Miracle-dz/UniFAR-FTUs huggingface dataset:
A Systematic Literature Review on Model-driven Engineering for Cyber-Physical Systems

This technical report presents a Systematic Literature Review (SLR) study that focuses on identifying and classifying the recent research practices pertaining to CPS development through MDE approaches. The study evaluates 140 research papers published during 2010–2018. Accordingly, a comprehensive analysis of various MDE approaches used in the development life-cycle of CPS is presented. Furthermore, the study identifies the research gaps and areas that need more investigation. The contribution helps researchers and practitioners to get an overall understanding of the research trends and existing challenges for further research/development.
An Efficient Vectorization Scheme for Stencil Computation

Stencil computation is one of the most important kernels in various scientific and engineering applications. A variety of work has focused on vectorization and tiling techniques, aiming at exploiting the in-core data parallelism and data locality respectively. In this paper, the downsides of existing vectorization schemes are analyzed. Briefly, they either incur data alignment conflicts or hurt the data locality when integrated with tiling. Then we propose a novel transpose layout to preserve the data locality for tiling and reduce the data reorganization overhead for vectorization simultaneously. To further improve the data reuse at the register level, a time loop unroll-and-jam strategy is designed to perform multistep stencil computation along the time dimension. Experimental results on the AVX2 and AVX-S12 CPUs show that our approach obtains a competitive performance with the classic vectorization methods (Auto Vectorization and Data Reorganization), state-of-the-art compilers (Pluto and SDSL), and highly-optimized work (DLT and Tessellation).
Temperature and Distance Dependence of Tidal Circularization in Close Binaries: A Catalog of Eclipsing Binaries in the Southern Hemisphere Observed by the TESS Satellite

Tidal forces are important for understanding how close binary stars and compact exoplanetary systems form and evolve. However, tides are difficult to model, and significant uncertainties exist about the strength of tides. Here, we investigate tidal circularization in close binaries using a large sample of well-characterized eclipsing systems. We searched TESS photometry from the southern hemisphere for eclipsing binaries. We derive best-fit orbital and stellar parameters by jointly modeling light curves and spectral energy distributions. To determine the eccentricity distribution of eclipsing binaries over a wide range of stellar temperatures (3000–50,000 K) and orbital separations a/R 1 (2–300), we combine our newly obtained TESS sample with eclipsing binaries observed from the ground and by the Kepler mission. We find a clear dependency of stellar temperature and orbital separation in the eccentricities of close binaries. We compare our observations with predictions of the equilibrium and dynamical tides. We find that while cool binaries agree with the predictions of the equilibrium tide, a large fraction of binaries with temperatures between 6250 K and 10,000 K and orbital separations between a/R 1 ∼ 4 and 10 are found on circular orbits, contrary to the predictions of the dynamical tide. This suggests that some binaries with radiative envelopes may be tidally circularized significantly more efficiently than usually assumed. Our findings on orbital circularization have important implications also in the context of hot Jupiters, where tides have been invoked to explain the observed difference in the spin–orbit alignment between hot and cool host stars.
Gradient-Based Markov Chain Monte Carlo for Bayesian Inference With Non-differentiable Priors

Abstract The use of nondifferentiable priors in Bayesian statistics has become increasingly popular, in particular in Bayesian imaging analysis. Current state-of-the-art methods are approximate in the sense that they replace the posterior with a smooth approximation via Moreau-Yosida envelopes, and apply gradient-based discretized diffusions to sample from the resulting distribution. We characterize the error of the Moreau-Yosida approximation and propose a novel implementation using underdamped Langevin dynamics. In misson-critical cases, however, replacing the posterior with an approximation may not be a viable option. Instead, we show that piecewise-deterministic Markov processes (PDMP) can be used for exact posterior inference from distributions satisfying almost everywhere differentiability. Furthermore, in contrast with diffusion-based methods, the suggested PDMP-based samplers place no assumptions on the prior shape, nor require access to a computationally cheap proximal operator, and consequently have a much broader scope of application. Through detailed numerical examples, including a nondifferentiable circular distribution and a nonconvex genomics model, we elucidate the relative strengths of these sampling methods on problems of moderate to high dimensions, underlining the benefits of PDMP-based methods when accurate sampling is decisive. Supplementary materials for this article are available online.
The Influence of Dropout on Membership Inference in Differentially Private Models

