Miracle-dz/UniFAR-FTUs huggingface dataset:
Design of Low-Inductance Switching Power Cell for GaN HEMT Based Inverter

In this paper, an ultralow inductance power cell is designed for a three-level active neutral point clamped (3L-ANPC) based on 650-V gallium nitride (GaN) high electron mobility transistor (HEMT) devices. The 3L-ANPC topology with GaN HEMT devices and the selected modulation scheme suitable for wide-bandgap devices are presented. The commutation loops, which mainly contribute to voltage overshoots and increase of switching losses, are discussed. The ultralow inductance power cell design based on a four-layer printed circuit board with the aim to maximize the switching performance of GaN HEMTs is explained. The design of gate drivers for the GaN HEMT devices is presented. Parasitic inductance and resistance of the proposed design are extracted with finite-element analysis and is discussed. Common-mode behaviors based on the simulation program with integrated circuit emphasis (SPICE) model of the converter are analyzed. Experimental results on the designed 3L-ANPC with output power of up to 1 kW are presented, which verifies the performance of the proposed design in terms of ultralow inductance.
Quantitative measurements of soft tissue structures using image-features in navigated endoscopy

Below we present a new method to obtain quantitative measurements in medical images of a tracked video endoscope. Such quantitative measurements can be critical biomarkers during endoscopic diagnosis, e.g. for the classification of tumors and polyps. Size-based classifications are often achieved by mere visual estimation which can be imprecise and subjective. To this day established systems of quantitative size measurement are restricted to specific anatomical structures and require additional tools next to the endoscope. We present a system of quantitative measurement during an endoscopic procedure based on a virtual model by utilizing methods from computer vision as well as structure from motion and combining those with an optical tracking system in a novel way. Our experiments show that quantitative measurements of anatomic structures can be reliably attained by our system with an accuracy which exceeds the reported accuracy of visual estimation.
Localization of Wireless Sensor Networks in the Wild: Pursuit of Ranging Quality

Localization is a fundamental issue of wireless sensor networks that has been extensively studied in the literature. Our real-world experience from GreenOrbs, a sensor network system deployed in a forest, shows that localization in the wild remains very challenging due to various interfering factors. In this paper, we propose CDL, a Combined and Differentiated Localization approach for localization that exploits the strength of range-free approaches and range-based approaches using received signal strength indicator (RSSI). A critical observation is that ranging quality greatly impacts the overall localization accuracy. To achieve a better ranging quality, our method CDL incorporates virtual-hop localization, local filtration, and ranging-quality aware calibration. We have implemented and evaluated CDL by extensive real-world experiments in GreenOrbs and large-scale simulations. Our experimental and simulation results demonstrate that CDL outperforms current state-of-art localization approaches with a more accurate and consistent performance. For example, the average location error using CDL in GreenOrbs system is 2.9 m, while the previous best method SISR has an average error of 4.6 m.
Analytic symbol error rate evaluation of M-PSK based regenerative cooperative networks over generalized fading channels

This paper is devoted to the analytic investigation of a maximum-ratio-combining based regenerative multi-relay cooperative wireless network over non-homogeneous scattering environments. Such propagation conditions are rather realistic as they are encountered often in practical wireless transmission scenarios. Novel analytic expressions are derived for the symbol-error-rate of M-ary phase shift keying (M-PSK) over independently and non-identically distributed fading channels. The derived expressions are based on the moment-generating-function (MGF) approach and are given in closed-form in terms of the generalized Lauricella series. A simple algorithm for computing this special function is also proposed while the offered results are validated extensively through comparisons with respective results from computer simulations. Based on this, they are particularly useful in the analytic performance evaluation of such cooperative systems. To this end, it is shown that the performance of the cooperative system is significantly affected, as expected, by the number of employed relays as well as by the value of the involved fading parameters η and μ.
Level-Set Methods for Tensor-Valued Images

Tensor-valued data are becoming more and more important as input for todays image analysis problems. This has been caused by a number of applications including diffusion tensor (DT-) MRI and physical measurements of anisotropic behaviour such as stress-strain relationships, interia and permittivity tensors. Consequently, there arises the need to filter and segment such tensor fields. In this paper we extend three important level set methods to tensor-valued data. To this end we first generalise Di Zenzo’s concept of a structure tensor for vector-valued images to tensor-valued data. This allows us to derive formulations of mean curvature motion and self-snakes in the case of tensor-valued images. We prove that these processes maintain positive semidefiniteness if the initial matrix data are positive semidefinite. Finally we present a geodesic active contour model for segmenting tensor fields. Since it incorporates information from all channels, it gives a contour representation that is highly robust under noise.
Hydroxyapatite Coating Prepared by Sol-gel Method on Stainless Steel Substrates

