1,550 research outputs found

    Doped GaSe crystals for laser frequency conversion

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    In this review, we introduce the current state of the art of the growth technology of pure, lightly doped, and heavily doped (solid solution) nonlinear gallium selenide (GaSe) crystals that are able to generate broadband emission from the near infrared (IR) (0.8 mm) through the mid- and far-IR (terahertz (THz)) ranges and further into the millimeter wave (5.64 mm) range. For the first time, we show that appropriate doping is an efficient method controlling a range of the physical properties of GaSe crystals that are responsible for frequency conversion efficiency and exploitation parameters. After appropriate doping, uniform crystals grown by a modified technology with heat field rotation possess up to 3 times lower absorption coefficient in the main transparency window and THz range. Moreover, doping provides the following benefits: raises by up to 5 times the optical damage threshold; almost eliminates two-photon absorption; allows for dispersion control in the THz range independent of the mid-IR dispersion; and enables crystal processing in arbitrary directions due to the strengthened lattice. Finally, doped GaSe demonstrated better usefulness for processing compared with GaSe grown by the conventional technology and up to 15 times higher frequency conversion efficiency

    Secrets of RLHF in Large Language Models Part I: PPO

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    Large language models (LLMs) have formulated a blueprint for the advancement of artificial general intelligence. Its primary objective is to function as a human-centric (helpful, honest, and harmless) assistant. Alignment with humans assumes paramount significance, and reinforcement learning with human feedback (RLHF) emerges as the pivotal technological paradigm underpinning this pursuit. Current technical routes usually include \textbf{reward models} to measure human preferences, \textbf{Proximal Policy Optimization} (PPO) to optimize policy model outputs, and \textbf{process supervision} to improve step-by-step reasoning capabilities. However, due to the challenges of reward design, environment interaction, and agent training, coupled with huge trial and error cost of large language models, there is a significant barrier for AI researchers to motivate the development of technical alignment and safe landing of LLMs. The stable training of RLHF has still been a puzzle. In the first report, we dissect the framework of RLHF, re-evaluate the inner workings of PPO, and explore how the parts comprising PPO algorithms impact policy agent training. We identify policy constraints being the key factor for the effective implementation of the PPO algorithm. Therefore, we explore the PPO-max, an advanced version of PPO algorithm, to efficiently improve the training stability of the policy model. Based on our main results, we perform a comprehensive analysis of RLHF abilities compared with SFT models and ChatGPT. The absence of open-source implementations has posed significant challenges to the investigation of LLMs alignment. Therefore, we are eager to release technical reports, reward models and PPO code

    A local outbreak of dengue caused by an imported case in Dongguan China

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    <p>Abstract</p> <p>Background</p> <p>Dengue, a mosquito-borne febrile viral disease, is found in tropical and sub-tropical regions around the world. Since the first occurrence of dengue was confirmed in Guangdong, China in 1978, dengue outbreaks have been reported sequentially in different provinces in South China transmitted by<sup>.</sup>peridomestic <it>Ae. albopictus </it>mosquitoes, diplaying <it>Ae. aegypti</it>, a fully domestic vector that transmits dengue worldwide. Rapid and uncontrolled urbanization is a characteristic change in developing countries, which impacts greatly on vector habitat, human lifestyle and transmission dynamics on dengue epidemics. In September 2010, an outbreak of dengue was detected in Dongguan, a city in Guangdong province characterized by its fast urbanization. An investigation was initiated to identify the cause, to describe the epidemical characteristics of the outbreak, and to implement control measures to stop the outbreak. This is the first report of dengue outbreak in Dongguan, even though dengue cases were documented before in this city.</p> <p>Methods</p> <p>Epidemiological data were obtained from local Center of Disease Control and prevention (CDC). Laboratory tests such as real-time Reverse Transcription Polymerase Chain Reaction (RT-PCR), the virus cDNA sequencing, and Enzyme-Linked immunosorbent assay (ELISA) were employed to identify the virus infection and molecular phylogenetic analysis was performed with MEGA5. The febrile cases were reported every day by the fever surveillance system. Vector control measures including insecticidal fogging and elimination of habitats of <it>Ae. albopictus </it>were used to control the dengue outbreak.</p> <p>Results</p> <p>The epidemiological studies results showed that this dengue outbreak was initiated by an imported case from Southeast Asia. The outbreak was characterized by 31 cases reported with an attack rate of 50.63 out of a population of 100,000. <it>Ae. albopictus </it>was the only vector species responsible for the outbreak. The virus cDNA sequencing analysis showed that the virus responsible for the outbreak was Dengue Virus serotype-1 (DENV-1).</p> <p>Conclusions</p> <p>Several characterized points of urbanization contributed to this outbreak of dengue in Dongguan: the residents are highly concentrated; the residents' life habits helped to form the habitats of <it>Ae. albopictus </it>and contributed to the high Breteau Index; the self-constructed houses lacks of mosquito prevention facilities. This report has reaffirmed the importance of a surveillance system for infectious diseases control and aroused the awareness of an imported case causing the epidemic of an infectious disease in urbanized region.</p

