Miracle-dz/UniFAR-FTUs huggingface dataset:
A 60-GHz Dual-Mode Distributed Active Transformer Power Amplifier in 65-nm CMOS

This paper presents a 60-GHz power amplifier (PA) fabricated in a 65-nm CMOS technology. The proposed PA utilizes a dual-mode amplification circuit topology to achieve a high level of output power and efficiency in a small die area. High-output power is achieved by combining class AB cascode stage with a conventional class A common source (CS) stage in a compact four-way differential distributed active transformer to increase the amplifier's power density. Driver stages consist of an enhanced cascode stage followed by a CS stage to achieve a high power (HP) gain. Fabricated in a 65-nm CMOS process, the maximum measured gain of the 60-GHz PA is 22 dB within a wide 3-dB bandwidth of 14 GHz. A maximum saturated output power of 19.7 dBm is measured in HP mode while consuming 430 mW over a 1.2 V core supply. In low-power (LP) mode of operation, the power gain of 20 dB and 19.7 dBm saturated power is measured at 60 GHz. The proposed dual-mode topology achieves an HP added efficiency of 25% and 19% in HP and LP modes, respectively.
Functional heterogeneity of type 1 fimbriae of Escherichia coli

Escherichia coli and other members of the family Enterobacteriaceae express surface fibrillar structures, fimbriae, that promote bacterial adhesion to host receptors. Type 1 fimbriae possess a lectinlike component, FimH, that is commonly thought to cause binding to mannose-containing oligosaccharides of host receptors. Since adhesion of type 1 fimbriated organisms are inhibited by mannose, the reactions are described as mannose sensitive (MS). We have studied the adhesion of the type 1 fimbriated CSH-50 strain of E. coli (which expresses only type 1 fimbriae) to fibronectin (FN). E. coli CSH-50 does not bind detectable amounts of soluble FN but adheres well to immobilized plasma or cellular FN. This adhesion was inhibited by mannose-containing saccharides. By using purified domains of FN, it was found that E. coli CSH-50 adheres primarily to the amino-terminal and gelatin-binding domains, only one of which is glycosylated, in an MS fashion. Binding of the mannose-specific lectin concanavalin A to FN and ovalbumin was eliminated or reduced, respectively, by incubation with periodate or endoglycosidase. Adhesion of E. coli CSH-50 to ovalbumin was reduced by these treatments, but adhesion to FN was unaffected. E. coli CSH-50 also adheres to a synthetic peptide copying a portion of the amino-terminal FN domain (FNsp1) in an MS fashion. Purified CSH-50 fimbriae bound to immobilized FN and FNsp1 in an MS fashion and inhibited adhesion of intact organisms. However, fimbriae purified from HB101 (pPKL4), a recombinant strain harboring the entire type 1 fim gene locus and expressing functional type 1 fimbriae, neither bound to FN or FNsp1 nor inhibited E. coli adhesion to immobilized FN or FNsp1. These novel findings suggest that there are two forms of type 1 MS fimbriae. One form exhibits only the well-known MS lectinlike activity that requires a substratum of mannose-containing glycoproteins. The other form exhibits not only the MS lectinlike activity but also binds to nonglycosylated regions of proteins in an MS manner.
Steered Microaggregation as a Unified Primitive to Anonymize Data Sets and Data Streams

As data grow in quantity and complexity, data anonymization is becoming increasingly challenging. On one side, a great diversity of masking methods, synthetic data generation methods, and privacy models exists, and this diversity is often perceived as unsettling by practitioners. On the other side, most of the anonymization methodology was designed for static, structured, and small data, whereas the current landscape includes big data and, in particular, data streams. We explore here a unified and conceptually simple anonymization approach, by presenting a primitive called steered microaggregation that can be tailored to enforce various privacy models on static data sets and also on data streams. Steered microaggregation is based on adding artificial attributes that are properly initialized and weighted in order to guide the microaggregation process into meeting certain desired constraints. To demonstrate the potential of this type of microaggregation, we show how it can be used to achieve <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-anonymity, <inline-formula> <tex-math notation="LaTeX">$t$ </tex-math></inline-formula>-closeness, <inline-formula> <tex-math notation="LaTeX">$l$ </tex-math></inline-formula>-diversity, and <inline-formula> <tex-math notation="LaTeX">$\epsilon $ </tex-math></inline-formula>-differential privacy in the context of static data sets; furthermore, we discuss how it can be used to achieve <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>-anonymity of data streams while controlling tuple reordering. Beyond its flexibility and theoretical appeal, steered microaggregation can drastically reduce information loss, as shown by our experimental evaluation.
Comparison Of Pressure Based Solver With Artificial Compressibility Method

