Miracle-dz/UniFAR-FTUs huggingface dataset:
A wideband rectifier array on dual‐polarized differential‐feed fractal slotted ground antenna for RF energy harvesting

This article reports a novel wideband rectenna for RF energy harvesting applications. A wideband fractal slotted ground antenna (SGA) is adopted. The operating frequency bands of the antenna are GSM, UMTS, Wi‐Fi, and LTE2600/4G bands. The antenna is fed by a dual‐polarized and differential‐feed (DP‐DF) microstrip lines disposed with an angle of 90° each relative to the other. The feed lines are etched on the bottom side of the substrate and connected to an array of four wideband RF‐to‐DC rectifiers. A nonuniform transmission lines filter ensures wideband behavior for each rectifier. The rectenna performances are simulated and measured. The experiments show an output DC voltage of 1 V at a power density of 26.6 μW/cm2 over the frequency band of operation with a peak efficiency of 50%. The proposed rectenna is suitable for energy harvesting applications in urban environments.
Fidelity of Prespacer Capture and Processing is Governed by the PAM Mediated Interaction of Cas1-2 Adaptation complex in Escherichia coli

During CRISPR adaptation, short sections of invader derived DNA of defined length are specifically integrated at the leader-repeat junction as spacers by Cas1-2 integrase complex. While several variants of CRISPR systems utilise Cas4 as an indispensible nuclease for processing the PAM containing prespacers to a defined length for integration– surprisingly– a few CRISPR systems such as type I-E are bereft of Cas4. Therefore, how the prespacers show impeccable conservation for length and PAM selection in type I-E remains intriguing. In Escherichia coli, we show that Cas1-2/I-E– via the type I-E specific extended C-terminal tail of Cas1 –displays intrinsic affinity for PAM containing prespacers of variable length and its binding protects the prespacer boundaries of defined length from the exonuclease action that ensues the pruning of aptly sized substrates for integration. This suggests that cooperation between Cas1-2 and cellular exonucleases drives the Cas4 independent prespacer capture and processing in type I-E.
A Novel q-parameter Automation in Tsallis Entropy for Image Segmentation

Image Thresholding is the necessary task in some image processing applications. The goal of any segmentation technique in image processing is to find out the object from the background in the given image. In this paper, q-parameter of the Tsallis entropy is analyzed in the existing and the proposed methods. Different techniques have been introduced to automate the q-parameter to obtain corresponding threshold value. After the comparison of all results by using misclassification error, the proposed one yields better results as demonstrated by statistical analysis.
Efficient and Generic Construction of Certification-Based Encryption in the Standard Model Based on the NIZK Proof System

Certificate-based encryption (CBE) is a new public key encryption paradigm which combines traditional PKI-based public-key encryption (PKE) and identity-based encryption (IBE) , and preserv es some of their most attractive features. CBE provides an efficient implicit certificate mechanism and allows a periodical update of certificate status . It eliminates third-party queries for the certificate status and simplifies the certificate revocation problem in the traditional PKI , while it solves the key escrow problem and the key distribution problem inherent in IBE. In this paper, we propose a new generic construction of CBE schemes from PKE and IBE, and prove it to be CCA-secure in the standard model. In our construction, we use an efficient one-time simulation-sound adaptive NIZK proof system as the security enhancing building block to guarantee the CCA-security of the generated CBE schemes . When compared to the previous method, the security requirements of the primitive encryption schemes in our construction are much weaker and the performance of the generated CBE schemes from our construction is much more efficient .
Efficacy of methylphenidate for the treatment of mental sequelae after traumatic brain injury