    Contactless multiscale measurement of cardiac motion using biomedical radar sensor

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    IntroductionA contactless multiscale cardiac motion measurement method is proposed using impulse radio ultra-wideband (IR-UWB) radar at a center frequency of 7.29 GHz.MotivationElectrocardiograph (ECG), heart sound, and ultrasound are traditional state-of-the-art heartbeat signal measurement methods. These methods suffer from defects in contact and the existence of a blind information segment during the cardiogram measurement.MethodsExperiments and analyses were conducted using coarse-to-fine scale. Anteroposterior and along-the-arc measurements were taken from five healthy male subjects (aged 25–43) when lying down or prone. In every measurement, 10 seconds of breath-holding data were recorded with a radar 55 cm away from the body surface, while the ECG was monitored simultaneously as a reference.ResultsCardiac motion detection from the front was superior to that from the back in amplitude. In terms of radar detection angles, the best cardiac motion information was observed at a detection angle of 120°. Finally, in terms of cardiac motion cycles, all the ECG information, as well as short segments of cardiac motion details named blind ECGs segments, were detected.SignificanceA contactless and multiscale cardiac motion detection method is proposed with no blind detection of segments during the entire cardiac cycle. This paves the way for a potentially significant method of fast and accurate cardiac disease assessment and diagnosis that exhibits promising application prospects in contactless online cardiac monitoring and in-home healthcare

    Visualized exploratory spatiotemporal analysis of hand-foot-mouth disease in southern China

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    Objectives: In epidemiological research, major studies have focused on theoretical models; however, few methods of visual analysis have been used to display the patterns of disease distribution.Design: For this study, a method combining the space-time cube (STC) with space-time scan statistics (STSS) was used to analyze the pattern of incidence of hand-foot-mouth disease (HFMD) in Guangdong Province from May 2008 to March 2009. In this research, STC was used to display the spatiotemporal pattern of incidence of HFMD, and STSS were used to detect the local aggregations of the disease.Setting: The hand-foot-mouth disease data were obtained from Guangdong Province from May 2008 to March 2009, with a total of 68,130 cases.Results: The STC analysis revealed a differential pattern of HFMD incidence among different months and cities and also showed that the population density and average precipitation are correlated with the incidence of HFMD. The STSS analysis revealed that the most likely aggregation includes the Shenzhen, Foshan and Dongguan populations, which are the most developed regions in Guangdong Province.Conclusion: Both STC and STSS are efficient tools for the exploratory data analysis of disease transmission. STC clearly displays the spatiotemporal patterns of disease. Using the maximum likelihood ratio, the STSS model precisely locates the most likely aggregation

    Area Disease Estimation Based on Sentinel Hospital Records

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    BACKGROUND: Population health attributes (such as disease incidence and prevalence) are often estimated using sentinel hospital records, which are subject to multiple sources of uncertainty. When applied to these health attributes, commonly used biased estimation techniques can lead to false conclusions and ineffective disease intervention and control. Although some estimators can account for measurement error (in the form of white noise, usually after de-trending), most mainstream health statistics techniques cannot generate unbiased and minimum error variance estimates when the available data are biased. METHODS AND FINDINGS: A new technique, called the Biased Sample Hospital-based Area Disease Estimation (B-SHADE), is introduced that generates space-time population disease estimates using biased hospital records. The effectiveness of the technique is empirically evaluated in terms of hospital records of disease incidence (for hand-foot-mouth disease and fever syndrome cases) in Shanghai (China) during a two-year period. The B-SHADE technique uses a weighted summation of sentinel hospital records to derive unbiased and minimum error variance estimates of area incidence. The calculation of these weights is the outcome of a process that combines: the available space-time information; a rigorous assessment of both, the horizontal relationships between hospital records and the vertical links between each hospital's records and the overall disease situation in the region. In this way, the representativeness of the sentinel hospital records was improved, the possible biases of these records were corrected, and the generated area incidence estimates were best linear unbiased estimates (BLUE). Using the same hospital records, the performance of the B-SHADE technique was compared against two mainstream estimators. CONCLUSIONS: The B-SHADE technique involves a hospital network-based model that blends the optimal estimation features of the Block Kriging method and the sample bias correction efficiency of the ratio estimator method. In this way, B-SHADE can overcome the limitations of both methods: Block Kriging's inadequacy concerning the correction of sample bias and spatial clustering; and the ratio estimator's limitation as regards error minimization. The generality of the B-SHADE technique is further demonstrated by the fact that it reduces to Block Kriging in the case of unbiased samples; to ratio estimator if there is no correlation between hospitals; and to simple statistic if the hospital records are neither biased nor space-time correlated. In addition to the theoretical advantages of the B-SHADE technique over the two other methods above, two real world case studies (hand-foot-mouth disease and fever syndrome cases) demonstrated its empirical superiority, as well