Pressure based solver (PBS) is an algorithm to solve the pressure equation which is derived from the continuity and momentum equations. In this paper, various interpolation schemes are used to simulate the velocity behaviour of viscous incompressible fluids on standard lid driven cavity test case. The simulation is done by varying the Reynolds number and the results are validated with artificial compressibility method (ACM). Keywords—Navier-Stokes equation, lid driven cavity, artificial compressibility method, pressure based solvers.
SELF‐REPORTED TRAINING METHODS OF MIXED MARTIAL ARTISTS AT A REGIONAL REALITY FIGHTING EVENT

This study surveyed 28 athletes competing at a regional mixed martial arts (MMA) event. The survey attempted to gather information regarding overall training volume, supplement use, and specific exercises used. The survey return rate was 100% (28/28). Twenty-five out of the 28 athletes supplemented their training with strength training. Overall frequency of strength training sessions/week ranged from 1–7, and overall frequency of fighting specific training sessions/week ranged from 3–12. Five out of the 28 athletes used/had used anabolic-androgenic steroids. Twelve of the MMA athletes did not perform exercises specifically for the neck musculature, and only 8 used the power clean and/or power snatch within their strength-training program. The results suggest that strength and conditioning specialists should educate MMA athletes regarding the importance of balanced training, effective exercises, and the side effects of anabolic androgenic steroid use.
A search for amino acid substitutions that universally activate response regulators

Two‐component regulatory systems, typically composed of a sensor kinase to detect a stimulus and a response regulator to execute a response, are widely used by microorganisms for signal transduction. Response regulators exhibit a high degree of structural similarity and undergo analogous activating conformational changes upon phosphorylation. The activity of particular response regulators can be increased by specific amino acid substitutions, which either prolong the lifetime or mimic key features of the phosphorylated state. We probed the universality of response regulator activation by amino acid substitution. Thirty‐six mutations that activate 11 different response regulators were identified from the literature. To determine whether the activated phenotypes would be retained in the context of a different response regulator, we recreated 51 analogous amino acid substitutions at corresponding positions of CheY. About 55% of the tested substitutions completely or partially inactivated CheY, ≈ 30% were phenotypically silent, and ≈ 15% activated CheY. Three previously uncharacterized activated CheY mutants were found. The 94NS (and presumably 94NT) substitutions resulted in resistance to CheZ‐mediated dephosphorylation. The 113AP substitution led to enhanced autophosphorylation and may increase the fraction of non‐phosphorylated CheY molecules that populate the activated conformation. The locations of activating substitutions on the response regulator three‐dimensional structure are generally consistent with current understanding of the activation mechanism. The best candidates for potentially universal activating substitutions of response regulators identified in this study were 13DK and 113AP.
Agglomeration, Urban Growth and Infrastructure in Global Climate Policy: A Dynamic CGE Approach

This paper presents an integrated model of urban agglomeration economies within a computable general equilibrium (CGE) model of global economic activity, energy use and carbon emissions to explore the theoretical and empirical nature of the interdependence of cities and the world economy in a climate policy context. Based on calibration data for 74 major OECD agglomerations, the integrated model is used to gauge the long-term impact of: i) global carbon pricing on urban systems and the economic activity; ii) urban infrastructure development on the economic costs of curbing carbon emissions. Importantly, it is found that combining urban infrastructure and carbon pricing allows for stringent emissions reduction targets, while still avoiding the economic and welfare costs of the carbon price only.
Draft Genome Sequences of Two Genetic Variant Strains of Edwardsiella piscicida, JF1305 and RSB1309, Isolated from Olive Flounder (Paralichythys olivaceus) and Red Sea Bream (Pagrus major) Cultured in Japan, Respectively

