Miracle-dz/UniFAR-FTUs huggingface dataset:
Systemic Administration of Polyelectrolyte Microcapsules: Where Do They Accumulate and When? In Vivo and Ex Vivo Study

Multilayer capsules of 4 microns in size made of biodegradable polymers and iron oxide magnetite nanoparticles have been injected intravenously into rats. The time-dependent microcapsule distribution in organs was investigated in vivo by magnetic resonance imaging (MRI) and ex vivo by histological examination (HE), atomic absorption spectroscopy (AAS) and electron spin resonance (ESR), as these methods provide information at different stages of microcapsule degradation. The following organs were collected: Kidney, liver, lung, and spleen through 15 min, 1 h, 4 h, 24 h, 14 days, and 30 days after intravenous injections (IVIs) of microcapsules in a saline buffer at a dosage of 2.5 × 109 capsule per kg. The IVI of microcapsules resulted in reversible morphological changes in most of the examined inner organs (kidney, heart, liver, and spleen). The capsules lost their integrity due to degradation over 24 h, and some traces of iron oxide nanoparticles were seen at 7 days in spleen and liver structure. The morphological structure of the tissues was completely restored one month after IVI of microcapsules. Comprehensive analysis of the biodistribution and degradation of entire capsules and magnetite nanoparticles as their components gave us grounds to recommend these composite microcapsules as useful and safe tools for drug delivery applications.
Eigendecomposition-Based GFDM for Interference-Free Data Transmission and Pilot Insertion for Channel Estimation

This paper proposes a new generalized frequency division multiplexing (GFDM) system that eliminates the effects of intrinsic interference and makes it possible to insert a pilot for channel estimation without interference. We express inter-subsymbol interference (ISI) and inter-carrier interference (ICI), which represent the intrinsic interference in GFDM systems, in a matrix form. The proposed GFDM system can remove the ISI through pre-processing and post-processing, which are done by eigendecomposition. We analytically derive the sufficient condition for the ICI removal. In this way, the proposed GFDM system is able to eliminate the effects of both the ISI and ICI. Furthermore, we investigate the prototype filter structures of the proposed GFDM system transformed by pre-processing and post-processing. We verify that the changed prototype filter structures are able to insert pilot symbols that are orthogonal to data symbols. Hence, the pilot symbols for channel estimation can be clearly observed. Simulation results demonstrate that the proposed system has better BER performance than conventional GFDM systems when the channel estimation process is considered.
Interference Coordination for 3-D Beamforming-Based HetNet Exploiting Statistical Channel-State Information

In this paper, we investigate the inter-tier interference coordination for a heterogeneous network (HetNet), where both macro and small cells work in the frequency-division duplexing mode and share the same spectrum. A 2-D large-scale antenna array is deployed at a macro-base station (BS), while conventional multiple antenna array is deployed at each small cell. First, we derive an approximation of macro-users’ signal-to-interference-plus-noise ratio (SINR), under the assumption of only statistical channel-state information (CSI) at macro-BS, and a 3-D beamforming transmission scheme is applied for macro-users. A lower-bound of small-cell users’ expected SINR is also derived using the property of complex Wishart matrix. Based on these, simple metrics are derived to measure the inter-tier interference. Then, new interference coordination algorithms are proposed to achieve a good tradeoff for the performance and traffic between macro-cells and small cells. The proposed algorithms require only a few additional statistical CSI. Moreover, we derive tractable ergodic rate approximation of both the macro-cell and small-cell users which are shown to match well with the Monte Carlo results.
Finite State Machine Based Countermeasure for Cryptographic Algorithms

In this work, we present a novel FPGA-based implementation of the AES algorithm which has a two-layered resistance against power analysis attacks. Our countermeasure is based on the concept of finite state machine equipped with a random number generator. Beyond masking the intermediate variables as the first layer of defense, we randomize the sequences of operations and add dummy computations as the second layer of defense. Therefore, the first order attack is prevented and the number of power traces needed for a successful second order attack is vastly increased and the correlation coefficient is decreased, as expected.
Coherent Sub-channel Based CSI Reconstruction for Wideband Massive MIMO Systems

