Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimation of Inter-Sentiment Correlations Employing Deep Neural Network Models

This paper focuses on sentiment mining and sentiment correlation analysis of web events. Although neural network models have contributed a lot to mining text information, little attention is paid to analysis of the inter-sentiment correlations. This paper fills the gap between sentiment calculation and inter-sentiment correlations. In this paper, the social emotion is divided into six categories: love, joy, anger, sadness, fear, and surprise. Two deep neural network models are presented for sentiment calculation. Three datasets - the titles, the bodies, the comments of news articles - are collected, covering both objective and subjective texts in varying lengths (long and short). From each dataset, three kinds of features are extracted: explicit expression, implicit expression, and alphabet characters. The performance of the two models are analyzed, with respect to each of the three kinds of the features. There is controversial phenomenon on the interpretation of anger (fn) and love (gd). In subjective text, other emotions are easily to be considered as anger. By contrast, in objective news bodies and titles, it is easy to regard text as caused love (gd). It means, journalist may want to arouse emotion love by writing news, but cause anger after the news is published. This result reflects the sentiment complexity and unpredictability.
Multi-layer Pruning Framework for Compressing Single Shot MultiBox Detector

We propose a framework for compressing state-of-the-art Single Shot MultiBox Detector (SSD). The framework addresses compression in the following stages: Sparsity Induction, Filter Selection, and Filter Pruning. In the Sparsity Induction stage, the object detector model is sparsified via an improved global threshold. In Filter Selection & Pruning stage, we select and remove filters using sparsity statistics of filter weights in two consecutive convolutional layers. This results in the model with the size smaller than most existing compact architectures. We evaluate the performance of our framework with multiple datasets and compare over multiple methods. Experimental results show that our method achieves state-of-the-art compression of 6.7X and 4.9X on PASCAL VOC dataset on models SSD300 and SSD512 respectively. We further show that the method produces maximum compression of 26X with SSD512 on German Traffic Sign Detection Benchmark (GTSDB). Additionally, we also empirically show our method’s adaptability for classification based architecture VGG16 on datasets CIFAR and German Traffic Sign Recognition Benchmark (GTSRB) achieving a compression rate of 125X and 200X with the reduction in flops by 90.50% and 96.6% respectively with no loss of accuracy. In addition to this, our method does not require any special libraries or hardware support for the resulting compressed models.
Adjustments of task-set control processes: Effect of task switch frequency on task-mixing and task-switching costs

The present study tested the hypothesis that task-switch frequency triggers adjustments of task-set control processes. A mixed-task condition where task switches are frequent should promote flexibility—thus improving task-switch performance—whereas a condition where task repetitions are more expected should favour stability—thus improving task-repeat performance. In two experiments, participants performed single-task and mixed-task blocks. In mixed-task blocks, tasks varied randomly on a trial-by-trial basis. For half of the mixed-task blocks, the frequency with which the task changed was 25%, for the other half, it was 50%. Overall, depending on the task-switch frequency, performance on both task-repeat and task-switch trials was modified. Switch cost was reduced and task-repeat performance was altered by the increase in switch probability. This study demonstrates context-sensitive adjustments of task-set control processes. These results further support the view that mixing cost reflects sustained and endogenous components of cognitive control.
Provably Fast and Near-Optimum Gate Sizing

We present a new approach for the cell selection problem based on a resource sharing formulation, which is a specialization of Lagrangian relaxation with multiplicative weight updates. For the convex continuous gate sizing problem, we can prove fast polynomial running times. This theoretical result also gives some justification to previous heuristic multiplicative weight update methods. For the discrete cell selection problem, where voltage thresholds can also be chosen, we employ the new algorithm heuristically and achieve superior results on industrial benchmarks compared with one of the previously best known algorithms, and competitive results on the ISPD 2013 benchmarks. Finally, we demonstrate how the approach can be parallelized effectively achieving speed-ups of up to 16.
Virtualization as an alternative for astronomical software integration

