Miracle-dz/UniFAR-FTUs huggingface dataset:
Energy Efficiency Optimization for Beamspace Massive MIMO Systems with Low-Resolution ADCs

In this article, we propose a sparse hybrid combining (SHC) scheme for the uplink transmission of beamspace massive multiple-input multiple-output (MIMO) system with low-resolution analog to digital converters (LADCs), to alleviate the performance bottleneck caused by the multi-user interference and quantization noise, with reduced hardware cost and power consumption. To this end, we formulate the optimization of the proposed SHC scheme as a system energy efficiency maximization problem under some practical constraints. The resulting problem contains the highly coupled nonconvex objective function, as well as the discrete binary constraints. By exploiting some fractional programming (FP) techniques and introducing auxiliary variables, we first recast the original challenging problem into a more tractable yet equivalent form. We then develop an efficient double-loop iterative algorithm based on the penalty dual decomposition (PDD) method to find its local stationary solutions. Finally, simulation results verify the effectiveness of the proposed SHC scheme by numerical examples in terms of the achieved system energy efficiency.
Gauginos as a signal for supersymmetry at pp-bar colliders.

We present a comprehensive analysis of the signals from the pair production of the mass eigenstates (W-italic-tilde, Z-italic-tilde, and gamma-tilde) of the gauge-Higgs-fermion system for both CERN and Fermilab Tevatron energies, assuming that gamma-tilde is relatively light (approx. .W-italic-tildeZ-italic-tilde and Z/sup 0/.-->.W-tildeW-tilde-bar are kinematically accessible, there is a substantial level of (i) jet(s) + p-italic-dash-bar/sub T/ events from the hadronic decays of W-italic-tilde and Z-italic-tilde, (ii) a comparable level of background-free multilepton + p-italic-dash-bar/sub T/ events, essentially free from hadronic activity from the leptonic decay of W-italic-tilde and Z-italic-tilde, and (iii) jet(s) + lepton(s) + p-italic-dash-bar/sub T/ events from the leptonic decay of one of the gauginos and hadronic decay of the other. We present rates and distributions for these events and show that a conclusive absence of such amore » signal could lead to more stringent direct mass limits on masses of the W-italic-tilde and Z-italic-tilde than are currently available. « less
A learning-based, fully automatic liver tumor segmentation pipeline based on sparsely annotated training data

Current fully automatic liver tumor segmentation systems are designed to work on a single CT-image. This hinders these systems from the detection of more complex types of liver tumor. We therefore present a new algorithm for liver tumor segmentation that allows incorporating different CT scans and requires no manual interaction. We derive a liver segmentation with state-of-the-art shape models which are robust to initialization. The tumor segmentation is then achieved by classifying all voxels into healthy or tumorous tissue using Extremely Randomized Trees with an auto-context learning scheme. Using DALSA enables us to learn from only sparse annotations and allows a fast set-up for new image settings. We validate the quality of our algorithm with exemplary segmentation results.
Interaction of green tea catechins with renal organic cation transporter 2

Abstract 1. Green tea extract (GTE) and EGCG have previously shown to increase the uptake of MPP+ into Caco-2 cells. However, whether GTE and its derivatives interact with renal basolateral organic cation transporter 2 (Oct2) which plays a crucial role for cationic clearance remains unknown. Thus, this study assessed the potential of drug-green tea (GT) catechins and its derivatives interactions with rat Oct2 using renal cortical slices and S2 stably expressing rat Oct2 (S2rOct2). 2. Both GTE and ECG inhibited MPP+ uptake in renal slices in a concentration-dependent manner (IC50 = 2.71 ± 0.360 mg/ml and 0.87 ± 0.151 mM), and this inhibitory effect was reversible. Inhibition of [3H]MPP+ transport in S2rOct2 by either GTE or ECG (IC50 = 1.90 ± 0.087 mg/ml and 1.67 ± 0.088 mM) was also observed. 3. The weak and reversible interactions of GTE and ECG with rOct2 indicate that consumption of GT beverages could not interfere with cationic drugs secreted via renal OCT2 in humans. However, the rise of therapeutic use of GTE and ECG might have to take into account the significant possibility of adverse drug–green tea catechins interactions which could alter renal organic cation drug clearance.
Type I Interferon Signaling Enhances CD8+ T Cell Effector Function and Differentiation during Murine Gammaherpesvirus 68 Infection

