Miracle-dz/UniFAR-FTUs huggingface dataset:
An ultrasensitive CMOS magnetic biosensor array with correlated double counting noise suppression

This paper presents a scalable and ultrasensitive frequency-shift magnetic biosensing array scheme. The theoretical limit of the sensor noise floor is shown to be dominated by the phase noise of the sensing oscillators. To increase the sensitivity, a noise suppression technique, Correlated Double Counting (CDC), is proposed with no power overhead. As an implementation example, a 64-cell sensor array is designed in a standard 65nm CMOS process. The CDC scheme achieves an additional 6dB noise suppression. The magnetic sensing capability of the presented sensor is verified by detecting micron size magnetic particles with an SNR of 14.6dB for a single bead and an effective dynamic range of at least 74.5dB.
Profile of Creativity and Innovation Among Higher Learning Institution Students in Malaysia

3 Abstract: The Malaysian Creativity and Innovation Instrument (MyCrIn) was used in this study to measure the levels of creativity and innovation among students at a higher learning institution (HLI). This study aims to profile students of HLI according to levels of creativity and innovation based on gender and ethnicity. The instrument contains 275 items, of which 180 are Likert scale items, 72 are dichotomous scale items and 23 are partial credit items. The MyCrIn is comprised of five constructs: Higher Order Thinking (HOT; 72 items), Curiosity (CUR; 24 items), Sensitivity (SEN; 64 items), Visionary (VIS; 45 items) and Adaptable to Change (ATC; 70 items). The MyCrIn was administered to 300 undergraduate students from one public university in Malaysia. Results show that the five constructs have a high reliability index (above .9). Results indicate that males have a higher level of higher order thinking ability (HOT:F = 5835, p =.001) and a higher visionary score (VIS:t = 5445, p =.000) compared to females. Student profiling of Malays, Chinese and other ethnicities showed no differences. In conclusion, the study has been able to profile HLI students according to their levels of creativity and innovation. This is expected to help administrators, university lecturers and employers in student selection in order to fulfil the needs of the employment sector. This can facilitate the channelling of creative and innovative minds toward the development of the nation.
Kinematic self-similar solutions in general relativity

The gravitational interaction is scale-free in both Newtonian gravity and general theory of relativity. The concept of self-similarity arises from this nature. Self-similar solutions reproduce themselves as the scale changes. This property results in great simplification of the governing partial differential equations. In addition, some self-similar solutions can describe the asymptotic behaviors of more general solutions. Newtonian gravity contains only one dimensional constant, the gravitational constant, while the general relativity contains another dimensional constant, the speed of light, besides the gravitational constant. Due to this crucial difference, incomplete similarity can be more interesting in general relativity than in Newtonian gravity. Kinematic self-similarity has been defined and studied as an example of incomplete similarity in general relativity, in an effort to pursue a wider application of self-similarity in general relativity. We review the mathematical and physical aspects of kinematic self-similar solutions in general relativity.
Positive minimal realizations of continuous-discrete linear systems with transfer function with separable denominator or numerator

The positive minimal realization problem for continuous-discrete linear single-input, single-output (SISO) systems is formulated. Two special case of the continuousdiscrete systems are analyzed. Method based on the state variable diagram for finding positive minimal realizations of given proper transfer functions is proposed. Sufficient conditions for the existence of positive minimal realizations of given proper transfer functions with separable numerator or transfer functions with separable denominator are established. Two procedures for computation of positive minimal realizations are proposed and illustrated by numerical examples.
Modelling of Thermal Power Plant using Full Factorial Design based ANFIS

Adaptive network based fuzzy inference system (ANFIS) is an intelligent neuro-fuzzy technique used for modelling and controlling ill-defined and uncertain systems. ANFIS is based on the input-output data pairs of the system under consideration. The size of the input-output data set is very crucial when the data available is very less and the generation of data is a costly affair. Under such circumstances, optimization in the number of data used for learning is of prime concern. In this paper we have proposed an ANFIS based system modelling where the number of data pairs employed for training is minimized by application of an engineering statistical technique called full factorial design. Our proposed method is experimentally validated by applying it to the data obtained from the thermal power plant of North Eastern Electrical Power Corporation Limited (NEEPCO) situated at Kathalguri, Assam, India. By employing our proposed method the number of data required for training the ANFIS network could be significantly reduced and thereby computation time as well as computation complexity is remarkably reduced. The results obtained by applying our proposed method are compared with those obtained by using conventional ANFIS network. It was found that our model compares favourably well with conventional ANFIS model
Effect of the prefabricated routing track distribution on FPGA area-efficiency

