Miracle-dz/UniFAR-FTUs huggingface dataset:
Inner–Outer Support Set Pursuit for Distributed Compressed Sensing

We address the distributed compressed sensing problem of reconstructing a sequence of jointly sparse signals under the condition of an inaccurate and insufficient estimate of the common support set. Correlations between the jointly sparse signals are modeled by the joint sparsity model 1 (JSM-1). We propose a novel algorithm, namely inner–outer support set pursuit (IOSSP), which removes the impact of the estimated common support set, to reduce the computing time as well as the reconstruction error. The IOSSP algorithm divides the support set of each individual sparse signal into two disjoint sets: an inner support set and an outer support set. Two separate procedures, the outer support set pursuit and inner support set pursuit, are then utilized to estimate the outer and inner support sets. We provide the convergence performance of the IOSSP algorithm in both the noiseless and noisy conditions. For the noiseless case, we derive the condition on the estimated common support set, which guarantees an exact reconstruction. For the noisy case, a bound of the reconstruction error is provided, and the derivation process is inspired by the compressive sampling matching pursuit algorithm. The experimental and simulation results demonstrate that the proposed IOSSP algorithm is superior on reconstruction error and computing time over the conventional algorithms for JSM-1, e.g., the parallel pursuit with side information and joint recovery strategy algorithms.
Borrelia burgdorferi Regulates Expression of Complement Regulator-Acquiring Surface Protein 1 during the Mammal-Tick Infection Cycle

ABSTRACT During the natural mammal-tick infection cycle, the Lyme disease spirochete Borrelia burgdorferi comes into contact with components of the alternative complement pathway. B. burgdorferi, like many other human pathogens, has evolved the immune evasion strategy of binding two host-derived fluid-phase regulators of complement, factor H and factor H-like protein 1 (FHL-1). The borrelial complement regulator-acquiring surface protein 1 (CRASP-1) is a surface-exposed lipoprotein that binds both factor H and FHL-1. Analysis of CRASP-1 expression during the mammal-tick infectious cycle indicated that B. burgdorferi expresses this protein during mammalian infection, supporting the hypothesized role for CRASP-1 in immune evasion. However, CRASP-1 synthesis was repressed in bacteria during colonization of vector ticks. Analysis of cultured bacteria indicated that CRASP-1 is differentially expressed in response to changes in pH. Comparisons of CRASP-1 expression patterns with those of other infection-associated B. burgdorferi proteins, including the OspC, OspA, and Erp proteins, indicated that each protein is regulated through a unique mechanism.
On Digitization of Romanian Cyrillic Printings of the 17th-18th Centuries

The paper describes in details recognition of Romanian texts of the 17th–18th centuries printed in the Cyrillic script, and their conversion to the modern Latin script. The challenges are discussed, and solutions of problems are proposed. The elaborated technology and a tool pack include historical alphabets, sets of recognition patterns, and spelling dictionaries in the corresponding orthographies for ABBYY Finereader. In addition, virtual keyboards, fonts, a transliteration utility, and the user manual were developed. This permits successful recognition of old Romanian texts in the Cyrillic script. Transliteration to the Latin script grants no-barrier access to historical documents.
Dense 3D Models From a Single RGB-D View

ANTTI POHJOLA: Dense 3D Models From a Single RGB-D View Tampere University of Technology Master of Science Thesis, 54 pages January 2016 Master's Degree Programme in Information Technology Major: Software Engineering Examiners: Professor Joni-Kristian Kämäräinen and Professor Tommi Mikkonen
Discrete optimization for error feedback network using lower bound estimation

We propose a new design method for error feedback (EF) with discrete coefficients. The lower bound estimation principle is used in order to search for the optimum solution and the EF networks designed by the proposed method have guaranteed optimality. Additionally, the method can reduce the calculation cost because we can cut the sub-trees based on the lower bound estimation. Finally, we present a numerical example by designing the (3, 3)th order EF with discrete coefficients whose decimal parts are 2 bits. From the results, we demonstrate the effectiveness of the proposed method and show that the calculation time is a few seconds.
Emphasizing 3D Properties in Recurrent Multi-View Aggregation for 3D Shape Retrieval