The integration of software which requires different operating system platforms to run, is a common challenge that has to be overcome by astronomical software developers. In recent years, the possibility to execute different operating systems (OS) and programs at the same time, on a single computer by means of virtual machines, known as virtualization, has emerged as a novel tool to integrate software from different platforms. In this paper, we share our virtualization experiences and how virtualization has improved the software integration of two astronomical software projects developed at the Instituto de Astronomía, Universidad Nacional Autónoma de Mexico (IAUNAM).
Does Instruction of Oral Health Behavior for Workers Improve Work Performance?—Quasi-Randomized Trial

Oral disease can cause economic loss due to impaired work performance. Therefore, improvement of oral health status and prevention of oral disease is essential among workers. The purpose of this study was to investigate whether oral health-related behavioral modification intervention influences work performance or improves oral health behavior and oral health status among Japanese workers. We quasi-randomly separated participants into the intervention group or the control group at baseline. The intervention group received intensive oral health instruction at baseline and a self-assessment every three months. Both groups received oral examinations and answered the self-questionnaire at baseline and at one-year follow-up. At follow-up, the prevalence of subjects who use fluoride toothpastes and interdental brushes/dental floss were significantly higher in the intervention group than in the control group. Three variables (tooth brushing in workplace, using fluoride toothpaste, and experience of receiving tooth brushing instruction in a dental clinic) showed significant improvement only in the intervention group. On the other hand, work performance and oral status did not significantly change in either group. Our intensive oral health-related behavioral modification intervention improved oral health behavior, but neither work performance nor oral status, among Japanese workers.
FACTORS INFLUENCING THE ADOPTION OF NEW FEEDING TECHNOLOGY BY THE FARMER INTEREST GROUPS (FIGs) OF VELLORE DISTRICT IN TAMIL NADU

The factors influencing the new feeding technology ie. , Dairy Cattle feed computation for Farmer Interest Groups (FIGs) in Vellore District of Tamil Nadu was analysed. The study was conducted among the 150 adopters and 102 non adopters of Farmer Interest Groups belonging to 12 villages from each of the 12 blocks of Vellore district. Binary logistic regression analysis was fitted to study the factors, which influenced the adoption of new low cost cattle feed computation technology. The factors influencing adoption rate of the new feeding technology were total dairy income, animal holding and net returns per litre of milk. On the other hand the variables such as age, education, family size, experience in dairy farming and net agricultural income had no significant effect towards the adoption rate. Further, the logit model had correctly predicted the adopters and non adopters by 97 per cent.
Does Type 1 Diabetic Adolescents’ Fear of Stigmatization Predict a Negative Perception Insulin Treatment?

The purpose of this study was to investigate stigmatization, sociodemographic/diabetes-related characteristics and parents-related characteristics as predictors of a negative perception of insulin treatment in adolescents with type 1 diabetes in Turkey. The study was carried out using a cross-sectional correlation design. The research sample included 80 adolescents with type 1 diabetes who volunteered to take part. A positive perception of insulin treatment (β = −.38, p < .001), stigmatization (β = −.24, p = .013), informing others about one’s type 1 diabetes (β = .24, p = .017) and only using insulin when alone in public places (β = .19, p = .042) were significant predictors of a negative perception of insulin treatment, and these variables explained 35% of the common variance. Diabetes’ nurses should take stigmatization into account during their training and plan appropriate measures. Entrepreneurial, randomized, and controlled studies should be conducted to decrease the negative influence of stigmatization on the perception of insulin treatment in individuals with type 1 diabetes.
Molecular characterization of antimicrobial resistance in non-typhoid Salmonella from patients with bacteraemia admitted at the Aga Khan University Hospital

