Miracle-dz/UniFAR-FTUs huggingface dataset:
Refractive index modification of SU-8 polymer based waveguide via fabrication parameters

This paper presents refractive index modification of SU-8 polymer based waveguide via fabrication parameters. The current biosensor market needs easy manufacturing in large quantities, low cost, small in size, easy to be used and fast response time, thus, an appropriate optical waveguide material needed to be chosen. Hence, the optical properties of SU-8 must be well understood in order to design waveguide with single-mode and strong evanescent field to realize sensitive biosensor. It is known that process parameters such as spin speed, exposure dosage and curing temperature affect the polymerization which in turn affect the optical properties especially refractive index. Due to this reason, it is the aim of this paper to investigate the effects of spin speed, exposure dosage and curing temperature on the refractive index of SU-8. This project also aims to improve the process recipe of SU-8 for waveguide fabrication, which requires high resolution and steep sidewall with minimum defect.
Guidance for conducting systematic scoping reviews

ABSTRACTReviews of primary research are becoming more common as evidence-based practice gains recognition as the benchmark for care, and the number of, and access to, primary research sources has grown. One of the newer review types is the ‘scoping review’. In general, scoping reviews are commonly used for ‘reconnaissance’ – to clarify working definitions and conceptual boundaries of a topic or field. Scoping reviews are therefore particularly useful when a body of literature has not yet been comprehensively reviewed, or exhibits a complex or heterogeneous nature not amenable to a more precise systematic review of the evidence. While scoping reviews may be conducted to determine the value and probable scope of a full systematic review, they may also be undertaken as exercises in and of themselves to summarize and disseminate research findings, to identify research gaps, and to make recommendations for the future research. This article briefly introduces the reader to scoping reviews, how they are different to systematic reviews, and why they might be conducted. The methodology and guidance for the conduct of systematic scoping reviews outlined below was developed by members of the Joanna Briggs Institute and members of five Joanna Briggs Collaborating Centres.
Compensation of Nonlinearities in ΣΔ Modulators Using Digital Assisted Analog Electronics Approach

This paper presents a Digital Signal Processing (DSP) technique to compensate nonlinearities in reconfigurable Sigma Delta (ΣΔ) Modulator. In order to design digitally enhanced transceiver, a problem of nonlinearities in these modulators should be addressed. The problem arises due to the constituent building block of ΣΔ Modulators i.e. Digital to Analog Converter (DAC). Since DAC is outside the ΣΔ signal path; the nonlinearities are not reduced by over-sampled quantization and shaping. In this paper, the nonlinearity effects of ΣΔ Modulator are captured by simulating the Signal to Noise Ratio (SNR), Signal to Noise and Distortion Ratio (SNDR), and Spurious Free Dynamic Range (SFDR). For correction, the nonlinearity affected samples are passed to a transversal filter where sample-by-sample compensation is done using the simulated ideal response as a reference. The Normalized Least Mean Square (NLMS) algorithm is employed to adjust and update the filter tap-weights. Simulation results show that for a three-tone input to 4-bit first order ΣΔ Modulator, the SNDR and SFDR improves by 24.6 dB and 34 dB respectively.
A Multi-Class Tactile Brain–Computer Interface Based on Stimulus-Induced Oscillatory Dynamics

We proposed a multi-class tactile brain–computer interface that utilizes stimulus-induced oscillatory dynamics. It was hypothesized that somatosensory attention can modulate tactile-induced oscillation changes, which can decode different sensation attention tasks. Subjects performed four tactile attention tasks, prompted by cues presented in random order and while both wrists were simultaneously stimulated: 1) selective sensation on left hand (SS-L); 2) selective sensation on right hand (SS-R); 3) bilateral selective sensation; and 4) selective sensation suppressed or idle state (SS-S). The classification accuracy between SS-L and SS-R (79.9 ± 8.7%) was comparable with that of a previous tactile BCI system based on selective sensation. Moreover, the accuracy could be improved to an average of 90.3 ± 4.9% by optimal class-pair and frequency-band selection. Three-class discrimination had an accuracy of 75.2 ± 8.3%, with the best discrimination reached for the classes SS-L, SS-R, and SS-S. Finally, four classes were classified with an accuracy of 59.4 ± 7.3%. These results show that the proposed system is a promising new paradigm for multi-class BCI.
Improving medical image retrieval through multi-descriptor similarity functions and association rules

