Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel GH7 Endo-β-1,4-Glucanase from Neosartorya fischeri P1 with Good Thermostability, Broad Substrate Specificity and Potential Application in the Brewing Industry

An endo-β-1,4-glucanase gene, cel7A, was cloned from the thermophilic cellulase-producing fungus Neosartorya fischeri P1 and expressed in Pichia pastoris. The 1,410-bp full-length gene encodes a polypeptide of 469 amino acids consisting of a putative signal peptide at residues 1–20, a catalytic domain of glycoside hydrolase family 7 (GH7), a short Thr/Ser-rich linker and a family 1 carbohydrate-binding module (CBM 1). The purified recombinant Cel7A had pH and temperature optima of pH 5.0 and 60°C, respectively, and showed broad pH adaptability (pH 3.0–6.0) and excellent stability at pH3.0–8.0 and 60°C. Belonging to the group of nonspecific endoglucanases, Cel7A exhibited the highest activity on barley β-glucan (2020 ± 9 U mg–1), moderate on lichenan and CMC-Na, and weak on laminarin, locust bean galactomannan, Avicel, and filter paper. Under simulated mashing conditions, addition of Cel7A (99 μg) reduced the mash viscosity by 9.1% and filtration time by 24.6%. These favorable enzymatic properties make Cel7A as a good candidate for applications in the brewing industry.
Enzymes in Fruit Juice Production Structure of Fruit Changes to Fruit during Ripening Background Information Use of Pectinases and Other Enzymes in Fruit Juice Production

Jam-makers have valued it for hundreds of years, wine-makers endeavour to destroy it and food technologists are variously trying to block or improve the enzymes that attack it. After cellulose, pectin is one of the most abundant carbohydrates on Earth. Yet despite its importance in the production of food and drink, pectin and the enzymes that break it down seldom receive the attention they deserve. This article describes the rôle of pectin, pectinases and other enzymes in fruit juice production. The structure of plant cells and the way they are built into tissues is complex. Only a simplified description will be given here, including sufficient detail for the reader to appreciate the action of enzymes in fruit juice production. Fruits are comprised mostly of parenchyma cells. These are relatively simple 'general purpose' plant cells, with thin walls made of two layers. The outermost of these, the primary cell wall, is made from cellulose fibres called microfibrils surrounded by a matrix of pectins, hemicelluloses and proteins. The inner, or secondary, cell wall is similar but contains less pectin (Figure 1). Between the cellular 'bricks' is a 'mortar' of pectin. Complete removal of this binding layer causes the tissue to fall apart. This is what has happened to fruits or vegetables which have gone soft. In such cases digestive enzymes, which have broken down the long chains of pectin molecules, have been produced by microbes such as the 'soft-rot' bacterium Erwinia carotovora. Cellulose is susceptible to enzymatic attack too, especially in the primary cell wall where its microfibrils are arranged at random rather than in the stronger regular pattern seen in the secondary wall. Degradation of the cellulose microfibrils leads to breakdown of the cell walls and their eventual disintegration. Table 1 shows the proportions of various materials found in the cell walls of some important fruit crops. There are two main stages in the formation of fruit. Soon after fertilisation the cells of the ovary (and in fruit like apples, those of the surrounding tissue as well) divide rapidly. In later weeks the young fruit swells as both these cells and the spaces between them enlarge. As the fruit ripens it becomes progressively softer. Much research has been done to discover exactly which enzymes are responsible for these and other changes in maturing fruit. One hope is that by monitoring the levels of these enzymes it might be possible for growers …
Improving Barcode Detection with Combination of Simple Detectors

Barcode detection is required in a wide range of real-life applications. Imaging conditions and techniques vary considerably and each application has its own requirements for detection speed and accuracy. In our earlier works we built barcode detectors using morphological operations and uniform partitioning with several approaches and showed their behaviour on a set of test images. In this work, we examine ensemble efficiency of those simple detectors using various aggregation methods. Using a combination of several simple features localization performance improves significantly.
Optical flow based obstacle avoidance for the visually impaired

Vision is a vital cue for human navigation. Thus, visually impaired people encounter many challenges in day-today travelling. Identifying and avoiding obstacles in the environment is the most crucial among them. To empower blind navigation, numerous electronic travel aids were created in the past few decades, by using various obstacle sensing technologies such as sonar, infrared, and stereo vision. However, optical flow estimations based navigation, which is heavily used by insects and experimented in the field of robotics, has not been used in them. This project aimed to evaluate the potential optical flow estimation based techniques has in guiding a visually impaired person to avoid obstacles using auditory and tactile feedback. To demonstrate the researched core concepts, a prototype consisting of a virtual reality world was designed and developed. It also employs an existing optical flow algorithm for motion estimation, other image processing techniques, speech synthesis for auditory feedback and embedded programming for tactile feedback. The modular design of the prototype enables it to be used either in simulation mode, or as a standalone application in a real world environment. This work demonstrates the attractive possibilities of using optical flow estimations for visually impaired navigation.
Improving the Performance of an Inkjet Printhead using Model Predictive Control

