Miracle-dz/UniFAR-FTUs huggingface dataset:
First THz and IR characterization of nanometer-scaled antenna-coupled InGaAs/InP Schottky-diode detectors for room temperature infrared imaging

Nanometer high performance InP Schottky detectors are scaled to IR wavelengths. The increased cutoff frequency of the Schottky detector was accomplished by both reducing its capacitance to attofarad range and also by reducing the contact resistance. The Schottky detectors were fabricated on InGaAs/InP substrates with the doping level as high as 1 x 1019 cm-2. The typical Schottky detector anode size was 0.1 x 1 μm2. Planar broadband antennas were designed for LWIR wavelengths to couple the radiation into the nanometer size detector. Several different IR antenna designs were evaluated, including complimentary square spirals, bow ties and crossed dipoles. A 6 × 7 array of antenna-coupled Schottky detectors was characterized at DC, yielding a 20 KΩ zero-bias resistance and a responsivity of 6 A/W for the entire array. The arrays were characterized at 2.5 THz, as well as in the IR (3-5μm and 10.6 μm). The current results for polarization sensitivity confirm that an antenna-coupled mechanism is responsible for the measured responsivity with the highest value measured at the THz range.
Genome-wide analysis of blood gene expression in migraine implicates immune-inflammatory pathways

Background Typical migraine is a frequent, debilitating and painful headache disorder with an estimated heritability of about 50%. Although genome-wide association (GWA) studies have identified over 40 single nucleotide polymorphisms associated with migraine, further research is required to determine their biological role in migraine susceptibility. Therefore, we performed a study of genome-wide gene expression in a large sample of 83 migraine cases and 83 non-migraine controls to determine whether altered expression levels of genes and pathways could provide insights into the biological mechanisms underlying migraine. Methods We assessed whole blood gene expression data for 17994 expression probes measured using IlluminaHT-12 v4.0 BeadChips. Differential expression was assessed using multivariable logistic regression. Gene expression probes with a nominal p value < 0.05 were classified as differentially expressed. We identified modules of co-regulated genes and tested them for enrichment of differentially expressed genes and functional pathways using a false discovery rate <0.05. Results Association analyses between migraine and probe expression levels, adjusted for age and gender, revealed an excess of small p values, but there was no significant single-probe association after correction for multiple testing. Network analysis of pooled expression data identified 10 modules of co-expressed genes. One module harboured a significant number of differentially expressed genes and was strongly enriched with immune-inflammatory pathways, including multiple pathways expressed in microglial cells. Conclusions These data suggest immune-inflammatory pathways play an important role in the pathogenesis, manifestation, and/or progression of migraine in some patients. Furthermore, gene-expression associations are measurable in whole blood, suggesting the analysis of blood gene expression can inform our understanding of the biological mechanisms underlying migraine, identify biomarkers, and facilitate the discovery of novel pathways and thus determine new targets for drug therapy.
Investigations of the isotropic etch of an ICP source for silicon microlens mold fabrication

This work investigates the isotropic etching properties of an inductively coupled plasma (ICP) etcher for masked and maskless etching steps in reference to fabrication of a silicon microlens mold. Using the described method a wide range of lens geometries and lens arrays with 100% fill factor can be achieved. The silicon etching is performed with a continuous SF6 based ICP. Analysis of the etching profile was done by SEM inspection and by optical interferometric measurements. For the masked etching step a consistent picture of the profile evolution is obtained, including a relation between the etching depth, the radius of curvature of the profile, the etching time and the size of the mask opening. For the maskless etching step, the optimal etch is purely isotropic. Within the tested process parameter range the maskless etching showed a non-isotropic behavior, which results in lens aberrations, crystal orientation dependence, poor uniformity and roughness. Generally a trade-off between the individual etching behaviors is found, but useful etching recipes can be found for a range of different lens geometries.
Exploiting social relations for sentiment analysis in microblogging

