Miracle-dz/UniFAR-FTUs huggingface dataset:
Compressive Sparse Data Gathering With Low-Rank and Total Variation in Wireless Sensor Networks

Wireless Sensor Networks (WSNs) have been deeply studied by many researchers and been widely used in many fields. Since a large amount of energy for WSNs is used for sensing and transmitting, researchers come up with many methods to reduce the number of sensed and transmitted data packets. Compressive Data Gathering (CDG) is a well-known method to gather WSNs data, but it does not realize sparse sensing as it needs to sense all data and compress them. The efficiency of Low-rank and TV regularizations for recovering WSNs data has been demonstrated, however, they are not combined to enable utilization of data correlation throughout the network. To recover the data accurately and to reduce the energy consumption in WSNs, we propose a Compressive Sparse Data Gathering (CSDG) scheme including a Compressive Sparse Sampling (CSS) method and a data recovery algorithm based on low-rank and Total Variation (TV) regularizations fully exploiting the sparsity and low-rank characteristics of WSNs data. The alternating direction method of multipliers and the steepest descent method are used to solve the problem. Simulations show that the CSDG method outperforms the state-of-the-art methods in terms of the recovery accuracy. Moreover, with fairly low sparse sampling ratio and high compression ratio, CSDG method can still recover the original signal with little error. As the number of sensed data and transmitted data is reduced greatly with sparse sampling and compression, the energy consumption of WSNs is lessen and the lifetime is prolonged.
Research on the Entry Threshold of P2P Lending Platform Considering the Social Reputation Level of Borrowers

According to two situations of establishing the threshold of social reputation of the online lending platform, this paper establishes the profit maximization model of P2P lending platform, analyzing the pricing of P2P lending platform and answering whether and when it is necessary to establish a social reputation threshold for borrowers. Moreover, this paper analyzes the influence of the platform's exclusive strategy on the number of bilateral users and the platform's profit. The results show that the platform needs to set the threshold when lenders are more sensitive to borrowers' social reputation. In addition, through the analysis of market size and platform profit, it is found that when the platform strengthens the sensitivity of lenders to the average social credit level of borrowers, it will increase the number of lenders and the platform's own profit at the same time.
Convergent and concurrent validity of the Frankfurt Complaint Questionnaire as a screener for psychosis risk

For the broad identification of a risk for a serious mental disorder, valid and reliable screeners are needed to detect those most likely benefitting from a time-consuming and costly in-depth clinical assessment. In the early detection of psychoses, multiple screeners for an ultra-high-risk have already been suggested. Yet, no screener explicitly targets an increased risk according to the basic symptoms (BS) criteria. We therefore explored the Frankfurt Complaint Questionnaire (FCQ) as a potential screener for BS in comparison with their gold standard clinical assessment using the Schizophrenia Proneness Instrument (SPI-A/SPI-CY) by examining its convergent (agreement between screener and gold standard, calculated by the overall percentages of agreement between FCQ and SPI-A/SPI-CY) and concurrent (degree to which a screener can identify individuals with the target condition, examined by diagnostic accuracy measures calculated using thresholds of receiver operating characteristic curves) validity. The sample consisted of 81 patients of a psychosis early detection service (41 with an at-risk mental state or psychosis, and 40 with a nonpsychotic mental disorder). Only two visual perception disturbances reached a beyond-chance level of agreement between FCQ and SPI-A/SPI-CY. For the BS criteria ‘cognitive perceptive basic symptoms’ and ‘cognitive disturbances’, only insufficient agreement between assessment techniques was detected with Cohen’s kappa being 0.228 and 0.130, respectively, with an overestimation by the FCQ. Diagnostic likelihood ratios indicated only a clinically irrelevant increase in the probability of detecting BS criteria; thus, the concurrent validity of both the total of all and of only criteria-relevant FCQ items was insufficient. Both concurrent and convergent validity of the FCQ were poor, and the FCQ dramatically overestimated clinician-assessed risk. Our results suggest that the FCQ should not be used as a screener for BS criteria and that the convergent validity is not guaranteed on the basis of face validity alone, but has to be formally assessed.
ASYMPTOTIC ANALYSIS FOR PORTFOLIO OPTIMIZATION PROBLEM UNDER AN EXTENDED HESTON’S STOCHASTIC VOLATILITY MODEL

