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Ionic liquids (ILs) have myriad potential uses as low vapor pressure solvents, catalysts and conducting liquids. Approximately one trillion room temperature ILs are possible if we include all mixtures. Due to this large number, the selection of a particular IL for a specific application is very difficult. Certain ILs with long alkyl chains have been shown to exhibit lubricious characteristics under macro testing conditions. A method is described here that compares the performance of ILs as lubricants for low load conditions for both micro and nano level contacts. An atomic force microscope with micro-sphere attached tip in a fluid cell is used to compare the lubricity of ILs with distinct molecular architectures. Overall lubrication performance of ionic liquid studied here at low load conditions seems to be an interplay of boundary regime and hydrodynamic regime and H-silicon showed much lower friction than on neat silicon.

Techniques are described which permit the application of very uniform thin epoxy coatings on boron or 5 mil diameter glass fiber. These thick interfaces improve the transverse strength and interlaminar shear strength of glass/epoxy composites by as much as 60% and 35% improvements are typical for boron/epoxy composites. Flexural and torsional fatigue strengths of both materials are improved by 1 to 3 orders of magnitude. The resistance of composites to boiling water is also dramatically improved. After a 2 hour boil, thick interface samples retain more than 80% of their original transverse strength while control samples retain only 65 to 75%.

To evaluate the ability of polyaryl thermoplastic coatings such as Polyphenylenesulfide (PPS) and polyphenyletheretheretherketone (PEEK), to protect zinc phosphate (Zn.Ph)-treated steels from corrosion in a wet, harsh environment (1.0 wt% H2SO4, 3.0 wt% NaCl and 96.0 wt% water at temperature from 25 to 200 deg C), we exposed them in autoclave to measure their performance in heating-cooling cyclic fatigue tests (1 cycle = 12 hr at 200 deg C + 12 hr at 25 deg C) for up to 90 cycles. Although no changes in appearance were seen in the PEEK specimens after 60 cycles, extension to 90 cycles caused delamination of the coating film from the Zn.Ph; the major reason was the degradation of the PEEK polymer caused by its hydrothermal-catalyzed esterification. In urea hydrogen peroxide (UHP) modified PPS-coating systems, chemical reactions at the interfaces between the PPS and Zn in the Zn.Ph layer led to the formation of a ZnS reaction product, which enhanced the Zn.Ph-to-PPS adhesive bond; correspondingly, there were no signs of peeling nor separation of the coating after 90 cycles. In addition, because these intermediate reaction products are insoluble at high pH, they minimized the rate of delamination of the PPS coating caused by the cathodic reaction, H2O + 1/202 + 2e right arrow 2OH(-), at the corrosion side of a defect in the film. In contrast, PEEK coatings containing non-reactive Zn.Ph Underwent cathodic delamination because of the susceptibility of Zn.Ph to alkali dissolution.

This study was conducted by the National Laboratory for Research of the Netherlands under cooperative sponsorship by the Federal Aviation Administration (FAA), and the Ministry of Transport of the Netherlands. The purpose of the study was the evaluation and measure of fundamental level of effort associated with the use of Data Link as a communications medium. Three Data Link interface designs were evaluated which combined effects of location, operability, size, and level of integration with the cockpit. The scenario was an oceanic flight of 2 hours duration, from a point over the North Atlantic, across the British Isles to a landing at Sciphol Airport, Amsterdam. Experimental conditions included routine flight and diversions in the flight due to oceanic storms and turbulence, enroute traffic conflicts, and airport runway closings. Data measures included subjective assessments of display usefulness, workload, and overall acceptability of Data Link compared to voice and objective measures of level of effort, and errors. In addition, physiological measures of heartrate, respiration, and head position were logged, and correlated with events of the flight. Overall, Data Link was rated acceptable in certain flight regimes, and unacceptable in others. Where excessive key entries were required, the Data Link function was rated lower than voice, and where automation alleviated the need for excessive keying, Data Link was rated about the same as voice.

This article is from Journal of Visualized Experiments : JoVE . Abstract The non-stationary nature and variability of neuronal signals is a fundamental problem in brain-machine interfacing. We developed a brain-machine interface to assess the robustness of different control-laws applied to a closed-loop image stabilization task. Taking advantage of the well-characterized fly visuomotor pathway we record the electrical activity from an identified, motion-sensitive neuron, H1, to control the yaw rotation of a two-wheeled robot. The robot is equipped with 2 high-speed video cameras providing visual motion input to a fly placed in front of 2 CRT computer monitors. The activity of the H1 neuron indicates the direction and relative speed of the robot's rotation. The neural activity is filtered and fed back into the steering system of the robot by means of proportional and proportional/adaptive control. Our goal is to test and optimize the performance of various control laws under closed-loop conditions for a broader application also in other brain machine interfaces.

