Miracle-dz/UniFAR-FTUs huggingface dataset:
Disordered Plamonics and Complex Metamaterials

Disordered Plasmonics and Complex Metamaterials Juan Sebastian Totero Gongora Complex systems are ensembles of interconnected elements where mutual interaction and an optimized amount of disorder produce advanced functionalities. These systems are abundant in our daily experience: typical examples are the brain, biological ecosystems, society, and finance. In the last century, researchers have investigated the fundamental properties of disordered systems, unveiling fascinating and counterintuitive dynamics. The main aim of this Dissertation is the study of a new platform of disorder-enhanced photonics systems, denoted as Complex Metamaterials. Due to its ultrafast time scale nanophotonics represents an ideal framework to investigate and harness complex dynamics. Starting from the theoretical modeling of disordered plasmonic systems, I discuss advanced real-life applications, including the generation of highly-resistant structural colors from porous metal surfaces and the realization of early-stage cancer detectors based on surface roughness and self-similarity. In addition to the effects of structural disorder on plasmonic systems I also investigate the complex emission dynamics from non-conventional nanolasers. Lasers represent the quintessential example of a complex photonic system due to the simultaneous presence of strong nonlinearities and multi-mode interactions. At the same time, the integration of nanolasers with silicon-based electronic circuitry represents one of the greatest technological challenges in the field of nanophotonics. By combining ab-initio simulations and analytical modeling, I characterize the nonlinear emission from three-dimensional plasmonic nanolasers known as SPASERs. My results show for the first time the occurrence of a spontaneous rotational emission in spherical SPASERs, which originates from the nonlinear interaction of several lasing modes. I further discuss how rotating nanolasers can be employed as a fundamental building block for 5 integrated quantum simulators, random information sources, and brain-inspired photonics platforms. Leveraging the practical limitations of SPASERs, I also propose a novel concept of near-field nanolaser based on invisible anapole modes. Anapoles constitute a peculiar state of electromagnetic radiation with no far-field emission and they have been recently discovered in dielectric nanoparticles. By integrating anapole lasers in a silicon-compatible platform, I discuss several advanced applications such as spontaneously polarized nanolasers and ultrafast pulse generators on-chip.
Behavior learning using emotional conditioning

We present a novel way to design a control system for a robot, using emotions as a way to produce richer internal states. We believe that using a single scalar as an evaluation of the quality of the policy and stating that the goal of the agent is to gather reward, as it is proposed by reinforcement learning, is not an appropriate granularity for creating an autonomous control system : even with a fine-tuned reward function, efficient on a specific task, it is often impractical to derive any useful knoweldge from it in order to build more flexible, neuromimetics control systems. A complete shift of paradigm is necessary for a bottom up approach\,: the robot is given pain and pleasure perception circuits and we examine how emotions arise and are the basis for respondant and operant conditioning. Inspired from the cerebral circuits of superior mammals responsible of this behavior, we propose an implementation in an autonomous robot using models of adaptive neural networks.
Segmentation of 3D dynamic meshes based on Reeb graph approach

This paper presents a new segmentation approach, for 3D dynamic meshes, based upon ideas from Morse theory and Reeb graphs. The segmentation process is performed using topological analysis of smooth functions defined on 3D mesh surface. The main idea is to detect critical nodes located on the mobile and immobile parts. Particularly, we define a new continuous scalar function, used for Reeb graph construction. This function is based on the heat diffusion properties. Clusters are obtained according to the values of scalar function while adding a refinement step. The latter is based on curvature information in order to adjust segmentation boundaries. Experimental results performed on 3D dynamic articulated meshes demonstrate the high accuracy and stability under topology changes and various perturbations through time.
Weighted-CS for reconstruction of highly under-sampled dynamic MRI sequences

