Miracle-dz/UniFAR-FTUs huggingface dataset:
Autoinducer 2-Dependent Escherichia coli Biofilm Formation Is Enhanced in a Dual-Species Coculture

ABSTRACT Biofilms in nature typically consist of multiple species, and microbial interactions are likely to have crucial effects on biofilm development, structure, and functions. The best-understood form of communication within bacterial communities involves the production, release, and detection of signal molecules (autoinducers), known as quorum sensing. Although autoinducers mainly promote intraspecies communication, autoinducer 2 (AI-2) is produced and detected by a variety of bacteria, thus principally allowing interspecies communication. Here we show the importance of AI-2-mediated signaling in the formation of mixed biofilms by Enterococcus faecalis and Escherichia coli. Our results demonstrate that AI-2 produced by E. faecalis promotes collective behaviors of E. coli at lower cell densities, enhancing autoaggregation of E. coli but also leading to chemotaxis-dependent coaggregation between the two species. Finally, we show that formation of such mixed dual-species biofilms increases the stress resistance of both E. coli and E. faecalis. IMPORTANCE The role of interspecies communication in the development of mixed microbial communities is becoming increasingly apparent, but specific examples of such communication remain limited. The universal signal molecule AI-2 is well known to regulate cell-density-dependent phenotypes of many bacterial species but, despite its potential for interspecies communication, the role of AI-2 in the establishment of multispecies communities is not well understood. In this study, we explore AI-2 signaling in a dual-species community containing two bacterial species that naturally cooccur in their mammalian hosts, i.e., Escherichia coli and Enterococcus faecalis. We show that active production of AI-2 by E. faecalis allows E. coli to perform collective behaviors at low cell densities. Additionally, AI-2- and chemotaxis-dependent coaggregation with E. faecalis creates nucleation zones for rapid growth of E. coli microcolonies in mixed biofilms and enhances the stress resistance of both species.
Developing a Business Process Modeling Language for the Banking Sector - A Design Science Approach

The need to extensively analyze business processes for multiple purposes is currently of major relevance to banks. Automatically analyzing business process models not only in a syntactical but also in a semantic way becomes increasingly important in order to achieve additional value from modeling efforts. In this article, we introduce a domain-specific BPML which supports the economically efficient semantic analysis needs of banks. Hence, we develop a language using process building blocks for the specific application of IT-driven business process analysis in the banking sector. With a design science approach, we adapt a language from the public sector to the banking requirements and evaluate our findings with the help of a real-life case from the banking industry.
Extraction of Drug from the Biological Matrix: A Review

The assessment of therapeutic compliance is commonly done by either indirect method or direct method. In indirect method, the assessments are done by indirect measurement of parameters such as discussion with patients and pill counts at intervals during the treatment which don’t measure the drug concentration in a matrix such as blood or urine. In direct method, the assessments which rely upon evidence provided by the patients or care giver on the presumptive compliance based upon electronic medical event monitoring system and this is based upon either the qualitative or quantitative measurement of the drug under investigation in a biological matrix provided by the system.
RNA force field with accuracy comparable to state-of-the-art protein force fields