In most commercial field programmable gate arrays (FPGA's) the number of wiring tracks in each channel is the same across the entire chip. A long-standing open question for both FPGA's and channeled gate arrays is whether or not some uneven distribution of routing tracks across the chip would lead to an area benefit. For example, many circuit designers intuitively believe that most congestion occurs near the center of a chip, and hence expect that having wider routing channels near the chip center would be beneficial. In this paper, we determine the relative area-efficiency of several different routing track distributions. We first investigate FPGA's in which horizontal and vertical channels contain different numbers of tracks in order to determine if such a directional bias provides a density advantage. Second, we examine routing track distributions in which the track capacities vary from channel to channel. We compare the area efficiency of these nonuniform routing architectures to that of an FPGA with uniform channel capacities across the entire chip. The main result is that the most area-efficient global routing architecture is one with uniform (or very nearly uniform) channel capacities across the entire chip in both the horizontal and vertical directions. This paper shows why this result, which is contrary to the intuition of many FPGA architects, is true. While a uniform routing architecture is the most area-efficient, several nonuniform and directionally biased architectures are fairly area-efficient provided that appropriate choices are made for the pin positions on the logic blocks and the logic block array aspect ratio.
Scaling Up a Distributed Computing Of Similarity Coefficient with Mapreduce

The work presented in this paper addresses the design and implementation of a Hadoop application and the experiments performed with this application in order to compute the Jaccard similarity metrics for two very large graphs. The algorithm involved uses the MapReduce programming model, whose aim is to distribute the computing process over several machines in order to reduce the overall running time. As a distributed programming model, MapReduce is one of the most important techniques behind Cloud computing metaphor, focused on data intensive computing in clustered environments. Hadoop open source framework provides to developers a Java API for implementing applications based on MapReduce programming paradigm. In this philosophy, the main task is divided into several smaller subtasks that can be executed or re-executed on any node in the cluster. The experimental results presented in this paper were obtained after performing various tests over two large data sets (WEBSPAM-UK 2007 and Slashdot) on a distributed cluster.
Heartscope: a software tool addressing autonomic nervous system regulat

The evaluation of cardiovascular control system requires ad-hoc software tools specifically designed to address the complexity of the regulation mechanisms in a multiparametric and multidisciplinary perspective. We introduce HeartScope a Windows-based C++ tool that brings together the most advanced signal processing methods for the analysis of cardiovascular regulation in a flexible and friendly framework
Designing Organizational Change in IT : A Theory Nexus

This paper presents an artifact to support the development of organizational change strategies. Based on a study of organizational change approaches we derived 10 alternative design theories. Each theory relates the conditions under which a specific change approach such as reengineering is prescriptive for an organization. Using these theories, we designed a theory nexus called the Strategic Change Nexus. This nexus is an artifact that binds together the 10 design theories into a cohesive recommendation specific to an organization’s unique strategic vision and context. The nexus leads to an analysis that produces a list-of-fit that reveals the degree to which each of the change design theories fits the organization’s setting. The Strategic Change Nexus was developed and evaluated within a field study research project involving three participating companies. Using action research, the IT organization in two of these companies collaborated with the researchers in providing promising evaluations of the version of the nexus described in this paper.
Review of Automatic Feature Extraction from High-Resolution Optical Sensor Data for UAV-Based Cadastral Mapping

Unmanned Aerial Vehicles (UAVs) have emerged as a rapid, low-cost and flexible acquisition system that appears feasible for application in cadastral mapping: high-resolution imagery, acquired using UAVs, enables a new approach for defining property boundaries. However, UAV-derived data are arguably not exploited to its full potential: based on UAV data, cadastral boundaries are visually detected and manually digitized. A workflow that automatically extracts boundary features from UAV data could increase the pace of current mapping procedures. This review introduces a workflow considered applicable for automated boundary delineation from UAV data. This is done by reviewing approaches for feature extraction from various application fields and synthesizing these into a hypothetical generalized cadastral workflow. The workflow consists of preprocessing, image segmentation, line extraction, contour generation and postprocessing. The review lists example methods per workflow step—including a description, trialed implementation, and a list of case studies applying individual methods. Furthermore, accuracy assessment methods are outlined. Advantages and drawbacks of each approach are discussed in terms of their applicability on UAV data. This review can serve as a basis for future work on the implementation of most suitable methods in a UAV-based cadastral mapping workflow.
Knowledge-Lean Approaches to Metonymy Recognition