ABSTRACT CD8+ T cell responses are critical to the control of replication and reactivation associated with gammaherpesvirus infection. Type I interferons (IFNs) have been shown to have direct and indirect roles in supporting CD8+ T cell development and function during viral infection; however, the role of type I interferons during latent viral infection has not been examined. Mice deficient in type I IFN signaling (IFNAR1−/− mice) have high levels of reactivation during infection with murine gammaherpesvirus 68 (MHV68), a murine gammaherpesvirus model for Epstein-Barr virus. We hypothesized that type I IFNs function to enhance the anti-gammaherpesvirus CD8+ T cell response. To test this, IFNAR1−/− mice were infected with MHV68 and the CD8+ T cell response was analyzed. In the absence of type I IFN signaling, there was a marked increase in short-lived effector CD8+ T cells, and MHV68-specific CD8+ T cells had upregulated expression of PD-1 and reduced tumor necrosis factor alpha (TNF-α), gamma IFN (IFN-γ), and interleukin-2 (IL-2) production. Suppressing MHV68 replication early in infection using the antiviral cidofovir rescued CD8+ T cell cytokine production and reduced PD-1 expression. However, suppressing high levels of reactivation in IFNAR1−/− mice failed to improve CD8+ T cell cytokine production during latency. T cell-specific abrogation of type I IFN signaling showed that the effects of type I IFNs on the CD8+ T cell response during MHV68 infection are independent of direct type I IFN signaling on T cells. Our findings support a model in which type I IFNs likely suppress MHV68 replication, thus limiting viral antigen and facilitating an effective gammaherpesvirus-directed CD8+ T cell response. IMPORTANCE The murine gammaherpesvirus MHV68 has both genetic and biologic homology to the human gammaherpesvirus Epstein-Barr virus (EBV), which infects over 90% of humans. Latent EBV infection and reactivation are associated with various life-threatening diseases and malignancies. Host suppression of gammaherpesvirus latency and reactivation requires both CD8+ T cells as well as type I interferon signaling. Type I IFNs have been shown to critically support the antiviral CD8+ T cell response in other virus models. Here, we identify an indirect role for type I IFN signaling in enhancing gammaherpesvirus-specific CD8+ T cell cytokine production. Further, this function of type I IFN signaling can be partially rescued by suppressing viral replication during early MHV68 infection. Our data suggest that type I IFN signaling on non-T cells can enhance CD8+ T cell function during gammaherpesvirus infection, potentially through suppression of MHV68 replication.
Hyperspectral Image Classification Based on Domain Adaptation Broad Learning

Hyperspectral images (HSI) are widely applied in numerous fields for their rich spatial and spectral information. However, in these applications, we always face the situation that the available labeled samples are limited or absent. Therefore, we propose an HSI classification method based on domain adaptation broad learning (DABL). First, according to the importance of the marginal and conditional distributions, the maximum mean discrepancy is used in mapped features to adapt these distributions between source and target domains. Meanwhile the manifold regularization is added to maintain the manifold structure of the input HSI data. Second, to further reduce the distribution difference and maintain manifold structure, the domain adaptation and manifold regularization are added to the output layer of DABL. Finally, the output weights can be easily calculated by the ridge regression theory. Experimental results on three real HSI datasets demonstrate the effectiveness of our proposed DABL.
Experimental Investigation of Washing Effects on the Properties of Textile Electrodes

The study represents the results of experimental research aimed at capturing the frequency characteristics of textile electrodes up to 20 kHz while considering their application in recording of biomedical signals. Two textile electrode models have been examined after a number of washing cycles according to the requirements of standardized procedures ISO 6330: 2012 and ISO 105-C06: 2010 for testing textile products.
NIHR: Name/ID Hybrid Routing in Information-centric VANET

