Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimation of the Parameters Involved in a First-Order Autoregressive Process for Contemporary Groups

Abstract A methodology was developed for estimating the parameters involved in a first-order autoregressive process; these parameters comprise a variance component associated with the random effect, a correlation coefficient, ρ, and a residual variance. These parameters were estimated using REML with an expectation-maximization algorithm. For two single-trait analyses (milk and fat production being the dependent variable), the example chosen for the analyses was year-month—treated as random and following a first-order autoregressive process—within fixed herd. Initially, estimates failed to converge, possibly because of a time trend in the data, which was not accounted for by the model. After the random effect that follows the first-order autoregressive process was redefined as month within fixed herd-year, the parameters converged, and ρ was estimated as . 8 for milk and fat yield. Results suggest that the estimation procedures may be useful for situations when a first-order autoregressive process seems appropriate.
Reductions in risk behaviour provide the most consistent explanation for declining HIV-1 prevalence in Uganda.

OBJECTIVE To monitor the HIV-1 epidemic in Western Uganda and the possible impact of interventions. DESIGN Results from sentinel surveillance of HIV-1 seroprevalence were compared with cross-sectional serosurvey data and model simulations. METHODS Age-specific trends in HIV-1 prevalence between 1991 and 1997 amongst antenatal clinic (ANC) attenders in the town of Fort Portal, where a comprehensive AIDS control programme has been implemented since 1991, were analysed. Results were compared with outputs from a mathematical model simulating the HIV-1 epidemic in Uganda. Two scenarios were modelled: one without and one with behaviour change. Sentinel surveillance data were compared with data from a population-based HIV-1 serosurvey at the study site, which was carried out in early 1995. RESULTS Data from 3271 ANC attenders identified greater education and being single as risk factors for HIV-1 infection. A significant decrease of risk for women with secondary school education over time was observed, whereas the risk for illiterate women remained high. Among women aged 15-19 years (n = 1045) education and marital status-adjusted HIV-1 prevalence declined steadily from 32.2% in 1991 to 10.3% in 1997. For 20-24-year-old women (n = 1010) HIV-1 prevalence increased until 1993 from 19.9% to 31.7% and decreased thereafter (21.7% in 1997). These trends closely follow the prediction of the model simulation assuming behaviour change, and for 1995-1997, confidence intervals of the HIV-1 prevalence estimate exclude the model output for an uninfluenced epidemic. No clear trends of HIV-1 prevalence were found in older women (n = 1216) and comparisons with the model were ambiguous. Sentinel surveillance data at the time of the population survey closely reflected results for the female general population sample for the two younger age-groups (15-19 and 20-24 years). In contrast, pregnant women aged 25-29 years showed significantly lower rates than the population sample (20.8% versus 45.1%). CONCLUSION HIV-1 prevalence amongst ANC attenders aged 15-24 years can be used to monitor the HIV-1 epidemic in the given setting. Declining trends of HIV-1 prevalence in women aged 15-19 and 20-24 years most likely correspond to a reduced HIV-1 incidence attributable to changes in behaviour. Our data also show that sentinel surveillance data need to be age-stratified to give useful information.
Antidiscrimination Law and Minority Employment

A penetrating critique of thirty years of antidiscrimination law in the United States, this book explains why equal opportunity and affirmative action policies have failed to improve black employment since the 1964 Civil Rights Act. Farrell Bloch reviews the effects of hiring policies on minority employment and analyzes recruitment practices to reveal why current United States laws fail to address some of the most important obstacles preventing minorities from getting jobs.
SOCIAL NETWORKS AND ETHNIC NICHES: AN ECONOMETRIC ANALYSIS OF THE MANUFACTURING SECTOR IN SOUTH AFRICA

This paper analyses the link between social networks and ethnic occupational niches in the manufacturing sector in South Africa. To this end, it employs the methodology of Bertrand "et al." to minimise the omitted variable bias induced by standard approaches investigating network effects and adopts Model's concentration index to define an ethnic niche. The results indicate that 25% of the sample is employed in ethnic niches in the manufacturing sector, but that niche employment varies markedly by language group. In addition, certain language groups tend to be clustered in advantageous niches where monthly income and skill levels are relatively high, while others occupy disadvantageous niches where monthly income and skill levels are relatively low. A number of different econometric specifications find strong evidence of social network effects. This highlights the role that these networks play in forming ethnic niches in the manufacturing sector in South Africa. Copyright (c) 2010 The Author. Journal compilation (c) 2010 Economic Society of South Africa.
New differential PSL coupled resonator filters

