Miracle-dz/UniFAR-FTUs huggingface dataset:
Investigation of Thermo-Optical Phase Modulator for Chip Based Structured Illumination Microscopy

Optical nanoscopy is an emerging field and enables super-resolution of biological cells. Among the existing nanoscopy techniques, structured illumination microscopy (SIM) is most promising candidate for live cell imaging due to its high-imaging speed, limited photo-toxicity and its suitability with most commonly used fluorophore. One of research focus of the optics group at the department is to develop photonic-chip based SIM. For SIM it is essential to perform phase stepping. This thesis involves developing a protocol for fabricating and investigation of on-chip polymer based phase modulator for SIM-on-chip. From our experimental result we can conclude that, fabrication of a polymer-based phase modulator is achievable using lift-off method. The entire fabrication process was optimized locally at UiT. The phase response of on-chip polymer based phase modulator is fast, has sufficient visibility and repeatable over time. I have also demonstrated three equidistant phase stepping as required for SIM imaging. This thermo-optics chip was designed with smaller interference angels (20° and 30°) to be able to capture the interference fringe patterns. We observed that a 60x, 1.2NA objective lens is needed to capture the interference fringes. The experimental results of fringe spacing show good agreement with the analytical results. Some limitation of using the polymer based thermos-optic phase modulation was also observed. One of them is the cross-heating. Experiment shows that for chosen chip continuous phase modulation time should be limited to 15 seconds, after 15 seconds phase shift measurements might not be reliable. After 15 seconds, both the arms of the waveguides are heated and the phase difference reduces. From the experimental results, required power for a π shift using 640 nm, TM mode is 185mW and for 561nm, TM mode it is 230mW. In TM mode phase starts to change with as little as 20mW power. The low power for TM mode also means that the chip will not be heated up so much, which is advantageous for live cell imaging. Whereas, For TE mode phase shift starts at a higher power (≈ 150mW) and total power required for one π shift is considerably more than TM mode. At higher power cross-heating happens much faster. From phase change according to the length experiment, we observed that for 1cm length arm, phase shift starts at ≈ 300mW, but the total power it takes for one π shift is approximately half of the power that is needed for 0.5 cm. Considering all these results, we can suggest that for an ideal SIM chip, one should use 640nm, TM mode in combination with shortest possible heat sensing length.
Temporal coordination of head motion in couples with history of interpersonal violence

Previous research in automated expression analysis has focused on discrete actions with little attention to their timing either within or between persons. We investigated the interpersonal coordination of rigid head motion in 11 intimate couples with a history of interpersonal violence. The couples participated in both a low-conflict task in which they were asked to discuss a neutral topic as well as a high-conflict task in which they were asked to discuss an issue that was cause for conflict. Actor-partner analysis, which explicitly models that each partner is both a cause and an effect of the other's behavior, was used to investigate differences between conditions in angular head velocities. Windowed crosscorrelation was used to model interpersonal dynamics. Angular head velocities were slower for men than for their partners. Head velocities were strongly correlated between partners, with frequent shifts in lead-lag relationships between them.
Open Access Research Article Identification of Novel Non-coding Small Rnas from Streptococcus Pneumoniae Tigr4 Using High-resolution Genome Tiling Arrays

