Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of LDPC codes for the Advanced Satellite Broadcasting System

We have been studying an advanced satellite broadcasting system which is aimed at improving the Integrated Services Digital Broadcasting for Satellite (ISDB-S) system. By making use of LDPC codes and the reduced roll-off factor, this advanced system can increase its transmission channel capacity to 30% that of the ISDB-S one. Furthermore, by applying multi-level amplitude phase shift keying (M-APSK) modulation schemes, we can increase the transmission channel capacity. We report on LDPC codes that are designed for the transmission format of the advanced satellite broadcasting system. The computer simulation results of B/Q/8PSK performances under the AWGN channel model are also reported. We also discuss and report the optimization result gained from a computer simulation of the radius ratio of LDPC-coded 16APSK and 32APSK modulation, which is proposed in this advanced system, with respect to Bit Error Rate (BER) under the AWGN channel model.
In-depth fuzz testing of IKE implementations

The correctness of security protocols can be proved using formal models. Typically, a security protocol is proven correct at a high level of abstraction, hiding away the implementation details. To execute the protocol on a real system, software engineers take up the task to implement the protocol. Programming is an error-prone activity: despite the fact that a security protocol is proven correct, its implementation may have vulnerabilities, which can be exploited by attackers. In this work we consider the problem of testing security protocol implementations for vulnerabilities, assuming that a formal model of the protocol is given. Finding security vulnerabilities is nontrivial. Even if a system correctly implements the model and behaves as expected when it performs intended tasks, i.e. tasks that are specified in the model, it is difficult to check that the implementation does not exhibit any additional behaviors, i.e. behaviors that are not specified in the model. Behaviors that are unintentionally implemented in the system can be dangerous and may introduce vulnerabilities in the system. When programmers implement the protocol, they need to consider how the system handles unexpected events, e.g. how the system reacts when the disk is full or how to handle malformed input. Such unexpected events are the low-level details that are typically abstracted away in the formal model. We can virtually split the program into two parts: (1) functional part which handles the expected behavior of the system, and (2) error handling part which implements how the program handles unexpected events. The top 4 most dangerous software errors listed at the Common Weakness Enumeration database1 are due to lack of or improper handling of unexpected inputs [6]. Typically, the functional part of the program is well specified in the model and it is less likely that the programmers will implement it incorrectly. We believe that due to lack of specification on how the implementation
Development of a Computerized Dynamic Assessment System on Number Sense

The purpose of this study was to develop a computerized and interactive number sense dynamic assessment system (CNSDA) on number sense to investigate the characteristics of elementary students’ performance. Number sense is the ability of awareness and reasoning for the relationships among the numbers embedded in the authentic context or situation. Around 150 fifth grade students were sampled. The results show that the adaptive hint system of CNSDA could promote the students’ number sense effectively. The correlation coefficients between CNSDA posttest and the Mathematic Computerized Adaptive Ability Test (MCAT) and the Computerized Estimation Test (CET) are higher than the static pretest. For the students with weaker number sense, CNSDA is a helpful learning and assessing resource.
RTP payload format for H.264/SVC scalable video coding

The scalable extension of H.264/AVC, known as scalable video coding or SVC, is currently the main focus of the Joint Video Team’s work. In its present working draft, the higher level syntax of SVC follows the design principles of H.264/AVC. Self-contained network abstraction layer units (NAL units) form natural entities for packetization. The SVC specification is by no means finalized yet, but nevertheless the work towards an optimized RTP payload format has already started. RFC 3984, the RTP payload specification for H.264/AVC has been taken as a starting point, but it became quickly clear that the scalable features of SVC require adaptation in at least the areas of capability/operation point signaling and documentation of the extended NAL unit header. This paper first gives an overview of the history of scalable video coding, and then reviews the video coding layer (VCL) and NAL of the latest SVC draft specification. Finally, it discusses different aspects of the draft SVC RTP payload format, including the design criteria, use cases, signaling and payload structure.
Drug Repurposing: The Anthelmintics Niclosamide and Nitazoxanide Are Potent TMEM16A Antagonists That Fully Bronchodilate Airways