A new parallel strip line (PSL) coupled resonator filter is developed for RF applications with differential signalling. A theory for the design of such filters is given. The correct measurement techniques of double-ended (differential) filters with single-ended network analyzers using mixed-mode S-parameters are discussed and measurements on a differential comb-line filter are presented.
Optimal invasive key-hole neurosurgery with a miniaturized 3D chip on the tip: Microendoscopic device

Objective: The goal of the performed study was to evaluate the possibility of a three-dimensional endoscope to become a combined microscope-endoscope device in one. We analyzed the ergonomy of the device, the implementation into the surgical workflow, the image quality, and the future perspectives such devices could have for the next generation of neurosurgeons. Materials and Methods: Within 6 months, 22 patients (10 male, 12 female, 20-65 age) underwent surgery in neuroaxis using the new 3D-microendoscope (ME). The new 3D-ME has (a) the ability to visualize the surgical field from out- to inside with all advantages offered by a microscope, and in the same moment, (b) its design is like a small diameter endoscope that allows stereoscopic views extracorporal, intracorporal, and panoramic “para-side” of the lesion. Results: In general, transcranial 3D-“microendoscopy” was performed in all patients with high-resolution 3D quality. No severe complications were observed intra- or postoperatively. With the addition of depth perception, the anatomic structures were well seen and observed. Conclusion: The 3D-microendoscopy is a very promising surgical concept associated with new technological developments. The surgeon is able to switch to a modern visualization instrument reaching the most optimal surgical approach without compromising safety, effectiveness, and visual information.
Embedded chip-in-flex (CIF) packages using wafer level package (WLP) with pre-applied anisotropic conductive films (ACFs)

For maximizing space efficiency and reducing process steps, embedded chip-in-flex (CIF) packages using wafer level package (WLP) with pre-applied anisotropic conductive films (ACFs) are one of the innovative packaging technology. This study was focused on the demonstration of CIF packages and their reliability evaluation. WLP was successfully performed in case of void-free ACF lamination on a 50 µm thin wafer, wafer dicing without ACF delamination, and flip-chip assembly which showed stable bump contact resistances. After flex-on-flex (FOF) assembly conditions were optimized, the CIF packages were successfully fabricated. The reliability of the packages such as high temperature/ humidity test (85 °C/85% RH), high temperature storage test (HTST), thermal cycling test (T/C) was evaluated. As a summary, the CIF packages showed excellent 85 °C/85% RH reliability.
MRI study of caudate nucleus volume and its cognitive correlates in neuroleptic-naive patients with schizotypal personality disorder.

OBJECTIVE "Cognitive" circuits anatomically link the frontal lobe to subcortical structures; therefore, pathology in any of the core components of these circuits, such as in the caudate nucleus, may result in neurobehavioral syndromes similar to those of the frontal lobe. Neuroleptic medication, however, affects the size of the caudate nucleus. For this reason, individuals diagnosed with schizotypal personality disorder offer an ideal group for the measurement of the caudate nucleus because they may be genetically related to individuals with schizophrenia but do not require neuroleptic treatment because of their less severe symptoms. METHOD Magnetic resonance imagining (MRI) scans obtained on a 1.5-T magnet with 1.5-mm contiguous slices were used to measure the caudate nucleus and lateral ventricles in 15 right-handed male subjects with schizotypal personality disorder who had no previous neuroleptic exposure and in 14 normal comparison subjects. Subjects were group matched for parental socioeconomic status, handedness, and gender. RESULTS First, the authors found significantly lower left and right absolute (13.1%, 13.2%) and relative (9.1%, 9.2%) caudate nucleus volumes in never-medicated subjects with schizotypal personality disorder than in normal subjects. Second, they found significant, inverse correlations between caudate nucleus volume and the severity of perseveration in two distinct working memory tasks in these neuroleptic-naive subjects with schizotypal personality disorder. CONCLUSIONS These data are consistent with the findings of reduced caudate nucleus volume reported in studies of neuroleptic-naive patients experiencing their first episode of schizophrenia and support the association of intrinsic pathology in the caudate nucleus with abnormalities in working memory in the schizophrenia spectrum.
Dendritic cell function at low physiological temperature

