Miracle-dz/UniFAR-FTUs huggingface dataset:
RSU Placement Method Considering Road Elements for Information Dissemination

—In Intelligent Transportation System (ITS), communication with RoadSide Unit (RSU) is expected that weak connectivity of vehicle-to-vehicle communication can be improved since the power average of RSU is large. However, to deploy and maintain RSUs is costly. Therefore, it is necessary to effectively place RSUs within limited cost. Many opportunities to communicate with vehicles are at intersections with a lot of trafﬁc volume. However, it is necessary to consider not only the trafﬁc volume but also a connection relation of the road network because buildings prevent radio waves. In this paper, we propose an RSU placement method considering road elements that affect radio wave spreading. This method consists of two actions: calculation of RSU placement priority with considering road elements affecting radio wave spreading and operation of updating RSU placement priority. As a result of simulation, our proposal is particularly effective in a scenario considering information relay because the communication performance of this method was higher than or equivalent to that of other RSU placements. Further, it is found that our proposal was possible to suppress redundant RSU placement by updating operation of RSU placement priority in a scenario which is not considering information relay.
Exposure-Response Analyses of Tigecycline Efﬁcacy in Patients with Complicated Skin and Skin-Structure Infections (cid:1)

Exposure-response analyses were performed for the microbiological and clinical efﬁcacy of tigecycline in the treatment of complicated skin and skin-structure infections, where Staphylococcus aureus and streptococci are the predominant pathogens. A prospective method was developed to create homogeneous patient populations for PK-PD analyses. Evaluable patients from three clinical trials were pooled for analysis. Patients received a tigecycline 100-mg loading dose/50 mg every 12 h or a 50-mg loading dose/25 mg every 12 h. At the test-of-cure visit, microbiologic and clinical responses were evaluated. Patients were prospectively evaluated and classiﬁed into cohorts based on baseline pathogens: S. aureus only (cohort 1), monomicrobial S. aureus or streptococci (cohort 2), two gram-positive pathogens (cohort 3), polymicrobial (cohort 4), or other monomicrobial infec- tions (cohort 5). A prospective procedure for combining cohorts was used to increase the sample size. Logistic regression evaluated steady-state 24-h area under the concentration-time curve (AUC 24 )/MIC ratio as a predictor of response, and classiﬁcation and regression tree (CART) analyses were utilized to determine AUC/MIC breakpoints. Analysis began with pooled cohorts 2 and 3, the focus of these analyses, and included 35 patients with 40 S. aureus and/or streptococcal pathogens. CART analyses identiﬁed a signiﬁcant AUC/MIC breakpoint of 17.9 ( P (cid:1) 0.0001 for microbiological response and P (cid:1) 0.0376 for clinical response). The continuous AUC/MIC ratio was predictive of microbiological response based on sample size ( P (cid:1) 0.0563). Analysis of all pathogens combined decreased the ability to detect exposure-response relationships. The prospective approach of creating homogeneous populations based on S. aureus and streptococci pathogens was critical for identifying exposure-response relationships. covariate. as
Climate ethics with an ethnographic sensibility --Manuscript