This paper investigates the potential of the new Weighted-Compressive Sensing approach which overcomes the major limitations of other compressive sensing and outperforms current state-of-the-art methods for low-rate reconstruction of sequences of MRI images. The underlying idea of this approach is to use the image of the previous time instance to extract an estimated probability model for the image of interest, and then use this model to guide the reconstruction process. This is motivated by the observation that MRI images are hugely sparse in Wavelet domain and the sparsity changes slowly over time.
Return to Where? You Can't Exploit What You Can't Find

Detecting and preventing exploitation of memory corruption vulnerabilities is highly challenging. Until now, no countermeasure has been able to fully prevent sophisticated exploitation techniques, such as return-oriented programming (ROP). Recent control-flow integrity (CFI) defenses from Google and Microsoft can be bypassed by constructing a ROP payload that adheres to the control-flow constraints or by exploiting implementation flaws. Microsoft's EMET has less overhead than full CFI, but offers less protection in return, and can be bypassed. Probabilistic countermeasures based on memory layout randomization (such as ASLR) are already in widespread use. However, the Pwn2own competitions have repeatedly demonstrated that attackers can bypass code randomization using memory leaks in browsers. To reduce the impact of memory disclosure, recent defenses utilize execute-only memory. In this work we show that execute-only memory is insufficient and that these solutions can still be bypassed. In particular, we show how to determine the code layout by analyzing pointers in the heap and on the stack without ever reading the code. On the defensive side, we build a comprehensive yet practical defense called Readactor that counters both direct reading of code and indirect layout disclosure through analysis of code pointers. We employ a thin hypervisor and a kernel patch to utilize true hardware execute-only memory, and prevent direct reading of code in Linux processes. We hide all code pointers in readable memory using a patched version of the LLVM compiler. We deploy a number of techniques to break ROP gadget chains and disorient the adversary. Specifically, we hide code pointers by converting them into direct jumps stored in execute-only memory to prevent indirect layout disclosure. Our solution is efficient, because it activates previously unused hardware capabilities in modern x86 processors and is often faster than industry CFI implementations. Our solution is also highly practical; we were able to automatically apply our defense to the Chromium web browser. Finally, our solution is comprehensive; we also protect the dynamically generated code emitted by the V8 JavaScript JIT compiler.
Diabetes-induced dysfunction of retinal Müller cells.

PURPOSE This study tested the hypothesis that the function of the glutamate transporter in retinal Müller cells is compromised early in the course of diabetes by a mechanism involving oxidation. Dysfunction of this transporter, which removes glutamate from the extracellular space, may play a critical role in the disruption of glutamate homeostasis that occurs in the diabetic retina. Because glutamate is toxic to retinal neurons and is likely to exacerbate oxidative stress, elucidation of the mechanisms by which diabetes elevates the concentration of this amino acid may help to better understand the pathogenesis of diabetic retinopathy. METHODS Müller cells were freshly isolated from normal rats and those made diabetic by streptozotocin injection. The activity of the Müller cell glutamate transporter, which is electrogenic, was monitored via the perforated-patch configuration of the patch-clamp technique. RESULTS Four weeks after the onset of hyperglycemia, dysfunction of the Müller cell glutamate transporter was detected (P = .005). After 13 weeks of streptozotocin-induced diabetes, the activity of this transporter was decreased by 67% (P = .001). Consistent with oxidation causing this dysfunction, exposure to a disulfide-reducing agent rapidly restored the activity of this transporter in Müller cells from diabetic retinas. CONCLUSIONS Soon after the onset of experimental diabetes, the function of the glutamate transporter in Müller cells is decreased by a mechanism that is likely to involve oxidation. The demonstration that the activity of this transporter can be rapidly restored raises the possibility that targeting this molecule for therapeutic intervention may restore glutamate homeostasis and, thereby, ameliorate sight-threatening complications of diabetic retinopathy.
Groupwise analytics via adaptive MapReduce