ABSTRACT Edwardsiella piscicida is a new species discovered within the group of organisms traditionally classified as Edwardsiella tarda. We present draft genome sequences of two variant strains of E. piscicida, JF1305 and RSB1309. Differences in protein-coding sequence between these isolates are associated with virulence, disease, and defense, suggesting differences in pathogenicity.
Analysis of risk prediction capability and validity of Morse Fall Scale Brazilian version.

Objective To analyse the power to predict risk and verify the validity of the Morse Fall Scale - Brazilian version (MFS-B). Method This is a methodological, longitudinal study with 1487 adult patients of two university hospitals of Rio Grande do Sul, Brazil conducted from November 2013 to March 2014. The MFS-B was used to assess the risk of falls. Statistical analysis comprised multivariate methods (discriminant function analysis and ROC curve). The research was approved by the ethics committees of the institutions. Results The best estimate to predict falls was at the cutoff point 44.78 of the average MFS-B score, with a sensitivity of 95.2% and a specificity of 64%. The occurrence of falls and the high-risk classification were significant (p<0.00001). Conclusions The results show that the MFS-B can appropriately predict the risk of falls at the cutoff point for the high-risk classification, according to the original classification. The MFS-B had adequate validation test results and maintained the six items of the original scale.
Electrosense: Crowdsourcing spectrum monitoring

We present Electrosense: a distributed, collaborative and low-cost wireless spectrum monitoring solution which is deployed on a large scale. The proposed framework provides tools to enable and promote a crowdsourced open spectrum monitoring platform for wide area deployments. The collected spectrum data is stored and processed in the backend which can be easily retrieved by the users through an open API. The framework also allows using various signal processing algorithms deployed on the sensors as well as in the backend. These algorithms provide statistics on spectrum usage, collaborative spectrum data decoding, help in applications like anomaly detection and localization. The goal of the demo is to introduce the framework, show the infrastructure already deployed, how to join the network and demo a few built-in applications.
A novel current sharing method for multi-module LLC resonant converters

A novel load current sharing method is proposed for multi-module LLC resonant converters in high power application in this paper. The paralleled system is controlled by the maximum current sharing method to achieve load sharing automatically. Moreover, a series inductor is connected to each LLC output side to restrain the current ripple of double switching frequency. The maximum current sharing method is more stable than master-slave control and will not increase complexity. Theoretical analysis of the stability of individual module is based on the envelope model. And the stability of parallel operation is analyzed according to interface stability method. The analysis of the series inductor is given under first harmonic approximation assumption. Finally, an experimental prototype of a 4.8kW multi-module LLC converter system with 100V input voltage and 540V output voltage was built and tested to verify the proposed scheme.
Morphology and Round Body Formation in Vibrio marinus

The morphology of Vibrio marinus MP-1 was studied by phase and electron microscopy. The ultrastructure of the vibrio form of V. marinus was found to be typically gram-negative with a trilaminar plasma membrane and cell wall. The coccoid or round bodies noted in otherwise pure cultures of V. marinus were frequently found in early and late stationary phase of growth. The round bodies in ultrathin section were found to contain at least one, and often three or four, cell units. Three types of round bodies were observed in ultrathin section, each differing in size and behavior: “spherules,” “spheres” or the “round body,” and “giant cells” or “macrospheres. ” The round bodies appeared to be associated with, or to result from, the constrictive cell division of V. marinus.
Gearbox fault prognosis based on CHMM and SVM

A new gearbox fault prognosis scheme based on continuous hidden Markov model (CHMM) and support vector machine (SVM) is developed. Based on the features which are the energies of intrinsic mode functions (IMFs) decomposed by empirical mode decomposition (EMD) extracted from normal gearbox vibration signal, a CHMM is trained to model the normal condition. The logarithm of the probability of this CHMM is then used to detect any defects and assess their severity. Then, SVM is used to predict the value of new feature which is the logarithm of the probability. Experimental data collected from a gearbox degradation test is used to verify the efficacy of the new scheme.
Quinine plus clindamycin improves chemotherapy of severe malaria in children