Background: This study aimed to evaluate the effect of methylphenidate for treating mental sequelae after traumatic brain injury (TBI). Methods: Thirty-six patients with TBI were randomly divided into the intervention group and placebo group. The participants in the intervention group received methylphenidate, while subjects in the placebo group were administered a placebo. This study was conducted from January 2014 to December 2016. The outcome measurements included Mental Fatigue Scale, Choice Reaction Time, Compensatory Tracking Task, Mental Arithmetic Test, Digit Symbol Substitution Test, Mini-Mental State Examination (MMSE), Beck Depression Inventory (BDI), and Hamilton Rating Scale for Depression. In addition, safety was also recorded and assessed. Results: A total of 33 subjects completed the study. Methylphenidate showed greater efficacy than placebo, with decreased scores on the Mental Fatigue Scale, Choice Reaction Time, and Compensatory Tracking Task in the intervention group compared to the placebo group (P < .01, respectively). Furthermore, increased scores on the Mental Arithmetic Test, Digit Symbol Substitution Test, and MMSE in the intervention group, compared to those in the placebo group (P < .01 respectively), were observed. In addition, a significant difference in the scores on the BDI (P = .04) and Hamilton Rating Scale for Depression (P = .005) was observed between the 2 groups. The safety at the end of the 30 week-treatment was similar between the 2 groups (P > .05). Conclusion: The results of this study demonstrated that methylphenidate could effectively improve mental fatigue and cognitive functions in patients with TBI.
Shear Forces from Flow Are Responsible for a Distinct Statistical Signature of Adherent Microbubbles in Large Vessels

Real-time ultrasound-based targeted molecular imaging in large blood vessels holds promise for early detection and diagnosis of stroke risk by identifying early markers for atherosclerosis prior to plaque formation. Singular spectrum-based targeted molecular (SiSTM) imaging is a recently proposed method that uses changes in statistical dimensionality—quantified by a normalized singular spectrum area (NSSA)—to image receptor-ligand–bound adherent microbubbles. However, the precise physical mechanism responsible for the distinct statistical signature was previously unknown. In this study, in vitro flow phantom experiments were performed to elucidate the physical mechanism in large blood vessel environments. In the absence of flow, an increase in the NSSA of adherent microbubbles with respect to tissue was not observed with increased microbubble concentration or pulse length (p > .23; n = 5) but was observed with increased flow rate (p < .01; n = 10). When observing the dynamics of the adherent microbubble statistics, a good correlation was observed between the NSSA and the derivative of image intensity (R2 > .97). In addition, a monotonic relationship between the NSSA and decorrelation was demonstrated. These findings confirm the hypothesis that the statistical signature of adherent microbubbles is derived from frame-to-frame decorrelation, which is induced by flow shear forces.
Embedded Ultrathin Cluster Electrodes for Long-Term Recordings in Deep Brain Centers

Neural interfaces which allow long-term recordings in deep brain structures in awake freely moving animals have the potential of becoming highly valuable tools in neuroscience. However, the recording quality usually deteriorates over time, probably at least partly due to tissue reactions caused by injuries during implantation, and subsequently micro-forces due to a lack of mechanical compliance between the tissue and neural interface. To address this challenge, we developed a gelatin embedded neural interface comprising highly flexible electrodes and evaluated its long term recording properties. Bundles of ultrathin parylene C coated platinum electrodes (N = 29) were embedded in a hard gelatin based matrix shaped like a needle, and coated with Kollicoat™ to retard dissolution of gelatin during the implantation. The implantation parameters were established in an in vitro model of the brain (0.5% agarose). Following a craniotomy in the anesthetized rat, the gelatin embedded electrodes were stereotactically inserted to a pre-target position, and after gelatin dissolution the electrodes were further advanced and spread out in the area of the subthalamic nucleus (STN). The performance of the implanted electrodes was evaluated under anesthesia, during 8 weeks. Apart from an increase in the median-noise level during the first 4 weeks, the electrode impedance and signal-to-noise ratio of single-units remained stable throughout the experiment. Histological postmortem analysis confirmed implantation in the area of STN in most animals. In conclusion, by combining novel biocompatible implantation techniques and ultra-flexible electrodes, long-term neuronal recordings from deep brain structures with no significant deterioration of electrode function were achieved.
Light Localization Induced by a Random Imaginary Refractive Index