Microblogging, like Twitter and Sina Weibo, has become a popular platform of human expressions, through which users can easily produce content on breaking news, public events, or products. The massive amount of microblogging data is a useful and timely source that carries mass sentiment and opinions on various topics. Existing sentiment analysis approaches often assume that texts are independent and identically distributed (i.i.d.), usually focusing on building a sophisticated feature space to handle noisy and short texts, without taking advantage of the fact that the microblogs are networked data. Inspired by the social sciences findings that sentiment consistency and emotional contagion are observed in social networks, we investigate whether social relations can help sentiment analysis by proposing a Sociological Approach to handling Noisy and short Texts (SANT) for sentiment classification. In particular, we present a mathematical optimization formulation that incorporates the sentiment consistency and emotional contagion theories into the supervised learning process; and utilize sparse learning to tackle noisy texts in microblogging. An empirical study of two real-world Twitter datasets shows the superior performance of our framework in handling noisy and short tweets.
Bipolar charging in polydisperse polymer powders in industrial processes

The purpose of this paper is to review the previous published work and to describe some results showing bipolar charging using polymer powders in two common industrial processes: fluidized beds and pneumatic transport. A new measurement system is described for measuring the bipolar charge distribution. This consists of a vertical array of seven Faraday pail sensors, which can selectively detect different charge components based upon particle size (gravity segregation) and charge (space charge repulsion). For the experiments reported here the charge and mass values were measured for each sensor allowing the calculation of charge to mass ratio (Q/M). In addition, size distribution and surface analyses were carried out for representative samples of the powder components. Data are presented for several types of polymer powders (volume mean diameter <100 /spl mu/m), with and without extraparticulate additives. The results, in all but one of the cases reported, show that even though the net charge may be positive or negative the fine particles show a negative charge and the coarse particles positive. These results are compared under several possible hypotheses.
Detection of QTL for milk protein percentage in Italian Friesian cattle by AFLP markers and selective genotyping

We targeted quantitative trait loci (QTL) for milk protein percentage (P%) in two Italian Holstein granddaughter design families using selective genotyping in combination with high throughput amplified fragment length polymorphism (AFLP) markers. A total of 64 extreme high and low sires in respect to estimated breeding value (EBV) for P% (EBVP%) were genotyped with 25 AFLP primer combinations that revealed 305 and 291 polymorphisms in the two families. Association between markers and EBVP% was investigated by a linear model only on bands having paternal origin (105 and 96 AFLP bands in family D and S, respectively). Although no marker was significantly associated with the target trait after correction for multiple comparisons, 17 AFLP markers, significant without correction for multiple tests, were considered suggestive of the presence of a QTL. Eleven of these were successfully located on six Bos taurus (BTA) chromosomes by radiation hybrid or in-silico mapping. Ten of these mapped in the immediate neighbourhood (less than 10 cM) of already described QTL for P%. Suggestive association was verified in four regions by microsatellites analysis: one on BTA 10; one on BTA 28; and two on BTA 18. Microsatellites identified significant effects by single marker and interval mapping analyses on BTA 10 and BTA 28, while they were only suggestive of the presence of QTL on BTA 18. In summary, our results firstly indicate that AFLP markers may be used to seek QTL exploiting a selective genotyping approach in GDD, a wide used experimental design in cattle; secondly, propose two approaches for AFLP mapping, namely in-silico mapping exploiting most updated release from the bovine whole genome sequencing project, and physical mapping exploiting a panel of Bovine/Hamster Radiation Hybrids; and thirdly, provide new information on QTLs for an economic important trait in a never investigated Holstein cattle population. AFLP in combination with selective genotyping can be a useful strategy for QTL searching in minor livestock species, sometimes having large economic impact in marginal areas, where more informative markers are still poorly developed.
Climate model emulation in an integrated assessment framework: a case study for mitigation policies in the electricity sector