    Evasion of anti-growth signaling: a key step in tumorigenesis and potential target for treatment and prophylaxis by natural compounds

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    The evasion of anti-growth signaling is an important characteristic of cancer cells. In order to continue to proliferate, cancer cells must somehow uncouple themselves from the many signals that exist to slow down cell growth. Here, we define the anti-growth signaling process, and review several important pathways involved in growth signaling: p53, phosphatase and tensin homolog (PTEN), retinoblastoma protein (Rb), Hippo, growth differentiation factor 15 (GDF15), AT-rich interactive domain 1A (ARID1A), Notch, insulin-like growth factor (IGF), and Krüppel-like factor 5 (KLF5) pathways. Aberrations in these processes in cancer cells involve mutations and thus the suppression of genes that prevent growth, as well as mutation and activation of genes involved in driving cell growth. Using these pathways as examples, we prioritize molecular targets that might be leveraged to promote anti-growth signaling in cancer cells. Interestingly, naturally-occurring phytochemicals found in human diets (either singly or as mixtures) may promote anti-growth signaling, and do so without the potentially adverse effects associated with synthetic chemicals. We review examples of naturally-occurring phytochemicals that may be applied to prevent cancer by antagonizing growth signaling, and propose one phytochemical for each pathway. These are: epigallocatechin-3-gallate (EGCG) for the Rb pathway, luteolin for p53, curcumin for PTEN, porphyrins for Hippo, genistein for GDF15, resveratrol for ARID1A, withaferin A for Notch and diguelin for the IGF1-receptor pathway. The coordination of anti-growth signaling and natural compound studies will provide insight into the future application of these compounds in the clinical setting

    Measurement of the cross-section and charge asymmetry of WW bosons produced in proton-proton collisions at s=8\sqrt{s}=8 TeV with the ATLAS detector

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    This paper presents measurements of the W+μ+νW^+ \rightarrow \mu^+\nu and WμνW^- \rightarrow \mu^-\nu cross-sections and the associated charge asymmetry as a function of the absolute pseudorapidity of the decay muon. The data were collected in proton--proton collisions at a centre-of-mass energy of 8 TeV with the ATLAS experiment at the LHC and correspond to a total integrated luminosity of 20.2~\mbox{fb^{-1}}. The precision of the cross-section measurements varies between 0.8% to 1.5% as a function of the pseudorapidity, excluding the 1.9% uncertainty on the integrated luminosity. The charge asymmetry is measured with an uncertainty between 0.002 and 0.003. The results are compared with predictions based on next-to-next-to-leading-order calculations with various parton distribution functions and have the sensitivity to discriminate between them.Comment: 38 pages in total, author list starting page 22, 5 figures, 4 tables, submitted to EPJC. All figures including auxiliary figures are available at https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/STDM-2017-13

    Search for doubly charged Higgs boson production in multi-lepton final states with the ATLAS detector using proton-proton collisions at √s = 13TeV

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    A search for doubly charged Higgs bosons with pairs of prompt, isolated, highly energetic leptons with the same electric charge is presented. The search uses a proton–proton collision data sample at a centre-of-mass energy of 13 TeV corresponding to 36.1 fb −1 of integrated luminosity recorded in 2015 and 2016 by the ATLAS detector at the LHC. This analysis focuses on the decays H±±→e±e±, H±±→e±μ± and H±±→μ±μ±, fitting the dilepton mass spectra in several exclusive signal regions. No significant evidence of a signal is observed and corresponding limits on the production cross-section and consequently a lower limit on m(H±±) are derived at 95% confidence level. With ℓ±ℓ±=e±e±/μ±μ±/e±μ±, the observed lower limit on the mass of a doubly charged Higgs boson only coupling to left-handed leptons varies from 770 to 870 GeV (850 GeV expected) for B(H±±→ℓ±ℓ±)=100% and both the expected and observed mass limits are above 450 GeV for B(H±±→ℓ±ℓ±)=10% and any combination of partial branching ratios
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