Differentially private models seek to protect the privacy of data the model is trained on, making it an important component of model security and privacy. At the same time, data scientists and machine learning engineers seek to use uncertainty quantification methods to ensure models are as useful and actionable as possible. We explore the tension between uncertainty quantification via dropout and privacy by conducting membership inference attacks against models with and without differential privacy. We find that models with large dropout slightly increases a model's risk to succumbing to membership inference attacks in all cases including in differentially private models.
Asymptotic analysis of subglacial plumes in stratified environments

Accurate predictions of basal melt rates on ice shelves are necessary for precise projections of the future behaviour of ice sheets. The computational expense associated with completely resolving the cavity circulation using an ocean model makes this approach unfeasible for multi-century simulations, and parametrizations of melt rates are required. At present, some of the most advanced melt rate parametrizations are based on a one-dimensional approximation to the melt rate that emerges from the theory of subglacial plumes applied to ice shelves with constant basal slopes and uniform ambient ocean conditions; in this work, we present an asymptotic analysis of the corresponding equations in which non-constant basal slopes and typical ambient conditions are imposed. This analysis exploits the small aspect ratio of ice shelf bases, the relatively weak thermal driving and the relative slenderness of the region separating warm, salty water at depth and cold, fresh water at the surface in the ambient ocean. We construct an approximation to the melt rate that is based on this analysis, which shows good agreement with numerical solutions in a wide variety of cases, suggesting a path towards improved predictions of basal melt rates in ice-sheet models.
On an inverse problem of nonlinear imaging with fractional damping

This paper considers the attenuated Westervelt equation in pressure formulation. The attenuation is by various models proposed in the literature and characterised by the inclusion of non-local operators that give power law damping as opposed to the exponential of classical models. The goal is the inverse problem of recovering a spatially dependent coefficient in the equation, the parameter of nonlinearity $\kappa(x)$, in what becomes a nonlinear hyperbolic equation with nonlocal terms. The overposed measured data is a time trace taken on a subset of the domain or its boundary. We shall show injectivity of the linearised map from $\kappa$ to the overposed data used to recover it and from this basis develop and analyse Newton-type schemes for its effective recovery.
Morphological changes and electrochemical response of mixed nickel manganese oxides as charge storage electrodes

Nickel manganese (Ni–Mn) oxide films were prepared by potentiostatic electrodeposition over stainless steel and post-thermal annealing at 250 °C. Morphological and structural changes were observed depending on the Ni to Mn ratio in the electrolyte. Single-phase Ni1−xMnxO oxide was formed at low Mn content, whereas two phases composed of Ni1−xMnxO and NixMn3−xO4 were formed at high Mn content. Electrochemical studies revealed an increase of the specific capacitance of the mixed Ni–Mn oxide electrodes compared to the single metal oxides, thus pin-pointing a synergistic effect. The Ni–Mn oxide film displayed a specific capacitance of about 300 F g−1 in a potential window of 0.5 V at an applied current density of 1 A g−1. The rate capability of the oxides was 58% when the applied current was increased from 1 A g−1 to 10 A g−1. The Ni–Mn oxide film exhibits excellent cycling stability with 100% capacitance retention after 1500 cycles.
HDTest: Differential Fuzz Testing of Brain-Inspired Hyperdimensional Computing

Brain-inspired hyperdimensional computing (HDC) is an emerging computational paradigm that mimics brain cognition and leverages hyperdimensional vectors with fully distributed holographic representation and (pseudo)randomness. Compared to other machine learning (ML) methods such as deep neural networks (DNNs), HDC offers several advantages including high energy efficiency, low latency, and one-shot learning, making it a promising alternative candidate on a wide range of applications. However, the reliability and robustness of HDC models have not been explored yet. In this paper, we design, implement, and evaluate HDTest to test HDC model by automatically exposing unexpected or incorrect behaviors under rare inputs. The core idea of HDTest is based on guided differential fuzz testing. Guided by the distance between query hypervector and reference hypervector in HDC, HDTest continuously mutates original inputs to generate new inputs that can trigger incorrect behaviors of HDC model. Compared to traditional ML testing methods, HDTest does not need to manually label the original input. Using handwritten digit classification as an example, we show that HDTest can generate thousands of adversarial inputs with negligible perturbations that can successfully fool HDC models. On average, HDTest can generate around 400 adversarial inputs within one minute running on a commodity computer. Finally, by using the HDTest-generated inputs to retrain HDC models, we can strengthen the robustness of HDC models. To the best of our knowledge, this paper presents the first effort in systematically testing this emerging brain-inspired computational model.
Λb→Λc*(2595,2625)ℓ−ν¯
 form factors from lattice QCD

