Search

Objectives: Our research adopts computational techniques to analyze disease outbreaks weekly over a large geographic area while maintaining local-level analysis by incorporating relevant high-spatial resolution cultural and environmental datasets. The abundance of data about disease outbreaks gives scientists an excellent opportunity to uncover patterns in disease spread and make future predictions. However, data over a sizeable geographic area quickly outpace human cognition. Our study area covers a significant portion of the African continent (about 17,885,000 km2). The data size makes computational analysis vital to assist human decision-makers. Methods: We first applied global and local spatial autocorrelation for malaria, cholera, meningitis, and yellow fever case counts. We then used machine learning to predict the weekly presence of these diseases in the second-level administrative district. Lastly, we used machine learning feature importance methods on the variables that affect spread. Results: Our spatial autocorrelation results show that geographic nearness is critical but varies in effect and space. Moreover, we identified many interesting hot and cold spots and spatial outliers. The machine learning model infers a binary class of cases or none with the best F1 score of 0.96 for malaria. Machine learning feature importance uncovered critical cultural and environmental factors affecting outbreaks and variations between diseases. Conclusions: Our study shows that data analytics and machine learning are vital to understanding and monitoring disease outbreaks locally across vast areas. The speed at which these methods produce insights can be critical during epidemics and emergencies., Comment: 15 pages, 3 figures, 7 tables

Inclusive electron scattering at carefully chosen kinematics can isolate scattering from short-range correlations (SRCs), produced through hard, short-distance interactions of nucleons in the nucleus. Because the two-nucleon (2N) SRCs arise from the same N-N interaction in all nuclei, the cross section in the SRC-dominated regime is identical up to an overall scaling factor, and the A/2H cross section ratio is constant in this region. This scaling behavior has been used to identify SRC dominance and to map out the contribution of SRCs for a wide range of nuclei. We examine this scaling behavior at lower momentum transfers using new data on $^2$H, $^3$H, and $^3$He which show that the scaling region is larger than in heavy nuclei. Based on the improved scaling, especially for $^3$H/$^3$He, we examine the ratios at kinematics where three-nucleon SRCs may play an important role. The data for the largest initial nucleon momenta are consistent with isolation of scattering from 3N-SRCs, and suggest that the very-highest momentum nucleons in $^3$He have a nearly isospin-independent momentum configuration, or a small enhancement of the proton distribution.

In 2018, the E12-17-003 experiment was conducted at the Thomas Jefferson National Accelerator Facility (JLab) to explore the possible existence of an nnLambda state in the reconstructed missing mass distribution from a tritium gas target [K. N. Suzuki et al., Prog. Theor. Exp. Phys. 2022, 013D01 (2022), B. Pandey et al., Phys. Rev. C 105, L051001 (2022)]. As part of this investigation, data was also collected using a gaseous hydrogen target, not only for a precise absolute mass scale calibration but also for the study of Lambda/Sigma^0 electroproduction. This dataset was acquired at Q^2~0.5 (GeV/c)^2, W=2.14 GeV, and theta_{gamma K}^{c.m.}~8 deg. It covers forward angles where photoproduction data is scarce and a low-Q^2 region that is of interest for hypernuclear experiments. On the other hand, this kinematic region is at a slightly higher Q^2 than previous hypernuclear experiments, thus providing crucial information for understanding the Q^2 dependence of the differential cross sections for Lambda/Sigma^0 hyperon electroproduction. This paper reports on the Q^2 dependence of the differential cross section for the e + p -> e' + K^+ + Lambda/Sigma^0 reaction in the 0.2-0.8 (GeV/c)^2, and provides comparisons with the currently available theoretical models., Comment: 11 pages, 15 figures

Mobile money services in Sub-Saharan Africa (SSA) have increased access to financial services. To ensure proper identification of users, countries have put in place Know-Your-Customer (KYC) measures such as SIM registration using an official identification. However, half of the 850 million people without IDs globally live in SSA, and the use of SIM cards registered in another person's name (third-party SIM) is prevalent. In this study, we explore challenges that contribute to and arise from the use of third-party SIM cards. We interviewed 36 participants in Kenya and Tanzania. Our results highlight great strides in ID accessibility, but also highlight numerous institutional and social factors that contribute to the use of third-party SIM cards. While privacy concerns contribute to the use of third-party SIM cards, third-party SIM card users are exposed to significant security and privacy risks, including scams, financial loss, and wrongful arrest.

The parameterization of the nucleon structure through Generalized Parton Distributions (GPDs) shed a new light on the nucleon internal dynamics. For its direct interpretation, Deeply Virtual Compton Scattering (DVCS) is the golden channel for GPDs investigation. The DVCS process interferes with the Bethe-Heitler (BH) mechanism to constitute the leading order amplitude of the $eN \to eN\gamma$ process. The study of the $ep\gamma$ reaction with polarized positron and electron beams gives a complete set of unique observables to unravel the different contributions to the $ep \gamma$ cross section. This separates the different reaction amplitudes, providing a direct access to their real and imaginary parts which procures crucial constraints on the model dependences and associated systematic uncertainties on GPDs extraction. The real part of the BH-DVCS interference amplitude is particularly sensitive to the $D$-term which parameterizes the Gravitational Form Factors of the nucleon. The separation of the imaginary parts of the interference and DVCS amplitudes provides insights on possible higher-twist effects. We propose to measure the unpolarized and polarized Beam Charge Asymmetries (BCAs) of the $\vec{e}^{\pm}p \to e^{\pm}p \gamma$ process on an unpolarized hydrogen target with {\tt CLAS12}, using polarized positron and electron beams at 10.6 GeV. The azimuthal and $t$-dependences of the unpolarized and polarized BCAs will be measured over a large $(x_B,Q^2)$ phase space using a 100 day run with a luminosity of 0.66$\times 10^{35}$cm$^{-2}\cdot$s$^{-1}$., Comment: Proposal to the Jefferson Lab Program Advisory Committee (PAC51)