: What responsibilities does each of us have to reduce or limit our greenhouse gas emissions? Advocates of individual emissions reductions acknowledge that there are limits to what we can reasonably demand from individuals. Climate ethics has not yet systematically explored those limits. Instead, it has become popular to suggest that such judgements should be ‘context-sensitive’ but this does not tell us what role different contextual factors should play in our moral thinking. The current approach to theory development in climate ethics is not likely to be the most effective way to fill this gap. In existing work, climate ethicists use hypothetical cases to consider what can be reasonably demanded of individuals in particular situations. In contrast, ‘climate ethics with an ethnographic sensibility’ uses qualitative social science methods to collect original data in which real individuals describe their own situations. These real-life cases are more realistic, more detailed and cover a broader range of circumstances than hypothetical cases. Normative analysis of real-life cases can help us to develop a more systematic understanding of the role that different contextual factors should play in determining individual climate responsibilities. It can also help us to avoid the twin dangers of ‘idealization’ and ‘special pleading’. Abstract What responsibilities does each of us have to reduce or limit our greenhouse gas emissions? Advocates of individual emissions reductions acknowledge that there are limits to what we can reasonably demand from individuals. Climate ethics has not yet systematically explored those limits. Instead, it has become popular to suggest that such judgements should be ‘context-sensitive’ but this does not tell us what role different contextual factors should play in our moral thinking. The current approach to theory development in climate ethics is not likely to be the most effective way to fill this gap. In existing work, climate ethicists use hypothetical cases to consider what can be reasonably demanded of individuals in particular situations. In contrast, ‘climate ethics with an ethnographic sensibility ’ uses qualitative social science methods to collect original data in which real individuals describe their own situations. These real-life cases are more realistic, more detailed and cover a broader range of circumstances than hypothetical cases. Normative analysis of real-life cases can help us to develop a more systematic understanding of the role that different contextual factors should play in determining individual climate responsibilities. It can also help us to avoid the twin dangers of ‘idealization’ and ‘special pleading’.
Soft gluon resummation for associated ttH production at the LH C

A b s tr a c t: We perform resummation of soft gluon corrections to the total cross section for the process pp ^ t t H . The resummation is carried out at next-to-leading-logarithmic (NLL) accuracy using the Mellin space technique, extending its application to the class of 2 ^ 3 processes. We present an analytical result for the soft anomalous dimension for a hadronic production of two coloured massive particles in association with a colour singlet. We discuss the impact of resummation on the numerical prediction for the associated Higgs boson production with top quarks at the LHC. LHC collision energy of 8, 13 and 14 TeV. The NLO+NLL predictions show a significant reduc­ tion of the scale uncertainty, compared to NLO results. The reduction of the positive and negative scale errors amounts to around 20-30% of the NLO error for V S = 13,14 TeV and to around 25-35% for V S = 8 TeV. This general reduction trend is not sustained for the
Secure Scrum and OpenSAMM for Secure Software Development

—Recent years saw serious attacks on software, e.g., the Heartbleed attack. Improving software security should be a main concern in all software development projects. Currently, Scrum is a popular agile software development method, used all around companies and universities. However, addressing IT security in Scrum projects is different to traditional security planning, which usually requires detailed planning in an initial planning phase. After this planning phase, only minor adjustments are expected. In contrast, Scrum is known for very little initial planning and for constant changes. This paper presents Secure Scrum, an extension to Scrum, that deals with the characteristics of security planning in Scrum. Secure Scrum is a variation of the Scrum framework that puts an emphasis on implementation of security related issues without the need of changing the underlying Scrum process or inﬂuencing team dynamics. To implement Secure Scrum in an organization, it helps to utilize a framework for strategic security planning. This paper uses the example of the OpenSAMM (Open Software Assurance Maturity Model) to show how Secure Scrum could be implemented in the ﬁeld. A ﬁeld test of Secure Scrum shows that the security level of software developed using Secure Scrum is higher then the security level of software developed using standard Scrum and that Secure Scrum is even suitable for use by non-security experts.
Alexandra, Ribeiro, ESTABLISHING URBAN GARDENS ON VACANT LAND WHILE CONSIDERING INTERNATIONAL GOOD PRACTICES: A LEGAL CASE STUDY FROM PORTUGAL.

There is a gap in most of the countries legal framework respecting its ability to connect vacant land and urban gardens. Hence research is needed to understand how regulation on vacant land might be designed to promote a more sustainable purpose to it. Urban gardens are a type of urban agriculture that could be potentiated by such. The aim of this paper is to show how that can be done through the Municipal Master Plans (MMP)legal and regulatory framework for the Portuguese case, by reviewing worldwide good practices on vacant land restorations for urban sustainable development. The paper comprises a literature review on good practices adopted in different countries regarding vacant lot restoration. The evaluation of good practices built on the achievement of three pillars of sustainability. Five Portuguese MMP were used, as empirical data, to support the design of a new legal and regulatory framework. The goal is to enhance the sustainable destination of vacant land by converting them into urban gardens.The analysis of these MMPs evidenced they disregard urban gardens as a tool to promote urban sustainability in spite of global trends to make urban territorial planning and management instruments greener. An additional outcome of this paper is to categorise different types of vacant land in the five municipalities under analysis according to their suitableness for urban garden conversion. The design of the legal framework enhancing of the conversion of vacant land into urban garden will contribute to the 2030 international agenda goals’ achievement. The proposal would create an innovative legal framework in the case of Portugal, that could be replicated by other countries.
DMSO_A_291343 617..625