We show the emergence of light localization in arrays of coupled optical waveguides with randomness only in the imaginary part of their permittivity and develop a one-parameter scaling theory for the normalized participation number of the Floquet-Bloch modes. This localization introduces a new length scale in the decay of the autocorrelation function of a paraxial beam propagation. Our results are relevant to a vast family of systems with randomness in the dissipative part of their impedance spatial profile.
World's first monolithic 3D-FPGA with TFT SRAM over 90nm 9 layer Cu CMOS

World's first monolithically integrated Thin-Film-Transistor (TFT) SRAM configuration circuits over 90nm 9 layers of Cu interconnect CMOS is successfully fabricated at 300mm LSI mass production line for 3-dimensional Field Programmable Gate Arrays (3D-FPGA). This novel technology built over the 9th layer of Cu metal features aggressively scaled amorphous Si TFT having 180nm transistor gate length, 20nm gate oxide, fully silicided gate, S/D, all below 400C processing essential to not impact underlying Cu interconnects. Low temperature TFT devices show excellent NTFT/PTFT transistor Ion/Ioff ratios over 2000/100 respectively, operate at 3.3V, E-field scalable, and are stable for SRAM configuration circuits. We believe this 3D-TFT technology is a major breakthrough innovation to overcome the conventional CMOS device shrinking limitation.
Product Features Extraction from Opinions According to Time

Nowadays, e-commerce shopping websites have experienced noticeable growth. These websites have gained consumers’ trust. After purchasing a product, many consumers share comments where opinions are usually embedded about the given product. Research on the automatic management of opinions that gives suggestions to potential consumers and portrays an image of the product to manufactures has been growing recently. After launching the product in the market, the reviews generated around it do not usually contain helpful information or generic opinions about this product (e.g. telephone: great phone.); in the sense that the product is still in the launching phase in the market. Within time, the product becomes old. Therefore, consumers perceive the advantages/ disadvantages about each specific product feature. Therefore, they will generate comments that contain their sentiments about these features. In this paper, we present an unsupervised method to extract different product features hidden in the opinions which influence its purchase, and that combines Time Weighting (TW) which depends on the time opinions were expressed with Term Frequency-Inverse Document Frequency (TF-IDF). We conduct several experiments using two different datasets about cell phones and hotels. The results show the effectiveness of our automatic feature extraction, as well as its domain independent characteristic. Keywords—Opinion mining, product feature extraction, sentiment analysis, SentiWordNet.
Right Ventricular Morphology and the Onset of Dyspnea: The MESA-Right Ventricle Study

Background The association of right ventricular (RV) structure and function with symptoms in individuals without cardiopulmonary disease is unknown. We hypothesized that greater RV mass and RV end-diastolic volume (RVEDV), smaller RV stroke volume (RVSV), and lower RV ejection fraction (RVEF) measured by cardiac magnetic resonance imaging (MRI) in participants free of clinical cardiovascular disease at baseline would be associated with a greater risk of self-reported dyspnea. Methods The Multi-Ethnic Study of Atherosclerosis (MESA) performed cardiac MRIs on participants without clinical cardiovascular disease between 2000 and 2002. We excluded subjects who reported “prevalent” dyspnea at the first assessment (24 months). The presence of dyspnea was assessed at 24 months, 42 months, and 60 months from baseline. Cox proportional hazards models were used to examine the relationship between RV measures and incident dyspnea. Results In the final study sample (N = 2763), there were significant interactions between RV measures and sex in terms of the risk of dyspnea (p<0.05). Among men (N = 1453), lower RV mass (p = 0.003), smaller RVEDV (p<0.001), smaller RV end-systolic volume (RVESV) (p = 0.03) and decreased RVSV (p<0.001) were associated with an increased risk of developing dyspnea after adjusting for covariates. Associations remained after adjusting for left ventricular function and lung function. However, there were no significant associations between RV measures and the risk of dyspnea in women. Conclusions Lower RV mass and smaller RV volumes were associated with an increased risk of dyspnea in men, but not in women.
Parametric Channel Prediction for Narrowband Mobile MIMO Systems Using Spatio-Temporal Correlation Analysis