Significance The complex and often highly dynamic 3D structures of RNA molecules are central to their diverse cellular functions. Molecular dynamics (MD) simulations have played a major role in characterizing the structure and dynamics of proteins, but the physical models (“force fields”) used for simulating nucleic acids are substantially less accurate overall than those used in protein simulations, creating a major challenge for MD studies of RNA. Here, we report an RNA force field capable of describing the structural and thermodynamic properties of RNA molecules with accuracy comparable to state-of-the-art protein force fields. This force field should facilitate the use of MD simulation as a tool for the study of biologically significant RNA molecules and protein–RNA complexes. Molecular dynamics (MD) simulation has become a powerful tool for characterizing at an atomic level of detail the conformational changes undergone by proteins. The application of such simulations to RNA structures, however, has proven more challenging, due in large part to the fact that the physical models (“force fields”) available for MD simulations of RNA molecules are substantially less accurate in many respects than those currently available for proteins. Here, we introduce an extensive revision of a widely used RNA force field in which the parameters have been modified, based on quantum mechanical calculations and existing experimental information, to more accurately reflect the fundamental forces that stabilize RNA structures. We evaluate these revised parameters through long-timescale MD simulations of a set of RNA molecules that covers a wide range of structural complexity, including single-stranded RNAs, RNA duplexes, RNA hairpins, and riboswitches. The structural and thermodynamic properties measured in these simulations exhibited dramatically improved agreement with experimentally determined values. Based on the comparisons we performed, this RNA force field appears to achieve a level of accuracy comparable to that of state-of-the-art protein force fields, thus significantly advancing the utility of MD simulation as a tool for elucidating the structural dynamics and function of RNA molecules and RNA-containing biological assemblies.
Explorer WOMAC , EQ-5 D and Knee Society Score Thresholds for Treatment Success After Total Knee Arthroplasty

One ormore of the authors of this paper have disclosed of interest, which may include receipt of payment, either support, or association with an entity in the biomedical fi have potential conflict of interest with this work. For ful http://dx.doi. org/10.1016/j.arth. 2015.06. 012. Reprint requests: Karlmeinrad Giesinger, MSc, MD and Traumatology, Kantonsspital St. Gallen, Rorsc CH-9000, Switzerland. http://dx.doi. org/10.1016/j.arth. 2015.06. 012 0883-5403/© 2015 The Authors. Published by Elsevier Inc Please cite this article as: Giesinger JM, et Arthroplasty, J Arthroplasty (2015), http://d Article history: Received 30 March 2015 Accepted 8 June 2015 Available online xxxx
Salient object detection via a linear feedback control system

Linear feedback control systems (LFCS) have been widely applied in signal analysis, filtering, and error correction. Many functional properties of LFCS are amenable to numerous object recognition and detection tasks. In fact, there exists an intimate relationship between control states and salient values. This prompts us to adopt the linear feedback control system to detect salient object in static images. Via an innovative iteration method, the system gradually converges an optimized stable state, which is associating with an accurate saliency map. In addition, to initialize the system, we propose the so called boundary homogeneity based on a priori knowledge on the boundary to estimate the background likelihood and indirectly depict a foreground (saliency) map. By our experimental results, we demonstrates that such feedback control model can bring about noticable improvement in salient object detection.
Fast Numerical Analysis of Electric Motor Using Nonlinear Model Order Reduction

The problem of the computationally efficient analysis of the electromagnetic system with nonlinearity is considered in the proposed work. Unlike the previously proposed proper orthogonal decomposition (POD)-based model order reduction (MOR), the proposed method based on the dynamic mode decomposition works well even under the highly nonlinear system. Using the proposed method, a highly saturated interior permanent-magnet (IPM) motor model is analyzed. Comparisons in terms of the radial air-gap flux density and torque are made with that of the full and POD-based models. The results show that the proposed method is capable of giving a good approximation of the full model of the IPM motor. Also, a reduction in the computational time can be achieved compared with that of the traditional POD-based MOR.
A self-learning personalized feedback agent for motivating physical activity

An important aspect in the treatment of various chronic diseases is to optimise physical activity levels. We present a general approach for the implementation of an electronic Feedback Agent that serves as a personal coach for achieving and maintaining a healthy level of physical activity through sustainable behavioural change. The Feedback Agent is a self-learning, context aware, personalized software agent that runs on the user's Smartphone and uses an external inertial sensor to keep track of the user's level of physical activity throughout the day. We highlight the three important aspects of feedback in our framework: the timing, content and representation of given feedback messages. Tailoring and optimization of feedback timing and content is in an advanced stage of research, while the representation aspect is largely a matter of future work.
Proteomic analysis of cell cycle progression in asynchronous cultures, including mitotic subphases, using PRIMMUS