Multi-view based shape descriptors have achieved impressive performance for 3D shape retrieval. The core of view-based methods is to interpret 3D structures through 2D observations. However, most existing methods pay more attention to discriminative models and none of them necessarily incorporate the 3D properties of the objects. To resolve this problem, we propose an encoder-decoder recurrent feature aggregation network (ERFA-Net) to emphasize the 3D properties of 3D shapes in multi-view features aggregation. In our network, a view sequence of the shape is trained to encode a discriminative shape embedding and estimate unseen rendered views of any viewpoints. This generation task gives an effective supervision which makes the network exploit 3D properties of shapes through various 2D images. During feature aggregation, a discriminative feature representation across multiple views is effectively exploited based on LSTM network. The proposed 3D representation has following advantages against other state-of-the-art: 1) it performs robust discrimination under the existence of noise such as view missing and occlusion, because of the improvement brought by 3D properties. 2) it has strong generative capabilities, which is useful for various 3D shape tasks. We evaluate ERFA-Net on two popular 3D shape datasets, ModelNet and ShapeNetCore55, and ERFA-Net outperforms the state-of-the-art methods significantly. Extensive experiments show the effectiveness and robustness of the proposed 3D representation.
Value Creation Using Clouds: Analysis of Value Drivers for Start-Ups and Small and Medium Sized Enterprises in the Textile Industry

Cloud Computing is increasingly emerging in support of the acronym "Anything as a Service" (XaaS). Whereas its benefits have been delineated frequently in the literature, no model has yet attempted to show how such applications are able to leverage business value in practice. The paper presents a systematic analysis of value drivers and leverages of clouds with emphasis on start-ups and SMEs, both in B2B and B2C markets, a case study on the textile and apparel industry pinpoints how various aspects and characteristics of cloud computing can be at the roots of successful value creation and hence, increased competitiveness.
Partial Occlusion During Resistance Exercise Alters Effort Sense and Pain

Hollander, DB, Reeves, GV, Clavier, JD, Francois, MR, Thomas, C, and Kraemer, RR. Partial occlusion during resistance exercise alters effort sense and pain. J Strength Cond Res 24(1): 235-243, 2010-The purpose of the study was to determine how manipulation of peripheral blood flow during resistance exercise using a light load affected perception and physiological measures compared with moderate load resistance exercise and a control trial. Seven subjects performed a 3 (session) by 2 (biceps curls and calf extensions) within-subjects study that was randomized and counterbalanced across 3 weeks. The 3 sessions included (a) light resistance exercise (3 sets to failure) at 30% of 1 repetition maximum (1RM) with partial occlusion (LRO), (b) moderate resistance at 70% of 1RM with no occlusion (MR), and (c) partial occlusion without exercise (OO). Ratings of perceived exertion (RPE), pain, and heart rate were assessed immediately after each set, whereas blood samples were taken before, immediately after, and 15 minutes after exercise. Results demonstrated that RPE and pain were lower in the OO condition than that in the MR and LRO conditions for biceps curls and calf extensions, Fs(2,24) = 22.75, 20.86, ps < 0.0001 and Fs(2,24) = 18.95, 24.52, ps < 0.01; however, no significant differences were noted between MR and LRO conditions. Heart rate was significantly higher for the LRO condition when compared with the MR trial, F(2,18) 20.12, p < 0.001. Results suggest that when partial vascular occlusion with a light load was applied, both pain and effort sense were altered to a similar degree as moderate loads but no occlusion. The practical application of results were that individuals may be better able to tolerate perceptual change at low loads with partial occlusion because joint stress may be minimized while local muscle metabolic demands increase, making resistance training maximally effective and minimally stressful on joints. Perceptual tracking of effort and pain may aid coaches who attempt this protocol.
A Novel Quantum-Behaved Bat Algorithm with Mean Best Position Directed for Numerical Optimization