Abstract Inkjet printing is considered one of the most promising printing technologies that offers several advantages including high speed, quiet operation and compatibility with a variety of substrates. That makes it an important manufacturing technology serving a wide variety of markets. Though the performance criteria imposed by today's applications are quite tight already, the future performance requirements will be even more challenging. However, the attainable performance is limited by two operational issues that are generally encountered, namely residual vibrations and cross-talk. This paper presents an approach based on Model Predictive Control (MPC) with which an input waveform is designed to improve the printing quality of a piezoelectric inkjet printer. The narrow-gap model is employed to predict the response of the ink channel under the application of the piezo input. Simulation and experimental results are presented to investigate the performance of the proposed approach.
Event-related potential evidence in Chinese children

Visual word N170 is an index of perceptual expertise for visual words across different writing systems. Recent developmental studies have shown the early emergence of visual word N170 and its close association with individual’s reading ability. In the current study, we investigated whether fine-tuning N170 for Chinese characters could emerge after short-term literacy learning in young pre-literate children. Two groups of Chinese preschool children were trained for visual identification and free writing respectively. Results showed that visual identification learning led to enhanced N170 sensitivity to characters over radical-combinations in the left hemisphere and line-combinations in the right hemisphere, and writing learning led to enhanced N170 sensitivity to characters over radical-combinations and line-combinations in the right hemisphere. These results suggested that the N170 component became more sensitive for the local graphic feature (strokes) of characters rapidly after brief literacy learning even in young children; and writing learning experiences specifically led to enhanced orthographic sensitivity in the right hemisphere.
Walking side-by-side: Recovery Colleges revolutionising mental health care

Purpose The Recovery College model is an innovative approach to providing education to consumers, carers and mental health staff, with the potential to facilitate both personal recovery gains and organisational transformation towards recovery-focused service provision. The purpose of this paper is to explore the experiences of students who attended the South Eastern Sydney Recovery College (SESRC). Design/methodology/approach An exploratory, descriptive qualitative design was employed with data collected through seven focus group interviews with consumers and mental health staff who had participated in courses run by the SESRC. Thematic analysis of the data was conducted using both deductive and inductive processes in order to interpret the data. Findings All participants were positive about their involvement in the RC. Four themes emerged from the thematic analysis: connection with others, hope for the future, the importance of the lived experience, and changing attitudes and systems. Originality/value The outcomes of this study indicate that the SESRC is achieving its aims in relation to both personal recovery gains, and the potential to impact on service transformation. It highlights the centrality of co-production as a fundamental aspect of the Recovery College model. This paper contributes to the emerging evidence base for this model and provides evidence that this model is applicable to the Australian context.
Assembly of Iron Oxide Nanocubes for Enhanced Cancer Hyperthermia and Magnetic Resonance Imaging

Multiple formulations of iron oxide nanoparticles (IONPs) have been proposed for enhancing contrast in magnetic resonance imaging (MRI) and for increasing efficacy in thermal ablation therapies. However, insufficient accumulation at the disease site and low magnetic performance hamper the clinical application of IONPs. Here, 20 nm iron oxide nanocubes were assembled into larger nanoconstructs externally stabilized by a serum albumin coating. The resulting assemblies of nanocubes (ANCs) had an average diameter of 100 nm and exhibited transverse relaxivity (r2 = 678.9 ± 29.0 mM‒1·s‒1 at 1.41 T) and heating efficiency (specific absorption rate of 109.8 ± 12.8 W·g‒1 at 512 kHz and 10 kA·m‒1). In mice bearing glioblastoma multiforme tumors, Cy5.5-labeled ANCs allowed visualization of malignant masses via both near infrared fluorescent and magnetic resonance imaging. Also, upon systemic administration of ANCs (5 mgFe·kg‒1), 30 min of daily exposure to alternating magnetic fields for three consecutive days was sufficient to halt tumor progression. This study demonstrates that intravascular administration of ANCs can effectively visualize and treat neoplastic masses.
The Horizon supercomputing system: architecture and software

