Miracle-dz/UniFAR-FTUs huggingface dataset:
Clinical usefulness of watch-PAT for assessing the surgical results of obstructive sleep apnea syndrome.

OBJECTIVE This study aimed to assess the accuracy and clinical efficacy of a wrist-worn device that is based on peripheral arterial tonometry (watch-PAT) to evaluate the surgical results of obstructive sleep apnea (OSA) syndrome subjects. STUDY DESIGN AND METHOD Thirty-five subjects who were diagnosed with OSA and underwent sleep surgeries such as septoplasty, tonsillectomy, or uvuloplasty to correct their airway collapse, participated in this study; the watch-PAT-derived respiratory disturbance index (RDI), apnea and hypopnea index (AHI), lowest oxygen saturation, and valid sleep time were measured after the sleep surgery. RESULTS The present study showed that RDI (32.8 ± 10.7 vs. 14.8 ± 7.5), AHI (30.3 ± 8.6 vs. 13.4 ± 8.2 events/h), lowest oxygen saturation (78.2% ± 8.4% vs. 90.5% ± 7.1%), and valid sleep time (329.1 ± 47.2 min and a postoperative value of 389.1 ± 50.1 min) recovered to within a normal range after surgery in 28 subjects. In addition, good agreement was found between watch-PAT-derived factors and visual analogue scales for changes in subjective symptoms, such as snoring, apnea, and daytime somnolence. Seven of the 35 subjects showed no improvement for their subjective symptoms and complained of snoring and apnea after surgery. We found that the RDI and AHI of those 7 subjects were not reduced, and the changes between pre- and postoperative values which were measured with watch-PAT were minimal. Their postoperative lowest oxygen saturation and valid sleep time were not elevated per the watch-PAT. The results support a strong correlation between the findings from watch-PAT and improved symptoms after surgical correction of an airway collapse. CONCLUSIONS Our study provides evidence that the factors measured by the watch-PAT might be reliable indicators of symptomatic changes in OSA subjects after sleep surgery and also shows that the watch-PAT is a highly sensitive portable device for estimating treatment results in OSA.
Analysis of Subthreshold Current Reset Noise in Image Sensors

To discuss the reset noise generated by slow subthreshold currents in image sensors, intuitive and simple analytical forms are derived, in spite of the subthreshold current nonlinearity. These solutions characterize the time evolution of the reset noise during the reset operation. With soft reset, the reset noise tends to mkT/2CPD when t→∞, in full agreement with previously published results. In this equation, CPD is the photodiode (PD) capacitance and m is a constant. The noise has an asymptotic time dependence of t−1, even though the asymptotic time dependence of the average (deterministic) PD voltage is as slow as logt. The flush reset method is effective because the hard reset part eliminates image lag, and the soft reset part reduces the noise to soft reset level. The feedback reset with reverse taper control method shows both a fast convergence and a good reset noise reduction. When the feedback amplifier gain, A, is larger, even small value of capacitance, CP, between the input and output of the feedback amplifier will drastically decrease the reset noise. If the feedback is sufficiently fast, the reset noise limit when t→∞, becomes mkT(CPD+CP1)22q2A(CPD+(1+A)CP) in terms of the number of electron in the PD. According to this simple model, if CPD = 10 fF, CP/CPD = 0.01, and A = 2700 are assumed, deep sub-electron rms reset noise is possible.
Region-of-interest tomography using multiresolution interpolation

The wavelet localization technique has been applied to region-of-interest tomography. It achieves a significant saving in the required projections if only a small region of a tomographic image is of interest. We first show that, with the same sampling requirement, a simple interpolation scheme applied on the samples can give a result at least as good as that achieved by using the wavelet localization approach. It means that we can use a much simpler approach to achieve the same performance. Second, we propose a new sampling scheme such that the required projections of each angle are further reduced in a multiresolution form. With this sampling scheme, more than 84% of projections are saved to reconstruct a 32/spl times/32 pixels region of a 256/spl times/256 pixels image. The signal-to-error ratio of the reconstructed region-of-interest is over 50 dB as compare with the case of full projection. Moreover, we also investigate the effect of applying the interlaced sampling scheme on the proposed method. It is seen that a further reduction in the sampling requirement can be achieved although a slight decrease in signal-to-error ratio may result.
Optimizing the Performance Evaluation of Robotic Arms with the Aid of Particle Swarm Optimization