This paper proposes a novel quantum-behaved bat algorithm with the direction of mean best position (QMBA). In QMBA, the position of each bat is mainly updated by the current optimal solution in the early stage of searching and in the late search it also depends on the mean best position which can enhance the convergence speed of the algorithm. During the process of searching, quantum behavior of bats is introduced which is beneficial to jump out of local optimal solution and make the quantum-behaved bats not easily fall into local optimal solution, and it has better ability to adapt complex environment. Meanwhile, QMBA makes good use of statistical information of best position which bats had experienced to generate better quality solutions. This approach not only inherits the characteristic of quick convergence, simplicity, and easy implementation of original bat algorithm, but also increases the diversity of population and improves the accuracy of solution. Twenty-four benchmark test functions are tested and compared with other variant bat algorithms for numerical optimization the simulation results show that this approach is simple and efficient and can achieve a more accurate solution.
On Stochastic Mortality Modeling

In the last decennium a vast literature on stochastic mortality models has been developed. All well-known models have nice features but also disadvantages. In this paper a stochastic mortality model is proposed that aims at combining the nice features from the existing models, while eliminating the disadvantages. More specifically, the model fits historical data very well, is applicable to a full age range, captures the cohort effect, has a non-trivial (but not too complex) correlation structure and has no robustness problems, while the structure of the model remains relatively simple. Also, the paper describes how to incorporate parameter uncertainty in the model. Furthermore, a risk neutral version of the model is given, that can be used for pricing.
Scavenging for Energy: A Rectenna Design for Wireless Energy Harvesting in UHF Mobile Telephony Bands

The development of distributed and ubiquitous electronic devices is an achievement of modern technology that has the potential to revolutionize many aspects of human life. Such electronic devices are being employed not only in consumer areas like home automation, intelligent transportation systems, and personal entertainment but also for health-care applications, such as noninvasive biomedical parameter monitoring, as well as industrial and military applications. A novel WEH for commercial telephony frequencies in the UHF band has been presented. The system, being based on a broadband slot antenna and a thin flexible substrate, weighs fewer than 15 g, which is far below the competition requirements and makes the harvester particularly appealing for realistic scenarios. Thanks to the proper design of the rectifier and the matching network, an excellent performance has been verified over the whole band, with a rectenna conversion efficiency of up to 60% and an EFoM equal to 37.6 dB for 2 μW/cm2 of incident power density.
Predicting Short- and Long-Term Vocabulary Learning via Semantic Features of Partial Word Knowledge

We show how the novel use of a semantic representation based on Osgood’s semantic diﬀerential scales can lead to eﬀective features in predicting short-and long-term learning in students using a vocabulary learning system. Previous studies in students’ intermediate knowledge states during vocabulary acquisition did not provide much information on which semantic knowledge students gained during word learning practice. Moreover, these studies relied on human ratings to evaluate the students’ responses. To solve this problem, we propose a semantic representation for words based on Osgood’s semantic decomposition of vocabulary [16]. To demonstrate our method can eﬀectively represent students’ knowledge in vocabulary acquisition, we build models for predicting the student’s short-term vocabulary acquisition and long-term retention. We compare the eﬀectiveness of our Osgood-based semantic representation to that provided by Word2Vec neural word embedding [13], and ﬁnd that prediction models using features based on Osgood scale-based scores (OSG) perform better than the baseline and are comparable in accuracy to those using Word2Vec score-based models (W2V). By using more interpretable Osgood-based scales, our study results can help with better understanding of students’ ongoing learning states and designing personalized learning systems that can address an individual’s weak points in vocabulary acquisition.
On optimisation programmes with hidden convexity

The main result of this paper is a method for finding hidden convexity in some smooth nonconvex programmes. Specifically, the method is identifying an equivalent convex formulation of the underlying nonconvex programme. The main idea of our method is to view a constrained optimisation programme as a control system, where the dual variable plays a role of a control signal. Therefore the existence of a global stabilising feedback controller implies the existence of an equivalent convex optimisation programme. In detail, the case of programmes with linear constraints is considered, for which sufficient conditions for finding hidden convexity are derived. If these sufficient conditions are satisfied an equivalent convex formulation can be obtained by using control-theoretic tools without a considerable computational cost. The whole procedure can be seen as a generalisation of the augmented Lagrangian method. This observation allows to obtain a control-theoretic interpretation of the augmented Lagrangian method, and an extension to incorporate linear inequality constraints.
Quantification of left ventricular indices from SSFP cine imaging: Impact of real‐world variability in analysis methodology and utility of geometric modeling