Compared with the stable core temperature, the skin temperature is lower and varies depending on ambient temperature and convection conditions. The function of DCs, which are plentiful in the skin at lower physiological temperatures, has not been reported. We show that DC performed some functions normally at 28°C, including phagocytosis and macropinocytosis. TLR‐4 signaling via MAPK pathways was delayed at 28°C but reached normal levels, which may explain the observed slower kinetics of stimulated macropinocytosis and TNF production. TLR‐4‐induced NO production was compromised severely at 28°C. Collagen degradation and migration through matrigel‐coated transwell inserts were decreased, but no effect on podosome number or DC migration through noncoated transwell filters was seen. Lowering the temperature differentially regulated functions associated with the role of DCs in adaptive immunity. LPS‐induced up‐regulation of CD86 was normal; however, CD40 up‐regulation was suppressed after TLR‐4 stimulation at 28°C. Nonactivated DC processed and presented antigen on MHC class II equally well at 28°C and 37°C. However, DCs that were loaded with antigens and stimulated with TLR ligand at 28°C were poor at activating T cells at 37°C compared with DCs that were activated and loaded with antigen at 37°C.
A Multiphase, Flexible, and Accurate Lattice for Pricing Complex Derivatives with Multiple Market Variables

With the rapid growth and the deregulation of financial markets, many complex derivatives have been structured to meet specific financial goals. Unfortunately, most complex derivatives have no analytical formulas for their prices, particularly when there is more than one market variable. As a result, these derivatives must be priced by numerical methods such as lattice. However, the nonlinearity error of lattices due to the nonlinearity of the derivative's value function could lead to oscillating prices. To construct an accurate, multivariate lattice, this study proposes a multiphase method that alleviates the oscillating problem by making the lattice match the “critical locations,” locations where nonlinearity of the derivative's value function occurs. Moreover, our lattice has the ability to model the jumps in the market variables such as regular withdraws from an investment account, which is hard to deal with analytically. Numerical results for vulnerable options, insurance contracts guaranteed minimum withdrawal benefit (GMWB), and defaultable bonds show that our methodology can be applied to the pricing of a wide range of complex financial contracts.
Topic Sentiment Analysis in Chinese News

Sentiment analysis in news is different from normal text sentiment analysis. News usually have a specific topic, a focus semantic emotion, therefore, this paper, based on the principal of using Emotion Dependency Tuple (EDT) as the basic unit of news emotion analysis, resolves topic sentiment analysis in news into three progressive sub-problem, namely, topic sentence recognition, EDT extraction and topic sentiment analysis. We use an improved TF- IDF and cross entropy to extract feature set of topics. Then, based on space vector model, calculate the topic association of a sentence and extract topic sentence. Finally, we construct topic sentence based on EDT and complete clustering of news topic sentiment. This method is evaluated using COAE2014 dataset, and differential means shows that our results close to the best results. This shows that the topic based EDT could effectively improve performance of sentiment analysis in news.
Improving the Capacity of Molecular Communication Using Enzymatic Reaction Cycles

This paper considers the capacity of a diffusion-based molecular communication link assuming the receiver uses chemical reactions. The key contribution is we show that enzymatic reaction cycles, which is a class of chemical reactions commonly found in cells consisting of a forward and a backward enzymatic reaction, can improve the capacity of the communication link. The technical difficulty in analyzing enzymatic reaction cycles is that their reaction rates are nonlinear. We deal with this by assuming that the amount of certain chemicals in the enzymatic reaction cycle is large. In order to simplify the problem further, we use singular perturbation to study a particular operating regime of the enzymatic reaction cycles. This allows us to derive a closed-form expression of the channel gain. This expression suggests that we can improve the channel gain by increasing the total amount of substrate in the enzymatic reaction cycle. By using numerical calculations, we show that the effect of the enzymatic reaction cycle is to increase the channel gain and to reduce the noise, which results in a better signal-to-noise ratio and in turn a higher communication capacity. Furthermore, we show that we can increase the capacity by increasing the total amount of substrate in the enzymatic reaction cycle.
Induction of ApL 3 Expression by Trehalose Complements the Starch-Deficient Arabidopsis Mutant adg 2-1 Lacking ApL 1 , the Large Subunit of ADP-Glucose Pyrophosphorylase 1

