Miracle-dz/UniFAR-FTUs huggingface dataset:
An Optimal Medium Access Control with Partial Observations for Sensor Networks

We consider medium access control (MAC) in multihop sensor networks, where only partial information about the shared medium is available to the transmitter. We model our setting as a queuing problem in which the service rate of a queue is a function of a partially observed Markov chain representing the available bandwidth, and in which the arrivals are controlled based on the partial observations so as to keep the system in a desirable mildly unstable regime. The optimal controller for this problem satisfies a separation property: we first compute a probability measure on the state space of the chain, namely the information state, then use this measure as the new state on which the control decisions are based. We give a formal description of the system considered and of its dynamics, we formalize and solve an optimal control problem, and we show numerical simulations to illustrate with concrete examples properties of the optimal control law. We show how the ergodic behavior of our queuing model is characterized by an invariant measure over all possible information states, and we construct that measure. Our results can be specifically applied for designing efficient and stable algorithms for medium access control in multiple-accessed systems, in particular for sensor networks.
Learning During Exploration: The Role of Behavioral Topography During Exploration in Determining Subsequent Adaptive Behavior in the Sprague-Dawley Rat (Rattus norvegicus)

Two investigations examine the hypothesis that one function of exploration is to create situations in which there is an opportunityto acquire useful information. In the first, male rats {Rattus nonvgicus, Sprague Dawley strain) with enriched (EC) or impoverished ( IC) experience ( leading to differences in exploratory behavior documented previously) were given an opportunity to explore an arena with a hidden escape route on two consecutive days. On the following day, subjects were chased by a mechanical device and the time required to escape the arena was recorded. No group differences were seen in pre-chase behaviors other than those related to the hidden escape route, or in stress-related behaviors while being chased. EC rats escaped significantly more quickly than IC rats, and a composite . score derived from pre-challenge behavior in the arena was correlated significantly with escape time under challenge. In the second experiment, EC and IC subjects were chased without previous experience in the area; EC rats escaped significantly more quickly than IC rats. In an analysis of the combined results from the two experiments, both environmental history and pre-challenge arena experience were found to exert significant influence on escape time. These findings demonstrate that different behaviors during exploration can lead to functionally significant differences in the information acquired as a result of exploration.
Performance Analysis of Genetic Algorithm with kNN and SVM for Feature Selection in Tumor Classification

Abstract—Tumor classification is a key area of research in the field of bioinformatics. Microarray technology is commonly used in the study of disease diagnosis using gene expression levels. The main drawback of gene expression data is that it contains thousands of genes and a very few samples. Feature selection methods are used to select the informative genes from the microarray. These methods considerably improve the classification accuracy. In the proposed method, Genetic Algorithm (GA) is used for effective feature selection. Informative genes are identified based on the T-Statistics, Signal-to-Noise Ratio (SNR) and F-Test values. The initial candidate solutions of GA are obtained from top-m informative genes. The classification accuracy of k-Nearest Neighbor (kNN) method is used as the fitness function for GA. In this work, kNN and Support Vector Machine (SVM) are used as the classifiers. The experimental results show that the proposed work is suitable for effective feature selection. With the help of the selected genes, GA-kNN method achieves 100% accuracy in 4 datasets and GA-SVM method achieves in 5 out of 10 datasets. The GA with kNN and SVM methods are demonstrated to be an accurate method for microarray based tumor classification.
Analysis and design of robust estimation filter for a class of continuous-time nonlinear systems

This article addresses the design of a multiconstrained robust estimation filter (MREF) for a class of continuous-time nonlinear systems in the presence of input and output disturbances. By constructing an augmented system, the MREF achieves the estimation of both states and faults, under existence conditions that are less restrictive than those associated with existing adaptive fault diagnosis observer (AFDO) and sliding mode observer design. Moreover, a detailed discussion on and comparison with the AFDO design are given. Furthermore, by introducing slack variables, improved results on MREF design are obtained such that different Lyapunov functions can be separately designed for multiple constraints. Simulation results are presented to illustrate our contributions.
Possible techniques for three dimensional hatching