In this modern world, robotic evaluation plays a most important role. In secure distance, this leads the humans to execute insecure task. To acquire an effective result, the system which makes the human task easier should be taken care of and the holdup behind the system should be eradicated. Only static parameters are considered and such parameters are not enough to obtain optimized value in existing work. For consecutively attaining optimized value in our previous work, we focused on both static and dynamic parameters in the robotic arm gearbox model. Now, a genetic algorithm is utilized and the result obtained is greater than the existing work. On the other hand, to attain an effective result the genetic algorithm itself is not enough since it takes massive time for computation process and the result obtained in this computation is not as much closer to the true value. By eliminating all those aforementioned issues, a proper algorithm needs to be utilized in order to achieve an efficient result than the existing and our previous works. In this paper, we anticipated to suggest a Particle Swarm Optimization technique that reduce the computation time as well as make the output result as much closer to the true value (i.e.,) experimentally obtained value.
A Prothrombinase-based Assay for Detection of Resistance to Activated Protein C

Summary In this paper we present a new method for the detection of resistance to activated protein C (APC) that is based on direct measurement of the effect of APC on the cofactor activity of plasma factor Va. The factor V present in a diluted plasma sample was activated with thrombin and its sensitivity towards APC was subsequently determined by incubation with phospholipids and APC. The loss of factor Va cofactor activity was quantified in a prothrombinase system containing purified prothrombin, factor Xa and phospholipid vesicles and using a chromogen-ic assay for quantitation of thrombin formation. The reaction conditions were optimized in order to distinguish normal, heterozygous and homozygous APC-resistant plasmas. Maximal differences in the response of these plasmas towards APC were observed when factor Va was inactivated by APC in the absence of protein S and when the cofactor activity of factor Va was determined at a low factor Xa concentration (0.3 nM). Addition of 0.2 nM APC and 20 μM phospholipid vesicles to a 1000-fold diluted sample of thrombin-activated normal plasma resulted in loss of more than 85% of the cofactor activity factor Va within 6 rnin. Under the same conditions, APC inactivated ∼ 60% and ∼20% of the factor Va present in plasma samples from APC-resistant individuals that were heterozygous or homozygous for the mutation Arg506⟶Gln in factor V, respectively. Discrimination between the plasma samples from normal and heterozygous and homozygous APC-resistant individuals was facilitated by introduction of the so-called APC-sensitivity ratio (APC-sr). The APC-sr was defined as the ratio of the factor Va cofactor activities determined in thrombin-activated plasma samples after 6 min incubation with or without 0.2 nM APC and was multiplied by 100 to obtain integers (APC-sr = {factor Va+APC/factor Va−APC} × 100). Clear differences were observed between the APC-sr of plasmas from normal healthy volunteers (APC-sr: 8-20, n = 33) and from individuals that were heterozygous (APC-sr: 35-50, n = 17) or homozygous APC resistant (APC-sr: 82-88, n = 7). There was no mutual overlap between the APC-sr of normal plasmas and plasmas from heterozygous or homozygous APC resistant individuals (p <0.0001). In all cases our test gave the same result as the DNA-based assay. Since the test is performed on a highly diluted plasma sample there is no interference by conditions that affect APC resistance tests that are based on clotting time determinations (e.g. coagulation factor deficiencies, oral anticoagulation, heparin treatment, the presence of lupus anticoagulants, pregnancy or the use of oral contraceptives). Furthermore, we show that part of the factor Va assay can be performed on an autoanalyzer which increases the number of plasma samples that can be handled simultaneously.
Image Registration Using Feature Points Extraction and Pseudo-Zernike Moments

In this paper a new image registration algorithm is proposed. Rotation, translation, and scaling (RTS) transformations are considered in the registration process. The proposed algorithm consists of three main steps: extraction of feature point using a Harris corner detector, obtaining the correspondence between the features points of the reference and input image based on using pseudo-Zernike moments of neighborhoods centered on feature points, and estimating the transformation parameters mapping the input image to the reference one by applying RANSAC. Experimental results illustrate the proposed algorithm is robust to translation, rotation, and slight scaling.
HU-331, a novel cannabinoid-based anticancer topoisomerase II inhibitor