Shared-nothing systems such as Hadoop vastly simplify parallel programming when processing disk-resident data whose size exceeds aggregate cluster memory. Such systems incur a significant performance penalty, however, on the important class of “groupwise set-valued analytics” (GSVA) queries in which the data is dynamically partitioned into groups and then a set-valued synopsis is computed for some or all of the groups. Key examples of synopses include top-k sets, bottom-k sets, and uniform random samples. Applications of GSVA queries include micro-marketing, root-cause analysis for problem diagnosis, and fraud detection. A naive approach to executing GSVA queries first reshuffles all of the data so that all records in a group are at the same node and then computes the synopsis for the group. This approach can be extremely inefficient when, as is typical, only a very small fraction of the records in each group actually contribute to the final groupwise synopsis, so that most of the shuffling effort is wasted. We show how to significantly speed up GSVA queries by slightly modifying the shared-nothing environment to allow tasks to occasionally access a small, common data structure; we focus on the Hadoop setting and use the “Adaptive MapReduce” infrastructure of Vernica et al. to implement the data structure. Our approach retains most of the advantages of a system such as Hadoop while significantly improving GSVA query performance, and also allows for incremental updating of query results. Experiments show speedups of up to 5x. Importantly, our new technique can potentially be applied to other shared-nothing systems with disk-resident data.
Economic efficiency evaluation of national economic development zones based on DEA and SFA

Considering comprehensively of the actual development of the national economic and technological development zones in China and the availability of the evaluation data, the paper used data envelopment analysis (DEA) and stochastic frontier analysis (SFA) to evaluate the economic efficiency of China's national development zones with different input and output indicators. The article had come up the economic efficiency ranking of different national economic development zones. Finally, the results of analysis is evaluated detailed and the strategies and recommendations of increasing the efficiency of economic and technological development zones are proposed.
An Examination of Composition-Property Relationships for Methotrexate-Loaded Glass Ionomer Cements

xi LIST OF ABBREVIATIONS AND SYMBOLS USED. xii ACKNOWLEDGEMENTS. xiv CHAPTER 1: INTRODUCTION . 1 1.1 Overview of Metastatic Disease in Bone . 1 1.2 Metastasis of the Vertebral Column . 3 1.2. 1 Disturbance of Bone Micro-Environment . 4 1.2. 2 Metastatic-Induced Skeletal-Related Events and Pathologic Vertebral Compression Fractures . 5 1.3 Prognosis and Clinical Course of Skeletal Metastases . 7 1.3. 1 Interventions for the Management of Metastatic-Related VCFs . 7 1.3. 1.1 Non-Operative Management for Spinal Metastases . 8 1.3. 1.2 Operative Management for Spinal Metastases . 8 1.4 Bone Cements as Drug Delivery Systems . 14 1.4. 1 Drug Release from PMMA Cements . 16 1.4. 2 Drug Release from Composite Resin Cements . 22 1.4. 3 Drug Release from Calcium Phosphate Systems . 23 1.4. 4 Limitations with Existing PVP/PKP Bone Cements . 25 1.4. 5 The Ideal Bone Cement Delivery System . 27 1.5 Glass Ionomer Cements for the Restoration of MBD-Related VCFs . 28 1.5. 1 The Development of Al-Free GICs . 30 1.5. 2 Drug Release from GICs . 33 1.6 The Problem Statement . 35
Inhibitory effects of Cinnamomum burmannii Blume stem bark extract and trans-cinnamaldehyde on nasopharyngeal carcinoma cells; synergism with cisplatin

