process having memory parameter d≥ 0.5, for which the process is nonstationary, or d≤ -. 5, for which the process is noninvertible. Series having d outside the range (-.5,.5) may arise in practice when a raw series is modeled without preliminary consideration of the stationarity and invertibility of the series or when a wrong decision is made concerning the stationarity and invertibility of the series. We find that the periodogram of a nonstationary or noninvertible fractionally integrated process at the jth Fourier frequency ωj= 2πj/n, where n is the sample size, suffers from an asymptotic relative bias which depends on j. We also examine the impact of periodogram bias on the regression estimator of d proposed by Geweke and Porter-Hudak (1983) in finite samples. The results indicate that the bias in the periodogram ordinates can strongly affect the GPH estimator even when the number of Fourier frequencies used in the regression is allowed to depend on the length of the series. We find that data tapering and elimination of the first periodogram ordinate in the regression can reduce this bias, at the cost of an increase in variance for nonstationary series. Additionally, we find for nonstationary series that the GPH estimator is more nearly invariant to first-differencing when a data taper is used.