Miracle-dz/UniFAR-FTUs huggingface dataset:
Playing in the Dark: No-regret Learning with Adversarial Constraints

We study a generalization of the classic Online Convex Optimization (OCO) framework by considering additional long-term adversarial constraints. Specifically, after an online policy decides its action on a round, in addition to a convex cost function, the adversary also reveals a set of $k$ convex constraints. The cost and the constraint functions could change arbitrarily with time, and no information about the future functions is assumed to be available. In this paper, we propose a meta-policy that simultaneously achieves a sublinear cumulative constraint violation and a sublinear regret. This is achieved via a black box reduction of the constrained problem to the standard OCO problem for a recursively constructed sequence of surrogate cost functions. We show that optimal performance bounds can be achieved by solving the surrogate problem using any adaptive OCO policy enjoying a standard data-dependent regret bound. A new Lyapunov-based proof technique is presented that reveals a connection between regret and certain sequential inequalities through a novel decomposition result. We conclude the paper by highlighting applications to online multi-task learning and network control problems.
Nondegeneracy of positive solutions for a biharmonic hartree equation and its applications

In this paper, we are interested in some problems related to the following biharmonic hartree equation \begin{equation*} \Delta^{2} u=(|x|^{-\alpha}\ast |u|^{p})u^{p-1},\sp \text{in}\quad\R^N. \end{equation*} where $p=\frac{2N-\alpha}{N-4}$, $N\geq 9$ and $0<\alpha<N$. First, by using the spherical harmonic decomposition and the Funk-Heck formula of the spherical harmonic functions, we prove the nondegeneracy of the positive solutions of the above biharmonic equation. As applications, we investigate the stability of a version of nonlocal Sobolev inequality \begin{equation} \int_{\R^N}|\Delta u|^{2} \geq S^{*}\left( \int_{\R^N}\Big(|x|^{-\alpha}\ast |u|^{p}\Big)u^{p} dx\right)^{\frac{1}{p}}, \end{equation} and give a gradient form remainder. Moreover, by applying a finite dimension reduction and local Poho$\check{z}$aev identity, we can also construct multi-bubble solutions for the following equation with potential \begin{equation*} \Delta^2 u+V(|x'|, x'')u =\Big(|x|^{-\alpha}\ast |u|^{p}\Big)u^{p-1}\hspace{4.14mm}x\in \mathbb{R}^N. \end{equation*} where $N\geq9$, $(x',x'')\in \mathbb{R}^2\times\mathbb{R}^{N-2}$ and $V(|x'|, x'')$ is a bounded and nonnegative function. We will show what is the role fo the dimension and the order of the Riesz potential in proving the existence result. In fact, the existence result is restricted to the range $6-\frac{12}{N-4}\leq\alpha<N$.
Comprar Impacts of Point Polluters on Terrestrial Biota · Comparative analysis of 18 contaminated areas | Kozlov, Mikhail | 9789048124664 | Springer

Tienda online donde Comprar Impacts of Point Polluters on Terrestrial Biota · Comparative analysis of 18 contaminated areas al precio 250,07 € de Kozlov, Mikhail | Zvereva, Elena | Zverev, Vitali, tienda de Libros de Medicina, Libros de Biologia - Ecologia
The Clinical Impact of the Pretreatment Platelet-to-Lymphocyte Ratio in Gastric Cancer Patients Who Receive Curative Treatment

Background/Aim: The platelet-to-lymphocyte ratio (PLR) is a promising prognostic marker in some malignancies. The present study evaluated the clinical impact of the PLR in patients with gastric cancer who underwent curative resection. Patients and Methods: This study included 258 patients who underwent curative treatment for gastric cancer between 2005 and 2020. The prognosis and clinicopathological parameters between the high- and low-PLR statuses were analyzed. Results: The overall survival (OS) stratified by each clinical factor was compared using the log-rank test, and a significant difference was observed using a pretreatment PLR of 150. When comparing the patient backgrounds between the high-PLR (PLR≥150) and low-PLR (PLR<150) groups, there were no significant differences between the two groups. The OS rates at 3 and 5 years after surgery were significantly higher at 70.8% and 60.4%, respectively, for the high-PLR group than at 83.6% and 79.7%, respectively, for the low-PLR group. Univariate and multivariate analyses of the OS showed that the PLR was a significant prognostic factor. In addition, when comparing the first recurrence sites, there were significant differences in peritoneal recurrence. Conclusion: The PLR is a significant risk factor for gastric cancer, making it a promising prognostic factor for patients with gastric cancer.
Evaluation of a self-imaging OCT for remote diagnosis and monitoring of retinal diseases

