Miracle-dz/UniFAR-FTUs huggingface dataset:
Examining Effects of Cognitive Style on Technology Acceptance Decisions

Acceptance of information technology by targeted users has been examined considerably by previous information systems (IS) research. A review of extant literature suggests a focus on the effects of important individual differences, such as attitidinal beliefs, perceptions, basic computer skills, gender, and age. Several theoretical models or frameworks prevail and have been empirically tested using various technologies and/or organizational contexts. Few studies (if any) have investigated the impact of an individual’s cognitive style on his or her technology acceptance decision. The current research discusses the relationship between cognitive style and technology acceptance and empirically tests hypotheses it suggests. We anchor our analysis using the KAI cognitive theory (Kirtons 1977) and conducts a survey study to test the effect of cognitive style on the individual’s decision on whether to accept a new technology. We synthesize relevant previous research and propose a factor model that explains or predicts technology acecptance by targeted university students. Our model encompasses the effect of cognitive styl and includes other important acceptance drivers, and is tested empirically using the evaluative respeonses to Microsoft ACCESS by 428 undergraduate students. An investigative locus of our study is comparing the responses by innvotors and adapters. We observe that cognitive style to have a significant effect on the individual’s technology acceptance decision-making, and that innovators are more likely to accept a new technology than adaptors. Using the subjects’ responses, we test the model as a whole as well as the hypotheses it suggests. Based on our data analysis, we highlight our important findings and discuss their implications to user acceptance research as well as the practices for fostering use of information technology by university students.
Minimum probability of error detection for asynchronous uplink MC-CDMA

Multi-Carrier Code Division Multiple Access (MC- CDMA) multiplexes several users using a spreading code in the frequency domain. Different chips of the same user travel on or- thogonal subcarriers and each subcarrier undergoes independent flat fading. As a result a single tap equalizer is required at the receiving end before forming the decision variable. Minimum Mean Square Error (MMSE) detector is a popular choice for this. In this paper we propose a Minimum Probability of Error (MPOE) detector for MC-CDMA uplink signals and compare the performance of this detector with the MMSE detector. Simulation results have been provided, which show the superiority of the MPOE detector over the MMSE detector in terms of Bit Error Rate (BER). This paper also studies system performance when complex Zhadoff-Chu sequences are used, which offers a low Crest Factor. Uplink MC-CDMA system based on the MPOE criterion. Perfomance of this detector has been compared with the MMSE detector. Theoretical and simulation results for the same have been presented. It can be seen that the MPOE de- tector outperforms the MMSE detector in terms of BER albeit at a slightly higher computational complexity when in weight adaptation mode. Once in the decision directed mode, both MMSE and MPOE detectors have linear complexity. Ways to reduce the computational complexity of the MPOE detector in the weight adaptation mode have been proposed in (7) for the downlink case and the same approach can be extended to the uplink case also. Another advantage of the MPOE detector over the MMSE detector is its improved resistance to the near far problem widely prevalent in mobile communication. We also discuss the performance of these detectors when using complex Zhadoff-Chu sequences to spread the users' data. These sequences have been shown to exhibit a lower crest factor (3), resulting in a reduced Peak to Average Power Ration (PAPR) problem, widely prevelant in FFT based schemes. Organization of the paper is as follows. Section II describes the signal model assumed. Section III derives the expression for the probability of error for MC-CDMA and using this expression, arrives at the MPOE detector. Simulation results are presented in Section IV. The conclusions are presented in Section V.
Time reproduction in children with ADHD and their nonaffected siblings.