There is an unmet need in severe asthma where approximately 40% of patients exhibit poor β-agonist responsiveness, suffer daily symptoms and show frequent exacerbations. Antagonists of the Ca2+-activated-Cl− channel, TMEM16A, offers a new mechanism to bronchodilate airways and block the multiple contractiles operating in severe disease. To identify TMEM16A antagonists we screened a library of ~580,000 compounds. The anthelmintics niclosamide, nitazoxanide and related compounds were identified as potent TMEM16A antagonists that blocked airway smooth muscle depolarization and contraction. To evaluate whether TMEM16A antagonists resist use- and inflammatory-desensitization pathways limiting β-agonist action, we tested their efficacy under harsh conditions using maximally contracted airways or airways pretreated with a cytokine cocktail. Stunningly, TMEM16A antagonists fully bronchodilated airways, while the β-agonist isoproterenol showed only partial effects. Thus, antagonists of TMEM16A and repositioning of niclosamide and nitazoxanide represent an important additional treatment for patients with severe asthma and COPD that is poorly controlled with existing therapies. It is of note that drug repurposing has also attracted wide interest in niclosamide and nitazoxanide as a new treatment for cancer and infectious disease. For the first time we identify TMEM16A as a molecular target for these drugs and thus provide fresh insights into their mechanism for the treatment of these disorders in addition to respiratory disease.
Surface Plasmon Resonance, Formation Mechanism, and Surface Enhanced Raman Spectroscopy of Ag+-Stained Gold Nanoparticles

A series of recent works have demonstrated the spontaneous Ag+ adsorption onto gold surfaces. However, a mechanistic understanding of the Ag+ interactions with gold has been controversial. Reported herein is a systematic study of the Ag+ binding to AuNPs using several in-situ and ex-situ measurement techniques. The time-resolved UV-vis measurements of the AuNP surface plasmonic resonance revealed that the silver adsorption proceeds through two parallel pseudo-first order processes with a time constant of 16(±2) and 1,000(±35) s, respectively. About 95% of the Ag+ adsorption proceeds through the fast adsorption process. The in-situ zeta potential data indicated that this fast Ag+ adsorption is driven primarily by the long-range electrostatic forces that lead to AuNP charge neutralization, while the time-dependent pH data shows that the slow Ag+ binding process involves proton-releasing reactions that must be driven by near-range interactions. These experimental data, together with the ex-situ XPS measurement indicates that adsorbed silver remains cationic, but not as a charged-neutral silver atom proposed by the anti-galvanic reaction mechanism. The surface-enhanced Raman activities of the Ag+-stained AuNPs are slightly higher than that for AuNPs, but significantly lower than that for the silver nanoparticles (AgNPs). The SERS feature of the ligands on the Ag+-stained AuNPs can differ from that on both AuNPs and AgNPs. Besides the new insights to formation mechanism, properties, and applications of the Ag+-stained AuNPs, the experimental methodology presented in this work can also be important for studying nanoparticle interfacial interactions.
Multiple Variables at the Leukocyte Cell Surface Impact Fc γ Receptor-Dependent Mechanisms

Fc γ receptors (FcγR) expressed on the surface of human leukocytes bind clusters of immunoglobulin G (IgG) to induce a variety of responses. Many therapeutic antibodies and vaccine-elicited antibodies prevent or treat infectious diseases, cancers and autoimmune disorders by binding FcγRs, thus there is a need to fully define the variables that impact antibody-induced mechanisms to properly evaluate candidate therapies and design new intervention strategies. A multitude of factors influence the IgG-FcγR interaction; one well-described factor is the differential affinity of the six distinct FcγRs for the four human IgG subclasses. However, there are several other recently described factors that may prove more relevant for disease treatment. This review covers recent reports of several aspects found at the leukocyte membrane or outside the cell that contribute to the cell-based response to antibody-coated targets. One major focus is recent reports covering post-translational modification of the FcγRs, including asparagine-linked glycosylation. This review also covers the organization of FcγRs at the cell surface, and properties of the immune complex. Recent technical advances provide high-resolution measurements of these often-overlooked variables in leukocyte function and immune system activation.
Exposing the Causal Effect of Body Mass Index on the Risk of Type 2 Diabetes Mellitus: A Mendelian Randomization Study

