Miracle-dz/UniFAR-FTUs huggingface dataset:
The American Aircraft Industrial Base: On the Brink

In air combat, “the merge” occurs when opposing aircraft meet and pass each other. Then they usually “mix it up. ” In a similar spirit, Air and Space Power Journal’s “Merge” articles present contending ideas. Readers can draw their own conclusions or join the intellectual battle-space. Please send comments to aspj@maxwell.af. mil .
Wireless Testing of Integrated Circuits.

2012 ii To My Family iii ACKNOWLEDGEMENTS First and foremost, I would like to thank my parents, sister, and her husband. I could only successfully finish my graduate study with their strong and constant support. I want to express my sincere gratitude and appreciation to my advisors Prof. John P. Hayes and Prof. David D. Wentzloff for their support, encouragement and guidance for these past four years. It is very special to have two advisors, and I was given a great opportunity to have a good relationship with them. I also would like to extend my sincere gratitude to my other committee members, Prof. Anderson, for devoting their time to review this thesis and advising me with valuable suggestions. I would like to acknowledge my colleagues for constructive and insightful discussions. I have not directly collaborated with them but I greatly appreciate their
Low-Light-Level Performance of Visual Systems

Abstract : Visual systems for employment at low light levels are examined from two points of view: As extensions of the human visual system and As optical information acquisition and conversion systems. The first point of view is adopted to examine the general suitability and the limitations of reliance on the dark-adapted human eye alone, the dark-adapted human eye aided by binoculars, and the light-adapted human eye aided by photoelectronic imaging systems such as image intensifiers and low-light-level television. The second point of view is adopted to analyze the dependence of photoelectronic imaging system performance on system parameters.
Multi-Sensor Fault Diagnosis of Underwater Thruster Propeller Based on Deep Learning

With the rapid development of unmanned surfaces and underwater vehicles, fault diagnoses for underwater thrusters are important to prevent sudden damage, which can cause huge losses. The propeller causes the most common type of thruster damage. Thus, it is important to monitor the propeller’s health reliably. This study proposes a fault diagnosis method for underwater thruster propellers. A deep convolutional neural network was proposed to monitor propeller conditions. A Hall element and hydrophone were used to obtain the current signal from the thruster and the sound signal in water, respectively. These raw data were fast Fourier transformed from the time domain to the frequency domain and used as the input to the neural network. The output of the neural network indicated the propeller’s health conditions. This study demonstrated the results of a single signal and the fusion of multiple signals in a neural network. The results showed that the multi-signal input had a higher accuracy than the one-signal input. With multi-signal inputs, training two types of signals with a separated neural network and then merging them at the end yielded the best results (99.88%), as compared to training two types of signals with a single neural network.
Development and Critiques of Conceptual Metaphor Theory

There is an increasing trend in revealing the effect of conceptual metaphor on activities in the context of education. In order to shed light on future studies in this field, it is necessary to review the development and critiques of conceptual metaphor theory in general and applications and previous studies under the context of education in particular. This paper defines the term "metaphor" at first and further reviews its implications in constructing the conceptualization of educational-related concepts. Problems and challenges of conceptual metaphor theory are also discussed.
Quinolines and Macrolides Resistance-Associated Mutations in Chlamydia trachomatis in Women Endocervical Samples in the West Region of Cameroon

Chlamydia trachomatis infection is a public health problem worldwide. Although antibiotic resistance of this strict intracellular bacterium is rare, it is important to monitor the appearance of resistance genes to available efficient antibiotics. This study aimed to screen for mutations in some of these genes in C. trachomatis clinical isolates, which may be associated to resistance to quinolone and macrolide antibiotics. Thirty-five endocervical samples were collected from women aged between 18 and 49 in five district hospitals in the Western Region of Cameroon. The mutations in quinolones (parC and gyrA) and macrolides (L4, L22 and 23S rRNA) resistance domains were detected by PCR followed by sequencing on positive samples to C. trachomatis. The overall mutation rate for the studied genes was 60% in the studied samples. Seven (20%) and twelve (34%) samples presented mutations in the parC and gyrA gene respectively. Mutations in L4 (11.42%) and L22 (60%) were detected in ours samples, while no mutation was found in 23S rRNA gene. Seven clinical samples (20%) presented mutations to both macrolide and quinolone resistance genes. This study revealed a relatively high rate of mutations in the resistance genes to macrolides and quinolones in C. trachomatis in the West Cameroon. This rate of mutation calls for the competent authorities for better surveillance of C. trachomatis infection in West Cameroon to avoid a sudden increase in resistance to antibiotics in the years to come.
RUT DEPTH PREDICTION BASED ON VISCOELASTIC APPROACH