Digital financial services have catalyzed financial inclusion in Africa. Commonly implemented as a mobile wallet service referred to as mobile money (MoMo), the technology provides enormous benefits to its users, some of whom have long been unbanked. While the benefits of mobile money services have largely been documented, the challenges that arise -- especially in the interactions between human stakeholders -- remain relatively unexplored. In this study, we investigate the practices of mobile money users in their interactions with mobile money agents. We conduct 72 structured interviews in Kenya and Tanzania (n=36 per country). The results show that users and agents design workarounds in response to limitations and challenges that users face within the ecosystem. These include advances or loans from agents, relying on the user-agent relationships in place of legal identification requirements, and altering the intended transaction execution to improve convenience. Overall, the workarounds modify one or more of what we see as the core components of mobile money: the user, the agent, and the transaction itself. The workarounds pose new risks and challenges for users and the overall ecosystem. The results suggest a need for rethinking privacy and security of various components of the ecosystem, as well as policy and regulatory controls to safeguard interactions while ensuring the usability of mobile money., Comment: To be published in IEEE Symposium on Security and Privacy 2024

This document presents the initial scientific case for upgrading the Continuous Electron Beam Accelerator Facility (CEBAF) at Jefferson Lab (JLab) to 22 GeV. It is the result of a community effort, incorporating insights from a series of workshops conducted between March 2022 and April 2023. With a track record of over 25 years in delivering the world's most intense and precise multi-GeV electron beams, CEBAF's potential for a higher energy upgrade presents a unique opportunity for an innovative nuclear physics program, which seamlessly integrates a rich historical background with a promising future. The proposed physics program encompass a diverse range of investigations centered around the nonperturbative dynamics inherent in hadron structure and the exploration of strongly interacting systems. It builds upon the exceptional capabilities of CEBAF in high-luminosity operations, the availability of existing or planned Hall equipment, and recent advancements in accelerator technology. The proposed program cover various scientific topics, including Hadron Spectroscopy, Partonic Structure and Spin, Hadronization and Transverse Momentum, Spatial Structure, Mechanical Properties, Form Factors and Emergent Hadron Mass, Hadron-Quark Transition, and Nuclear Dynamics at Extreme Conditions, as well as QCD Confinement and Fundamental Symmetries. Each topic highlights the key measurements achievable at a 22 GeV CEBAF accelerator. Furthermore, this document outlines the significant physics outcomes and unique aspects of these programs that distinguish them from other existing or planned facilities. In summary, this document provides an exciting rationale for the energy upgrade of CEBAF to 22 GeV, outlining the transformative scientific potential that lies within reach, and the remarkable opportunities it offers for advancing our understanding of hadron physics and related fundamental phenomena., Comment: Updates to the list of authors; Preprint number changed from theory to experiment; Updates to sections 4 and 6, including additional figures

The electromagnetic form factors of the proton and neutron encode information on the spatial structure of their charge and magnetization distributions. While measurements of the proton are relatively straightforward, the lack of a free neutron target makes measurements of the neutron's electromagnetic structure more challenging and more sensitive to experimental or model-dependent uncertainties. Various experiments have attempted to extract the neutron form factors from scattering from the neutron in deuterium, with different techniques providing different, and sometimes large, systematic uncertainties. We present results from a novel measurement of the neutron magnetic form factor using quasielastic scattering from the mirror nuclei $^3$H and $^3$He, where the nuclear effects are larger than for deuterium but expected to largely cancel in the cross-section ratios. We extracted values of the neutron magnetic form factor for low-to-modest momentum transfer, $0.6

Livestock mobility, particularly that of small and large ruminants, is one of the main pillars of production and trade in West Africa: livestock is moved around in search of better grazing or sold in markets for domestic consumption and for festival-related activities. These movements cover several thousand kilometers and have the capability of connecting the whole West African region thus facilitating the diffusion of many animal and zoonotic diseases. Several factors shape mobility patterns even in normal years and surveillance systems need to account for such changes. In this paper, we present a procedure based on temporal network theory to identify possible sentinel locations using two indicators: vulnerability (i.e. the probability of being reached by the disease) and time of infection (i.e. the time of first arrival of the disease). Using these indicators in our structural analysis of the changing network enabled us to identify a set of nodes that could be used in an early warning system. As a case study we simulated the introduction of F.A.S.T. (Foot and Mouth Similar Transboundary) diseases in Senegal and used data taken from 2020 Sanitary certificates (LPS, laissez-passer sanitaire) issued by the Senegalese Veterinary Services to reconstruct the national mobility network. Our analysis showed that a static approach can significantly overestimate the speed and the extent of disease propagation, whereas temporal analysis revealed that the reachability and vulnerability of the different administrative departments (used as nodes of the mobility network) change over the course of the year. For this reason, several sets of sentinel nodes were identified in different periods of the year, underlining the role of temporality in shaping patterns of disease diffusion., Comment: 36 pages (25 main manuscript, 11 supplementary information), 17 figures (7 main manuscript, 10 supplementary information), submitted to Transboundary and Emerging Diseases

We explore the abilities of two machine learning approaches for no-arbitrage interpolation of European vanilla option prices, which jointly yield the corresponding local volatility surface: a finite dimensional Gaussian process (GP) regression approach under no-arbitrage constraints based on prices, and a neural net (NN) approach with penalization of arbitrages based on implied volatilities. We demonstrate the performance of these approaches relative to the SSVI industry standard. The GP approach is proven arbitrage-free, whereas arbitrages are only penalized under the SSVI and NN approaches. The GP approach obtains the best out-of-sample calibration error and provides uncertainty quantification.The NN approach yields a smoother local volatility and a better backtesting performance, as its training criterion incorporates a local volatility regularization term.