To assess the impact of “real‐world” practice variation in the process of quantifying left ventricular (LV) mass, volume indices, and ejection fraction (EF) from steady‐state free precession cardiovascular magnetic resonance (CMR) images. The utility of LV geometric modeling techniques was also assessed.
Nuclear Factor of Activated T Cells 5 Deficiency Increases the Severity of Neuronal Cell Death in Ischemic Injury

Nuclear factor of activated T cells 5 (NFAT5) has been implicated in regulating several genes that are thought to be neuroprotective in ischemic injury. Because of the embryonic lethality of NFAT5 knockout (NFAT5–/–) mice, the heterozygous (NFAT5+/–) mice were used to study the in vivo role of NFAT5 in hypoxia/ischemia (H/I) condition. The NFAT5+/– mice exhibited more severe neurological deficits, larger infarct area and edema formation associated with increased aquaporin 4 expressions in the brain. Under in vitro H/I condition, increased apoptotic cell death was found in NFAT5–/– neurons. Moreover, SMIT, a downstream to NFAT5, was upregulated in NFAT5+/+ neurons, while the SMIT level could not be upregulated in NFAT5–/– neurons under H/I condition. The elevation of reactive oxygen species generation in NFAT5–/– neurons under H/I condition further confirmed that NFAT5–/– neurons were more susceptible to oxidative stress. The present study demonstrated that activation of NFAT5 and its downstream SMIT induction is important in protecting neurons from ischemia-induced oxidative stress.
HYBRID MODEL OF RSA, AES AND BLOWFISH TO ENHANCE CLOUD SECURITY

Cloud is a term used as a metaphor for the wide area networks (like internet) or any such large networked environment. It came partly from the cloud-like symbol used to represent the complexities of the networks in the schematic diagrams. It represents all the complexities of the network which may include everything from cables, routers, servers, data centers and all such other devices. Cloud based systems saves data off multiple organizations on shared hardware systems. Data segregation is done by encrypting data of users, but encryption is not complete solution. We can do segregate data by creating virtual partitions of data for saving and allowing user to access data in his partition only. In our research work we have used the hybrid combination of RSA, AES and Blowfish for data encryption along with data fragmentation using Gateway.
Superhydrophobic turbulent drag reduction as a function of surface grating parameters

Abstract Despite the confirmation of slip flows and successful drag reduction (DR) in small-scaled laminar flows, the full impact of superhydrophobic (SHPo) DR remained questionable because of the sporadic and inconsistent experimental results in turbulent flows. Here we report a systematic set of bias-free reduction data obtained by measuring the skin-friction drags on a SHPo surface and a smooth surface at the same time and location in a turbulent boundary layer (TBL) flow. Each monolithic sample consists of a SHPo surface and a smooth surface suspended by flexure springs, all carved out from a $2.7 \times 2.7 {\mathrm{mm}}^{2}$ silicon chip by photolithographic microfabrication. The flow tests allow continuous monitoring of the plastron on the SHPo surfaces, so that the DR data are genuine and consistent. A family of SHPo samples with precise profiles reveals the effects of grating parameters on turbulent DR, which was measured to be as much as ${\sim }75\, \%$ .
Real Estate and its Role in Household Portfolio Choice

We empirically examines the financial portfolio choice of households as a function of their exposure to real estate risk as a possible background risk. Using Panel Study of Income Dynamics data from 1984 to 2001, our estimation results control for sample selection and unobservable time-invariant heterogeneity in an environment of non-strictly exogenous explanatory variables. Our analysis finds that larger real estate exposure is correlated with a lower likelihood of stock market participation and with reduced holdings of stocks and other risky financial assets in households' financial asset portfolios. We also measure the variability of homeowners' house values and provide evidence that it is also associated with lower stock market participation and, conditional on participation, lower equity investments.Previous version titled "Real Estate and its Role in Asset Allocation"
Evaluation of Si:HfO2 Ferroelectric Properties in MFM and MFIS Structures