This paper introduces a basic technique for drawing non-photorealistic images of volume models. The turtle graphics approach to imitating painting operations is implemented in 3D space. Objects are defined by sets of scattered range data. Analytically (that is, functionally represented) and procedurally defined geometric objects can also be used. The proposed technique is described in detail and painting examples that demonstrate its applicability to non-photorealistic rendering or hatching are provided.
How to cook a temporal proof system for your pet language

An abstract temporal proof system is presented whose program-dependent part has a high-level interface with the programming language actually studied. Given a new language, it is sufficient to deline the interface notions of atomic transitions, justice, and fairness in order to obtain a full temporal proof system for this language. This construction is particularly useful for the analysis of concurrent systems. We illustrate the construction on the shared-variable model and on CSP. The generic proof system is shown to be relatively complete with respect to pure first-order temporal logic.
Evaluation of shear bond strength of zirconia to tooth structure after different zirconia surface treatment techniques

This study aimed to evaluate the effect of zirconia different surface treatments (primer, sandblast with 50μmAl2O3, Er,Cr:YSGG laser) on shear bond strength between zirconia surface and resin cement. Material and methods: Sixty presintered Y-TZP zirconia cylinder specimens (IPS e.max ZirCAD, Ivoclar vivadent) will be fabricated and sintered in high temperature furnace of (1500 C for 8 hours) according to manufacturer's instructions to the selected size and shape of (5mm. in diameter and 6mm in height). All specimens were ground flat using 600.800. 1000.1200, aluminum oxide abrasive paper to obtain a standardized surface roughness. Surface roughness values were then recorded in µm using surface roughness tester (profilometer) to obtain a standardized data base line for all samples. The specimens were then randomly divided into three main groups (n=20); group A: no surface treatment (control group), group B: specimens in this group treated with 50μm Al2O3 and group C: specimens in this group treated with Er,Cr:YSGG laser. Sixty sound human premolars were used in this study, after construction of acrylic blocks, the occlusal surface of the teeth were ground flat, with diamond cutting disk to obtain a flat dentine surface . Prior to cementation of zirconia cylinders to tooth specimens subgroups (A1,B1,C1) will receive a coat of metal/zirconia primer and left to react for three minutes, while the subgroups (A2,B2,C2) were left undisturbed. Bonding surface of zirconia cylinder was then luted with SpeedCEM self adhesive resin cement under a static load of 2Kg. placed on the vertical arm of the surveyor and allowed to auto cure for 4minutes.The final cemented specimens were then stored in distilled water at room temperature for 24hours. All specimens were subjected to shear loading force in a universal testing machine at crosshead speed of 1mm/min. The shear bond strength values were analyzed statistically with one-way ANOVA; the fractured surfaces of zirconia cylinders were examined with a stereo-microscope to observe the failure mode. Results: The air borne-particle of 50μm followed by primer application showed significantly the higher bond strength than other groups. Conclusion: Within the limitation of this study, the results showed that sandblasting the bonding surface of zirconium cylinders with 50μmAl2O3 produced the highest values of shear bond strength , also the use of primer enhanced shear bond strength as well.
Algorithm Engineering for Color-Coding to Facilitate Signaling Pathway Detection

To identify linear signaling pathways, Scott et al. [RECOMB, 2005] recently proposed to extract paths with high interaction probabilities from protein interaction networks. They used an algorithmic technique known as color-coding to solve this NP-hard problem; their implementation is capable of finding biologically meaningful pathways of length up to 10 proteins within hours. In this work, we give various novel algorithmic improvements for color-coding, both from a worst-case perspective as well as under practical considerations. Experiments on the interaction networks of yeast and fruit fly as well as a testbed of structurally comparable random networks demonstrate a speedup of the algorithm by orders of magnitude. This allows more complex and larger structures to be identified in reasonable time; finding paths of length up to 13 proteins can even be done in seconds and thus allows for an interactive exploration and evaluation of pathway candidates.
Growth hormone-deficient dwarfism in the rat: a new mutation.