Vehicular Ad hoc network (VANET) has received great attention in recent research, but many challenges still lie in innovating efficient routing protocols to support the highly dynamic environment. Existing ID-based routing protocols cannot fundamentally tackle the dynamic topology problem in VANET. The recent emerging Information-Centric Networking (ICN) makes routing decisions based on data itself instead of a particular host, seeming to have the potential to handle the dynamic topology, but problems (e.g., severe flooding overhead) still remain. Therefore, inspired by the idea of ICN, we propose a name/ID hybrid routing (NIHR) protocol that combines the data-namebased routing and host-ID-based routing to address the above two issues simultaneously. In particular, we develop an announce strategy to improve the efficiency of the in-network cache, and we design a bloom filter based structure to achieve fast content lookup. Simulation results show NIHR's high performance in terms of Packet Delivery Ratio (PDR), Roundtrip time (RTT) and roundtrip hop count. Especially, to verify NIHR’s performance in real-world scenarios, we have implemented a vehicular real-time video conference system based on MK5 OBU [1] (On-Board Unit).
Semantic Similarity Estimation Using Vector Symbolic Architectures

For many natural language processing applications, estimating similarity and relatedness between words are key tasks that serve as the basis for classification and generalization. Currently, vector semantic models (VSM) have become a fundamental language modeling tool. VSMs represent words as points in a high-dimensional space and follow the distributional hypothesis of meaning, which assumes that semantic similarity is related to the context. In this paper, we propose a model whose representations are based on the semantic features associated with a concept within the ConceptNet knowledge graph. The proposed model is based on a vector symbolic architecture framework, which defines a set of arithmetic operations to encode the semantic features within a single high-dimensional vector. In addition to word distribution, these vector representations consider several types of information. Moreover, owing to the properties of high-dimensional spaces, they have the additional advantage of being interpretable. We analyze the model’s performance on the SimLex-999 dataset, a dataset where commonly used distributional models (e.g., word2vec or GloVe) perform poorly. Our results are similar to those of other hybrid models, and they surpass several state-of-the-art distributional and knowledge-based models.
Application of Distributed Optical Fiber Temperature Measurement System to Hydraulic Concrete

Based on the advantages of distributed optical fiber temperature measurement technique and the key points of temperature measurement during the dam concrete construction,the corresponding techniques of routing,positioning,laying,protection,connection are represented.And improved suggestions of optical fiber real time temperature measurement technique are proposed.Take the process of temperature measurement in Xiluodu Hydropower Station on the Jinsha River and Shenxigou Hydropower Station on the Dadu River for an example.The results show that the proposed method is effective,reliable and accurate.Thus,it provides basis for the dam safety assessment.
Traffic Aware Beamformer Design for Integrated Access and Backhaul with Flexible TDD

Integrated access and backhaul (IAB) networks consist of IAB-donor, IAB-nodes, and user-equipments (UEs). Both IAB-donor and IAB-node provide access to UEs while IAB-donor and IAB-nodes exchange UEs data via wireless in-band backhaul using the same frequency-time resources shared with access links. Multi-antenna beamformer techniques can be used to mitigate the complicated cross-link interference scenarios arising from IAB systems. In this paper, an iterative beamformer design with the weighted queue minimization (WQM) objective is proposed for the time-division-duplexed (TDD) based IAB system. In the considered TDD based IAB model, in a given timeslot, IAB-nodes and IAB-donor are assumed to be different uplink (UL)/downlink (DL) transmission modes to mitigate conventional half-duplex loss. Also, the beamformer design is carried out over two timeslots, considering both UL and DL transmission at each node. Specifically, user-specific UL/DL queues are introduced at the IAB-nodes to guarantee the BS to/from UE data delivery. The proposed beamformer solution is based on the iterative evaluation of Karush-Kuhn-Tucker (KKT) conditions of the optimization problem, which can practically be implemented in both centralized and decentralized manner. The numerical examples illustrate the superior system performance of the proposed method in comparison to the conventional half-duplex relaying system.
Flight Path Optimization for UAVs to Provide Location Service to Ground Targets

