Miracle-dz/UniFAR-FTUs huggingface dataset:
Generative Pattern Dissemination for Collaborative Intrusion Detection

New cyber security threats emerge dynamically, challenging conventional Intrusion Detection Systems, limited by isolated analysis, to maintain an updated decision base. Although Collaborative Intrusion Detection Systems improve attack detection performance by providing mechanisms for sharing and correlating analysis data, existing solutions neglect the aspect of a scalable dissemination of monitoring data. In this context, we present a novel approach that distributes network flow data among members in a group of cooperating infrastructures to enhance local data views while meeting requirements for low communication overhead, privacy and interoperability. Flows are partitioned using Locality Sensitive Hashing and persisted in a local data store by using the respective hash values. Gaussian Mixture Models are fitted on stored flows and the resulting model parameters are sent to a global data store, enabling members to locally reconstruct the corresponding models from which synthetic data can be sampled to improve local attack detection. Representing local data as model parameters significantly reduces the amount of data exchanged and ensures privacy. Associated processing latency is reduced by exploiting the parallelization enabled by data partitioning. Traffic classification experiments on multiple network security datasets show the superior performance of our approach in comparison to alternative scenarios.
TransU2-Net: A Hybrid Transformer Architecture for Image Splicing Forgery Detection

In recent years, various convolutional neural network (CNN) based frameworks have been presented to detect forged regions in images. However, most of the existing models can not obtain satisfactory performance due to tampered areas with various sizes, especially for objects with large-scale. In order to obtain an accurate object-level forgery localization result, we propose a novel hybrid transformer architecture, which exhibits both advantages of spatial dependencies and contextual information from different scales, namely, TransU2-Net. Specifically, long-range semantic dependencies are captured by the last block of encoder to locate large-scale tampered areas more completely. Meanwhile, non-semantic features are filtered out by enhancing low-level features under the guidance of high-level semantic information in the skip connections to achieve more refined spatial recovery. Therefore, our hybrid model can locate spliced forgeries with various sizes without requiring large data set pre-training. Experimental results on the Casia2.0 and Columbia datasets show that our framework achieves better performance over state-of-the-art methods. On the Casia 2.0 dataset, F-measure improve by 8.4% compared to the previous method.
A Novel Three-port Photovoltaic Micro-inverter with Active Power Decoupling Method

Conventional photovoltaic micro-inverters use large electrolytic capacitors to balance the power pulsation with twice of the grid frequency, which will affect the lifetime of the inverter. This paper proposes a novel three-port micro-inverter with active power decoupling circuit and its control strategy. The proposed inverter reduces the sizes of the DC input capacitor and decoupling capacitor, and the small film capacitor is applied to decouple the power pulsation instead of the electrolytic capacitor. In addition, flyback transformer isolates decoupling circuit and PV module. After establishing the equivalent circuit model of the proposed micro-inverter, the circuit parameters are designed. The simulation results show that the proposed circuit effectively buffer the power pulsations with only 30μF capacitance, and the output grid-connected current total harmonic distortion is 3.03%. The input DC capacitor is reduced to 20μF, which would greatly improve the stability and lifetime of inverters.
High Performance CMOS Voltage Level Shifters Design for Low Voltage Applications

To convert signals from one logic level or voltage level to another, a level shifter circuit is used in analog and digital integrated circuits (IC’s). It is also known as a voltage level translator or a logic-level shifter. An integrated circuit voltage level changer allows for compatibility across integrated circuits with various voltage needs. In this work, a voltage level shifter that efficiently converts voltage from the subthreshold area to the super-threshold region while reducing propagation latency is introduced. The proposed circuit improves power efficiency and delays by employing a low voltage converter, one Pull Down and one Pull Up CMOS network. We simulate the proposed design in 45nm, 65nm, 90nm and 180nm CMOS technologies. The simulated result shows that, by employing the proposed level shifter an improvement of 69.12% in propagation delay is observed as compared to recent designs in 90nm CMOS technology. In 45nm technology our design improves the propagation delay 67.07% compared to existing designs. In corner analysis the proposed technique gives better result as compared to the recently reported techniques.
The Analytical Switching Modelling Method of Grid-Connected Converters for Transient Stability Analysis