Mutations in animals have provided insight into many aspects of normal and pathological human physiology. This paper reports the discovery and initial characterization of a new mutant dwarf rat. The mutation, inherited as an autosomal recessive, arose spontaneously in a breeding colony of Lewis rats at the Medical Research Council Cellular Immunology Unit, Sir William Dunn School of Pathology, Oxford, U.K., in 1985 and the strain has now been established both in Oxford and at Mill Hill. Body growth in the mutant is retarded such that at 3 months of age both males and females weigh approximately 40% less than their normal litter-mates, and continue to grow at a slower rate. The mutants show a selective reduction in pituitary GH synthesis and storage (pituitary GH concentrations were approximately 10% of normal in males and 6% in females). The concentration of their anterior pituitary trophic hormones (LH, TSH, prolactin and ACTH) were within the normal range in dwarf animals. Exogenous GH treatment for 5 days resulted in an increase in growth rate from 1.5 +/- 0.3 to 3.9 +/- 0.4 g/day in male mutants, and 0.8 +/- 0.2 to 3.1 +/- 0.1 g/day in females. Longitudinal bone growth rates were more than doubled by this treatment from 49 +/- 5 to 100 +/- 10 micron/day in females and from 52 +/- 11 to 131 +/- 16 micron/day in males. Dot blot and Northern blot analysis of pituitary mRNA extracts revealed that the GH message in mutants was between 20 and 25% of normal, and that the GH transcript was of normal size. (ABSTRACT TRUNCATED AT 250 WORDS)
Space multiplexed multiphoton microscopy by temporal focusing of ultrashort pulses

The ability to perform optical sectioning is one of the great advantages of laser-scanning microscopy. This introduces, however, a number of difficulties due to the scanning process, such as lower frame rates due to the serial acquisition process. Here we show that by introducing spatiotemporal pulse shaping techniques to multiphoton microscopy it is possible to obtain full-frame depth resolved imaging completely without scanning. Our method relies on temporal focusing of the illumination pulse. The pulsed excitation field is compressed as it propagates through the sample, reaching its shortest duration at the focal plane, before stretching again beyond it. Combining temporal focusing with line-scanning microscopy results in an enhanced depth resolution, equivalent to that achieved by point scanning. Both the scanningless and the line-scanning techniques are applied to obtain depth-resolved two-photon excitation fluorescence (TPEF) images of drosophila egg-chambers.
Adaptive time-domain pre-emphasis technique for multi-gigabit VLSI systems

In this paper, we describe the application of adaptive pulse-width modulated (PWM) pre-emphasis to the equalization of higher-order copper channels. This method provides an alternative to FIR pre-emphasis with advantages in the light of developments in modern CMOS scaling. However additional high-frequency noise which is typical for strong PWM pre-emphasis setting can be a problem. Our research is focused on optimatization of the standard PWM scheme for adaptive PWM pre-emphasis method. Finally, data-dependent adaptive PWM pre-emphasis technique is implemented in Agilent ADS environment.
Automated Raman spectral preprocessing of bone and other musculoskeletal tissues

Raman spectroscopy of bone is complicated by fluorescence background and spectral contributions from other tissues. Full utilization of Raman spectroscopy in bone studies requires rapid and accurate calibration and preprocessing methods. We have taken a step-wise approach to optimize and automate calibrations, preprocessing and background correction. Improvements to manual spike removal, white light correction, software image rotation and slit image curvature correction are described. Our approach is concisely described with a minimum of mathematical detail.
Can “sense of presence” experiences in bereavement be conceptualised as spiritual phenomena?