In this paper, we study the portfolio optimization problem under an extended Heston stochastic volatility model. By using asymptotic analysis technique, we are able to derive approximations of the optimal value function and the optimal strategy. We give an explicit asymptotic approximation of the optimal strategy for the case of hyperbolic absolute risk aversion utility functions and prove that the leading order term of the optimal strategy recovers the approximation up to the first order of the optimal value function. AMS Subject Classification: 90C39, 90C59, 91G10, 35Q93
Feature selection of Complex Power Quality Disturbances and Parameter Optimization of Random Forest

A hybrid method based on modified discrete artificial bee colony algorithm(MDABC) for power quality disturbance(PQD) signal feature selection and parameter optimization of random forest(RF) is proposed. Firstly, time-frequency features of the complex power quality disturbance signal are extracted using s-transform(ST) to form an original feature set; Then, by using default parameters of RF, the out-of-bag(OOB) Permutation test value of each feature in the original feature set is calculated as the feature weight, and the features of the training and verification data set are rearranged in descending order accordingly. Finally, taking the generalization error of RF as the objective function, the forest scale: nTree, the number of input features:Ni and the node feature subset size:q are optimized using MDABC to determine the optimal parameters of RF and the optimal feature set. It can be seen from the experiment that compared with the RF classifier before optimization, the accuracy of the MDABC-RF classifier in the classification of 16 and 19 complex PQD signals is better, and its operating efficiency is greatly improved.
Assessment of Ice Volume Changes in the Cryosphere via Simplified Heat Transport Model

In order to describe changes in ice volume in the cryosphere, a differential equation mathematical model is used in this paper. The dominating effects of freezing and thawing in the cryosphere enable simplification of the heat transport equations. This results in a mathematical model that can be solved exactly and is useful in investigating other climatic components, which in turn may be similarly analyzed for possible Global Circulation Model (GCM) validation. Data forms representing temperature and ice volume during the Pleistocene are available and can be directly compared with the exact solution of the simplified differential equation used in this paper. The model parameters may then be adjusted to approximate the effects of climate change; the adjusted model then run in reverse time, to develop an alternative history of ice volume of the cryosphere to be compared with the actual data interpretations previously published in the literature. In this fashion, an assessment may be made as to possible climate impacts in the cryosphere.
The development of the Australian Space Forecast Centre (ASFC)

Abstract. The Ionospheric Prediction Service (IPS) was formed in 1947 to provide monthly prediction services for high frequency (HF) radio, in particular to support HF communications with the United Kingdom. It was quickly recognized that to be effective such a service also had to provide advice when ionospheric storms prevented HF communications from taking place. With the advent of the International Geophysical Year (IGY), short-term forecasts were also required for research programmes and the task of supplying the Australian input to these was given to Frank Cook, of the IPS, while Jack Turner, also of the IPS, supervised the generation of ionospheric maps to support high latitude HF communications. These two important IGY activities formed the platform on which all future IPS services would be built. This paper reviews the development of the Australian Space Forecast Centre (ASFC), which arose from these early origins.
The Effect of Water Solubles on the Hygroscopicity of Urban Aerosols