In this paper, we propose an ESPRIT-based parametric prediction scheme for narrowband MIMO systems that fully exploits both temporal and spatial correlations in realistic MIMO channels. The proposed predictor uses a vector transmit spatial signature model and two-dimensional ESPRIT for the estimation of the channel parameters. The proposed scheme outperforms existing algorithms and is well suited to both two dimensional azimuth only and three dimensional MIMO spatial channel models.
Encoding attentional-states during visuomotor adaptation.

We recently showed that visuomotor adaptation acquired under attentional distraction is better recalled under a similar level of distraction compared to no distraction. This paradoxical effect suggests that attentional state (e.g., divided or undivided) is encoded as an internal context during visuomotor learning, and should be reinstated for successful recall (Song & Bédard, in press). To investigate if there is a critical temporal window for encoding attentional state in visuomotor memory, we manipulated whether participants performed the secondary attention-demanding task concurrently in the early or late phase of visuomotor learning. Recall performance was enhanced when the attentional states between recall and the early phase of visuomotor learning were consistent. However, it reverted to untrained levels when tested under the attentional state of the late phase learning. This suggests that attentional state is primarily encoded during the early phase of learning before motor errors decrease and reach an asymptote. Furthermore, we demonstrate that when divided and undivided attentional states were mixed during visuomotor adaptation, only divided attention was encoded as an internal cue for memory retrieval. Therefore, a single attentional state appears to be primarily integrated with visuomotor memory while motor error reduction is in progress during learning. Meeting abstract presented at VSS 2015.
Analysis of probabilistic processes and automata theory

This chapter surveys some basic algorithms for analyzing Markov chains (MCs) and Markov decision processes (MDPs), and discusses their computational complexity. We focus on discrete-time processes, and we consider both ﬁnite-state models as well as countably inﬁnite-state models that are ﬁnitely-presented. The analyses we will primarily focus on are hitting (reachability) probabilities and ω -regular model checking, but we will also discuss various reward-based analyses. Although it may not be evident at ﬁrst, there are fruitful connections between automata theory and stochastic processes. Firstly, and not surprisingly, ω -automata play a naturally important role for specifying ω -regular properties of sample paths (trajectories) of stochastic processes. Computing the probability of the event that a random sample path satisﬁes a given ω -regular property constitutes the (linear-time) model checking problem for probabilistic systems. Secondly, it turns out that there are close relationships between classic inﬁnite-state automata-theoretic models and classic denumerably inﬁnite-state stochastic processes, even though these models were developed independently in separate mathematical communities. Roughly speaking, some classic stochastic processes share their underlying state transition systems with corresponding classic automata-theoretic models. Furthermore, exploiting these connections to automata theory is fruitful for the algorithmic analysis of such stochastic processes, and for their controlled MDP extensions. This holds even when the analyses are much simpler than model checking, such as computing (optimal) hitting probabilities.
Escherichia coli‐based cell‐free synthesis of virus‐like particles

Virus‐like particles (VLP) have received considerable attention for vaccine, drug delivery, gene therapy and material science applications. Although the number of unique VLP and their applications are rapidly growing, the positive impact of VLP applications is limited by the current diverse, expensive, and typically low‐yielding production technologies available. These technologies, when scaled, often result in structurally and compositionally inconsistent products. We present Escherichia coli‐based cell‐free protein synthesis as a production technology to overcome many of the limitations of current VLP production processes. Using this technique, the MS2 bacteriophage coat protein VLP was produced at a yield 14 times the best published production yield. Also, a C‐terminally truncated Hepatitis B core protein VLP was produced at similarly high yields (6 × 1013 VLP/mL). These VLP were found to have comparable characteristics to those produced in vivo. The scalability of this technology was tested without loss in production yields. To our knowledge, this is the first time a prokaryote‐based in vitro transcription/translation system has generated a virus‐like particle. Biotechnol. Bioeng. 2008;100: 28–37. Biotechnol. Bioeng. 2008;100: 28–37. © 2007 Wiley Periodicals, Inc.
Mutilabel MRFs with Label Adjacency Constraint : Globally Optimal Solutions and Applications