Nasopharyngeal carcinoma (NPC) is a malignancy that occurs in the epithelium of the nasopharynx. The standard treatment of NPC patients with locoregionally advanced stages is problematic and is often associated with toxicities. Therefore, it is essential to screen for naturally occurring compounds with strong apoptosis-inducing activity and minimal toxicity. This study investigated the effects of the standardized methanol extract of Cinnamomum burmannii Blume stem bark and its main constituent, trans-cinnamaldehyde (TCA), on human NPC cell lines. The content of TCA in C. burmannii methanol extract was standardized to be 13.61% w/w by means of gas chromatography-mass spectrometry (GC-MS). NPC cell proliferation was clearly inhibited within 24 h of treatment, with TCA exhibiting greater activity than the methanol extract. TCA was more active against NPC cells compared with cisplatin. There was a pronounced downregulation of the proliferation markers, Ki67 and proliferating cell nuclear antigen (PCNA) in the TCA-treated cells; while morphological observation indicated the induction of apoptosis. Caspase activation and prominent DNA damage, which are markers of apoptosis induction were detected. TCA demonstrated the ability to scavenge nitric oxide. The simultaneous combination of TCA and cisplatin produced synergistic anti-proliferative effects. Collectively, these data indicate the potential use of TCA for the treatment of NPC.
DARK BURSTS IN THE SWIFT ERA: THE PALOMAR 60 INCH-SWIFT EARLY OPTICAL AFTERGLOW CATALOG

We present multicolor optical observations of long-duration γ-ray bursts (GRBs) made over a three-year period with the robotic Palomar 60 inch telescope (P60). Our sample consists of all 29 events discovered by Swift for which P60 began observations less than 1 hr after the burst trigger. We were able to recover 80% of the optical afterglows from this prompt sample, and we attribute this high efficiency to our red coverage. Like Melandri et al. (), we find that a significant fraction (≈50%) of Swift events show a suppression of the optical flux with regard to the X-ray emission (the so-called “dark” bursts). Our multicolor photometry demonstrates this is likely due in large part to extinction in the host galaxy. We argue that previous studies, by selecting only the brightest and best-sampled optical afterglows, have significantly underestimated the amount of dust present in typical GRB environments.
A New Model of Minimum Variance Hedge Ratio: EGARCH-Copula-EWMA

This paper proposes a new model to calculate minimum variance hedge ratio based on EGARCH-CopulaEWMA model. Based on Minimum variance hedging model, the new model calculates Futures yield rate by EGARCH model and Spot yield rate by EWMA model respectively when it calculates the median correlation coefficient of Futures yield rate and Spot yield rate. The new model make the nonlinear phase-matching of Futures yield rate and Spot yield rate which improve the accuracy of the correlation coefficient in case the price of Futures or spot has large fluctuations. We choose the Aluminum Futures contracts AL1208 and the price of Aluminum spot in the same period to test the model, the effectiveness of the portfolio is 0.7862707 which reduce the risk comparing with non-hedging. The conclusion shows that the model can be used in hedging to lessen the risk of spot price effectively. KeywordsHedge ratio; EWMA-Copula-EGARCH model; Futures; Spot
The Collie: a wait-free compacting collector

We describe the Collie collector, a fully concurrent compacting collector that uses transactional memory techniques to achieve wait-free compaction. The collector uses compaction as the primary means of reclaiming unused memory, and performs "individual object transplantations" as transactions. We introduce new terms and requirements useful for analyzing concurrent relocating collectors, including definitions of referrer sets, object transplantation and the notion of individually transplantable objects. The Collie collector builds on these terms and on a detailed analysis of an object's legal states during compaction. Collie uses a combination of read barriers, write barriers and transactional memory operations. Its read-barrier supports fast, direct object referencing while using a bound, constant time, wait- free triggering path. Collie thereby avoids the constant indirection cost of Brooks [9] style barriers or handle-based heaps [25]. Collie is demonstrated using speculative multi-address atomicity [11], a form of hardware transactional memory supported by the Azul Vega architecture [2]. We evaluate the Collie collector on the Azul platform, on which previous concurrent collectors such as the Pauseless Collector [12] and its generational variant [30] have been commercially available for several years. We discuss Collie's performance while running sustained workloads, and compare it to the Pauseless collector on the same platform. The Collie collector provides significant MMU [5] improvements even in the 1-msec time windows compared to the Pauseless collector. At the same time, it matches Pauseless in throughput and in the ability to scale to large heap sizes. We believe that the Collie collector is the first garbage collector to leverage hardware-assisted transactional memory. While Collie directly leverages Vega's speculative multi-address atomicity feature (SMA) [11], its design can be easily adapted to other hardware- assisted transactional memory systems. Specifically, the upcoming Intel TSX instruction set extensions [21] include capabilities similar to SMA. We expect Collie to be easily implementable on future commodity servers based on Intel Haswell processors and following processor generations.
Learning Weighted Lower Linear Envelope Potentials in Binary Markov Random Fields

