Probing triple-Higgs productions via 4b2γ4b2\gamma decay channel at a 100 TeV hadron collider

The quartic self-coupling of the Standard Model Higgs boson can only be measured by observing the triple-Higgs production process, but it is challenging for the Large Hadron Collider (LHC) Run 2 or International Linear Collider (ILC) at a few TeV because of its extremely small production rate. In this paper, we present a detailed Monte Carlo simulation study of the triple-Higgs production through gluon fusion at a 100 TeV hadron collider and explore the feasibility of observing this production mode. We focus on the decay channel $HHH\rightarrow b\bar{b}b\bar{b}\gamma\gamma$, investigating detector effects and optimizing the kinematic cuts to discriminate the signal from the backgrounds. Our study shows that, in order to observe the Standard Model triple-Higgs signal, the integrated luminosity of a 100 TeV hadron collider should be greater than $1.8\times 10^4$ ab$^{-1}$. We also explore the dependence of the cross section upon the trilinear ($\lambda_3$) and quartic ($\lambda_4$) self-couplings of the Higgs. We find that, through a search in the triple-Higgs production, the parameters $\lambda_3$ and $\lambda_4$ can be restricted to the ranges $[-1, 5]$ and $[-20, 30]$, respectively. We also examine how new physics can change the production rate of triple-Higgs events. For example, in the singlet extension of the Standard Model, we find that the triple-Higgs production rate can be increased by a factor of $\mathcal{O}(10)$.Comment: 33 pages, 11 figures, added references, corrected typos, improved text, affiliation is changed. This is the publication versio

Neural Fourier Filter Bank

We present a novel method to provide efficient and highly detailed reconstructions. Inspired by wavelets, we learn a neural field that decompose the signal both spatially and frequency-wise. We follow the recent grid-based paradigm for spatial decomposition, but unlike existing work, encourage specific frequencies to be stored in each grid via Fourier features encodings. We then apply a multi-layer perceptron with sine activations, taking these Fourier encoded features in at appropriate layers so that higher-frequency components are accumulated on top of lower-frequency components sequentially, which we sum up to form the final output. We demonstrate that our method outperforms the state of the art regarding model compactness and convergence speed on multiple tasks: 2D image fitting, 3D shape reconstruction, and neural radiance fields. Our code is available at https://github.com/ubc-vision/NFFB

Changing Patterns of Spatial Clustering of Schistosomiasis in Southwest China between 1999–2001 and 2007–2008: Assessing Progress toward Eradication after the World Bank Loan Project

We compared changes in the spatial clustering of schistosomiasis in Southwest China at the conclusion of and six years following the end of the World Bank Loan Project (WBLP), the control strategy of which was focused on the large-scale use of chemotherapy. Parasitological data were obtained through standardized surveys conducted in 1999–2001 and again in 2007–2008. Two alternate spatial cluster methods were used to identify spatial clusters of cases: Anselin’s Local Moran’s I test and Kulldorff’s spatial scan statistic. Substantial reductions in the burden of schistosomiasis were found after the end of the WBLP, but the spatial extent of schistosomiasis was not reduced across the study area. Spatial clusters continued to occur in three regions: Chengdu Plain, Yangtze River Valley, and Lancang River Valley during the two periods, and regularly involved five counties. These findings suggest that despite impressive reductions in burden, the hilly and mountainous regions of Southwest China remain at risk of schistosome re-emergence. Our results help to highlight specific locations where integrated control programs can focus to speed the elimination of schistosomiasis in China

Unraveling Trends in Schistosomiasis: Deep Learning insights into National Control Programs in China