Anthracyclines, a large group of quinonoid compounds, are used to treat some forms of cancer. Although highly effective in cancer therapy, the mechanism of action of these compounds is not specific; they act on cancer and other cells by numerous mechanisms. A new anticancer quinone (HU-331) was synthesized from cannabidiol. It shows significant high efficacy against human cancer cell lines in vitro and against in vivo tumor grafts in nude mice. In this study, we investigated its mode of action and present evidence on its unique mechanism. HU-331 does not cause cancer cell cycle arrest, cell apoptosis, or caspase activation. HU-331–caused cell death of human cancer cell lines is not mediated by reactive oxygen intermediates/species, as exposure to HU-331 failed to elicit the generation of reactive oxygen species. HU-331 inhibits DNA topoisomerase II even at nanomolar concentrations but has only a slight nonsignificant effect on DNA topoisomerase I action. The cannabinoid quinone HU-331 is a highly specific inhibitor of topoisomerase II, compared with most known anticancer quinones. It might represent a new potent anticancer drug. [Mol Cancer Ther 2007;6(1):173–83]
The Traumatic Brain Injury Endpoints Development (TED) Initiative: Progress on a Public-Private Regulatory Collaboration to Accelerate Diagnosis and Treatment of Traumatic Brain Injury.

The Traumatic Brain Injury Endpoints Development (TED) Initiative is a 5-year, Department of Defense (DoD) funded project that is working toward the ultimate goal of developing better designed clinical trials, leading to more precise diagnosis, and effective treatments for traumatic brain injury (TBI). TED is comprised of leading academic clinician-scientists, along with innovative industry leaders in biotechnology and imaging technology, patient advocacy organizations, and philanthropists, working collaboratively with regulatory authorities, specifically the US Food and Drug Administration (FDA). The goals of the TED Initiative are to gain consensus and validation of TBI clinical outcome assessment measures and biomarkers for endorsement by global regulatory agencies for use in drug and device development processes. This manuscript summarizes the Initiative's Stage 1 progress over the first 18 months, including intensive engagement with a number of FDA divisions responsible for review and validation of biomarkers and clinical outcome assessments, progression into the prequalification phase of FDA's Medical Device Development Tool program for a candidate set of neuroimaging biomarkers, and receipt of FDA's Recognition of Research Importance Letter regarding TBI. Other signal achievements relate to the creation of the TED Metadataset, harmonizing study measures across eight major TBI studies, and the leadership role played by TED investigators in the conversion of the NINDS TBI Common Data Elements (CDEs) to Clinical Data Interchange Standards Consortium (CDISC) standards. This paper frames both the near-term expectations and the Initiative's long-term vision to accelerate approval of treatments for patients affected by TBI in urgent need of effective therapies.
Demonstration Abstract: Haskell Type Browser

Despite 25 years of experience with ML-style typing and numerous implementations of type inference algorithms for this kind of type system, programmers are still struggling with error messages reported when the inference algorithm fails. Virtually every Haskell programmer can tell stories about type errors where it took hours to identify the actual problem with the program. While initiated functional programmers may accept this as a fact of life, it makes life especially hard for beginners, in fact, too hard for some.
Infrastructure-assisted efficient broadcasting in hybrid vehicular networks

Transmission power adaptation has been widely employed to improve on the network performance. However designing an adaptation technique that could lower the number of collisions and delay under unreliable connectivity and fast topological changes due to high speed vehicles is a challenging task. In this paper we proposed an efficient broadcasting scheme using transmission power adjustment. There are two main contributions. Firstly, a multi-tiered architecture is described for hybrid vehicular networking. Offloading control message exchange among vehicles from vehicle-to-vehicle (V2V) to vehicle-to-infrastructure (V2I) can potentially results in better overall performance. Secondly, a centralized transmission power adaptation technique is proposed. By taking in to account the current topology state, contextual information of vehicle movement is derived in terms of estimated link expiration time. Each vehicle is then assigned a transmission power which ensures connectivity with long lasting links only. A simulation based performance evaluation study shows that the proposed power adaptation technique results in significantly lower packet collision rate and delay while maintaining a shorter average transmission range.
INFORMATION GEOMETRY OF PROPAGATION ALGORITHMS AND APPROXIMATE INFERENCE