Background: The identification of non-coding transcripts in human, mouse, and Escherichia coli has revealed their widespread occurrence and functional importance in both eukaryotic and prokaryotic life. In prokaryotes, studies have shown that non-coding transcripts participate in a broad range of cellular functions like gene regulation, stress and virulence. However, very little is known about non-coding transcripts in Streptococcus pneumoniae (pneumococcus), an obligate human respiratory pathogen responsible for significant worldwide morbidity and mortality. Tiling microarrays enable genome wide mRNA profiling as well as identification of novel transcripts at a high-resolution. Results: Here, we describe a high-resolution transcription map of the S. pneumoniae clinical isolate TIGR4 using genomic tiling arrays. Our results indicate that approximately 66% of the genome is expressed under our experimental conditions. We identified a total of 50 non-coding small RNAs (sRNAs) from the intergenic regions, of which 36 had no predicted function. Half of the identified sRNA sequences were found to be unique to S. pneumoniae genome. We identified eight overrepresented sequence motifs among sRNA sequences that correspond to sRNAs in different functional categories. Tiling arrays also identified approximately 202 operon structures in the genome. Conclusions: In summary, the pneumococcal operon structures and novel sRNAs identified in this study enhance our understanding of the complexity and extent of the pneumococcal 'expressed' genome. Furthermore, the results of this study open up new avenues of research for understanding the complex RNA regulatory network governing S. pneumoniae physiology and virulence. Background The emerging regulatory roles of RNA in prokaryotic and eukaryotic organisms are expanding the central dogma of molecular biology. While the full spectrum of cellular functions regulated by small non-coding RNA (called sRNA in prokaryotes) are yet to be established, work is going on to identify and study the role of non-coding regulatory RNAs in biological systems. In bacteria alone, more than 150 sRNAs are described [1]. The majority were identified in E. coli, and their functional characterization showed that they perform regulatory roles in sugar metabolism [2-4], iron homeostasis [5] and cell surface composition. In bacteria, sRNA also mediates post
Effect of Pigment Epithelium Derived Factor on the Expression of Glutamine Synthetase in Early Phase of Experimental Diabetic Retinopathy

Purpose: A predominant function of Müller cells is to regulate glutamate levels, but in diabetic retinopathy (DR) the function is compromised. The present study was performed to investigate the role of pigment epithelial-derived factor (PEDF) on the expression of glutamine synthetase (GS) in retina of diabetic rats. Methods: The levels of interleukin-1ß (IL-1ß), PEDF, and GS in the retina of diabetic rats were analyzed by Western blotting and real-time-RT-PCR, and glutamate concentrations in retina or vitreous body were determined by high-pressure liquid chromatography. After being treated with PEDF in diabetic rats, these proteins (IL-1ß and GS) and their mRNAs, as well as glutamate concentrations, were detected. To confirm the effect of PEDF on GS against the role of IL-1ß, treatments with IL-1ß companied with or without PEDF were performed in the eyes of normal rats. Results: Diabetes increased IL-1ß levels and decreased PEDF and GS levels in retina. Simultaneously, diabetes induced elevated glutamate concentrations in retina and vitreous body. Administration of PEDF ameliorated the characteristic changes in diabetic retinopathy. Moreover, the effect of IL-1ß on the expression of GS was inhibited by PEDF in retina of normal rats. Conclusions: PEDF increases expression of GS against the effect of IL-1ß in early diabetic retinopathy. These findings suggest that PEDF may act as an anti-inflammatory factor against decrease of GS expression in retinal Müller cells in diabetic retinopathy.
Analisis Pengaruh Kepuasan Kerja Dan Motivasi Kerja Terhadap Kinerja Guru Sekolah Teknik Menengah (STM) Cinta Rakyat Pematang Siantar

The purpose of this quantitative descriptive explanatory survey study was to analyze the influence of physiological and security needs on work motivation and to analyze the influence of work satisfaction and work motivation on the performance of the teachers of Sekolah Teknik Menengah Cinta Rakyat Pematang Siantar. The population of this study was all of the 42 teachers teaching at Sekolah Teknik Menengah Cinta Rakyat Pematang Siantar. The obtained were analyzed through multiple linear regression tests. The result of the first hypothesis analysis showed that simultaneously physiological and security needs had a significant positive influence on work motivation with determination coefficient (R) of 0.251 or 25.1%. This means that the ability of independent variables (physiological and security needs) to influence the work motivation of the teachers of Sekolah Teknik Menengah Cinta Rakyat Pematang Siantar was only 25.1%, while the remaining 74.9% were influenced by the variables which were not studied. Partially, the physiological and security needs had a significant positive influence on work motivation and the most dominant variable was security need. The result of the second hypothesis analysis showed that simultaneously work satisfaction and work motivation had a significant positive influence on teachers’ performance with determination coefficient (R ) of 0.269 or 26.9%. This means that the ability of independent variables (work satisfaction and work motivation) to influence the performance of the teachers of Sekolah Teknik Menengah Cinta Rakyat Pematang Siantar was only 26.9%, while the remaining 73.1% were influenced by the variables which were not studied. Partially, the work satisfaction and work motivation had a significant positive influence on teachers’ performance and the most dominant variable was work motivation.
Hyperbaric Oxygen Suppresses NADPH Oxidase in a Rat Subarachnoid Hemorrhage Model