In this paper, the author extracted some microphysical and optical properties of urban aerosols from OPAC by varying the concentrations of water soluble at the spectral range of 0. 25μm to 2. 5μm and eight relative humidities (RHs) (0, 50, 70, 80, 90, 95, 98, and 99%). The microphysical properties extracted were diameters, volume mix ratio, number mix ratio, mass mix ratio and refractive indices while the optical properties are optical depth and asymmetric parameters all as a function of RHs. Using the microphysical properties, hygroscopic growth factors of the mixtures and their effective refractive indices were determined while using optical depth we determined its relation with RHs, the enhancement parameters and Angstrom parameters. The hygroscopic growths and enhancement parameters were then parameterized using some models to determine their relationship with RHs. The data fitted the models very well. The angstrom coefficients show that the mixtures have bi-modal type of distribution with the dominance of fine mode particles and the mode sizes increase with the increase in water soluble concentrations and RH. The relation of optical depth with RH shows improvement with the increase in water soluble but decreases with the increase in wavelengths. The asymmetric parameters show that hygroscopic growth enhances forward scattering at smaller wavelengths.
CCGA: Clustering and Capturing Group Activities for DGA-Based Botnets Detection

Botnet is a part of the most destructive threats to network security and is often used in malicious activities. DGA-based botnet, which uses Domain Generation Algorithm (DGA) to evade detection, has become the main channel to carry out online crimes. In the past, many detection mechanisms focusing on domain features are proposed, but the potential problem is that the features extracting only from the domain names are insufficient and the enemies could easily forge them to disturb detection. In this paper, we propose a novel approach named CCGA to detect DGA-based botnet by leveraging the concerted group behaviors of infected hosts on DNS traffic. The analysis of group behaviors enhances the robustness of our system irrespective of various evasion techniques, such as fake-querying, packet encryption and noise generated by normal users. The proposed scheme associates hosts together in an unsupervised way and then uses supervised learning to distinguish whether it's a botnet. Our system is evaluated in a large ISP over two days and compared with the state of art FANCI. Experimental results show that CCGA can accurately and effectively detect DGA-based botnet in a real-world network. Our system also catches 5 unknown botnet groups and provides a novel method to verify them. Therefore, the system will provide an unique perspective on the current state of globally distributed malware, particularly the ones that use DNS.
The Tropical Andean Bee Fauna (Insecta: Hymenoptera: Apoidea), with Examples from Colombia

Using reports from the literature and data from collections, we provide the first checklist of the tropical Andean bee species found above 2500 m, with a particular emphasis on those in Colombia, where the data are strongest. This listing consists of 65 species in 26 genera from 5 families for Colombia and 90 species in 27 genera for Venezuela, Ecuador, and Peru. For Colombia, the Apidae and Halictidae are the most speciose taxa of those families found at high elevations and contain a similar numbers of species; however, unlike Apidae, Halictidae is not well understood taxonomically and appears to be the most diverse apoid lineage in the tropical Andes. Most bee species occur in cloud forest and only a few in Paramo. Too little data is available for general conclusions on the bee faunas for the remaining countries at this time. We also present an overview of the biogeogra- phy, distribution, and biology of this little-known fauna and suggest future directions for research on these bees.
Structural equation model for burn severity with topographic variables and susceptible forest cover.

Due to its significant roles in post-fire responses of forest ecosystem, numerous studies have been investigating factors affecting burn severity. In the broad sense, topography, fuels, and fire weather, known as the forest fire triangle, determine the degree of burn severity. Most previous studies have adopted ordinary least squares (OLS) methods to investigate these factors, which have proven effective for capturing the direct and linear effects of those variables on burn severity. However, they oversimplify the relationships among variables and have limitations in explaining the complex effects of the variables. One way to overcome this limitation is the structural equation model (SEM) method. SEM can decompose effects of a variable into direct effects and indirect (i.e., acting through other variables) effects. The goal of this study is to capture a systematic structure, explaining how topographic characteristics including slope, elevation, topographic wetness index (TWI), solar radiation index (SRI), and susceptible forest cover type (i.e., Japanese red pine) affect burn severity. We built a hypothetical SEM and estimated the model in AMOS. The results strongly suggest that the effects of topographic characteristics are far more complex than those suggested by the OLS analyses in previous studies. Specifically, elevation and TWI had direct and indirect negative effects on burn severity, while slope and SRI had only an indirect positive effect, which was not captured in the linear regression model. Nonetheless, the percentage of red pine showed the strongest positive effect on burn severity (i.e., increasing burn severity). The results of this study and those of previous studies reinforce the importance of controlling susceptible forest cover through forest management and silviculture.
A joint model for stated choice and best-worst scaling data using latent attribute importance: application to rail-air intermodality