Hydroxyapatite (HA) coating was deposited onto 316L stainless steel substrates by sol-gel technique and repeating with drawing. The phase constitution, morphology, bonding strength and anticorrosion of the coating were characterized. The effects of annealing temperature on coating performances were investigated. The results show that the porous fine HA coating with poor crystallization is formed when annealing at 400 ～500 ℃, HA crystalline and interfacial bonding strength are improved by elevating annealing temperature. HA coating improves the anticorrosion capability of stainless steel.
Tumor suppressor candidate 3: A novel grading tool and predictor of clinical malignancy in human gliomas

For several years, the cause of autosomal recessive mental retardation has been attributed to the deletion or mutation of a gene named tumor suppressor candidate 3 (TUSC3). Previous research has identified that TUSC3 is a potential tumor suppressor gene in oral epidermoid carcinoma, lung cancer and esophageal cancer. However, to the best of our knowledge, no previously published data has existed on the expression of TUSC3 in gliomas. The present study focused on the expression of TUSC3 in brain gliomas. Additionally, the present study sought to identify he association between TUSC3 expression and the typical clinical and pathological disease manifestations of gliomas. TUSC3 levels were evaluated using a western blot assay and immunohistochemistry on tissue microarray slides. Results indicated a significant decrease in TUSC3 expression in glioma tissues compared with the normal adjacent tissues. Furthermore, TUSC3 expression and World Health Organization grade demonstrated an inverse association in patients with glioma. This revealed that lower levels of TUSC3 in gliomas may be associated with a poorly-differentiated (high grade) tumor and thus a higher malignancy. Through the combination of the results of the present study and future research projects, TUSC3 may be a novel grading tool that assists with evaluating tumor malignancy and consequently a more active therapeutic regimen may be used in patients with glioma.
Adaptive Unsupervised Feature Selection With Structure Regularization

Feature selection is one of the most important dimension reduction techniques for its efficiency and interpretation. Since practical data in large scale are usually collected without labels, and labeling these data are dramatically expensive and time-consuming, unsupervised feature selection has become a ubiquitous and challenging problem. Without label information, the fundamental problem of unsupervised feature selection lies in how to characterize the geometry structure of original feature space and produce a faithful feature subset, which preserves the intrinsic structure accurately. In this paper, we characterize the intrinsic local structure by an adaptive reconstruction graph and simultaneously consider its multiconnected-components (multicluster) structure by imposing a rank constraint on the corresponding Laplacian matrix. To achieve a desirable feature subset, we learn the optimal reconstruction graph and selective matrix simultaneously, instead of using a predetermined graph. We exploit an efficient alternative optimization algorithm to solve the proposed challenging problem, together with the theoretical analyses on its convergence and computational complexity. Finally, extensive experiments on clustering task are conducted over several benchmark data sets to verify the effectiveness and superiority of the proposed unsupervised feature selection algorithm.
Modeling the Role of Wnt Signaling in Human and Drosophila Stem Cells

The discovery of induced pluripotent stem (iPS) cells, barely more than a decade ago, dramatically transformed the study of stem cells and introduced a completely new way to approach many human health concerns. Although advances have pushed the field forward, human application remains some years away, in part due to the need for an in-depth mechanistic understanding. The role of Wnts in stem cells predates the discovery of iPS cells with Wnts established as major pluripotency promoting factors. Most work to date has been done using mouse and tissue culture models and few attempts have been made in other model organisms, but the recent combination of clustered regularly interspaced short palindromic repeats (CRISPR) gene editing with iPS cell technology provides a perfect avenue for exploring iPS cells in model organisms. Drosophila is an ideal organism for such studies, but fly iPS cells have not yet been made. In this opinion article, we draw parallels between Wnt signaling in human and Drosophila stem cell systems, propose ways to obtain Drosophila iPS cells, and suggest ways to exploit the versatility of the Drosophila system for future stem cell studies.
CrossNets: possible neuromorphic networks based on nanoscale components

Extremely dense neuromorphic networks may be based on hybrid 2D arrays of nanoscale components, including molecular latching switches working as adaptive synapses, nanowires as axons and dendrites, and nano‐CMOS circuits serving as neural cell bodies. Possible architectures include ‘free‐growing’ networks that may form topologies very close to those of cerebral cortex, and several species of distributed crossbar‐type networks, ‘CrossNets’ (including notably ‘InBar’ and ‘RandBar’), with better density and speed scaling. Numerical modelling show that the specific signal sign asymmetry used in CrossNets allows self‐excitation of recurrent networks with long‐range cell interaction, without a symmetry‐breaking global latchup. Our next goal is to develop methods of globally supervised teaching of extremely large networks with no external access to individual synapses. Such development would open a way towards cerebral‐cortex‐scale networks (with ∼1010 neural cells and ∼1014 synapses) capable of advanced information processing and self‐evolution at a speed several orders of magnitude higher than their biological prototypes. Copyright © 2003 John Wiley & Sons, Ltd.
A novel fast detection method of infrared LSS-Target in complex urban background