In recent years, grid-connected power electronic converters have continuously rising influence on dynamics of bulk power systems, making modelling of power electronic converters critical to modern power system stability studies. However, few existing studies can systematically model the switching characteristics or handle discontinuous state variables of power electronic converters. To make up for the shortages, this article proposes a general four-step analytical switching modelling method of grid-connected converters: formulating holonomic differential-algebraic equations of the converter containing all switching actions, transforming all state-dependent switching conditions into time-dependent ones, deriving differential equations of the system in all time periods, and analyzing the continuity of each state variables at all switching moments. An example model is established and then evaluated by detailed simulations to verify the effectiveness of the proposed modelling method. Transient stability analysis based on the example model shows the practicality of the proposed method and the importance of considering switching characteristics in analytical modelling of power electronic converters.
The Uses of Research: A Case Study in Research and Policy

Abstract: Three case studies of the use of research and evaluation results in a provincial ministry of education are presented. The cases are framed in terms of Cousins and Leithwood (1986) review of the research utilization literature. The factors affecting utilization in each case are analyzed. The cases point to the need for a stronger political orientation in examining research use in organizations. Implications for the study of utilization and for the conduct of useful research are drawn.
APHRODITE: Constructing a Long-Term Daily Gridded Precipitation Dataset for Asia Based on a Dense Network of Rain Gauges

A daily gridded precipitation dataset covering a period of more than 57 yr was created by collecting and analyzing rain gauge observation data across Asia through the activities of the Asian Precipitation—Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE) project. APHRODITE's daily gridded precipitation is presently the only long-term, continental-scale, high-resolution daily product. The product is based on data collected at 5,000–12,000 stations, which represent 2.3–4.5 times the data made available through the Global Telecommunication System network and is used for most daily gridded precipitation products. Hence, the APHRODITE project has substantially improved the depiction of the areal distribution and variability of precipitation around the Himalayas, Southeast Asia, and mountainous regions of the Middle East. The APHRODITE project now contributes to studies such as the determination of Asian monsoon precipitation change, evaluation of water resources, .
eMBB, URLLC, and mMTC 5G Wireless Network Slicing: A Communication-Theoretic View

Enhanced mobile broadband (eMBB), massive machine-type communications (mMTCs), & highly- reliable reduced delay connectivity are three general capabilities that 5G cellular network is designed to offer (URLLCs). Network slicing can support service diversity by allocating resources to each service in order to guarantee efficiency and isolate it from other services. In order to slice the radio access network (RAN), resources are often distributed orthogonally across the services. In this study, the possible benefits of non-orthogonal RAN sharing resources in uplink communication from a collection of eMBB, mMTC, & URLLC devices to a shared ground station are examined. Contrary to traditional NOMA approaches, which include users with homogenous requirements and can thus be studied over a normal multi-access channel, the method is known as heterogeneity nonorthogonal multi-access (H-NOMA). The paper creates a communication theoretic model to take into consideration the disparate needs and traits of the 3 services. In order to ensure efficiency with non-orthogonal RAN slicing, the notion of dependability heterogeneity is proposed being a model paradigm which takes use of the various dependability needs throughout the applications. According to this research, H- NOMA can, in some regimes, result in substantial improvements in efficiency tradeoffs between the three basic functions as opposed to orthogonal slicing.
Non-Linear Conductivity Response of Graphene on Thin-Film PET Characterized by Transmission and Reflection Air-Plasma THz-TDS