The paper discussed that one of the criteria for pavement failure is rut depth and rut depth prediction can be obtained from the creep test of the bituminous mixture used in the pavement structure. This research developed creep compliance curves for different uniaxial stress levels and temperatures. The portion of viscous response from the creep compliance curve is used to evaluate viscous constant. As the value of K (inverse of viscous constant) depends on temperature, and state of the stress, an appropriate constant must be used for each particular condition in the pavement structures. Analysis of for a typical pavement structure is performed. The state of the stress in the pavement structure is calculated by using ELSYM5. With the assumption that the rut depth observed at the surface is 32% contribute by bituminous layer, the number of standard axle load repetitions is predicted. Rut depth prediction based on a creep test is compared to rut depth prediction based on the Asphalt Institute. Rut depth prediction based on this research for high speed vehicle ( 100Hz ) is 1/6 of the Asphalt Institute. However for vehicle with lower speed ( e.g. 1Hz ) rut depth prediction is 3 times higher than the Asphalt Institute Somewhere Between 1 Hz and 100Hz. Both results are the same.
Biological trait profiles discriminate between native and non-indigenous marine invertebrates

The increasing rate of marine invasions to Western Europe in recent decades highlights the importance of addressing the central questions of invasion biology: what allows an invader to be successful, and which species are likely to become invasive? Consensus is currently lacking regarding the key traits that determine invasiveness in marine species and the extent to which invasive and indigenous species differ in their trait compositions. This limits the ability to predict invasive potential. Here we propose a method based on trait profiles which can be used to predict non-indigenous species likely to cause the greatest impact and native species with a tendency for invasion. We compiled a database of 12 key biological and life history traits of 85 non-indigenous and 302 native marine invertebrate species from Western Europe. Using multivariate methods, we demonstrate that biological traits were able to discriminate between native and non-indigenous species with an accuracy of 78%. The main discriminant traits included body size, lifespan, fecundity, offspring protection, burrowing depth and, to a lesser extent, pelagic stage duration. Analysis revealed that the typical non-indigenous marine invertebrate is a mid-sized, long-lived, highly fecund suspension feeder which either broods its offspring or has a pelagic stage duration of 1–30 days, and is either attached-sessile or burrows to a depth of 5 cm. Biological traits were also able to predict native species classed as “potentially invasive” with an accuracy of 78%. Targeted surveillance and proactive management of invasive species requires accurate predictions of which species are likely to become invasive in the future. Our findings add to the growing evidence that non-indigenous species possess a greater affinity for certain traits. These traits are typically present in the profile of “potentially invasive” native species.
Attack Evolution: Identifying Attack Evolution Characteristics to Predict Future Attacks

heterogeneous and dynamic problems of engineering technology and systems for industry and government. ISR is a permanent institute of the University of Maryland, within the Glenn L. Martin Institute of Technology/A. James Clark School of Engineering. It is a National Science Foundation Engineering Research Center. Web site http://www.isr. umd.edu I R INSTITUTE FOR SYSTEMS RESEARCH UNDERGRADUATE REPORT
Convolutional Neural Networks for Multimodal Remote Sensing Data Classification

