Miracle-dz/UniFAR-FTUs huggingface dataset:
Cavity quantum electro-optics. II. Input-output relations between traveling optical and microwave fields

In the previous paper [M. Tsang, Phys. Rev. A 81, 063837 (2010), e-print arXiv:1003.0116], I proposed a quantum model of a cavity electro-optic modulator, which can coherently couple an optical cavity mode to a microwave resonator mode and enable novel quantum operations on the two modes, including laser cooling of the microwave mode, electro-optic entanglement, and backaction-evading optical measurement of a microwave quadrature. In this sequel, I focus on the quantum input-output relations between traveling optical and microwave fields coupled to a cavity electro-optic modulator. With red-sideband optical pumping, the relations are shown to resemble those of a beam splitter for the traveling fields, so that in the ideal case of zero parasitic loss and critical coupling, microwave photons can be coherently up-converted to "flying" optical photons with unit efficiency, and vice versa. With blue-sideband pumping, the modulator acts as a nondegenerate parametric amplifier, which can generate two-mode squeezing and hybrid entangled photon pairs at optical and microwave frequencies. These fundamental operations provide a potential bridge between circuit quantum electrodynamics and quantum optics.
How the Black/White Paradigm Renders Mexicans/Mexican Americans and Discrimination against Them Invisible

A number of authors have noted the relative lack of attention Mexicans and Mexican Americans receive by academics and popular media alike. ' Scholars, popular print and visual media that attract large audiences all ignore the experiences of Mexicans/Mexican Americans. This lack of attention is apparent in virtually every realm of American society. Discussions concerning discrimination and race/ethnic relations in the United States are no exception. Indeed, the Civil Rights Movement and discourse on race/ethnic relations are almost inextricably intertwined with, and exclusively focused on, the contributions and experiences of Blacks. Some
Effects of Fe spin transition on the elasticity of (Mg, Fe)O magnesiowüstites and implications for the seismological properties of the Earth's lower mantle

High-pressure x-ray diffraction of (Mg{sub 0.8}Fe{sub 0.2})O at room temperature reveals a discontinuity in the bulk modulus at 40 ({+-}5) GPa, similar pressure at which an electronic spin-pairing transition of Fe{sup 2+} is also observed. In the x-ray diffraction experiments the transition is completed only at 80 GPa, possibly reflecting lack of equilibration. Combining recent measurements, we document anomalies in the compression curve of Mg-rich magnesiowuestites that are manifestations of the spin transition. The best fit to a third order Birch-Murnaghan equation for the low-spin phase of magnesiowuestite with 17-20 mol% FeO yields bulk modulus K{sub T0} = 190 ({+-}150) GPa, pressure derivative ({partial_derivative}K{sub T}/{partial_derivative}){sub T0} = 4.6 ({+-}2.7) and unit-cell volume V{sub 0} = 71 ({+-}5) {angstrom}{sup 3}, consistent with past estimates of the ionic radius of octahedrally-coordinated low-spin Fe{sup 2+} in oxides. A sharp spin transition at lower-mantle depths between 1100 and 1900 km (40-80 GPa) would cause a unit-cell volume decrease ({Delta}{nu}{sub {phi}}) of 3.7 ({+-}0.8) to 2.0 ({+-}0.2) percent and bulk sound velocity increase ({Delta}{nu}{sub {phi}}) of 8.1 ({+-}6-1.7) percent ({nu}{sub {phi}} = {radical}K{sub s}/{rho}). Even in the absence of a visible seismic discontinuity, we expect the Fe-spin transition to imply a correction to current compositionalmore » models of the lower mantle, with up to 10 mol percent increase of magnesiowuestite being required to match the seismological data. « less
Clinical application of targeted next-generation sequencing for colorectal cancer patients: a multicentric Belgian experience