Besides reproducing tabular data properties of standalone tables, synthetic relational databases also require modeling the relationships between related tables. In this paper, we propose the Row Conditional-Tabular Generative Adversarial Network (RC-TGAN), a novel generative adversarial network (GAN) model that extends the tabular GAN to support modeling and synthesizing relational databases. The RC-TGAN models relationship information between tables by incorporating conditional data of parent rows into the design of the child table's GAN. We further extend the RC-TGAN to model the influence that grandparent table rows may have on their grandchild rows, in order to prevent the loss of this connection when the rows of the parent table fail to transfer this relationship information. The experimental results, using eight real relational databases, show significant improvements in the quality of the synthesized relational databases when compared to the benchmark system, demonstrating the effectiveness of the RC-TGAN in preserving relationships between tables of the original database.

When protons and neutrons (nucleons) are bound into atomic nuclei, they are close enough together to feel significant attraction, or repulsion, from the strong, short-distance part of the nucleon-nucleon interaction. These strong interactions lead to hard collisions between nucleons, generating pairs of highly-energetic nucleons referred to as short-range correlations (SRCs). SRCs are an important but relatively poorly understood part of nuclear structure and mapping out the strength and isospin structure (neutron-proton vs proton-proton pairs) of these virtual excitations is thus critical input for modeling a range of nuclear, particle, and astrophysics measurements. Hitherto measurements used two-nucleon knockout or ``triple-coincidence'' reactions to measure the relative contribution of np- and pp-SRCs by knocking out a proton from the SRC and detecting its partner nucleon (proton or neutron). These measurementsshow that SRCs are almost exclusively np pairs, but had limited statistics and required large model-dependent final-state interaction (FSI) corrections. We report on the first measurement using inclusive scattering from the mirror nuclei $^3$H and $^3$He to extract the np/pp ratio of SRCs in the A=3 system. We obtain a measure of the np/pp SRC ratio that is an order of magnitude more precise than previous experiments, and find a dramatic deviation from the near-total np dominance observed in heavy nuclei. This result implies an unexpected structure in the high-momentum wavefunction for $^3$He and $^3$H. Understanding these results will improve our understanding of the short-range part of the N-N interaction.

In nuclear reaction experiments, the measured decay energy spectra can give insights into the shell structure of decaying systems. However, extracting the underlying physics from the measurements is challenging due to detector resolution and acceptance effects. The Richardson-Lucy (RL) algorithm, a deblurring method that is commonly used in optics and has proven to be a successful technique for restoring images, was applied to our experimental nuclear physics data. The only inputs to the method are the observed energy spectrum and the detector's response matrix also known as the transfer matrix. We demonstrate that the technique can help access information about the shell structure of particle-unbound systems from the measured decay energy spectrum that isn't immediately accessible via traditional approaches such as chi-square fitting. For a similar purpose, we developed a machine learning model that uses a deep neural network (DNN) classifier to identify resonance states from the measured decay energy spectrum. We tested the performance of both methods on simulated data and experimental measurements. Then, we applied both algorithms to the decay energy spectrum of $^{26}\mathrm{O} \rightarrow ^{24}\mathrm{O}$ + n + n measured via invariant mass spectroscopy. The resonance states restored using the RL algorithm to deblur the measured decay energy spectrum agree with those found by the DNN classifier. Both deblurring and DNN approaches suggest that the raw decay energy spectrum of $^{26}\mathrm{O}$ exhibits three peaks at approximately 0.15~MeV, 1.50~MeV, and 5.00~MeV, with half-widths of 0.29~MeV, 0.80~MeV, and 1.85~MeV, respectively.

After irradiation of Fe-Cr alloys of low purity (model alloys of F-M steels), minor solute elements as P, Ni and Si have been shown to create solute clusters which significantly contribute to hardening and might be associated with small dislocation loops. In order to understand the role of each impurity on the formation of the nano-features formed under irradiation and the eventual synergies between the different species, Fe-15at.%Cr-X (X=Si, Ni, P, NiSiP) alloys of different composition have been ion irradiated and characterized using atom probe tomography. Irradiation were performed at 300 {\textdegree}C up to 2.5 dpa in four alloys: Fe15CrNi, Fe15CrSi, Fe15CrP and Fe15CrNiSiP. Influence of C atoms implanted during irradiation on the nanostructure evolution is also discussed. The study of the evolution of the nanofeatures formed under irradiation with the dose as a function of the composition highlights the role of P and C on the formation of the nano-clusters and confirm the radiation-induced nature of solute-rich clusters.

The average coflow completion time (CCT) is the standard performance metric in coflow scheduling. However, standard CCT minimization may introduce unfairness between the data transfer phase of different computing jobs. Thus, while progress guarantees have been introduced in the literature to mitigate this fairness issue, the trade-off between fairness and efficiency of data transfer is hard to control. This paper introduces a fairness framework for coflow scheduling based on the concept of slowdown, i.e., the performance loss of a coflow compared to isolation. By controlling the slowdown it is possible to enforce a target coflow progress while minimizing the average CCT. In the proposed framework, the minimum slowdown for a batch of coflows can be determined in polynomial time. By showing the equivalence with Gaussian elimination, slowdown constraints are introduced into primal-dual iterations of the CoFair algorithm. The algorithm extends the class of the sigma-order schedulers to solve the fair coflow scheduling problem in polynomial time. It provides a 4-approximation of the average CCT w.r.t. an optimal scheduler. Extensive numerical results demonstrate that this approach can trade off average CCT for slowdown more efficiently than existing state of the art schedulers.