This article explores the possibility of conceptualising the frequently occurring experience of “sensing the presence of the deceased” in bereavement as a spiritual phenomenon and examines how such a conceptualisation can be related to two recent perspectives in the field of bereavement research, “continuing bonds” and “meaning-making. ” It is argued that “sense of presence” experiences are expressions of the continuing relationship with the deceased that can be spiritually understood but that pose various challenges for their meaningful integration into the bereaved person's worldview or meaning structures–something that may need to be more explicitly incorporated into current theoretical frameworks. It is suggested that these experiences can be the catalyst for “post-traumatic growth” through a socially mediated and interactive narrative exploration and that this has important implications for bereavement counselling and therapy.
FARA: reorganizing the addressing architecture

sloppy This paper describes FARA, a new organization of, network architecture concepts. FARA (Forwarding directive, Association, and Rendezvous Architecture) defines an abstract model with considerable generality and flexibility, based upon the decoupling of end-system names from network addresses. The paper explores the implications of FARA and the range of architecture instantiations that may be derived from FARA. As an illustration, the paper outlines a particular derived architecture, M-FARA, which features support for generalized mobility and multiple realms of network addressing.
Towards dependable data repairing with fixing rules

One of the main challenges that data cleaning systems face is toautomaticallyidentify and repair data errors in adepend- ablemanner. Though data dependencies (a.k.a.integrity constraints) have been widely studied to capture errors in data, automated and dependable data repairing on these errors has remained a notoriously hard problem. In this work, we introduce an automated approach for dependably repairing data errors, based on a novel class offixing rules. A fixing rule contains an evidence pattern, a set of nega- tive patterns, and a fact value. The heart of fixing rules is deterministic: given a tuple, the evidence pattern and the negative patterns of a fixing rule are combined to precisely capture which attribute is wrong, and the fact indicates how to correct this error. We study several fundamental prob- lems associated with fixing rules, and establish their com- plexity. We develop ecient algorithms to check whether a set of fixing rules is consistent, and discuss approaches to resolve inconsistent fixing rules. We also devise ecient algorithms for repairing data errors using fixing rules. We experimentally demonstrate that our techniques outperform other automated algorithms in terms of the accuracy of re- pairing data errors, using both real-life and synthetic data.
Nanobeam Mechanics: Elasticity, Strength, and Toughness of Nanorods and Nanotubes

The Young's modulus, strength, and toughness of nanostructures are important to proposed applications ranging from nanocomposites to probe microscopy, yet there is little direct knowledge of these key mechanical properties. Atomic force microscopy was used to determine the mechanical properties of individual, structurally isolated silicon carbide (SiC) nanorods (NRs) and multiwall carbon nanotubes (MWNTs) that were pinned at one end to molybdenum disulfide surfaces. The bending force was measured versus displacement along the unpinned lengths. The MWNTs were about two times as stiff as the SiC NRs. Continued bending of the SiC NRs ultimately led to fracture, whereas the MWNTs exhibited an interesting elastic buckling process. The strengths of the SiC NRs were substantially greater than those found previously for larger SiC structures, and they approach theoretical values. Because of buckling, the ultimate strengths of the stiffer MWNTs were less than those of the SiC NRs, although the MWNTs represent a uniquely tough, energy-absorbing material.
Multiobjective design of permanent magnet synchronous machines based on analytical sub-domain particle swarm optimization

In this paper, multiobjective design optimization (MDO) of three-phase permanent magnet synchronous machines is presented which has been formulated from the analytical sub-domain model and particle swarm optimization. Five machine parameters i.e. magnet arc, slot opening, magnet thickness, airgap length and stator inner radius, are identified in the analytical sub-domain model and then optimized using the particle swarm optimization (PSO) algorithm to provide the optimal motor design with certain objective functions. The objective functions are the low cogging torque, low total harmonics distortion, high output torque, and high efficiency. The results from this MDO show that the magnet arc is optimized from full-pitch to 0.8 of full-pitch which yields 20% cost-saving in magnet volume, the back-emf total harmonics distortion of 4.7%, the cogging torque of 0.45Nm and 93.1% efficiency when the stator inner radius, Rsi is set to 32mm for 15slot/10pole PMSM. Whereas, the 6slot/4pole PMSM exhibits the back-emf total harmonics distortion of 9.3%, the cogging torque of 0.17Nm and 95.7% efficiency when the stator inner radius, Rsi is set to 20.9mm. MDO which combines the analytical sub-domain model with PSO algorithm can lead to faster PMSM design process and the results are comparable with that of finite element method.
Adipose-Derived Stem Cells as a Tool for Dental Implant Osseointegration: an Experimental Study in the Dog