An overview is given of Horizon, a shared-memory multiple-instruction-stream-multiple-data-stream computer architecture currently under study. Its performance target is a sustained rate of 100 GFLOPS (billions of floating-point operators per second), using a few hundred identical scalar processors. The Horizon architecture is described and its performance is estimated. The processor instruction set and a simple programming example are given. <<ETX>>
An Integrated Outlook on the Metagenome and Metabolome of Intestinal Diseases

Recently, metagenomics and metabolomics are the two most rapidly advancing “omics” technologies. Metagenomics seeks to characterize the composition of microbial communities, their operations, and their dynamically co-evolving relationships with the habitats they occupy, whereas metabolomics studies unique chemical endpoints (metabolites) that specific cellular processes leave behind. Remarkable progress in DNA sequencing and mass spectrometry technologies has enabled the comprehensive collection of information on the gut microbiome and its metabolome in order to assess the influence of the gut microbiota on host physiology on a whole-systems level. Our gut microbiota, which consists of prokaryotic cells together with its metabolites, creates a unique gut ecosystem together with the host eukaryotic cells. In this review, we will highlight the detailed relationships between gut microbiota and its metabolites on host health and the pathogenesis of various intestinal diseases such as inflammatory bowel disease and colorectal cancer. Therapeutic interventions such as probiotic and prebiotic administrations and fecal microbiota transplantations will also be discussed. We would like to promote this unique biology-wide approach of incorporating metagenome and metabolome information as we believe that this can help us understand the intricate interplay between gut microbiota and host metabolism to a greater extent. This novel integration of microbiome, metatranscriptome, and metabolome information will help us have an improved holistic understanding of the complex mammalian superorganism, thereby allowing us to gain new and unprecedented insights to providing exciting novel therapeutic approaches for optimal intestinal health.
Semantic publishing: the coming revolution in scientific journal publishing

Recent developments in Web technology can be used for semantic enhancement of scholarly journal articles, by aiding publication of data and metadata and providing ‘lively’ interactive access to content. Such semantic enhancements are already being undertaken by leading STM publishers, and automated text processing will help these enhancements become affordable and routine. Publisher, editor, and author all have primary roles in that process; an incremental approach is needed. Publication of data and metadata to the Web make possible added‐value ‘ecosystem services‘; semantic publishing will bring substantial benefits to scholarly communication.
An Electro Optical Honeycomb Networks-on-Chip based on a New Nonblocking Switch

Network-on-Chip (NoC) is an emerging paradigm for communications within large VLSI systems implemented on a single silicon chip. However, the electronic network on chip design faces many problems like energy consumption, bandwidth and QoS. Compared with traditional electronic NoC, optical Network on Chip exhibits advantages of high-bandwidth, low latency and power dissipation. In this paper, a new 4×4 optical non-blocking switch is introduced on the basis of the latest development of nanophotonic technologies and of the prompt progress of optical integration technologies. The new approach can solve the problem of internal blocking with a fine symmetrical feature, while it needs the minimal number of resonators. Optical-loss budget under this architecture is also evaluated, calculated and compared with currently existing optical switches in this paper. An electro optical honeycomb network-on-chip is constructed based on the new switch architecture. It functions with low power dissipation and high bandwidth for the future network on chip.
Simulating the Spread of Infectious Disease over Large Realistic Social Networks Using Charm++

Preventing and controlling outbreaks of infectious diseases such as pandemic influenza is a top public health priority. EpiSimdemics is an implementation of a scalable parallel algorithm to simulate the spread of contagion, including disease, fear and information, in large (108 individuals), realistic social contact networks using individual-based models. It also has a rich language for describing public policy and agent behavior. We describe CharmSimdemics and evaluate its performance on national scale populations. Charm++ is a machine independent parallel programming system, providing high-level mechanisms and strategies to facilitate the task of developing highly complex parallel applications. Our design includes mapping of application entities to tasks, leveraging the efficient and scalable communication, synchronization and load balancing strategies of Charm++. Our experimental results on a 768 core system show that the Charm++ version achieves up to a 4-fold increase in performance when compared to the MPI version.
Automatic Crack Detection and Inpainting

— Image inpainting is the process of restoring the lost or damaged regions or modifying the image contents imperceptibly. It refers to the process of filling-in missing data in a designated region of the visual input. In this paper, the technique presented is for detection and removal of cracks from digitized paintings. Crack detection is done automatically by using bottom-hat morphological operation and median filtering is applied only on crack pixels for filling the cracks. We have found PSNR (peak signal to noise ratio)of the images in which the cracks are restored by applying median filtering only on crack pixels and compared the results with the other approach which restores crack by applying median filtering technique on whole crack image.
Reproducible Biofilm Cultivation of Chemostat-Grown Escherichia coli and Investigation of Bacterial Adhesion on Biomaterials Using a Non-Constant-Depth Film Fermenter