We present the first lattice-QCD determination of the form factors describing the semileptonic decays $\Lambda_b \to \Lambda_c^*(2595)\ell^-\bar{\nu}$ and $\Lambda_b \to \Lambda_c^*(2625)\ell^-\bar{\nu}$, where the $\Lambda_c^*(2595)$ and $\Lambda_c^*(2625)$ are the lightest charm baryons with $J^P=\frac12^-$ and $J^P=\frac32^-$, respectively. These decay modes provide new opportunities to test lepton flavor universality and also play an important role in global analyses of the strong interactions in $b\to c$ semileptonic decays. We determine the full set of vector, axial vector, and tensor form factors for both decays, but only in a small kinematic region near the zero-recoil point. The lattice calculation uses three different ensembles of gauge-field configurations with $2+1$ flavors of domain-wall fermions, and we perform extrapolations of the form factors to the continuum limit and physical pion mass. We present Standard-Model predictions for the differential decay rates and angular observables. In the kinematic region considered, the differential decay rate for the $\frac12^-$ final state is found to be approximately 2.5 times larger than the rate for the $\frac32^-$ final state. We also test the compatibility of our form-factor results with zero-recoil sum rules.
Predicting the effects of radiotherapy based on diffusion kurtosis imaging in a xenograft mouse model of esophageal carcinoma

The aim of the present study was to assess the predictive value of diffusion kurtosis imaging (DKI) on the effects of radiotherapy in a xenograft model of esophageal cancer. A total of 40 tumor-bearing mice, established by injection of Eca-109 cells in nude mice, were used. The experimental group (n=24) received a single dose of 15 Gy (6 MV by X-ray), and the control group (n=16) did not receive any treatment. Tumor volume, apparent diffusion coefficient (ADC), mean kurtosis (MK) and mean diffusivity (MD) of the two groups were compared, and the expression of aquaporin (AQP) 3 and necrosis ratio at matched time points in xenografts were also observed. There was a significant difference between the two groups from the 7th day of radiotherapy onwards; the xenograft volume of the experimental group was significantly smaller compared with the control group (P<0.05). On the 3rd day, the ADC and MD of the experimental group was significantly higher compared with the control group, and MK was significantly lower compared with the control group (P<0.05). On the 3rd day, AQP3 expression in the experimental group was lower compared with the control group, and the proportion of necrotic cells was higher compared with the control group (P<0.05). Single large fraction dose radiotherapy inhibited the growth of a xenografted esophageal tumor. Changes in ADC, MK and MD were observed prior to morphological changes in the tumor. The change in AQP3 expression and necrosis ratio was in also agreement with the DKI parameters assessed. DKI may thus provide early predictive ability on the effect of radiotherapy in esophageal carcinoma.
RG1-VLP and Other L2-Based, Broad-Spectrum HPV Vaccine Candidates