The main goal of this paper is to use the enlargement of ltration framework for pricing zerocoupon CAT bonds. For this purpose, we develop two models where the trigger event time is perfectly covered by an increasing sequence of stopping times with respect to a reference ltration. Hence, depending on the nature of these stopping times the trigger event time can be either accessible or totally inaccessible. When some of these stopping times are not predictable, the trigger event time is totally inaccessible, and very nice mathematical computations can be derived. When the stopping times are predictable, the trigger event time is accessible, and this case would be a meaningful choice for Model 1 from a practical point of view since features like seasonality are already captured by some quantities such as the stochastic intensity of the Poisson process. We compute the main tools for pricing the zero-coupon CAT bond and show that our constructions are more general than some existing models in the literature. We obtain some closed-form prices of zero-coupon CAT bonds in Model 2 so we give a numerical illustrative example for this latter., Comment: Journal of Mathematical Finance, Scientific Research, In press

Microfinance, despite its significant potential for poverty reduction, is facing sustainability hardships due to high default rates. Although many methods in regular finance can estimate credit scores and default probabilities, these methods are not directly applicable to microfinance due to the following unique characteristics: a) under-explored (developing) areas such as rural Africa do not have sufficient prior loan data for microfinance institutions (MFIs) to establish a credit scoring system; b) microfinance applicants may have difficulty providing sufficient information for MFIs to accurately predict default probabilities; and c) many MFIs use group liability (instead of collateral) to secure repayment. Here, we present a novel control-theoretic model of microfinance that accounts for these characteristics. We construct an algorithm to learn microfinance decision policies that achieve financial inclusion, fairness, social welfare, and sustainability. We characterize the convergence conditions to Pareto-optimum and the convergence speeds. We demonstrate, in numerous real and synthetic datasets, that the proposed method accounts for the complexities induced by group liability to produce robust decisions before sufficient loans are given to establish credit scoring systems and for applicants whose default probability cannot be accurately estimated due to missing information. To the best of our knowledge, this paper is the first to connect microfinance and control theory. We envision that the connection will enable safe learning and control techniques to help modernize microfinance and alleviate poverty., Comment: 37 pages, 12 figures

A narrow near-threshold proton-emitting resonance (Ex = 11.4 MeV, J$^{\pi}$ = 1/2$^{+}$ and $\Gamma_{p}$ = 4.4 keV) was directly observed in $^{11}$B via proton resonance scattering. This resonance was previously inferred in the $\beta$-delayed proton emission of the neutron halo nucleus $^{11}$Be. The good agreement between both experimental results serves as a ground to confirm the existence of such exotic decay and the particular behavior of weakly bound nuclei coupled to the continuum. $R$-matrix analysis shows a sizable partial decay width for both, proton and $\alpha$ emission channels.

The strong interaction is not well understood at low energy, or for interactions with low momentum transfer $Q^2$, but one of the clearest insights we have comes from Chiral Perturbation Theory ($\chi$PT). This effective treatment gives testable predictions for the nucleonic generalized polarizabilities -- fundamental quantities describing the nucleon's response to an external field. We have measured the proton's generalized spin polarizabilities in the region where $\chi$PT is expected to be valid. Our results include the first ever data for the transverse-longitudinal spin polarizability $\delta_{LT}$, and also extend the coverage of the polarizability $\bar{d_2}$ to very low $Q^2$ for the first time. These results were extracted from moments of the structure function $g_2$, a quantity which characterizes the internal spin structure of the proton. Our experiment ran at Jefferson Lab using a polarized electron beam and a polarized solid ammonia (NH$_3$) target. The $\delta_{LT}$ polarizability has remained a challenging quantity for $\chi$PT to reproduce, despite its reduced sensitivity to higher resonance contributions; recent competing calculations still disagree with each other and also diverge from the measured neutron data at very low $Q^2$. Our proton results provide discriminating power between existing calculations, and will help provide a better understanding of this strong QCD regime.

The African School of Fundamental Physics and Applications, also known as the African School of Physics (ASP), was initiated in 2010, as a three-week biennial event, to offer additional training in fundamental and applied physics to African students with a minimum of three-year university education. Since its inception, ASP has grown to be much more than a school. ASP has become a series of activities and events with directed ethos towards physics as an engine for development in Africa. One such activity of ASP is the African Conference on Fundamental and Applied Physics (ACP). The first edition of ACP took place during the 2018 edition of ASP at the University of Namibia in Windhoek. In this paper, we report on the second edition of ACP, organized on March 7--11, 2022, as a virtual event., Comment: 12 pages

Many current and future nuclear physics (NP) experiments across the United States have and are implementing micro-pattern gas detectors (MPGDs) to be used for tracking and PID purposes. MPGDs are capable of operating in high rate environments and providing excellent spatial resolution over a large-area with a low material budget. Summarized in this white paper is the role that MPGDs are playing in NP experiments and the R&D which is needed to meet the requirements of future NP experiments., Comment: contribution to Snowmass 2021

We experimentally demonstrate the difference between a ridge polariton laser, and a conventional edge-emitting ridge laser operating under electron-hole population inversion. The horizontal laser cavities are 20 -- 60 $\mu$m long GaN etched ridge structures with vertical Bragg reflectors. We investigate the laser threshold under optical pumping and assess quantitatively the effect of a varying optically-pumped length. The laser effect is achieved for an exciton reservoir length of just 15% of the cavity length, which would not be possible in a conventional ridge laser, with an inversion-less polaritonic gain about 10 times larger than in equivalent GaN lasers. The modelling of the cavity free spectral range demonstrates the polaritonic nature of the modes.

Rainfall is an important variable to be able to monitor and forecast across Africa, due to its impact on agriculture, food security, climate related diseases and public health. Numerical Weather Models (NWM) are an important component of this work, due to their complete spatial coverage, high resolution, and ability to forecast into the future. In this study, we seek to evaluate the spatiotemporal skill of short-term rainfall forecasts of rainfall across Africa. Specifically, the European Centre for Medium-Range Weather Forecasts (ECMWF) and the National Centers for Environmental Prediction-Global Forecast System (NCEP-GFS) forecast models are verified by Rainfall Estimates 2.0 (RFE2) and African Rainfall Climatology Version 2 (ARC2), which are fused products of satellite and in-situ observations and are commonly used in analysis of African rainfall. We found that the model rainfall forecasts show good consistency with the satellite rainfall observations in spatial distribution over Africa on the seasonal timescale. Evaluation metrics show high spatial and seasonal variations over the African continent, including a strong link to the location of the inter-tropical convergence zone (ITCZ) and topographically enhanced precipitation. The rainfall forecasts at one week aggregation time are improved against daily forecasts., Comment: 50 pages, 10 figures, 3 supplementary figures