Current approaches to metonymy recognition are mainly supervised, relying heavily on the manual annotation of training and test data. This forms a considerable hindrance to their application on a wider scale. This dissertation therefore aims to relieve the knowledge acquisition bottleneck with respect to metonymy recognition by examining knowledge-lean approaches that reduce this need for human effort. This investigation involves the study of three algorithms that constitute an entire spectrum of machine learning approaches — unsupervised, supervised and semi-supervised ones. Chapter 2 will discuss an unsupervised approach to metonymy recognition, and will show that promising results can be reached when the data are automatically annotated with grammatical information. Although the robustness of these systems is limited, they can serve as a pre-processing step for the selection of useful training data, thereby reducing the workload for human annotators. Chapter 3 will investigate memory-based learning, a “lazy” supervised algorithm. This algorithm, which relies on an extremely simple learning stage, is able to replicate the results of more complex systems. Yet, it will also become clear that the performance of this algorithm, like that of others in the literature, depends heavily on grammatical annotation. Finally, chapter 4 will present a semi-supervised algorithm that produces very promising results with only ten labelled training instances. In addition, it will be shown that less than half of the training data from chapter 3 can lead to the same performance as the entire set. Semantic information in particular will prove very useful in this respect. In short, this dissertation presents experimental results which indicate that the knowledge acquisition bottleneck in metonymy recognition can be relieved with unsupervised and semi-supervised methods. These approaches may make the extension of current algorithms to a wide-scale metonymy resolution system a much more feasible task.
Layer Bonding of Solvent-Cast Thin Films for Pharmaceutical Solid Dosage Forms

In the pharmaceutical industry, the conventional tablet manufacturing process, a batchbased process based on solid powder handling, presents challenges such as inhomogeneous blending between Active Pharmaceutical Ingredients (APIs) and excipients, low yield, and low production rate. These difficulties can be resolved by the realization of a continuous manufacturing process through co-processing of APIs and excipients in the liquid-phase solution. A solvent-cast thin film, produced from liquid solution, can then be manufactured into tablets by way of a folding process. In order to design detailed compaction processes and machines, required compression pressure for layer bonding and mechanical properties of materials should also be investigated. The bonding strength of solvent-cast thin film layers was quantitatively measured by lap shear test. Based on this measurement, bonding threshold pressure was proposed as an indicator showing degree of bonding. At the same time, the layer bonding mechanism of solvent-cast thin films was interpreted as an interdiffusion of amorphous polymer chain end segments. In this context, relative contact area, polymer mobility, which is measured by glass transition temperature, and dwell time were proposed as critical factors in determining bonding threshold pressure. The relationships between those critical factors and process parameters such as surface roughness, residual water and excipient concentration, and compression rate were investigated. The mechanical and viscoelastic properties of solvent-cast thin films were also characterized. Solvent-cast thin films showed ductile-brittle transition, i.e., change of indentation hardness and strength factors among tensile properties with respect to residual water concentration. Changes of creep modulus and tensile properties at various stress levels and strain rates were also observed. Thesis Supervisor: Dr. Jung-Hoon Chun Title: Professor of Mechanical Engineering
A CONTINUOUS-TIME GARCH MODEL FOR STOCHASTIC VOLATILITY WITH DELAY

We consider a (B, S)-security market with standard riskless asset B(t) = B0ert and risky asset S(t) with stochastic volatility depending on time t and the history of stock price over the interval [t − τ, t]. The stock price process S(t) satisfies a stochastic delay differential equation (SDDE) with past-dependent diffusion coefficient. We state some results on option pricing in such a market and its completeness. We derive a continuous-time analogue of GARCH(1,1) model for our past-dependent volatility. We then show that the equation for the expected squared volatility under the risk-neutral measure is a deterministic delay differential equation, and we construct the solutions for such an equation. We also construct numerical solutions and develop estimation procedures to the option pricing problem, and show the comparison of numerical results.
Tissue-resident memory CD8+ T cells continuously patrol skin epithelia to quickly recognize local antigen

Recent work has demonstrated that following the clearance of infection a stable population of memory T cells remains present in peripheral organs and contributes to the control of secondary infections. However, little is known about how tissue-resident memory T cells behave in situ and how they encounter newly infected target cells. Here we demonstrate that antigen-specific CD8+ T cells that remain in skin following herpes simplex virus infection show a steady-state crawling behavior in between keratinocytes. Spatially explicit simulations of the migration of these tissue-resident memory T cells indicate that the migratory dendritic behavior of these cells allows the detection of antigen-expressing target cells in physiologically relevant time frames of minutes to hours. Furthermore, we provide direct evidence for the identification of rare antigen-expressing epithelial cells by skin-patrolling memory T cells in vivo. These data demonstrate the existence of skin patrol by memory T cells and reveal the value of this patrol in the rapid detection of renewed infections at a previously infected site.
Extended evaluation of the virologic, immunologic, and clinical course of volunteers who acquired HIV-1 infection in a phase III vaccine trial of ALVAC-HIV and AIDSVAX B/E.