We demonstrate that the conductivity of graphene on thin-film polymer substrates can be accurately determined by reflection-mode air-plasma-based THz time-domain spectroscopy (THz-TDS). The phase uncertainty issue associated with reflection measurements is discussed, and our implementation is validated by convincing agreement with graphene electrical properties extracted from more conventional transmission-mode measurements. Both the reflection and transmission THz-TDS measurements reveal strong non-linear and instantaneous conductivity depletion across an ultra-broad bandwidth (1–9 THz) under relatively high incident THz electrical field strengths (up to 1050 kV/cm).
Integrating multi-plane and multi-region radiomic features to predict pathologic response to neoadjuvant chemoradiation in rectal cancers via pre-treatment MRI

Radiomic analysis has shown significant potential for predicting treatment response to neoadjuvant therapy in rectal cancers via routine MRI, though primarily based off a single acquisition plane or single region of interest. To exploit intuitive clinical and biological aspects of tumor extent on MRI, we present a novel multi-plane, multi-region radiomics framework to more comprehensively characterize and interrogate treatment response on MRI. Our framework was evaluated on a cohort of 71 T2-weighted axial and coronal MRIs from patients diagnosed with rectal cancer and who underwent chemoradiation. 2D radiomic features were extracted from three regions of interest (tumor, fat proximal to tumor, and perirectal fat) across axial and coronal planes, with a two-stage feature selection scheme designed to identify descriptors associated with pathologic complete response. When evaluated via a quadratic discriminant analysis classifier, our multi-plane, multi-region radiomics model outperformed single-plane or single-region feature sets with an area under the ROC curve (AUC) of 0.80 ± 0.03 in discovery and AUC=0.65 in hold-out validation. Uniquely, the optimal feature set comprised descriptors from across multiple planes (axial, coronal) as well as multiple regions (tumor, proximal fat, perirectal fat). Our multi-plane, multi-region radiomics framework may thus enable more comprehensive phenotyping of treatment response on MRI, potentially finding application for improved personalization of therapeutic and surgical interventions in rectal cancers.
A framework for the study of individual behavior and social interactions

Recent work in economics has begun to integrate sociological ideas onto the modelling of individual behavior. In particular, this new approach emphasizes how social context and social interdependences influence the ways in which individuals make choices. This paper provides an overview of an approach to integrating theoretical and empirical analysis of such environments. The analysis is based on a framework due to Brock and Durlauf (2000a, 2000b). Empirical evidence on behalf of this perspective is assessed and some policy implications are explored. (This abstract was borrowed from another version of this item.)
NORMING RATES AND LIMIT THEORY FOR SOME TIME‐VARYING COEFFICIENT AUTOREGRESSIONS

A time‐varying autoregression is considered with a similarity‐based coefficient and possible drift. It is shown that the random‐walk model has a natural interpretation as the leading term in a small‐sigma expansion of a similarity model with an exponential similarity function as its AR coefficient. Consistency of the quasi‐maximum likelihood estimator of the parameters in this model is established, the behaviours of the score and Hessian functions are analysed and test statistics are suggested. A complete list is provided of the normalization rates required for the consistency proof and for the score and Hessian function standardization. A large family of unit root models with stationary and explosive alternatives is characterized within the similarity class through the asymptotic negligibility of a certain quadratic form that appears in the score function. A variant of the stochastic unit root model within the class is studied, and a large‐sample limit theory provided, which leads to a new nonlinear diffusion process limit showing the form of the drift and conditional volatility induced by sustained stochastic departures from unity. The findings provide a composite case for time‐varying coefficient dynamic modelling. Some simulations and a brief empirical application to data on international Exchange Traded Funds are included. Copyright © 2014 Wiley Publishing Ltd
Biocatalytic Profiling of Free and Immobilized Partially Purified Alkaline Protease from an Autochthonous Bacillus aryabhattai Ab15-ES