1Aix Marseille University School of Medicine — La Timone Medical Campus, EA 3279: CEReSS — Health Service Research and Quality of Life Center, Marseille, France; 2Assistance Publique, Hôpitaux de Marseille (AP-HM), Marseille, France Introduction: The proportion of new dialysis patients with comorbidities increased by an average of 5.6% per year in the Provence-Alpes-Côte d’Azur (PACA) region, with major increases in obese, cancer, and diabetic patients. This study aimed to describe comorbidity profiles among obese–diabetic end-stage renal disease (ESRD) patients in the Renal Epidemiology and Information Network (REIN) registry of the PACA region of France on December 31, 2018. Methods: Data for this retrospective cross-sectional study were retrieved from the REIN registry of the PACA region. Data were analyzed using two models. Firstly, the ESRD patients were divided into two groups and binary logistic regression model used for the analysis of the data. Secondly, ESRD patients were divided into four groups and multinomial logistic regression model used. Univariate analysis was performed for group comparison using x and t-tests, while binary logistic and multinomial logistic regression models were used for multivariate analysis to derive ORs and 95% CIs. Results: Among the 4,491 ESRD patients in this study, 623 were obese–diabetic and 3,868 nonobese–nondiabetic and obese only/ diabetic only. Obese–diabetic ESRD patients were younger (<75 years, OR 0.46, p<0.001), smoked less (OR 0.51, p<0.001), were mainly dialyzed at centers (OR 1.29, p=0.014), and less likely to be on the renal transplant waiting list (OR 0.46, p<0.001) compared to the other group. Obese–diabetic ESRD patients also had more comorbidities, including cardiovascular diseases (OR 1.38, p=0.028), coronary insufficiency (OR 1.49, p=0.001) and chronic obstructive pulmonary disease (OR 1.75, p<0.001), but had fewer cases of cancer (OR 0.68, p=0.024) compare to the other group. Conclusion: Obese–diabetic patients with ESRD have many specific characteristics. These patients were younger, but had more cardiovascular comorbidities and were less likely to be on the waiting list for transplantation. They should receive special attention and be the subject of prevention and therapeutic education.
Capacity of the range of random walk: The law of the iterated logarithm

We establish both the $\limsup$ and the $\liminf$ law of the iterated logarithm (LIL), for the capacity of the range of a simple random walk in any dimension $d\ge 3$. While for $d \ge 4$, the order of growth in $n$ of such LIL at dimension $d$ matches that for the volume of the random walk range in dimension $d-2$, somewhat surprisingly this correspondence breaks down for the capacity of the range at $d=3$. We further establish such LIL for the Brownian capacity of a $3$-dimensional Brownian sample path and novel, sharp moderate deviations bounds for the capacity of the range of a $4$-dimensional simple random walk.
Analysis of a microcirculatory windkessel model using photoplethysmography with green light: A pilot study

In this study, a vasomotion quantification method using a photoplethysmography prototype, which performs near-infrared spectroscopy in combination with green light, is proposed. A structure that suppresses the motion artifact and that is held by the eyeglasses on the back of the ear enables the relative concentration changes of total hemoglobin and pulse wave amplitude to be measured during exercise with and without the presence of wind impacting the face. We established a microcirculatory windkessel model including arteriovenous anastomoses estimated from the blood flow changes in the depth direction that were acquired using three wavelengths of light and reproduced the vasomotion on a computer. The values predicted by the model were in good agreement with the measured values. The extracted vasomotion can be used to understand autonomic control by the central nervous system.
Sequence Model Imitation Learning with Unobserved Contexts

