Miracle-dz/UniFAR-FTUs huggingface dataset:
Constrained Active Learning for Anchor Link Prediction Across Multiple Heterogeneous Social Networks

Nowadays, people are usually involved in multiple heterogeneous social networks simultaneously. Discovering the anchor links between the accounts owned by the same users across different social networks is crucial for many important inter-network applications, e.g., cross-network link transfer and cross-network recommendation. Many different supervised models have been proposed to predict anchor links so far, but they are effective only when the labeled anchor links are abundant. However, in real scenarios, such a requirement can hardly be met and most anchor links are unlabeled, since manually labeling the inter-network anchor links is quite costly and tedious. To overcome such a problem and utilize the numerous unlabeled anchor links in model building, in this paper, we introduce the active learning based anchor link prediction problem. Different from the traditional active learning problems, due to the one-to-one constraint on anchor links, if an unlabeled anchor link a=(u,v) is identified as positive (i.e., existing), all the other unlabeled anchor links incident to account u or account v will be negative (i.e., non-existing) automatically. Viewed in such a perspective, asking for the labels of potential positive anchor links in the unlabeled set will be rewarding in the active anchor link prediction problem. Various novel anchor link information gain measures are defined in this paper, based on which several constraint active anchor link prediction methods are introduced. Extensive experiments have been done on real-world social network datasets to compare the performance of these methods with state-of-art anchor link prediction methods. The experimental results show that the proposed Mean-entropy-based Constrained Active Learning (MC) method can outperform other methods with significant advantages.
Risky Decision-Making but Not Delay Discounting Improves during Inpatient Treatment of Polysubstance Dependent Alcoholics

Background: High levels of impulsivity, characteristics of addicted patients, are known to be important predictors of relapse. However, so far, little is known about the stability or variability of two main components of impulsivity (delay discounting and decision-making). The present study examined the changes in impulsivity during the first week of an abstinence based, behavioral orientated inpatient treatment program. Method: Thirty-seven polysubstance dependent alcoholics completed the Delay Discounting Task (DDT), and the Iowa Gambling Task (IGT) using the original version with decks A′B′C′D′, and an alternative version with decks K′L′M′N′, for measuring decision-making, after 2 and 6 weeks of active treatment. Results: It was found that performances on the IGT changed during treatment while performances on the DDT did not (test-retest period: 4 weeks). Conclusion: The results provide preliminary evidence that improvements in decision-making might be related to treatment effects. All patients followed a highly structured cognitive-behavioral treatment program, which might have enhanced their executive functioning (coping skills training).
Magnetic Flux Distribution of Linear Machines with Novel Three-Dimensional Hybrid Magnet Arrays

The objective of this paper is to propose a novel tubular linear machine with hybrid permanent magnet arrays and multiple movers, which could be employed for either actuation or sensing technology. The hybrid magnet array produces flux distribution on both sides of windings, and thus helps to increase the signal strength in the windings. The multiple movers are important for airspace technology, because they can improve the system’s redundancy and reliability. The proposed design concept is presented, and the governing equations are obtained based on source free property and Maxwell equations. The magnetic field distribution in the linear machine is thus analytically formulated by using Bessel functions and harmonic expansion of magnetization vector. Numerical simulation is then conducted to validate the analytical solutions of the magnetic flux field. It is proved that the analytical model agrees with the numerical results well. Therefore, it can be utilized for the formulation of signal or force output subsequently, depending on its particular implementation.
What's Mine is Yours

Objective: To evaluate the relationship between partner well-being and outcomes of chronically diseased individuals participating in an employer sponsored well-being improvement program. Methods: Using the Actor Partner Interdependence Model, we evaluated whether prior partner well-being was associated with well-being change among 2025 couples. Logistic regression models were then used to explore how spousal well-being risks relate to development and elimination of risks among program participants. Results: High well-being partners were associated with positive well-being change. Specifically, the partner effect for spouses’ high well-being on disease management participants was a 1.5 point higher well-being in the following time period (P = 0.001) while the partner effect of participants’ high well-being on spouses was nearly 1.1 points (P = 0.010). Conclusions: Well-being within couples is interdependent, and partner well-being is an important predictor of individual well-being change.
Fall detection for the elderly using a cane robot based on ZMP estimation