OBJECTIVE Time reproduction is deficient in children with attention-deficit/hyperactivity disorder (ADHD). Whether this deficit is familial and could therefore serve as a candidate endophenotype has not been previously investigated. It is unknown whether timing deficits are also measurable in adolescent children with ADHD and nonaffected siblings. METHOD These issues were investigated in 226 children with ADHD, 188 nonaffected siblings, and 162 normal controls ages 5 to 19. Children participated in a visual and auditory time reproduction task. They reproduced interval lengths of 4, 8, 12, 16, and 20 seconds. RESULTS Children with ADHD and their nonaffected siblings were less precise than controls, particularly when task difficulty was systematically increased. Time reproduction skills were familial. Time reproduction deficits were more pronounced in younger children with ADHD than in older children. Children with ADHD could be clearly dissociated from control children until the age of 9. After this age, group differences were somewhat attenuated, but were still present. Differences between nonaffected siblings and controls were constant across the age range studied. Deficits were unaffected by modality. CONCLUSIONS Time reproduction may serve as a candidate endophenotype for ADHD, predominantly in younger children with (a genetic risk for) ADHD.
The Novel Relationship between Urban Air Pollution and Epilepsy: A Time Series Study

Background and purpose The data concerning the association between environmental pollution and epilepsy attacks are limited. The aim of this study was to explore the association between acute air pollution exposure and epilepsy attack. Methods A hospital record-based study was carried out in Xi’an, a heavily-polluted metropolis in China. Daily baseline data were obtained. Time-series Poisson regression models were applied to analyze the association between air pollution and epilepsy. Results A 10 μg/m3 increase of NO2, SO2, and O3 concentrations corresponded to 3.17% (95%Cl: 1.41%, 4.93%), 3.55% (95%Cl: 1.93%, 5.18%), and -0.84% (95%Cl: -1.58%, 0.09%) increase in outpatient-visits for epilepsy on the concurrent days, which were significantly influenced by sex and age. The effects of NO2 and SO2 would be stronger when adjusted for PM2.5. As for O3, a -1.14% (95%Cl: -1.90%, -0.39%) decrease was evidenced when adjusted for NO2. The lag models showed that the most significant effects were evidenced on concurrent days. Conclusions We discovered previously undocumented relationships between short-term air pollution exposure and epilepsy: while NO2 and SO2 were positively associated with outpatient-visits of epilepsy, O3 might be associated with reduced risk.
CAAS: an atmospheric correction algorithm for the remote sensing of complex waters

Abstract. The current SeaDAS atmospheric correction algorithm relies on the computation of optical properties of aerosols based on radiative transfer combined with a near-infrared (NIR) correction scheme (originally with assumptions of zero water-leaving radiance for the NIR bands) and several ancillary parameters to remove atmospheric effects in remote sensing of ocean colour. The failure of this algorithm over complex waters has been reported by many recent investigations, and can be attributed to the inadequate NIR correction and constraints for deriving aerosol optical properties whose characteristics are the most difficult to evaluate because they vary rapidly with time and space. The possibility that the aerosol and sun glint contributions can be derived in the whole spectrum of ocean colour solely from a knowledge of the total and Rayleigh-corrected radiances is developed in detail within the framework of a Complex water Atmospheric correction Algorithm Scheme (CAAS) that makes no use of ancillary parameters. The performance of the CAAS algorithm is demonstrated for MODIS/Aqua imageries of optically complex waters and yields physically realistic water-leaving radiance spectra that are not possible with the SeaDAS algorithm. A preliminary comparison with in-situ data for several regional waters (moderately complex to clear waters) shows encouraging results, with absolute errors of the CAAS algorithm closer to those of the SeaDAS algorithm. The impact of the atmospheric correction was also examined on chlorophyll retrievals with a Case 2 water bio-optical algorithm, and it was found that the CAAS algorithm outperformed the SeaDAS algorithm in terms of producing accurate pigment estimates and recovering areas previously flagged out by the later algorithm. These findings suggest that the CAAS algorithm can be used for applications focussing in quantitative assessments of the biological and biogeochemical properties in complex waters, and can easily be extended to other sensors such as OCM-2, MERIS and GOCI.
A regional survey of health insurance coverage for complementary and alternative medicine: current status and future ramifications.