This paper looks at modelling choices in the presence of a new mode of transport, where there is a need to understand the sensitivities to a number of new attributes. Stated choice (SC) data and two types of Best-worst scaling (BWS) data (i.e. case 1 and case 2) are collected from the same respondents. We mix survey methods rather than using a longer SC survey to better understand choice behaviour whilst reducing the boredom caused by one very long set of SC choices. Although BWS data has been increasingly collected alongside stated choice (SC) data, little is known about the relationships between BWS responses and SC responses at the level of individual respondents. Also, little effort has been made to jointly exploit the behavioural information from BWS data and SC data to improve the understanding of choices. This paper proposes a joint model which links the BWS and SC data through the notion of latent attribute importance. The modelling results show that people perceive attribute importance in a relatively consistent way across different survey methods, i.e. a person who perceives higher importance from an attribute is likely to show stronger sensitivity to that attribute in SC tasks, give more weight to the same attribute in BWS1 tasks and exhibit a wider gaps in terms of attractiveness between levels for the same attribute – in comparison with other individuals. This consistency shows that the additional behavioural information can be gained by using a joint model estimated on BWS1 and BWS2 data alongside more traditional SC data, helping us to improve the explanation of the choices and the role of the attributes. Our results however do not find a one-to-one relationship between different survey methods and analysts thus need to be mindful that there remain some differences in how attributes are evaluated between SC, BWS1 and BWS2 surveys.
Intestinal microbiota of mangrove red snapper (Lutjanus argentimaculatus Forsskål, 1775) reared in sea cages

Using polymerase chain reaction ampli¢cation of 16S rDNA coupled to denaturing gradient gel electrophoresis (DGGE) and sequencing of isolated amplicons, we investigated the microbiota of the intestinal digesta and mucosal surface in mangrove red snapper cultured in a cage aquaculture area in Daya Bay. A total of 14 sequences were characterized by phylogenetic analysis. Among the bacterial species determinated from sequences, the g-Proteobacteria group (64.25%, nine species) dominated absolutely in ¢sh intestines. Others belonged to Spirochaetes (14.3%, two species), Cyanobacteria (14.3%, two species) and Firmicutes (7.15%, one species). However, the bacteria were identi¢ed as uncultured accounting for 28.6% (four species). The apparent bacterial richness (calculated as the numbers of DGGE bands) was signi¢cantly higher in digesta than that in mucosal tissue samples (Po0.05). There existed ¢ve dominant individual populations including one unknown species of Firmicutes, Arthrospira sp. ,Vibrio metschnikovii,Vibrio harveyi andVibrio sp. in intestinal digesta, and in contrast, only three dominant individual populations including Vibrio natriegens, V. harveyi and Vibrio sp. in intestinal mucosal surface. The results indicated that the microbiota in intestinal digesta was signi¢cantly diierent from that in mucosal surface.
Effect of meloxicam on serum vitamin and cytokine levels during endotoxemia

Gerec ve Yontem: Arastirmada elli yetiskin erkek Sprague Dawley rat kullanildi. Bes adet rat 0 zaman orneklemeyi elde etmek icin ayrildiktan sonar kalan ratlar 3 esit gruba ayrildi. Birinci gruba lipopolisakkarit (4 mg, intraperitoneal), ikinci gruba meloksikam (50 mg/kg, intraperitoneal) ve ucuncu gruba lipopolisakkarit (4 mg, intraperitoneal) + meloksikam (50 mg/kg, intraperitoneal) uygulandi. Kan ornekleri 2. , 4. ve 8. saatlerde alindi. Serum retinol, β-karoten, vitamin C, interloykin-1α, interloykin-1β, interloykin-2 ve rutin biyokimyasal parametreler olculdu.
Phased Array Antenna Element with Embedded Cavity and MMIC using Direct Digital Manufacturing

