Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards Simple but Efficient Next Utterance Ranking

Retrieval-based dialogue systems converse with humans by ranking candidate responses according to their relevance to the history of the conversation (context). Recent studies either match the context with the response on only sequence level or use complex architectures to match them on the word and sequence levels. We show that both information levels are important and that a simple architecture can capture them effectively. We propose an end to endmulti level response retrieval dialogue system. Our model learns to match the context with the best response by computing their semantic similarity on the word and sequence levels. Empirical evaluation on two dialogue datasets shows that our model outperforms several state of the art systems and performs as good as the best system while being conceptually simpler.
Enhancing Attention by Synchronizing Respiration and Fingertip Pressure: A Pilot Study Using Functional Near-Infrared Spectroscopy

Sustained attention is a fundamental ability ensuring effective cognitive processing and can be enhanced by meditation practice. However, keeping a focused meditative state is challenging for novices because involuntary mind-wandering frequently occurs during their practice. Inspired by the potential of force-control tasks in invoking internal somatic attention, we proposed a haptics-assisted meditation (HAM) to help reduce mind-wandering and enhance attention. During HAM, participants were instructed to maintain awareness on the respiration and meanwhile adjust bimanual fingertip pressures to keep synchronized with the respiration. This paradigm required somatosensory attention as a physiological foundation, aiming to help novices meditate starting with the body and gradually gain essential meditation skills. A cross-sectional study on 12 novices indicated that the participants reported less mind-wandering during HAM compared with the classic breath-counting meditation (BCM). In a further longitudinal study, the experimental group with 10 novices showed significantly improved performance in several attentional tests after 5 days’ practice of HAM. They tended to show more significant improvements in a few tests than did the control group performing the 5-day BCM practice. To investigate the brain activities related to HAM, we applied functional near-infrared spectroscopy (fNIRS) to record cerebral hemodynamic responses from the prefrontal and sensorimotor cortices when performing HAM, and we assessed the changes in cerebral activation and functional connectivity (FC) after the 5-day HAM practice. The prefrontal and sensorimotor regions demonstrated a uniform activation when performing HAM, and there was a significant increase in the right prefrontal activation after the practice. We also observed significant changes in the FC between the brain regions related to the attention networks. These behavioral and neural findings together provided preliminary evidence for the effectiveness of HAM on attention enhancement in the early stage of meditation learning.
Immunogenicity and Protective Efficacy of Seasonal Human Live Attenuated Cold-Adapted Influenza Virus Vaccine in Pigs

Influenza A virus infection is a global health threat to livestock and humans, causing substantial mortality and morbidity. As both pigs and humans are readily infected with influenza viruses of similar subtype, the pig is a robust and appropriate model for investigating swine and human disease. We evaluated the efficacy of the human cold-adapted 2017–2018 quadrivalent seasonal LAIV in pigs against H1N1pdm09 challenge. LAIV immunized animals showed significantly reduced viral load in nasal swabs. There was limited replication of the H1N1 component of the vaccine in the nose, a limited response to H1N1 in the lung lymph nodes and a low H1N1 serum neutralizing titer. In contrast there was better replication of the H3N2 component of the LAIV, accompanied by a stronger response to H3N2 in the tracheobronchial lymph nodes (TBLN). Our data demonstrates that a single administration of human quadrivalent LAIV shows limited replication in the nose and induces detectable responses to the H1N1 and H3N2 components. These data suggest that pigs may be a useful model for assessing LAIV against influenza A viruses.
Log2vec: A Heterogeneous Graph Embedding Based Approach for Detecting Cyber Threats within Enterprise

Conventional attacks of insider employees and emerging APT are both major threats for the organizational information system. Existing detections mainly concentrate on users' behavior and usually analyze logs recording their operations in an information system. In general, most of these methods consider sequential relationship among log entries and model users' sequential behavior. However, they ignore other relationships, inevitably leading to an unsatisfactory performance on various attack scenarios. We propose log2vec, a heterogeneous graph embedding based modularized method. First, it involves a heuristic approach that converts log entries into a heterogeneous graph in the light of diverse relationships among them. Next, it utilizes an improved graph embedding appropriate to the above heterogeneous graph, which can automatically represent each log entry into a low-dimension vector. The third component of log2vec is a practical detection algorithm capable of separating malicious and benign log entries into different clusters and identifying malicious ones. We implement a prototype of log2vec. Our evaluation demonstrates that log2vec remarkably outperforms state-of-the-art approaches, such as deep learning and hidden markov model (HMM). Besides, log2vec shows its capability to detect malicious events in various attack scenarios.
Enforcing Last-Level Cache Partitioning through Memory Virtual Channels