OBJECTIVE The purpose of this survey is to evaluate the extent of health insurance coverage for complementary and alternative medicine (CAM) within one region in the United States, a study prompted by the increased utilization of CAM. DESIGN Prospective telephone interview of health insurance representatives. LOCATION A contiguous three-state area (New York, New Jersey, and Connecticut) in the North-east. RESULTS Almost all of the insurers surveyed cover chiropractic services. Less than half of the insurers reimburse acupuncture, usually for chronic pain management. Coverage for massage therapy is minimal and usually associated with physical therapy or chiropractic treatment. Other CAM services receive negligible coverage. CONCLUSIONS Current health insurance coverage of CAM is limited essentially to chiropractic medicine, acupuncture and massage therapy. Coverage of CAM is made confusing by different policies, practitioner requirements, and health plans within each carrier.
Teacher Training in Urban Settings: Inquiry, Efficacy, and Culturally Diverse Field Placements

This study describes two years of findings with a unique field experience (teaching science inquiry activities to African-American girls in a summer STEM camp) for preservice elementary education majors. It reports on the effects of the field experience, in conjunction with blocked science and mathematics methods courses, on preservice teachers’ scores on the Science Teaching Efficacy Belief Instrument (STEBI-B), as well as their rankings of their course experiences with regard to science self-efficacy.
CROSS-SPECIES MODELS OF OBSESSIVE-COMPULSIVE SPECTRUM DISORDERS

Advances in our understanding of the genetic and neural substrates of obsessivecompulsive disorder (OCD) and related spectrum disorders such as trichotillomania, as well as their characteristic behavioral and cognitive symptoms, render the search and evaluation of appropriate animal models especially timely. Such modeling in neurology and neuropsychiatry generally occurs on at least two levels: the etiological, in terms of genetics and molecular pathology, and the symptomatic, in terms of identifying suitable neurocognitive endophenotypes that encompass the range of behavioral and psychiatric manifestations of particular disorders in the
Sann: Solvent accessibility prediction of proteins by nearest neighbor method

We present a method to predict the solvent accessibility of proteins which is based on a nearest neighbor method applied to the sequence profiles. Using the method, continuous real‐value prediction as well as two‐state and three‐state discrete predictions can be obtained. The method utilizes the z‐score value of the distance measure in the feature vector space to estimate the relative contribution among the k‐nearest neighbors for prediction of the discrete and continuous solvent accessibility. The Solvent accessibility database is constructed from 5717 proteins extracted from PISCES culling server with the cutoff of 25% sequence identities. Using optimal parameters, the prediction accuracies (for discrete predictions) of 78.38% (two‐state prediction with the threshold of 25%), 65.1% (three‐state prediction with the thresholds of 9 and 36%), and the Pearson correlation coefficient (between the predicted and true RSA's for continuous prediction) of 0.676 are achieved An independent benchmark test was performed with the CASP8 targets where we find that the proposed method outperforms existing methods. The prediction accuracies are 80.89% (for two state prediction with the threshold of 25%), 67.58% (three‐state prediction), and the Pearson correlation coefficient of 0.727 (for continuous prediction) with mean absolute error of 0.148. We have also investigated the effect of increasing database sizes on the prediction accuracy, where additional improvement in the accuracy is observed as the database size increases. The SANN web server is available at http://lee.kias. re.kr/∼newton/sann/. Proteins 2012; © 2012 Wiley Periodicals, Inc.
Voluntary Compliance with Market‐Based Environmental Policy: Evidence from the U. S. Acid Rain Program

The U. S. Acid Rain Program implemented a nationwide market for electric utilities' sulfur dioxide (SO2) emissions and included voluntary compliance possibilities for nonaffected sources. I observe significant voluntary participation‐albeit with small impact on the SO2 market‐mostly from sources with counterfactual emissions below their allowance allocations. An ex post analysis suggests that costs from the resulting higher emissions outweigh savings from shifts in emissions reductions from high‐cost affected sources to low‐cost nonaffected sources. Further, utilities' voluntary participation is well explained by economic variables, which provides new evidence of cost‐effective compliance strategies and low transaction costs.
University of Miami Division of Clinical Pharmacology Therapeutic Rounds: Medications Used to Treat Anorexia in the Frail Elderly