For assisting the elderly or physically challenged walking, a cane robot which be driven by an Omni-directional mobile robot has been proposed. A variety of sensors fixed on the cane robot is used for monitoring user's motion and detecting environment around user. The user's intentions of to which user want to move can be estimated by monitoring the applied force to cane robot, then the cane robot is controlled to move and aid user to walk. As a nursing-care robot, the safety is a most important concern; therefore a fall detection concept is proposed to estimate the risk of falls in elderly by referencing to the Zero Moment Point (ZMP) stabilization. An on-shoe sensor is proposed to estimate ZMP by obtaining dynamic reaction force at the contact of the foot with the ground. The safety of elderly's walking is defined in the case of that the ZMP is inside support polygon. If ZMP is on or out of the boundary of support polygon, the user will fall down or have a trend of falling down. Experimental results are presented success of proposed ZMP estimation and fall detection schemes.
Efficient control of internal combustion engines for electric power generation without throttle actuator

A system consisting of an internal combustion engine (ICE) and an electric generator, as used in serial electric hybrid vehicles (EHV) or range-extended electric vehicles, is considered in this paper. The use of a torque controlled generator provides an additional actuating variable for the control of the ICE. In this way, the power of the ICE can be controlled without using throttle actuator while following nearly maximum efficiency trajectory. A simple control algorithm is proposed for this approach based on an inner speed and outer power control loop. The resulting system is simple, robust and efficient requiring less energy storage than the usual on/off control strategy for EHV. The proposed algorithm has been implemented in a prototype and validated experimentally.
Water Transport through Ultrathin Polyamide Nanofilms Used for Reverse Osmosis

Thin‐film composite membranes comprising a polyamide nanofilm separating layer on a support material are state of the art for desalination by reverse osmosis. Nanofilm thickness is thought to determine the rate of water transport through the membranes; although due to the fast and relatively uncontrolled interfacial polymerization reaction employed to form these nanofilms, they are typically crumpled and the separating layer is reported to be ≈50–200 nm thick. This crumpled structure has confounded exploration of the independent effects of thickness, permeation mechanism, and the support material. Herein, smooth sub‐8 nm polyamide nanofilms are fabricated at a free aqueous–organic interface, exhibiting chemical homogeneity at both aqueous and organic facing surfaces. Transfer of these ultrathin nanofilms onto porous supports provides fast water transport through the resulting nanofilm composite membranes. Manipulating the intrinsic nanofilm thickness from ≈15 down to 8 nm reveals that water permeance increases proportionally with the thickness decrease, after which it increases nonlinearly to 2.7 L m−2 h−1 bar−1 as the thickness is further reduced to ≈6 nm.
Single Cycle Structure-Based Humanization of an Anti-Nerve Growth Factor Therapeutic Antibody

Most forms of chronic pain are inadequately treated by present therapeutic options. Compelling evidence has accumulated, demonstrating that Nerve Growth Factor (NGF) is a key modulator of inflammatory and nociceptive responses, and is a promising target for the treatment of human pathologies linked to chronic and inflammatory pain. There is therefore a growing interest in the development of therapeutic molecules antagonising the NGF pathway and its nociceptor sensitization actions, among which function-blocking anti-NGF antibodies are particularly relevant candidates. In this respect, the rat anti-NGF αD11 monoclonal antibody (mAb) is a potent antagonist, able to effectively antagonize rodent and human NGF in a variety of in vitro and in vivo systems. Here we show that mAb αD11 displays a significant analgesic effect in two different models of persistent pain in mice, with a remarkable long-lasting activity. In order to advance αD11 mAb towards its clinical application in man, anti-NGF αD11 mAb was humanized by applying a novel single cycle strategy based on the a priori experimental determination of the crystal and molecular structure of the parental Fragment antigen-binding (Fab). The humanized antibody (hum-αD11) was tested in vitro and in vivo, showing that the binding mode and the NGF neutralizing biological activities of the parental antibody are fully preserved, with even a significant affinity improvement. The results firmly establish hum-αD11 as a lead candidate for clinical applications in a therapeutic area with a severe unmet medical need. More generally, the single-cycle structure-based humanization method represents a considerable improvement over the standard humanization methods, which are intrinsically empirical and require several refinement cycles.
Ultra-wideband aided fast localization and mapping system

