Miracle-dz/UniFAR-FTUs huggingface dataset:
Fractal analysis of retinal vessels suggests that a distinct vasculopathy causes lacunar stroke

Objectives: Lacunar strokes account for 25% of all ischemic strokes and may represent the cerebral manifestation of a systemic small vessel vasculopathy of unknown etiology. Altered retinal vessel fractal dimensions may act as a surrogate marker for diseased cerebral vessels. We used a cross-sectional study to investigate fractal properties of retinal vessels in lacunar stroke. Methods: We recruited patients presenting with lacunar stroke and patients with minor cortical stroke as controls. All patients were examined by a stroke expert and had MRI at presentation. Digital retinal photographs were taken of both eyes. Monofractal and multifractal analyses were performed with custom-written semiautomated software. Results: We recruited 183 patients. Seventeen were excluded owing to poor photographic quality, leaving 166 patients (86 with lacunar and 80 with cortical stroke). The mean age was 67.3 years (SD 11.5 years). The patients with lacunar stroke were younger but the prevalence of diabetes, hypertension, and white matter hyperintensities did not differ between the groups. The mean Dbox (monofractal dimension) was 1.42 (SD 0.02), the mean D0 (multifractal dimension) 1.67 (SD 0.03). With multivariate analysis, decreased Dbox and D0 (both representing decreased branching complexity) were associated with increasing age and lacunar stroke subtype after correcting for hypertension, diabetes, stroke severity, and white matter hyperintensity scores. Conclusions: Lacunar stroke subtype and increasing age are associated with decreased fractal dimensions, suggesting a loss of branching complexity. Further studies should concentrate on longitudinal associations with other manifestations of cerebral small vessel disease.
Software Dependencies, Work Dependencies, and Their Impact on Failures

Prior research has shown that customer-reported software faults are often the result of violated dependencies that are not recognized by developers implementing software. Many types of dependencies and corresponding measures have been proposed to help address this problem. The objective of this research is to compare the relative performance of several of these dependency measures as they relate to customer-reported defects. Our analysis is based on data collected from two projects from two independent companies. Combined, our data set encompasses eight years of development activity involving 154 developers. The principal contribution of this study is the examination of the relative impact that syntactic, logical, and work dependencies have on the failure proneness of a software system. While all dependencies increase the fault proneness, the logical dependencies explained most of the variance in fault proneness, while workflow dependencies had more impact than syntactic dependencies. These results suggest that practices such as rearchitecting, guided by the network structure of logical dependencies, hold promise for reducing defects.
Habitual sleep patterns and risk for stroke and coronary heart disease

Background Habitual sleep patterns may independently affect morbidity and mortality. However, the effect of habitual sleep patterns on the risk for stroke and coronary heart disease is unclear. Methods We evaluated the association between sleep duration and daytime somnolence (often or almost always taking daytime naps) with the incidence of stroke and coronary heart disease in a national cohort of 7,844 adults who participated in the First National Health and Nutrition Examination Survey Epidemiologic Follow-up Study. Cox proportional hazards analyses were used to examine these relationships during the 10-year follow-up. Results After adjusting for differences in age, race, gender, education, cigarette smoking, body mass index, serum cholesterol, systolic blood pressure, and diabetes mellitus, the risk for stroke was increased in persons who reported sleeping greater than 8 hours at night compared with persons who slept between 6 and 8 hours (relative risk [RR] = 1.5, 95% confidence interval [CI] = 1.1 to 2.0). Daytime somnolence was also associated with stroke incidence (RR = 1.4, 95% CI = 1.1 to 1.8). Persons who reported both greater than 8 hours of sleep and daytime somnolence were at the greatest risk for stroke (RR = 1.9, 95% CI = 1.2 to 3.1). Similar results were also found for coronary heart disease, although the results did not reach statistical significance in the multivariate adjusted model. Conclusions Habitual sleep patterns have significant effects on the risk for stroke.
Analysis of transmit-receive diversity in Rayleigh fading