OBJECTIVES: to achieve the ambitious goal of eliminating schistosome infections, the Chinese government has implemented diverse control strategies. This study explored the progress of the 2 most recent national schistosomiasis control programs in an endemic area along the Yangtze River in China. METHODS: We obtained village-level parasitological data from cross-sectional surveys combined with environmental data in Anhui Province, China from 1997 to 2015. A convolutional neural network (CNN) based on a hierarchical integro-difference equation (IDE) framework (i.e., CNN-IDE) was used to model spatio-temporal variations in schistosomiasis. Two traditional models were also constructed for comparison with 2 evaluation indicators: the mean-squared prediction error (MSPE) and continuous ranked probability score (CRPS). RESULTS: The CNN-IDE model was the optimal model, with the lowest overall average MSPE of 0.04 and the CRPS of 0.19. From 1997 to 2011, the prevalence exhibited a notable trend: it increased steadily until peaking at 1.6 per 1000 in 2005, then gradually declined, stabilizing at a lower rate of approximately 0.6 per 1000 in 2006, and approaching zero by 2011. During this period, noticeable geographic disparities in schistosomiasis prevalence were observed; high-risk areas were initially dispersed, followed by contraction. Predictions for the period 2012 to 2015 demonstrated a consistent and uniform decrease. CONCLUSION: The proposed CNN-IDE model captured the intricate and evolving dynamics of schistosomiasis prevalence, offering a promising alternative for future risk modeling of the disease. The comprehensive strategy is expected to help diminish schistosomiasis infection, emphasizing the necessity to continue implementing this strategy

Anti-artifacts techniques for neural recording front-ends in closed-loop brain-machine interface ICs

In recent years, thanks to the development of integrated circuits, clinical medicine has witnessed significant advancements, enabling more efficient and intelligent treatment approaches. Particularly in the field of neuromedical, the utilization of brain-machine interfaces (BMI) has revolutionized the treatment of neurological diseases such as amyotrophic lateral sclerosis, cerebral palsy, stroke, or spinal cord injury. The BMI acquires neural signals via recording circuits and analyze them to regulate neural stimulator circuits for effective neurological treatment. However, traditional BMI designs, which are often isolated, have given way to closed-loop brain-machine interfaces (CL-BMI) as a contemporary development trend. CL-BMI offers increased integration and accelerated response speed, marking a significant leap forward in neuromedicine. Nonetheless, this advancement comes with its challenges, notably the stimulation artifacts (SA) problem inherent to the structural characteristics of CL-BMI, which poses significant challenges on the neural recording front-ends (NRFE) site. This paper aims to provide a comprehensive overview of technologies addressing artifacts in the NRFE site within CL-BMI. Topics covered will include: (1) understanding and assessing artifacts; (2) exploring the impact of artifacts on traditional neural recording front-ends; (3) reviewing recent technological advancements aimed at addressing artifact-related issues; (4) summarizing and classifying the aforementioned technologies, along with an analysis of future trends

Implications from assessing environmental effects on spatio-temporal pattern of schistosomiasis in the Yangtze Basin, China

Schistosomiasis remains a major public health problem in the South China, particularly in lake and marshland regions. Modelling the spatio-temporal pattern of schistosomiasis guides disease prevention and control programs and is a research area of growing interest. However, few attempts have been made to evaluate the changing (nonlinear) effects of environmental determinants on schistosomiasis. In this context, a hierarchical spatiotemporal model was applied to evaluate how environmental determinants affect the changing trend of schistosomiasis in Anhui Province, China, based on annual parasitological and environmental data for the period 1997-2010. Results showed that – compared to changing effect – environmental factors had a constant (linear) effect on schistosomiasis. The disease was also found to fluctuate over time, which was due to the two latest national schistosomiasis control programs. In addition to statistical benefits of this approach, our analysis implied that climate change might not contribute to variation of schistosomiasis; rather, prevention activities affect schistosomiasis when the disease prevalence remains at a low level. Finally, the analytical method proposed in our study provides a template for modelling the spatio-temporal pattern of a disease whose transmission is largely determined by environmental determinants

Report drawn up on behalf of the Committee on Economic and Monetary Affairs on the possible loan from the OPEC countries to the Federal Republic of Germany and to France. EP Working Documents 1982-83, Document 1-284/82, 4 June 1982