The small binding energy of the hypertrition leads to predictions of non-existence of bound hypernuclei for isotriplet three-body systems such as $nn\Lambda$. However, invariant mass spectroscopy at GSI has reported events that may be interpreted as the bound $nn\Lambda$ state. The $nn\Lambda$ state was sought by missing-mass spectroscopy via the $(e,e'K^+)$ reaction at Jefferson Lab's experimental Hall A. The present experiment has higher sensitivity to the $nn\Lambda$-state investigation in terms of better precision by a factor of about three. The analysis shown in this article focuses on the derivation of the reaction cross-section for the $^3{\rm{H}}(\gamma^{*},K^+)\textrm{X}$ reaction. Events that were detected in an acceptance, where a Monte Carlo simulation could reproduce the data well ($|\delta p/p| < 4\%$), were analyzed to minimize the systematic uncertainty. No significant structures were observed with the acceptance cuts, and the upper limits of the production cross-section of the $nn\Lambda$ state were obtained to be $21$ and $31~\rm{nb/sr}$ at the $90\%$ confidence level when theoretical predictions of $(-B_{\Lambda}, \Gamma) = (0.25,0.8)$ and $(0.55, 4.7)$ MeV, respectively, were assumed. The cross-section result provides valuable information for examining the existence of $nn\Lambda$., Comment: 27 pages, 12 figures

We propose to use the High Momentum Spectrometer of Hall C combined with the Neutral Particle Spectrometer (NPS) to perform high precision measurements of the Deeply Virtual Compton Scattering (DVCS) cross section using a beam of positrons. The combination of measurements with oppositely charged incident beams is the only unambiguous way to disentangle the contribution of the DVCS$^2$ term in the photon electroproduction cross section from its interference with the Bethe-Heitler amplitude. This provides a stronger way to constrain the Generalized Parton Distributions of the nucleon. A wide range of kinematics accessible with an 11 GeV beam off an unpolarized proton target will be covered. The $Q^2-$dependence of each contribution will be measured independently.

In this work, we provide a metric to calculate the most significant software security weaknesses as defined by an aggregate metric of the frequency, exploitability, and impact of related vulnerabilities. The Common Weakness Enumeration (CWE) is a well-known and used list of software security weaknesses. The CWE community publishes such an aggregate metric to calculate the `Most Dangerous Software Errors'. However, we find that the published equation highly biases frequency and almost ignores exploitability and impact in generating top lists of varying sizes. This is due to the differences in the distributions of the component metric values. To mitigate this, we linearize the frequency distribution using a double log function. We then propose a variety of other improvements, provide top lists of the most significant CWEs for 2019, provide an analysis of the identified software security weaknesses, and compare them against previously published top lists., Comment: 12 pages

The unpolarized and polarized Beam Char\-ge Asymmetries (BCAs) of the $\vv{e}^{\pm}p \to e^{\pm}p \gamma$ process off unpolarized hydrogen are discussed. The measurement of BCAs with the CLAS12 spectrometer at the Thomas Jefferson National Accelerator Facility, using polarized positron and electron beams at 10.6 GeV is investigated. This experimental configuration allows to measure azimuthal and $t$-dependences of the unpolarized and polarized BCAs over a large $(x_B,Q^2)$ phase space, providing a direct access to the real part of the Compton Form Factor (CFF) ${\mathcal H}$. Additionally, these measurements confront the Bethe-Heitler dominance hypothesis and eventual effects beyond leading twist. The impact of potential positron beam data on the determination of CFFs is also investigated within a local fitting approach of experimental observables. Positron data are shown to strongly reduce correlations between CFFs and consequently improve significantly the determination of $\Re {\rm e} [\mathcal{H}]$., Comment: 11 pages, 10 figures, Article part of the EPJA Topical Issue about "Positron beams and physics at Jefferson Lab". arXiv admin note: text overlap with arXiv:2007.15081

We study by scanning thermal microscopy the nanoscale thermal conductance of films (40 to 400 nm thick) of [1]benzothieno[3,2-b][1]benzothiophene (BTBT) and 2,7-dioctyl[1]benzothieno[3,2-b][1]benzothiophene (C8-BTBT-C8). We demonstrate that the out-of-plane thermal conductivity is significant along the interlayer direction, larger for BTBT (0.63 +/- 0.12 W m-1 K-1) compared to C8-BTBT-C8 (0.25 +/- 0.13 W m-1 K-1). These results are supported by molecular dynamics calculations (Approach to Equilibrium Molecular Dynamics method) performed on the corresponding molecular crystals. The calculations point to significant thermal conductivity (3D-like) values along the 3 crystalline directions, with anisotropy factors between the crystalline directions below 1.8 for BTBT and below 2.8 for C8-BTBT-C8, in deep contrast with the charge transport properties featuring a two-dimensional character for these materials. In agreement with the experiments, the calculations yield larger values in BTBT compared to C8-BTBT-C8 (0.6-1.3 W m-1 K-1 versus 0.3-0.7 W m-1 K-1, respectively). The weak thickness dependence of the nanoscale thermal resistance is in agreement with a simple analytical model., Comment: Nanoscale (2021)

Understanding the landscape of software vulnerabilities is key for developing effective security solutions. Fortunately, the evaluation of vulnerability databases that use a framework for communicating vulnerability attributes and their severity scores, such as the Common Vulnerability Scoring System (CVSS), can help shed light on the nature of publicly published vulnerabilities. In this paper, we characterize the software vulnerability landscape by performing a historical and statistical analysis of CVSS vulnerability metrics over the period of 2005 to 2019 through using data from the National Vulnerability Database. We conduct three studies analyzing the following: the distribution of CVSS scores (both empirical and theoretical), the distribution of CVSS metric values and how vulnerability characteristics change over time, and the relative rankings of the most frequent metric value over time. Our resulting analysis shows that the vulnerability threat landscape has been dominated by only a few vulnerability types and has changed little during the time period of the study. The overwhelming majority of vulnerabilities are exploitable over the network. The complexity to successfully exploit these vulnerabilities is dominantly low; very little authentication to the target victim is necessary for a successful attack. And most of the flaws require very limited interaction with users. However on the positive side, the damage of these vulnerabilities is mostly confined within the security scope of the impacted components. A discussion of lessons that could be learned from this analysis is presented., Comment: 7 pages

