Miracle-dz/UniFAR-FTUs huggingface dataset:
A self‐assembled monolayer‐based micropatterned array for controlling cell adhesion and protein adsorption

We developed a surface micropatterning technique to control the cell adhesion and protein adsorption. This micropatterned array system was fabricated by a photolithography technique and self‐assembled monolayer (SAM) deposition. It was hypothesized that the wettability and functional terminal group would regulate cell adhesion and protein adsorption. To demonstrate this hypothesis, glass‐based micropatterned arrays with various functional terminal groups, such as amine (NH2) group (3‐aminopropyl‐triethoxysilane, APT), methyl (CH3) group (trichlorovinylsilane, TVS), and fluorocarbon (CF3) group (trichloro(1H, 1H, 2H, 2H‐perfluorooctyl)silane, FOTS), were used. The contact angle was measured to determine the hydrophilic and hydrophobic properties of materials, demonstrating that TVS and FOTS were hydrophobic, whereas APTs were relatively hydrophilic. The cell adhesion was significantly affected by the wettability, showing that the cells were not adhered to hydrophobic surfaces, such as TVS and FOTS. Thus, the cells were selectively adhered to glass substrates within TVS‐ and FOTS‐based micropatterned arrays. However, the cells were randomly adhered to APTs‐based micropatterned arrays due to hydrophilic property of APTs. Furthermore, the protein adsorption of the SAM‐based micropatterned array was analyzed, showing that the protein was more absorbed to the TVS surface. The surface functional terminal group enabled the control of protein adsorption. Therefore, this SAM‐based micropatterned array system enabled the control of cell adhesion and protein adsorption and could be a potentially powerful tool for regulating the cell–cell interactions in a well‐defined microenvironment. Bioeng. 2011; 108:1194–1202. © 2010 Wiley Periodicals, Inc.
Towards a Holistic Understanding of Security Process: Formal Controls and Informal Relationships

Despite a variety of existing approaches and techniques for securing corporate information assets, information security threats continue to present an ongoing challenge to business and governments. Existing research suggests that improving the effectiveness of information security depends on the customization of existing security models to specific businesses requirements. A greater socio-technical focus is also cited as necessary. We have used a relational processes lens to examine interactions between the key actors relevant to information security management in a large Australian financial institution from which we present the results of an in-depth case study. By examining organizational information security practices we identify how organizational actors engage in cognitive, social and political processes to achieve various security-related objectives. We suggest that a focus on social and political processes, such as networking and negotiation, complements formal policy and governance structures in achieving organizational security objectives and can assist information security stakeholders in working together more effectively.
Novel hyper-heuristics applied to the domain of bin packing

Principal to the ideology behind hyper-heuristic research is the desire to increase the level of generality of heuristic procedures so that they can be easily applied to a wide variety of problems to produce solutions of adequate quality within practical timescales. This thesis examines hyper-heuristics within a single problem domain, that of Bin Packing where the benefits to be gained from selecting or generating heuristics for large problem sets with widely differing characteristics is considered. Novel implementations of both selective and generative hyper-heuristics are proposed. The former approach attempts to map the characteristics of a problem to the heuristic that best solves it while the latter uses Genetic Programming techniques to automate the heuristic design process. Results obtained using the selective approach show that solution quality was improved significantly when contrasted to the performance of the best single heuristic when applied to large sets of diverse problem instances. Although enforcing the benefits to be gained by selecting from a range of heuristics the study also highlighted the lack of diversity in human designed algorithms. Using Genetic Programming techniques to automate the heuristic design process allowed both single heuristics and collectives of heuristics to be generated that were shown to perform significantly better than their human designed counterparts. The thesis concludes by combining both selective and generative hyper-heuristic approaches into a novel immune inspired system where heuristics that cover distinct areas of the problem space are generated. The system is shown to have a number of advantages over similar cooperative approaches in terms of its plasticity, efficiency and long term memory. Extensive testing of all of the hyper-heuristics developed on large sets of both benchmark and newly generated problem instances enforces the utility of hyper-heuristics in their goal of producing fast understandable procedures that give good quality solutions for a range of problems with widely varying characteristics.
Numerical Simulation of Inert Solid-Phase Three- Component Mixtures Subjected to Explosive Compaction