Abstract Background Hand, foot, and mouth disease (HFMD) has become an emerging infectious disease in China in the last decade. There has been evidence that meteorological factors can influence the HFMD incidence, and understanding the mechanisms can help prevent and control HFMD. Methods HFMD incidence data and meteorological data in Minhang District, Shanghai were obtained for the period between 2009 and 2015. Distributed lag non-linear models (DLNMs) were utilized to investigate the impact of meteorological factors on HFMD incidence after adjusting for potential confounders of long time trend, weekdays and holidays. Results There was a non-linear relationship between temperature and HFMD incidence, the RR of 5th percentile compared to the median is 0.836 (95% CI: 0.671–1.042) and the RR of 95th percentile is 2.225 (95% CI: 1.774–2.792), and the effect of temperature varied across age groups. HFMD incidence increased with increasing average relative humidity (%) (RR = 1.009, 95% CI: 1.005–1.015) and wind speed (m/s) (RR = 1.197, 95% CI: 1.118–1.282), and with decreasing daily rainfall (mm) (RR = 0.992, 95% CI: 0.987–0.997) and sunshine hours (h) (RR = 0.966, 95% CI: 0.951–0.980). Conclusions There were significant relationships between meteorological factors and childhood HFMD incidence in Minhang District, Shanghai. This information can help local health agencies develop strategies for the control and prevention of HFMD under specific climatic conditions

An XMM-Newton View of the ANdromeda Galaxy as Explored in a Legacy Survey (New-ANGELS) I: the X-ray Source Catalogue

We introduce the New-ANGELS program, an XMM-Newton survey of $\sim7.2\rm~deg^2$ area around M 31, which aims to study the X-ray populations in M 31 disk and the X-ray emitting hot gas in the inner halo of M 31 up to 30 kpc. In this first paper, we report the catalogue of 4506 detected X-ray sources, and attempt to cross-identify or roughly classify them. We identify 352 single stars in the foreground, 35 globular clusters and 27 supernova remnants associated with M 31, as well as 62 AGNs, 59 galaxies, and 1 galaxy clusters in the background. We uniquely classify 236 foreground stars and 17 supersoft sources based on their X-ray colors. X-ray binaries (83 LMXBs, 1 HMXBs) are classified based on their X-ray colors and X-ray variabilities. The remaining X-ray sources either have too low S/N to calculate their X-ray colors or do not have a unique classification, so are regarded as unclassified. The X-ray source catalogue is published online. Study of the X-ray source populations and the contribution of X-ray sources in the unresolved X-ray emissions based on this catalogue will be published in companion papers.Comment: 30 pages, 12 figures. Accepted for publication in APJ

All-dielectric planar chiral metasurface with gradient geometric phase

Planar optical chirality of a metasurface measures its differential response between left and right circularly polarized (CP) lights and governs the asymmetric transmission of CP lights. In 2D ultra-thin plasmonic structures the circular dichroism is limited to 25% in theory and it requires high absorption loss. Here we propose and numerically demonstrate a planar chiral all-dielectric metasurface that exhibits giant circular dichroism and transmission asymmetry over 0.8 for circularly polarized lights with negligible loss, without bringing in bianisotropy or violating reciprocity. The metasurface consists of arrays of high refractive index germanium Z-shape resonators that break the in-plane mirror symmetry and induce cross-polarization conversion. Furthermore, at the transmission peak of one handedness, the transmitted light is efficiently converted into the opposite circular polarization state, with a designated geometric phase depending on the orientation angle of the optical element. In this way, the optical component sets before and after the metasurface to filter the light of certain circular polarization states are not needed and the metasurface can function under any linear polarization, in contrast to the conventional setup for geometry phase based metasurfaces. Anomalous transmission and two-dimensional holography based on the geometric phase chiral metasurface are numerically demonstrate as proofs of concept