The third annual report of the University Research Initiative project at UCSB on High-Temperature, High-Performance Composites consists of four sections compiled in a total of six books. The first sections is concerned with coatings and interfaces and is expressed in Book 1. The second section focuses on strength and fracture resistance and is found in Books 2 and 3. The third section describes research on flow and creep strength, this information is presented in Book 4. The fourth section is concerned with various aspects of processing in matrices and composites and is described in Books 5. and 6. Keywords: Ceramics; Intermetallics; Toughening.

The third annual report of the University Research Initiative project at UCSB on High-Temperature, High-Performance Composites consists of four sections compiled in a total of six books. The first sections is concerned with coatings and interfaces and is expressed in Book 1. The second section focuses on strength and fracture resistance and is found in Books 2 and 3. The third section describes research on flow and creep strength, this information is presented in Book 4. The fourth section is concerned with various aspects of processing in matrices and composites and is described in Books 5. and 6. Keywords: Ceramics; Intermetallics; Toughening.

This article is from Frontiers in Human Neuroscience , volume 8 . Abstract Modulation of sensorimotor rhythms (SMR) was suggested as a control signal for brain-computer interfaces (BCI). Yet, there is a population of users estimated between 10 to 50% not able to achieve reliable control and only about 20% of users achieve high (80–100%) performance. Predicting performance prior to BCI use would facilitate selection of the most feasible system for an individual, thus constitute a practical benefit for the user, and increase our knowledge about the correlates of BCI control. In a recent study, we predicted SMR-BCI performance from psychological variables that were assessed prior to the BCI sessions and BCI control was supported with machine-learning techniques. We described two significant psychological predictors, namely the visuo-motor coordination ability and the ability to concentrate on the task. The purpose of the current study was to replicate these results thereby validating these predictors within a neurofeedback based SMR-BCI that involved no machine learning.Thirty-three healthy BCI novices participated in a calibration session and three further neurofeedback training sessions. Two variables were related with mean SMR-BCI performance: (1) a measure for the accuracy of fine motor skills, i.e., a trade for a person’s visuo-motor control ability; and (2) subject’s “attentional impulsivity”. In a linear regression they accounted for almost 20% in variance of SMR-BCI performance, but predictor (1) failed significance. Nevertheless, on the basis of our prior regression model for sensorimotor control ability we could predict current SMR-BCI performance with an average prediction error of M = 12.07%. In more than 50% of the participants, the prediction error was smaller than 10%. Hence, psychological variables played a moderate role in predicting SMR-BCI performance in a neurofeedback approach that involved no machine learning. Future studies are needed to further consolidate (or reject) the present predictors.

This article is from Frontiers in Human Neuroscience , volume 8 . Abstract Brain signals recorded from the primary motor cortex (M1) are known to serve a significant role in coding the information brain–machine interfaces (BMIs) need to perform real and imagined movements, and also to form several functional networks with motor association areas. However, whether functional networks between M1 and other brain regions, such as these motor association areas, are related to the performance of BMIs is unclear. To examine the relationship between functional connectivity and performance of BMIs, we analyzed the correlation coefficient between performance of neural decoding and functional connectivity over the whole brain using magnetoencephalography. Ten healthy participants were instructed to execute or imagine three simple right upper limb movements. To decode the movement type, we extracted 40 virtual channels in the left M1 via the beam forming approach, and used them as a decoding feature. In addition, seed-based functional connectivities of activities in the alpha band during real and imagined movements were calculated using imaginary coherence. Seed voxels were set as the same virtual channels in M1. After calculating the imaginary coherence in individuals, the correlation coefficient between decoding accuracy and strength of imaginary coherence was calculated over the whole brain. The significant correlations were distributed mainly to motor association areas for both real and imagined movements. These regions largely overlapped with brain regions that had significant connectivity to M1. Our results suggest that use of the strength of functional connectivity between M1 and motor association areas has the potential to improve the performance of BMIs to perform real and imagined movements.

This report addresses the feasibility of and requirements for interfacing two powerful software engineering tools - POD (Performance Oriented Design) and HOS (High Order Software). POD is a software engineering tool for the life cycle managemetn of system performance. It is a tool which provides a structured machine readable format (the System Description File or SDF) for representing a system's hardware architecture, software structure and external load demand. Based on this representation, POD provides a vehicle to calculate system performance values such as response time, throughput and device utilization. HOS is a methodology for defining systems in a hardware and language independent manner. It consists of a specification language AXES, which provides mechanisms for defining functions, control structures, and data types, a User System Evaluation and Integration Tool (USE.IT), which is a family of tools for defining systems using the AXES language, an Analyzer for analyzing the logical correctness of systems defined in AXES, and a family of RATs (Resource Allocation Tools), which translate descriptions from the AXES specification language into target languages such as Fortran and (potentially) POD. In considering the feasibility of and requirements for interfacing POD and HOS, is assessed in terms of its ability to describe the required POD input specifications. In addition, consideration is given to possible HOS extensions to support POD, and an approach for interfacing these tools is suggested.