In a randomized trial, a 4-day quinine-clindamycin regimen was compared with the standard 7-day quinine regimen for 100 Gabonese children (50 children in each group) with severe Plasmodium falciparum malaria. In each group, only one patient died. Parasite clearance and fever clearance times were significantly shorter in the quinine-clindamycin group (P = 0.03 and P = 0.01, respectively) than in the quinine group, and significantly more recurring fever episodes occurred in the quinine group than in the quinine-clindamycin group shortly after initial fever clearance and parasite clearance (P < 0.001).
Automatically Pairing Measured Findings across Narrative Abdomen CT Reports

Radiological measurements are one of the key variables in widely adopted guidelines (WHO, RECIST) that standardize and objectivize response assessment in oncology care. Measurements are typically described in free-text, narrative radiology reports. We present a natural language processing pipeline that extracts measurements from radiology reports and pairs them with extracted measurements from prior reports of the same clinical finding, e.g., lymph node or mass. A ground truth was created by manually pairing measurements in the abdomen CT reports of 50 patients. A Random Forest classifier trained on 15 features achieved superior results in an end-to-end evaluation of the pipeline on the extraction and pairing task: precision 0.910, recall 0.878, F-measure 0.894, AUC 0.988. Representing the narrative content in terms of UMLS concepts did not improve results. Applications of the proposed technology include data mining, advanced search and workflow support for healthcare professionals managing radiological measurements.
Comparative Study on Immediate Versus Delayed Meniscus Allograft Transplantation

Background: Meniscus allograft transplantation (MAT) is generally used for patients who sustain symptoms after meniscectomy, which could be called delayed MAT. Meniscus allograft transplantation for patients immediately after meniscectomy has not been reported. Hypothesis: Compared with the conventional delayed MAT, immediate MAT might provide better clinical results and reduce joint degeneration. Study Design: Cohort study; Level of evidence, 3. Methods: The study was performed with 18 transplanted menisci (6 medial, 12 lateral) from 16 patients. Eight menisci were transplanted immediately after meniscectomy (IM group); 10 menisci, from patients who complained of knee symptoms at a mean time of 35 months (range, 9-92 months) after total meniscectomy, underwent delayed transplantation (DE group). Fourteen patients undergoing meniscectomy during the same period were included as controls (ME group). Degenerative changes in knee joints were evaluated by plain radiographs and magnetic resonance imaging (MRI). Allograft extrusion and relative percentage of extrusion were measured on MRI. Other outcome assessments included preoperative and postoperative International Knee Documentation Committee (IKDC), Tegner, and Lysholm scores; visual analog scale (VAS) for pain; and range of motion and isokinetic muscle strength evaluation. Results: The mean length of follow-up was 50.8 months (range, 44-62 months) for the IM group, 72.0 months (range, 44-94 months) for the DE group, and 54.3 months (range, 45-62 months) for the ME group. A statistically significant difference in favor of the IM and ME groups was found on the VAS (0.4 [IM group] vs 1.1 [ME group] vs 2.5 [DE group]) and muscle strength (P < .05). The mean IKDC score in the IM group was significantly higher than that in the DE group (93 [range, 85-99] vs 74 [range, 38-95], respectively; P < .05). The IM group showed significantly less preoperative to postoperative cartilage degeneration changes on radiographs and MRI when compared with the DE and ME groups (Kellgren-Lawrence score changes: 0.25 [IM group] vs 1.0 [DE group] vs 1.7 [ME group]; Yulish score changes: 0.25 [IM group] vs 1.0 [DE group] vs 1.1 [ME group]; P < .05). Extrusion of the allograft was observed in the body of the menisci in all patients. No significant difference was found in terms of the Lysholm score, Tegner score, joint narrowing, or meniscus extrusion (P > .05). Conclusion: Compared with delayed MAT, immediate MAT led to more satisfactory subjective results, less joint degeneration, and less muscle strength deficits. The short-term results of delayed meniscus transplantation were close to those of meniscectomy.
Accelerated Singular Value-Based Ultrasound Blood Flow Clutter Filtering With Randomized Singular Value Decomposition and Randomized Spatial Downsampling

