Miracle-dz/UniFAR-FTUs huggingface dataset:
Coverage Analysis of Max-SIR Cell Association in HetNets Under Nakagami Fading

For maximum signal-to-interference (SIR) ratio cell association, we investigate the coverage probability of HetNets under Nakagami fading. Prompting serious analytical complexities, Nakagami-type fading, however, describes several important wireless environments of 4G/5G standards, including multi-antenna systems. Adopting tools of stochastic geometry, we provide a number of closed-form approximations for the coverage probability, which have been missing in the literature. Our analysis covers integer and noninteger Nakagami, Rician, and $\kappa -\mu$ shadowed fading distributions, and also multiuser zero-forcing beamforming in the downlink. Furthermore, the analysis of this paper incorporates the traits of AWGN, partially loaded systems, and bounded path-loss function, which are often overlooked in studying HetNets. The result are easy to compute, preserve acceptable accuracy, and explicitly demonstrate the impact of fading parameters, density of BSs, SIR thresholds, loads, and path-loss model. We reveal important insights regarding the practice of densification in conjunction with SIR thresholds, BS loads, and path-loss model. It is observed that from a network-level perspective, a bounded path-loss model can be grasped via a reduction of the density of BSs granting association as well as interference, for which the former becomes dominant in dense configurations.
Integration of Information Systems and Cybersecurity Countermeasures: An Exposure to Risk Perspective

This paper investigates the relationship between Information Systems (IS) integration and the use of cybersecurity countermeasures using an adapted exposure to risk perspective which considers both the probability of a risk through vulnerability points theory and the impact of the risk if it occurs. Based on an econometric analysis of a survey sample of 9,721 French firms, the study finds that higher degrees of system integration entail higher degrees of cybersecurity usage. Whereas previously it was thought that systems integration reduces the number of vulnerabilities and thus the need for cybersecurity countermeasures, we find that the more the system is integrated, the greater the use of self-protective cybersecurity countermeasures. We theorize that this finding comes from the elimination of many uncontrollable vulnerabilities and the presence of fewer, but controllable, vulnerability points. This finding holds both for internal and external integration but is stronger in the latter case. Moreover, results show that internal dynamism is positively correlated with cybersecurity countermeasures. Our reasoning applies to cybersecurity in terms of self-protective security measures but not necessarily to risk-transfer security measures.
Thermal Characteristics OfPLA-bamboo Composites

The effective properties for the thermal characteristics of polylactic acid (PLA) bamboo composites, such as thermal conductivity, density and porosity were investigated experimentally. The thermal insulation characteristics are significantly dominated by these parameters. The thermal conductivity was measured by the transient hot wire method and the steady state method. The measured data was compared with each other and also used for the verification of the validity of Russell’s theoretical thermal conductivity model for green composites. The results show that the thermal conductivity of PLA-bamboo depends on the direction of fiber alignment as well as the direction of stacking. The thermal conductivity decreases gradually with decreasing the porosity (i.e., increasing the density of fiber). It was also clear that the theoretical estimation based on Russell’s model is adaptable to the anisotropic PLA-bamboo composites. All of the thermal conductivity measured by using the steady state method is lower than that measured by using the hot wire method. The thermal conductivity through the thickness direction is lower than that of surface plane averaged thermal conductivity. Due to the anisotropicy of its low thermal conductivity, the PLA-bamboo “green” composites have excellent insulation properties.
Relative Localization of RFID Tags using Spatial-Temporal Phase Profiling