Biomaterials-associated infections are primarily initiated by the adhesion of microorganisms on the biomaterial surfaces and subsequent biofilm formation. Understanding the fundamental microbial adhesion mechanisms and biofilm development is crucial for developing strategies to prevent such infections. Suitable in vitro systems for biofilm cultivation and bacterial adhesion at controllable, constant and reproducible conditions are indispensable. This study aimed (i) to modify the previously described constant-depth film fermenter for the reproducible cultivation of biofilms at non-depth-restricted, constant and low shear conditions and (ii) to use this system to elucidate bacterial adhesion kinetics on different biomaterials, focusing on biomaterials surface nanoroughness and hydrophobicity. Chemostat-grown Escherichia coli were used for biofilm cultivation on titanium oxide and investigating bacterial adhesion over time on titanium oxide, poly(styrene), poly(tetrafluoroethylene) and glass. Using chemostat-grown microbial cells (single-species continuous culture) minimized variations between the biofilms cultivated during different experimental runs. Bacterial adhesion on biomaterials comprised an initial lag-phase I followed by a fast adhesion phase II and a phase of saturation III. With increasing biomaterials surface nanoroughness and increasing hydrophobicity, adhesion rates increased during phases I and II. The influence of materials surface hydrophobicity seemed to exceed that of nanoroughness during the lag-phase I, whereas it was vice versa during adhesion phase II. This study introduces the non-constant-depth film fermenter in combination with a chemostat culture to allow for a controlled approach to reproducibly cultivate biofilms and to investigate bacterial adhesion kinetics at constant and low shear conditions. The findings will support developing and adequate testing of biomaterials surface modifications eventually preventing biomaterial-associated infections.
From infinity to one: The reduction of some mean field games to a global control problem

This paper presents recent results from Mean Field Game theory underlying the introduction of common noise that imposes to incorporate the distribution of the agents as a state variable. Starting from the usual mean field games equations introduced in [11 , 12 , 13 ] and adapting them to games on graphs, we introduce a partial differential equation, often referred to as the Master equation (see [14]), from which the MFG equations can be deduced. Then, this Master equation can be reinterpreted using a global control problem inducing the same behaviors as in the non-cooperative initial mean field game.
Mars Rover Antenna for Solar-Array Integration

A low-gain crossed-slot microstrip patch antenna integrated with the solar-array panel has been successfully developed for the Mars rover application at the frequency of 400 MHz. It achieved a very low mass of 0.5 kg and occupied very small real estate (6.5 percent) of the solar panel. The electrical and mechanical characteristics of several other omni-directional low-gain antennas also are discussed in this article.
High level programming framework for FPGAs in the data center

Heterogeneous computing offers a promising solution for energy efficient computing in the data center. FPGA based heterogeneous computing is an especially promising direction since it allows for the creation of custom hardware solutions for data centric parallel applications. One of the main issues delaying wide spread adoption of FPGAs as main stream high performance computing devices is the difficulty in programming them. OpenCL was meant to address the difficulties and the non-uniformity related to programming heterogeneous devices, unfortunately because of its complexity it sets the bar high for many software programmers, preventing them from directly benefiting from the computing power and energy efficiency that OpenCL and heterogeneous computing have to offer. This work presents an effort to bridge the gap by extending an existing Java programming framework (APARAPI), based on OpenCL, so that it can be used to program FPGAs at a high level of abstraction and increased ease of programmability. We run several real world algorithms to assess the performance of the APARAPI framework on both a low end and a high end system. On the low end and high and systems respectively we find up to 78-80 percent power reduction and 4.8X-5.3X speed increase running NBody simulation, as well as up to 65-80 percent power reduction and 6.2X-7X speed increase for a K-Means MapReduce algorithm running on top of the Hadoop framework and APARAPI.
Multi-resolution vehicle detection using artificial vision

This paper describes a vehicle detection system using a single camera. It is based on the search for areas with a high vertical symmetry in multi-resolution images; symmetry is computed using different sized boxes centered on all the columns of the interest areas. All the columns with high symmetry are analyzed to get the width of detected objects. Horizontal edges are examined to find the base of the vehicle in the individuated area. The aim is to find horizontal lines located below an area with sufficient amount of edges. The algorithm deletes all the bounding boxes which are too large, too small, or too far from the camera in order to decrease the number of false positives. All the results found in different interest areas are mixed together and the overlapping bounding boxes are localized and managed in order to delete false positives. The algorithm analyzes images on a frame by frame basis, without any temporal correlation.