Ensuring fairness or providing isolation between multiple workloads with different characteristics that are colocated on a single, shared-memory system is a challenge. Recent multicore processors provide last-level cache (LLC) hardware partitioning to provide hardware support for isolation, with the cache partitioning often specified by the user. While more LLC capacity often results in higher performance, in this work we identify that a workload allocated more LLC capacity result in worse performance on real-machine experiments, which we refer to as MiW (more is worse). Through various controlled experiments, we identify that another workload with less LLC capacity causes more frequent LLC misses. The workload stresses the main-memory system shared by both workloads and degrades the performance of the former workload even if the LLC partitioning is used (a balloon effect). To resolve this problem, we propose virtualizing the datapath of main-memory controllers and dedicating the memory virtual channels (mVCs) to each group of applications, grouped for LLC partitioning. mVC can further fine-tune the performance of groups by differentiating buffer sizes among mVCs. It can reduce the total system cost by executing latency-critical and throughput-oriented workloads together on shared machines, of which performance criteria can be achieved only on dedicated machines if mVCs are not supported. Experiments on a simulated chip multiprocessor show that our proposals effectively eliminate the MiW phenomenon, hence providing additional opportunities for workload consolidation in a datacenter. Our case study demonstrates potential savings of machine count by 21.8% with mVC, which would otherwise violate a service level objective (SLO).
Neural Network Overlay Using FPGA DSP Blocks

With the increasing wider application of neural networks, there has been significant focus on accelerating this class of computations. Larger, more complex networks are being proposed in a variety of domains, requiring more powerful computation platforms. The inherent parallelism and regularity of neural network structures means custom architectures can be adopted for this purpose. FPGAs have been widely used to implement such accelerators because of their flexibility, achievable performance, efficiency, and abundant peripherals. While platforms that utilize multicore CPUs and GPUs are also competitive, FPGAs offer superior energy efficiency, and a wider space of optimisations to enhance performance and efficiency. FPGAs are also more suitable for performing such computations at the edge, where multicore CPUs and GPUs are are less likely to be used and energy efficiency is paramount.
Your Cache Has Fallen: Cache-Poisoned Denial-of-Service Attack

Web caching enables the reuse of HTTP responses with the aim to reduce the number of requests that reach the origin server, the volume of network traffic resulting from resource requests, and the user-perceived latency of resource access. For these reasons, a cache is a key component in modern distributed systems as it enables applications to scale at large. In addition to optimizing performance metrics, caches promote additional protection against Denial of Service (DoS) attacks. In this paper we introduce and analyze a new class of web cache poisoning attacks. By provoking an error on the origin server that is not detected by the intermediate caching system, the cache gets poisoned with the server-generated error page and instrumented to serve this useless content instead of the intended one, rendering the victim service unavailable. In an extensive study of fifteen web caching solutions we analyzed the negative impact of the CachePoisoned DoS (CPDoS) attack-as we coined it. We show the practical relevance by identifying one proxy cache product and five CDN services that are vulnerable to CPDoS. Amongst them are prominent solutions that in turn cache high-value websites. The consequences are severe as one simple request is sufficient to paralyze a victim website within a large geographical region. The awareness of the newly introduced CPDoS attack is highly valuable for researchers for obtaining a comprehensive understanding of causes and countermeasures as well as practitioners for implementing robust and secure distributed systems.
Fallout: Leaking Data on Meltdown-resistant CPUs

Meltdown and Spectre enable arbitrary data leakage from memory via various side channels. Short-term software mitigations for Meltdown are only a temporary solution with a significant performance overhead. Due to hardware fixes, these mitigations are disabled on recent processors. In this paper, we show that Meltdown-like attacks are still possible on recent CPUs which are not vulnerable to Meltdown. We identify two behaviors of the store buffer, a microarchitectural resource to reduce the latency for data stores, that enable powerful attacks. The first behavior, Write Transient Forwarding forwards data from stores to subsequent loads even when the load address differs from that of the store. The second, Store-to-Leak exploits the interaction between the TLB and the store buffer to leak metadata on store addresses. Based on these, we develop multiple attacks and demonstrate data leakage, control flow recovery, and attacks on ASLR. Our paper shows that Meltdown-like attacks are still possible, and software fixes with potentially significant performance overheads are still necessary to ensure proper isolation between the kernel and user space.
HandPoseMenu: Hand Posture-Based Virtual Menus for Changing Interaction Mode in 3D Space

A system control technique (changing the interaction mode) is needed to provide various spatial interaction techniques for virtual, augmented and mixed reality (VR/AR/MR) applications. We propose HandPoseMenu, a hand posture-based virtual menus system in 3D space. HandPoseMenu recognizes the non-dominant hand's posture using a depth sensor that is attached to a wearable display and presents the virtual menu corresponding to the hand posture beside the non-dominant hand. When the user selects a desired function among the presented menu as a dominant hand, the interaction mode changes. The combination of the two system controls (graphical menu and hand posture) makes it possible to display the menu that the user wants to use in 3D space. This paper describes the implementation of HandPoseMenu and its application.
SmartLobby: A 24/7 Human-Machine-Interaction Space within an Office Environment