This work addresses the problem of optimally solving Markov Random Fields(MRFs) in which labels obey a certain topology constraint. Utilizing prior information, such as domain knowledge about the appearance, shape, or spatial configuration of objects in a scene can greatly improve the accuracy of segmentation algorithms in the presence of noise, clutter, and occlusion. Nowhere is this more evident than in the segmentation of biomedical images, where typically the spatial relationships among the image regions inherently reflect those of the anatomical structures being imaged. In this work, we propose a new methodology to segment a special class of images, which exhibit nested layer topologies often encountered in biomedical applications. The segmentation problem is modeled using multi-label Markov Random Fields with an additional label adjacency constraint (LAC). The multi-label MRF energy with LAC is transformed via boolean variables encoding into an equivalent function of binary variables. We show this boolean function is submodular, graph representable, and can be minimized exactly and efficiently with graph cut techniques. Our experimental results on both synthetic and real images demonstrate the utility of the proposed LAC segmentation algorithm.
Multi-Level Surface Maps for Outdoor Terrain Mapping and Loop Closing

To operate outdoors or on non-flat surfaces, mobile robots need appropriate data structures that provide a compact representation of the environment and at the same time support important tasks such as path planning and localization. One such representation that has been frequently used in the past are elevation maps which store in each cell of a discrete grid the height of the surface in the corresponding area. Whereas elevation maps provide a compact representation, they lack the ability to represent vertical structures or even multiple levels. In this paper, we propose a new representation denoted as multi-level surface maps (MLS maps). Our approach allows to store multiple surfaces in each cell of the grid. This enables a mobile robot to model environments with structures like bridges, underpasses, buildings or mines. Additionally, they allow to represent vertical structures. Throughout this paper we present algorithms for updating these maps based on sensory input, to match maps calculated from two different scans, and to solve the loop-closing problem given such maps. Experiments carried out with a real robot in an outdoor environment demonstrate that our approach is well-suited for representing large-scale outdoor environments
Predictive Factors for a Long Postoperative Stay after Emergency Laparoscopic Cholecystectomy Using the 2013 Tokyo Guidelines: A Retrospective Study

Laparoscopic cholecystectomy (LC) is widely used for treating early acute cholecystitis (AC) and substantially reduces hospital costs. This study aimed to identify and evaluate risk factors associated with long postoperative hospital stays (PHSs) in patients undergoing emergency LC for AC according to the 2013 Tokyo Guidelines (TG13). Clinical data of patients who underwent emergency LC for AC between 2011 and 2017 were retrospectively collected. Patients were divided into early discharge (ED, discharge in three days or less postoperatively) and late discharge (LD, discharge in more than three days postoperatively) groups based on clinical progression and PHS after LC. Preoperative characteristics and perioperative outcomes were analysed as potential risk factors for LD. Among 149 patients, 104 (69.8%) were discharged within 3 days postoperatively, whereas 45 (30.2%) had long PHSs. Main causes of LD were fever and inflammation. Univariate analysis of preoperative risk factors revealed significant differences in age, white blood cell count, C-reactive protein, total bilirubin (T-bil), and alkaline phosphatase (ALP) levels; anticoagulation therapy; and TG13 severity grade. Multivariate analysis revealed that TG13 severity grade II, age >65 years, and elevated T-bil and ALP levels are independent factors for long PHS. Older age, worse biliary function, and increased TG13 severity grade might predict prolonged PHSs in AC patients undergoing emergency LC.