Objectives To evaluate the feasibility and accuracy of a portable, self-imaging optical coherence tomography (OCT) for measuring central subfield thickness (CST) and achieving diagnostic concordance for retinal lesions compared with clinic-based spectral-domain OCT (SD-OCT). Methods This comparative, cross-sectional study was conducted between August 2020 and February 2021. Two groups of adult participants were recruited: (1) a selected cohort of 160 participants with confirmed diagnosis and (2) a consecutive cohort of 315 participants recruited randomly. All participants underwent self-imaging OCT examination, as well as standard OCT examination. CST was automatically calculated for comparisons between the two OCT devices. Diagnostic concordance for retinal lesions and the success rate of self-imaging were assessed within the consecutive cohort. Results In the selected cohort, self-imaging OCT images yielded consistent CST with SD-OCT, with a mean difference of 0.1±7.7 µm for normal eyes, 4.9±10.6 µm for macular oedema, −1.3±9.5 µm for choroidal neovascularisation, 5.0±7.8 µm for epiretinal membrane. The self-imaging OCT also demonstrated good repeatability, with a mean test–retest difference in CST of 0.7±3.9 µm and limits of agreement ranging from −6.9 to 8.3 µm. Additionally, within the consecutive cohort, interdevice κ values ranged for detecting various retinal lesions ranged from 0.8 to 1.0, except in the cases of retinal detachment (κ=0.5). All eyes (100%) in the selected cohort and 242 eyes (76.8%) in the consecutive cohort successfully completed self-imaging. Participants spent less time on self-imaging compared with SD-OCT operated by a technician (66.7±20.1 vs 73.3±32.5, p<0.01). A majority of participants (90%) found the self-imaging process ‘easy’ and ‘comfortable’. Conclusions and relevance This study demonstrates that our self-imaging OCT and clinical-used SD-OCT are highly consistent not only in measuring the CST but also in identifying most retinal lesions.
How osteons form: A quantitative hypothesis-testing analysis of cortical pore filling and wall asymmetry

Osteon morphology provides valuable information about the interplay between different processes involved in bone remodelling. The correct quantitative interpretation of these morphological features is challenging due to the complexity of interactions between osteoblast behaviour, and the evolving geometry of cortical pores during pore closing. We present a combined experimental and mathematical modelling study to provide insights into bone formation mechanisms during cortical bone remodelling based on histological cross-sections of quiescent human osteons and hypothesis-testing analyses. We introduce wall thickness asymmetry as a measure of the local asymmetry of bone formation within an osteon and examine the frequency distribution of wall thickness asymmetry in cortical osteons from human iliac crest bone samples from women 16–78 years old. Our measurements show that most osteons possess some degree of asymmetry, and that the average degree of osteon asymmetry in cortical bone evolves with age. We then propose a comprehensive mathematical model of cortical pore filling that includes osteoblast secretory activity, osteoblast elimination, osteoblast embedment as osteocytes, and osteoblast crowding and redistribution along the bone surface. The mathematical model is first calibrated to symmetric osteon data, and then used to test three mechanisms of asymmetric wall formation against osteon data: (i) delays in the onset of infilling around the cement line; (ii) heterogeneous osteoblastogenesis around the bone perimeter; and (iii) heterogeneous osteoblast secretory rate around the bone perimeter. Our results suggest that wall thickness asymmetry due to off-centred Haversian pores within osteons, and that nonuniform lamellar thicknesses within osteons are important morphological features that can indicate the prevalence of specific asymmetry-generating mechanisms. This has significant implications for the study of disruptions of bone formation as it could indicate what biological bone formation processes may become disrupted with age or disease.
Multidisciplinary investigation into stock structure of small pelagic fishes in southern Africa