Introduction: High body mass index (BMI) is a positive associated phenotype of type 2 diabetes mellitus (T2DM). Abundant studies have observed this from a clinical perspective. Since the rapid increase in a large number of genetic variants from the genome-wide association studies (GWAS), common SNPs of BMI and T2DM were identified as the genetic basis for understanding their associations. Currently, their causality is beginning to blur. Materials and Methods: To classify it, a Mendelian randomisation (MR), using genetic instrumental variables (IVs) to explore the causality of intermediate phenotype and disease, was utilized here to test the effect of BMI on the risk of T2DM. In this article, MR was carried out on GWAS data using 52 independent BMI SNPs as IVs. The pooled odds ratio (OR) of these SNPs was calculated using inverse-variance weighted method for the assessment of 5 kg/m2 higher BMI on the risk of T2DM. The leave-one-out validation was conducted to identify the effect of individual SNPs. MR-Egger regression was utilized to detect potential pleiotropic bias of variants. Results: We obtained the high OR (1.470; 95% CI 1.170 to 1.847; P = 0.001), low intercept (0.004, P = 0.661), and small fluctuation of ORs {from -0.039 [(1.412 – 1.470) / 1.470)] to 0.075 [(1.568– 1.470) / 1.470)] in leave-one-out validation. Conclusion: We validate the causal effect of high BMI on the risk of T2DM. The low intercept shows no pleiotropic bias of IVs. The small alterations of ORs activated by removing individual SNPs showed no single SNP drives our estimate.
Realistic Image Generation using Region-phrase Attention

The Generative Adversarial Network (GAN) has recently been applied to generate synthetic images from text. Despite significant advances, most current state-of-the-art algorithms are regular-grid region based; when attention is used, it is mainly applied between individual regular-grid regions and a word. These approaches are sufficient to generate images that contain a single object in its foreground, such as a "bird" or "flower". However, natural languages often involve complex foreground objects and the background may also constitute a variable portion of the generated image. Therefore, the regular-grid based image attention weights may not necessarily concentrate on the intended foreground region(s), which in turn, results in an unnatural looking image. Additionally, individual words such as "a", "blue" and "shirt" do not necessarily provide a full visual context unless they are applied together. For this reason, in our paper, we proposed a novel method in which we introduced an additional set of attentions between true-grid regions and word phrases. The true-grid region is derived using a set of auxiliary bounding boxes. These auxiliary bounding boxes serve as superior location indicators to where the alignment and attention should be drawn with the word phrases. Word phrases are derived from analysing Part-of-Speech (POS) results. We perform experiments on this novel network architecture using the Microsoft Common Objects in Context (MSCOCO) dataset and the model generates $256 \times 256$ conditioned on a short sentence description. Our proposed approach is capable of generating more realistic images compared with the current state-of-the-art algorithms.
Sclerotinia sclerotiorum Thioredoxin Reductase Is Required for Oxidative Stress Tolerance, Virulence, and Sclerotial Development