The disaccharide trehalose has strong effects on plant metabolism and development. In Arabidopsis seedlings, growth on trehalose-containing medium leads to an inhibition of root elongation, an accumulation of starch in the shoots, an increased activity of ADP-Glc pyrophosphorylase (AGPase), and an induction of the expression of the AGPase gene, ApL3 (A. Wingler, T. Fritzius, A. Wiemken, T. Boller, R.A. Aeschbacher [2000] Plant Physiol 124: 105–114). We used Arabidopsis mutants deficient in starch synthesis to examine whether the primary effect of trehalose was to affect carbohydrate allocation by the induction of AGPase in the photosynthetic tissue. In a mutant lacking the large AGPase subunit, ApL1, (adg2-1 mutant) growth on trehalose restored AGPase activity and led to a strong accumulation of starch in the shoots. In contrast, starch synthesis could not be induced in a mutant lacking the small AGPase subunit, ApS, (adg1-1 mutant) or in a mutant lacking plastidic phosphoglucomutase (pgm1-1 mutant). These results indicate that ApL3 can substitute for ApL1 in the AGPase complex. In addition, root elongation in the mutants, especially in the adg1-1 mutant, was partially resistant to trehalose, suggesting that the induction of ApL3 expression and the resulting accumulation of starch in the shoots were partially responsible for the effects of trehalose on the growth of wild-type plants.
Exploring mobile data on smartphones from collection to analysis

The explosive increasing data on mobile terminals has multiple perspective of value for users and service providers, such as improving user experience, resource allocation and mobile devices marketing, etc. However, it lacks massive fine scale mobile data for studies. Previous research still limited in a grain scale, making analysis in a static way to the data obtained from Internet Service Providers (ISPs). In this paper, we propose a dynamic data analysis system to explore the mobile data from collection to analysis. It achieves data collection in a fine scale with dynamic manner. Accordingly, the analysis function is also formed to adapt to dynamic increments of data. Besides, this system can be easily extended with different modules. To show these characteristics of this system, we elaborate several demonstrations of analysis results in aspects of user usage pattern. Furthermore, clustering analysis is made to some specific smartphone applications that contribute to the rapid growth of mobile data.
Neurotrophic Effects of Extracellular Guanosine

Central nervous system (CNS) astrocytes release guanosine extracellularly, that exerts trophic effects. In CNS, extracellular guanosine (GUO) stimulates mitosis, synthesis of trophic factors, and cell differentiation, including neuritogenesis, is neuroprotective, and reduces apoptosis due to several stimuli. Specific receptor-like binding sites for eGUO in the nervous system may mediate its effects through both MAP kinase and PI3-kinase signalling pathways. Extracellular guanine (eGUA) also exerts several effects; the trophic effects of eGUO are likely regulated by conversion of eGUO to eGUA by a membrane located purine nucleoside phosphorylase (ecto-PNP) and by conversion of eGUA to xanthine by guanine deaminase.
Black-White Income Inequality and Metropolitan Socioeconomic Structure

ABSTRACT: We draw on leading theories about the structural causes of racial inequality in the US to investigate inter-metropolitan differences in white and black per capita income. The analysis, which is based on a sample of 112 metropolitan areas and uses 1990 census data, examines the influence of spatial, economic, and demographic factors on black-white income inequality. Our results show severe income inequality between blacks and whites in most metropolitan areas, with black per capita income being 55% of white per capita income, on average. We find that racial educational inequality and unemployment differences were the strongest predictors of racially based income inequality. We also find that metropolitan areas that are highly ranked on a business and financial dominance hierarchy have the most interracial income inequality. However, when a metropolitan area has a high level of manufacturing employment vis-a-vis low service employment it has less income inequality. We discuss the implications of these and other findings for theories about, and public policy regarding, urban inequality.
SIDEpro: A novel machine learning approach for the fast and accurate prediction of side‐chain conformations