The temporal regulation of protein abundance and post-translational modifications is a key feature of cell division. Recently, we analysed gene expression and protein abundance changes during interphase under minimally perturbed conditions (Ly et al. 2014; Ly et al. 2015). Here we show that by using specific intracellular immunolabeling protocols, FACS separation of interphase and mitotic cells, including mitotic subphases, can be combined with proteomic analysis by mass spectrometry. Using this PRIMMUS (PRoteomic analysis of Intracellular iMMUnolabeled cell Subsets) approach, we now compare protein abundance and phosphorylation changes in interphase and mitotic fractions from asynchronously growing human cells. We identify a set of 115 phosphorylation sites increased during G2, which we term ‘early risers’. This set includes phosphorylation of S738 on TPX2, which we show is important for TPX2 function and mitotic progression. Further, we use PRIMMUS to provide a proteome-wide analysis of protein abundance remodeling between prophase, prometaphase and anaphase.
Effect of Coir Fiber on the Stress–Strain Behavior of a Reconstituted Fine-Grained Soil

The heterogeneous nature of the soil poses great challenge as well as opportunity to geotechnical engineers all over the world. As the availability of good sites is becoming difficult, active research is going on throughout the world to improve the engineering properties of the soft soils. Among all the ground improvement techniques, the soil reinforcement is emerging as an attractive alternative. Addition of natural fiber to the soil is a very good soil-reinforcement technique in the context of sustainable development. Coir fiber can be effectively used to tackle many short-term stability issues in geotechnical engineering related to shear strength, permeability, etc. In the present study, comprehensive experimental work has been conducted to investigate the effect of coir fiber on the stress–strain characteristics of a reconstituted cohesive soil. Laboratory model studies are conducted to study the effect of length and amount of fiber on the shear strength of soil. Tests were carried out using fiber contents varying in the range of 0%–2% by dry weight of the soil. The unconfined compressive strength of soil is significantly increased when coir fiber is added to it. The increase is directly proportional to the quantity of the fiber used. The peak compressive strength of the fiber-reinforced soil with 1.5% fiber content is more than twice that of the un-reinforced soil. Mixing of fiber of length 15 mm is found beneficial from laboratory experiments on 38-mm (diameter) × 76-mm (height) samples. Triaxial compression tests results showed that the fiber content in the range of 1.5%–2% is highly beneficial to enhance and strength of the fine-grained soil. Also, it is observed that peak deviator stress increases with increase in fiber content for all confining pressures. A remarkable increase in cohesion and friction angle values has been observed with the addition of fiber, and they increases nonlinearly with the fiber content. Moreover, the stiffness and ductility of the soil are quite improved with the use of natural fiber.
Precise BER performance of BPSK in two-wave with diffuse power fading channel and cochannel interference

We presents the precise bit error rate (BER) analysis for a binary phase-shift keying (BPSK) system in two-wave with diffuse power (TWDP) fading channel in co-channel interference (CCI) environment. A precise BER expression is derived using a characteristic function (CF) for the case of perfect coherent detection. The method of Chernoff Bound is used to derive the BER versus SIR. The impact of different TWDP fading scenarios on the BER performance is presented. Simulation results of TWDP fading channel with and without co-channel interference are compared.
Selective base excision repair of DNA damage by the non‐base‐flipping DNA glycosylase AlkC