Sclerotinia sclerotiorum is a destructive ascomycete plant pathogen with worldwide distribution. Extensive research on different aspects of this pathogen’s capability to cause disease will help to uncover clues about new ways to safely control Sclerotinia diseases. The thioredoxin (Trx) system consists of Trx and thioredoxin reductase (TrxR), which play critical roles in maintenance of cellular redox homeostasis. In this study, we functionally characterized a gene encoding a TrxR (SsTrr1) in S. sclerotiorum. The amino acids of SsTrr1 exhibited high similarity with reported TrxRs in plant pathogens and targeted silencing of SsTrr1 lead to a decrease in TrxR activities of mycelium. SsTrr1 showed high expression levels during hyphae growth, and the levels decreased at the different stages of sclerotial development. SsTrr1 gene-silenced strains produced a smaller number of larger sclerotia on potato dextrose agar medium. The observations were consistent with the inhibitory effects on sclerotial development by the TrxR inhibitor, anrunofin. The expression of SsTrr1 showed a dramatic increase under the oxidative stress and the hyphal growth of gene-silenced strains showed more sensitivity to H2O2. SsTrr1 gene-silenced strains also showed impaired virulence in different hosts. Taken together, our results suggest that SsTrr1 encodes a TrxR that is of great important for oxidative stress tolerance, virulence, and sclerotial development of S. sclerotiorum.
Tumor-Specific Delivery of Immune Checkpoint Inhibitors by Engineered AAV Vectors

Immune checkpoint inhibitors (ICIs) can block distinct receptors on T cells or tumor cells thus preventing T cell inactivation and tumor immune escape. While the clinical response to treatment with ICIs in cancer patients is impressive, this therapy is often associated with a number of immune-related adverse events. There is therefore a need to explore innovative strategies of tumor-specific delivery of ICIs. Delivery of therapeutic proteins on a genetic level can be accomplished with viral vectors including those derived from adeno-associated virus (AAV). Here, we assessed the tumor-targeted Her2-AAV, a receptor-targeted AAV vector binding to the tumor antigen Her2/neu for cell entry, as vehicle for ICI gene delivery. Initially, we packaged the coding sequence of a scFv-Fc fusion protein directed against mouse programmed cell death protein-1 (PD-1) into Her2-AAV. Upon transduction of Her2/neu+ RENCA cells, AAV-encoded αPD-1 was readily detectable in the cell culture supernatant and revealed specific binding to its target antigen. In vivo, in BALB/c mice bearing subcutaneous RENCA-Her2/neu tumors, Her2-AAV mediated specific gene delivery into tumor tissue upon intravenous administration as verified by luciferase gene transfer and in vivo imaging thus demonstrating unimpaired tumor-targeting by Her2-AAV vectors in immunocompetent animals. When delivering the αPD-1 gene, levels of ICI were similar in tumor tissue for Her2-AAV and AAV2 but substantially reduced in liver for Her2-AAV. When combined with chemotherapy a tendency for reduced progression of tumor growth was documented for Her2-AAV treated mice. To get closer to the clinical situation, AAV constructs that deliver the complete coding sequence of the therapeutic antibody nivolumab which is directed against human PD-1 were generated next. The AAV-Nivolumab constructs were expressed and released from transduced MDA-MB-453 cells in vitro and from RENCA-Her2/neu cells upon intratumoral as well as intravenous administration in vivo. Antibody processing and expression levels were further improved through optimization of construct design. In conclusion, we provide proof-of-principle for redirecting the biodistribution of ICIs from liver and serum to tumor tissue by the use of engineered AAV vectors. This strategy can be easily combined with other types of immunotherapeutic concepts.
GPU Accelerated AES Algorithm

It has been widely accepted that Graphics Processing Units (GPU) is one of promising schemes for encryption acceleration, in particular, the support of complex mathematical calculations such as integer and logical operations makes the implementation easier; however, complexes such as parallel granularity, memory allocation still imposes a burden on real world implementations. In this paper, we propose a new approach for Advanced Encryption Standard accelerations, including both encryption and decryption. Specifically, we adapt the Electronic Code Book mode for cryptographic transformation, look up table scheme for fast lookup, and a granularity of one state per thread for thread scheduling. Our experimental results offer researchers a good understanding on GPU architectures and software accelerations. In addition, both our source code and experimental results are freely available.
Specific single- and multi-objective evolutionary algorithms for the chance-constrained knapsack problem