Abstract. We present a carbon-cycle–climate modelling framework using model emulation, designed for integrated assessment modelling, which introduces a new emulator of the carbon cycle (GENIEem). We demonstrate that GENIEem successfully reproduces the CO2 concentrations of the Representative Concentration Pathways when forced with the corresponding CO2 emissions and non-CO2 forcing. To demonstrate its application as part of the integrated assessment framework, we use GENIEem along with an emulator of the climate (PLASIM-ENTSem) to evaluate global CO2 concentration levels and spatial temperature and precipitation response patterns resulting from CO2 emission scenarios. These scenarios are modelled using a macroeconometric model (E3MG) coupled to a model of technology substitution dynamics (FTT), and represent different emissions reduction policies applied solely in the electricity sector, without mitigation in the rest of the economy. The effect of cascading uncertainty is apparent, but despite uncertainties, it is clear that in all scenarios, global mean temperatures in excess of 2 °C above pre-industrial levels are projected by the end of the century. Our approach also highlights the regional temperature and precipitation patterns associated with the global mean temperature change occurring in these scenarios, enabling more robust impacts modelling and emphasizing the necessity of focusing on spatial patterns in addition to global mean temperature change.
Therapeutic Drug Monitoring of Antiepileptic Medications

Medications used to treat and prevent seizures (antiepileptic medications, AEMs) have been commonly managed by therapeutic drug monitoring (TDM) to optimize efficacy and avoid toxicity (Neels et al., 2004; Patsalos et al., 2008). TDM has been applied mostly to the firstgeneration AEMs that have been used clinically in the United States and Europe for several decades, namely carbamazepine, ethosuximide, phenobarbital, phenytoin, primidone, and valproic acid. First-generation AEMs generally have significant inter-individual variability in their pharmacokinetics (absorption, distribution, metabolism, and excretion) and low therapeutic indices. Two randomized, controlled studies of AEM TDM showed that practitioners often apply information from TDM incorrectly (Froscher et al., 1981; Januzzi et al., 2000). Consequently, improved education of medical practitioners on TDM is important for the future. In the last twenty-five years, 14 new AEMs have entered the market in the United States and/or Europe (LaRoche & Helmers, 2004a,b; Patsalos, 1999). These drugs are sometimes characterized as secondor third-generation AEMs and include the following drugs: eslicarbazepine acetate, felbamate, gabapentin, lacosamide, lamotrigine, levetiracetam, oxcarbazepine, pregabalin, rufinamide, stiripentol, tiagabine, topiramate, vigabatrin and zonisamide. Eslicarbazepine acetate, lacosamide, rufinamide, and stiripentol have not yet been approved in the United States. In contrast to the first-generation AEMs, the newer agents generally (although not always) have wider therapeutic ranges and less adverse effects. This chapter focuses on TDM of AEMs in treatment of epilepsy, emphasizing whether the pharmacokinetics and clinical profile of the drug make TDM useful. AEMs are sometimes used to treat disorders other than epilepsy such as trigeminal neuralgia, fibromyalgia, and migraine headaches (Johannessen Landmark, 2008; LaRoche & Helmers, 2004a). There are several main challenges in TDM of AEMs (Patsalos et al., 2008). First, there are no simple diagnostic or laboratory tests for seizure disorders. The electroencephalogram (EEG) is useful for diagnosis of seizure disorders but is too labor-intensive for long-term patient observation. Second, seizures often occur unpredictably, sometimes with long periods of time between episodes. Lastly, the toxicity of AEMs can resemble neurologic disease, sometimes leading to inappropriate escalations of medication therapy even when the dose is actually too high. One of the most basic assumptions of TDM is that the concentration of drug being measured correlates with the concentration at the target site of action (e.g., brain tissue). TDM of AEMs
Compact first order temperature-compensated CMOS current reference

This paper presents a new simple compact current reference topology with first order temperature compensation, which only utilizes 5 CMOS transistors and one resistor. The proposed topology was used in order to design two current references with 1 μA and 24 μA current output with functionality proven by measurement in the temperature range from −40° C to 120°C. The chips were produced with 0.35 μm CMOS technology of AMS. Ten samples were characterized. The best achieved temperature coefficients in the −40…120 °C range are 143 ppm/°C and 166 ppm/°C for the 1 μA and 24μA references, respectively. For the commercial 0°…85°C range the best achieved temperature coefficients are 111 ppm/°C and 108 ppm/°C for the 1 μA and 24μA references. All results are obtained without the need of trimming.
Education is the strongest socio‐economic predictor of smoking in pregnancy