1 Chapter 1: An introduction to small pelagic fish and stock identification in southern Africa. 3 Chapter 2: Investigating stock structure in small pelagic fish of southern Africa using otolith morphology. 33 Chapter 3: Spatial and temporal variability in elemental signatures of sardine otoliths in South Africa. 61 Chapter 4: Mitochondrial and microsatellite loci indicate high diversity with low geographic structure in southern African sardine (Sardinops sagax) . 89 Chapter 5: A preliminary investigation of genetic differentiation using microsatellite loci hints a break of gene flow between sites for anchovy (Engraulis encrasicolus) off the coast of South Africa. 133 Chapter 6: Synthesis: Variable patterns of stock structure evident in a dynamic environment. 151 References 165 Glossary 191 Appendix 2: R Code used in Chapter 2 196 Appendix 3: Code used in Chapter 3 201 Appendix 4: Supplementary material from Chapter 4 205 Appendix 5: Supplementary material from Chapter 5 213
MatK impacts Differential Chloroplast Translation of Ribosomal and Photosynthetic genes by limiting spliced tRNA-K(UUU) abundance

The protein levels of chloroplast photosynthetic genes and genes related to the chloroplast genetic apparatus vary to adapt to different conditions. However, the underlying mechanisms governing these variations remain unclear. The chloroplast intron Maturase K is encoded within the trnK intron and has been suggested to be required for splicing several group IIA introns, including the trnK intron. In this study, we employed RNA immunoprecipitation followed by high-throughput sequencing (RIP-Seq) to identify MatK’s preference for binding to group IIA intron domains I and VI within target transcripts. Importantly, these domains are crucial for branch point selection, and we discovered alternative branch points in three MatK target introns, the first observed instances of alternative splicing in chloroplasts. The alternative trnK lariat structure showed increased accumulation during heat acclimation. The cognate codon of tRNA-K(UUU) is highly enriched in mRNAs encoding ribosomal proteins and ribosome profiling in a trnK-matK over-expressor exhibited elevated levels of the spliced tRNA-K(UUU). Our analysis revealed a significant up-shift in the translation of ribosomal proteins compared to photosynthetic genes. Our findings suggest the existence of a novel regulatory mechanism linked to the abundance of tRNA-K(UUU), enabling the differential expression of functional chloroplast gene groups.
The shared features of effective improvement programmes for teachers’ assessment literacy

ABSTRACT This paper aims to explore the shared features of effective professional development programmes for improving teachers’ assessment literacy (AL). On the basis of the literature review of 17 empirical studies related to teachers’ AL improvement, the features of effectiveness can be categorized into three themes: 1) What (Content): The programme content should be contextualized and tailored to the teacher’s assessment training needs; 2) How (Method): The delivery method should help to build a collaborative learning community, advocate active engagement, and provide continuing professional development opportunity; and 3) Why (Orientation): The programme should be oriented to cultivate teachers as reflective practitioners and to facilitate their identity (re)construction as assessors. The implications for future research are also discussed to direct further efforts in teachers’ AL improvement.
A Change Propagation Process for Distributed Software Architecture

In the context of software architecture evolution, understanding the impacts of a change to be applied on a distributed software architecture is necessary for various activities related to maintenance and change management. In this paper, we propose formal models and a platform based on eclipse plugins for modeling and analysis of the software architecture description and their related source codes. The proposed models aim at the construction of graph representation based on the architecture description and the software source codes. The graph implementation is mapped with facts of a distributed knowledge-based system, which performs change propagation rules to evaluate the impact of a change performed on distributed components.
SuperTweetEval: A Challenging, Unified and Heterogeneous Benchmark for Social Media NLP Research