A 10.5 nm silicon doped HfO<sub>2</sub> film is deposited and examined on three different bottom electrodes: a TiN electrode such as would be found in capacitive FeRAM, a lightly doped p-Si substrate as would be present in an FeFET, and an n+ Si electrode. The HfO<sub>2</sub> n+ silicon is shown to have a coercive voltage of 2.9 V compared to 1.9 V for the film deposited on TiN. This is shown to be due to a 1.2 nm oxide present at the HfO<sub>2</sub>/Si interface dropping 36% of the voltage that is applied to the ferroelectric film stack. An FeFET fabricated with the film shows a 0.55 V threshold voltage shift due to ferroelectric polarization charge for a maximum applied gate bias of 5 V. After accounting for non-zero flat-band voltages, a 5 V bias on the transistor gate is shown to correspond to a <inline-formula> <tex-math notation="LaTeX">$5.3~\mathrm {(\mu C/cm^{2})}$ </tex-math></inline-formula> remnant polarization in the ferroelectric film. This corresponds with a theoretical maximum threshold voltage shift of 9.46 V, indicating that there is significant room for growth in FeFET performance if materials and processing challenges can be overcome.
A bag of visual words approach for centromere and cytoplasmic staining pattern classification on HEp-2 images

Antinuclear autoantibodies (ANAs) are important markers to diagnose autoimmune diseases, very serious and also invalidating illnesses. The benchmark procedure for ANAs diagnosis is the indirect immunofluorescence (IIF) assay performed on the HEp-2 substrate. Medical doctors first determine the fluorescence intensity exhibited by HEp-2 cells, and then report the staining pattern for positive wells only. With reference to staining pattern recognition, in the literature we found works recognizing five main patterns characterized by well-defined cell edges. These approaches are based on cell segmentation, a task that should be harder than the classification itself. We present here a method extending the panel of detectable HEp-2 staining patterns, introducing the centromere and cytoplasmic patterns, which do not show well-defined cell edges, and where a segmentation-based classification may fail. We apply a local approach which extracts SIFT descriptors and then classifies an image through the bag of visual words approach. This permits to represent complex image contents without applying the segmentation procedure. We test our approach on a dataset of HEp-2 images with large variability in both fluorescence intensity and staining patterns. Despite the large skew of the a-priori class distribution, our system correctly recognizes the 98.3% of samples, with a F-measure equal to 92.3%, 95.2% and 99.0%, for each class.
Enhanced Modulation Bandwidth in Complex Cavity Injection Grating Lasers

Enhanced modulation bandwidth in complex cavity lasers can be obtained by exploiting the coupling between two adjacent cavity modes having proper spectral separation. We investigate the conditions that a complex cavity injection laser device must satisfy in order to take advantage of this effect to significantly increase its modulation bandwidth and we present a general design rule. According to the proposed guidelines, a structure is designed and then dynamically analyzed using a finite-difference time-domain program to show the validity of the proposed method. As an example the proposed guidelines have been adapted also to the design of a distributed Bragg reflector laser and extended modulation was found.
The Interpose PUF: Secure PUF Design against State-of-the-art Machine Learning Attacks

The design of a silicon Strong Physical Unclonable Function (PUF) that is lightweight and stable, and which possesses a rigorous security argument, has been a fundamental problem in PUF research since its very beginnings in 2002. Various effective PUF modeling attacks, for example at CCS 2010 and CHES 2015, have shown that currently, no existing silicon PUF design can meet these requirements. In this paper, we introduce the novel Interpose PUF (iPUF) design, and rigorously prove its security against all known machine learning (ML) attacks, including any currently known reliability-based strategies that exploit the stability of single CRPs (we are the first to provide a detailed analysis of when the reliability based CMA-ES attack is successful and when it is not applicable). Furthermore, we provide simulations and confirm these in experiments with FPGA implementations of the iPUF, demonstrating its practicality. Our new iPUF architecture so solves the currently open problem of constructing practical, silicon Strong PUFs that are secure against state-of-the-art ML attacks.