Frequency division duplex (FDD) massive multiple-input multiple-output (MIMO) systems require a large amount of channel state information (CSI) feedback from each user in the uplink (UL), which result in huge overhead. This brings great challenges. To tackle this, we study the relationship of CSI between two different frequency bands, and propose a novel coherent sub-channel based CSI reconstruction (CSBCR) scheme utilizing the correlation of CSI in different frequency bands. Our scheme can reconstruct the downlink (DL) CSI depending on the UL CSI without any feedback from users. The simulation results suggest that the proposed scheme achieves an improved performance compared with other previous works. Besides, our scheme can be employed in any system where the CSI can be obtained through the CSI of another frequency band even if the frequency interval is large.
Shortening of apparent transverse relaxation time of inorganic phosphate as a breast cancer biomarker

Phosphorus MRS offers a non‐invasive tool for monitoring cell energy and phospholipid metabolism and can be of additional value in diagnosing cancer and monitoring cancer therapy. In this study, we determined the transverse relaxation times of a number of phosphorous metabolites in a group of breast cancer patients by adiabatic multi‐echo spectroscopic imaging at 7 T. The transverse relaxation times of phosphoethanolamine, phosphocholine, inorganic phosphate (Pi), glycerophosphocholine and glycerophosphatidylcholine were 184 ± 8 ms, 203 ± 17 ms, 87 ± 8 ms, 240 ± 56 ms and 20 ± 10 ms, respectively. The transverse relaxation time of Pi in breast cancer tissue was less than half that of healthy fibroglandular tissue. This effect is most likely caused by an up‐regulation of glycolysis in breast cancer tissue that leads to interaction of Pi with the GAPDH enzyme, which forms part of the reversible pathway of exchange of Pi with gamma‐adenosine tri‐phosphate, thus shortening its apparent transverse relaxation time. As healthy breast tissue shows very little glycolytic activity, the apparent T2 shortening of Pi due to malignant transformation could possibly be used as a biomarker for cancer.
Safety of benzodiazepines and opioids in interstitial lung disease: a national prospective study

Safety concerns are a barrier to prescribing benzodiazepines (BDZs) and opioids in interstitial lung disease (ILD). We therefore examined the association of BDZs and opioids on risk of admission to hospital and death. We conducted a population-based longitudinal cohort study of fibrotic ILD patients starting long-term oxygen therapy in Sweden between October 2005 and December 2014. Effects of BDZs and opioids on rates of admission to hospital and mortality were analysed using Fine–Gray and Cox regression while adjusting for potential confounders. We included 1603 patients (61% females). BDZs were used by 196 (12%) patients and opioids were used by 254 (15%) patients. There was no association between BDZs and increased admission. Treatment with high- versus low-dose BDZs was associated with increased mortality (subdistribution hazard ratio (SHR) 1.46, 95% CI 1.08–1.98 versus 1.13, 95% CI 0.92–1.38). Opioids showed no association with increased admission. Neither low-dose opioids (≤30 mg·day−1 oral morphine equivalent) (SHR 1.18, 95% CI 0.96–1.45) nor high-dose opioids (>30 mg·day−1 oral morphine equivalent) (SHR 1.11, 95% CI 0.89–1.39) showed association with increased mortality. This first ever study to examine associations between BDZ and opioid use and harm in ILD supports the use of opioids and low-dose BDZs in severely ill patients with respiratory compromise. This first ever study to examine associations between benzodiazepine and opioid use and harm in ILD supports the use of opioids and low-dose benzodiazepines in severely ill patients with respiratory compromise http://ow.ly/yBfZ30lXCKu
A Voltage Quadrupler Rectifier Based Pulsewidth Modulated LLC Converter With Wide Output Range