Background and Purpose— One of the major contributors to brain injury after subarachnoid hemorrhage (SAH) is oxidative stress, and 1 of the major enzymatic sources of superoxide anion production in the brain is NADPH oxidase. Therefore, we studied whether hyperbaric oxygen (HBO) suppresses neuronal NADPH oxidase in a rat model of SAH. Methods— Eighty-three Sprague-Dawley male rats were assigned to sham, SAH, and SAH treated with HBO groups. SAH was induced by endovascular perforation. HBO (2.8 atmospheres absolutes for 2 hours) was started at 1 hour after perforation. Rats were euthanized at 6 or 24 hours, and brains were collected for histology, biochemistry, and molecular biology studies including NADPH oxidase activity, gp91phox mRNA expression, and lipid peroxidation assays. Mortality and neurological scores were evaluated. Results— We observed an increased neuronal immunoreactivity of gp91phox at 24 hours after SAH. The upregulation of gp91phox mRNA was associated with increased oxidative stress. HBO decreased NADPH oxidase expression, activity, and the level of oxidative stress at 24 hours after SAH. HBO reduced neuronal injury and improved functional performance throughout the observation period. Conclusion— HBO suppresses NADPH oxidase and oxidative stress in cerebral tissues at 24 hours after SAH.
Core evidence place in therapy summary for bevacizumab in NSCLC

Introduction: Lung cancer is the leading cause of cancer-related mortality. Platinum-based chemotherapy is the usual first-line treatment for advanced nonsmall cell lung cancer (NSCLC), although an efficacy plateau has been reached with this approach. Bevacizumab is a recombinant, humanized, monoclonal antibody to vascular endothelial growth factor, which inhibits tumor angiogenesis and is being evaluated as a different mechanism to improve outcomes in patients with stage IIIB/stage IV (metastatic) NSCLC. Aims: To review the emerging evidence for the potential use of bevacizumab in stage IIIB/IV NSCLC. Evidence review: Adding bevacizumab to carboplatin plus paclitaxel improves response rates and significantly prolongs time to disease progression, which translates into a significant extension of overall survival (median 2.3 months in one key study). Low levels of intracellular adhesion molecule-1 are associated with better response. Preliminary evidence suggests that combining bevacizumab with erlotinib could improve outcomes in patients relapsing following platinum-based chemotherapy. Episodes of bleeding (particularly pulmonary hemorrhage) are the predominant adverse events associated with bevacizumab, probably a result of tumor disintegration. There is limited evidence that the high acquisition cost of bevacizumab unfavorably affects assessment of its cost effectiveness, although there are few other treatment options in these patients with poor prognosis. Place in therapy: The encouraging results obtained with bevacizumab in patients with NSCLC are leading to its adoption in some treatment guidelines. Emerging evidence indicates improved outcomes when bevacizumab is added to carboplatin/paclitaxel in previously untreated patients with NSCLC, and when used with erlotinib in patients who have relapsed following platinum-based chemotherapy.
HOCOMOCO: a comprehensive collection of human transcription factor binding sites models

