Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of core size and PEG coating layer of iron oxide nanoparticles on the distribution and metabolism in mice

Introduction In vivo distribution of polyethylene glycol (PEG)ylated functional nanoparticles is vital for determining their imaging function and therapeutic efficacy in nanomedicine. However, contradictory results have been reported regarding the effect of core size and PEG surface of the nanoparticles on biodistribution. Methods To clarify this ambiguous understanding, using iron oxide nanoparticles (IONPs) as a model system, we investigated the effect of core size and PEG molecule weights on in vivo distribution in mice. Three PEGylated IONPs, including 14 nm IONP@PEG2,000, 14 nm IONP@PEG5,000, and 22 nm IONP@PEG5,000, were prepared with a hydrodynamic size of 26, 34, and 81 nm, respectively. The blood pharmacokinetics and tissue distribution were investigated in detail. Results The results indicated that the PEG layer, rather than core size, played a dominant role in determining the half-life time of IONPs. Specifically, increased molecular weight of the PEG layer led to a longer half-life time. These PEGylated IONPs were mainly excreted by liver clearance. While the PEG molecular layer constituted the key factor to determine the clearance ratio, core size affected the clearance rate. Conclusion Complete blood count analysis and histopathology suggested excellent biocompatibility of PEGylated IONPs for future clinical trials.
Formally Verifying Memory Isolation Based on ARM Processors

Memory isolation is an important property ensured by many security systems, e.g., shielding systems, for programs, e.g., the untrusted OS and security critical applications, executed on the systems. The property states that each of the programs cannot intentionally or unintentionally read or write memory allocated for other programs. In this paper, we propose a general framework to formally model and verify systems that ensure memory isolation based on ARM processors. Specifically, first, we propose a general model for the systems in the framework. The model shows how to change configurations on ARM processors, e.g., extended page tables or configurations used for specifying memory in the secure world, without of violating the isolation. Then, we propose a general refinement strategy to model the memory management of the systems through the general model. If the memory management can be modeled by using the strategy, the memory management ensures memory isolation. We have used the framework to model and verify memory management of a security system, which is called as OSP and utilizes both of virtualization extensions on ARM processors and ARM TrustZone to isolate memory of programs. Our result shows that the system actually ensures the isolation for the programs executed on the system.
A Novel PBPK Modeling Approach to Assess Cytochrome P450 Mediated Drug‐Drug Interaction Potential of the Cytotoxic Prodrug Evofosfamide

Evofosfamide is a cytotoxic small‐molecule prodrug preferentially activated under hypoxic conditions. The cytotoxicity of evofosfamide impacted the generation of in vitro drug‐drug interaction (DDI) data, especially in vitro induction results. Therefore, a novel physiologically based pharmacokinetic (PBPK) approach was used, which involved available in vitro and clinical data of evofosfamide and combined it with induction data from the prototypical cytochrome P450 (CYP)3A inducer rifampicin. The area under the concentration‐time curve (AUC) ratios of midazolam were above 0.80, indicating that induction of CYP3A by evofosfamide administered weekly is unlikely to occur in humans. Moreover, static and PBPK modeling showed no clinically relevant inhibition via CYP2B6, CYP2D6, and CYP3A4. In conclusion, PBPK models were used to supplement in vitro information of a cytotoxic compound. This approach may set a precedent for future studies of cytotoxic drugs, potentially reducing the need for clinical DDI studies and providing more confidence in the clinical use of approved cytotoxic compounds for which DDI information is sparse.
An Adaptive Robust Online Method for AUC Maximization

Recently, increasing attention has been focused on the problem of online AUC maximization, and a great deal of efficient algorithms has been proposed. In spite of the promising performance of those online algorithms, however, most of them are sensitive to the outliers, which make them unsuitable for the applications with noisy data. To tackle the issue, in this paper, an adaptive robust method for online AUC maximization, termed AROAM is suggested. Specifically, a ramp loss based objective function oriented to AUC metric is firstly defined in AROAM, which has the strong ability of suppressing the influence of outliers. Then, concave-convex procedure is adopted for the convex approximation of the objective function. Finally, to further improve the performance of AROAM, an adaptive learning rate strategy is developed in each iteration, which can update the classifier effectively. Empirical studies on the benchmark data sets demonstrate the superiority of the proposed method in comparison with the state-of-the-arts.
A Compact ACS-Fed Triple-Band Dual-Polarized Stubs-Loaded Frequency Reconfigurable Printed Antenna for WiMAX and WLAN Applications