Partially purified alkaline protease produced by an indigenous bacterial strain, Bacillus aryabhattai Ab15-ES, was insolubilized in alginate beads using an entrapment technique. Maximum entrapped enzyme activities of 68.76% and 71.06% were recorded at optimum conditions of 2% (w/v) sodium alginate and 0.3 M calcium chloride. Biochemical profiling of free and immobilized proteases was investigated by determining their activity and stability as well as kinetic properties. Both enzyme preparations exhibited maximum activity at the optimum pH and temperature of 8.0 and 50 °C, respectively. However, in comparison to the free enzyme, the immobilized protease showed improved pH stability at 8.0–9.0 and thermal stability at 40–50 °C. In addition, the entrapped protease exhibited a higher Vmax and increased affinity to the substrate (1.65-fold) than the soluble enzyme. The immobilized protease was found to be more stable than the free enzyme, retaining 80.88% and 38.37% of its initial activity when stored at 4 °C and 25 °C, respectively, for 30 d. After repeated use seven times, the protease entrapped in alginate beads maintained 32.93% of its original activity. These findings suggest the efficacy and sustainability of the developed immobilized catalytic system for various biotechnological applications.
Molecular dynamics simulation of the production of acoustic waves by pulsed laser irradiation

In this work we model the production of acoustic waves in a material irradiated by a pulsed laser, by means of molecular-dynamics simulation. We show that with this technique and using a simple Lennard-Jones interaction potential, quantitative information on the acoustic waves is obtained for a wide range of laser energies. Results for laser fluences producing heating and even melting and ablation of the irradiated material are presented, thus extending what can be obtained by means of the standard thermoelastic models. Moreover, we show that at low fluences the obtained results are in very good agreement with standard thermoelastic calculations.
Hepatocyte-specific knockout of HIF-2α cannot alleviate carbon tetrachloride-induced liver fibrosis in mice

Background The effects of hypoxia inducible factor-2α (HIF-2α) deficiency on liver fibrosis have not been demonstrated in a fibrosis model induced by carbon tetrachloride (CCl4). We aimed to examine whether hepatocyte-specific HIF-2α deletion could ameliorate CCl4-induced liver fibrosis in mice. Methods Hepatocyte-specific HIF-2α knockout mice were created using an albumin promoter-driven Cre recombinase. HIF-2α knockout (KO) mice and floxed control wild-type (WT) mice were fed a normal diet (ND) and received either twice weekly intraperitoneal injections of CCl4 solution (CCl4 dissolved in olive oil) or the corresponding amount of olive oil for 8 weeks. The indicators of liver function, glucose and lipid metabolism, and liver histology were compared among the different groups. Results Hepatocyte-specific HIF-2α knockout had no effect on the growth, liver function, glucose or lipid metabolism in mice. CCl4-treated KO and WT mice had a similar pattern of injury and inflammatory cell infiltration in the liver. Quantification of Masson staining, α-smooth muscle actin (α-SMA) immunohistochemistry, and the hydroxyproline (HYP) content revealed similar liver fibrosis levels between KO and WT mice injected intraperitoneally with CCl4. Immunohistochemistry analysis suggested that HIF-2α was mainly expressed in the portal area and hepatic sinusoids but not in hepatocytes. Bioinformatics analyses further indicated that HIF-2α expression was neither liver specific nor hepatocyte specific, and the effect of HIF-2α in hepatocytes on liver fibrosis may not be as important as that in liver sinuses. Conclusions Hepatocyte HIF-2α expression may not be a key factor in the initiation of liver fibrogenesis, and hepatocyte-specific deletion of HIF-2α may not be the ideal therapeutic strategy for liver fibrosis.
Cardiac Troponin I in Patients Undergoing Percutaneous and Surgical Myocardial Revascularization: Comparison of Analytical Methods