Many object localization applications need the relative locations of a set of objects as oppose to their absolute locations. Although many schemes for object localization using Radio Frequency Identification (RFID) tags have been proposed, they mostly focus on absolute object localization and are not suitable for relative object localization because of large error margins and the special hardware that they require. In this paper, we propose an approach called Spatial-Temporal Phase Profiling (STPP) to RFID based relative object localization. The basic idea of STPP is that by moving a reader over a set of tags during which the reader continuously interrogating the tags, for each tag, the reader obtains a sequence of RF phase values, which we call a phase profile, from the tag's responses over time. By analyzing the spatial-temporal dynamics in the phase profiles, STPP can calculate the spatial ordering among the tags. In comparison with prior absolute object localization schemes, STPP requires neither dedicated infrastructure nor special hardware. We implemented STPP and evaluated its performance in two real-world applications: locating misplaced books in a library and determining baggage order in an airport. The experimental results show that STPP achieves about 84% ordering accuracy for misplaced books and 95% ordering accuracy for baggage handling.
Change of Femoral Anteversion Angle in Children With Intoeing Gait Measured by Three-Dimensional Computed Tomography Reconstruction: One-Year Follow-Up Study

Objective To evaluate femoral anteversion angle (FAA) change in children with intoeing gait depending on age, gender, and initial FAA using three-dimensional computed tomography (3D-CT). Methods The 3D-CT data acquired between 2006 and 2016 were retrospectively reviewed. Children 4 to 10 years of age with symptomatic intoeing gait with follow-up interval of at least 1 year without active treatment were enrolled. Subjects were divided into three groups based on age: group 1 (≥4 and <6 years), group 2 (≥6 and <8 years), and group 3 (≥8 and <10 years). Initial and follow-up FAAs were measured using 3D-CT. Mean changes in FAAs were calculated and compared. Results A total of 200 lower limbs of 100 children (48 males and 52 females, mean age of 6.1±1.6 years) were included. The mean follow-up period was 18.0±5.4 months. Average initial and follow-up FAA in children with intoeing gait was 31.1°±7.8° and 28.9°±8.2°, respectively. The initial FAA of group 1 was largest (33.5°±7.7°). Follow-up FAA of group 1 was significantly reduced to 28.7°±9.2° (p=0.000). FAA changes in groups 1, 2, and 3 were −6.5°±5.8°, −6.4°±5.1°, and −5.3°±4.0°, respectively. These changes of FAA were not significantly (p=0.355) different among the three age groups. However, FAA changes were higher (p=0.012) in females than those in males. In addition, FAA changes showed difference depending on initial FAA. When initial FAA was smaller than 30°, mean FAA change was −5.6°±4.9°. When initial FAA was more than 30°, mean FAA change was −6.8°±5.4° (p=0.019). Conclusion FAA initial in children with intoeing gait was the greatest in age group 1 (4–6 years). This group also showed significant FAA decrease at follow-up. FAA changes were greater when the child was a female, younger, and had greater initial FAA.
Robust visual multitask tracking via composite sparse model

Abstract. Recently, multitask learning was applied to visual tracking by learning sparse particle representations in a joint task, which led to the so-called multitask tracking algorithm (MTT). Although MTT shows impressive tracking performances by mining the interdependencies between particles, the individual feature of each particle is underestimated. The utilized L1,q norm regularization assumes all features are shared between all particles and results in nearly identical representation coefficients in nonsparse rows. We propose a composite sparse multitask tracking algorithm (CSMTT). We develop a composite sparse model to formulate the object appearance as a combination of the shared feature component, the individual feature component, and the outlier component. The composite sparsity is achieved via the L1,∞ and L1,1 norm minimization, and is optimized by the alternating direction method of multipliers, which provides a favorable reconstruction performance and an impressive computational efficiency. Moreover, a dynamical dictionary updating scheme is proposed to capture appearance changes. CSMTT is tested on real-world video sequences under various challenges, and experimental results show that the composite sparse model achieves noticeable lower reconstruction errors and higher computational speeds than traditional sparse models, and CSMTT has consistently better tracking performances against seven state-of-the-art trackers.
Flame Recognition Algorithm Research under Complex Background

The paper presents a flame recognition algorithm under complex background. The light changes are mainly studied on the impact of the flame recognition system. An adaptive brightness threshold method which aimed at improving the speed and efficiency of the algorithm is proposed. The static and dynamic flame features are analyzed and the probability model of the flame detection is established based on the trust model. The Suspected probability is used to reflect the video image to appear the probability of fire. The experimental results show that the algorithm remains with stronger adaptive and anti-jamming ability for the white shadow interference of moving objects, static white shadow interference, street lamps, car lamps and lighting changes effects and so on, the suspected probability can always be lower than 5%. Therefore, the algorithm in practice has a broad application prospects.
An application of the finite-discrete element method in the simulation of ceramic breakage: methodology for a validation study for alumina specimens