DNA glycosylases preserve genome integrity and define the specificity of the base excision repair pathway for discreet, detrimental modifications, and thus, the mechanisms by which glycosylases locate DNA damage are of particular interest. Bacterial AlkC and AlkD are specific for cationic alkylated nucleobases and have a distinctive HEAT‐like repeat (HLR) fold. AlkD uses a unique non‐base‐flipping mechanism that enables excision of bulky lesions more commonly associated with nucleotide excision repair. In contrast, AlkC has a much narrower specificity for small lesions, principally N3‐methyladenine (3mA). Here, we describe how AlkC selects for and excises 3mA using a non‐base‐flipping strategy distinct from that of AlkD. A crystal structure resembling a catalytic intermediate complex shows how AlkC uses unique HLR and immunoglobulin‐like domains to induce a sharp kink in the DNA, exposing the damaged nucleobase to active site residues that project into the DNA. This active site can accommodate and excise N3‐methylcytosine (3mC) and N1‐methyladenine (1mA), which are also repaired by AlkB‐catalyzed oxidative demethylation, providing a potential alternative mechanism for repair of these lesions in bacteria.
A novel method to regenerate an optimal CNN by exploiting redundancy patterns in the network

Deploying Convolution Neural Networks (CNN) based computer vision applications on low-power embedded devices is challenging due to massive computation and memory bandwidth requirements. Research is on-going on faster algorithms, network pruning, and model compression techniques to produce light-weight networks. In this paper, we propose a novel method which exploits a redundancy pattern in the network to regenerate an efficient and functionally identical CNN for a given network. We identify the pattern based on the layer parameters (kernel size and stride) and data flow analysis among the layers to avoid the redundant processing and memory requirements while maintaining identical accuracy. Our proposed method augments the state-of-the-art pruning and model compression techniques to achieve further performance boost-up. The proposed method is experimented with the Caffe [1] framework for ResNet-50 [2] inference on Samsung smartphone with an octa-core ARM Cortex-A53 processor. The results show an improvement of 4x in performance and memory at layer level, ∼22% performance improvement and 6% memory reduction at network level.
A Physical Insight Into the Influence of Dominant Mode of Rectangular Microstrip Antenna on Its Cross-Polarization Characteristics and Its Improvement With T-Shaped Microstrip Antenna

In this paper, the cross polar radiation of rectangular microstrip patch antenna due to its own lowest order dominant TM10 mode has been investigated thoroughly. The nature of the field distribution beneath the patch is found to be the key reason for cross polar radiation of such patch antenna. A quick hand computer aided design formulation has been proposed to compute the approximate cross polar radiation peak gain as well as its position in elevation plane. Based on the theoretical view, a simple single layer T shaped microstrip antenna has also been proposed for the improvement in cross polarization suppression of rectangular microstrip antenna.
Substrate product ratios of enzymes in the kynurenine pathway measured in plasma as indicators of functional vitamin B-6 status.

BACKGROUND Tryptophan metabolism through the kynurenine pathway includes 2 vitamin B-6 [pyridoxal 5'-phosphate (PLP)]-dependent enzymes. We recently showed that plasma 3-hydroxykynurenine (HK) was elevated at low PLP concentrations. OBJECTIVE We further evaluated and characterized kynurenine-based indexes as possible markers of functional B-vitamin status in plasma. DESIGN Cross-sectional and longitudinal data were derived from the Western Norway B-vitamin Intervention Trial, including PLP, kynurenine, HK, kynurenic acid (KA), anthranilic acid, xanthurenic acid (XA), and 3-hydroxyanthranilic acid (HAA) measured in plasma at 2 time points. Partial Spearman's correlation, generalized additive models, and receiver operating characteristic (ROC) analysis were used to assess associations of kynurenines with PLP. RESULTS Ratios HK:XA, HK:HAA, and HK:KA showed markedly stronger negative correlations with PLP than did HK alone (Spearman's ρ = -0.36, -0.29, and -0.31 compared with -0.18, respectively). All associations were nonlinear, with the strongest relation at low PLP. In the ROC analysis, areas under the curve for discriminating low PLP (less than the fifth percentile; 18.6 nmol/L) were 0.78, 0.78, and 0.74, respectively, compared with 0.65 for HK. Oral treatment with 40 mg pyridoxin hydrochloride for 28 d reduced the ratios by up to 60%, with strongest reductions for subjects with low plasma PLP at baseline. Whereas HK was associated with kidney function and several inflammatory markers, such associations were abolished or attenuated for the ratios. CONCLUSION Plasma values of HK:XA and HK:HAA, which are substrate-product pairs for kynurenine transaminase and kynureninase, respectively, may reflect the intracellular availability of the cofactor (PLP) and, therefore, present as potential markers of functional vitamin B-6 status.
Left Ventricle Segmentation in Cardiac MR Images Using Fully Convolutional Network