Abstract Aims To investigate socio‐economic disparities in smoking in pregnancy (SIP) by the mother's education, occupational class and current economic conditions. Design Cross‐sectional analysis with linked survey and register data. Setting South‐western Finland. Participants A total of 2667 pregnant women [70% of the original sample (n = 3808)] from FinnBrain, a prospective pregnancy cohort study. Measurements The outcome was smoking during the first pregnancy trimester, measured from the Finnish Medical Birth Register. Education and occupational class were linked from population registers. Income support recipiency and subjective economic wellbeing were questionnaire‐based measures of current economic conditions. These were adjusted for age, partnership status, residential area type, parental separation, parity, childhood socio‐economic background, childhood adversities (the Trauma and Distressing Events During Childhood scale) and antenatal stress (Edinburgh Postnatal Depression Scale). Logistic regressions and attributable fractions (AF) were estimated. Findings Mother's education was the strongest socio‐economic predictor of SIP. Compared with university education, adjusted odds ratios (aORs) of SIP were: 2.2 [95% confidence interval (CI) = 1.2–3.9; P = 0.011] for tertiary vocational education, 4.4 (95% CI = 2.1–9.0; P < 0.001) for combined general and vocational secondary education, 2.9 (95% CI = 1.4–6.1; P = 0.006) for general secondary education, 9.5 (95% CI 5.0–18.2; P < 0.001) for vocational secondary education and 14.4 (95% CI = 6.3–33.0; P < 0.001) for compulsory schooling. The total AF of education was 0.5. Adjusted for the other variables, occupational class and subjective economic wellbeing did not predict SIP. Income support recipiency was associated positively with SIP (aOR = 1.8; 95% CI = 1.1–3.1; P = 0.022). Antenatal stress predicted SIP (aOR = 2.0; 95% CI = 1.4–2.8; P < 0.001), but did not attenuate its socio‐economic disparities. Conclusions In Finland, socio‐economic disparities in smoking in pregnancy are attributable primarily to differences in the mother's educational level (low versus high) and orientation (vocational versus general).
A novel nucleotide oligomerisation domain 2 mutation in a family with Blau syndrome: Phenotype and function

Mutations in the nucleotide binding domain of the PRR, NOD2, are associated with the autoinflammatory diseases Blau syndrome and early-onset sarcoidosis. Current theories suggest that constitutive activation of the NOD2 pathway may be responsible for pathogenesis of these diseases. Here, we report the phenotype of a kindred with Blau syndrome caused by a novel NOD2 mutation (p.E383D). Signaling protein and cytokine expression were examined, and the results of these experiments challenge current theories of constitutive NOD2 activation in the pathophysiology of Blau syndrome.
A Modular Plug-And-Play Sensor System for Urban Air Pollution Monitoring: Design, Implementation and Evaluation

Urban air pollution has caused public concern globally because it seriously affects human life. Modern monitoring systems providing pollution information with high spatio-temporal resolution have been developed to identify personal exposures. However, these systems’ hardware specifications and configurations are usually fixed according to the applications. They can be inconvenient to maintain, and difficult to reconfigure and expand with respect to sensing capabilities. This paper aims at tackling these issues by adopting the proposed Modular Sensor System (MSS) architecture and Universal Sensor Interface (USI), and modular design in a sensor node. A compact MSS sensor node is implemented and evaluated. It has expandable sensor modules with plug-and-play feature and supports multiple Wireless Sensor Networks (WSNs). Evaluation results show that MSS sensor nodes can easily fit in different scenarios, adapt to reconfigurations dynamically, and detect low concentration air pollution with high energy efficiency and good data accuracy. We anticipate that the efforts on system maintenance, adaptation, and evolution can be significantly reduced when deploying the system in the field.
Bike-Sharing Systems under Markovian Environment