Weight loss and anorexia are common problems that are associated with increased morbidity and mortality in the growing frail elderly population. Orexigenic agents are often prescribed in an attempt to improve appetite and lean muscle mass. Much of the data regarding their benefit comes from studies involving younger patients with illnesses such as acquired immunodeficiency syndrome or cancer. This article reviews the use and potential adverse events associated with these medications in frail elderly patients. This article also discusses the effects of the different antidepressants and antipsychotics on weight gain and appetite.
Neuropsychiatric manifestations in multiple sclerosis: correlation of fatigue and depression with disease progression

Abstract Fatigue is one of the most common disabling symptoms in multiple sclerosis (MS) with significant impact on daily life. The aim of this study is to explore the association among MS fatigue, clinical disability and depression. Fifty-seven patients were assessed by fatigue severity scale (FSS), expanded disability status scale (EDSS) and Beck depression inventory (BDI). Mean FSS score was 4·1 ± 1·6. Based on FSS scores, patients were divided into three groups: Patients with FSS score >5 (n = 10, 32%) were evaluated to present with fatigue symptoms, patients with borderline fatigue (n = 29, 50%) had an FSS score between 4 and 5 and patients with no fatigue (n = 18, 18%) had an FSS<4. When the patients were compared according to the presence of fatigue symptoms, patients with fatigue had significantly higher EDSS scores (p = 0·03). BDI evaluation revealed that 33 (57%) patients had a score 11. MS patients with fatigue showed significantly higher BDI scores when compared to patients without fatigue (p = 0·0002). A significant relationship among fatigue, disease disability and depression was observed in our study, implying the complex interplay of fatigue and depression with disability.
Cardiac Dysrhythmias Induced by Infusion of Local Anesthetics into the Lateral Cerebral Ventricle of Cats

&NA; The hypothesis that neurogenically mediated cardiac arrhythmias can be induced by the intracerebroventrical (ICV) infusion of local anesthetic solutions was tested in 11 chronically prepared, unmedicated cats. Test substances were bupivacaine (0.1%), lidocaine (0.4%), procaine (0.4 or 0.8%), or saline (pH 5.8). Cats received one or more of the test substances with two or more days between infusions. Four cats were also given bupivacaine intravenously at 1.1 and 1.4 mg/kg to help determine whether ECG changes after ICV injection of local anesthetic were due to direct cardiac action after systemic absorption. Total dose was 3.8‐7.8 × the largest ICV dose (0.7 mg). No ventricular arrhythmias were observed after the ICV infusion of saline or with intravenous doses of bupivacaine as large as 1.4 mg/kg. Only one of six cats given lidocaine ICV developed sustained, severe ventricular arrhythmias. Five of seven cats given ICV procaine developed ventricular arrhythmias. All ten cats given ICV bupivacaine developed ventricular arrhythmias. It is concluded that local anesthetics can produce neurogenically mediated ventricular arrhythmias in cats and that, of the three local anesthetics tested, bupivacaine is the most potent and effective and lidocaine is the least potent and effective.
Deep Image Homography Estimation

We present a deep convolutional neural network for estimating the relative homography between a pair of images. Our feed-forward network has 10 layers, takes two stacked grayscale images as input, and produces an 8 degree of freedom homography which can be used to map the pixels from the first image to the second. We present two convolutional neural network architectures for HomographyNet: a regression network which directly estimates the real-valued homography parameters, and a classification network which produces a distribution over quantized homographies. We use a 4-point homography parameterization which maps the four corners from one image into the second image. Our networks are trained in an end-to-end fashion using warped MS-COCO images. Our approach works without the need for separate local feature detection and transformation estimation stages. Our deep models are compared to a traditional homography estimator based on ORB features and we highlight the scenarios where HomographyNet outperforms the traditional technique. We also describe a variety of applications powered by deep homography estimation, thus showcasing the flexibility of a deep learning approach.
Disproportionate Juvenile Minority Confinement