International guidelines made RAS (KRAS and NRAS) status a prerequisite for the use of anti-EGFR agents for metastatic colorectal cancer (CRC) patients. Daily, new data emerges on the theranostic and prognostic role of molecular biomarkers; this is a strong incentive for a validated, sensitive, and broadly available molecular screening test. Next-generation sequencing (NGS) has begun to supplant other technologies for genomic profiling. We report here our 2 years of clinical practice using NGS results to guide therapeutic decisions. The Ion Torrent AmpliSeq colon/lung cancer panel, which allows mutation detection in 22 cancer-related genes, was prospectively used in clinical practice (BELAC ISO 15189 accredited method). The DNA of 741 formalin-fixed paraffin-embedded CRC tissues, including primary tumors and metastasis, was obtained from 14 different Belgian institutions and subjected to targeted NGS. Of the tumors tested, 98% (727) were successfully sequenced and 89% (650) harbored at least one mutation. KRAS, BRAF and NRAS mutations were found in 335 (46%), 78 (11%) and 32 (4%) samples, respectively. These mutation frequencies were consistent with those reported in public databases. Moreover, mutations and amplifications in potentially actionable genes were identified in 464 samples (64%), including mutations in PIK3CA (14%), ERBB2 (0.4%), AKT1 (0.6%), and MAP2K1 (0.1%), as well as amplifications of ERBB2 (0.3%) and EGFR (0.3%). The median turnaround time between reception of the sample in the laboratory and report release was 8 calendar days. Overall, the AmpliSeq colon/lung cancer panel was successfully applied in daily practice and provided reliable clinically relevant information for CRC patients.
Performance evaluation of iterative LDPC-coded MIMO OFDM system with time interleaving in mobile line-of-sight environments

Iterative low-density parity-check (LDPC) coded multiple-input multiple-output (MIMO) systems are known to be able to theoretically achieve excellent performance by computer simulation. If the systems can exploit time interleaving long enough to cover a fading cycle, excellent error rate performance should be obtained in mobile line-of-sight (LOS) environments. This paper describes an iterative LDPC minimum mean square error with soft interference cancellation (LDPC-MMSE-SIC) receiver with a time de-interleaver before the MMSE detector and evaluates it using channel state information (CSI) acquired in outdoor measurements. We show that the iterative receiver with time interleaving improves the error rate performance significantly in mobile LOS environments and outperforms an LDPC maximum likelihood detection (LDPC-MLD) receiver with the same error correction and interleaving.
Tumor Cell–Accelerated Senescence Is Associated With DNA-PKcs Status and Telomere Dysfunction Induced by Radiation

Whether telomere structure integrity is related to radiosensitivity is not well investigated thus far. In this study, we investigated the relation between telomere instability and radiation-induced accelerated senescence. Partial knockdown of DNA-dependent catalytic subunit of protein kinase (DNA-PKcs) in human breast cancer cell line MCF-7 was established by small interfering RNA. Radiosensitivity of control and DNA-PKcs knockdown MCF-7 cells was analyzed by clonogenetic assay. Cell growth was measured by real-time cell electronic sensing. Senescence and apoptosis were evaluated by β-galactosidase histochemical staining and fluorescence-activated cell sorting, respectively. DNA damage was determined by long polymerase chain reaction (PCR). Telomere length and integrity were analyzed by real-time PCR and cytogenetic assay, respectively. DNA-PKcs knockdown MCF-7 cells were more sensitive to X-irradiation than control cells. Further investigation revealed that accelerated senescence is more pronounced than apoptosis in cells after radiation, particularly in DNA-PKcs knockdown cells. The cytogenetic assay and kinetics of DNA damage repair revealed that the role of telomere end-capping in DNA-PKcs, rather than DNA damage repair, was more relevant to radiosensitivity. To our knowledge, this is the first study to show that DNA-PKcs plays an important role in radiation-induced accelerated senescence via maintenance of telomere integrity in MCF-7 cells. These results could be useful for future understanding of the radiation-induced genome instability and its consequences.
Survival of the feces: Does a nematode lungworm adaptively manipulate the behavior of its cane toad host?