The article considers the axisymmetric problem concerning the explosive compaction of a mixture from aluminum, sulfur and carbon placed into a cylindrical steel ampoule. The inert substance (graphite) is added to the mixture to avoid the reaction between aluminum and sulfur. The numerical computations have demonstrated that the thickness of the explosive layer essentially influences on the final result of explosive compaction. Insufficient thickness of explosives, as well as the excessive thickness may be a reason for an incompletely compacted final product or lead to the formation of cracks or damage. Keywords— shock wave synthesis; solid mixtures; multicomponent medium
Learning People Detectors for Tracking in Crowded Scenes

People tracking in crowded real-world scenes is challenging due to frequent and long-term occlusions. Recent tracking methods obtain the image evidence from object (people) detectors, but typically use off-the-shelf detectors and treat them as black box components. In this paper we argue that for best performance one should explicitly train people detectors on failure cases of the overall tracker instead. To that end, we first propose a novel joint people detector that combines a state-of-the-art single person detector with a detector for pairs of people, which explicitly exploits common patterns of person-person occlusions across multiple viewpoints that are a frequent failure case for tracking in crowded scenes. To explicitly address remaining failure modes of the tracker we explore two methods. First, we analyze typical failures of trackers and train a detector explicitly on these cases. And second, we train the detector with the people tracker in the loop, focusing on the most common tracker failures. We show that our joint multi-person detector significantly improves both detection accuracy as well as tracker performance, improving the state-of-the-art on standard benchmarks.
Streptozocin-Induced Diabetic Mouse Model of Urinary Tract Infection

ABSTRACT Diabetics have a higher incidence of urinary tract infection (UTI), are infected with a broader range of uropathogens, and more commonly develop serious UTI sequelae than nondiabetics. To better study UTI in the diabetic host, we created and characterized a murine model of diabetic UTI using the pancreatic islet β-cell toxin streptozocin in C3H/HeN, C3H/HeJ, and C57BL/6 mouse backgrounds. Intraperitoneal injections of streptozocin were used to initiate diabetes in healthy mouse backgrounds, as defined by consecutive blood glucose levels of >250 mg/dl. UTIs caused by uropathogenic Escherichia coli (UTI89), Klebsiella pneumoniae (TOP52 1721), and Enterococcus faecalis (0852) were studied, and diabetic mice were found to be considerably more susceptible to infection. All three uropathogens produced significantly higher bladder and kidney titers than buffer-treated controls. Uropathogens did not have as large an advantage in the Toll-like receptor 4-defective C3H/HeJ diabetic mouse, arguing that the dramatic increase in colonization seen in C3H/HeN diabetic mice may partially be due to diabetic-induced defects in innate immunity. Competition experiments demonstrated that E. coli had a significant advantage over K. pneumoniae in the bladders of healthy mice and less of an advantage in diabetic bladders. In the kidneys, K. pneumoniae outcompeted E. coli in healthy mice but in diabetic mice E. coli outcompeted K. pneumoniae and caused severe pyelonephritis. Diabetic kidneys contained renal tubules laden with communities of E. coli UTI89 bacteria within an extracellular-matrix material. Diabetic mice also had glucosuria, which may enhance bacterial replication in the urinary tract. These data support that this murine diabetic UTI model is consistent with known characteristics of human diabetic UTI and can provide a powerful tool for dissecting this infection in the multifactorial setting of diabetes.
Cost-Efficient Sampling for Performance Prediction of Configurable Systems (T)