In front of the major challenges to increase its productivity while satisfying its customer, it is today important to establish in advance the operational performances of the RTG Abidjan Terminal. In this article, by using an M/G/1 retrial queue system, we obtained the average number of parked delivery trucks and as well as their waiting time. Finally, we used Matlab to represent them graphically then analyze the RTG performances according to the traffic rate., Comment: 15 pages, 3 figures

Positron beams, both polarized and unpolarized, are identified as essential ingredients for the experimental programs at the next generation of lepton accelerators. In the context of the hadronic physics program at Jefferson Lab (JLab), positron beams are complementary, even essential, tools for a precise understanding of the electromagnetic structure of nucleons and nuclei, in both the elastic and deep-inelastic regimes. For instance, elastic scattering of polarized and unpolarized electrons and positrons from the nucleon enables a model independent determination of its electromagnetic form factors. Also, the deeply-virtual scattering of polarized and unpolarized electrons and positrons allows unambiguous separation of the different contributions to the cross section of the lepto-production of photons and of lepton-pairs, enabling an accurate determination of the nucleons and nuclei generalized parton distributions, and providing an access to the gravitational form factors. Furthermore, positron beams offer the possibility of alternative tests of the Standard Model of particle physics through the search of a dark photon, the precise measurement of electroweak couplings, and the investigation of charged lepton flavor violation. This document discusses the perspectives of an experimental program with high duty-cycle positron beams at JLab., Comment: 18 pages, 7 figures This version superseeds the previous version which scientific content was decomposed into several more elaborated articles. All of these articles will be collected in the EPJ A Topical Issue about "Positron beam and physics at Jefferson Lab (e+@Jlab)"

The Common Weakness Enumeration (CWE) is a prominent list of software weakness types. This list is used by vulnerability databases to describe the underlying security flaws within analyzed vulnerabilities. This linkage opens the possibility of using the analysis of software vulnerabilities to identify the most significant weaknesses that enable those vulnerabilities. We accomplish this through creating mashup views combining CWE weakness taxonomies with vulnerability analysis data. The resulting graphs have CWEs as nodes, edges derived from multiple CWE taxonomies, and nodes adorned with vulnerability analysis information (propagated from children to parents). Using these graphs, we develop a suite of metrics to identify the most significant weakness types (using the perspectives of frequency, impact, exploitability, and overall severity)., Comment: 6 pages

Short Range Correlations (SRCs) have been identified as being responsible for the high momentum tail of the nucleon momentum distribution, n(k). Hard, short-range interactions of nucleon pairs generate the high momentum tail and imprint a universal character on n(k) for all nuclei at large momentum. Triple coincidence experiments have shown a strong dominance of np pairs, but these measurements involve large final state interactions. This paper presents the results from Jefferson Lab experiment E08014 which measured inclusive electron scattering cross-section from Ca isotopes. By comparing the inclusive cross section from 48Ca to 40Ca in a kinematic region dominated by SRCs we provide a new way to study the isospin structure of SRCs., Comment: 7 pages, 3 figures

Studies in malaria control cover many areas such as medicine, sociology, biology, mathematic, physic, computer science and so forth. Researches in the realm of mathematic are conducted to predict the occurrence of the disease and to support the eradication process. Basically, the modeling methodology is predominantly deterministic and differential equation based while selecting clinical and biological features that seem to be important. Yet, if the individual characteristics matter when modeling the disease, the overall estimation of the malaria is not done based on the health status of each individual but in a non-specified percentage of the global population. The goal of this paper is to propose a model that relies on a daily evolution of the individual's state, which depends on their mobility and the characteristics of the area they visit. Thus, the mobility data of a single person moving from one area to another, gathered thanks to mobile networks, is the essential building block to predict the outcome of the disease. We implement our solution and demonstrate its effectiveness through empirical experiments. The results show how promising the model is in providing possible insights into the failure of the disease control in the Kedougou region.

Chemisorption process and catalytic activity of CO to CO2 conversion on PdXRu1-X (X : 0, 0.1, 0.3, 0.5, 0.7, 0.9 and 1) extended as a benchmark for further investigation of very complex nanoparticle (NP) structures have been checked into thoroughly by using the synchrotron-based hard X-ray photoelectron spectroscopy (HAXPES). Assessment and diagnostic of core levels and valence bands data highlight valuable information regarding the surface interaction and structure of PdRu bimetallic nanoparticles (BM-NPs). Core level shift observed from the C 1s clearly emphasized that the Pd0.5Ru0.5 NPs which provide the highest catalytic efficiency (CO oxidation) exhibits a preferential adsorption of the CO molecule at the top site. Otherwise, our results also display that remaining NPs exhibit two components assigned to the bridge and hollow CO sites. Combination of Pd 3d5/2 and Ru 3p3/2 core levels results points out a transition from alloy structures to core-shell configuration with increasing the molar ratio of Ru. Valence-band maximum (VBM) demonstrates a position dependent to the molar composition of Ru. Additionally, by digging into the electronic structures (shape and width) of each NPs very deeply, we clearly emphasise the valuable relationship between composition, atomic arrangement, d-band and catalytic properties of bimeatllic PdRu. According to the HAXPES results, the strong and clear evidence for the enhanced CO to CO2 conversion ability of Pd0.5Ru0.5-NP may be assigned to the existence of a most favourable spatial d-band extension and an optimum balance between the core-shell and alloy structures. Electronic and chemical data and interpretations are consistent with the PdRu catalytic performances. This present prospection gives a new step towards a better knowledge on the catalytic surface interaction of binary, ternary and multimetallic NPs with reactants.