Accurate protein side‐chain conformation prediction is crucial for protein modeling and existing methods for the task are widely used; however, faster and more accurate methods are still required. Here we present a new machine learning approach to the problem where an energy function for each rotamer in a structure is computed additively over pairs of contacting atoms. A family of 156 neural networks indexed by amino acid and contacting atom types is used to compute these rotamer energies as a function of atomic contact distances. Although direct energy targets are not available for training, the neural networks can still be optimized by converting the energies to probabilities and optimizing these probabilities using Markov Chain Monte Carlo methods. The resulting predictor SIDEpro makes predictions by initially setting the rotamer probabilities for each residue from a backbone‐dependent rotamer library, then iteratively updating these probabilities using the trained neural networks. After convergences of the probabilities, the side‐chains are set to the highest probability rotamer. Finally, a post processing clash reduction step is applied to the models. SIDEpro represents a significant improvement in speed and a modest, but statistically significant, improvement in accuracy when compared with the state‐of‐the‐art for rapid side‐chain prediction method SCWRL4 on the following datasets: (1) 379 protein test set of SCWRL4; (2) 94 proteins from CASP9; (3) a set of seven large protein‐only complexes; and (4) a ribosome with and without the RNA. Using the SCWRL4 test set, SIDEpro's accuracy (χ1 86.14%, χ1+2 74.15%) is slightly better than SCWRL4‐FRM (χ1 85.43%, χ1+2 73.47%) and it is 7.0 times faster. On the same test set SIDEpro is clearly more accurate than SCWRL4‐rigid rotamer model (RRM) (χ1 84.15%, χ1+2 71.24%) and 2.4 times faster. Evaluation on the additional test sets yield similar accuracy results with SIDEpro being slightly more accurate than SCWRL4‐flexible rotamer model (FRM) and clearly more accurate than SCWRL4‐RRM; however, the gap in CPU time is much more significant when the methods are applied to large protein complexes. SIDEpro is part of the SCRATCH suite of predictors and available from: http://scratch.proteomics. ics.uci. edu/. Proteins 2012; © 2011 Wiley Periodicals, Inc.
Comparative Evaluation of the Datex-Ohmeda S/5 Entropy Module and the Bispectral Index® Monitor during Propofol–Remifentanil Anesthesia

Background:Different analytical concepts were introduced to quantify the changes of the electroencephalogram. The Datex-Ohmeda S/5 Entropy Module (Datex-Ohmeda Division, Instrumentarium Corp., Helsinki, Finland) was the first commercial monitor based on the entropy generating two indices, the state entropy (SE) and the response entropy (RE). The aim of the current study was to compare the accuracy of SE and RE with the Bispectral Index® monitor (BIS®; Aspect Medical Systems, Newton, MA) during propofol–remifentanil anesthesia. Methods:The authors investigated 20 female patients during minor gynecologic surgery. SE, RE, BIS, mean arterial blood pressure, heart rate, and sedation level were recorded every 20 s during stepwise increase (target-controlled infusion, 0.5 &mgr;g/ml) of propofol until the patients lost response. Five minutes after loss of response, remifentanil infusion (0.4 &mgr;g · kg−1 · min−1) was started. Spearman correlation coefficient and prediction probability were calculated for sedation levels with SE, RE, BIS, mean arterial blood pressure, and heart rate. The ability of the investigated parameters to distinguish between the anesthesia steps awake versus loss of response, awake versus anesthesia, anesthesia versus first reaction, and anesthesia versus extubation was analyzed with the prediction probability. Results:SE correlates best with sedation levels, but no significant differences of the prediction probability values among SE, RE, and BIS were found. The prediction probability for all investigated steps of anesthesia did not show significant differences among SE, RE, and BIS. SE, RE, and BIS were superior to mean arterial blood pressure and heart rate. Conclusion:SE, RE, and BIS revealed similar information about the level of sedation and allowed the authors to distinguish between different steps of anesthesia. Both monitors provided useful additional information for the anesthesiologist.