Content-based image retrieval (CBIR) systems still face the problem of low precision of system results. To improve the precision of such systems, many image visual extractors have been developed and employed to represent the images. However, the usage of a large number of extractors and consequently, a large number of features, leads to the “dimensionality curse”, where the retrieval performance and the query accuracy diminish. In this paper, we propose a new method, called Statistical Fractal-scaled Product Metric (SFPM), to maximize the accuracy of CBIR systems and speedup similarity queries. The SFPM method combines association rule mining and the Fractal-scaled Product Metric (FPM) [4], to determine a reduced set of features and appropriate scale factors in multi-descriptor image similarity assessment. The FPM is an unsupervised method to determine a scale factor among features in multi-descriptor image similarity assessment based on the Fractal Theory. Experiments have shown that SFPM reduced the feature vector size in up to 65% and improved in up to 27% the query precision when comparing with the use of the FPM technique. The results show that the proposed method SFPM is effective in determining a reduced set of features and a near-optimal set of scale factors for the descriptors involved, and it is well-suited to improve the quality of content-based query in CBIR systems.
Long-term impacts of disturbance on nitrogen-cycling bacteria in a New England salt marsh

Recent studies on the impacts of disturbance on microbial communities indicate communities show differential responses to disturbance, yet our understanding of how different microbial communities may respond to and recover from disturbance is still rudimentary. We investigated impacts of tidal restriction followed by tidal restoration on abundance and diversity of denitrifying bacteria, ammonia-oxidizing bacteria (AOB), and ammonia-oxidizing archaea (AOA) in New England salt marshes by analyzing nirS and bacterial and archaeal amoA genes, respectively. TRFLP analysis of nirS and betaproteobacterial amoA genes revealed significant differences between restored and undisturbed marshes, with the greatest differences detected in deeper sediments. Additionally, community patterns indicated a potential recovery trajectory for denitrifiers. Analysis of archaeal amoA genes, however, revealed no differences in community composition between restored and undisturbed marshes, but we detected significantly higher gene abundance in deeper sediment at restored sites. Abundances of nirS and betaproteobacterial amoA genes were also significantly greater in deeper sediments at restored sites. Porewater ammonium was significantly higher at depth in restored sediments compared to undisturbed sediments, suggesting a possible mechanism driving some of the community differences. Our results suggest that impacts of disturbance on denitrifying and ammonia-oxidizing communities remain nearly 30 years after restoration, potentially impacting nitrogen-cycling processes in the marsh. We also present data suggesting that sampling deeper in sediments may be critical for detecting disturbance effects in coastal sediments.
An optimized kit-free method for making strand-specific deep sequencing libraries from RNA fragments

Deep sequencing of strand-specific cDNA libraries is now a ubiquitous tool for identifying and quantifying RNAs in diverse sample types. The accuracy of conclusions drawn from these analyses depends on precise and quantitative conversion of the RNA sample into a DNA library suitable for sequencing. Here, we describe an optimized method of preparing strand-specific RNA deep sequencing libraries from small RNAs and variably sized RNA fragments obtained from ribonucleoprotein particle footprinting experiments or fragmentation of long RNAs. Our approach works across a wide range of input amounts (400 pg to 200 ng), is easy to follow and produces a library in 2–3 days at relatively low reagent cost, all while giving the user complete control over every step. Because all enzymatic reactions were optimized and driven to apparent completion, sequence diversity and species abundance in the input sample are well preserved.
A Top-down Approach to Melody Match in Pitch Contour for Query by Humming (cid:63)