LLC resonant converter is a soft switching frequency modulated dc–dc topology with its switching frequency near the resonant frequency. However, in applications where a wide output voltage is desired, it is extremely difficult to tune its operation close to the resonant frequency. In this paper, a novel pulsewidth modulated LLC type resonant converter based on voltage quadrupler rectifier is proposed. The proposed converter always operates at the resonant frequency and is able to achieve a wide output voltage range by modulating the duty cycle of the secondary side auxiliary mosfet. This brings the benefits of the decreased circulating current and corresponding conduction loss, as well as the simplification of the parameters selection and magnetic component design. Zero-voltage-switching and zero-current-switching are realized among all power mosfets and all power diodes, respectively. Detailed circuit operation principles and modeling method are presented. A 1.3-kW converter prototype, generating 250–420 V output from 390-V dc-link is designed. Both the circuit functionality and the theoretical analysis are verified in the experimental results.
Broadcast Range Performances for Random Access-Based Wireless Mutual Broadcast

The wireless mutual broadcast (WMB) sharing informative data among proximal nodes has been recently spotlighted as a key enabler for smarter and safer society. These WMB applications may require different intended broadcast coverage (BC) depending on their attributes, and this coverage is profoundly affected by mutual interference among nodes. In this regard, this letter investigates the BC in terms of the proximity between nodes [so called the broadcast range (BR)] under a stochastic geometry framework. Furthermore, it proposes the design principles to improve the performances for an intended BR.
Effects and safety of atmospheric low‐temperature plasma on bacterial reduction in chronic wounds and wound size reduction: A systematic review and meta‐analysis

The use of atmospheric low‐temperature plasma (AP) on chronic wounds and its effect on microbial bioburden in open wounds has not been explored with a systematic review and meta‐analysis. PRISMA guidelines were followed and PubMed, Embase, CENTRAL, and CINAHL databases searched for randomised controlled trials (RCTs), which compared AP with no AP for the management of open, chronic wounds. The primary outcomes of reduction of bioburden or wound size were included. Meta‐analyses were performed; odds ratio (OR) and 95% confidence intervals (CIs) were extracted and pooled in a random effects model.
ComP-Net: Command Processor Networking for Eficient Intra-kernel Communications on GPUs

Current state-of-the-art in GPU networking advocates a host-centric model that reduces performance and increases code complexity. Recently, researchers have explored several techniques for networking within a GPU kernel itself. These approaches, however, sufer from high latency, waste energy on the host, and are not scalable with larger/more GPUs on a node. In this work, we introduce Command Processor Networking (ComP-Net), which leverages the availability of scalar cores integrated on the GPU itself to provide high-performance intra-kernel networking. ComP-Net enables eicient synchronization between the Command Proces-sors and Compute Units on the GPU through a line locking scheme implemented in the GPU’s shared last-level cache. We illustrate that ComP-Net can improve application performance by up to 20% and provide up to 50% reduction in energy consumption vs. competing networking techniques across a Jacobi stencil, allreduce collective, and machine learning applications.
Cultural Factors impacting the Global Energy Transition - A Review

Energy transition from fossil fuels to renewable has been a case of debate in social, political, economic and environmental points of view owing to the long term impacts it has on populace and Governments. The energy transition requires infrastructural change for introduction, production and diffusion which takes decades to be developed. But the most important threat to the transition is the time and effort it takes to persuade the society for adaption. Many developed nations have shown improvement in the percentage of transition after a global movement took place in 2009 but still the larger part of the globe has not been able to adapt it. The paper compares various socio economic political and cultural factors affecting the transition in various countries both developing and developed. These perspectives are important for decision makers since they can adversely affect the intended benefits of any technology or at least slow down the transition.
A Fully Digital Physical Unclonable Function Based Temperature Sensor for Secure Remote Sensing