A key challenge of the development and maintenanceof configurable systems is to predict the performance ofindividual system variants based on the features selected. It isusually infeasible to measure the performance of all possible variants, due to feature combinatorics. Previous approaches predictperformance based on small samples of measured variants, butit is still open how to dynamically determine an ideal samplethat balances prediction accuracy and measurement effort. Inthis paper, we adapt two widely-used sampling strategies forperformance prediction to the domain of configurable systemsand evaluate them in terms of sampling cost, which considersprediction accuracy and measurement effort simultaneously. Togenerate an initial sample, we introduce a new heuristic based onfeature frequencies and compare it to a traditional method basedon t-way feature coverage. We conduct experiments on six realworldsystems and provide guidelines for stakeholders to predictperformance by sampling.
The Characteristics in the Sensitivity of Microfiber Fabry-Perot Interferometric Transducers

We inscribe a Fabry-Perot (FP) resonator in the microfiber utilizing the 193-nm UV exposure and the phase mask technique. Some new characteristics in contrast to the conventional counterparts are measured, which are attributed to the index change in the grating and the dispersion of the effective grating length, respectively. The FP spectral dependencies on external strain, temperature, and refractive index are investigated. Our fabricated structures can have potential of acting as ultrasonic transducers and photo acoustic imaging.
A combined experimental and numerical analysis on the seismic behavior of short reinforced concrete columns with different structural sizes and axial compression ratios

The results of an experimental program on eight short reinforced concrete columns having different structural sizes and axial compression ratios subjected to monotonic/cyclic lateral loading were reported. A 3D mesoscopic simulation method for the analysis of mechanical properties of reinforced concrete members was established, and then it was utilized as an important supplement and extension of the traditional experimental method. Lots of numerical trials , based on the restricted experimental results and the proposed 3D mesoscopic simulation method, were carried out to sufficiently evaluate the seismic performances of short reinforced concrete columns with different structural sizes and axial compression ratios. The test results indicate that (1) the failure pattern of reinforced concrete columns can be significantly affected by the shear-span ratio; (2) increasing the axial compression ratio could improve the load capacity of the reinforced concrete column, but the deformation capacity would be restricted and the failure mode would be more brittle, consequently the energy dissipation capacity could be deteriorated; and (3) the load capacity, the displacement ductility, and the energy dissipation capacity of the short reinforced concrete columns all exhibit clear size effect, namely, the size effect could significantly affect the seismic behavior of reinforced concrete columns.
Recursive Programs for Document Spanners

A document spanner models a program for Information Extraction (IE) as a function that takes as input a text document (string over a finite alphabet) and produces a relation of spans (intervals in the document) over a predefined schema. A well studied language for expressing spanners is that of the regular spanners: relational algebra over regex formulas, which are obtained by adding capture variables to regular expressions. Equivalently, the regular spanners are the ones expressible in non-recursive Datalog over regex formulas (extracting relations that play the role of EDBs from the input document). In this paper, we investigate the expressive power of recursive Datalog over regex formulas. Our main result is that such programs capture precisely the document spanners computable in polynomial time. Additional results compare recursive programs to known formalisms such as the language of core spanners (that extends regular spanners by allowing to test for string equality) and its closure under difference. Finally, we extend our main result to a recently proposed framework that generalizes both the relational model and document spanners.
A²-MAC: An Adaptive, Anycast MAC Protocol for Wireless Sensor Networks

Energy constraints in wireless sensor nodes necessitate the design and development of energy-efficient MAC protocols to arbitrate access to the shared communication medium. While there exists a plethora of sensor MAC protocols, these protocols do not individually vary the duty-cycle of each sensor according to local connectivity status, to maximize energy savings. In this paper, we propose A^2-MAC - an Adaptive, Anycast MAC protocol for low-powered wireless sensor networks. It utilizes: (i) a random wakeup schedule, such that each node can independently and randomly wakeup in each cycle without coordination and time synchronization; (ii) adaptive duty-cycles based on network topology; and (iii) adaptive anycast forwarders selection, which allows each node to transmit to any member in its forwarding set. There are two key adaptive mechanisms in A^2-MAC: (i) each node varies its duty-cycle and set of forwarding nodes such that energy consumption can be locally minimized for a given local delay performance objective; and (ii) nodes cooperatively reduce the duty-cycles required of their forwarding nodes, depending on local network connectivity. By allowing nodes to operate with different duty-cycles and forwarding sets, A^2-MAC achieves better energy-latency tradeoffs and extends node lifetime substantially, while providing good end-to-end latency.
An Ultra Low-Power Non-Volatile Memory Design Enabled by Subquantum Conductive-Bridge RAM