Despite its relevance, the maturity of NLP for social media pales in comparison with general-purpose models, metrics and benchmarks. This fragmented landscape makes it hard for the community to know, for instance, given a task, which is the best performing model and how it compares with others. To alleviate this issue, we introduce a unified benchmark for NLP evaluation in social media, SuperTweetEval, which includes a heterogeneous set of tasks and datasets combined, adapted and constructed from scratch. We benchmarked the performance of a wide range of models on SuperTweetEval and our results suggest that, despite the recent advances in language modelling, social media remains challenging.
Interpretable Deep Reinforcement Learning for Optimizing Heterogeneous Energy Storage Systems

Energy storage systems (ESS) are pivotal component in the energy market, serving as both energy suppliers and consumers. ESS operators can reap benefits from energy arbitrage by optimizing operations of storage equipment. To further enhance ESS flexibility within the energy market and improve renewable energy utilization, a heterogeneous photovoltaic-ESS (PV-ESS) is proposed, which leverages the unique characteristics of battery energy storage (BES) and hydrogen energy storage (HES). For scheduling tasks of the heterogeneous PV-ESS, a practical cost function plays a crucial role in guiding operator’s strategies to maximize benefits. We develop a comprehensive cost function that takes into account degradation, capital, and operation/maintenance costs to reflect real-world scenarios. Moreover, while numerous methods excel in optimizing ESS energy arbitrage, they often rely on black-box models with opaque decision-making processes, limiting practical applicability. To overcome this limitation and enable explainable scheduling strategies, a prototype-based policy network with inherent interpretability is introduced. This network employs human-designed prototypes to guide decision-making by comparing similarities between prototypical situations and encountered situations, which allows for naturally explained scheduling strategies. Comparative results across four distinct cases demonstrate the effectiveness and practicality of our proposed pre-hoc interpretable optimization method when contrasted with black-box models.
Predictor-Rejector Multi-Class Abstention: Theoretical Analysis and Algorithms

We study the key framework of learning with abstention in the multi-class classification setting. In this setting, the learner can choose to abstain from making a prediction with some pre-defined cost. We present a series of new theoretical and algorithmic results for this learning problem in the predictor-rejector framework. We introduce several new families of surrogate losses for which we prove strong non-asymptotic and hypothesis set-specific consistency guarantees, thereby resolving positively two existing open questions. These guarantees provide upper bounds on the estimation error of the abstention loss function in terms of that of the surrogate loss. We analyze both a single-stage setting where the predictor and rejector are learned simultaneously and a two-stage setting crucial in applications, where the predictor is learned in a first stage using a standard surrogate loss such as cross-entropy. These guarantees suggest new multi-class abstention algorithms based on minimizing these surrogate losses. We also report the results of extensive experiments comparing these algorithms to the current state-of-the-art algorithms on CIFAR-10, CIFAR-100 and SVHN datasets. Our results demonstrate empirically the benefit of our new surrogate losses and show the remarkable performance of our broadly applicable two-stage abstention algorithm.
Data Flow Lifecycles for Optimizing Workflow Coordination

A critical performance challenge in distributed scientific workflows is coordinating tasks and data flows on distributed resources. To guide these decisions, this paper introduces data flow lifecycle analysis. Workflows are commonly represented using directed acyclic graphs (DAGs). Data flow lifecycles (DFL) enrich task DAGs with data objects and properties that describe data flow and how tasks interact with that flow. Lifecycles enable analysis from several important perspectives: task, data, and data flow. We describe representation, measurement, analysis, visualization, and opportunity identification for DFLs. Our measurement is both distributed and scalable, using space that is constant per data file. We use lifecycles and opportunity analysis to reason about improved task placement and reduced data movement for five scientific workflows with different characteristics. Case studies show improvements of 15×, 1.9×, and 10--30×. Our work is implemented in the DataLife tool.
Quick-and-Wide Propagation of Disaster Tweets: Why It Matters and How to Measure It