Consider the inference problem of undirected graphical models[8, 9]. When the graph is tree, the Belief Propagation (BP) algorithm (J.Pearl[11]) is an efficient algorithm and the exact inference is computed. However, when the graph is “loopy,” and the loops are big, the exact inference becomes intractable. Besides sampling methods, such as MCMC, tractable approximate inference gives us one practical solution, and the “loopy BP” algorithm is one of the most successful methods. Recently, it is pointed out that the idea of loopy BP have been used many fields, for example, Bethe approximation[3] in statistical physics, and the decoding algorithms of Low Density Parity Check (LDPC) codes [4] and turbo codes [2] in error correction codes. Although we observe the loopy BP works well in many applications, its theoretical aspects are not fully understood. Among some theoretical studies of loopy BP, we have studied it from information geometrical viewpoint[6, 7]. In this abstract, we first summerize the results of [6, 7] by defining the problem and showing the properties loopy BP based on information geometry[1]. We further show its relation to other propagation algorithms, including the convex concave computational procedure (CCCP)[14] and Adaptive TAP approximation[10]
Identifying vocational education and training

This paper observes that vocational education and training’s identity has been founded on four types of characteristics: epistemological, teleological, hierarchical and pragmatic. No single characteristic is found to be adequate to identify vocational education and training across jurisdictions and across historical periods. Both Rushbrook and Stevenson seek for vocational education and training what Rushbrook calls an ‘abstracted institutional teleology’. Yet such a quest may degenerate into essentialism, and in any case is vulnerable to being made obsolete by the changes which vocational education and training is meant to be stimulating and equipping us for. The paper concludes by arguing for a definition of vocational education and training which is a compound of the four general characteristics considered.
RNF4-mediated SUMOylation is essential for NDRG2 suppression of lung adenocarcinoma

N-Myc downstream-regulated gene 2 (NDRG2) protein is a tumor suppressor that inhibits cancer growth, metastasis and invasion. The ubiquitin ligase RNF4 integrates signaling by SUMO and ubiquitin through its selective recognition and ubiquitination of SUMO-modified proteins. We evaluated NDRG2 SUMOylation in lung adenocarcinoma cells and its underlying molecular mechanism. The results showed that NDRG2 is covalently modified by SUMO1 at K333, which suppressed anchorage independent adenocarcinoma cell proliferation and tumor growth. In human lung adenocarcinomas cells, RNF4 targeted NDRG2 to proteasomal degradation by stimulating its SUMOylation. Endogenous RNF4 expression was increased in human lung adenocarcinomas cells, and there was a concomitant upregulation of SUMO. These findings indicate that SUMOylation of NDRG2 is necessary for its tumor suppressor function in lung adenocarcinoma and that RNF4 increases the efficiency of this process.
Identification of colonization factors of enterotoxigenic Escherichia coli with PCR-based technique

SUMMARY Colonization factors (CFs) mediate attachment of enterotoxigenic Escherichia coli (ETEC) to the intestinal mucosa and induce protective immunity against ETEC diarrhoea. We designed CF-specific polymerase chain reaction (PCR) primers, and developed a simple PCR-based genotypic CF identification method. ETEC strains (n=17) isolated from patients with diarrhoea in Thailand were examined for genotypical identification of CFs of ETEC strains. Coli surface antigen 6 (CS6) was the most common CF (29%), followed by CS13 (12%), colonization factor antigen I (CFA/I), CS2 and CS3, and CS17/CS19 (6% each), while 41% of the strains were negative. This simple PCR method for the detection of CF genes is useful for surveillance of ETEC infections in diagnostic laboratories.
Reduction of Kinematic Short Baseline Multipath Effects Based on Multipath Hemispherical Map