Research regarding disproportionate minority contact (DMC) and the juvenile justice system has concentrated on the extent to which DMC exists instead of why it exists. There remains a dearth of discussion on the theoretical underpinning of the overrepresentation of minorities in the juvenile justice system. The current research addresses this theoretical gap by examining the relationship between the racial threat hypothesis and Black–White disparity in out-of-home placements in the juvenile justice system. State-level panel data were used in the comparison of juvenile arrests to placement data. The study yielded mixed support for the racial threat hypothesis, finding percentage Black to be significantly related to racial disparity in placement rates but the ratio of Black to White employment not significant. The results showing that crime-prone, urban areas exhibit higher rates of Black–White placement disproportionality indicate that some portion of the disproportionality stems from broader social inequalities.
Multi-institutional European experience of robotic thymectomy for thymoma.

BACKGROUND Robotic thymectomy for early-stage thymomas has been recently suggested as a technically sound and safe approach. However, due to a lack of data on long term results, controversy still exists regarding its oncological efficacy. In this multi-institutional series collected from four European Centres with high volumes of robotic procedures, we evaluate the results after robot-assisted thoracoscopic thymectomy for thymoma. METHODS Between 2002 and 2014, 134 patients (61 males and 73 females, median age 59 years) with a clinical diagnosis of thymoma were operated on using a left-sided (38%), right-sided (59.8%) or bilateral (2.2%) robotic approach. Seventy (52%) patients had associated myasthenia gravis (MG). RESULTS The average operative time was 146 minutes (range, 60-353 minutes). Twelve (8.9%) patients needed open conversion: in one case, a standard thoracoscopy was performed after robotic system breakdown, and in six cases, an additional access was required. Neither vascular and nerve injuries, nor perioperative mortality occurred. A total of 23 (17.1%) patients experienced postoperative complications. Median hospital stay was 4 days (range, 2-35 days). Mean diameter of resected tumors was 4.4 cm (range, 1-10 cm), Masaoka stage was I in 46 (34.4%) patients, II in 71 (52.9%), III in 11 (8.3%) and IVa/b in 6 (4.4%) cases. At last follow up, 131 patients were alive, three died (all from non-thymoma related causes) with a 5-year survival rate of 97%. One (0.7%) patient experienced a pleural recurrence. CONCLUSIONS Our data suggest that robotic thymectomy for thymoma is a technically feasible and safe procedure with low complication rates and short hospital stays. Oncological outcome appears to be good, particularly for early-stage tumors, but a longer follow-up period and more cases are necessary in order to consider this as a standard approach. Indications for robotic thymectomy for stage III or IVa thymomas are rare and should be carefully evaluated.
SWIPT with practical modulation and RF energy harvesting sensitivity

In this paper, we investigate the performance of simultaneous wireless information and power transfer (SWIPT) in a point-to-point system, adopting practical M-ary modulation. We take into account the fact that the receiver's radio-frequency (RF) energy harvesting circuit can only harvest energy when the received signal power is greater than a certain sensitivity level. For both power-splitting (PS) and time-switching (TS) schemes, we derive the energy harvesting performance as well as the information decoding performance for the Nakagami-m fading channel. We also analyze the performance tradeoff between energy harvesting and information decoding by studying an optimization problem, which maximizes the information decoding performance and satisfies a constraint on the minimum harvested energy. Our analysis shows that (i) for the PS scheme, modulations with high peak-to-average power ratio achieve better energy harvesting performance, (ii) for the TS scheme, it is desirable to concentrate the power for wireless power transfer in order to minimize the non-harvested energy caused by the RF energy harvesting sensitivity level, and (iii) channel fading is beneficial for energy harvesting in both PS and TS schemes.