Miracle-dz/UniFAR-FTUs huggingface dataset:
The Multiscale Bowler-Hat Transform for Vessel Enhancement in 3D Biomedical Images

Enhancement and detection of 3D vessel-like structures has long been an open problem as most existing image processing methods fail in many aspects, including a lack of uniform enhancement between vessels of different radii and a lack of enhancement at the junctions. Here, we propose a method based on mathematical morphology to enhance 3D vessel-like structures in biomedical images. The proposed method, 3D bowler-hat transform, combines sphere and line structuring elements to enhance vessel-like structures. The proposed method is validated on synthetic and real data and compared with state-of-the-art methods. Our results show that the proposed method achieves a high-quality vessel-like structures enhancement in both synthetic and real biomedical images, and is able to cope with variations in vessels thickness throughout vascular networks while remaining robust at junctions.
OMPRESSION BY THE SIGNS : DISTRIBUTED LEARNING IS A TWO-WAY STREET

Training large neural networks requires distributing learning over multiple workers. The rate limiting step is often in sending gradients from workers to parameter server and back again. We present SIGNSGD with majority vote: the first gradient compression scheme to achieve 1-bit compression of worker-server communication in both directions with non-vacuous theoretical guarantees. To achieve this, we build an extensive theory of sign-based optimisation, which is also relevant to understanding adaptive gradient methods like ADAM and RMSPROP. We prove that SIGNSGD can get the best of both worlds: compressed gradients and SGDlevel convergence rate. SIGNSGD can exploit mismatches between `1 and `2 geometry: when noise and curvature are much sparser than the gradients, SIGNSGD is expected to converge at the same rate or faster than full-precision SGD. Measurements of the `1 versus `2 geometry of real networks support our theoretical claims, and we find that the momentum counterpart of SIGNSGD is able to match the accuracy and convergence speed of ADAM on deep Imagenet models.
Identification, Estimation and Approximation of Risk under Interventions that Depend on the Natural Value of Treatment Using Observational Data

Abstract Robins et al. (2004, Comparative Quantification of Health Risks: Global and Regional Burden of Disease Attributable to Selected Major Risk Factors. Geneva: World Health Organization) introduced the extended g-formula to estimate from observational data the risk of failure under hypothetical interventions wherein a subject’s treatment at time k is assigned based on the natural value of treatment at k; that is, the value of treatment that would have been observed at k were the intervention discontinued right before k. Several authors have parametrically applied the extended g-formula to estimate long-term failure risk under hypothetical interventions on time-varying behaviors in observational studies. For example, Taubman et al. (2009, Intervening on risk factors for coronary heart disease: an application of the parametric g-formula. International Journal of Epidemiology, 380(6):1599–1611) used this approach to estimate the 20-year risk of coronary heart disease in the Nurses’ Health Study under the hypothetical intervention “If a subject’s natural value of exercise by the end of day k is less than 30 minutes, set her exercise on day k to exactly 30 minutes; otherwise, do not intervene on her on that day”. Non-parametrically, the extended g-formula differs from the (non-extended) g-formula of Robins (1986, A new approach to causal inference in mortality studies with a sustained exposure period: application to the healthy worker survivor effect. Mathematical Modelling, 7:1393–1512) in that it is a function of (i) a user-specified intervention depending on the natural value of treatment and (ii) the distribution of natural treatment itself. Richardson and Robins (2013, http://www.csss.washington.edu/Papers/) recently defined a sufficient condition such that the extended g-formula may identify risk under an intervention that depends on the natural value of treatment, provided this expression is well-defined. In this paper, we complement this result by showing that the extended g-formula associated with an intervention depending on the natural value of treatment is algebraically equivalent to the (non-extended) g-formula associated with a particular random dynamic regime that does not depend on this value. Using previous results for random dynamic regimes, we show that this equivalence immediately gives a sufficient positivity condition that guarantees the extended g-formula is well-defined as well as semi-parametric alternatives to the parametric extended g-formula for estimation. Finally, given a hypothetical intervention that depends on the natural value of treatment, we define a plausible (implementable) approximation to this hypothetical intervention along with an untestable assumption that gives exact equivalence.
Number : WUCSE-2003-42 2003-0519 Towards a Packet Classification Benchmark