Multipath hemispherical map (MHM) is a kind of multipath mitigation approach that takes advantage of the spatial repeatability of the multipath effect under an unchanged environment. This approach is not only suitable for static environments, but also for some kinematic platforms, such as a moving ship and airplane, where the dominant multipath effects come from the platform itself and the multipath effects from the surrounding environment are considered minor or negligible. Previous studies have verified the feasibility of the MHM approach in static environments. In this study, we expanded the MHM approach to a kinematic shipborne environment. Both static and kinematic tests were carried out to demonstrate the feasibility of the MHM approach. The results indicate that, after MHM multipath mitigation, the root mean square (RMS) of baseline length deviations are reduced by 10.47% and 10.57%, and the RMS of residual values are reduced by 39.89% and 21.91% for the static and kinematic tests, respectively. Power spectrum analysis has shown that the MHM approach is more effective in mitigating multipath in low-frequency bands; the high-frequency multipath effects still exist, and are indistinguishable from observation noise. Taking the observation noise into account, the residual reductions increase to 41.68% and 24.51% in static and kinematic tests, respectively. To further improve the performance of MHM for kinematic platforms, we also analyzed the influence of spatial coverage and resolution on residual reduction.
Delay Minimization for Spatial Data Processing in Wireless Networked Disaster Areas

Spatial big data analytics has become possible with the data collected from the sensors in smart phones, which can support decision-making in disaster scenarios. However, sometimes the regular communication infrastructure can be destroyed after disasters. Movable base stations (MBS), as studied by the company NTT, offer an easily deployable solution to construct an emergency communication network, but are not suitable for transmitting big data from sensing devices to the cloud for data processing in the cloud. To solve this issue, we studied a novel algorithm to process spatial big data efficiently in a wirelessly networked disaster area that uses multiple MBSs. More specifically, we proposed a novel algorithm to minimize overall delay for spatial data processing in wirelessly-networked disaster areas (SDP-WNDA), to enable quick responses to data analysis. Our proposed model and genetic algorithm solution showed to have a reduced maximum end- to-end (E2E) delay over various network sizes, when compared to some conventional solutions. For the realistic constraints, the cloud solution was the best conventional method, followed by the system which used the fog nodes to process as much data as possible, but the genetic algorithm (GA) had a slight advantage over all other methods. However, as the computation rate, μk, was increased, the maximum processing algorithm got much stronger. Also, as the communication capacity, R, was increased, the cloud computing solution was more successful. The fact that none of the conventional cases matched the capabilities of the GA for increased computation or increased transmission rates suggests the need for this to be investigated even further.
HuR-Regulated mRNAs Associated with Nuclear hnRNP A1-RNP Complexes

Post-transcriptional regulatory networks are dependent on the interplay of many RNA-binding proteins having a major role in mRNA processing events in mammals. We have been interested in the concerted action of the two RNA-binding proteins hnRNP A1 and HuR, both stable components of immunoselected hnRNP complexes and having a major nuclear localization. Specifically, we present here the application of the RNA-immunoprecipitation (RIP)-Chip technology to identify a population of nuclear transcripts associated with hnRNP A1-RNPs as isolated from the nuclear extract of either HuR WT or HuR-depleted (KO) mouse embryonic fibroblast (MEF) cells. The outcome of this analysis was a list of target genes regulated via HuR for their association (either increased or reduced) with the nuclear hnRNP A1-RNP complexes. Real time PCR analysis was applied to validate a selected number of nuclear mRNA transcripts, as well as to identify pre-spliced transcripts (in addition to their mature mRNA counterpart) within the isolated nuclear hnRNP A1-RNPs. The differentially enriched mRNAs were found to belong to GO categories relevant to biological processes anticipated for hnRNP A1 and HuR (such as transport, transcription, translation, apoptosis and cell cycle) indicating their concerted function in mRNA metabolism.
A novel ZCS single phase matrix converter for traction applications

This paper proposed a new ZCS single phase ac-ac matrix converter for the traction applications. The proposed soft switching matrix converter is enhanced with an auxiliary resonant circuit in order to achieve the zero current switching for main bidirectional switches of the matrix converter. The main advantage of this proposed topology is soft switching of matrix converter to achieve switching loses limitation. This paper describes the operation of the proposed matrix converter, simulation analysis and experimental validation of the prototype for 50V-16.7Hz-100W-400Hz.