Miracle-dz/UniFAR-FTUs huggingface dataset:
Zero-Effort Cross-Domain Gesture Recognition with Wi-Fi

Wi-Fi based sensing systems, although sound as being deployed almost everywhere there is Wi-Fi, are still practically difficult to be used without explicit adaptation efforts to new data domains. Various pioneering approaches have been proposed to resolve this contradiction by either translating features between domains or generating domain-independent features at a higher learning level. Still, extra training efforts are necessary in either data collection or model re-training when new data domains appear, limiting their practical usability. To advance cross-domain sensing and achieve fully zero-effort sensing, a domain-independent feature at the lower signal level acts as a key enabler. In this paper, we propose Widar3.0, a Wi-Fi based zero-effort cross-domain gesture recognition system. The key insight of Widar3.0 is to derive and estimate velocity profiles of gestures at the lower signal level, which represent unique kinetic characteristics of gestures and are irrespective of domains. On this basis, we develop a one-fits-all model that requires only one-time training but can adapt to different data domains. We implement this design and conduct comprehensive experiments. The evaluation results show that without re-training and across various domain factors (i.e. environments, locations and orientations of persons), Widar3.0 achieves 92.7% in-domain recognition accuracy and 82.6%-92.4% cross-domain recognition accuracy, outperforming the state-of-the-art solutions. To the best of our knowledge, Widar3.0 is the first zero-effort cross-domain gesture recognition work via Wi-Fi, a fundamental step towards ubiquitous sensing.
Who Limits the Resource Efficiency of My Datacenter: An Analysis of Alibaba Datacenter Traces

Cloud platform provides great flexibility and cost-efficiency for end-users and cloud operators. However, low resource utilization in modern datacenters brings huge wastes of hardware resources and infrastructure investment. To improve resource utilization, a straightforward way is co-locating different workloads on the same hardware. To figure out the resource efficiency and understand the key characteristics of workloads in co-located cluster, we analyze an 8-day trace from Alibaba's production trace. We reveal three key findings as follows. First, memory becomes the new bottleneck and limits the resource efficiency in Alibaba's datacenter. Second, in order to protect latency-critical applications, batch-processing applications are treated as second-class citizens and restricted to utilize limited resources. Third, more than 90% of latency-critical applications are written in Java applications. Massive self-contained JVMs further complicate resource management and limit the resource efficiency in datacenters.
Dependent Task Placement and Scheduling with Function Configuration in Edge Computing

In Mobile Edge Computing (MEC), each edge server can be configured with only a small number of functions due to the limited capacity of various resources. Meanwhile, mobile applications become more complicated, consisting of multiple dependent tasks which are typically modeled as a Directed Acyclic Graph (DAG). In edge computing, when an application arrives, we need to place and schedule its tasks onto edge servers and/or the remote cloud, where the functions to execute the tasks are configured. In this work, we jointly consider the problem of dependent task placement and scheduling with on-demand function configuration on servers. Our objective is to minimize the application completion time. Specifically, for the special case when the configuration on each edge server is fixed, we derive an algorithm to find the optimal task placement and scheduling efficiently. When the on-demand function configuration is allowed, we propose a novel approximation algorithm, named GenDoc, and analyze theoretically its additive error from the optimal solution. Our extensive experiments on the cluster trace from Alibaba (including 20365 unique applications with DAG information) show that GenDoc outperforms state-of-the-art baselines in processing 86.14% of these unique applications, and reduces their average completion time by at least 24% (and up to 54%). Moreover, GenDoc consistently performs well on various settings of key parameters.
Accurate synthesis of integrated RF passive components using surrogate models

Passive components play a key role on the design of RF CMOS integrated circuits. Their synthesis, however, is still an unsolved problem due to the lack of accurate analytical models that can replace the computationally expensive electromagnetic simulations (EM). Both, physical-based and surrogate models have been reported that fail to accurately model the complete design space of inductors. Surrogate-assisted optimization techniques, where coarse models are locally enhanced during the inductor synthesis process by using new EM-simulated points to update the model, have been proposed, but either the efficiency is dramatically decreased due to the online EM simulations or the optimization may converge to suboptimal regions. In this paper, we present a new surrogate model, valid in the entire design space with less than 1% error when compared with EM simulations. This model can be generated offline, and, when embedded within an optimization algorithm, allows the synthesis of integrated inductors with high accuracy and high efficiency, reducing the synthesis time in three orders of magnitude.
Reduced orbitofrontal-striatal activity on a reversal learning task in obsessive-compulsive disorder.