We analyze the error performance of a wireless communication system employing transmit-receive diversity in Rayleigh fading. By focussing on the complex Gaussian statistics of the independent and identically distributed entries of the channel matrix, we derive a formula for the characteristic function (cf) of the maximum output signal-to-noise ratio (SNR). We use this cf to obtain a closed-form expression of the symbol error probability (SEP) for coherent binary keying. An approximate expression for the SEP when the average SNR per branch is large is also obtained. The method can be easily extended to obtain the SEP of M-ary modulation schemes.
Rare radiative exclusive B decays in soft-collinear effective theory

We consider rare radiative B decays such as $\overline{B}\ensuremath{\rightarrow}{K}^{*}\ensuremath{\gamma}$ or $\overline{B}\ensuremath{\rightarrow}\ensuremath{\rho}\ensuremath{\gamma}$ in soft-collinear effective theory (SCET) and show that the decay amplitudes are factorized to all orders in ${\ensuremath{\alpha}}_{s}$ and at leading order in ${\ensuremath{\Lambda}}_{\mathrm{QCD}}{/m}_{b}. $ By employing two-step matching, we classify the operators for radiative B decays in powers of a small parameter $\ensuremath{\lambda}(\ensuremath{\sim}\sqrt{{\ensuremath{\Lambda}}_{\mathrm{QCD}}{/m}_{b}})$ and obtain the relevant operators to order $\ensuremath{\lambda}$ in ${\mathrm{SCET}}_{\mathrm{I}}. $ These operators are constructed with or without spectator quarks including the four-quark operators contributing to annihilation and W-exchange channels. And we employ ${\mathrm{SCET}}_{\mathrm{II}}$ where the small parameter becomes of order ${\ensuremath{\Lambda}}_{\mathrm{QCD}}{/m}_{b},$ and evolve the operators in order to compute the decay amplitudes for rare radiative decays in soft-collinear effective theory. We show explicitly that the contributions from the annihilation channels and the W-exchange channels vanish at leading order in SCET. We present the factorized result for the decay amplitudes in rare radiative B decays at leading order in SCET and at next-to-leading order in ${\ensuremath{\alpha}}_{s}. $
A 12 mW wide dynamic range CMOS front end for a portable GPS receiver

At submicron channel lengths, CMOS is an attractive alternative to silicon bipolar and GaAs MESFET technologies for use in wireless receivers. A 12mW Global Positioning System (GPS) receiver front-end, comprising a low noise amplifier (LNA) and mixer implemented in a standard 0.35/spl mu/m digital CMOS process, demonstrates the aptitude of CMOS for portable wireless applications.
IDENTIFYING DRIVING FACTORS BEHIND INDIAN MONSOON PRECIPITATION USING MODEL SELECTION BASED ON DATA DEPTH

We introduce a novel one-step model selection technique for general regression estimators, and implement it in a linear mixed model setup to identify important predictors affecting Indian Monsoon precipitation. Under very general assumptions, this technique correctly identifies the set of non-zero values in the true coefficient (of length p) by comparing only p+1 models. Here we use wild bootstrap to estimate the selection criterion. Mixed models built on predictors selected by our procedure are more stable and accurate than full models across testing years in predicting median daily rainfall at a station.
Sample Subset Optimization Techniques for Imbalanced and Ensemble Learning Problems in Bioinformatics Applications

Data sampling is a widely used technique in a broad range of machine learning problems. Traditional sampling approaches generally rely on random resampling from a given dataset. However, these approaches do not take into consideration additional information, such as sample quality and usefulness. We recently proposed a data sampling technique, called sample subset optimization (SSO). The SSO technique relies on a cross-validation procedure for identifying and selecting the most useful samples as subsets. In this paper, we describe the application of SSO techniques to imbalanced and ensemble learning problems, respectively. For imbalanced learning, the SSO technique is employed as an under-sampling technique for identifying a subset of highly discriminative samples in the majority class. In ensemble learning, the SSO technique is utilized as a generic ensemble technique where multiple optimized subsets of samples from each class are selected for building an ensemble classifier. We demonstrate the utilities and advantages of the proposed techniques on a variety of bioinformatics applications where class imbalance, small sample size, and noisy data are prevalent.
Robust Subspace Mixture Models for Anomaly Detection in High Dimensions