Medical image analysis, especially segmenting a specific organ, has an important role in developing clinical decision support systems. In cardiac magnetic resonance (MR) imaging, segmenting the left and right ventricles helps physicians diagnose different heart abnormalities. There are challenges for this task, including the intensity and shape similarity between the left ventricle and other organs, inaccurate boundaries, and presence of noise in most of the images. In this paper, we propose an automated method for segmenting the left ventricle in cardiac MR images. We first automatically extract the region of interest and then employ it as an input of a fully convolutional network. We train the network accurately despite the small number of left ventricle pixels in comparison with the whole image. Thresholding on the output map of the fully convolutional network and selection of regions based on their roundness are performed in our proposed post-processing phase. The Dice score of our method reaches 87.24% by applying this algorithm on the York dataset of heart images.
Efficient directional and L1-optimized intra-prediction for light field image compression

Light field images can be conveniently captured by consumer-level plenoptic cameras. However, as the resulting data rates are very high, providing efficient compression for this type of data is of critical importance. This remains an open problem which has recently attracted a lot of attention from the coding community. State-of-the-art compression systems prove to be inefficient when directly applied on this type of data due to the inherent spatial discontinuities in light field images. In this paper, a novel intra-prediction method for disk-shaped pixel clusters is proposed. An L1 minimization of the prediction residuals is performed followed by clustering of the predictors, leading to an optimized set of predictors for the macro-pixels. Furthermore, directional intra-prediction modes based on HEVC are devised for the macro-pixels. Experimental results obtained on the EPFL light field image dataset demonstrate that the proposed coding scheme yields an average of 3.22 dB and 1.45 dB gain in PSNR, and 59.6% and 30.88% average rate savings compared to HEVC and the state-of-the-art in light field image coding respectively.
Customized Three Dimensional Printed Porous Polyethylene for Calvarial Reconstruction

Porous polyethylene has been widely used for cranio-maxillofacial procedures due to its highly stable, flexible and has been shown to exhibit rapid soft-tissue and bone ingrowth. Generally, it is available as standard shape which needs to be intra-operatively contoured and manually adapted to fit the defect of each patient. In this study, a technique of producing customized porous polyethylene implant for calvarial defect reconstruction was reported. The technique began with acquiring patients data by computed tomography and was three dimensionally reconstructed using a medical imaging software. The shape of implant was then digitally designed to fit the defect based on the patients anatomy and transferred to three dimensional printing machine to fabricate the implant using proprietary polyethylene formulation as raw material. This technique can be used to cover any cranial defect size, offering similar or even better cosmetic results to standard alloplast cranioplasty while decreasing operation time. This customized porous implant can permit ingrowth of tissue to increase interface stability, implant strength and decrease the risk of infection similarly to commercial product.
Base Station Selection for Massive MIMO Networks With Two-Stage Precoding

Two-stage precoding has been proposed to reduce the overhead of both the channel training and the channel state information feedback in massive multiple-input multiple-output systems. But the overlap of the angle-spreading-ranges (ASR) for different user clusters may seriously degrade the performance of two-stage precoding. In this letter, we propose an ASR overlap mitigating scheme through the base station (BS) selection. First, the BS selection is formulated as a sum signal-to-interference-plus-noise ratio maximization problem. Then, the problem is solved by a low-complex algorithm through maximizing the signal-to-leakage-plus-noise ratio (SLNR). In addition, we propose a low-overhead algorithm with the lower bound on the average SLNR as the objective function. Finally, we demonstrate the efficacy of the proposed schemes through numerical simulations.