Alumina (aluminum oxide, Al2O3) particles are pelletised and fired to produce high porosity catalyst pellets of complex shapes. These pellets fill cylindrical reactor columns with particulate packing structures that are key to the in-service performance, but will suffer breakages which impact on catalyst performance. The combined FiniteDiscrete Element Method (FEMDEM) is ideally suited to the simulation of both the multi-body pellet dynamic packing and quasi-static interactions as well as the stress field of each individual pellet, its deformations and fragmentation. The application of FEMDEM fracture modelling to a fine-grained brittle and porous material is novel. This paper presents a methodology for a validation study through comparison with three pointbending and Brazilian tests and discusses FEMDEM's potential in modelling multi-body fragile systems.
Nitrogen dioxide detection using copper oxide thin film sensor prepared by direct current sputtering technique

Semiconducting copper oxide (CuO) thin films have been deposited using DC sputtering technique using copper (Cu) target for detection of oxidizing nitrogen dioxide (NO2) gas. A series of CuO thin films (gas sensors) (C1-C7) of various thicknesses had been prepared on Corning glass substrate. The time of deposition was between 90 to 270 minutes at 30-minutes time interval. The thickness of the gas sensors was measured using a surface profiler (Dektak 3) and found to be in the range between 159 nm to 604 nm. The resistance and the gas sensing properties to NO2, mainly the sensitivity, response and recovery time were investigated using the gas sensor characterization system (GSCS) for a single gas sensor and for an array of sensors in series configurations at different operating temperatures. The resistance of the gas sensor decreased when exposed to NO2 gas. The best sensitivity (0.859) for the single gas sensor configuration was found to be sensor C3 which was deposited at 150 minutes, corresponding to 247 nm thickness. While, for the sensor array configuration, the best sensitivity (0.788) was found to be sensor AC3 at the combination of 90 and 150 minutes-deposition time. The response time for the gas sensor C3 was 57 seconds and the recovery time was 60 seconds; whereas for the array gas sensor AC3, the response and recovery time were 45 seconds and 60 seconds, respectively. Thus, the single configuration had a better sensitivity and response time compared to the array configuration. Hence, the single configuration was the preferable gas sensor for NO2 gas.
Reassessing the mechanics of parasite motility and host-cell invasion

The capacity to migrate is fundamental to multicellular and single-celled life. Apicomplexan parasites, an ancient protozoan clade that includes malaria parasites (Plasmodium) and Toxoplasma, achieve remarkable speeds of directional cell movement. This rapidity is achieved via a divergent actomyosin motor system, housed within a narrow compartment that lies underneath the length of the parasite plasma membrane. How this motor functions at a mechanistic level during motility and host cell invasion is a matter of debate. Here, we integrate old and new insights toward refining the current model for the function of this motor with the aim of revitalizing interest in the mechanics of how these deadly pathogens move.
Miniature differential mobility analyzer for compact field-portable spectrometers

ABSTRACT A low-flow miniature differential mobility analyzer (mDMA) has been developed for compact field-portable mobility spectrometers to classify the submicrometer aerosol. The mDMA was designed for an ultra-low aerosol flow rate of 0.05 L/min. At a sheath flow rate of 0.2 L/min, the mDMA's upper size limit was estimated to be about 921 nm. The mDMA has a classification zone of 2.54 cm long, an outer diameter of 2.54 cm, and an inner diameter of 1.778 cm. The design allows low-cost fabrication and easy assembly. Tandem DMA measurements were carried out to evaluate the performance of the mDMA. Its transfer function was described using Stolzenburg's model. The experimentally measured transfer function shows close agreement with the theory. The transmission efficiency was comparable to that of the Knutson–Whitby DMA for particles in the range of 10–1000 nm. The mobility resolution was comparable to that of the TSI 3085 nanoDMA at the same aerosol flow rate. The design features and performance of the mDMA make it suitable for compact field portable mobility size spectrometers for measurement of nanoparticles and submicrometer aerosol.
Germline DNA Copy Number Aberrations Identified as Potential Prognostic Factors for Breast Cancer Recurrence