Robust subspace mixture models for density estimation of high dimensional data with an application for anomaly detection, are described. The essence of the proposed method is as follows: First, we learn a low dimensional representation using Whitened Principal Component Analysis (WPCA), then the source multidimensional data is projected onto this subspace and the density of its data points is estimated using a robust mixture model. Finally, the likelihood of the multidimensional data points is ranked according to the learnt density. Then, a method for online model adaption and parameter identification in the original feature space that accounts for the occurrence of a specific anomaly, is described.
Communication during Prose Recall Conversations by Young and Old Dyads.

This study focused on the cooperative processes occurring during collaborative prose recall by adult dyads differing in age (young and old) and relationship (married and unacquainted). Analyses of the content of the conversations indicate that all groups produced similar proportions of story‐related and conversation‐related productions. At the beginning of the conversations, individual stimulus‐based productions were predominant. The end of the conversations were characterized by increased proportions of task discussion, particularly for married couples, and an increase in sociability/support productions by older adults, particularly older unacquainted dyads. Thus, all groups adopted the arguably superior strategy of beginning their recall conversations with an initial surge of individually recalled story information, and it was only at the end of the conversation that group differences in collaboration strategies were observed.
Analyzing Talk in ESL Peer Response Groups: Stances, Functions, and Content

This study analyzes the interaction during peer response as it occurs in an authentic writing class. Transcripts of 27 response groups are analyzed using the constant comparative method (Glaser & Strauss, 1967) to identify reader stances and determine the characteristics of these stances. We identified four categories of reader stances—authoritative, interpretive, probing, and collaborative. We then analyzed the language functions and topics discussed during the response sessions. This analysis reveals interesting differences across the four stances in five function categories (Summarize Essay, Express Intention, Give Suggestion, Give Opinion, and Give Information) and in three content categories (Writing Process, Ideas, and Audience and Purpose). We conclude that interactive peer response offers benefits to the students. However, in the probing and collaborative stances, the writer is encouraged to articulate the intended meaning of the text, thereby clarifying, expanding, and shaping meaning. These two stances therefore engage students in a fuller understanding of the writing process.
The role of the balanced scorecard in innovation management

This paper aims to study how the Balanced Scorecard is related to the process of innovation in organizations. As a contribution, the work expands the usefulness of the model, by specifying external stimuli, dynamic tension, innovation strategies and perceived innovation success. This is a descriptive study developed from a sample of 121 companies by means of a questionnaire survey. The data analysis was done with use of structural equation modelling. The findings suggest a complex long-term process, vital for companies that have their perception of success influenced by elements from outside the organization (external stimuli) and internal stimuli (dynamic voltage and innovation strategies). Innovation management becomes reckless in the absence of mechanisms that balance the tensions evidenced by indicators including conflicting temporal dimension in the long term, and the risk is greater when the perception of success is captured solely by short-term financial indicators.
Activation of human complement by the pneumococcal toxin pneumolysin

Highly purified pneumolysin (at a concentration of 10 micrograms/ml) caused significant activation of human complement, as measured by conversion of C3. Complement activation in the presence of pneumolysin was not observed in sera chelated with a combination of Mg2+ and ethylene glycol-bis(beta-aminoethyl ether)-N,N-tetraacetic acid, and activation was only slight in C2-deficient sera. This suggests that the toxin is capable of activating the classical complement pathway. Treatment of normal human serum with pneumolysin also significantly reduced its opsonic activity for Streptococcus pneumoniae.
The Acceptable Noise Level and the Pure-Tone Audiogram.