To reduce automobile exhaust pollution, traffic congestion and parking difficulties, bike-sharing systems are rapidly developed in many countries and more than 500 major cities in the world over the past decade. In this paper, we discuss a large-scale bike-sharing system under Markovian environment, and propose a mean-field matrix-analytic method in the study of bike-sharing systems through combining the mean-field theory with the time-inhomogeneous queues as well as the nonlinear QBD processes. Firstly, we establish an empirical measure process to express the states of this bike-sharing system. Secondly, we apply the mean-field theory to establishing a time-inhomogeneous MAP(t)/MAP(t)/1/K+2L+1 queue, and then to setting up a system of mean-field equations. Thirdly, we use the martingale limit theory to show the asymptotic independence of this bike-sharing system, and further analyze the limiting interchangeability as N goes to infinity and t goes to infinity. Based on this, we discuss and compute the fixed point in terms of a nonlinear QBD process. Finally, we analyze performance measures of this bike-sharing system, such as, the mean of stationary bike number at any station and the stationary probability of problematic stations. Furthermore, we use numerical examples to show how the performance measures depend on the key parameters of this bike-sharing system. We hope the methodology and results of this paper are applicable in the study of more general large-scale bike-sharing systems.
Advanced OR and AI Methods in Transportation AGENT-BASED MODELLING OF A SOCIAL DILEMMA IN MODE CHOICE BASED ON TRAVELERS ’ EXPECTATIONS AND SOCIAL LEARNING MECHANISMS

This study attempts to apply an agent-based approach to modelling travel behaviour. A social dilemma situation of travel mode choice is modelled and viewed as a complex system by considering psychological and sociological aspects, which are represented by individuals’ expectations and social learning mechanisms. We apply an imitation game in order to evolve the decision making rules of each traveller. The study reveals some informed insights for resolving the social dilemma, such as the conditions that make cooperation as a possible outcome. Some behaviour and policy implications are also discussed in this paper.
Transient Phase-Induced Nucleation in Ionic Liquid Crystals and Size-Frustrated Thickening

The crystallization behavior of amphiphilic ionic imidazolium liquid crystals has been studied with in situ small- and wide-angle X-ray scattering. We found that below the melting point four crystal phases exist. Their relative stability is checked by investigating the mutual transitions and using a heating scan. The following sequence is observed: triclinic extended bilayer > triclinic double bilayer > perpendicular double bilayer. A transient phase with a low density, which may not be stable at any temperature, is observed to serve as the nucleation mechanism for all three phases. The large size of the transient crystals is found to frustrate the layer thickening, which occurs from the double bilayer to extended bilayer transition. The competition between the thermodynamic driving force and the imposed constraints leads to the formation of wrinkles. The influence of water on the crystallization behavior is demonstrated to be indirect, which reduces the size of the crystals.
The association between health information exchange and measures of patient satisfaction

Summary Objective: Health information exchange (HIE) is the interorganizational sharing of patient information and is one of many health information technology initiatives expected to transform the U.S. healthcare system. Two outcomes expected to be improved by HIE are patient-provider communication and patient satisfaction . This analysis examined the relationship between the level of HIE engagement and these two factors in a sample of U.S. hospitals. Methods: Independent variables came from existing secondary sources and the dependent measures were from the Hospital Consumer Assessment of Healthcare Providers and Systems. The analysis included 3,278 hospitals. Using ordinary least squares regression, implemented HIE was positively associated with the percentage of patients reporting nurses communicated well and higher satisfaction. Due to the potential for selection bias, results were further explored using a propensity score analysis. Results: Hospitals that had adopted HIE, but not yet implemented saw no benefits. Hospitals’ level of HIE was not associated with the percentage of patients reporting doctors communicated well. According to propensity score corrected estimates, implemented HIE was associated with the percentage of patients who reported nurses always communicated well and who would definitely recommend the hospital. Conclusion: Few studies have examined the impact of HIE at the organizational level. This examination provides some evidence that hospitals engaging in HIE are associated with higher patient satisfaction.