An ACS-fed dual-polarized stubs-loaded frequency reconfigurable printed antenna for multiband operation is presented and designed on FR-4 substrate. The antenna is composed of an inverted U-shaped stub and two asymmetrical L-shaped stubs connected in branched manner with ACS-fed. The antenna provides circular polarization (CP) functionality in the 4.9 GHz public safety WLAN band. The predicated impedance bandwidths of 260 MHz (2.32-2.58 GHz), 640 MHz (3.51-4.15 GHz), 480 MHz (4.94-5.42 GHz) and axial ratio bandwidth (ARBW) of 320 MHz (4.95-5.27 GHz) is achieved for 2.4/5.2 GHz WLAN, 3.5/5.5 GHz WiMAX and 4.9 GHz public safety WLAN applications. By employing three diodes at different locations on stubs and changing states of diodes, frequency reconfiguration functionality is achieved while keeping antenna size 14.70×26.50 mm2. Gain, axial ratio and radiation pattern for the antenna are analyzed and presented in the paper.
Conceptual and empirical advances in Neotropical biodiversity research

The unparalleled biodiversity found in the American tropics (the Neotropics) has attracted the attention of naturalists for centuries. Despite major advances in recent years in our understanding of the origin and diversification of many Neotropical taxa and biotic regions, many questions remain to be answered. Additional biological and geological data are still needed, as well as methodological advances that are capable of bridging these research fields. In this review, aimed primarily at advanced students and early-career scientists, we introduce the concept of “trans-disciplinary biogeography,” which refers to the integration of data from multiple areas of research in biology (e.g., community ecology, phylogeography, systematics, historical biogeography) and Earth and the physical sciences (e.g., geology, climatology, palaeontology), as a means to reconstruct the giant puzzle of Neotropical biodiversity and evolution in space and time. We caution against extrapolating results derived from the study of one or a few taxa to convey general scenarios of Neotropical evolution and landscape formation. We urge more coordination and integration of data and ideas among disciplines, transcending their traditional boundaries, as a basis for advancing tomorrow’s ground-breaking research. Our review highlights the great opportunities for studying the Neotropical biota to understand the evolution of life.
Discrete-Time Robust Control of Variable Speed Wind Turbine Using Quantitative Feedback Theory

A discrete-time robust controller for the variable speed wind turbine (VSWT) is designed in this paper. The two-mass model of VSWT (TMMV) has been considered for the proposed control design to extract the maximum power from the wind. The discretized TMMV (DTMMV) has been obtained using Euler method. An efficient and effective robust control technique namely discrete quantitative feedback theory (DQFT) is used for the specified range of parametric uncertainty and specifications in the frequency domain. The proposed controller satisfies the robust performance, sufficient gain and phase margins, process and measurement noise attenuation, and fast convergence. Finally, the robust stability and robust tracking performance has been demonstrated through simulation studies of the proposed control scheme in the presence of uncertainty.
EVN: An Elastic Virtual Network Supporting NFV Customized and Rapid Migration

The virtual network functions (VNF) enables to reduce reliance on expensive proprietary networking gear and increase network elasticity. In this paper, we propose an Elastic Virtual Networks (EVN) system to realize a complete virtual network layout, which supports resource customization, automated deployment, and flexible migration. Through the port and MAC address mapping, a new physical node can access the Virtual Networks (VNs), and the related VNFs are deployed through Docker. Moreover, we set up a white list function to reserve the capacity of the hosts that will be accessed in the future to facilitate a fast access. The experiment results verify that the VNF migration time in EVN by Docker improves three to four times compared with the traditional VM solution.
The ClinGen Epilepsy Gene Curation Expert Panel—Bridging the divide between clinical domain knowledge and formal gene curation criteria

The field of epilepsy genetics is advancing rapidly and epilepsy is emerging as a frequent indication for diagnostic genetic testing. Within the larger ClinGen framework, the ClinGen Epilepsy Gene Curation Expert Panel is tasked with connecting two increasingly separate fields: the domain of traditional clinical epileptology, with its own established language and classification criteria, and the rapidly evolving area of diagnostic genetic testing that adheres to formal criteria for gene and variant curation. We identify critical components unique to the epilepsy gene curation effort, including: (a) precise phenotype definitions within existing disease and phenotype ontologies; (b) consideration of when epilepsy should be curated as a distinct disease entity; (c) strategies for gene selection; and (d) emerging rules for evaluating functional models for seizure disorders. Given that de novo variants play a prominent role in many of the epilepsies, sufficient genetic evidence is often awarded early in the curation process. Therefore, the emphasis of gene curation is frequently shifted toward an iterative precuration process to better capture phenotypic associations. We demonstrate that within the spectrum of neurodevelopmental disorders, gene curation for epilepsy‐associated genes is feasible and suggest epilepsy‐specific conventions, laying the groundwork for a curation process of all major epilepsy‐associated genes.
Architectural Review of Co-Adaptive Brain Computer Interface