The chance-constrained knapsack problem is a variant of the classical knapsack problem where each item has a weight distribution instead of a deterministic weight. The objective is to maximize the total profit of the selected items under the condition that the weight of the selected items only exceeds the given weight bound with a small probability of α. In this paper, we consider problem-specific single-objective and multi-objective approaches for the problem. We examine the use of heavy-tail mutations and introduce a problem-specific crossover operator to deal with the chance-constrained knapsack problem. Empirical results for single-objective evolutionary algorithms show the effectiveness of our operators compared to the use of classical operators. Moreover, we introduce a new effective multi-objective model for the chance-constrained knapsack problem. We use this model in combination with the problem-specific crossover operator in multi-objective evolutionary algorithms to solve the problem. Our experimental results show that this leads to significant performance improvements when using the approach in evolutionary multi-objective algorithms such as GSEMO and NSGA-II.
Towards a Better Indicator for Cache Timing Channels

Recent studies highlighting the vulnerability of computer architecture to information leakage attacks have been a cause of significant concern. Among the various classes of microarchitectural attacks, cache timing channels are especially worrisome since they have the potential to compromise users' private data at high bit rates. Prior works have demonstrated the use of cache miss patterns to detect these attacks. We find that cache miss traces can be easily spoofed and thus they may not be able to identify smarter adversaries. In this work, we show that \emph{cache occupancy}, which records the number of cache blocks owned by a specific process, can be leveraged as a stronger indicator for the presence of cache timing channels. We observe that the modulation of cache access latency in timing channels can be recognized through analyzing pairwise cache occupancy patterns. Our experimental results show that cache occupancy patterns cannot be easily obfuscated even by advanced adversaries that successfully evade cache miss-based detection.
Task-Based Augmented Contour Trees with Fibonacci Heaps

This paper presents a new algorithm for the fast, shared memory, multi-core computation of augmented contour trees on triangulations. In contrast to most existing parallel algorithms our technique computes augmented trees, enabling the full extent of contour tree based applications including data segmentation. Our approach completely revisits the traditional, sequential contour tree algorithm to re-formulate all the steps of the computation as a set of independent local tasks. This includes a new computation procedure based on Fibonacci heaps for the join and split trees, two intermediate data structures used to compute the contour tree, whose constructions are efficiently carried out concurrently thanks to the dynamic scheduling of task parallelism. We also introduce a new parallel algorithm for the combination of these two trees into the output global contour tree. Overall, this results in superior time performance in practice, both in sequential and in parallel thanks to the OpenMP task runtime. We report performance numbers that compare our approach to reference sequential and multi-threaded implementations for the computation of augmented merge and contour trees. These experiments demonstrate the run-time efficiency of our approach and its scalability on common workstations. We demonstrate the utility of our approach in data segmentation applications.
Cutting Your Losses: Learning Fault-Tolerant Control and Optimal Stopping under Adverse Risk

Recently, there has been a surge in interest in safe and robust techniques within reinforcement learning (RL). Current notions of risk in RL fail to capture the potential for systemic failures such as abrupt stoppages from system failures or surpassing of safety thresholds and the appropriate responsive controls in such instances. We propose a novel approach to risk minimisation within RL in which, in addition to taking actions that maximise its expected return, the controller learns a policy that is robust against stoppages due to an adverse event such as an abrupt failure. The results of the paper cover fault-tolerant control in \textit{worst-case scenarios} under random stopping and optimal stopping, all in unknown environments. By demonstrating that the class of problems is represented by a variant of stochastic games, we prove the existence of a solution which is a unique fixed point equilibrium of the game and characterise the optimal controller behaviour. We then introduce a value function approximation algorithm that converges to the solution through simulation in unknown environments.