Turnkey solutions that combine energy-efficient remote sensing and secure communication of telemetry are desirable in data collection, risk control and situation appraisal with the large scale deployment of resource constrained Internet of Things devices. In this paper, a new low-cost physical unclonable function (PUF) based temperature sensor for secure remote temperature sensing is proposed. The design exploits the approximately linear positive temperature coefficient of CMOS inverter in super-threshold operation to calibrate the running frequency of ring oscillator (RO) in a reconfigurable RO PUF at different temperature. The RO frequency corresponding to the sensed temperature is fed into a randomizer seeded by the input challenge to select new RO pairs for comparison to generate a random, unique and physically unclonable digital tag, which is valid for a selected input challenge to a target device at a particular temperature. Using only standard logic cells and a very simple structure, the proposed temperature sensor can be easily implemented on FPGA and integrated into other digital systems. It protects the integrity of the sensed information by preventing falsified sensor data and masquerade sensing node. The FPGA implementation of our proposed design has demonstrated the feasibility of making a trust temperature telemetry system out of PUF.
Identifying Superfluous Network Transmissions in Android Applications

The network transmission is an important way to exchange information between Android applications and their own backend or other third-party servers. Some transmissions are necessary for the apps' functionalities, while other transmissions are superfluous. The superfluous network transmission not only increases the network traffic but also may leak users' sensitive data, which threatens the user's privacy. To identify the superfluous network transmissions, we propose a static-analysis approach. We first study the features of network transmissions to figure out the difference between necessary transmissions and superfluous ones: whether the responses of network transmissions are used by apps. Then we utilize information flow analysis to trace the use of the responses and identify superfluous network transmissions. Evaluation with real world market apps shows that our approach could effectively detect superfluous network transmissions in Android apps.
Morningness-eveningness and social anxiety symptoms: the influence of depression symptoms on the indirect effect through punishment sensitivity and experiential avoidance

ABSTRACT Social anxiety has recently been linked to morningness-eveningness; however, the psychological mechanisms underlying this relationship are not well known. As such, the purpose of the current study is to propose a model by which morningness-eveningness is related to social anxiety symptoms through punishment sensitivity and experiential avoidance within an adult American, community sample recruited via Amazon’s Mechanical Turk (MTurk). It was hypothesized that experiential avoidance and punishment sensitivity would be associated with increased social anxiety symptoms and that morningness-eveningness would be negatively related to social anxiety symptoms. Furthermore, eveningness was hypothesized to be associated with increased punishment sensitivity and in turn, greater experiential avoidance. Lastly, the relationship between morningness-eveningness and social anxiety was hypothesized to be mediated by punishment sensitivity among the group with high depression levels, but not among the group with lesser depression symptoms. The results indicated that eveningness was related to social anxiety symptoms through experiential avoidance, and that depression symptoms influenced the relationship between morningness-eveningness and punishment sensitivity such that, in those high in depression symptoms, there was a significant association between eveningness and punishment sensitivity, but not among those with lower depression levels. The study findings build upon existing chronobiological research and addresses inconsistencies in previous literature.
EPSMD: An Efficient Privacy-Preserving Sensor Data Monitoring and Online Diagnosis System

With the development of Mobile Healthcare Monitoring Network (MHMN), patients' personal data collected by body sensors not only allows patients to monitor their health or make online pre-diagnosis but also enable clinicians to make proper decisions by utilizing data mining technique. However, the sensitive data privacy is still a major concern. In this paper, we first propose an Efficient Privacy-preserving Sensor data Monitoring and online Diagnosis (EPSMD) system for outsourced computing, then furnish an improved Multidimensional Range Query Technique (MRQT) to gain a broad range of applications in practice. In addition, a privacy-preserving naive Bayesian classifier based on MRQT is designed to protect patients' data in data mining and online diagnosis efficiently. Security analysis proves that patients' data privacy can be well protected without loss of data confidentiality, and performance evaluation demonstrates the efficiency and accuracy in data monitoring and disease pre-diagnosis, respectively.
ISAR Cross-Range Scaling Using Radon Transform and its Projection

In this paper, we propose a cross-range scaling technique for inverse synthetic aperture radar (ISAR) images, by estimating the rotation velocity (RV) of a target. In the proposed method, the major axes of two consecutive ISAR images are determined using the Radon transform and its projection onto the angle direction. We then establish an appropriate cost function using the major axes. Finally, the RV is estimated using the bisection algorithm. Experimental results show that the proposed method can perform robust cross-range scaling in a short computation time, even in a low signal to noise ratio environment.
Genotypic and phenotypic characterization of Escherichia coli isolated from mollusks in Brazil and the United States