CONTEXT The orbitofrontal cortex (OFC)-striatal circuit, which is important for motivational behavior, is assumed to be involved in the pathophysiology of obsessive-compulsive disorder (OCD) according to current neurobiological models of this disorder. However, the engagement of this neural loop in OCD has not been tested directly in a cognitive activation imaging paradigm so far. OBJECTIVE To determine whether the OFC and the ventral striatum show abnormal neural activity in OCD during cognitive challenge. DESIGN A reversal learning task was employed in 20 patients with OCD who were not receiving medication and 27 healthy controls during an event-related functional magnetic resonance imaging experiment using a scanning sequence sensitive to OFC signal. This design allowed investigation of the neural correlates of reward and punishment receipt as well as of "affective switching," ie, altering behavior on reversing reinforcement contingencies. RESULTS Patients with OCD exhibited an impaired task end result reflected by a reduced number of correct responses relative to control subjects but showed adequate behavior on receipt of punishment and with regard to affective switching. On reward outcome, patients showed decreased responsiveness in right medial and lateral OFC as well as in the right caudate nucleus (border zone ventral striatum) when compared with controls. During affective switching, patients recruited the left posterior OFC, bilateral insular cortex, bilateral dorsolateral, and bilateral anterior prefrontal cortex to a lesser extent than control subjects. No areas were found for which patients exhibited increased activity relative to controls, and no differential activations were observed for punishment in a direct group comparison. CONCLUSIONS These data show behavioral impairments accompanied by aberrant OFC-striatal and dorsal prefrontal activity in OCD on a reversal learning task that addresses this circuit's function. These findings not only confirm previous reports of dorsal prefrontal dysfunction in OCD but also provide evidence for the involvement of the OFC-striatal loop in the pathophysiology of OCD.
Sharing Network Parameters for Crosslingual Named Entity Recognition

Most state of the art approaches for Named Entity Recognition rely on hand crafted features and annotated corpora. Recently Neural network based models have been proposed which do not require handcrafted features but still require annotated corpora. However, such annotated corpora may not be available for many languages. In this paper, we propose a neural network based model which allows sharing the decoder as well as word and character level parameters between two languages thereby allowing a resource fortunate language to aid a resource deprived language. Specifically, we focus on the case when limited annotated corpora is available in one language ($L_1$) and abundant annotated corpora is available in another language ($L_2$). Sharing the network architecture and parameters between $L_1$ and $L_2$ leads to improved performance in $L_1$. Further, our approach does not require any hand crafted features but instead directly learns meaningful feature representations from the training data itself. We experiment with 4 language pairs and show that indeed in a resource constrained setup (lesser annotated corpora), a model jointly trained with data from another language performs better than a model trained only on the limited corpora in one language.
Complex Oculomotor Behavior 1 Running head : Complex Oculomotor Behavior Automated Classification of Complex Oculomotor Behavior

Complex oculomotor behavior in response to a simple step stimulus can include a variety of different types of saccadic patterns including combinations of normal saccades, simple/corrected/multi-corrected overshoots/undershoots, express, dynamic overshoots, and compound saccades depending on the state of the oculomotor plant and the neuronal control signal supplied by the brain. This paper presents an algorithmic framework that allows automated classification of such behavior. Automated classification results were compared to manually classified data used as a reference baseline. In addition, this work investigates the impact of various filtering methods and basic eye movement classification algorithms on the accuracy of classification of complex oculomotor behavior. The proposed framework can be used in clinical examination of normal and abnormal visual systems.
Molecular Detection of Spirometra decipiens in the United States

The genus Spirometra belongs to the family Diphyllobothriidae and order Pseudophyllidea, and includes intestinal parasites of cats and dogs. In this study, a plerocercoid labeled as Spirometra mansonoides from the USA was examined for species identification and phylogenetic analysis using 2 complete mitochondrial genes, cytochrome c oxidase I (cox1) and NADH dehydrogenase subunit 3 (nad3). The cox1 sequences (1,566 bp) of the plerocercoid specimen (USA) showed 99.2% similarity to the reference sequences of the plerocercoid of Korean Spirometra decipiens (GenBank no. KJ599679), and 99.1% similarity in regard to nad3 (346 bp). Phylogenetic tree topologies generated using 4 analytical methods were identical and showed high confidence levels with bootstrap values of 1.00, 100%, 100%, and 100% for Bayesian inference (BI), maximum-likelihood (ML), neighbor-joining (NJ), and maximum parsimony (MP) methods, respectively. Representatives of Diphyllobothrium and Spirometra species formed a monophyletic group, and the sister-genera status between these species was well supported. Trapezoic proglottids in the posterior 1/5 region of an adult worm obtained from an experimentally infected cat were morphologically examined. The outer uterine loop of the uterus coiling characteristically consisted of 2 complete turns. The results clearly indicated that the examined Spirometra specimen from the USA matched to S. decipiens very well, and indicated possible presence of the life cycle of this species in this region.
Secure Capacity of Wireless Broadcast Networks

