A 223- $$\mu W$$ μ W single-to-differential RF mixer with 8.6dBm IIP3 using current-bleeding and body-effect for sub-6 GHz 5G applications

Analog Integrated Circuits and Signal Processing - As the 5G era beckons in the world of communication and information technology, there is a surge in demand for battery-operated, mobile wireless...     

Analysis and optimization of fixture under dynamic machining condition with chip removal effect

Dynamic interactions in the tool–workpiece and workpiece–fixture systems significantly impinge on the quality of finished workpieces. The presented simulation system integrates the effects of workpiece fixture dynamics with the other factors contributing to the machining process dynamics. It provides more accurate prediction of the process output which helps in the design of the optimum fixture configuration prior to the production stage. Modelling of the frictional contact behaviour between the fixture element and the workpiece helps to improve the prediction accuracy of the simulation system which accelerates the convergence to the optimum fixture configuration design and consequently improves the machined part dimensional accuracy and geometric integrity. The developed simulation is capable of modelling complicated part geometries by interfacing with commercial ANSYS.V10^® packages. This research work minimizes the deformation of workpiece using integrated optimization tool of Genetic algorithm (GA) and ANSYS Parametric Design Language (APDL) of finite element analysis. The same layouts given by the above optimization tool are used in the experimental setup and it is found that the improved geometric tolerance of squarness and flatness of the given workpiece. The chip removal effect and frictional contact between the workpiece and the fixture elements are taken into account based on element death technique and nonlinear finite-element analysis. A Case study of an open slot milling process illustrates the application of the proposed improved geometric tolerance approach.     

Fabrication and Characterisation of Rutile-TiO_2 Coatings on Metallic Alloy Substrates

RUTILE-TJO2is a versatile material possessing manyinteresting physical,chemical,optical and dielectricproperties[l].It is also a good tribological material thatcan offer low friction and low wear rate[2,3].However,the application of rutile in the tribological field hasbeen limited to titanium alloys only so far,for example,by thermal oxidation of titanium alloys[4,5].Very fewinvestigations have been directed to the tribologicalapplications of rutile films on substrates other thantitanium al…     

Extranasal Staphylococcus aureus colonization predisposes to bloodstream infections in patients on hemodialysis with noncuffed internal jugular vein catheters

Introduction: Staphylococcal infection of endogenous origin is an important cause of morbidity and mortality in patients who receive hemodialysis (HD). The risk of such infections in nasal carriers of the organism is well defined. Extranasal carriage of the organism at extranasal sites may pose similar risks. Methods: A total of 70 patients about to undergo internal jugular vein catheterization for HD were enrolled in this prospective observational study. Swab cultures were obtained from anterior nares, posterior pharynx, axillae, toe web spaces, and vascular access sites at baseline and 1 week later. A patient was defined as a persistent carrier when the same organism was grown in both samples. Staphylococcus aureus bloodstream infections were assessed by blood and catheter tip cultures over a 90‐day period. Findings: The mean age of the patients was 43.71 ± 16.2 years. Persistent S. aureus carriage at anterior nares, throat, axilla, toe web spaces, vascular access site, and all sites was documented in 27.9%, 11.4%, 40%, 32.9%, 4.3%, and 64.2% of patients, respectively. Fifteen patients developed S. aureus infections. Catheter related S. aureus infections (CRI) were more likely in persistent carriers than nonpersistent carriers with odds ratios (95% CI) of 10.2 (2.8–37.1), 8.6 (1.7–42.2), 17.3 (3.4–86.0), 3.0 (0.9–9.8), and 1.9 (0.2–22.4) for anterior nares, throat, axilla, toe web spaces, and vascular access site carriers, respectively. The probability of developing CRI in persistent S. aureus carriers was 55% compared to none in noncarriers at 90 days (P = 0.04). Discussion: Extranasal S. aureus carriage is as significant a risk factor as nasal carriage for staphylococcal infections in patients on HD through catheters. The study is limited by lack of molecular phenotyping.     

Automated detection of glioblastoma tumor in brain magnetic imaging using ANFIS classifier

This article proposes a novel and efficient methodology for the detection of Glioblastoma tumor in brain MRI images. The proposed method consists of the following stages as preprocessing, Non‐subsampled Contourlet transform (NSCT), feature extraction and Adaptive neuro fuzzy inference system classification. Euclidean direction algorithm is used to remove the impulse noise from the brain image during image acquisition process. NSCT decomposes the denoised brain image into approximation bands and high frequency bands. The features mean, standard deviation and energy are computed for the extracted coefficients and given to the input of the classifier. The classifier classifies the brain MRI image into normal or Glioblastoma tumor image based on the feature set. The proposed system achieves 99.8% sensitivity, 99.7% specificity, and 99.8% accuracy with respect to the ground truth images available in the dataset.     