Today's popular TV series tend to develop continuous, complex plots spanning several seasons, but are often viewed in controlled and discontinuous conditions. Consequently, most viewers need to be re-immersed in the story before watching a new season. Although discussions with friends and family can help, we observe that most viewers make extensive use of summaries to re-engage with the plot. Automatic generation of video summaries of TV series' complex stories requires, first, modeling the dynamics of the plot and, second, extracting relevant sequences. In this paper, we tackle plot modeling by considering the social network of interactions between the characters involved in the narrative: substantial, durable changes in a major character's social environment suggest a new development relevant for the summary. Once identified, these major stages in each character's storyline can be used as a basis for completing the summary with related sequences. Our algorithm combines such social network analysis with filmmaking grammar to automatically generate character-oriented video summaries of TV series from partially annotated data. We carry out evaluation with a user study in a real-world scenario: a large sample of viewers were asked to rank video summaries centered on five characters of the popular TV series Game of Thrones, a few weeks before the new, sixth season was released. Our results reveal the ability of character-oriented summaries to re-engage viewers in television series and confirm the contributions of modeling the plot content and exploiting stylistic patterns to identify salient sequences.

Data sent over the Internet can be monitored and manipulated by intermediate entities in the data path from the source to the destination. For unencrypted communications (and some encrypted communications with known weaknesses), eavesdropping and man-in-the-middle attacks are possible. For encrypted communication, the identification of the communicating endpoints is still revealed. In addition, encrypted communications may be stored until such time as newly discovered weaknesses in the encryption algorithm or advances in computer hardware render them readable by attackers. In this work, we use public data to evaluate both advertised and observed routes through the Internet and measure the extent to which communications between pairs of countries are exposed to other countries. We use both physical router geolocation as well as the country of registration of the companies owning each router. We find a high level of information exposure; even physically adjacent countries use routes that involve many other countries. We also found that countries that are well `connected' tend to be more exposed. Our analysis indicates that there exists a tradeoff between robustness and information exposure in the current Internet., Comment: 5 pages, 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications

Experimental cross sections for the $^4He(e,e'p)X$ reaction up to a missing momentum of 0.632 GeV/$c$ at $x_B=1.24$ and $Q^2$=2(GeV/$c$)$^2$ are reported. The data are compared to Relativistic Distorted Wave Impulse Approximation(RDWIA) calculations for $^4He(e,e'p)^3H$ channel. Significantly more events in the triton mass region are measured for $p_{m}$$>$0.45 GeV/$c$ than are predicted by the theoretical model, suggesting that the effects of initial-state multi-nucleon correlations are stronger than expected by the RDWIA model., Comment: Submitted to PRC

Let G = (V, E, L) be an edge-labeled graph such that V is the set of vertices, E is the set of edges, L is the set of labels (colors) and each edge e \in E has a label l(e) associated; The goal of the minimum labeling global cut problem (MLGCP) is to find a subset L \subseteq L of labels such that G = (V, E , L\L ) is not connected and |L| is minimized. This work proposes three new mathematical formulations for the MLGCP as well as branch-and-cut algorithms to solve them. The computational experiments showed that the proposed methods are able to solve small to average sized instances in a reasonable amount of time.

Speaker diarization may be difficult to achieve when applied to narrative films, where speakers usually talk in adverse acoustic conditions: background music, sound effects, wide variations in intonation may hide the inter-speaker variability and make audio-based speaker diarization approaches error prone. On the other hand, such fictional movies exhibit strong regularities at the image level, particularly within dialogue scenes. In this paper, we propose to perform speaker diarization within dialogue scenes of TV series by combining the audio and video modalities: speaker diarization is first performed by using each modality, the two resulting partitions of the instance set are then optimally matched, before the remaining instances, corresponding to cases of disagreement between both modalities, are finally processed. The results obtained by applying such a multi-modal approach to fictional films turn out to outperform those obtained by relying on a single modality.

Measurements of elastic electron scattering data within the past decade have highlighted two-photon exchange contributions as a necessary ingredient in theoretical calculations to precisely evaluate hydrogen elastic scattering cross sections. This correction can modify the cross section at the few percent level. In contrast, dispersive effects can cause significantly larger changes from the Born approximation. The purpose of this experiment is to extract the carbon-12 elastic cross section around the first diffraction minimum, where the Born term contributions to the cross section are small to maximize the sensitivity to dispersive effects. The analysis uses the LEDEX data from the high resolution Jefferson Lab Hall A spectrometers to extract the cross sections near the first diffraction minimum of 12C at beam energies of 362 MeV and 685 MeV. The results are in very good agreement with previous world data, although with less precision. The average deviation from a static nuclear charge distribution expected from linear and quadratic fits indicate a 30.6% contribution of dispersive effects to the cross section at 1 GeV. The magnitude of the dispersive effects near the first diffraction minimum of 12C has been confirmed to be large with a strong energy dependence and could account for a large fraction of the magnitude for the observed quenching of the longitudinal nuclear response. These effects could also be important for nuclei radii extracted from parity-violating asymmetries measured near a diffraction minimum., Comment: 14 pages, 10 figures

Identifying and characterizing the dynamics of modern tv series subplots is an open problem. One way is to study the underlying social network of interactions between the characters. Standard dynamic network extraction methods rely on temporal integration, either over the whole considered period, or as a sequence of several time-slices. However, they turn out to be inappropriate in the case of tv series, because the scenes shown onscreen alternatively focus on parallel storylines, and do not necessarily respect a traditional chronology. In this article, we introduce Narrative Smoothing, a novel network extraction method taking advantage of the plot properties to solve some of their limitations. We apply our method to a corpus of 3 popular series, and compare it to both standard approaches. Narrative smoothing leads to more relevant observations when it comes to the characterization of the protagonists and their relationships, confirming its appropriateness to model the intertwined storylines constituting the plots., Comment: arXiv admin note: substantial text overlap with arXiv:1602.07811