LSS-Target (the Low altitude, Slow speed and Small Target) is likely to be a threat to the observation platform, thus infrared LSS-Target detection is an urgent task. LSS-Target is a challenging issue due to the low Signal-to-Noise Ratio (SNR) and sophisticated background. Motivated by the analysis of infrared imaging characteristics, this paper proposes a novel fusion method for IR LSS-Target detection with complex urban background, which is suitable for precise guidance and self defense. First, an adaptive threshold segmentation based on accumulative histogram and maximum likelihood estimation are utilized to eliminate the clutter and improve SNR of the initial image. Second, a template is set up to identify the seed points in the image. Third, a constrained four criteria region growth algorithm is performed to separate the entire regions. Finally, the confidence measure is constructed, which can eliminate false targets and the background edges. Experimental results show that the method in this paper ca.
Ethernet over commercial lighting by a Visible Light Communication

A Visible Light Communication (VLC) system was realized upgrading, via minor external modifications, a commercial lamp including its own Phosphorescent Light Emitting Diode (PH-LED). The lamp now provides an Ethernet 10Base-T transmission over a Non-Directed Line-Of-Sight (NDLOS) link in an environment with strong background light (up to ∼3000 lx) and high tolerance to misalignment (up to 45 degrees). The system operation has been tested with packet loss measurements of randomly generated packets and with Bit Error Ratio (BER) measurements of an Ethernet-equivalent 12.5 Mbit/s transmission of a Manchester coded OOK signal over a distance of 1 m in NDLOS. The proposed technology has been implemented into a commercial lighting equipment without any relevant modification of the lamps.
Achievable Capacity Scaling Laws of Three-Dimensional Wireless Social Networks

With the development of aeronautical telecommunication and unmanned aerial vehicles (UAVs), wireless networks will be extended to three-dimensional (3-D) space. Besides, 3-D wireless networks have been widely deployed in battlefields, which consist of aircraft, UAVs, ground troops, and fleets. When nodes in these wireless networks form swarm and cooperate with each other, there will be social behavior among them and 3-D wireless social networks emerge. Although the study of wireless social networks has been initiated, the capacity of 3-D wireless social networks is unknown. In this paper, we derive the achievable capacity of 3-D wireless social networks. It shows that the capacity is a function of the pathloss exponent, the number of nodes, the social group concentration, the contact concentration, and the size of social group. When the social group concentration or the contact concentration exceeds a threshold, the wireless social network is scalable and the capacity of wireless social network is much larger than that of the wireless network without social behavior. Besides, we discover the existence of a singular point for social group concentration and contact concentration, where the network capacity skips to a larger value than the neighborhood. The results reveal the interplay between wireless communication and social connection in 3-D space, which brings an insight into the design of 3-D wireless networks.
Feasibility of Using Conductively Cooled Magnets in Cryomidules of Superconducting Linacs

As part of a search for optimal ways to configure cryomodules of the low-beta section of a high-current, high-power superconducting linac, an option of using conductively cooled superconducting focusing lenses was evaluated. Superconducting magnet was installed inside existing test cryostat, which was modified by adding current feed-throughs and two conductively cooled current leads. Each lead was equipped with heat sinks at the temperatures of liquid nitrogen and liquid helium. The magnet was mounted inside the cryostat on an individual heat sink plate, and thermometers were installed on the leads, heat sinks, and on the magnet. In this report we provide some details of the test setup and analyse results of the temperature measurements.
Genetic and environmental influences on the relationship between ADHD symptoms and internalizing problems: A Chinese twin study

Several twin studies have investigated the overlap between attention deficit hyperactivity disorder (ADHD) and externalizing problems; however, limited information is known regarding the genetic and environmental contribution to the overlap between ADHD and internalizing problems. This study examined the genetic and environmental influences on the variation in and covariation between ADHD symptoms and internalizing problems by using the Child Behavior Checklist (CBCL). We investigated 1,316 child and adolescent twins, including 780 monozygotic twins and 536 dizygotic twins, aged 6 years to 18 years from the Chinese Child and Adolescent Twin Registry. ADHD symptoms and internalizing problems were quantified through parent rating by using the Attention Problems Scale and other three scales, which include Anxious/Depressed, Withdrawn, and Somatic Complaints of CBCL. Genetic and environmental susceptibilities common to ADHD symptoms and internalizing problems were examined through bivariate twin modeling. Results showed that genetic factors substantially influenced the ADHD symptoms with a heritability of 72%. Modest genetic influences and substantial shared environmental influences (20–77%) were observed in the three internalizing problem scales. Common genetic and shared environmental influences were essential for the overlap between ADHD and the three internalizing problems respectively. Approximately one‐fifth of the genetic variance of ADHD symptoms was shared with anxiety/depression. In conclusion, substantial genetic and shared environmental influences on ADHD symptoms and internalizing problems were observed in Chinese children and adolescents. Our finding supports a common etiology between ADHD and internalizing problems. This finding can also help explain the co‐existence of these behavior problems. © 2015 Wiley Periodicals, Inc.
Association between fish consumption and risk of dementia: a new study from China and a systematic literature review and meta-analysis