As dynamic, non-routine disaster events appear and disappear in a short period, quickly and widely disseminating emergency warnings and alerts to the public is a critical communication goal for emergency management officers and citizen journalists. Twitter has become a prominent communication medium to achieve such a communication goal, attracting academic scholars, government agencies, and industry practitioners. However, most academic research and government reports have relied on either the retweet count or retweet time to understand factors affecting the propagation of disaster information. We argue that neither measure is sufficient to reflect the extent to which disaster tweets are quickly and widely propagated. Hence, we propose a new measure called the Propagation Index (PI) to better evaluate quick and wide propagation of disaster information. Using two Twitter datasets, we empirically examine the proposed measure in association with the Twitter features and compare its statistical results with those of the retweet count and retweet time. Our findings suggest that the PI more accurately captures how quickly and widely disaster tweets are propagated than the other measures. Therefore, this study contributes to academia, governments, and industry to improve their understanding of the propagation of disaster information on Twitter.
Interannual variations of area burnt in Tasmanian bushfires: relationships with climate and predictability

The area burnt each summer in Tasmania is related to coincident (summer) climate variables, especially the total summer rainfall. The relationship with temperature is weaker and largely reflects the relationship between rainfall and temperature. As the El Nino–Southern Oscillation is known to be related to Australian rainfall and simple indices of this phenomenon form the basis of the operational seasonal climate forecast scheme used in Australia, it is not surprising that indices of the El Nino–Southern Oscillation can also, it appears, provide a potentially useful forecast system for Tasmanian bushfire extent. In particular, sea surface temperatures in the Coral Sea during winter are correlated with the area burnt in the following summer. The effect of summer rainfall on the area burnt each year suggests that global warming may not simply lead to increased burning, contrasting with the situation in other parts of the globe. A weak, long-term decline in area burnt appears to be due to a weak increase in summer rainfall.
Effects of material property variations on slip estimates for subduction interface slow‐slip events

We investigate the influence of elastic heterogeneity on geodetic inversions of slow‐slip events by inverting for slip distributions of four events along the Hikurangi Margin, New Zealand. We generate Green's functions using a finite element code in conjunction with a New Zealand‐wide seismic velocity model to assign elastic properties. We find that these heterogeneous models typically require ~20% less slip than homogeneous models in cases where the slip is deep or there is reasonable geodetic coverage above the slipping region. In cases where the slip is shallow (and mostly offshore) and there is little geodetic coverage directly above the slipping region, the heterogeneous models can predict significantly larger amounts of slip (42% in our study). These changes in the predicted amounts of slip have important implications for quantifying slip budgets accommodated by slow slip at subduction zones worldwide.
Security-SLA-Guaranteed Service Function Chaining Deployment in Cloud-Fog Computing Networks

— Network Function Virtualization (NFV) has gained prominence in next-generation cloud computing, such as the fog-based radio access network, due to their ability to support better QoS in network resource allocation. However, most of the current SFC deployment works do not consider the Security-Service-Level-Agreement (SSLA) in the deployment solution. Therefore, in this work, we propose the SSLA of the placement of Service Function Chains (SFCs) to defend against attacks. Firstly, we formulate linear programming to guarantee the SSLA in the deployment solution. Then, we propose the Maximal-Security SFCs deploying algorithm (MS), to maximize the security of the SFC deployment. However, the MS algorithm will cause a higher deployment cost. To reduce the deployment cost, we propose the Minimal-Cost and SSLA-Guaranteed SFCs deploying algorithm (MCSG), to minimize the placement cost and guarantee the SSLA. In order to reduce the blocking ratio caused by MCSG, the Minimal-Cost and SSLA-Guaranteed SFCs deploying algorithm with Feedback Adjustment (MCSG-FA) is proposed. Finally, we evaluate our proposed algorithms, and the simulations prove which the blocking ratio and the deployment cost are better than that of the compared algorithm when meeting the SSLA requirements.
Passive-blind Image Forgery Detection Techniques

In this Paper, we will review the research area of passive-blind image forgery detection techniques, Image analysis for finding out the condition of animage without relying on pre-registration or pre-embedded information.We consider the main functions of passive-blind image forensics as being image forgery detection and image source identification. In this vein,we provide a detailed review ofPassive-blind Image Forgery.The resources available to the researchers and the challenges facingthe passive-blind image forgery detection techniquesresearch.