In this paper, a novel frame-based algorithm called recursive alignment(RA) for query-by-humming(QBH) application is presented. Compared with other approaches, RA optimizes melody alignment problems in a top-down fashion which is more capable of capturing long-distance information in human singing. Three RA variations which run much faster at the expense of less accuracy are presented, and they can be used as ﬁlters of QBH systems. A QBH system built upon RA and its variations is also described brieﬂy. The experiment results show that the proposed algorithm compares favorably with other methods we have implemented.
Relatively Socially Acceptable Prejudice Within and Between Societies

Two studies investigated the relative social acceptability of certain prejudices within a society (Study 1) and between societies (Study 2), using (less) internal motivation to control prejudice as an indicator of social acceptability. In Study 1, White British participants reported less internal motivation to control prejudice against people with schizophrenia than against Black people. In Study 2, Jamaican participants reported less internal motivation to control anti-homosexual prejudice than did either British participants or American participants. Other differences in motivation to control prejudice were smaller, absent, or at odds with this difference, indicating that differences in motivation to control anti-homosexual prejudice were not solely due to cultural differences concerning motivation to control prejudice in general. Results are discussed in terms of novel findings, relevance to the literature and possible future research.
The Impact of Local Acquisition Time on the Accuracy of Microwave Surface Soil Moisture Retrievals over the Contiguous United States

Satellite-derived soil moisture products have become an important data source for the study of land surface processes and related applications. For satellites with sun-synchronous orbits, these products are typically derived separately for ascending and descending overpasses with different local acquisition times. Moreover, diurnal variations in land surface conditions, and the extent to which they are accurately characterized in retrieval algorithms, lead to distinct systematic and random error characteristics in ascending versus descending soil moisture products. Here, we apply two independent evaluation techniques (triple collocation and direct comparison against sparse ground-based observations) to quantify (correlation-based) accuracy differences in satellite-derived surface soil moisture acquired at different local acquisition times. The orbits from different satellites are separated into two overpass categories: AM (12:00 a.m. to 11:59 a.m. Local Solar Time) and PM (12:00 p.m. to 11:59 p.m. Local Solar Time). Results demonstrate how patterns in the accuracy of AM versus PM retrieval products obtained from a variety of active and passive microwave satellite sensors vary according to land cover and across satellite products with different local acquisition times.
Coping strategies, stressful life events, problem behaviors, and depressed affect

Abstract This study investigated the relationships of coping strategies, drinking motives, and stressful life events (major, daily positive, and daily negative) on emotional and behavioral problems, and academic functioning among a sample of 1251 Icelandic youth (mean age 18.9 years). Major stressful life events and negative daily events were associated with youth maladjustment across multiple domains of functioning. Coping motives for drinking predicted both alcohol use and alcohol problems. Emotion-focused coping was a strong predictor of depressed affect, and task-oriented coping was related inversely to emotional and behavioral problems. The findings with this sample of Icelandic youth were highly similar with previous findings with an American sample by Windle and Windle (1996), and suggest the need for more focused interventions on coping strategies and maladjustment among youth.
Enhancing semantic and geographic annotation of web images via logistic canonical correlation regression

Photo community sites such as Flickr and Picasa Web Album host a massive amount of personal photos with millions of new photos uploaded every month. These photos constitute an overwhelming source of images that require effective management. There is an increasingly imperative need for semantic annotation of these web images. This paper addresses the problem by considering two kinds of annotation: semantic annotation and geographic annotation. Both are useful for image search and retrieval and for facilitating communities and social networks. This paper proposes a novel method of Logistic Canonical Correlation Regression (LCCR) for the annotation task. This model exploits the canonical correlation between heterogeneous features and an annotation lexicon of interest, and builds a generalized annotation engine based on canonical correlations in order to produce enhanced annotation for web images. We validate the effectiveness of our algorithm using a dataset of over 380,000 images tagged with GPS coordinates.
Face Recognition Using Kernel-Based NPE