Electroencephalogram (EEG) based brain computer interface (BCI) detect specific EEG pattern from brain scalp and translate them into control commands for external devices. EEG based BCIs are indeed very promising for people suffering from neuromuscular disorder, but still lack adoption as access modalities outside laboratories. Two major factors responsible for this are (a) User variability: huge performance variations among and within user; (b) Signal Variability: High signal variations within or in between BCI sessions. To some extent advanced signal processing and classification methods can adapt with these variability. This makes machines to adapt with users; however these techniques do not focus on cause of these user and signal variability. Co-adaptive BCI systems are newly introduced concept which identify cause of variability and incorporate appropriate action for it. This enables both user and machine adapt with each other. This review paper describes a framework for co-adaptive BCI system as an initial point for any adaptive BCI solution.
Flying solo: single/unmarried mothers and stigma in Ireland

We welcome the recent interest shown by the Mental Health Commission in electroconvulsive therapy (ECT). However, we are concerned at some of the resultant comments in the medical and general press regarding the perceived geographical variations between Irish mental health services in the rate of ECT administration. All rates are calculated on the basis of a numerator divided by an appropriate denominator. Regarding ECT, the numerator is 'the number of patients prescribed electroconvulsive therapy' recorded in the 'statistical information required for visit of inspection' forwarded on an annual basis by mental health institutions to the Inspectorate of Mental Services. We note that this definition will include those inpatients completing a course of ECT that was commenced late the previous year. Therefore, it is possible that a single course of ECT for an individual patient will be included in the calculation of the ECT rate for two consecutive years. Given that ECT is primarily used on an inpatient basis for the treatment of depressive illness, it seems reasonable to conclude that the most clinically relevant and appropriate denominator to use in calculating a rate for ECT administration is the number of patients with a diagnosis of depression admitted to individual psychiatric units. We wish to draw the attention of our colleagues and the Mental Health Commission to our recent observations using data from Report of the Inspector of Mental Hospitals and Activities of Irish Psychiatric Services for the year 2002. Essentially, we used the data from these reports to calculate a rate of ECT administration for individual services provided there was appropriate contemporaneous information within the relevant reports. Our primary aim was to evaluate our own clinical practice in relation to that of our peers in the context of our auditing the high rate of ECT and administration attributed to our service in 2002. Unfortunately, our findings question the integrity of these data and suggest that caution is advisable when using these data sources to comment on rates of ECT administration. For example, one hospital was reported in the Report of the Inspector of Mental Hospitals to have administrated ECT to 38 patients but the corresponding Activities of Irish Psychiatric Services indicated that only four patients with a depressive disorder (out of total of 33 admissions for the year) were admitted to this institution! The only possible interpretation of this conflicting data is that the numerator reported was the number of applications of ECT used. Therefore we excluded this institution from the rest of the analysis.
A Low Power Low Noise Front End Amplifier for ECG Monitoring

An ultra-low power low noise front end amplifier (FEA) is presented for electrocardiography monitoring. The noise performance is optimized by adopting the adjusted capacitive feedback chopper-stabilized technique. To further increase the input impedance and reject DC electrode offset (DEO), the impedance boosting loop and DC servo loop are employed, respectively. Implemented in 65 nm CMOS process, the proposed FEA consumes 113 nA from 1 V supply, to achieve $2.6 \mu \mathrm {V}$ input referred noise, 100 mV DEO rejection and $945 \mathrm {M}\Omega $ input impedance. Furthermore, the AFE realizes a low noise efficiency factor of 3.4.
Vulnerability Analysis of Weighted Indian Power Grid Network Based on Complex Network Theory

In power grid (PG) networks some critical bus and transmission line has the major impact on the cascading failures and large-scale blackouts. In this work, we have investigated the vulnerability of Indian power grid (PG) and IEEE 118 bus for intentional and random attack strategies using complex network (CN) theory. We show that the PG's are vulnerable to intentional attacks and robust to random failures. We apply eight different attack strategies to unweighted and weighted PG networks. Here our approach based on CN theory does not aim to focus on the detailed operation of a PG networks, rather it gives details about its structural vulnerability. We concluded that weighted network analysis could give more accurate result since the weight is related to the electrical concept of PG. This process can help to identify the most vulnerable transmission lines and nodes, whose protection can increase the robustness and reliability of any PG network.
On Spatial and Temporal Variations in Ultra Dense Wireless Networks