We consider using UAVs to provide location service to ground targets. UAVs fly over the target area and broadcast their locations periodically via wireless signals. When a UAV flies along a straight line, a target will observe the strongest signal when the UAV is at the closest location, based on which it can infer its location. The problem is to minimize the flight length subject to the constraint that the transmission range of a UAV is limited and all targets in the area should be located. We formulate the problem and give an optimal flight path to cover a square with side length no greater than a certain value. In the general case when the given area cannot be covered by the square, we propose to divide UAVs into two groups, whose flight paths are either parallel or orthogonal. We conduct simulations to compare our approach with existing approaches. Results verify the superiority of our approach in terms of flight length and localization error.
Rider Optimization based Optimized Deep-CNN towards Attack Detection in IoT

More researchers have made efforts on introducing various models for IoT security frameworks, however, no single IoT framework could assure the optimal security in opposition to varied kinds of attacks. Thereby, this paper intends to propose a new attack detection system by interlinking the Development and Operations (DevOps) concept. The proposed attack detection system involves two stages: Proposed Feature Extraction and Classification. In the first stage, the concatenation of statistical and higher-order statistical features is extracted. These extracted features are then subjected to Deep Convolutional Neural Network (CNN) based classification to identify the attacks in the network. To improve the classification accuracy, the convolution layers in DCNN are optimally tuned using Rider Optimization Algorithm (ROA). Finally, analysis is carried out for validating the betterment of the adopted scheme.
The assessment of frailty in older people in acute care

As a person ages there is an accumulation of stressors and lifetime risk factors that combine with multi-organ physiological change to give rise to an increased risk of poor outcomes (e.g. death, institutionalisation, falls and iatrogenic disease). This vulnerability can be quantified by a frailty scale. Frailty can be seen as a measurement of the level of support that is required by a person. This measurement is useful as a predictive tool to determine the health services needed by the patient and for research purposes to assist in public health planning.
Generalized Slip Transformations and Air-Gap Harmonics in Field Models of Electrical Machines

In numerical field analysis of steady states of electrical machines, frequency-domain methods are often much faster than time-domain methods. Frequency-domain techniques often involve simplifications that impact their accuracy on harmonic effects due to slotting, saturation, and time harmonics in winding currents. The nature of these inaccuracies and their relationship to air-gap field harmonics is not that well covered in the literature. Correct prediction of air-gap field harmonics can be based on careful use of spectral Dirichlet-to-Neumann mappings and generalized slip transformations. We show how nonzero harmonics in the air-gap fields can be reliably predicted and explain the nature of inaccuracies in certain common steady-state solution techniques.
A Distance-Detection Receiver for Ambient Backscatter Communications with MPSK RF Source

Ambient Backscatter Communication (AmBC) is a promising technology for green IoT, which overcomes the energy, cost and spectrum resource shortage challenges. In AmBC, the weak backscatter link strength caused by the double-fading is a big challenge for IoT device symbol detection. This paper focuses on receiver design with the M PSK RF source symbol. Most previous works have not considered the issue of channel estimation that is very important for wireless communications. We focus on precisely estimating the channels at each of the AmBC receiving antennas, in particular on resolving the quadrant ambiguities in the channel estimates. The proposed channel estimator makes use of both the pilot and the data symbols of the RF source to eliminate quadrant ambiguity and enhance the estimation accuracy. We propose a novel distance detector (DD) that makes its decision in each IoT symbol interval based on which of the calibrated channel estimates the current channel estimate is closer to in Euclidean distance. What is more, we propose two modified distance detection methods to enhance the bit error rate (BER) performance. Finally, extensive numerical results show that the proposed distance detection method achieves performance comparable to that of the optimal detector with perfect channel state information (CSI).
Patterns of reflux in the great saphenous vein system