Breast cancer recurrence (BCR) is a common treatment outcome despite curative-intent primary treatment of non-metastatic breast cancer. Currently used prognostic and predictive factors utilize tumor-based markers, and are not optimal determinants of risk of BCR. Germline-based copy number aberrations (CNAs) have not been evaluated as determinants of predisposition to experience BCR. In this study, we accessed germline DNA from 369 female breast cancer subjects who received curative-intent primary treatment following diagnosis. Of these, 155 experienced BCR and 214 did not, after a median duration of follow up after breast cancer diagnosis of 6.35 years (range = 0.60–21.78) and 8.60 years (range = 3.08–13.57), respectively. Whole genome CNA genotyping was performed on the Affymetrix SNP array 6.0 platform. CNAs were identified using the SNP-Fast Adaptive States Segmentation Technique 2 algorithm implemented in Nexus Copy Number 6.0. Six samples were removed due to poor quality scores, leaving 363 samples for further analysis. We identified 18,561 CNAs with ≥1 kb as a predefined cut-off for observed aberrations. Univariate survival analyses (log-rank tests) identified seven CNAs (two copy number gains and five copy neutral-loss of heterozygosities, CN-LOHs) showing significant differences (P<2.01×10−5) in recurrence-free survival (RFS) probabilities with and without CNAs.We also observed three additional but distinct CN-LOHs showing significant differences in RFS probabilities (P<2.86×10−5) when analyses were restricted to stratified cases (luminal A, n = 208) only. After adjusting for tumor stage and grade in multivariate analyses (Cox proportional hazards models), all the CNAs remained strongly associated with the phenotype of BCR. Of these, we confirmed three CNAs at 17q11.2, 11q13.1 and 6q24.1 in representative samples using independent genotyping platforms. Our results suggest further investigations on the potential use of germline DNA variations as prognostic markers in cancer-associated phenotypes.
High-performance continuous-wave room temperature 4.0-μm quantum cascade lasers with single-facet optical emission exceeding 2 W

A strain-balanced, AlInAs/InGaAs/InP quantum cascade laser structure, designed for light emission at 4.0 μm using nonresonant extraction design approach, was grown by molecular beam epitaxy. Laser devices were processed in buried heterostructure geometry. An air-cooled laser system incorporating a 10-mm × 11.5-μm laser with antireflection-coated front facet and high-reflection-coated back facet delivered over 2 W of single-ended optical power in a collimated beam. Maximum continuous-wave room temperature wall plug efficiency of 5.0% was demonstrated for a high-reflection-coated 3.65-mm × 8.7-μm laser mounted on an aluminum nitride submount.
Multi-device, Multi-tenant Model Selection with GP-EI

AutoML has become a popular service that is provided by most leading cloud service providers today. In this paper, we focus on the AutoML problem from the \emph{service provider's perspective}, motivated by the following practical consideration: When an AutoML service needs to serve {\em multiple users} with {\em multiple devices} at the same time, how can we allocate these devices to users in an efficient way? We focus on GP-EI, one of the most popular algorithms for automatic model selection and hyperparameter tuning, used by systems such as Google Vizer. The technical contribution of this paper is the first multi-device, multi-tenant algorithm for GP-EI that is aware of \emph{multiple} computation devices and multiple users sharing the same set of computation devices. Theoretically, given $N$ users and $M$ devices, we obtain a regret bound of $O((\text{\bf {MIU}}(T,K) + M)\frac{N^2}{M})$, where $\text{\bf {MIU}}(T,K)$ refers to the maximal incremental uncertainty up to time $T$ for the covariance matrix $K$. Empirically, we evaluate our algorithm on two applications of automatic model selection, and show that our algorithm significantly outperforms the strategy of serving users independently. Moreover, when multiple computation devices are available, we achieve near-linear speedup when the number of users is much larger than the number of devices.
HISTORICAL DEVELOPMENT