In Africa, non-typhoid Salmonella (NTS) infections are common and selflimiting, however, they present life-threatening complications especially inchildren and adults who are immunosuppressed. In these individuals,antimicrobial treatment maybe required. The increasing antimicrobial resistancein NTS contributes to its spread and threatens the use of commonly available andclinically important antimicrobial agents. Over the last decade or more, resistanceto commonly available antimicrobials including ampicillin, cotrimoxazole,streptomycin, chloramphenicol and tetracycline rose remarkably.This study used 116 culture confirmed isolates of NTS from bacteremicpatients admitted in the medical ward of Aga Khan University Hospital, examinedover a 12-month period, 2007. NTS isolates were identified by culture methods,and confirmed by slide agglutination tests according to Kauffmann-White schemeutilizing the Salmonella poly-O, H1 and H2 agglutination antisera. Antimicrobialsusceptibility tests were done using the disk diffusion method. Conjugationexperiment was done to determine genetic basis of resistance and polymerasechain reaction was done to detect presence of genes encoding the quinoloneresistance-determining region.Resistant isolates contained plasmids of various sizes. Some isolates hadonly one plasmid while others had up to five plasmids of varying sizes. The largeplasmids extracted ranged from 90 kb to slightly over 147 kb in size; while thesmall size plasmids ranged from about 2.1 kb to 5.6 kb. The isolates that hadplasmids all had a 43.5kb plasmid size. Some isolates in Salmonella serotype groupB and group C3 had the largest plasmid size, slightly above 147 kb. The gyrB, parCand parE had 500bp products.The resistance to ampicillin, tetracycline, cotrimoxazole andchloramphenicol was low, but there was an increase in quinolone andfluoroquinolone antimicrobials.The study concluded that, there is a decrease in resistance to conventionaldrugs of choice for treatment of invasive NTS in Kenya, but there is an increase inresistance to quinolone and flouroquinolone; and a new resistance to cefotaximeand ceftriaxone.
XML-Based Integration of the SMIILE Tool Prototype and Software Metrics Repository

An adequate system for collecting and analyzing software metric results is crucial for the successful interpretation of software characteristics during the software development process. Furthermore, the right interpretation can also identify poor quality in complex modules within software systems. However, there is a gap between raw metrics data and the right interpretation of them. In this paper, the integration of a language independent metric tool (SMIILE prototype [9]) for metrics data extraction and the software metrics repository for storing and analyzing extracted data will be described. With this integration we hope to overcome some of the difficulties that application of sofware metrics experienced in practice.
Rho family GTPases, Rac and Cdc42, control the localization of neonatal dentate granule cells during brain development

The hippocampus is generally considered as a brain center for learning and memory. We have recently established an electroporation‐mediated gene transfer method to investigate the development of neonatal dentate granule cells in vivo. Using this new technique, we introduced knockdown vectors against Rac1 small GTPase into precursors for dentate granule cells at postnatal day 0. After 21 days, Rac1‐deficient cells were frequently mispositioned between the granule cell layer (GCL) and hilus. About 60% of these mislocalized cells expressed a dentate granule cell marker, Prox1. Both the dendritic spine density and the ratio of mature spine were reduced when Rac1 was silenced. Notably, the deficient cells have immature thin processes during migrating in the early neonatal period. Knockdown of another Rac isoform, Rac3, also resulted in mislocalization of neonatally born dentate granule cells. In addition, knockdown of Cdc42, another Rho family protein, also caused mislocalization of the cell, although the effects were moderate compared to Rac1 and 3. Despite the ectopic localization, Rac3‐ or Cdc42‐disrupted mispositioned cells expressed Prox1. These results indicate that Rho signaling pathways differentially regulate the proper localization and differentiation of dentate granule cells.
Detection of Hard Exudates in Retinal Fundus Images Using Deep Learning

Diabetic Retinopathy (DR) is a retinal disorder that affects the people having diabetes mellitus for a long time (20 years). DR is one of the main reasons for the preventable blindness all over the world. If not detected early, the patient may progress to severe stages of irreversible blindness. Lack of Ophthalmologists poses a serious problem for the growing diabetes patients. It is advised to develop an automated DR screening system to assist the Ophthalmologist in decision making. Hard exudates develop when DR is present. It is important to detect hard exudates in order to detect DR in an early stage. Research has been done to detect hard exudates using regular image processing techniques and Machine Learning techniques. Here, a deep learning algorithm has been presented in this paper that detects hard exudates in fundus images of the retina.
The MANTRA campaigns - studying the stratosphere from balloons