Purpose The vast majority of previous studies suggest that there is no relationship between the acceptable noise level (ANL) and pure-tone hearing thresholds reported as the average pure-tone hearing thresholds (pure-tone average). This study aims to explore (a) the relationship between hearing thresholds at individual frequencies and the ANL and (b) a measure of the slope of the audiogram and ANL. Method Sixty-three Danish adult hearing aid users participated. Assessments were pure-tone audiogram and 3 different versions of the ANL test made monaurally at 2 different sessions. Results The findings show that low-frequency hearing thresholds and the slope of the audiogram are significantly related to all versions of the ANL. Conclusion It is possible that previous studies have failed to discover a relationship between ANL and hearing thresholds due to the use of the broad 4-frequency pure-tone average. This has implications for our understanding of the ANL test.
Field study of response accuracy and decision confidence with regard to lineup composition and lineup presentation

Response accuracy with regard to lineup composition (present/absent target) and presentation (simultaneous/sequential), as well as decision confidence as a predictor and postdictor of response accuracy, was tested in a field experiment (N = 426). Overall response accuracy was 43%. It was not found significant main effects of lineup presentation or composition or a significant interaction between these variables in regard to response accuracy. By using both traditional methods of lineups’ efficiency comparison, and novel approach – ROC analysis, either procedure superiority was not revealed. Prospective confidence did not relate to response accuracy, but correct identifications were made with more retrospective confidence than were incorrect identifications. In simultaneously presented target absent lineups and sequentially presented target present lineups, correct identification resulted in a statistically significant higher level of retrospective confidence than did incorrect identifications. Participants were over-confident in their accuracy. The calibration curve, plotted for choosers, based on retrospective decision confidence was meaningful, but far from linear, while calibration curve based on prospective decision was flat. Thus the sequential lineup may not be superior to the simultaneous lineup and confidence may not be a very reliable indicator of accuracy in field setting, regardless of approach used for data analysis.
Nozizeption und Schmerz: neurophysiologische Grundlagen

Zusammenfassung: Nozizeption bezeichnet die Aufnahme, Weiterleitung und Verarbeitung schmerzauslösender Reize im peripheren und zentralen Nervensystem. Die periphere Aufnahme der Reize erfolgt an Endigungen nozizeptiver Nervenzellen der Dorsalwurzelganglien. Die meisten Nozizeptoren können durch mechanische, thermische und chemische Reize sowie durch Entzündungsmediatoren erregt werden. Die nozizeptiven Neurone projizieren über die Dorsalwurzel ins Rückenmark. Hier erfolgt die Umschaltung sowohl auf Motoneurone als auch auf aszendierende, in Richtung Gehirn projizierende Bahnen. Das aszendierende System verläuft über den Thalamus unter anderem zum limbischen System und zum Kortex. Die Verschaltung der nozizeptiven Neurone auf spinale Motoneurone ermöglicht das reflektorische Wegziehen einer Extremität bei Verletzung. Die wichtigsten Neurotransmitter des aszendierenden Systems sind Substanz P und Glutamat. Neben dem aszendierenden System verfügt der Körper über ein deszendierendes System, das der körpereigenen Schmerzunterdrückung dient. Die wichtigsten Transmitter des deszendierenden Systems sind die endogenen Opioide. Das deszendierende System kann auch durch andere körpereigene Substanzen wie Serotonin, Adrenalin und Noradrenalin aktiviert werden. Letztere spielen eine wichtige Rolle zur Schmerzunterdrückung in Stresssituationen.
Label-Free Luminescent Mesoporous Silica Nanoparticles for Imaging and Drug Delivery

We report herein a straightforward and label-free approach to prepare luminescent mesoporous silica nanoparticles. We found that calcination at 400 °C can grant mesoporous organosilica nanoparticles with strong fluorescence of great photo- and chemical stability. The luminescence is found to originate from the carbon dots generated from the calcination, rather than the defects in the silica matrix as was believed previously. The calcination does not impact the particles' abilities to load drugs and conjugate to biomolecules. In a proof-of-concept study, we demonstrated that doxorubicin (Dox) can be efficiently encapsulated into these fluorescent mesoporous silica nanoparticles. After coupled to c(RGDyK), the nanoconjugates can efficiently home to tumors through interactions with integrin αvβ3 overexpressed on the tumor vasculature. This calcination-induced luminescence is expected to find wide applications in silica-based drug delivery, nanoparticle coating, and immunofluorescence imaging.
Using neural networks as an aid in the determination of disease status: comparison of clinical diagnosis to neural-network predictions in a pedigree with autosomal dominant limb-girdle muscular dystrophy.