Dimension reduction is an important data preparation step for face recognition. A new nonlinear dimensionality reduction method called kernel neighborhood preserving embedding (KNPE) is proposed in this paper. This new method extends the well-known neighborhood preserving embedding (NPE) from linear domain to a nonlinear domain with the kernel trick that has been used kernel-based learning algorithms. Extensive experiments have been conducted on the three well-known face databases. The experimental results show that our proposed KNPE algorithm yields much better performance than the other related algorithms.
Systemic inflammatory response depends on initial stroke severity but is attenuated by successful thrombolysis.

Initial Stroke Severity but Is Attenuated by Successful Thrombolysis. To the Editor: We read with interest the article by Audebert et al1 concerning inflammatory response in patients with acute ischemic stroke. The authors describe an association between inflammatory parameters and stroke severity, as well as stroke volume measured by cranial computed tomography (CCT) and magnetic resonance imaging. Moreover, they analyzed in more detail the subgroup of patients receiving thrombolysis and found that the inflammatory markers were significantly lower in patients with improvement after recombinant tissue plasminogen activator treatment. This is an additional important study concerning inflammation in acute stroke and supports other investigations analyzing C-reactive protein (CRP) in acute ischemic stroke.2–5 The largest study up to now was recently published by Di Napoli et al6 and could demonstrate that elevated levels of CRP were related to the risk of new cardiovascular events. In general, the findings of the recent study corroborate our results concerning the prognostic relevance of early serial CRP measurements in 127 patients with acute ischemic stroke.5 In our study, the first CRP measurement was performed within 12 hours after symptom onset (mean, 5.0 hours). The second CRP measurement was performed within 24 hours after symptom onset (mean, 19.6 hours). The third was performed 24 hours after the second measurement (mean, 43.1 hours). We also determined the lesion volume on diffusion-weighted imaging (DWI) in a subgroup of 43 patients in which the DWI was performed within 12 hours after symptom onset. However, we only observed a significant association between the third CRP value and the DWI lesion size. In contrast, Audebert et al1 described a significant association between inflammatory response and lesion size already for the first CRP measurement regarding all included patients. These differences might be explained by the use of different imaging techniques: DWI within 12 hours after symptom onset in our investigation and CCT or T2-weighted magnetic resonance imaging in the study by Audebert et al,1 as well as the later CRP determination (first CRP within 24 hours after symptom onset). Furthermore, one possible limitation of the study is the fact that follow-up imaging is not performed in every patient and that the lesion volume measured with early CCT might be underestimated. In our opinion, it would be helpful to know in which proportion of patients only a CCT was performed and how long the time interval between symptom onset, imaging, and the first CRP measurement was. In our opinion, the main novel finding of Audebert et al1 was the observation of significant lower CRP values during follow-up in patients who improve after thrombolysis.
Pedestrian Detection Using Covariance Descriptor and On-line Learning

edestrian detection is an important yet challenging problem in object classification due to flexible body pose, loose clothing and ever-changing illumination. In this paper, we employ covariance features and propose an on-line learning classifier which combines naive Bayes classifier and cascade support vector machines (SVM) to improve the precision and recall rate of pedestrian detection in still images. Experimental results show that our strategy can significantly increase both precision and recall rates in some difficult situations. Furthermore, even under the same initial training condition, our method outperforms HOG + AdaBoost in USC Pedestrian Detection Test Set, INRIA Person dataset and Penn-Fudan Database for Pedestrian Detection and Segmentation.
CBR System for Diagnosis of Patients