Conductive-bridge RAM (CBRAM) memory cells offer speed, voltage, and energy advantages over floating gate flash cells. Here, we describe a memory design which carries these cell-level advantages up to the product level, achieving 100x lower read and write power and 10x lower standby power than typical flash-based designs.
Is a Rigorous Agile Methodology the Best Development Strategy for Small Scale Tech Startups

Recently, Agile development processes have become popular in the software development community, and have been shown to be effective in large organizations. However, given that the communication and cooperation dynamics in startup companies are very different from that of larger, more established companies, and the fact that the initial focus of a startup might be significantly different from its ultimate goal, it is questionable whether a rigid process model that works for larger companies is appropriate in tackling the problems faced by a startup. When we scale down even further and observe the small scale startup with only a few members, many of the same problems that Agile methodology sets out to solve do not even exist. Then, for a small scale startup, is it still worth putting the resources into establishing a process model? Do the benefits of adopting an Agile methodology outweigh the opportunity cost of spending the resources elsewhere? This paper examines the advantages and disadvantages of adopting an Agile methodology in a small scale tech startup and compares it to other process models, such as the Waterfall model and Lean Startup. In determining whether a rigorous agile methodology is the best development strategy for small scale tech startups, we consider the metrics of cost, time, quality, and scope in light of the particular needs of small startup organizations, and present a case study of a company that has needed to answer this very question.
Thompson Sampling is Asymptotically Optimal in General Environments

We discuss a variant of Thompson sampling for nonparametric reinforcement learning in a countable classes of general stochastic environments. These environments can be non-Markov, non-ergodic, and partially observable. We show that Thompson sampling learns the environment class in the sense that (1) asymptotically its value converges to the optimal value in mean and (2) given a recoverability assumption regret is sublinear.
Processing XML queries and updates on map/reduce clusters

In this demo we will showcase a research prototype for processing queries and updates on large XML documents. The prototype is based on the idea of statically and dynamically partitioning the input document, so to distribute the computing load among the machines of a Map/Reduce cluster. Attendees will be able to run predefined queries and updates on documents conforming to the XMark schema, as well as to submit their own queries and updates.
HYDRAULIC SERVO SYSTEM USING A FEEDBACK LINEARIZATION CONTROLLER AND DISTURBANCE OBSERVER - SENSITIVITY OF SYSTEM PARAMETERS -

In this study, the control performance of a hydraulic servo system with a feedback linearization compensator is investigated. The focus of this study is set on the quantitative investigation of the effects(sensitivities) of disturbances and system parameters’ variation on control performances of the hydraulic control system. Finally, verifies the efficacy of a disturbance observer to overcome the control performances deterioration due to system parameters' variations, disturbances in the control system.
Semi-Automatic Image Labelling Using Depth Information

Image labeling tools help to extract objects within images to be used as ground truth for learning and testing in object detection processes. The inputs for such tools are usually RGB images. However with new widely available low-cost sensors like Microsoft Kinect it is possible to use depth images in addition to RGB images. Despite many existing powerful tools for image labeling, there is a need for RGB-depth adapted tools. We present a new interactive labeling tool that partially automates image labeling, with two major contributions. First, the method extends the concept of image segmentation from RGB to RGB-depth using Fuzzy C-Means clustering, connected component labeling and superpixels, and generates bounding pixels to extract the desired objects. Second, it minimizes the interaction time needed for object extraction by doing an efficient segmentation in RGB-depth space. Very few clicks are needed for the entire procedure compared to existing, tools. When the desired object is the closest object to the camera, which is often the case in robotics applications, no clicks at all are required to accurately extract the object.
Optimization and Implementation on Fpga of the DCT/IDCT Algorithm