The aim of this study was to determine the serogroups, antimicrobial resistance and genetic diversity of Escherichia coli isolates from samples of bivalve mollusks collected along Santa Catarina coast, Brazil, and from the Chesapeake Bay, Maryland, USA. One hundred forty‐one E. coli isolates were characterized for serogroups with 181 specific O antisera and antimicrobial susceptibility using the disk diffusion method. The genetic diversity was assessed using pulsed‐field gel electrophoresis (PFGE). The results showed that among the isolates, 19.9% were classified as multi‐drug resistant (MDR) and resistance was most frequently observed to cephalothin, nitrofurantoin, and ampicillin. The predominant serogroups were O6, O8, and O38. Some serogroups were recognized as pathogenic E. coli. PFGE dendrograms indicated extensive genetic diversity among the isolates. Although characteristics of the E. coli isolates were highly variable, it is important to note that E. coli belonging to pathogenic serogroups and MDR isolates are present in mollusks of both study areas. This is the first report on the phenotypic and genotypic characterization of E. coli from mollusks from Santa Catarina and the Chesapeake Bay that should encourage studies focusing on comparison of isolates across countries.
Stability Constrained Optimal Allocation of DGs in Autonomous Micro-grids

Optimal location and sizing of the DGs including stability constraints is being attempted in this paper. In case of an autonomous micro-grid, it becomes inevitable to ensure the stability of the system. Hence critical clearing angle of the generators is included as a stability constraint in the formulation of the objective function for the optimal location and size of the DGs in the micro-grid. The proposed methodology enhances the stability of autonomous micro-grids on post contingency conditions. Case study analysis is performed upon the standard 33 bus radial distribution system to validate the proposed technique and the resilience needed during contingencies are analyzed.
Hardware-accelerated cache simulation for multicore by FPGA

Developers often use a virtual platform to develop software before the hardware is available. For software optimization, it is important to profile the cache misses of applications in a realistic operating environment under the virtual platform. In the multicore era, it is hard to simulate the coherence cache miss in a high speed way. In this paper, we propose a hardware-accelerated architecture to simulate the cache misses of a multicore system. We implement the cache miss simulator over a virtual platform with FPGA. Users can profile their software as running over the multicore system. The evaluation shows the throughput achieves 65 MB of trace log per second, when FPGA works in 100 MHz and about 570,000 logic elements are occupied to simulate 4 sets of L1 cache and 1 set of L2 cache in the multicore system with 4 virtual CPUs. The system achieves 1.6 to 2 times of speedup, when comparing with the popular cache miss simulator, Dinero IV. Dinero does less work and does not support coherence cache misses in the multicore system. The evaluation result shows high advantage to speed up the cache miss simulation of the multicore system by the hardware-accelerated architecture as well as FPGA.
A Vision-Based Approach to UAV Detection and Tracking in Cooperative Applications

This paper presents a visual-based approach that allows an Unmanned Aerial Vehicle (UAV) to detect and track a cooperative flying vehicle autonomously using a monocular camera. The algorithms are based on template matching and morphological filtering, thus being able to operate within a wide range of relative distances (i.e., from a few meters up to several tens of meters), while ensuring robustness against variations of illumination conditions, target scale and background. Furthermore, the image processing chain takes full advantage of navigation hints (i.e., relative positioning and own-ship attitude estimates) to improve the computational efficiency and optimize the trade-off between correct detections, false alarms and missed detections. Clearly, the required exchange of information is enabled by the cooperative nature of the formation through a reliable inter-vehicle data-link. Performance assessment is carried out by exploiting flight data collected during an ad hoc experimental campaign. The proposed approach is a key building block of cooperative architectures designed to improve UAV navigation performance either under nominal GNSS coverage or in GNSS-challenging environments.