This paper proposes an ultra-wideband (UWB) aided localization and mapping system that leverages on inertial sensor and depth camera. Inspired by the fact that visual odometry (VO) system, regardless of its accuracy in the short term, still faces challenges with accumulated errors in the long run or under unfavourable environments, the UWB ranging measurements are fused to remove the visual drift and improve the robustness. A general framework is developed which consists of three parallel threads, two of which carry out the visualinertial odometry (VIO) and UWB localization respectively. The other mapping thread integrates visual tracking constraints into a pose graph with the proposed smooth and virtual range constraints, such that a bundle adjustment is performed to provide robust trajectory estimation. Experiments show that the proposed system is able to create dense drift-free maps in real-time even running on an ultra-low power processor in featureless environments.
P4-Compatible High-Level Synthesis of Low Latency 100 Gb/s Streaming Packet Parsers in FPGAs

Packet parsing is a key step in SDN-aware devices. Packet parsers in SDN networks need to be both reconfigurable and fast, to support the evolving network protocols and the increasing multi-gigabit data rates. The combination of packet processing languages with FPGAs seems to be the perfect match for these requirements. In this work, we develop an open-source FPGA-based configurable architecture for arbitrary packet parsing to be used in SDN networks. We generate low latency and high-speed streaming packet parsers directly from a packet processing program. Our architecture is pipelined and entirely modeled using templated \textttC++ classes. The pipeline layout is derived from a parser graph that corresponds to a P4 code after a series of graph transformation rounds. The RTL code is generated from the \textttC++ description using Xilinx Vivado HLS and synthesized with Xilinx Vivado. Our architecture achieves a \SI100 \giga\bit/\second data rate in a Xilinx Virtex-7 FPGA while reducing the latency by 45% and the LUT usage by 40% compared to the state-of-the-art.
Increasing sensitivity to DNA damage is a potential driver for human ovarian cancer

Ovarian cancer is one of the most common cancers among women, accounting for more deaths than any other gynecological diseases. However, the survival rate for ovarian cancer has not essentially improved over the past thirty years. Thus, to understand the molecular mechanism of ovarian tumorigenesis is important for optimizing the early diagnosis and treating this disease. In this study, we observed obvious DNA lesions, especially DNA double strand breaks (DSBs) accompanying cell cycle checkpoint activation, in the human epithelial ovarian cancer samples, which could be due to the impaired DNA response machinery. Following this line, we found that these DNA damage response-deficient primary cancer cells were hypersensitive to DNA damage and lost their ability to repair the DNA breaks, leading to genomic instability. Of note, three key DNA damage response factors, RNF8, Ku70, and FEN1 exhibited dramatically decreased expression level, implying the dysfunctional DNA repair pathways. Re-expression of wild type RNF8, Ku70, or FEN1 in these cells restored the DNA lesions and also partially rescued the cells from death. Our current study therefore proposes that accumulated DNA lesions might be a potential driver of ovarian cancer and the impaired DNA damage responders could be the targets for clinical treatment.
Are life-like characteristics useful for autonomous agents?