Packet classification is the enabling technology for next generation network services and often the primary bottleneck in high-performance routers. Due to the importance and complexity of the problem, a myriad of algorithms and resulting implementations exist. The performance and capacity of many algorithms and classification devices, including TCAMs, depend upon properties of the filter set and query patterns. Unlike microprocessors in the field of computer architecture, there are no standard performance evaluation tools or techniques available to evaluate packet classification algorithms and products. Network service providers are reluctant to distribute copies of real filter databases for security and confidentiality reasons, hence realistic test vectors are a scarce commodity. The small subset of the research community who obtain real databases either limit performance evaluation to the small sample space or employ ad hoc methods of modifying those databases. We present a tool for creating synthetic filter databases that retain characteristics of a seed database and provide systematic mechanisms for varying the number and composition of the filters. We propose a benchmarking methodology based on this tool that provides a mechanism for evaluating packet classification performance on a uniform scale. We seek to initiate a broader discussion within the community that will result in a standard packet classification benchmark.
Efficient octilinear steiner tree construction based on spanning graphs

0ctilinear interconnect is a promising technique to shorten wire lengths. We present two practical heuristic octilinear Steiner tree (OSMT) algorithms in the paper. They are both based on octilinear spanning graphs. The one by edge substitution (OST-E) has a worst case running time of O(nlogn) and similar performance as the batched greedy algorithm[9]. The other one by triangle contraction (OST-T) has a small increase in running time and better performance. Experiments on both industry and random test cases are conducted.
Sevoflurane Inhibits Unstimulated and Agonist-induced Platelet Antigen Expression and Platelet Function in Whole Blood In Vitro

Background Previous studies have reported conflicting results about the effect of sevoflurane on platelet aggregation. To clarify this point, we investigated the effects of sevoflurane on platelet antigen expression and function in vitro. Methods Human whole blood was incubated for 1 h with 0.5 and 1 minimum alveolar concentration sevoflurane, 21% O2, and 5% CO2. A control sample was kept at the same conditions without sevoflurane. After stimulation with adenosine diphosphate or thrombin receptor agonist peptide 6, samples were stained with fluorochrome conjugated antibodies, and the expression of platelet glycoproteins GPIIb/IIIa, GPIb, and P-selectin, as well as activated GPIIb/IIIa, were measured with two-color flow cytometry. In addition, platelet function was assessed by means of thromboelastography and using the platelet function analyzer 100. Results Already in subanesthetic concentrations, sevoflurane inhibits unstimulated and agonist-induced GPIIb/IIIa surface expression and activated GPIIb/IIIa expression on platelets in whole blood. The agonist-induced redistribution of GPIb into the open canalicular system was also impaired by sevoflurane, whereas no effect on P-selectin expression in activated platelets could be found. Sevoflurane significantly reduced the maximum thromboelastographic amplitude. Furthermore, platelet function analyzer 100 closure times were significantly prolonged. Conclusion The results show that sevoflurane significantly impairs platelet antigen expression in vitro. It is especially the inhibition of GPIIb/IIIa expression and activation that impairs bleeding time as reflected in thromboelastographic measurements and platelet function analyzer 100 closure times. The exact inhibitory mechanism remains unclear.
SISI: A New Device for In Situ Incubations at the Ocean Surface

The sea-surface microlayer (SML) forms the uppermost boundary layer between atmosphere and ocean, and has distinctive physico-chemical and biological features compared to the underlying water. First findings on metabolic contributions of microorganisms to gas exchange processes across the SML raised the need for new in situ technologies to explore plankton-oxygen turnover in this special habitat. Here, we describe an inexpensive research tool, the Surface In Situ Incubator (SISI), which allows simultaneous incubations of the SML, and water samples from 1 m and 5 m, at the respective depths of origin. The SISI is deployed from a small boat, seaworthy up to 5 bft (Beaufort scale), and due to global positioning system (GPS) tracking, capable of drifting freely for hours or days. We tested the SISI by applying light/dark bottle incubations in the Baltic Sea and the tropical Pacific Ocean under various conditions to present first data on planktonic oxygen turnover rates within the SML, and two subsurface depths. The SISI offers the potential to study plankton-oxygen turnover within the SML under the natural influence of abiotic parameters, and hence, is a valuable tool to routinely monitor their physiological role in biogeochemical cycling and gas exchange processes at, and near, the sea surface.
Making “fetch” happen: The influence of social and linguistic context on nonstandard word growth and decline