Abstract Parasites can enhance their fitness by modifying the behavior of their hosts in ways that increase rates of production and transmission of parasite larvae. We used an antihelminthic drug to experimentally alter infections of lungworms (Rhabdias pseudosphaerocephala) in cane toads (Rhinella marina). We then compared subsequent behaviors of dewormed toads versus toads that retained infections. Both in the laboratory and in the field, the presence of parasites induced hosts to select higher body temperatures (thereby increasing rates of lungworm egg production), to defecate in moister sites, and to produce feces with higher moisture content (thereby enhancing survival of larvae shed in feces). Because those behavioral modifications enhance rather than decrease parasite fitness, they are likely to have arisen as adaptive manipulations of host behavior rather than as host adaptations to combat infection or as nonadaptive consequences of infection on host physiology. However, the mechanisms by which lungworms alter cane toad thermal preference and defecation are not known. Although many examples of host manipulation by parasites involve intermediate hosts facilitating their own demise, our findings indicate that manipulation of definitive hosts can be as subtle as when and where to defecate.
Learning from Interpretation Transition using Feed-Forward Neural Networks

Abstract. Understanding the evolution of dynamical systems is an ILP topic with many application domains, e.g., multi-agent systems, robotics and systems biology. In this paper, we present a method relying on an artiﬁcial neural network (NN) to learn rules describing the evolution of a dynamical system of Boolean variables. The experimental results show the potential of this approach, which opens the way to many extensions naturally supported by NNs, such as the handling of noisy data, continuous variables or time delayed systems.
Soluble Fgl2 restricts autoimmune hepatitis progression via suppressing Tc17 and conventional CD8+ T cell function

Autoimmune hepatitis (AIH) is an inflammatory disease caused by an aberrant immune response to hepatic self‐antigens in which regulatory T cells (Tregs) are critical for maintaining immunosupression. The soluble form of fibrinogen‐like protein 2 (sFGL2), a novel effector molecule of Treg, is rarely investigated in AIH. In the present study, we dissected the role of sFGL2 in autoimmune hepatitis and its potential mechanism underlying AIH progression.
Use of agricultural statistics to verify the interannual variability in land surface models: a case study over France with ISBA-A-gs

Abstract. In order to verify the interannual variability of the above-ground biomass of herbaceous vegetation simulated by the ISBA-A-gs land surface model, within the SURFEX modelling platform, French agricultural statistics for C3 crops and grasslands were compared with the simulations for the 1994–2008 period. While excellent correlations are obtained for grasslands, representing the interannual variability of crops is more difficult. It is shown that, the Maximum Available soil Water Capacity (MaxAWC) has a large influence on the correlation between the model and the agricultural statistics. In particular, high values of MaxAWC tend to reduce the impact of the climate interannual variability on the simulated biomass. Also, high values of MaxAWC allow the simulation of a negative trend in biomass production, in relation to a marked warming trend, of about 0.12 Kyr−1 on average, affecting the daily maximum air temperature during the growing period (April–June). This trend is particularly acute in Northern France. The estimates of MaxAWC for C3 crops and grasslands, currently used in SURFEX, are about 129 mm and do not vary much. Therefore, more accurate grid-cell values of this parameter are needed.
The effect of an out-of-school mindfulness program on adolescents’ stress reduction and emotional wellbeing

In recent years schools and youth-serving organizations have progressively adopted programs to reduce adolescents’ stress levels and improve optimism trough mindfulness interventions. The aim of this study was to examine the effects of a mindfulness out-of-school program for adolescents, on perceived levels of stress, optimism and mindfulness skills. Thirty adolescents (15 girls and 15 boys), aging from 16 to 18 years old ( M = 16.8) were randomly allocated to either 8-week mindfulness extracurricular program (n = 15; 8 girls and 7 boys) or a control group (n = 15; 7 girls and 8 boys). The results demonstrate that participants in the intervention group reported reductions in perceived stress and increases in levels of optimism and in five specific mindfulness skills. These findings suggest that using an out-of-school mindfulness program may be an effective setting to teach adolescents to use mindfulness to manage stress and to cultivate more positive emotional and social skills. This study is therefore significant for encourage the implementation of out-of-school mindfulness program that contribute to positive youth development and for an improvement of their health and more holistic health and well-being.
Multi-Party Competition: A Computational Model with Abstention and Biased Voters