The MANTRA (Middle Atmosphere Nitrogen Trend Assessment) series of high-altitude balloon flights is being undertaken to investigate changes in the concentrations of mid-latitude stratospheric ozone, and of nitrogen and chlorine compounds that play a role in ozone chemistry. Two balloons have been launched from Vanscoy, Saskatchewan, the first in August 1998 and the second in August 2000. Each carried a payload of instruments to measure vertical concentration profiles of stratospheric trace gases, and made observations from a float altitude of about 35 km for one day. Several of these instruments were flown 15-20 years ago and thus provide a link to historical data predating the onset of mid-latitude ozone loss. We are now preparing for two additional MANTRA flights, in 2002 and 2003. These new flights will extend the number of trace gases measured, and will include most of the previously flown instruments along with several new ones. This will enable a comparison of measurements of the same gases made by different instruments for the investigation of previously observed discrepancies and an assessment of the instruments' performance. The measurements will also be used to quantify changes in the chemical balance of the stratosphere, with a focus on changes in nitrogen oxides. In addition, the resulting data will be used for validation of several satellite instruments.
Computer Programs for Assessment of Long-Wavelength Radio Communications, Version 2.0: User's Guide and Source Files

Abstract : This document describes a revision of the Navy's Long-Wavelength Propagation Capability (LWPC) developed by the Space and Naval Warfare Systems Center, San Diego. This version of the program includes improvements to the graphics routines, increased flexibility in specification of alternative ionospheric models, and an option to execute a full-wave mode conversion model for the signal-strength calculations. This version is principally composed of FORTRAN subroutines with a few additional routines written in C to implement the graphics capabilities under the Windows 95/NT operating systems.
Similarities in Blood Mononuclear Cell Membrane Phospholipid Profiles during Malignancy

Phospholipids (PLs), key elements of cellular membranes, are regulated reciprocally with membrane proteins and can act as sensors for alterations in physiological or pathological states of cells including initiation and development of cancer. On the other hand, peripheral blood mononuclear cells (MNCs) play an important role in antitumor immune response by reacting to cancerous modifications in distant organs. In the current study, we tested the hypothesis that tumor initiation and development are reflected in the alteration pattern of the MNC PL component. We analyzed MNC membrane PL fractions in samples from healthy individuals and from patients with diverse types of cancers to reveal possible alterations induced by malignancy. Compared to healthy controls, the cancer samples demonstrated shifts in several membrane PL profiles. In particular, when analyzing cancer data pooled together, there were significantly higher levels in lysophosphatidylcholine, phosphatidylcholine, and phosphatidylethanolamine fractions, and significantly lower quantities in phosphatidylinositol, phosphatidylserine, and phosphatidic acid fractions in cancer samples compared to controls. The levels of sphingomyelins and diphosphatidylglycerols were relatively unaffected. Most of the differences in PLs were sustained during the analysis of individual cancers such as breast cancer and chronic lymphocytic leukemia. Our findings suggest the presence of a common pattern of changes in MNC PLs during malignancy.
Priming Deep Neural Networks with Synthetic Faces for Enhanced Performance

Today's most successful facial image analysis systems are based on deep neural networks. However, a major limitation of such deep learning approaches is that their performance depends strongly on the availability of large annotated datasets. In this work, we prime deep neural networks by pre-training them with synthetic face images for specific facial analysis tasks. We demonstrate that this approach enhances both the generalization performance as well as the dataset efficiency of deep neural networks. Using a 3D morphable face model, we generate arbitrary amounts of annotated data with full control over image characteristics such as facial shape and color, pose, illumination, and background. With a series of experiments, we extensively test the effect of priming deep neural networks with synthetic face examples for two popular facial image analysis tasks: face recognition and facial landmark detection. We observed the following positive effects for both tasks: 1) Priming with synthetic face images improves the generalization performance consistently across all benchmark datasets. 2) The amount of real-world data needed to achieve competitive performance is reduced by 75% for face recognition and by 50% for facial landmark detection. 3) Priming with synthetic faces is consistently superior at enhancing the performance of deep neural networks than data augmentation and transfer learning techniques. Furthermore, our experiments provide evidence that priming with synthetic faces is able to enhance performance because it reduces the negative effects of biases present in real-world training data. The proposed synthetic face image generator, as well as the software used for our experiments, have been made publicly available.
A Scalable Dual-Polarized 256-Element Ku-Band SATCOM Phased-Array Transmitter with 36.5 dBW EIRP Per Polarization