Licensed human papillomavirus (HPV) vaccines contain virus-like particles (VLPs) self-assembled from L1 major-capsid proteins that are remarkably effective prophylactic immunogens. However, the induced type-restricted immune response limits coverage to the included vaccine types, and costly multiplex formulations, restrictive storage and distribution conditions drive the need for next generation HPV vaccines. Vaccine candidates based upon the minor structural protein L2 are particularly promising because conserved N-terminal epitopes induce broadly cross-type neutralizing and protective antibodies. Several strategies to increase the immunological potency of such epitopes are being investigated, including concatemeric multimers, fusion to toll-like receptors ligands or T cell epitopes, as well as immunodominant presentation by different nanoparticle or VLP structures. Several promising L2-based vaccine candidates have reached or will soon enter first-in-man clinical studies. RG1-VLP present the HPV16L2 amino-acid 17–36 conserved neutralization epitope “RG1” repetitively and closely spaced on an immunodominant surface loop of HPV16 L1-VLP and small animal immunizations provide cross-protection against challenge with all medically-significant high-risk and several low-risk HPV types. With a successful current good manufacturing practice (cGMP) campaign and this promising breadth of activity, even encompassing cross-neutralization of several cutaneous HPV types, RG1-VLP are ready for a first-in-human clinical study. This review aims to provide a general overview of these candidates with a special focus on the RG1-VLP vaccine and its road to the clinic.
Long-term disease control of metastatic type 2 papillary renal cell carcinoma using local treatment and molecular targeted therapy: A case report

A 46-year-old man underwent right partial nephrectomy for type 2 papillary renal cell carcinoma (PRCC) in 2011. Lung metastasis and lymph node (LN) metastases around the inferior vena cave appeared in 2012. A right radical nephrectomy and extensive LN dissection was performed and the resection of lung metastasis was performed one month after the nephrectomy. Mediastinal LN metastases occurred in 2013, and resection of the affected LNs was performed. Sunitinib and zoledronic acid was started in 2014 because mediastinal LN swelling and multiple bone metastases appeared. Sunitinib treatment was stopped soon after due to adverse events and axitinib treatment was started. Axitinib was effective and the patient had stable disease for 30 months. Adverse events were successfully controlled by dose reduction and periodic drug withdrawal schedules (for example, 5 days on, 2 days off). Axitinib was further continued for 19 months as the metastatic lesions had progressed slowly. Temsirolimus treatment was started in 2019, but it was stopped after three cycles due to interstitial pneumonia. The patient died 80 months after the initial recurrence. Using multidisciplinary treatment, durable disease control was achieved in a patient with metastatic type 2 PRCC.
Extracellular vesicles derived from oesophageal cancer containing P4HB promote muscle wasting via regulating PHGDH/Bcl‐2/caspase‐3 pathway

Abstract Cachexia, characterized by loss of skeletal muscle mass and function, is estimated to inflict the majority of patients with oesophageal squamous cell carcinoma (ESCC) and associated with their poor prognosis. However, its underlying mechanisms remain elusive. Here, we developed an ESCC‐induced cachexia mouse model using human xenograft ESCC cell lines and found that ESCC‐derived extracellular vesicles (EVs) containing prolyl 4‐hydroxylase subunit beta (P4HB) induced apoptosis of skeletal muscle cells. We further identified that P4HB promoted apoptotic response through activating ubiquitin‐dependent proteolytic pathway and regulated the stability of phosphoglycerate dehydrogenase (PHGDH) and subsequent antiapoptotic protein Bcl‐2. Additionally, we proved that the P4HB inhibitor, CCF642, not only rescued apoptosis of muscle cells in vitro, but also prevented body weight loss and muscle wasting in ESCC‐induced cachexia mouse model. Overall, these findings demonstrate a novel pathway for ESCC‐induced muscle wasting and advocate for the development of P4HB as a potential intervention target for cachexia in patients with ESCC.
Identifying and Analyzing Dependencies in and among Complex Cyber Physical Systems

Contemporary Critical Infrastructures (CIs), such as the power grid, comprise cyber physical systems that are tightly coupled, to form a complex system of interconnected components with interacting dependencies. Modelling methodologies have been suggested as proper tools to provide better insight into the dependencies and behavioural characteristics of these complex systems. In order to facilitate the study of interconnections in and among critical infrastructures, and to provide a clear view of the interdependencies among their cyber and physical components, this paper proposes a novel method, based on a graphical model called Modified Dependency Structure Matrix (MDSM). The MDSM provides a compact perspective of both inter-dependency and intra-dependency between subsystems of one complex system or two distinct systems. Additionally, we propose four parameters that allow the quantitative assessment of the characteristics of dependencies, including multi-order dependencies in large scale CIs. We illustrate the workings of the proposed method by applying it to a micro-distribution network based on the G2ELAB 14-Bus model. The results provide valuable insight into the dependencies among the network components and substantiate the applicability of the proposed method for analyzing large scale cyber physical systems.
Infrared chemiluminescence using a SISAM spectrometer. Reactions producing vibrationally excited HF