In this work, we present the SmartLobby, an intelligent environment system integrated into the lobby of a research institute. The SmartLobby is running 24/7, i.e. it can be used any time by anyone without any preparations. The goal of the system is to conduct research in the domain of human machine cooperation. One important first step towards this goal is a detailed human state modeling and estimation. As the system is built into the lobby area, also people having no scientific background are interacting with the system which strongly reduces the bias in the collected data. On software side the SmartLobby mainly integrates state-of-the-art algorithms that enable a thorough analysis of human behavior and state. These algorithms constitute the fundamental basis for the development of higher level system components. Here, we present our system with its various hardware and software components. Thereby, we focus on the realization of a non-intrusive head-eye-tracking as a key component to continuously observe persons using the system. A first multi-week lasting experiment utilizes this capability to investigate a method for content personalization, which demonstrates the effectiveness of the whole system.
Asynchronous Task-Based Execution of the Reverse Time Migration for the Oil and Gas Industry

We propose a new framework for deploying Reverse Time Migration (RTM) simulations on distributed-memory systems equipped with multiple GPUs. Our software, TB-RTM, infrastructure engine relies on the StarPU dynamic runtime system to orchestrate the asynchronous scheduling of RTM computational tasks on the underlying resources. Besides dealing with the challenging hardware heterogeneity, TB-RTM supports tasks with different workload characteristics, which stress disparate components of the hardware system. RTM is challenging in that it operates intensively at both ends of the memory hierarchy, with compute kernels running at the highest level of the memory system, possibly in GPU main memory, while I/O kernels are saving solution data to fast storage. We consider how to span the wide performance gap between the two extreme ends of the memory system, i.e., GPU memory and fast storage, on which large-scale RTM simulations routinely execute. To maximize hardware occupancy while maintaining high memory bandwidth throughout the memory subsystem, our framework presents the new-of-core (OOC) feature from StarPU to prefetch data solutions in and out not only from/to the GPU/CPU main memory but also from/to the fast storage system. The OOC technique may trigger opportunities for overlapping expensive data movement with computations. TB-RTM framework addresses this challenging problem of heterogeneity with a systematic approach that is oblivious to the targeted hardware architectures. Our resulting RTM framework can effectively be deployed on massively parallel GPU-based systems, while delivering performance scalability up to 500 GPUs.
Stretchable self-healable semiconducting polymer film for active-matrix strain-sensing array

Skin-inspired semiconductor that is intrinsically stretchable, self-healable, and strain-sensitive for advanced sensory devices. Skin-like sensory devices should be stretchable and self-healable to meet the demands for future electronic skin applications. Despite recent notable advances in skin-inspired electronic materials, it remains challenging to confer these desired functionalities to an active semiconductor. Here, we report a strain-sensitive, stretchable, and autonomously self-healable semiconducting film achieved through blending of a polymer semiconductor and a self-healable elastomer, both of which are dynamically cross-linked by metal coordination. We observed that by controlling the percolation threshold of the polymer semiconductor, the blend film became strain sensitive, with a gauge factor of 5.75 × 105 at 100% strain in a stretchable transistor. The blend film is also highly stretchable (fracture strain, >1300%) and autonomously self-healable at room temperature. We proceed to demonstrate a fully integrated 5 × 5 stretchable active-matrix transistor sensor array capable of detecting strain distribution through surface deformation.
Lipoaspiration and Lymph Node Transfer for Treatment of Breast Cancer-related Lymphedema: A Systematic Review

Lipoaspiration and venous lymph node transfer have each been described as procedures that would improve symptoms of lymphedema. We aim to describe the efficacy of the combination of lipoaspiration and lymph node transfer and to report the outcomes in breast cancer-related lymphedema patients. The search was conducted by querying the PubMed, EMBASE, and Ovid Medline databases for studies that considered the use of lipoaspiration and venous lymph node transfer as surgical treatment for breast cancer-related lymphedema. Different combinations of the keywords “aspiration lipectomy” AND “lymphedema” AND “lymph node transfer” were used for the search. From a total of 20 articles, five met inclusion criteria. All patients included in these studies had stage II or III lymphedema. Two studies considered lipoaspiration as the first step followed by lymph node transfer, two considered lymph node transfer as the first step followed by lipoaspiration, and one applied both procedures simultaneously. A meaningful volume reduction was achieved in all cases. Patients who underwent lymph node transfer first followed by lipoaspiration appeared to have the best outcomes. This systematic review suggests that the combination of lymph node transfer and lipoaspiration is a potential surgical treatment that may improve outcomes achieved by one single procedure in patients with stage II to III breast cancer-related lymphedema.
A new leptoceratopsid dinosaur from Maastrichtian-aged deposits of the Sustut Basin, northern British Columbia, Canada