Transcription factor (TF) binding site (TFBS) models are crucial for computational reconstruction of transcription regulatory networks. In existing repositories, a TF often has several models (also called binding profiles or motifs), obtained from different experimental data. Having a single TFBS model for a TF is more pragmatic for practical applications. We show that integration of TFBS data from various types of experiments into a single model typically results in the improved model quality probably due to partial correction of source specific technique bias. We present the Homo sapiens comprehensive model collection (HOCOMOCO, http://autosome.ru/HOCOMOCO/, http://cbrc.kaust.edu.sa/hocomoco/) containing carefully hand-curated TFBS models constructed by integration of binding sequences obtained by both low- and high-throughput methods. To construct position weight matrices to represent these TFBS models, we used ChIPMunk software in four computational modes, including newly developed periodic positional prior mode associated with DNA helix pitch. We selected only one TFBS model per TF, unless there was a clear experimental evidence for two rather distinct TFBS models. We assigned a quality rating to each model. HOCOMOCO contains 426 systematically curated TFBS models for 401 human TFs, where 172 models are based on more than one data source.
Task-driven sampling of attributed networks

This paper introduces new techniques for sampling attributed networks to support standard Data Mining tasks. The problem is important for two reasons. First, it is commonplace to perform data mining tasks such as clustering and classification of network attributes (attributes of the nodes, including social media posts). Furthermore, the extraordinarily large size of real-world networks necessitates that we work with a smaller graph sample. Second, while random sampling will provide an unbiased estimate of content, random access is often unavailable for many networks. Hence, network samplers such as Snowball sampling, Forest Fire, Random Walk, Metropolis-Hastings Random Walk are widely used; however, these attribute-agnostic samplers were designed to capture salient properties of network structure, not node content. The latter is critical for clustering and classification tasks. There are three contributions of this paper. First, we introduce several attribute-aware samplers based on Information Theoretic principles. Second, we prove that these samplers have a bias towards capturing new content, and are equivalent to uniform sampling in the limit. Finally, our experimental results over large real-world datasets and synthetic benchmarks are insightful: attribute-aware samplers outperform both random sampling and baseline attribute-agnostic samplers by a wide margin in clustering and classification tasks.
Using box structures with the Z notation

The box structure method (BSM) provides a framework that can be used to introduce formality into the requirements specification stage of software development. A method of requirements specification is presented which integrates the Z notation with BSM. The requirements specification is confined to the top level black box specification and the corresponding top level state box specification. The authors describe criteria for good requirements specification and explain advantages of the integrated method for achieving them. Summary introductions are given to both BSM and Z followed by an examination of the relationship between the two methods. They explain the integrated method and illustrate it using a simple birthday reminder system. Finally, they discuss issues that have emerged from the use of this method and indicate areas for future research. <<ETX>>
OntoEDS: Protecting Energy Delivery Systems by Collaboratively Analyzing Security Requirements

Sophisticated attacks on Energy Delivery Systems (EDS) are no longer theoretical, and instead pose a serious threat to American economies. The EDS community has worked collaboratively to develop security requirements to protect EDS against such attacks, but the documents that contain these requirements are often dense, ambiguous and difficult for humans to understand, resulting in highly subjective security implementa- tions that reduce their effectiveness. Therefore, there is a need for a methodology that models and visualizes security requirements enabling quick retrieval, understanding and analysis, along with the evaluation and evolution of the implementations of such requirements within EDS. With this in mind, this paper presents a collaborative tool called OntoEDS that provides a well- defined representation of security requirements within ontological representations, and a set of ontology exploration techniques to analyze and evaluate the implementations of such requirements against the current attack surface. We also present a case study exemplifying the usefulness of our tool surrounding the series of EDS attacks that occurred in Ukraine in 2015 and 2016.
Power and area-efficient adaptive equalization at microwave frequencies

We present a low power analog adaptive equalization technique suitable for combating inter-symbol-interference at very high data rates. The proposed technique, which we term the lumped parameter equalizer, addresses several of the problems associated with conventional microwave equalizers based on the tapped delay line structure. The theory is given, and simulation results comparing it with the performance of ideal tapped delay line filters are shown. Circuit implementations are discussed, along with the effect of nonidealities on equalizer performance.
A Temporal Masking Technique and its Performace Analysis for Audio Watermarking