A SISAM (spectrometre interferential a selection par l'amplitude de modulation) has been used to observe infrared chemiluminescence from vibrationally excited HF formed in the reactions of F atoms with H2 and H2O2, and of O atoms with C2HF3. In experiments on F + H2→ HF(v⩽ 3)+ H, conditions could be reached where the nascent relative vibrational populations could be determined as N3: N2: N1= 0.31 ± 0.03: 0.48 ± 0.03: 0.21 ± 0.03, in good agreement with previous measurements. Similar measurements on the F + H2O2 system gave N4: N3: N2: N1= 0.15 ± 0.03: 0.25 ± 0.03: 0.31 ± 0.03: 0.30 ± 0.03 for the Nv distribution from the primary reaction F + H2O2→ HF(v⩽ 4)+ HO2. Only weak emission from HF(v= 5), and none from higher levels, could be detected under conditions where the secondary reaction, F + HO2→ HF(v⩽ 9)+ O2, should occur. It seems that this reaction does not populate the higher HF levels preferentially, probably because it proceeds via an (HOOF)+ complex. The HF(v) emission in the last system is assigned to the products of the highly exothermic secondary reaction O + CHF → HF + CO. Emission could be detected only from HF(v⩽ 3), yielding the relative populations N3: N2: N1= 0.18 ± 0.02: 0.23 ± 0.03: 0.59 ± 0.06. Finally, a short assessment of the use of SISAM spectrometry in infrared chemiluminescence experiments is presented.
The Prevalence and Characteristics of Breakthrough Cancer Pain in Patients Receiving Low Doses of Opioids for Background Pain

Simple Summary The aim of this study was to assess the prevalence and characteristics of breakthrough cancer pain (BTcP) in patients receiving low doses of opioids for background pain. This prospective study showed that in this population, BTcP prevalence was 69.8%. Many patients did not achieve a sufficient level of satisfaction with BTcP medications, particularly with oral morphine. Data also suggest that better optimization of background analgesia, though apparently acceptable, may limit the number of BTcP episodes. Abstract The aim of this study was to assess the prevalence and characteristics of breakthrough cancer pain (BTcP) in patients receiving low doses of opioids for background pain. A consecutive sample of advanced cancer patients receiving less than 60 mg/day of oral morphine equivalent (OME) was selected. Epidemiological data, background pain intensity, and current analgesic therapy were recorded. The presence of BTcP was diagnosed according to a standard algorithm. The number of BTcP episodes, intensity of BTcP, its predictability and triggers, onset duration, interference with daily activities, BTcP medications, satisfaction with BTcP medication, and time to meaningful pain relief were collected. A total of 126 patients were screened. The mean intensity of background pain was 2.71 (1.57), and the mean OME was 28.5 mg/day (SD15.8). BTP episodes were recorded in 88 patients (69.8%). The mean number/day of BTP episodes was 4.1 (SD 7.1, range 1–30). In a significant percentage of patients, BTcP was both predictable and unpredictable (23%). The BTcP onset was less than 20 min in the majority of patients. The mean duration of untreated episodes was 47.5 (SD 47.6) minutes. The mean time to meaningful pain relief after taking a BTcP medication was >20 min in 44.5% of patients. The efficacy of BTcP medication was not considered good in more than 63% of patients. Gender (females) (OR = 4.16) and lower Karnofsky (OR = 0.92) were independently associated with BTcP. A higher number of BTcP episodes/day was associated with gender (females) (p = 0.036), short duration of BTcP (p = 0.005), poorer efficacy of BTcP medication (none or mild) (p = 0.001), and late meaningful pain relief (p = 0.024). The poor efficacy of BTcP medication was independently associated with a higher number of episodes/day (OR = 0.22). In patients who were receiving low doses of opioids, BTcP prevalence was 69.8%. Many patients did not achieve a sufficient level of satisfaction with BTcP medications, particularly with oral morphine. Data also suggest that better optimization of background analgesia, though apparently acceptable, may limit the number of BTcP episodes.