The biological interaction between the jaw bones and dental implant is fundamental for the long-term success of dental implant placement. Nevertheless, the insufficient bone volume remains a major clinical problem, especially in case of immediate dental implant. Using a canine model, the present study proves the regenerative potential of adipose- derived stem cells (ADSCs) to repair peri-implant bone defects occurring in immediate dental implant placement. In six labradors, all mandibular premolars and the first molars were extracted bilaterally and three months later dental implants were installed with a marginal gap. The marginal defects were filled with hydroxyapatite (HA)-based scaffolds previously seeded with ADSCs. After one month of healing, specimens were prepared for histological and histomorphometric evaluations. Histological analyses of ground sections show that ADSCs significantly increase bone regeneration. Several new vessels, osteoblasts and new bone matrix were detected. By contrast, no inflammatory cells have been revealed. ADSCs could be used to accelerate bone healing in peri- implant defects in case of immediate dental implant placement.
Barriers and facilitators to implementing electronic prescription: a systematic review of user groups' perceptions

OBJECTIVE We conducted a systematic review identifying users groups' perceptions of barriers and facilitators to implementing electronic prescription (e-prescribing) in primary care. METHODS We included studies following these criteria: presence of an empirical design, focus on the users' experience of e-prescribing implementation, conducted in primary care, and providing data on barriers and facilitators to e-prescribing implementation. We used the Donabedian logical model of healthcare quality (adapted by Barber et al) to analyze our findings. RESULTS We found 34 publications (related to 28 individual studies) eligible to be included in this review. These studies identified a total of 594 elements as barriers or facilitators to e-prescribing implementation. Most user groups perceived that e-prescribing was facilitated by design and technical concerns, interoperability, content appropriate for the users, attitude towards e-prescribing, productivity, and available resources. DISCUSSION This review highlights the importance of technical and organizational support for the successful implementation of e-prescribing systems. It also shows that the same factor can be seen as a barrier or a facilitator depending on the project's own circumstances. Moreover, a factor can change in nature, from a barrier to a facilitator and vice versa, in the process of e-prescribing implementation. CONCLUSIONS This review summarizes current knowledge on factors related to e-prescribing implementation in primary care that could support decision makers in their design of effective implementation strategies. Finally, future studies should emphasize on the perceptions of other user groups, such as pharmacists, managers, vendors, and patients, who remain neglected in the literature.
3D Reconstruction Using Labeled Image Regions

In this paper we present a novel algorithm for reconstructing 3D scenes from a set of images. The user defines a set of polygonal regions with corresponding labels in each image using familiar 2D photo-editing tools. Our reconstruction algorithm computes the 3D model with maximum volume that is consistent with the set of regions in the input images. The algorithm is fast, uses only 2D intersection operations, and directly computes a polygonal model. We implemented a user-assisted system for 3D scene reconstruction and show results on scenes that are difficult or impossible to reconstruct with other methods.
EDM of Metal Matrix Composite for Parameter Design Using Lexicographic Goal Programming

This paper reports the results of a metal matrix composite (MMC) machined with electric discharge machining (EDM). The results were optimized using lexicographic goal programming to predict the ideal parametric combinations for machining of MMCs. Optimal conditions for the significant parameters were listed depending upon the requirements of the machining process which may vary from rough machining (higher material removal rate) and finish machining (lower surface roughness). The mean thickness of the recast layer formed after machining was also studied.