This paper presents a Ku-band dual-polarized transmit phased-array with 256-elements spaced $\lambda/\mathbf{2}$ apart at 14 GHz in the x and y directions. The design is based on 64 silicon quad-core transmit chips with 8 channels, and these chips are used to feed a $\mathbf{2x2}$ quad antennas with dual polarizations. The output PldB per channel is 12 dBm at 14 GHz. The silicon core-chips are flipped directly on a 12-layer low-cost printed circuit board (PCB) with stacked patch antennas and Wilkinson dividers. The 256-element phased-array results in a measured EIRP of 64.5 dBm and 66.5 dBm at PldB and Psat, respectively, at normal incidence, per polarization. Measured patterns show a scan region of $\pm \mathbf{60}^{\mathbf{o}}$ in E-and H-planes with low sidelobes and near-ideal patterns. The design achieves a cross polarization level $< -\mathbf{27\ dB}$ up to $\pm \mathbf{45}^{\mathbf{o}}$ and $< -\mathbf{23\ dB}$ at $\pm \mathbf{60}^{\mathbf{o}}$ scan angle, in both planes. The array is scalable to allow the construction of large-scale phased-arrays (1024 elements or more). To our knowledge, this represents state-of-the-art in Ku-band transmit phased-arrays in terms of integration level making it suitable for a low-cost mobile Ku-band SATCOM terminal.
Ultra B2 - Promoção de ligações covalentes do colágeno corneal (Corneal cross-linking) no tratamento de ceratocone: resultados preliminares

PURPOSE: To present early visual and keratometric results for corneal cross-linking with riboflavin and UV irradiation in patients with progressive keratoconus. METHODS: Twenty-five eyes of twenty patients (15 males and 5 females) with a progressive keratoconus in the previous 6 months were followed. Unaided visual acuity (UVA), best spectacle corrected visual acuity (BSCVA), spherical equivalent (SEQ), manifest cylinder, and maximal corneal curvature (max K) values were followed at 1, 3 and 6 months. All patients were submitted to corneal cross-linking using riboflavin (vitamin B2) as the photosensitizer and ultraviolet light (UV, wavelength 370 nm). Epithelium was removed with 20% alcohol, cornea was soaked with vitamin B2 for 15 min, and then irradiated with UV light for 30 min, after which a bandage contact lens (BCL) was placed. RESULTS: UVA increased after one month (from 0.15 ± 0.15 to 0.23 ± 0.20), and went on increasing at 3 and 6 months, reaching statistical significance (p=0.025 e p=0.037, respectively). BSCVA increased from 0.41 ± 0.27 to 0.49 ± 0.29 at month six, without reaching statistical significance at any time point. Progression of keratoconus stopped in all patients, in contrast with progression in all of them in the six-month period prior to the surgery. Max K decreased by more than 2 D (from 53.02 ± 8.42 to 50.88 ± 6.05 D), SEQ less that 1 D (from -3.27 ± 4.08 to -2.68 ± 3.02 D), while refractive cylinder decreased less than 0.5 D (from -2.29 ± 1.77 to -1.86 ± 0.92 D), without reaching a statistically significant difference. None of the eyes lost any line of BSCVA, 12 maintained the preoperative BSCVA, 7 gained one line, 5 gained two lines, and 1 patient gained three lines of BSCVA. CONCLUSIONS: Corneal cross-linking with riboflavin and UV light seems to be a safe (no loss of BSCVA) and effective (anatomical and optical properties maintained) procedure, which has shown to stop the progression of the keratoconus: a reduction, although not statistically significant, of the corneal curvature, spherical equivalent and refractive cylinder took place in patients where previous progression of keratoconus had been described.