Autonomous agent behavioral studies have concentrated mainly on the social aspects, but we believe that inherent life-like characteristics such as reproduction, aging, metabolic cycle and movement are able to improve agent designs as well. These characteristics form life models for implementing useful features in an agent without using complex formal methods. We describe how each characteristic may be useful to an agent. This sets the stage for future experiments to be performed and further research in an area which has received little attention.
Achievable degrees of freedom (DoF) analysis in multi-user half-duplex relay interference networks

The information transmission problem in a class of wireless multi-user single-antenna half-duplex relay interference networks is studied. In these networks there are multiple clusters of sources. All the terminals in each source cluster desire to transmit independent messages to a single destination, through multiple layers of intermediate half-duplex relays. We adopt a cluster successive relaying (CSR) scheme, which divides each layer of relays into two alternatively activated clusters, in order to efficiently utilize the half-duplex relays. Using the interference alignment technique, we show that by allowing all sources to non-orthogonally transmit information and all relays to participate in the transmission process, a higher sum degrees of freedom (DoF) can be achieved, compared with directly applying existing transmission design in the considered networks.
Modified LMMSE turbo equalization

This letter presents a modified linear minimum mean square error (LMMSE) turbo equalization scheme that uses an augmented real matrix representation for quadrature modulation systems. In the proposed scheme, the estimates of the two quadrature components of the transmitted symbol have both their individual variances and their covariance considered. Hence, the new scheme is able to achieve a significant performance improvement while retaining a complexity similar to that of the existing LMMSE turbo equalization scheme.
Efficient channel estimation for millimeter wave MIMO with limited RF chains

In this paper, an efficient channel estimation scheme is proposed for the point-to-point lens-antenna-array enabled millimeter wave (mmWave) multiple-input multiple-output (MIMO) system with limited number of radio frequency (RF) chains at both source and destination. By exploiting the energy focusing property of lens antenna arrays at both the transmitter and receiver, as well as the multi-path sparsity of mmWave channels, the proposed scheme employs two-way training to achieve energy-based antenna selections at both the source and destination, thus significantly reducing the number of RF chains required. The proposed scheme has low complexity for implementation and yet does not require any prior knowledge of the channel. It is shown by simulations that compared to the traditional channel training method for MIMO systems without lens antenna, the effective data rate achieved by the lens array enabled mmWave MIMO system can be significantly improved, thanks to the energy focusing capability of lens antenna arrays and the matching efficient channel estimation scheme proposed.
Proceed to Checkout? The Impact of Time in Advanced Ticket Purchase Decisions

When purchasing tickets in advance, sports consumers are often faced with uncertainty. Most notably, in today's real-time environment, it can be challenging for consumers to determine how ticket prices and seat availability will change over time. Guided by the generic advanced-booking decision model, the current study investigated the role of time, ticket source (primary or secondary market), and team identification in advanced ticket purchasing by exploring a consumer's perceptions of ticket availability and finding a lower price. The results suggest the perceived likelihood of ticket availability and finding a lower priced ticket increased as the date of the game drew closer. Ticket source and team identification were also found to be statistically significant main eftects factors, while ticket source significantly moderated consumer perceptions of finding a lower price over time. These outcomes both confirm and contradict various findings in the leisure literature and provide a strong foundation for future sport-related examinations.
Compensatory Cognitive Training for Operation Enduring Freedom/Operation Iraqi Freedom/Operation New Dawn Veterans With Mild Traumatic Brain Injury

Objective: The purpose of the study was to evaluate the efficacy of group-based compensatory cognitive training (CCT) for Operation Enduring Freedom (OEF)/Operation Iraqi Freedom(OIF)/Operation New Dawn (OND) Veterans with a history of mild traumatic brain injury. Method: One hundred nineteen OEF/OIF/OND Veterans with history of mild traumatic brain injury participated at 3 sites, and 50 of the Veterans were randomized to CCT group, while 69 Veterans were randomized to the usual care control group. The CCT group participated in 10 weeks of CCT. Both CCT and usual care groups were assessed at baseline, 5 weeks (midway through CCT), 10 weeks (immediately following CCT), and 15 weeks (5-week follow-up) on measures of subjective cognitive complaints, use of cognitive strategies, psychological functioning, and objective cognitive performance. Results: Veterans who participated in CCT reported significantly fewer cognitive and memory difficulties and greater use of cognitive strategies. They also demonstrated significant improvements on neurocognitive tests of attention, learning, and executive functioning, which were 3 of the cognitive domains targeted in CCT. Conclusions: Findings indicate that training in compensatory cognitive strategies facilitates behavioral change (ie, use of cognitive strategies) as well as both subjective and objective improvements in targeted cognitive domains.
Threshold selection algorithm for basic Send-on-Delta sampling strategies