New Algorithms for Resource Reclaiming from Precedence Constrained Tasks in Multiprocessor Real-Time Systems

The scheduling of tasks in multiprocessor real-time systems has attracted many researchers in the recent past. Tasks in these systems have deadlines to be met, and most of the real-time scheduling algorithms use worst case computation times to schedule these tasks. Many resources will be left unused if the tasks are dispatched purely based on the schedule produced by these scheduling algorithms, since most of the tasks will take less time to execute than their respective worst case computation times. Resource reclaiming refers to the problem of reclaiming the resources left unused by a real-time task when it takes less time to execute than its worst case computation time. In this paper, we propose two algorithms to reclaim these resources from real-time tasks that are constrained by precedence relations and resource requirements, in shared memory multiprocessor systems. We introduce a notion called a restriction vector for each task which captures its resource and precedence constraints with other tasks. This will help not only in the efficient implementation of the algorithms, but also in obtaining an improvement in performance over the reclaiming algorithms proposed in earlier work [[2]]. We compare our resource reclaiming algorithms with the earlier algorithms and, by experimental studies, show that they reclaim more resources, thereby increasing the guarantee ratio (the ratio of the number of tasks guaranteed to meet their deadlines to the number of tasks that have arrived), which is the basic requirement of any resource reclaiming algorithm. From our simulation studies, we demonstrate that complex reclaiming algorithms with high reclaiming overheads do not lead to an improvement in the guarantee ratio.     

Manual Therapy Facilitates Homeostatic Adaptation to Bone Microstructural Declines Induced by a Rat Model of Repetitive Forceful Task

The effectiveness of manual therapy in reducing the catabolic effects of performing repetitive intensive force tasks on bones has not been reported. We examined if manual therapy could reduce radial bone microstructural declines in adult female Sprague–Dawley rats performing a 12-week high-repetition and high-force task, with or without simultaneous manual therapy to forelimbs. Additional rats were provided 6 weeks of rest after task cessation, with or without manual therapy. The control rats were untreated or received manual therapy for 12 weeks. The untreated TASK rats showed increased catabolic indices in the radius (decreased trabecular bone volume and numbers, increased osteoclasts in these trabeculae, and mid-diaphyseal cortical bone thinning) and increased serum CTX-1, TNF-α, and muscle macrophages. In contrast, the TASK rats receiving manual therapy showed increased radial bone anabolism (increased trabecular bone volume and osteoblast numbers, decreased osteoclast numbers, and increased mid-diaphyseal total area and periosteal perimeter) and increased serum TNF-α and muscle macrophages. Rest, with or without manual therapy, improved the trabecular thickness and mid-diaphyseal cortical bone attributes but not the mineral density. Thus, preventive manual therapy reduced the net radial bone catabolism by increasing osteogenesis, while rest, with or without manual therapy, was less effective.     

A neuro-genetic based short-term forecasting framework for network intrusion prediction system

Information systems are one of the most rapidly changing and vulnerable systems, where security is a major issue. The number of security-breaking attempts originating inside organizations is increasing steadily. Attacks made in this way, usually done by ＂authorized＂ users of the system, cannot be immediately traced. Because the idea of filtering the traffic at the entrance door, by using firewalls and the like, is not completely successful, the use of intrusion detection systems should be considered to increase the defense capacity of an information system. An intrusion detection system （IDS） is usually working in a dynamically changing environment, which forces continuous tuning of the intrusion detection model, in order to maintain sufficient performance. The manual tuning process required by current IDS depends on the system operators in working out the tuning solution and in integrating it into the detection model. Furthermore, an extensive effort is required to tackle the newly evolving attacks and a deep study is necessary to categorize it into the respective classes. To reduce this dependence, an automatically evolving anomaly IDS using neuro-genetic algorithm is presented. The proposed system automatically tunes the detection model on the fly according to the feedback provided by the system operator when false predictions are encountered. The system has been evaluated using the Knowledge Discovery in Databases Conference （KDD 2009） intrusion detection dataset. Genetic paradigm is employed to choose the predominant features, which reveal the occurrence of intrusions. The neuro-genetic IDS （NGIDS） involves calculation of weightage value for each of the categorical attributes so that data of uniform representation can be processed by the neuro-genetic algorithm. In this system unauthorized invasion of a user are identified and newer types of attacks are sensed and classified respectively by the neuro-genetic algorithm. The experimental results obtained in this work show that the system achieves improvement in terms of misclassification cost when compared with conventional IDS. The results of the experiments show that this system can be deployed based on a real network or database environment for effective prediction of both normal attacks and new attacks.     

Multiple metastatic infections in a hemodialysis patient with untunneled internal jugular catheter

We present an end‐stage renal disease patient on dialysis with fever. The primary source was right internal jugular vein catheter which had metastatic infections in the body probably via an arteriovenous communication in a cavity in left lung. Patient had right psoas muscle abscess and a left kidney abscess. An ¹⁸F‐fluorodeoxyglucose‐positron emission spectroscopy scan was done to find out left kidney abscess. A search of literature did not reveal many patients of psoas abscess secondary to infection of hemodialysis access.     

Performance modeling of DTN routing with heterogeneous and selfish nodes

The performance modeling study of Delay-Tolerant Network routing, in general, assumes the nodes to be homogeneous (in terms of features such as the coverage range) and uncompromised (in terms of forwarding messages). However, in realistic settings this may not be the case. The routing performance modeling of such realistic scenarios that involve multifariously-featured and egotistic nodes would be interesting and insightful. To this end, in this paper, we analytically model the routing behavior of such nodes using Ordinary Differential Equations for two different routing protocols namely, Epidemic Routing and Two-Hop Routing. Furthermore, we also study the degradation in the routing performance caused by an increase in the fraction of selfish nodes present in the heterogeneous node population. The proposed analytical model is validated via extensive simulations.