This paper analyses the properties of a computational model of multi-party competition in two and three policy dimensions. We present four substantive results: Firstly, centrifugal incentives prevent rational parties from moving to the mean of voters' preference distributions. Secondly, the number of parties competing for votes and the inclination to abstain from voting are positively related to parties' optimum distance to the political centre. Thirdly, the number of parties in the political arena also increases both the distance between parties' location in the policy space and the inter-temporal volatility of their platforms. Finally, assuming that voters rely on past observations of partisan positioning behaviour in order to assess the credibility of parties, this memory of a party's record is positively related to both the distances between partisan platforms and their deviation from the mean of voters' preferences but has a dampening effect for platform volatility.
Variety Wins: Soccer-Playing Robots and Infant Walking

Although both infancy and artificial intelligence (AI) researchers are interested in developing systems that produce adaptive, functional behavior, the two disciplines rarely capitalize on their complementary expertise. Here, we used soccer-playing robots to test a central question about the development of infant walking. During natural activity, infants' locomotor paths are immensely varied. They walk along curved, multi-directional paths with frequent starts and stops. Is the variability observed in spontaneous infant walking a “feature” or a “bug? ” In other words, is variability beneficial for functional walking performance? To address this question, we trained soccer-playing robots on walking paths generated by infants during free play and tested them in simulated games of “RoboCup. ” In Tournament 1, we compared the functional performance of a simulated robot soccer team trained on infants' natural paths with teams trained on less varied, geometric paths—straight lines, circles, and squares. Across 1,000 head-to-head simulated soccer matches, the infant-trained team consistently beat all teams trained with less varied walking paths. In Tournament 2, we compared teams trained on different clusters of infant walking paths. The team trained with the most varied combination of path shape, step direction, number of steps, and number of starts and stops outperformed teams trained with less varied paths. This evidence indicates that variety is a crucial feature supporting functional walking performance. More generally, we propose that robotics provides a fruitful avenue for testing hypotheses about infant development; reciprocally, observations of infant behavior may inform research on artificial intelligence.
Video Analytics for Customer Emotion and Satisfaction at Contact Centers

Due to the high levels of competition in a global market, companies have put more emphasis on building strong customer relationships and increasing customer satisfaction levels. With technological improvements in information and communication technologies, a highly anticipated key contributor to improve the customer experience and satisfaction in service episodes is through the application of video analytics, such as to evaluate the customer's emotions over the full service cycle. Currently, emotion recognition from video is a challenging research area. One of the most effective solutions to address this challenge is to utilize both the audio and visual components as two sources contained in the video data to make an overall assessment of the emotion. The combined use of audio and visual data sources presents additional challenges, such as determining the optimal data fusion technique prior to classification. In this paper, we propose an audio–visual emotion recognition system to detect the universal six emotions (happy, angry, sad, disgust, surprise, and fear) from video data. The detected customer emotions are then mapped and translated to give customer satisfaction scores. The proposed customer satisfaction video analytics system can operate over video conferencing or video chat. The effectiveness of our proposal is verified through numerical results.
A Point-of-Interest Recommendation Method Using Location Similarity

POI recommendation aims to recommend places which users have not visited before. In this paper, we proposed a POI recommendation method using location similarity, which assumes that people may be interested in the places that are similar with the places that they have been to before. In order to calculate the similarity of locations, we proposed a novel method using time slots. Every two hours can be considered as a time slot. In other words, one day can be segmented into 12 time slots. For each location, the check-in times in each time slot can be collected. These check-in times can form a vector, which can be used to calculate the similarity of two locations. According to the similarity, the score of each unvisited locations can be calculated and sorted. Finally, the POI recommendation can be generated from the top-n unvisited locations. The experiment results show that the proposed method is effective.
Retroperitoneal Sarcoma - A Diagnostic Challenge with Only a Surgical Cure