We consider imitation learning problems where the learner's ability to mimic the expert increases throughout the course of an episode as more information is revealed. One example of this is when the expert has access to privileged information: while the learner might not be able to accurately reproduce expert behavior early on in an episode, by considering the entire history of states and actions, they might be able to eventually identify the hidden context and act as the expert would. We prove that on-policy imitation learning algorithms (with or without access to a queryable expert) are better equipped to handle these sorts of asymptotically realizable problems than off-policy methods. This is because on-policy algorithms provably learn to recover from their initially suboptimal actions, while off-policy methods treat their suboptimal past actions as though they came from the expert. This often manifests as a latching behavior: a naive repetition of past actions. We conduct experiments in a toy bandit domain that show that there exist sharp phase transitions of whether off-policy approaches are able to match expert performance asymptotically, in contrast to the uniformly good performance of on-policy approaches. We demonstrate that on several continuous control tasks, on-policy approaches are able to use history to identify the context while off-policy approaches actually perform worse when given access to history.
PalQuant: Accelerating High-precision Networks on Low-precision Accelerators

Recently low-precision deep learning accelerators (DLAs) have become popular due to their advantages in chip area and energy consumption, yet the low-precision quantized models on these DLAs bring in severe accuracy degradation. One way to achieve both high accuracy and efficient inference is to deploy high-precision neural networks on low-precision DLAs, which is rarely studied. In this paper, we propose the PArallel Low-precision Quantization (PalQuant) method that approximates high-precision computations via learning parallel low-precision representations from scratch. In addition, we present a novel cyclic shuffle module to boost the cross-group information communication between parallel low-precision groups. Extensive experiments demonstrate that PalQuant has superior performance to state-of-the-art quantization methods in both accuracy and inference speed, e.g., for ResNet-18 network quantization, PalQuant can obtain 0.52\% higher accuracy and 1.78$\times$ speedup simultaneously over their 4-bit counter-part on a state-of-the-art 2-bit accelerator. Code is available at \url{https://github.com/huqinghao/PalQuant}.
Thermodynamic Formalism on the Skorokhod space: the continuous time Ruelle operator, entropy, pressure, entropy production and expansiveness

Consider the semi-flow given by the continuous time shift $\Theta_t:\mathcal{D} \to \mathcal{D} $, $t \geq 0$, acting on the $\mathcal{D} $ of \textit{c\`{a}dl\`{a}g} paths $w: [0,\infty) \to S^1$, where $S^1$ is the unitary circle. We equip the space $\mathcal{D} $ with the Skorokhod metric, and we show that the semi-flow is expanding. We also introduce a stochastic semi-group $e^{t\, L}$, $t \geq 0,$ where $L$ acts linearly on continuous functions $f:S^1\to\mathbb{R}$. This stochastic semigroup and an initial vector of probability $\pi$ define an associated stationary shift-invariant probability $\mathbb{P}$ on the Polish space $\mathcal{D} $. Given such $\mathbb{P}$ and an H\"older potential $V:S^1 \to \mathbb{R}$, we define a continuous time Ruelle operator, which is described by a family of linear operators $ \mathbb{L}^t_V$, $t\geq 0,$ acting on continuous functions $\varphi: S^1 \to \mathbb{R}$. More precisely, given any H\"older $V$ and $t\geq 0$, the operator $ \mathbb{L}^t_V$, is defined by $\varphi \to \psi(y) = \mathbb{L}^t_V(\varphi)(y)= \int_{w(t)=y} e^{ \int_0^t V(w(s)) ds} \varphi (w(0)) d \mathbb{P}(w). $ For some specific parameters we show the existence of an eigenvalue $\lambda_V$ and an associated H\"older eigenfunction $\varphi_V>0$. After a coboundary procedure we obtain another stochastic semigroup, with infinitesimal generator $L_V$, and this will define a new probability $\mathbb{P}_V$ on $\mathcal{D}$, which we call the Gibbs (or, equilibrium) probability for the potential $V$. In this case, we define entropy for some shift-invariant probabilities on $\mathcal{D}$, and we consider a variational problem of pressure. Finally, we define entropy production and present our main result: we analyze its relation with time-reversal and symmetry of $L$. We also show that the continuous-time shift $\Theta_t$, acting on the Skorohod space $D$, is expanding.
Optimal Rates for Regularized Conditional Mean Embedding Learning