Singular value decomposition (SVD)-based ultrasound blood flow clutter filters have recently demonstrated substantial improvement in clutter rejection for ultrafast plane wave microvessel imaging, and have become the commonly used clutter filtering method for many novel ultrafast imaging applications such as functional ultrasound and super-resolution imaging. At present, however, the computational burden of SVD remains as a major hurdle for practical implementation and clinical translation of this method. To address this challenge, in the study we present two blood flow clutter filtering methods based on randomized SVD (rSVD) and randomized spatial downsampling to accelerate SVD clutter filtering with minimal compromise to the clutter filter performance. rSVD accelerates SVD computation by approximating the <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula> largest singular values, while random downsampling accelerates both full SVD and rSVD by decomposing the original large data matrix into small matrices that can be processed in parallel. An <italic>in vitro</italic> blood flow phantom study with the presence of heavy tissue clutter showed significantly improved computational performance using the proposed methods with minimal deterioration to the clutter filter performance (less than 3-dB reduction in blood to clutter ratio, less than 0.2-cm<sup>2</sup>/s<sup>2</sup> increase in flow mean squared error, less than 0.1-cm/s increase in the standard deviation of the vessel blood flow signal, and less than 0.3-cm/s increase in tissue clutter velocity for both full SVD and rSVD when the downsampling factor was less than <inline-formula> <tex-math notation="LaTeX">$20\times$ </tex-math></inline-formula>). The maximum acceleration was about threefold from randomized spatial downsampling, and approximately another threefold from rSVD. An <italic>in vivo</italic> rabbit kidney perfusion study showed that rSVD provided comparable performance to full SVD in clutter rejection <italic>in vivo</italic> (maximum difference of blood to clutter ratio was less than 0.6 dB), and random downsampling provided artifact-free perfusion imaging results when combined with both full SVD and rSVD. The blood to clutter ratio was still above 10 dB with a downsampling factor of <inline-formula> <tex-math notation="LaTeX">$60\times$ </tex-math></inline-formula>. We also demonstrated real-time microvessel imaging feasibility (~40-ms processing time) by combining rSVD with random downsampling. The findings and methods presented in this paper may greatly facilitate the new area of ultrafast microvessel imaging research.
Electricity and fuel consumption in Europe: a panel error correction model for residential demand elasticities.

Our objective is to derive robust long term demand elasticities for energy in different end-use sectors. These can be used as a reference for developing long term energy scenario’s based on bottom-up, technology oriented , models such as Markal and TIMES. This paper focuses on the residential sector. Pane l data from 13 EU member states have been used to derive elasticities, based on the err or-correction (ECM) specification following Engle and Granger (1987). OLS standard deviations are likely to be biased in heterogeneous panels. A circular bootstrap methodology has been used to derive standard deviations and these has bee compared with OLS esti mates. The long term income elasticity for electricity is 0.83 and a price elas ticity of -. 19. The short term price elasticity appears to be higher than the long term price elasticity. The long term income elasticity for fuels is 0.28 and the price elastici ty -. 16. Bootstrapped standard errors are twice as large as OLS estimates, but point estimate s are still statistically significant.
Deep-learning-based object-level contour detection with CCG and CRF optimization

Contour detection is a fundamental problem in computer vision. However, there is still a considerable disparity between detection results and actual contours. To detect object-level contours on the basis of comprehensive analysis of potential edges, we present a deep-learning-based approach with a conditional random fields (CRF) model. We obtain the initial edgemap with a VGGNet-based model, and establish a contour correlation graph (CCG) to describe the potential edges and their relationships. Then a CRF model is adopted to fulfill the optimization on the basis of the analysis of object-level contour characteristics and to predict the validity of candidate contours. The experiment results on various datasets demonstrate that the proposed method outperforms the existing methods by a noticeable margin.