In an online community, new words come and go: today’s “haha” may be replaced by tomorrow’s “lol. ” Changes in online writing are usually studied as a social process, with innovations diffusing through a network of individuals in a speech community. But unlike other types of innovation, language change is shaped and constrained by the grammatical system in which it takes part. To investigate the role of social and structural factors in language change, we undertake a large-scale analysis of the frequencies of non-standard words in Reddit. Dissemination across many linguistic contexts is a predictor of success: words that appear in more linguistic contexts grow faster and survive longer. Furthermore, social dissemination plays a less important role in explaining word growth and decline than previously hypothesized.
Research on the analytic factor neuron model based on cloud generator and its application in oil&gas SCADA security defense

This paper puts forward an analytic factor neuron model which combines reasoning machine based on the cloud generator with the Factors Neural Network theory. The factor neuron model is realized based on mobile intelligent agent and malicious behavior perception technology. Therefore, it, compared with the traditional security defense technology, has strong flexibility, mobility, scalability and other features. At the same time, the model has a cross-platform characteristics and distributed characteristics, which is suitable for the demand of the SCADA system security defense. This paper builds a neural network with a group of neurons model. By configuring each factor neuron model in the neural network, the safety of SCADA system can be protected effectively.
Essential thrombocythaemia

Introduction In normal health, the bone marrow makes different kinds of blood cells to keep us healthy. It makes white cells to fight infection, red cells to carry oxygen around the body and platelets to help our blood clot if we are injured. The myeloproliferative neoplasms (MPN) are blood disorders where too many blood cells are produced (Figure 1). Essential thrombocythaemia (ET) is an MPN where too many platelets are made (Figure 2). It is called ‘essential’ to indicate that is a primary bone marrow disorder and not secondary to another problem. It is a rare disorder occurring in around 2 per 100 000 people and is more common in those over 60 years old. In a few patients, it can progress to more serious problems such as myelofibrosis where the bone marrow becomes scarred and its normal function severely impaired, or develop into a form of leukaemia.
"Voxelization" in 3D Searching- A Study

of engineering design is increasing exponentially in order to reduce the conceptual designing phase time due to rapid increase in technology. This leads to increase in frequent retrieval of the 3D models through web searching mechanism. So, it becomes a necessary challenge to design a 3D search engine which can search 3D models accurately as well as efficiently. The 3D searching is a technique developed to help the web users for extracting 3D models like complex engineering parts, various purpose graphical models, etc. The search engine takes input in the form of queries like text, 2D sketches, 3D sketches, 3Dmodel, 2Dmodel etc. When input queries is matched with the existing model in the database or similar model that are present in the database, the best multiple result is provided to user. This paper describes the basics of query by sketch which takes input by sketching manually with the aid of user interface. This input is normalized and further processed by Voxelization, Skeltonization and create Skeletal graph which is then mapped to database to extract best possible match. However, the main focus of this paper is to discuss the process of Voxelization method in very simple steps, as it plays a very important aspect in 3D searching.
Glucose transporter deficiency syndrome (GLUT1DS) and the ketogenic diet