The myocardial infarction (MI) types 4a and 5 guidelines recommend cardiac troponin (cTn) diagnostic decision limits of 5 and 10 times the 99th percentile, respectively. Different cTn kits elicit different responses, so the MI diagnosis is still challenging. The study aimed to establish the cutoff values and the accuracy of three different cTnI kits in the diagnosis of post-procedural MI. We analyzed 115 patients with multivessel stable chronic coronary artery disease; 26 underwent percutaneous coronary intervention, and 89 underwent coronary artery bypass graft. Delayed-enhancement magnetic resonance imaging was performed before and after each intervention for definitive MI diagnoses. Two contemporary and one high-sensitivity cTnI immunoassays were used. ROC curves determined the accuracy of each assay. Low accuracy was observed after applying the current guidelines recommendations. The three cTnI assays accuracies improved when adjusted by the new ROC cutoffs, reaching 82% for MI type 5 for all assays, and 78%, 88%, and 87% for MI type 4 for Siemens, Beckman, and Abbott, respectively. The ultrasensitive and contemporary tests’ accuracy for MI types 4a and 5 diagnoses are equivalent when adjusted for these new cutoffs. The hs-cTnI assays had lower accuracy than contemporary tests for MI types 4a and 5 diagnoses.
Wideband Dual-Polarized Endfire Phased Array Antenna With Small Ground Clearance for 5G mmWave Mobile Terminals

A dual-polarized endfire phased array antenna is presented for 5G mmWave mobile terminal applications. The antenna element combines a pair of top-hat dipoles with an open slot in two substrate layers. The dipole is excited by an open-ended substrate integrated waveguide (SIW) for vertical polarization, and the slot is coupled by a bent stripline for horizontal polarization. Both radiators can provide wide bandwidth, and share a small ground clearance of merely 1.6 mm. A $1\times4$ phased array is designed with an element spacing of 6 mm. Decoupling vias and decoupling slots are added between elements to improve port isolation. The simulated and measured overlapped bandwidth of the two polarizations are 21.4% and 14.6%, respectively. The isolation between any two ports is higher than 18 dB. The measured scanning beams of both polarizations are capable of covering ±42° within 3-dB gain variation.
Submicrometer resonant tunnelling diodes fabricated by photolithography and selective wet etching

A new process based on photolithography and selective wet etching has been used to fabricate small area resonant tunnelling diodes. The low‐temperature current‐voltage (I‐V) characteristics of diodes with conducting widths less than 0.1 μm show additional peaks due to 1D lateral quantum confinement. We observe a pronounced asymmetry in I‐V which we explain in terms of tunnelling from emitter states which have a different degree of lateral quantum confinement.
An Iterated Function System for Reich Contraction in Complete b Metric Space

—In this paper, we introduce R Iterated Function System and employ the Hutchinson Barnsley theory (HB) to construct a fractal set as its unique ﬁxed point by using Reich contractions in a complete b metric space. We discuss about well posedness of ﬁxed point problem for b metric space.
Dynamic Optimality of Yield Curve Strategies

This paper formulates and analyzes a dynamic optimization problem of bond portfolios within Markovian Heath-Jarrow-Morton term structure models. In particular, we investigate optimal yield curve strategies analytically and numerically, and provide theoretical justification for a typical strategy which is recommended in practice for an expected change in the shape of the yield curve. In the numerical analysis, we utilize a new technique based on the asymptotic expansion approach in order to increase efficiency in computation.
A Fast-Converging Radial Basis Function Neural Network-Based MPPT Controller for Static and Dynamic Variations in Solar Irradiation

The use of maximum power point tracking techniques, often known as MPPT algorithms, is required to improve the performance of PV systems. In rapidly varying atmospheric conditions, the traditional MPPT approaches do not work as intended. In the paper, a perturb and observe technique based MPPT algorithm is developed together with a radial basis function neural network (RBFNN). To specify and track the maximum power point (MPP), the proposed framework is implemented. Employing the RBFNN as the input-output training information set, the optimal duty cycle is computed while considering varied PV array current and voltage values. Further, an intelligent reconfiguration strategy is developed to enhance the MPP and array characteristics. The proposed hybrid RBFNN and intelligent reconfiguration methodology enhance the performance by 43.05%, 12.22%, 6.81%, 5.6% with the reduced convergence time of 0.06 sec under different shading conditions.