We address the consistency of a kernel ridge regression estimate of the conditional mean embedding (CME), which is an embedding of the conditional distribution of $Y$ given $X$ into a target reproducing kernel Hilbert space $\mathcal{H}_Y$. The CME allows us to take conditional expectations of target RKHS functions, and has been employed in nonparametric causal and Bayesian inference. We address the misspecified setting, where the target CME is in the space of Hilbert-Schmidt operators acting from an input interpolation space between $\mathcal{H}_X$ and $L_2$, to $\mathcal{H}_Y$. This space of operators is shown to be isomorphic to a newly defined vector-valued interpolation space. Using this isomorphism, we derive a novel and adaptive statistical learning rate for the empirical CME estimator under the misspecified setting. Our analysis reveals that our rates match the optimal $O(\log n / n)$ rates without assuming $\mathcal{H}_Y$ to be finite dimensional. We further establish a lower bound on the learning rate, which shows that the obtained upper bound is optimal.
The Econometrics of Financial Duration Modeling

We establish new results for estimation and inference in financial durations models, where events are observed over a given time span, such as a trading day, or a week. For the classical autoregressive conditional duration (ACD) models by Engle and Russell (1998, Econometrica 66, 1127-1162), we show that the large sample behavior of likelihood estimators is highly sensitive to the tail behavior of the financial durations. In particular, even under stationarity, asymptotic normality breaks down for tail indices smaller than one or, equivalently, when the clustering behaviour of the observed events is such that the unconditional distribution of the durations has no finite mean. Instead, we find that estimators are mixed Gaussian and have non-standard rates of convergence. The results are based on exploiting the crucial fact that for duration data the number of observations within any given time span is random. Our results apply to general econometric models where the number of observed events is random.
Optimizing counterdiabaticity by variational quantum circuits

Using counterdiabatic (CD) driving—aiming at suppression of diabatic transition—in digitized adiabatic evolution has garnered immense interest in quantum protocols and algorithms. However, improving the approximate CD terms with a nested commutator ansatz is a challenging task. In this work, we propose a technique of finding optimal coefficients of the CD terms using a variational quantum circuit. By classical optimization routines, the parameters of this circuit are optimized to provide the coefficients corresponding to the CD terms. Then their improved performance is exemplified in Greenberger–Horne–Zeilinger state preparation on the nearest-neighbour Ising model. Finally, we also show the advantage over the usual quantum approximation optimization algorithm, in terms of fidelity with bounded time. This article is part of the theme issue ‘Shortcuts to adiabaticity: theoretical, experimental and interdisciplinary perspectives’.
Spinning up the Surface: Evidence for Planetary Engulfment or Unexpected Angular Momentum Transport?

In this paper, we report the potential detection of a nonmonotonic radial rotation profile in a low-mass lower-luminosity giant star. For most low- and intermediate-mass stars, the rotation on the main sequence seems to be close to rigid. As these stars evolve into giants, the core contracts and the envelope expands, which should suggest a radial rotation profile with a fast core and a slower envelope and surface. KIC 9267654, however, seems to show a surface rotation rate that is faster than its bulk envelope rotation rate, in conflict with this simple angular momentum conservation argument. We improve the spectroscopic surface constraint, show that the pulsation frequencies are consistent with the previously published core and envelope rotation rates, and demonstrate that the star does not show strong chemical peculiarities. We discuss the evidence against any tidally interacting stellar companion. Finally, we discuss the possible origin of this unusual rotation profile, including the potential ingestion of a giant planet or unusual angular momentum transport by tidal inertial waves triggered by a close substellar companion, and encourage further observational and theoretical efforts.