In this paper, we present a comparison between two methods, the modified Loeffler algorithm (11 MUL and 29 ADD) and distributed arithmetic, to implement the DCT/IDCT algorithm for MPEG or H.26x video compression using VHDL description language. The implementation has been achieved on Altera Stratix EP1S10 FPGA which provides a dedicated DSP blocks required for common signal processing functions. A new solution based on this DSP blocks used to implement multipliers for the modified Loeffler algorithm in order to optimize speed and area
Statistical Chinese spoken document retrieval using latent topical information

Information retrieval which aims to provide people with easy access to all kinds of information is now becoming more and more emphasized. However, most approaches to information retrieval are primarily based on literal term matching and operate in a deterministic manner. Thus their performance is often limited due to the problems of vocabulary mismatch and not able to be steadily improved through use. In order to overcome these drawbacks as well as to enhance the retrieval performance, in this paper we explore the use of topical mixture model for statistical Chinese spoken document retrieval. Various kinds of model structures and learning approaches were extensively investigated. In addition, the retrieval capabilities were verified by comparison with the conventional vector space model and latent semantic indexing model, as well as our previously presented HMM/N-gram retrieval model. The experiments were performed on the TDT2 Chinese collection. Noticeable improvements in retrieval performance were obtained.
A High Certificate Authority Scheme for Authentication in Mobile Ad hoc Networks

: In mobile ad hoc networks (MANETs), it is easy to launch wormhole, man-in-the-middle and denial of service (DoS) attacks, or to impersonate another node. Trust based cross layer approach established a network consisting confidentiality and authentication of packets in both routing and link layers. , in this paper, we propose to develop an enhanced distributed certificate authority scheme to provide data integrity, thus making the network more secure from both inside and outside attacks. The proposed scheme makes use of Shamir’s secret sharing scheme along with a redundancy technique to support certificate renewal and revocation. The malicious nodes are detected by the trusting mechanism by monitoring the behavior hop by hop. By simulation results, we show that the proposed scheme achieves more packet delivery ratio while attaining less delay and overhead, compared with the trust based cross layer approach.
Multiple approaches to analysing query diversity

In this paper we examine user queries with respect to diversity: providing a mix of results across different interpretations. Using two query log analysis techniques (click entropy and reformulated queries), 14.9 million queries from the Microsoft Live Search log were analysed. We found that a broad range of query types may benefit from diversification. Additionally, although there is a correlation between word ambiguity and the need for diversity, the range of results users may wish to see for an ambiguous query stretches well beyond traditional notions of word sense.
Persistence of Cerebral Palsy Diagnosis

We examined the stability of nondisabling and disabling cerebral palsy at age 2 in a longitudinally followed tri-county low-birth-weight (<2000 g) birth cohort. A total of 1105 newborns were enrolled, 901 (81.5%) survived to age 2, and 86% (n = 777) were followed up. Of the 113 cerebral palsy diagnoses at age 2, 61 (9% of the cohort, n = 61/777) had disabling cerebral palsy and 52 (7%, n = 52/777) had nondisabling cerebral palsy. Of 48 followed children diagnosed with disabling cerebral palsy at age 2, 98% were again classified as having cerebral palsy at school age, and 1 had an uncertain cerebral palsy status. By contrast, 41% (n = 17) of the 43 children diagnosed with nondisabling cerebral palsy at age 2 were classified as not having cerebral palsy. Of the 517 followed children who were not diagnosed with cerebral palsy at age 2, 7% (n = 35) were classified as having late emerging nondisabling cerebral palsy at school age.