In this work, we extend a previous work where we proposed a suitable state model built from a Karhunen-Loeve Transformation to build a new decision process from which, we can extract useful knowledge and information about the identified underlying sub-communities from an initial network. The aim of the method is to build a framework for a multi-level knowledge retrieval. Besides the capacity of the methodology to reduce the high dimensionality of the data, the new detection scheme is able to extract, from the sub-communities, the dense sub-groups with the definition and formulation of new quantities related to the notions of energy and co-energy. The energy of a node is defined as the rate of its participation to the set of activities while the notion of co-energy defines the rate of interaction/link between two nodes. These two important features are used to make each link weighted and bounded, so that we are able to perform a thorough refinement of the sub-community discovery. This study allows to perform a multi-level analysis by extracting information either per-link or per-intra-subcommunity. As an improvement of this work, we define the notion of pivot to relate the node(s) with the greatest influence in the network. We propose the use of a thorough tool based on the formulation of the transformation of a suitable probabilistic model into a possibilistic model to extrac, Comment: 15 pages, 5 figures; Conference: CNRIA 2018. arXiv admin note: substantial text overlap with arXiv:1312.4617 by other authors

We present new data probing short-range correlations (SRCs) in nuclei through the measurement of electron scattering off high-momentum nucleons in nuclei. The inclusive 4He/3He cross section ratio is observed to be both x and Q2 independent for 1.5 < x < 2, confirming the dominance of two- nucleon (2N) short-range correlations (SRCs). For x > 2, our data do not support a previous claim of three-nucleon (3N) correlation dominance. While contributions beyond those from stationary 2N- SRCs are observed, our data show that isolating 3N-SRCs is more complicated than for 2N-SRCs., Comment: 6 pages, 2 figures, new experimental results from JLab E08-014

Most of the codes that have an algebraic decoding algorithm are derived from the Reed Solomon codes. They are obtained by taking equivalent codes, for example the generalized Reed Solomon codes, or by using the so-called subfield subcode method, which leads to Alternant codes and Goppa codes over the underlying prime field, or over some intermediate subfield. The main advantages of these constructions is to preserve both the minimum distance and the decoding algorithm of the underlying Reed Solomon code. In this paper, we propose a generalization of the subfield subcode construction by introducing the notion of subspace subcodes and a generalization of the equivalence of codes which leads to the notion of generalized subspace subcodes. When the dimension of the selected subspaces is equal to one, we show that our approach gives exactly the family of the codes obtained by equivalence and subfield subcode technique. However, our approach highlights the links between the subfield subcode of a code defined over an extension field and the operation of puncturing the $q$-ary image of this code. When the dimension of the subspaces is greater than one, we obtain codes whose alphabet is no longer a finite field, but a set of r-uples. We explain why these codes are practically as efficient for applications as the codes defined on an extension of degree r. In addition, they make it possible to obtain decodable codes over a large alphabet having parameters previously inaccessible. As an application, we give some examples that can be used in public key cryptosystems such as McEliece.

The Polarized Electrons for Polarized Positrons experiment at the injector of the Continuous Electron Beam Accelerator Facility has demonstrated for the first time the efficient transfer of polarization from electrons to positrons produced by the polarized bremsstrahlung radiation induced by a polarized electron beam in a high-$Z$ target. Positron polarization up to 82\% have been measured for an initial electron beam momentum of 8.19~MeV/$c$, limited only by the electron beam polarization. This technique extends polarized positron capabilities from GeV to MeV electron beams, and opens access to polarized positron beam physics to a wide community., Comment: 5 pages, 4 figures

Structure functions, as measured in lepton-nucleon scattering, have proven to be very useful in studying the quark dynamics within the nucleon. However, it is experimentally difficult to separately determine the longitudinal and transverse structure functions, and consequently there are substantially less data available for the longitudinal structure function in particular. Here we present separated structure functions for hydrogen and deuterium at low four--momentum transfer squared, Q^2< 1 GeV^2, and compare these with parton distribution parameterizations and a k_T factorization approach. While differences are found, the parameterizations generally agree with the data even at the very low Q^2 scale of the data. The deuterium data show a smaller longitudinal structure function, and smaller ratio of longitudinal to transverse cross section R, than the proton. This suggests either an unexpected difference in R for the proton and neutron or a suppression of the gluonic distribution in nuclei., Comment: 11 pages, 7 figures, 2 data tables

Modern popular TV series often develop complex storylines spanning several seasons, but are usually watched in quite a discontinuous way. As a result, the viewer generally needs a comprehensive summary of the previous season plot before the new one starts. The generation of such summaries requires first to identify and characterize the dynamics of the series subplots. One way of doing so is to study the underlying social network of interactions between the characters involved in the narrative. The standard tools used in the Social Networks Analysis field to extract such a network rely on an integration of time, either over the whole considered period, or as a sequence of several time-slices. However, they turn out to be inappropriate in the case of TV series, due to the fact the scenes showed onscreen alternatively focus on parallel storylines, and do not necessarily respect a traditional chronology. This makes existing extraction methods inefficient to describe the dynamics of relationships between characters, or to get a relevant instantaneous view of the current social state in the plot. This is especially true for characters shown as interacting with each other at some previous point in the plot but temporarily neglected by the narrative. In this article, we introduce narrative smoothing, a novel, still exploratory, network extraction method. It smooths the relationship dynamics based on the plot properties, aiming at solving some of the limitations present in the standard approaches. In order to assess our method, we apply it to a new corpus of 3 popular TV series, and compare it to both standard approaches. Our results are promising, showing narrative smoothing leads to more relevant observations when it comes to the characterization of the protagonists and their relationships. It could be used as a basis for further modeling the intertwined storylines constituting TV series plots.