Ultra densification along with the use of wider bands at higher frequencies are likely to be key elements towards meeting the throughput/coverage objectives of 5G wireless networks. In addition to increased parallelism, densification leads to improved, but eventually bounded, benefits from proximity of users to base stations, while resulting in increased aggregate interference. Such networks are expected to be interference limited, and in higher frequency regimes, the interference is expected to become spatially variable due to the increased sensitivity of propagation to obstructions and the proximity of active interferers. This paper studies the characteristics of the spatial random fields associated with interference and Shannon capacity in ultra-dense limiting regimes. They rely on the theory of Gaussian random fields which arise as natural limits under densification. Our models show how densification and operation at higher frequencies, could lead to increasingly rough temporal variations in the interference process. This is characterized by the Hölder exponent of the interference field. We show that these fluctuations make it more difficult for mobile users to adapt modulation and coding. We further study how the spatial correlations in users' rates impact backhaul dimensioning. Therefore, this paper identifies and quantifies challenges associated with densification in terms of the resulting unpredictability and the correlation of interference on the achievable rates.
Efficacy and safety of elbasvir/grazoprevir in participants with hepatitis C virus genotype 1, 4, or 6 infection from the Asia–Pacific region and Russia: Final results from the randomized C‐CORAL study

Although treatment with direct‐acting antivirals has dramatically improved morbidity and mortality attributable to chronic hepatitis C virus infection, universal access to these medicines has been slow in the Asia–Pacific region and Russia. This study evaluated efficacy and safety of elbasvir/grazoprevir in participants with hepatitis C virus infection from Asia–Pacific countries and Russia (C‐CORAL).
A prototype of a self-motion training system based on deep convolutional neural network and multiple FAMirror

With the development of deep learning methods, there has been a significant development in motion and speech recognition technologies, which have become common methods in Human-Computer Interaction (HCI). In addition, a mirror-metaphor is something that can be easily found around us, and it has become one of the displays for augmented reality as it enables participants to observe themselves. This paper proposes a prototype of self-motion training AR system based on these two important aspects. In the self-motion training system, we propose a method to represent one motion as one image. This method enables faster deep learning and motion recognition. For a self-motion training system, there are two essential requirements. One is that the participants should have the ability to observe their motion as well as a reference motion model, and it should be possible to correct their motion by comparing with the reference model. The other requirement is that the system could recognize a participant's motion from among various motion models in a database. Here, we introduce the configuration of a self-motion training system based on AR and its implementation details. In addition, the system examines the accuracy of the participant's motion with a reference motion model.
CORA: Conflict Razor for Policies in SDN

Software Defined Network (SDN) enables flexible update of network functions with a well-defined abstraction between the control and the data plane. However, multiple active network functions with the same priority will potentially trigger conflicts among policies with overlapped flow space, causing the flow table explosion. In contrast to the local switch conflict resolution schemes proposed by previous works, this paper tackles the same problem from a different angle and resolves the policy conflict problem by coordinating all switches under a global centralized view. Specifically, we propose COnflict RAzor (CORA), which tremendously reduces the storage cost of conflicting policies leveraging the global network information obtained in the controller. The basic idea of CORA is migrating policies causing large explosions across the network if necessary, while keeping the semantics equivalence. We prove CORA's NP hardness and propose a heuristic to efficiently search a near-optimal policy migration strategy. Our experiments demonstrate that, CORA can effectively reduce the flow table storage occupation by at least 49% within less than 40 seconds.
A Lattice Representation of Independence Relations

Independence relations in general include exponentially many statements of independence, that is, exponential in terms of the number of variables involved. These relations are typically fully characterised however, by a small set of such statements and an associated set of derivation rules. While various computational problems on independence relations can be solved by manipulating these smaller sets without the need to explicitly generate the full relation, existing algorithms are still associated with often prohibitively high running times. In this paper, we introduce a lattice representation for sets of independence statements, which provides further insights in the structural properties of independence and thereby renders the algorithms for some well-known problems on independence relations less demanding. By means of experimental results, in fact, we demonstrate a substantial gain in efficiency of closure computation of semi-graphoid independence relations.
New Block-Based Spatial Modulation

Spatial modulation (SM) conveys additional information using antenna patterns in MIMO system. The existing SM schemes limit the active antennas to a fixed number in each transmit vector to avoid detection ambiguity. Motivated by this, we introduce a new block-based SM (BSM) scheme wherein transmit vectors can have different number of active antennas, with the constraint that the total number of active antennas over a transmission block is fixed. This enables us to not only avoid detection ambiguity but also achieve low bit error rate than an existing SM scheme.
Playing Technique Classification Based on Deep Collaborative Learning of Variational Auto-Encoder and Gaussian Process

Modeling musical timbre is critical for various music information retrieval (MIR) tasks. This work addresses the task of classifying playing techniques, which involves extremely subtle variations of timbre among different categories. A deep collaborative learning framework is proposed to represent a music with greater discriminative power than previously achieved. Firstly, a novel variational autoencoder (VAE) is developed to eliminate the variation of acoustic features within a class. Secondly, a Gaussian process classifier is jointly learned to distinguish the variations of timbres between classes, which increases the discriminative power of the learned representations. We derive a new lower bound that guides a VAE-based representation. Experiments were conducted on a database of seven classes of guitar playing techniques. The experimental results demonstrated that the proposed method outperforms baselines in terms of the Fl-score and accuracy.