This paper proposes an algorithm to select dynamically an appropriate threshold for basic amplitude sampling transmission strategies (also called Send-on-Delta SoD strategies) given an available transmission rate. It is based on previously found relationships between threshold and throughput, and on justified approximations. The algorithm is presented to be computed in a Send-on-Delta (SoD) driver and is tested for a simple networked control system through simulations. It is compared with a conforming periodic transmission strategy and a constant threshold send-on-delta transmission strategy. Results show the feasibility of the proposed solution.
Design of a water flow and usage meter

South Africa could potentially face a shortage of water in the near future. Efficient and low cost methods to determine water usage are vital to help prevent this issue. Flow and usage meters are necessary to ensure accurate usage readings. An electromagnetic flow meter and a water usage meter were developed. The designed module can be implemented on a standard water pipe at residential areas. The developed system harvests energy using a solar panel.
A Survey on Internet of Things Enabled Smart Campus Applications

The fictional future home, workspace or city, as predicted by science TV shows of the 1960s, is now a reality. Modern microelectronics and communication technologies offer the type of smart living that looked practically inconceivable just a few decades ago. The Internet of Things (IoT) is one of the main drivers of the future smart spaces. It enables new operational technologies and offers vital financial and environmental benefits. With IoT, spaces are evolving from being just 'smart' to become intelligent and connected. This survey paper focuses on how to leverage IoT technologies to build a modular approach to smart campuses. The paper identifies the key benefits and motivation behind the development of IoT-enabled campus. Then, it provides a comprehensive view of general types of smart campus applications. Finally, we consider the vital design challenges that has to be met to realise a smart campus.
XPO1 inhibitor combination therapy with bortezomib or carfilzomib induces nuclear localization of IκBα and overcomes acquired proteasome inhibitor resistance in human multiple myeloma

Acquired proteasome-inhibitor (PI) resistance is a major obstacle in the treatment of multiple myeloma (MM). We investigated whether the clinical XPO1-inhibitor selinexor, when combined with bortezomib or carfilzomib, could overcome acquired resistance in MM. PI-resistant myeloma cell lines both in vitro and in vivo and refractory myeloma patient biopsies were treated with selinexor/bortezomib or carfilzomib and assayed for apoptosis. Mechanistic studies included NFκB pathway protein expression assays, immunofluorescence microscopy, ImageStream flow-cytometry, and proximity-ligation assays. IκBα knockdown and NFκB activity were measured in selinexor/bortezomib-treated MM cells. We found that selinexor restored sensitivity of PI-resistant MM to bortezomib and carfilzomib. Selinexor/bortezomib treatment inhibited PI-resistant MM tumor growth and increased survival in mice. Myeloma cells from PI-refractory MM patients were sensitized by selinexor to bortezomib and carfilzomib without affecting non-myeloma cells. Immunofluorescence microscopy, Western blot, and ImageStream analyses of MM cells showed increases in total and nuclear IκBα by selinexor/bortezomib. Proximity ligation found increased IκBα-NFκB complexes in treated MM cells. IκBα knockdown abrogated selinexor/bortezomib-induced cytotoxicity in MM cells. Selinexor/bortezomib treatment decreased NFκB transcriptional activity. Selinexor, when used with bortezomib or carfilzomib, has the potential to overcome PI drug resistance in MM. Sensitization may be due to inactivation of the NFκB pathway by IκBα.