We give a constructive characterization for the capacity of wireless broadcast networks that are prone to Byzantine attacks. The adversary controls a single node in the network and can modify the packets flowing through the node. The central trade-off in such a scenario is that of security and throughput. We define secure capacity as the highest possible transmission rate from the source such that the destination can detect any modification in the information packets. Prior work in this direction mainly concentrate on nodes performing random network coding, where the capacity is shown to be bounded by C − z0, where C is the minimum cut between the source and the destination and z0 is the maximum number of packets the adversary can modify. We show that by carefully designing the transmission scheme, rates higher than C − z0 are achievable. In particular, we show that some nodes in the network carefully duplicating the packets results in increased capacity of the network. In order to efficiently search over all the possible transmission strategies, we formulate the problem of characterizing secure capacity as a linear optimization program. We give an explicit routing (and duplication) strategy that achieves the capacity given by the optimal solution of the optimization program, thus establishing the secure capacity of the given wireless broadcast network. We also show that there exist networks in which secure capacity with in-network monitoring can be arbitrarily larger than that without in-network monitoring.
Evidence for the occurrence of natural hybridization in reed‐associated Pythium species

A comparison of oomycete diversity in reed stands (Phragmites australis) of Lake Constance, Germany, and maize fields close by provided evidence for the occurrence of natural hybridization between Pythium phragmitis, a newly described reed pathogen, and an as-yet unknown Pythium species closely related to P. phragmitis and P. arrhenomanes. Internal transcribed spacer and β-tubulin sequences of a large set of Pythium isolates from reeds showed dimorphic signals at several positions, indicative of a mixture of characters of two parent species. Involvement of P. phragmitis in the putative hybrid species was confirmed after cloning and sequencing of ITS regions and β-tubulin genes of the hybrid isolates. Mitochondrially inherited coxII gene sequences did not show dimorphic sites and suggested that the hybridization event was relatively ancient, or that other species might be involved. Intermediate habitat preferences, morphological characters and aggressiveness towards reeds and other grasses confirmed the suggestion that these isolates comprise a natural hybrid between two Pythium species. Pythium arrhenomanes, likely to be involved in the putative hybrid's evolution, was repeatedly isolated from maize fields adjacent to P. phragmitis-infested reed stands. The interface between natural habitats with established oomycete communities and agricultural fields with potentially introduced pathogens might constitute an evolutionary hot-spot giving rise to new species with as-yet unknown host ranges. As indicated by inoculation tests, the hybrid was significantly more pathogenic towards reed rhizomes than P. phragmitis, which caused no damage to these organs. This is apparently the first report of the occurrence of natural hybridization in Pythium.
Momentum – an Active Time-Oriented Database for Intelligent Abstraction , Exploration and Analysis of Clinical Data

The temporal-reasoning task focuses on intelligent analysis of time-oriented data, while the temporalmaintenance task focuses on effective storage, query, and retrieval of these data. Both are highly relevant for biomedical applications such as monitoring, therapy, quality assessment, and visualization and exploration of time-oriented data, which cannot be expected to resolve each time both tasks, or to understand the internal details of specialized modules that perform them. Thus, it is imperative to supply a system, known as a temporal mediator, which integrates these tasks. One potential problem in existing temporal-mediation approaches is lack of sufficient responsiveness when querying the database for complex abstract concepts that are derived from the raw data, especially regarding a large patient group. We propose a new integration approach: The active time-oriented database. This approach is a temporal extension of the active-database concept, a merger of temporal reasoning and temporal maintenance within a persistent database framework. The approach preserves the efficiency of databases in handling data storage and retrieval while enabling specification and performance of complex temporal reasoning using an incremental-computation approach. The new approach provides persistence and truth-maintenance of the resultant abstractions. We implemented the active timeoriented database approach within the Momentum system. Initial experiments with the Momentum system are encouraging, and an evaluation is underway to assess its validity.
The Delaunay Document Layout Descriptor

Security applications related to document authentication require an exact match between an authentic copy and the original of a document. This implies that the documents analysis algorithms that are used to compare two documents (original and copy) should provide the same output. This kind of algorithm includes the computation of layout descriptors from the segmentation result, as the layout of a document is a part of its semantic content. To this end, this paper presents a new layout descriptor that significantly improves the state of the art. The basic of this descriptor is the use of a Delaunay triangulation of the centroids of the document regions. This triangulation is seen as a graph and the adjacency matrix of the graph forms the descriptor. While most layout descriptors have a stability of 0% with regard to an exact match, our descriptor has a stability of 74% which can be brought up to 100% with the use of an appropriate matching algorithm. It also achieves 100% accuracy and retrieval in a document retrieval scheme on a database of 960 document images. Furthermore, this descriptor is extremely efficient as it performs a search in constant time with respect to the size of the document database and it reduces the size of the index of the database by a factor 400.
Impact of port disruption on transportation network