Markov random fields containing higher-order terms are becoming increasingly popular due to their ability to capture complicated relationships as soft constraints involving many output random variables. In computer vision an important class of constraints encode a preference for label consistency over large sets of pixels and can be modeled using higher-order terms known as lower linear envelope potentials. In this paper we develop an algorithm for learning the parameters of binary Markov random fields with weighted lower linear envelope potentials. We first show how to perform exact energy minimization on these models in time polynomial in the number of variables and number of linear envelope functions. Then, with tractable inference in hand, we show how the parameters of the lower linear envelope potentials can be estimated from labeled training data within a max-margin learning framework. We explore three variants of the lower linear envelope parameterization and demonstrate results on both synthetic and real-world problems.
Identifying the Epitope Regions of Therapeutic Antibodies Based on Structure Descriptors

Therapeutic antibodies are widely used for disease detection and specific treatments. However, as an exogenous protein, these antibodies can be detected by the human immune system and elicit a response that can lead to serious illnesses. Therapeutic antibodies can be engineered through antibody humanization, which aims to maintain the specificity and biological function of the original antibodies, and reduce immunogenicity. However, the antibody drug effect is synchronously reduced as more exogenous parts are replaced by human antibodies. Hence, a major challenge in this area is to precisely detect the epitope regions in immunogenic antibodies and guide point mutations of exogenous antibodies to balance both humanization level and drug effect. In this article, the latest dataset of immunoglobulin complexes was collected from protein data bank (PDB) to discover the spatial features of immunogenic antibody. Furthermore, a series of structure descriptors were generated to characterize and distinguish epitope residues from non-immunogenic regions. Finally, a computational model was established based on structure descriptors, and results indicated that this model has the potential to precisely predict the epitope regions of therapeutic antibodies. With rapid accumulation of immunoglobulin complexes, this methodology could be used to improve and guide future antibody humanization and potential clinical applications.
DM EMI Noise Prediction for Constant On-Time, Critical Mode Power Factor Correction Converters

Critical conduction mode (CRM) power factor correction (PFC) converters are widely used in industries. For CRM PFC converters, high inductor current ripples generate high differential mode (DM) electromagnetic interference (EMI) noise, which calls for big EMI filters. On the other hand, the switching frequency varies during a half line cycle. The characteristics of the EMI in CRM PFC converters have not been carefully investigated and the worst case DM EMI noise has not been identified. The design of an EMI filter is difficult. In this paper, a mathematical model based on the principle of quasi-peak noise detection is proposed to predict the EMI noise in CRM PFC converters. The developed model is verified by experimental results. Based on this model, the worst case DM EMI noise can be predicted. This will greatly help in the design of EMI filters for CRM PFC converters.
An Inter-Landmark Approach to 4-D Shape Extraction and Interpretation: Application to Myocardial Motion Assessment in MRI

This paper presents a novel approach to shape extraction and interpretation in 4-D cardiac magnetic resonance imaging data. Statistical modeling of spatiotemporal interlandmark relationships is performed to enable the decomposition of global shape constraints and subsequently of the image analysis tasks. The introduced descriptors furthermore provide invariance to similarity transformations and thus eliminate pose estimation errors in the presence of image artifacts or geometrical inconsistencies. A set of algorithms are derived to address key technical issues related to constrained boundary tracking, dynamic model relaxation, automatic initialization, and dysfunction localization. The proposed framework is validated with a relatively large dataset of 50 subjects and compared to existing statistical shape modeling methods. The results indicate increased adaptation to spatiotemporal variations and imaging conditions.