Sarcomas are solid tumours of mesenchymal cell origin and account for 1% of all adult malignancies. Retroperitoneal sarcomas more commonly affect people in their 50’s who can present to a general surgeon for assessment of non-specific abdominal symptoms. This nature of their presentation and anatomical location provides a diagnostic challenge and initial investigations may be normal. Patients can therefore present late when the tumour is locally advanced. Complete surgical resection with negative macroscopic margins is the treatment of choice and the only proven modality to improve survival and reduce disease recurrence. Extensive resection of multiple organs may be necessary to offer any chance of cure. The benefits of other treatments such as radiotherapy and chemotherapy are less certain. We will present the case of a 63-year-old man who presented with a chronic history of non-specific abdominal symptoms and outline the results of his investigations and subsequent management. We will briefly discuss some of the issue relating to the diagnosis and management of retroperitoneal sarcomas in general.
Graph Signal Sampling via Reinforcement Learning

We model the sampling and recovery of clustered graph signals as a reinforcement learning (RL) problem. The signal sampling is carried out by an agent which crawls over the graph and selects the most relevant graph nodes to sample. The goal of the agent is to select signal samples which allow for the most accurate recovery. The sample selection is formulated as a multi-armed bandit (MAB) problem, which lends naturally to learning efficient sampling strategies using the well-known gradient MAB algorithm. In a nutshell, the sampling strategy is represented as a probability distribution over the individual arms of the MAB and optimized using gradient ascent. Some illustrative numerical experiments indicate that the sampling strategies obtained from the gradient MAB algorithm outperform existing sampling methods.
EDC: Improving the Performance and Space Efficiency of Flash-Based Storage Systems with Elastic Data Compression

By leveraging data reduction technologies, such as data compression, all flash-based storage systems can have the same total cost of ownership (TCO) as traditional HDD-based storage systems. Thus, data compression has become a commodity feature for space efficiency and reliability in flash-based storage systems by reducing write traffic and space capacity demand. However, it introduces noticeable processing overheads on the critical I/O path, which degrades the system performance significantly. Existing data compression schemes for flash-based storage systems use fixed compression algorithms for all the incoming write data, failing to recognize and exploit the significant diversity in compressibility and access patterns of data and missing an opportunity to improve the system performance, the space efficiency or both. To achieve a reasonable trade-off between these two important design objectives, in this paper we introduce an Elastic Data Compression scheme, called EDC, which exploits the data compressibility and access intensity characteristics by judiciously matching data of different compressibility with different compression algorithms while leveraging the access idleness. Specifically, for compressible data blocks EDC exploits the compression diversity of the workload, and employs algorithms of higher compression rate in periods of lower system utilization and algorithms of lower compression rate in periods of higher system utilization. For non-compressible (or very lowly compressible) data blocks, it will write them through to the flash storage directly without any compression. The experiments conducted on our lightweight prototype implementation of the EDC system show that EDC saves storage space by up to 38.7 percent, with an average of 33.7 percent . In addition, it significantly outperforms the fixed compression schemes in the I/O performance measure by up to 61.4 percent, with an average of 36.7 percent.
A 0.02 Ppb/Step Wide Range DCXO Based on Time-Average-Frequency: Demonstration on FPGA

Frequency source is one of the foundational elements in electronics. It is used to derive clock signal that establishes the sense of time inside electronic system. An important type of frequency source is the one whose frequency can be adjusted through external control, such as VCXO and DCXO. This type of frequency-adjustable source is useful for many applications such as Doppler radar, frequency modulation, data transmission, telemetry, and telecommunication among others. Frequency adjustability and frequency stability are two requirements that contradict each other. The solution is usually a compromise among factors of performance, power, cost and size. Time-Average-Frequency Direct Period Synthesis (TAF-DPS) is an emerging frequency synthesis technique that provides a new perspective on solving this problem. In this work, a TAF-DPS based DCXO architecture is presented. The architecture is proven with an implementation on FPGA. Its frequency granularity is achieved at 0.02 ppb/step, monotonicity is mathematically guaranteed, tuning range is virtually unlimited. The linearity within a 1% range of 26 MHz is measured as 0.005%.