Studies of the genetics of certain inherited diseases require expertise in the determination of disease status even for single-locus traits. For example, in the diagnosis of autosomal dominant limb-girdle muscular dystrophy (LGMD1A), it is not always possible to make a clear-cut determination of disease, because of variability in the diagnostic criteria, age at onset, and differential presentation of disease. Mapping such diseases is greatly simplified if the data present a homogeneous genetic trait and if disease status can be reliably determined. Here, we present an approach to determination of disease status, using methods of artificial neural-network analysis. The method entails "training" an artificial neural network, with input facts (based on diagnostic criteria) and related results (based on disease diagnosis). The network contains weight factors connecting input "neurons" to output "neurons," and these connections are adjusted until the network can reliably produce the appropriate outputs for the given input facts. The trained network can be "tested" with a second set of facts, in which the outcomes are known but not provided to the network, to see how well the training has worked. The method was applied to members of a pedigree with LGMD1A, now mapped to chromosome 5q. We used diagnostic criteria and disease status to train a neural network to classify individuals as "affected" or "not affected. " The trained network reproduced the disease diagnosis of all individuals of known phenotype, with 98% reliability. This approach defined an appropriate choice of clinical factors for determination of disease status. Additionally, it provided insight into disease classification of those considered to have an "unknown" phenotype on the basis of standard clinical diagnostic methods.
Non-muscle alpha-dystroglycan is involved in epithelial development

The dystroglycan complex is a transmembrane linkage between the cytoskeleton and the basement membrane in muscle. One of the components of the complex, alpha-dystroglycan binds both laminin of muscle (laminin-2) and agrin of muscle basement membranes. Dystroglycan has been detected in nonmuscle tissues as well, but the physiological role in nonmuscle tissues has remained unknown. Here we show that dystroglycan during mouse development in nonmuscle tissues is expressed in epithelium. In situ hybridization revealed strong expression of dystroglycan mRNA in all studied epithelial sheets, but not in endothelium or mesenchyme. Conversion of mesenchyme to epithelium occurs during kidney development, and the embryonic kidney was used to study the role of alpha-dystroglycan for epithelial differentiation. During in vitro culture of the metanephric mesenchyme, the first morphological signs of epithelial differentiation can be seen on day two. Northern blots revealed a clear increase in dystroglycan mRNA on day two of in vitro development. A similar increase of expression on day two was previously shown for laminin alpha 1 chain. Immunofluorescence showed that dystroglycan is strictly located on the basal side of developing kidney epithelial cells. Monoclonal antibodies known to block binding of alpha-dystroglycan to laminin-1 perturbed development of epithelium in kidney organ culture, whereas control antibodies did not do so. We suggest that the dystroglycan complex acts as a receptor for basement membrane components during epithelial morphogenesis. It is likely that this involves binding of alpha- dystroglycan to E3 fragment of laminin-1.
Free Energy Gap and Statistical Thermodynamic Fidelity of DNA Codes

DNA nanotechnology often requires collections of oligonucleotides called "DNA free energy gap codes" that do not produce erroneous crosshybridizations in a competitive muliplexing environment. This paper addresses the question of how to design these codes to accomplish a desired amount of work within an acceptable error rate. Using a statistical thermodynamic and probabilistic model of DNA code fidelity and mathematical random coding theory methods, theoretical lower bounds on the size of DNA codes are given. More importantly, DNA code design parameters (e.g., strand number, strand length and sequence composition) needed to achieve experimental goals are identified.