Objective: To report the patterns of reflux in the great saphenous vein as well as to investigate the correlations between patterns of reflux, the demographics and the clinical findings in the population studied. Methods: A total of 1882 limbs were assessed by duplex ultrasound examination in 1449 patients (348 men and 1101 women). Ages ranged from 21 to 94 years (mean 51.8). The presence of symptoms of venous disease (aching, heaviness, night cramps, swelling, itching, burning, tingling and throbbing) and clinical signs were recorded. Results: Varicose veins without saphenous reflux occurred at a younger age (43 versus 55.6 years P < 0.05). The presence of incompetence at the saphenofemoral junction occurred in older patients (58.5 versus 54.1 years P < 0.05). Venous reflux to the ankle also occurred in older patients (mean 64.0 years P < 0.05). Saphenous vein reflux without clinical varices was associated with more advanced signs (C4–C6: 20.3% P < 0.05). A younger age was associated with less advanced signs (C0–C2:49.4 versus C4–C6: 60.1 years P < 0.05). Presence of symptoms was associated with advancing patient age (51.1 versus 49.1 years P < 0.05). Conclusions: A significant correlation between the extent of great saphenous vein reflux and the patient age and the clinical stage of SVI has been observed in this study. The authors hypothesize that these findings support the concept of early treatment of venous insufficiency before symptomatic and physiological deterioration occurs.
Respiratory variations in pulse oximeter waveform amplitude are influenced by venous return in mechanically ventilated patients under general anaesthesia

Background and objectives: Respiratory variations in pulse oximetry plethysmographic waveform amplitude (&Dgr;POP) are related to respiratory variations in arterial pulse pressure (&Dgr;PP) in the critical care setting. The aims of this study were to test the hypothesis that in mechanically ventilated patients undergoing general anaesthesia, &Dgr;POP calculation is feasible and can detect changes in preload. Methods: Twenty‐five mechanically ventilated patients were studied immediately after induction of general anaesthesia. Haemodynamic data (mean arterial pressure [MAP], central venous pressure [CVP], &Dgr;PP and &Dgr;POP) were recorded at baseline, before and after tilting the patient from anti‐Trendelenburg to Trendelenburg position in order to induce preload changes. Results: Change from anti‐Trendelenburg to Trendelenburg position induced changes in MAP (58 ± 9 to 67 ± 10 mmHg, P < 0.05), CVP (4 ± 4 to 13 ± 5 mmHg, P < 0.05), &Dgr;PP (14 ± 8 to 7 ± 5%, P < 0.05) and &Dgr;POP (17 ± 12 to 9 ± 5%, P < 0.05). There was a significant relationship between &Dgr;POP in anti‐Trendelenburg position and percent change in MAP after volume expansion (r = 0.82; P < 0.05). Conclusions: &Dgr;POP can be determined in the operating room and is influenced by changes in preload. This new index has potential clinical applications for the prediction of fluid responsiveness.
Oblique Projected Dynamical Systems and Incremental Stability Under State Constraints

Projected dynamical systems (PDS) are discontinuous dynamical systems obtained by projecting a vector field on the tangent cone of a given constraint set. As such, PDS provide a convenient formalism to model constrained dynamical systems. When dealing with vector fields, which satisfy certain monotonicity properties, but not necessarily with respect to usual Euclidean norm, the resulting PDS does not necessarily inherit this monotonicity, as we will show. However, we demonstrate that if the projection is carried out with respect to a well-chosen norm, then the resulting “oblique PDS” preserves the monotonicity of the unconstrained dynamics. This feature is especially desirable as monotonicity allows to guarantee important (incremental) stability properties and stability of periodic solutions (under periodic excitation). These properties can now be guaranteed based on the unconstrained dynamics using “smart” projection instead of having to carry out a difficult a posteriori analysis on a constrained discontinuous dynamical system. To illustrate this, an application in the context of observer re-design is presented, which guarantees that the state estimate lies in the same state set as the observed state trajectory.
Some Unanticipated Consequences of Organizational Restructuring

We explore two consequences of organizational restructuring that are unanticipated by managers. At the cognitive level of analysis, we propose that organizational restructuring has the unanticipated consequence of producing cognitive order for top executives, and at the environmental level, organizational restructuring has the unanticipated consequence of contributing to long-term environmental turbulence. Both feed back to promote further organizational restructuring, making restructuring a self-reinforcing loop. We derive formal propositions from this theoretical framework, discuss issues in testing the propositions, and specify implications for future theory building and management practice.