Glucose transporter type 1 (GLUT1) deficiency syndrome (GLUT1DS, OMIM 606777) is caused by impaired glucose transport into brain mediated by GLUT1, the glucose transporter at the blood–brain barrier. The condition is diagnosed by hypoglycorrhachia, impaired glucose uptake into erythrocytes, and heterozygous mutations in the SLC2A1 gene (OMIM 138140, gene map locus 1p35‐31.3). Patients present with early‐onset epilepsy, developmental delay, and a complex movement disorder. The phenotype is highly variable and several atypical variants have been described. The ketogenic diet (KD) provides ketones as an alternative fuel to the brain. Calculation, administration, supplements, and adverse effects of the KD in GLUT1DS do not differ from patients treated for intractable childhood epilepsy. In GLUT1DS, the KD should be introduced early to meet the energy demands of the developing brain and should be maintained into puberty. Seizures are effectively controlled, but the effects on neurodevelopment and on the movement disorder are less impressive. The KD remains the treatment of choice for GLUT1DS, but recent insights into anticonvulsive diet mechanisms, animal models for GLUT1DS, and the development of alternative KDs provide new opportunities to improve the treatment of this condition.
Pattern based procedural textures

Numerous real-time applications such computer games or flight simulators require non-repetitive high-resolution texturing on large landscapes. We propose an algorithm which procedurally determines the texture value at any surface location by aperiodically combining provided patterns according to user-defined controls such as a probability distribution (possibly non stationary). Our algorithm can be implemented on programmable hardware by taking advantage of the texture indirection ability of recent graphics boards. We use explicit and virtual indirection tables to determine the pattern to apply at each pixel as well as its attributes (displacement, scaling, time.). This provides the programmer with a very high resolution virtual texture with nice properties: Low memory consumption, no periodicity, control of the statistics, numerous control parameters (which can be edited on the fly). Our representation consists of building blocks that we combine in order to illustrate various convenient texture modalities such as aperiodic tiling, sparse convolution, domain transitions and animated textures.
Detecting Aβ deposition and RPE cell senescence in the retinas of SAMP8 mice.

AIM Our previous study indicated that Aβ-induced Retinal Pigment Epithelial (RPE) cell senescence may be associated with chronic inflammation in age-related macular degeneration (AMD). The present study was designed to explore whether Aβ deposition and RPE senescence could be found in the senescence-prone mouse strain 8 (SAMP8), which is an animal model for AMD. METHODS Eyes of both SAMP8 and age-matched SAMR1 (SAM resistant) mice were examined in vivo by fundus photography and electroretinography (ERG). Retinal morphological features were assessed using light and electron microscopy. Aβ deposition and p16-positive senescent RPE cells were traced using immunofluorescence labeling. P16 expression was detected using western blot. Expressions of IL-6 and IL-8 in RPE/choroid were analyzed using RT-PCR. RESULTS In fundus of SAMP8, age-dependent increase of drusen-like lesions and the increase of granular autofluorescent spots were respectively detected using IR (near-infrared) and AF (autofluorescence) imaging of confocal scanning laser ophthalmoscope. The amplitude of the ERGs declined with age in SAMP8 and these changes were paralleled with the significant changes in retinal morphological features examined by funduscopy. Histopathological analysis found significant loss of photoreceptor outer segments (OS) and abnormal localization of RPE cells in aged SAMP8 mice. Degenerative changes in RPE cells of aged SAMP8 mice, including massive vacuoles, thickened Bruch's membrane (BrM), and loss of basal infoldings were further confirmed by electron microscopy. Increased Aβ deposits in OS layer and p16-positive senescent RPE cells were observed using immunofluorescence microscopy. Western blot confirmed that P16 expression was significantly increased in RPE cells of aged SAMP8 mice. Expressions of proinflammatory IL-6 and IL-8 were significantly upregulated in RPE/choroid of aged SAMP8 mice. CONCLUSIONS Our results showed that aged SAMP8 mice developed ocular pathology similar to some features of human AMD. In this AMD mouse model, Aβ deposition and RPE senescence may be associated with AMD development, and RPE senescence is likely a mechanistic link between Aβ deposition and inflammation.
Optical coherence tomography for glaucoma diagnosis: An evidence based meta-analysis