This report addresses the feasibility of and requirements for interfacing two powerful software engineering tools - POD (Performance Oriented Design) and HOS (High Order Software). POD is a software engineering tool for the life cycle managemetn of system performance. It is a tool which provides a structured machine readable format (the System Description File or SDF) for representing a system's hardware architecture, software structure and external load demand. Based on this representation, POD provides a vehicle to calculate system performance values such as response time, throughput and device utilization. HOS is a methodology for defining systems in a hardware and language independent manner. It consists of a specification language AXES, which provides mechanisms for defining functions, control structures, and data types, a User System Evaluation and Integration Tool (USE.IT), which is a family of tools for defining systems using the AXES language, an Analyzer for analyzing the logical correctness of systems defined in AXES, and a family of RATs (Resource Allocation Tools), which translate descriptions from the AXES specification language into target languages such as Fortran and (potentially) POD. In considering the feasibility of and requirements for interfacing POD and HOS, is assessed in terms of its ability to describe the required POD input specifications. In addition, consideration is given to possible HOS extensions to support POD, and an approach for interfacing these tools is suggested.

This article is from Frontiers in Systems Neuroscience , volume 8 . Abstract The concept of a brain-machine interface (BMI) or a computer-brain interface is simple: BMI creates a communication pathway for a direct control by brain of an external device. In reality BMIs are very complex devices and only recently the increase in computing power of microprocessors enabled a boom in BMI research that continues almost unabated to this date, the high point being the insertion of electrode arrays into the brains of 5 human patients in a clinical trial run by Cyberkinetics with few other clinical tests still in progress. Meanwhile several EEG-based BMI devices (non-invasive BMIs) were launched commercially. Modern electronics and dry electrode technology made possible to drive the cost of some of these devices below few hundred dollars. However, the initial excitement of the direct control by brain waves of a computer or other equipment is dampened by large efforts required for learning, high error rates and slow response speed. All these problems are directly related to low information transfer rates typical for such EEG-based BMIs. In invasive BMIs employing multiple electrodes inserted into the brain one may expect much higher information transfer rates than in EEG-based BMIs because, in theory, each electrode provides an independent information channel. However, although invasive BMIs require more expensive equipment and have ethical problems related to the need to insert electrodes in the live brain, such financial and ethical costs are often not offset by a dramatic improvement in the information transfer rate. Thus the main topic of this review is why in invasive BMIs an apparently much larger information content obtained with multiple extracellular electrodes does not translate into much higher rates of information transfer? This paper explores possible answers to this question by concluding that more research on what movement parameters are encoded by neurons in motor cortex is needed before we can enjoy the next generation BMIs.

Punjab is Pakistan's largest province and according to the School Census of Punjab, there are around 12.86 million students enrolled in public schools, and there are 391,799 teachers working in 52,470 public schools, resulting in a 33:1 student-teacher ratio. Pakistan as a whole and Punjab province both have literacy rates of above 70%, yet this is not a real reflection of Pakistan's educational system. Punjab’s current educational policy has major flaws, including high student-teacher ratio, uneven distribution of teachers with scarcity in rural regions, deteriorating educational outcomes, a declining proportion of children who attend government schools, declining proportion of public-school graduates working in white-collar jobs, increasing number of out-of-school children (“Punjab Province”, 2018), and many others. Pakistan needs to enhance its public education system not only to tackle economic, social, and developmental challenges but also to meet international commitments like the Sustainable Development Goals (SDGs). The digital revolution, driven by technological advancements, has transformed various industries, including education. This shift allows the adoption of Learning Management Systems (LMS) in higher education institutions within Punjab's government education system. By replacing traditional textbooks with digital content and utilizing interactive learning interfaces, policymakers and educators can create a more effective and engaging learning environment. The study's implications extend beyond Punjab, serving as a valuable guide for similar programs globally aiming to enhance student performance and engagement in government schools.

The annual report of the Office of Naval Research grant at UCSB on Strength and Fracture Energy of Bimaterials. Bimaterials Interfaces includes three sections: Mechanics of Interfaces, Coating Design for Composite Systems, and Mechanics of Brittle Matrix Composites. For more details see Executive Summary.