Echo hiding embeds watermark information bit in the delay time. For imperceptibility, we propose a temporal masking technique to match the psycho acoustic model. Based on the spreading property of PN sequences and expansions of logarithm and binomial, two asymptotic detection gains are derived depending on the echo gain is small or large. This performance analysis of the detection gain explains the improvement with an increment of a small echo gain and the degradation when a large echo gain is raised even higher. Computer simulation confirms our analysis.
An algorithm for processing and analysis of Gas Chromatography-Mass Spectrometry (GC-MS) signals for early detection of Parkinson's disease

Parkinson's disease (PD) is one of the most prevalent neurodegenerative disorders, affecting about 1% of the people over 65. Early detection of PD is important as it enables slowing or stopping its progression. Analyzing Volatile Organic Compounds (VOCs) in blood, which may be involved in biochemical pathways specific to the disease, may reveal biomarkers that could potentially assist in early detection of PD stage and progression. VOCs can be detected by using the Solid-Phase Micro Extraction (SPME) technique, together with Gas-Chromatograph Mass Spectra (GC-MS). The output of the GC-MS is a signal with multiple peaks, where the locations of the peaks and their areas represents the various VOCs and their corresponding concentrations. In this study we have developed an algorithm for automatic analysis and processing of GC-MS signals based on VOCs in blood samples. The algorithm detects all peaks (local maxima) in this signal, with the corresponding amplitude and retention time, and computes the areas of the peaks. The algorithm aligns and groups all peaks from different samples of a similar retention time, and normalizes the areas according to internal standard area. Based on the amplitude and area, only peaks whose peak-to-noise ratio is high enough and which are substantially different from blank peaks are considered for further analysis. Two groups of rats were considered for the experimental evaluation of the algorithm: a control group of sham rats (n=9), and a second group of pre-Parkinsonian rats (n=10). A supervised learning algorithm was employed on a partial set of features to evaluate the possibility of using the areas of the peaks in order to predict whether a sample was from an intact or an impaired rat. A 6-d feature vector was constructed using the areas of peaks with large difference between groups. Using a leave-one-out cross-validation, a correct identification rate of 84.2% was achieved. Although these results are preliminary, they may indicate the potential of using the GCMS signal obtained from blood VOCs for discriminating between intact and PD induced samples.
Noninvasive molecular imaging of small living subjects using Raman spectroscopy

Molecular imaging of living subjects continues to rapidly evolve with bioluminescence and fluorescence strategies, in particular being frequently used for small-animal models. This article presents noninvasive deep-tissue molecular images in a living subject with the use of Raman spectroscopy. We describe a strategy for small-animal optical imaging based on Raman spectroscopy and Raman nanoparticles. Surface-enhanced Raman scattering nanoparticles and single-wall carbon nanotubes were used to demonstrate whole-body Raman imaging, nanoparticle pharmacokinetics, multiplexing, and in vivo tumor targeting, using an imaging system adapted for small-animal Raman imaging. The imaging modality reported here holds significant potential as a strategy for biomedical imaging of living subjects.
A Framework of Adaptive Brain Computer Interfaces

Stationarity is often found in session-to-session transfers of Brain Computer Interfaces (BCIs). To cope with the problem, a framework based on Common Spatial Patterns (CSP), Linear Discriminant Analysis (LDA), and covariate shift adaptation methods is proposed. Covariate shift adaptation is an effective method which can adapt to the testing sessions without the need for labeling the testing session data. This framework has been applied on one electrocorticogram (ECoG) dataset and one Electroencephalogram (EEG) dataset from BCI Competition III. Despite the different characteristics of ECoG and EEG, non-stationarity appeared in both datasets. Results showed that the proposed framework compares favorably with those methods used in the BCI Competition, revealing the effectiveness of covariate shift adaptation in tackling the nonstationarity in Brain Computer Interfaces.