This paper introduces a multilayer, wideband, high-efficiency, patch antenna with embedded cavity and monolithic microwave integrated circuit (MMIC) phase shifter using direct digital manufacturing (DDM). DDM platform combines fused deposition modeling (FDM) of thermoplastics and micro-dispensing of silver nanoparticle inks to realize cost-effective customized multilayer RF structures. DDM offers design flexibilities in terms of material properties, thicknesses, and shapes that can be harnessed to realize high-performance antennas and arrays. Specifically, an X-band phased array antenna element with embedded cavity and MMIC phase shifter is demonstrated with 81% radiation efficiency (excluding IC loss) and 23% impedance matching bandwidth.
4 5 Rorschach Nomological Network and 6 Resting-State Large Scale Brain Networks 7 Introducing a New Research Design 8 9

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A Dual-Band Millimeter-Wave Antenna for 5G Mobile Applications

In this work, a microstrip antenna suitable for broadband millimeter wave mobile communication is proposed. The microstrip antenna is fed by a coplanar waveguide (CPW) structure with a matching port connected to a 50-Ω resistor. The operating bandwidth of the antenna is able to cover both the 28 GHz and the 39 GHz bands for 5G millimeter wave applications. In addition, an eight-element array is developed and studied. Results show that the array can cover the beamwidth from −30° to 30° in yoz-plane, which can meet the beamforming requirement for the 5G wireless communications.
Compact Comparator for Dual-Polarized Monopulse Array Based on Novel Eight-Port Coupler

A compact planar comparator is proposed for a dually-polarized monopulse beamforming. A novel eight-port coupler is employed as the central part to produce the sum- and difference- beams for two orthogonal polarizations, independently and simultaneously. The proposed comparator has a double-layer microstrip configuration smaller than the area of 0. 75λg × 0. 2λg, and without using T-junctions, vias, closed loops, or steps on each layer. An example of a dual linearly-polarized monopulse array composed of two elements working at 5.8 GHz is built and simulated to verify and demonstrate the performance of the compact comparator. Satisfying properties of sum- and difference-beams for two orthogonal polarizations can be observed, and good matching, isolation, and power division can be achieved in a 10% fractional bandwidth.
Towards Decreasing Side Lobes Produced by Near-Field Phase Gradient Metasurfaces

When steering or tilting the beam of a planar high-gain antenna using a near-field phase gradient metasurface, undesirable side lobes are often noted. These side lobes can be predicted reasonably well by exciting the metasurface with a normally incident uniform plane wave but direct optimisation of such an electrically large metasurface to reduce strongest undesirable side lobes is computationally very expensive. Here we have applied a more efficient approach to reduce the levels of all side lobes below −20 dB.
Institutional Aspects of the Maputo Development Corridor

Maputo Development Corridor (MDC), what actors and stakeholders are involved in the policy- and decision-making processes, and draws some lessons for future development corridors and spatial development initiatives (SDIs) in the broader Southern African region. The analysis reveals that the institutional structure of the MDC - which is based on such aspects as 'political champions', 'fast-tracking' of project design and implementation, the crowding-in of private investment and a minimalist approach to institutions - is designed for the facilitation of 'bankable' private investments projects and public-private partnerships (PPPs), but contains several institutional and organisational weaknesses which have negative consequences for broader 'development' goals, job creation and the integration of provincial and local governments and communities in the process. These drawbacks in combination with the radically different conditions prevailing in the neighbouring countries suggest that the MDC approach needs to be considerably revised if it is to be applied to regional SDIs, especially if these are aiming beyond transport routes and huge investment initiatives.