Abstract Objective To assess the association of fish consumption with risk of dementia and its dose–response relationship, and investigate variations in the association among low-, middle- and high-income countries. Design A new community-based cross-sectional study and a systematic literature review. Settings Urban and rural communities in China; population-based studies systematically searched from worldwide literature. Subjects Chinese adults aged ≥60 years in six provinces (n 6981) took part in a household health survey of dementia prevalence and risk factors. In addition, 33 964 participants from eleven published and eligible studies were included in the systematic review and meta-analysis. Results In the new study in China, 326 participants were diagnosed with dementia (4·7 %); those who consumed any amount of fish in the past two years v. those who consumed no fish had reduced risk of dementia (adjusted OR=0·73, 95 % CI 0·64, 0·99), but the dose–response relationship was not statistically significant. The meta-analysis of available data from the literature and the new study showed relative risk (RR) of dementia of 0·80 (95 % CI 0·74, 0·87) for people with fish consumption; the impact was similar among countries with different levels of income. Pooled dose–response data revealed RR (95 % CI) of 0·84 (0·72, 0·98), 0·78 (0·68, 0·90) and 0·77 (0·61, 0·98) in people with low, middle and high consumption of fish, respectively. Corresponding figures for Alzheimer’s disease were 0·88 (0·74, 1·04), 0·79 (0·65, 0·96) and 0·67 (0·58, 0·78), respectively. Conclusions Greater consumption of fish is associated with a lower risk of dementia. Increasing fish consumption may help prevent dementia worldwide regardless of income level.
The Effect of Technological Conditions of Hard Turning on the Formation of White Layer

In fast spreading hard turning occasionally a so-called white layer appears on the machined surface, which is mostly harmful. The formation of white layers and their composition, structure and thickness were investigated in the turning of the inner cylindrical surface of gear wheels made from 20MnCr5 case hardened steel, in order to identify to what extent the technological parameters of turning influence the white layer formation. On the basis of the measurement results it was possible to include border-line technological conditions in an empirical formula with which white layer formation can be avoided.
Herbivory in Spiders: The Importance of Pollen for Orb-Weavers

Orb-weaving spiders (Araneidae) are commonly regarded as generalist insect predators but resources provided by plants such as pollen may be an important dietary supplementation. Their webs snare insect prey, but can also trap aerial plankton like pollen and fungal spores. When recycling their orb webs, the spiders may therefore also feed on adhering pollen grains or fungal spores via extraoral digestion. In this study we measured stable isotope ratios in the bodies of two araneid species (Aculepeira ceropegia and Araneus diadematus), their potential prey and pollen to determine the relative contribution of pollen to their diet. We found that about 25% of juvenile orb-weaving spiders’ diet consisted of pollen, the other 75% of flying insects, mainly small dipterans and hymenopterans. The pollen grains in our study were too large to be taken up accidentally by the spiders and had first to be digested extraorally by enzymes in an active act of consumption. Therefore, pollen can be seen as a substantial component of the spiders’ diet. This finding suggests that these spiders need to be classified as omnivores rather than pure carnivores.
Gravitational and Barrier Effects in D-Dimensional Invasion Percolation Reservoir Models

The invasion percolation (IP) model continues to find uses in simulating reservoir engineering phenomena. Gravitational buoyancy and barrier effects can be introduced into a simulation model and studied statistically in two, three and higher dimensions. The changes in the fractions of injected material and phase transitional behaviours are studied. Analysis is made of both trapping and non-trapping invasion percolation processes alongwith changes in the trapped defender (hydrocarbon) within the reservoir when mud/oil buoyancy effects are varied. The effect of combinations of non-compressible defender trapping and non-porous barriers are explored with the barrier shown to have a more marked effect on the model than trapping. A number of useful metrics for the new gravitational invasion percolation (GIP) model are described in the context of hydrocarbon extraction. Simulation approaches and interpretations for CO2 deposition applications are also discussed.