BACKGROUND The Thai Phase III Trial of ALVAC-HIV and AIDSVAX B/E showed an estimated vaccine efficacy (VE) of 31% to prevent acquisition of human immunodeficiency virus (HIV). Here we evaluated the effect of vaccination on disease progression after infection. METHODS CD4(+) T-cell counts and HIV viral load (VL) were measured serially. The primary analysis evaluated vaccine efficacy (VEP) as the percent reduction (vaccine vs placebo) in cumulative probability of a primary composite endpoint of clinical and CD4(+) count components at prespecified time points after infection. Secondary analyses of biomarker-based endpoints were assessed using marginal mean and linear mixed models. RESULTS There were 61 endpoints in the modified intent-to-treat cohort (mITT; n = 114). There was no evidence for efficacy at 30, 42, 54, and 60 months in the mITT and per protocol (n = 90) cohorts. Estimated VEP (mITT) was15.8% (-21.9, 41.8) at 60 months postinfection. There was weak evidence of lower VL and higher CD4(+) count at 60 and 66 months in the vaccine group. Lower mucosal VL was observed among vaccine recipients, primarily in semen (P = .04). CONCLUSIONS Vaccination did not affect the clinical course of HIV disease after infection. A potential vaccine effect on the genital mucosa warrants further study.
Automatic Clinical Question Answering Based on UMLS Relations

We propose an approach to automatic clinical question answering based on UMLS relations. Rules are defined to identify the medical concepts and their relations in the questions and documents with the help of Metamap transfer and SemRep. The phrase-level answers are generated through matching concepts and relations between question and documents. Experiment shows that our approach obtains high precision and recall.
Miniemulsion polymerization as a versatile tool for the synthesis of functionalized polymers

The miniemulsion technique is a particular case in the family of heterophase polymerizations, which allows the formation of functionalized polymers by polymerization or modification of polymers in stable nanodroplets. We present here an overview of the different polymer syntheses within the miniemulsion droplets as reported in the literature, and of the current trends in the field.
Evaluation of reactive mobile ad hoc wireless networks over different topological network node densities

This paper examines the performance of reactive ad hoc wireless protocols namely AODV and DSR under different network densities. The relation between connectivity and density is identified in this research. Therefore node density is vital in determining the performance of the network. The probability for a dense network to achieve connection is significantly higher than its sparse counterpart. But when these networks communicate through each other there are many other issues that will affect the performance of network. On Demand MANET protocols are considered to perform better then proactive protocols in highly dynamic and robust networks, therefore they are best suited to be tested against topologies with inconsistent densities. The consideration of the paper does not look into transmission power and energy consumption but is focused on the rate needed by the protocol to converge and settle consistently on a high delivery ratio, fewer dropped packets and less delay.
ISIPC: Instant Synchronous Interprocess Communication

Interprocess communication (IPC) is often used to exchange data between cooperative processes, and the performance of IPC largely determines the processing time of application programs. Moreover, it is used for most of the kernel calls in a microkernel-based operating system (OS). Therefore, the performance of IPC affects the performance of the OS. In addition, the completion of the messagepassing mechanism has to be indicated by executing a receive operation in order to maintain synchronization. Thus, two operations are required in this mechanism to complete the communication. On the other hand, no receive operation is required to indicate the completion of the communication in the case of asynchronous communication; however, in this case, no proof of the data being received is provided to the sender process. In this paper, we propose an instant synchronous interprocess communication (ISIPC) mechanism that can achieve both instantaneous communication and data synchronization. ISIPC has two functions: push function and sack function. We describe the design of the ISIPC mechanism and also its implementation on the Tender operating system. In addition, we present the evaluation results for the ISIPC mechanism.
An Artificial Immune Model for Abnormal Fluctuation of Stock Price

The abnormal fluctuation of stock price is a harmful factor for the stock market, and how to correctly identify the abnormal fluctuation seems to be important. For the prevailing uncertain conditions in the stock market, static method is limited during detecting anomaly. In this paper, artificial immune principle is used to distinguish the "self" and "non-self" of stock price fluctuation through immune method, such as Negative Selection Algorithm, and a capable artificial immune model SPAF-M is built to intelligently sense, detect and defense the abnormal fluctuation of stock price. In order to improve risk management of the stock market, a novel risk evaluation function is proposed to judge an unknown object anomaly or not. It will be a challenge to apply immunity idea to stock market in our future work.