Port, as a critical facilitator in international trade and logistics, plays a unique role in global supply chain activities. Maritime ports are exposed to many disruption sources such as natural disasters, labour strikes and terrorism. Disruptions in port can have a wide range of potential negative impact on its transportation networks; while sometimes also benefit other ports in close proximity. As supply chains get leaner, the magnitude of such impact is expected to grow. It is crucial to understand how transportation network is affected by port disruptions, in order to develop strategies and policies to maintain its capacity and resilience. This paper aims to present a model for intermodal transportation network that evaluates the impacts of disruptions occurring at a focal port, focusing specifically on mitigation strategies of port utilization and port alliance. Disruption frequency and duration are modeled with a Discrete Time Markov Chain distribution. Order lead times are determined by the status of focal port, congestion backlogs as well as mitigating actions of the terminal operators. Numerical studies are conducted to demonstrate the possible effects of port disruption on terminal operators, shipping companies, cargo owners, shipping routes and inland transport. 1 Author for correspondence
Content and Structure Based Approach For XML Similarity

Since the last decade, XML has become inevitable for complex data representation. In this paper, we address a problem of measuring the similarity between XML documents and propose a new XML document similarity approach, which considers the asymmetric similarity and the similarity of both semantic content and document structure. Here, we only consider the measurement of similarity between two XML documents based on the same schema. A prototype has been implemented to validate and evaluate the performances of our proposal. We do believe that our method can also be used to evaluate the similarity of other tree-structured complex data
An ENU-induced mutation in mouse glycyl-tRNA synthetase (GARS) causes peripheral sensory and motor phenotypes creating a model of Charcot-Marie-Tooth type 2D peripheral neuropathy

SUMMARY Mutations in the enzyme glycyl-tRNA synthetase (GARS) cause motor and sensory axon loss in the peripheral nervous system in humans, described clinically as Charcot-Marie-Tooth type 2D or distal spinal muscular atrophy type V. Here, we characterise a new mouse mutant, GarsC201R, with a point mutation that leads to a non-conservative substitution within GARS. Heterozygous mice with a C3H genetic background have loss of grip strength, decreased motor flexibility and disruption of fine motor control; this relatively mild phenotype is more severe on a C57BL/6 background. Homozygous mutants have a highly deleterious set of features, including movement difficulties and death before weaning. Heterozygous animals have a reduction in axon diameter in peripheral nerves, slowing of nerve conduction and an alteration in the recovery cycle of myelinated axons, as well as innervation defects. An assessment of GARS levels showed increased protein in 15-day-old mice compared with controls; however, this increase was not observed in 3-month-old animals, indicating that GARS function may be more crucial in younger animals. We found that enzyme activity was not reduced detectably in heterozygotes at any age, but was diminished greatly in homozygous mice compared with controls; thus, homozygous animals may suffer from a partial loss of function. The GarsC201R mutation described here is a contribution to our understanding of the mechanism by which mutations in tRNA synthetases, which are fundamentally important, ubiquitously expressed enzymes, cause axonopathy in specific sets of neurons.
Distributed fair scheduling for many-cores

Transition of embedded processors from multi-cores to many-cores continues unabated. Many-cores execute tens of tasks in parallel and in some contexts, it is crucial that the processing cores are distributed fairly amongst the tasks. Traditional queue-based centralized fair schedulers designed for multi-cores will have excessive overhead on many-cores due to the enlarged optimization search-space. Further, the processing requirements of executing tasks may vary under different phases of their execution necessitating lightweight dynamic fair schedulers to regularly perform partial reallocation of the cores. We introduce a distributed dynamic fair scheduler that can scale up with the increase in number of cores because it disburses the processing overhead of scheduling amongst all the cores. Based on observations made for task executions on many-cores, we propose an optimal solution under certain constraints for the fair scheduling problem, which in general is NP-Hard.
The control of constrained system with time-delay and its experimental evaluations using RC model helicopter

In this paper, we consider the control of a system with time-delay and constraints on states and control inputs. It is well-known that the the presence of time-delay and physical constraints in dynamical systems causes the instability and preference degradation. In designing control laws for the system, we apply the following approach. We design a predictive controller and stabilize the system with time-delay using the controller. Then we implement a reference governor to the stabilized system. We apply the proposed method to a RC (radio controlled) helicopter control system. The effectiveness of our approach is evaluated through simulations and experiments of the yaw angle control.