At the start of the twenty-first century, higher education in the United States stands as a formidable enterprise. As an established "knowledge industry" it represents about 3 percent of the gross national product. Virtually every governor and legislature across the nation evokes colleges and universities as critical to a state's economic and cultural development. Its profile includes more than 4,000 accredited institutions that enroll over fifteen million students and confers in excess of two million degrees annually. Colleges and universities spend about $26 billion per year on research and development, of which $16 billion comes from federal agencies. The research universities' ability to attract expertise is recognized internationally.
A Dense Phase Descriptor for Human Ear Recognition

Ear print is an imminent biometric modality that has been attracting increasing attention in the biometric community. However, compared with well-established modalities, such as face and fingerprints, a limited number of contributions has been offered on ear imaging. Moreover, only several studies address the aspect of ear characterization (i.e., feature design). In this respect, in this paper, we propose a novel descriptor for ear recognition. The proposed descriptor, namely, dense local phase quantization (DLPQ) is based on the phase responses, which is generated using the well-known LPQ descriptor. Furthermore, local dense histograms are extracted from the horizontal stripes of the phase maps followed by a pooling operation to address viewpoint changes and, finally, concatenated into an ear descriptor. Although the proposed DLPQ descriptor is built on the traditional LPQ, we particularly show that drastic improvements (of over 20%) are attained with respect to this latter descriptor on two benchmark data sets. Furthermore, the proposed descriptor stands out among recent ear descriptors from the literature.
An Analysis of the Optimum Node Density for Simultaneous Wireless Information and Power Transfer in Ad Hoc Networks

This paper investigates simultaneous wireless information and power transfer (SWIPT) in the ad hoc network, where access points (APs) with multiple antennas can transfer energy as well as information using a common spectrum resource. The receiving nodes decode the incoming information data (information decoding, ID) and/or harvest the RF energy (energy harvesting, EH), where two different receiving node architectures—time switching (TS) and power splitting (PS)—are considered. By using a stochastic geometry approach, we aim to analyze the transmission capacity and the harvested energy per unit area as performance measures of the SWIPT in the ad hoc network. From the analytical results, we can derive the optimal node densities of ID nodes and EH nodes for TS architectures and, furthermore, optimize the power splitting ratio jointly with the node density for the PS architectures such that the harvested energy per unit area is maximized when the target transmission capacity is given. The proposed node density optimization gives us a useful insight into the design of SWIPT-based ad hoc network, where we can show how densely the APs/nodes can be deployed in a given area and furthermore, find that the ad hoc network with PS receiving nodes outperforms that with TS receiving nodes for a large target transmission capacity, and vice versa.
cDNA cloning and functional characterisation of four antimicrobial peptides from Paa spinosa

Abstract Antimicrobial peptides (AMPs) are small peptides found in many organisms defending themselves against pathogens. AMPs form the first line of host defence against pathogenic infections and are key components of the innate immune system of amphibians. In the current study, cDNAs of precursors of four novel antimicrobial peptides in the skin of Paa spinosa were cloned and sequenced using the 3′-RACE technique. Mature peptides, named spinosan A–D, encoded by the cDNAs were chemically synthesized and their chemical properties were predicted. The antimicrobial, antioxidative, cyotoxic and haemolytic activities of these four AMPs were determined. While the synthesised spinosans A–C exhibited no activity towards any of the bacterial strains tested, spinosan-D exhibited weak but broad-spectrum antimicrobial activities against Gram-positive and Gram-negative bacteria. All peptides were weakly haemolytic towards rabbit erythrocytes, had a strong antioxidative activity, and a low cytotoxic activity against HeLa cells. These findings provide helpful insights that may be useful in the future design of anti-infective peptide agents.