A partial dinosaur skeleton from the Sustut Basin of northern British Columbia, Canada, previously described as an indeterminate neornithischian, is here reinterpreted as a leptoceratopsid ceratopsian, Ferrisaurus sustutensis, gen. et. sp. nov. The skeleton includes parts of the pectoral girdles, left forelimb, left hindlimb, and right pes. It can be distinguished from other named leptoceratopsids based on the proportions of the ulna and pedal phalanges. This is the first unique dinosaur species reported from British Columbia, and can be placed within a reasonably resolved phylogenetic context, with Ferrisaurus recovered as more closely related to Leptoceratops than Montanoceratops. At 68.2–67.2 Ma in age, Ferrisaurus falls between, and slightly overlaps with, both Montanoceratops and Leptoceratops, and represents a western range extension for Laramidian leptoceratopsids.
Path Loss Characterization of 7-GHz Terrestrial Propagation Channel in Urban Environment

To satisfy dramatic increasing data demand, sharing spectrum for Wireless Local Area Networks (WLAN) is being considered. Two bands at 7 GHz (6875 - 7125 MHz) and 13 GHz (12700 - 13250 MHz) are currently allocated to point-to-point links, mobile links and fixed-satellite service. The analysis of potential interference between these incumbent services and WLAN devices is the ultimate purpose of this paper. Few path loss studies have been done in these bands and they only estimate attenuation through some materials and do not develop empirical propagation models at these frequencies. Narrowband drive tests with a moving receiver and fixed high-raised transmitter were conducted at both 7 and 13 GHz. This paper reports measurement results at 7 GHz in an urban environment with flat terrain, and corresponding log-distance path loss model. The measured results are compared with existing deterministic and statistical path loss models. We compare different terrain and clutter resolutions used in the deterministic model with respect to prediction error. Analysis of 7-GHz results for other scenarios and 13-GHz results will be reported in the near future. This work will provide useful guidelines for future coexistence studies in these bands.
PAPR and BER Performances of Direct Spectrum Division Transmission Applied by Clipping and Filtering in ACI Environment

Currently, demands for broadband communication are increasing in satellite communications. However, there is a problem that it is difficult to use of frequency bands effectively due to scattered unused bands caused by DAMA (Demand Assigned Multiple Access). In order to solve this problem, DSDT (Direct spectrum division transmission) has been developed. In this scheme, the single carrier modulated signal is finely divided into sub-spectra in the frequency domain on the transmission side and they are allocated to the unused bands over a satellite transponder. Then they are combined on the reception side, and finally the original single carrier modulated signal is recovered. However, there is a problem that the PAPR (Peak-to-average power ratio) increases in direct spectrum division transmission as the number of spectrum division increases. In order to improve the PAPR degradations, we propose a new direct spectrum division transmission applied by clipping and filtering method, which can be easily realized without transmitting the PAPR control information to the receiving side. Moreover, this paper indicates the proposed scheme improves the degradation due to the adjacent channel interference (ACI) from the DSDT spectra applied by clipping. The computer simulation results show that the PAPR performances of the DSDT with clipping and filtering are improved without BER (Bit error rate) degradation by setting the adequate clipping thresholds and adjacent channel interference due to clipping can be reduced by filtering.
Disinformation as Collaborative Work

In this paper, we argue that strategic information operations (e.g. disinformation, political propaganda, and other forms of online manipulation) are a critical concern for CSCW researchers, and that the CSCW community can provide vital insight into understanding how these operations function-by examining them as collaborative "work" within online crowds. First, we provide needed definitions and a framework for conceptualizing strategic information operations, highlighting related literatures and noting historical context. Next, we examine three case studies of online information operations using a sociotechnical lens that draws on CSCW theories and methods to account for the mutual shaping of technology, social structure, and human action. Through this lens, we contribute a more nuanced understanding of these operations (beyond "bots" and "trolls") and highlight a persistent challenge for researchers, platform designers, and policy makers-distinguishing between orchestrated, explicitly coordinated, information operations and the emergent, organic behaviors of an online crowd.
ABSTRACT: Access Control in Searchable Encryption with the use of Attribute-Based Encryption and SGX

We designed a hybrid encryption scheme that deals with the problem of storing data on untrusted clouds. Our work is an extension of [2, 7] and combines Symmetric Searchable Encryption (SSE) [3] and Attribute-Based Encryption (ABE) [4], along with the functionality offered by Intel SGX [6]. Our scheme compromises four SGX enclaves: Master Authority (MS) that generates public parameters and issues secret ABE keys to the users according to their attributes, a CSP enclave that verifies, stores and processes search requests by users, a KeyTray (KT) that acts as a storage server for SSE keys and a Revocation Enclave (REV) that controls access rights.