Purpose Early detection, monitoring and understanding of changes in the retina are central to the diagnosis of glaucomatous optic neuropathy, and vital to reduce visual loss from this progressive condition. The main objective of this investigation was to compare glaucoma diagnostic accuracy of commercially available optical coherence tomography (OCT) devices (Zeiss Stratus, Zeiss Cirrus, Heidelberg Spectralis and Optovue RTVue, and Topcon 3D-OCT). Patients 16,104 glaucomatous and 11,543 normal eyes reported in 150 studies. Methods Between Jan. 2017 and Feb 2017, MEDLINE®, EMBASE®, CINAHL®, Cochrane Library®, Web of Science®, and BIOSIS® were searched for studies assessing glaucoma diagnostic accuracy of the aforementioned OCT devices. Meta-analysis was performed pooling area under the receiver operating characteristic curve (AUROC) estimates for all devices, stratified by OCT type (RNFL, macula), and area imaged. Results 150 studies with 16,104 glaucomatous and 11,543 normal control eyes were included. Key findings: AUROC of glaucoma diagnosis for RNFL average for all glaucoma patients was 0.897 (0.887–0.906, n = 16,782 patient eyes), for macula ganglion cell complex (GCC) was 0.885 (0.869–0.901, n = 4841 eyes), for macula ganglion cell inner plexiform layer (GCIPL) was 0.858 (0.835–0.880, n = 4211 eyes), and for total macular thickness was 0.795 (0.754–0.834, n = 1063 eyes). Conclusion The classification capability was similar across all 5 OCT devices. More diagnostically favorable AUROCs were demonstrated in patients with increased glaucoma severity. Diagnostic accuracy of RNFL and segmented macular regions (GCIPL, GCC) scans were similar and higher than total macular thickness. This study provides a synthesis of contemporary evidence with features of robust inclusion criteria and large sample size. These findings may provide guidance to clinicians when navigating this rapidly evolving diagnostic area characterized by numerous options.
High Resolution Turntable Radar Imaging via Two Dimensional Deconvolution with Matrix Completion

Resolution is the bottleneck for the application of radar imaging, which is limited by the bandwidth for the range dimension and synthetic aperture for the cross-range dimension. The demand for high azimuth resolution inevitably results in a large amount of cross-range samplings, which always need a large number of transmit-receive channels or a long observation time. Compressive sensing (CS)-based methods could be used to reduce the samples, but suffer from the difficulty of designing the measurement matrix, and they are not robust enough in practical application. In this paper, based on the two-dimensional (2D) convolution model of the echo after matched filter (MF), we propose a novel 2D deconvolution algorithm for turntable radar to improve the radar imaging resolution. Additionally, in order to reduce the cross-range samples, we introduce a new matrix completion (MC) algorithm based on the hyperbolic tangent constraint to improve the performance of MC with undersampled data. Besides, we present a new way of echo matrix reconstruction for the situation that only partial cross-range data are observed and some columns of the echo matrix are missing. The new matrix has a better low rank property and needs just one operation of MC for all of the missing elements compared to the existing ways. Numerical simulations and experiments are carried out to demonstrate the effectiveness of the proposed method.
Joining technologies for a temperature-stable integration of a LTCC-based pressure sensor

Abstract. Besides the well-known application as circuit boards and housings, multilayer low-temperature co-fired ceramics (LTCC) offer a flexible and temperature-stable platform for the development of complex sensor elements. Commercial LTCC qualities are usually available with a matching set of metallization pastes which allow the integration of various electrical functions. However, for the integration of ceramic sensor elements based on LTCC into standardized steel housings it is necessary to compensate the mismatching thermal expansion behaviour. Therefore balancing elements made of Kovar® (Fe–29 wt% Ni–17 wt% Co) and alumina ceramic (Al2O3) can be used. These components have to be joined hermetically to each other and to the LTCC sensors. In this study, brazing experiments were performed for combinations of Kovar–Al2O3 and Kovar–LTCC with Ag–Cu–Ti- and Ag–Cu–In–Ti-based commercial braze filler metals, Cusil-ABA® and Incusil®-ABA, respectively. For both active braze filler metals, optimized processing parameters were investigated to realize hermetic Kovar–Al2O3 and Kovar–LTCC joints.