Microarray technology allows to measure the expression levels of thousands of genes in an experiment. The use of computational methods is fundamental in cancer research. One of the possibilities is the use of artificial intelligence techniques. Several of these techniques have been used to analyze expression arrays. This paper presents a case-based reasoning (CBR) system for automatic classification of leukemia patients from microarray data. The system incorporates novel algorithms for data mining that allow to filter and classify as well as extraction of knowledge. The system has been tested and the results obtained are presented in this paper.
Genetic susceptibility and head injury as risk factors for Alzheimer's disease among community‐dwelling elderly persons and their first‐degree relatives

We performed a community‐based study to investigate the relationship of genetic susceptibility and head injury to Alzheimer's disease(AD) in 138 patients with AD and 193 healthy elderly control subjects. Data concerning presence or absence of dementia and certain exposures were also obtained from 799 first‐degree relatives of the patients and 1,238 first‐degree relatives of the control subjects. Adjusting for age, gender, and other risk factors, the odds ratio for AD associated with head injury was 3.7 (95% confidence interval [CI], 1.4–9.7). The association was highest for head injuries that occurred after age 70. The risk of AD was higher in first‐degree relatives of patients with onset prior to age 70 than in relatives of control subjects (risk ratio [RR] = 2.5; 95% CI, 1.1–5.6). The risk was not increased for relatives of patients with onset of AD at age 70 or older. Compared with relatives without head injury, the risk of AD was increased among both head‐injured relatives of patients (RR = 5.9; 95% CI, 2.3–14.8) and head‐injured relatives of control subjects (RR = 6.9; 95% CI, 2.5–18.9). Our results are consistent with the hypothesis that severe head injury and genetic susceptibility are associated with AD. Both associations concur with current concepts regarding the role of amyloid in AD. Although we regard head injury, like genetic susceptibility, to be a putative risk factor for AD, the temporal relationship between head injury and AD warrants further investigation.
Dual gating method for eliminating motion-related inaccuracies in cardiac PET

The aim of this study was to develop gating method that eliminates both respiratory and cardiac motion-related inaccuracies in cardiac PET images utilizing two independent trigger events on PET list mode (LM) data without count loss. The method is based on an idea that two independent triggers are sent periodically into LM data based on respiratory and electrocardiogram (ECG) cycles. This enables separation of dual gated LM data into subgroups which each contain events from certain respiratory and cardiac phase. Two additional assumptions are made: amplitude of respiratory movement as well respiratory triggers are available, and only the last diastolic time interval of cardiac cycle varies due to heart rate instability. An algorithm on MatLab programming environment (Mathworks, INC) for generating dual gated phases from the LM data exported from the DVCT PET/CT scanner General Electrics was developed. The method was tested in phantom studies mimicking realistic respiratory and cardiac motions. Dual gated LM data was grouped to three respiratory phases and four cardiac phases. These dual gated phases were fed back to the database to process 12 dual gated images. Movement of cylindrical (2 mm diameter and 2 mm height) source which rotates (40 mm diameter) and moves axially (20 mm shift) was separated to 12 spatially different segments with well-defined borders on cylindrical surface. Circular images overlapped visually less than 3 mm with each other. Visually examined axially gated images overlapped from 3 to 5 mm. Dual gating method was also tested in one patient study with FDG. In coronal view the surface of myocardium of patient moved 21 mm in cranio-caudal direction when comparing end-expiratory diastolic PET image with end-inspiratory systolic PET image. We have showed that motion correction using the dual gating in cardiac studies improves the accuracy of cardiac PET images. The developed algorithm enables to divide dual gated PET data to several spatially different locations without count loss. Further studies are required to ensure feasibility of the method in human studies.
Average case analysis of k -CNF and k -DNF learning algorithms

We present average case models of algorithms for learning Conjunctive Normal Form (CNF, i.e., conjunctions of disjunctions) and Disjunctive Normal Form (DNF, i.e., disjunctions of conjunctions). Our goal is to predict the expected error of the learning algorithm as a function of the number n of training examples, averaging over all sequences of n training examples. We show that our average case models accurately predict the expected error and demonstrate that the analysis can lead to insight into the behavior of the algorithm and the factors that a ect the error.