In recent years, enormous research has been made to improve the classification performance of single-modal remote sensing (RS) data. However, with the ever-growing availability of RS data acquired from satellite or airborne platforms, simultaneous processing and analysis of multimodal RS data pose a new challenge to researchers in the RS community. To this end, we propose a deep-learning-based new framework for multimodal RS data classification, where convolutional neural networks (CNNs) are taken as a backbone with an advanced cross-channel reconstruction module, called CCR-Net. As the name suggests, CCR-Net learns more compact fusion representations of different RS data sources by the means of the reconstruction strategy across modalities that can mutually exchange information in a more effective way. Extensive experiments conducted on two multimodal RS datasets, including hyperspectral (HS) and light detection and ranging (LiDAR) data, i.e., the Houston2013 dataset, and HS and synthetic aperture radar (SAR) data, i.e., the Berlin dataset, demonstrate the effectiveness and superiority of the proposed CCR-Net in comparison with several state-of-the-art multimodal RS data classification methods. The codes will be openly and freely available at https://github.com/danfenghong/IEEE_TGRS_CCR-Net for the sake of reproducibility.
La responsabilidad social empresarial

This article is based on the results of a study that was aimed to describe the progress of curriculum strategic management of the Corporate Social Responsibility in faculties of Economics and Administrative Sciences in Santiago de Cali, from the leadership role assumed by managers. The approach to the institutions was done using a level of descriptive analysis that incorporated the teleological, organizational and the teaching and research components, a purposive sample of 18 managers of 11 faculties. The results allowed to observe, first, that all faculties consider Corporate Social Responsibility in the general guidelines curriculum, however, it appears that is not being assumed in the actual practices that materialize curricular strategic management, as evidenced by other studies. That is, “from words to action” there is long way to go, a necessary synergy between theory and practice that enables its appropriation
IoT-Sentry: A Cross-Layer-Based Intrusion Detection System in Standardized Internet of Things

With the widespread expansion of internet connected devices, securing the Internet of Things (IoT) has become one of the biggest challenges and a crucial issue for ensuring a secure and robust IoT vision. The usage of adhoc topologies and the resource constraints of IoT devices and networks makes first line of defense mechanisms like cryptography unsuitable to implement. Therefore, second line of defense mechanisms such as the intrusion detection system become fundamental to detect attacks. In this work, we propose IoT-Sentry, a cross-layer intrusion detection system to detect five different attacks with zero additional overhead. Also, there is a lack of rich, illustrative and concise public datasets in IoT for evaluation of intrusion detection models for IoT networks. Our research work fills this research gap by (1) developing a novel cross-layer IoT dataset which contains four simulation instances for the five attacks in static IoT networks with up to 100 nodes, (2) utilize novel features of cross-layer attacks, and (3) employ ensemble learning model to detect IoT attacks. In our work, the Cooja IoT simulator has been utilized for generating malicious and benign traffic. The IoT attack dataset is then analyzed and fed into centralized detection module implemented at the 6LoWPAN border router. On evaluation, IoT-Sentry achieves on average an accuracy of 99% for 4 out of 5 attacks. To the best of our knowledge, this is the first time that cross layer intrusion detection system catering to five attacks from different layers is developed for securing standardized IoT networks.
Monolithic Passive−Active Integration of Epitaxially Grown Quantum Dot Lasers on Silicon

Quantum dot (QD) lasers epitaxially grown on Si have already been demonstrated to show record low threshold, high temperature tolerance, and low feedback sensitivity. When grown on the silicon photonic chip and integrated with Si waveguides (WGs), QD lasers offer considerable economical and foundry‐scalable solutions to on‐chip light sources. Yet, a technology that enables both growth and integration of QD lasers on a silicon photonic chip has not been demonstrated. Herein, a novel device platform which enables integration of the QD active region with passive WG structures is designed. By doing so, complex and high‐performance lasers such as distributed Bragg reflector lasers, mode‐locked lasers, and sampled grating distributed Bragg reflector tunable lasers are demonstrated in this platform. The same laser epitaxial stack can be easily grown on the substrate of a silicon photonic chip to allow light coupling from QD laser cavities to the silicon WGs.
DECISION MAKING BASED ON EXPERT ASSESSMENTS: USE OF BELIEF NETWORKS TO TAKE INTO ACCOUNT UNCERTAINTY, BIAS, AND WEAK SIGNALS

Summary Decision making based on assessments made by a large number of experts of many different technical domains is a very difficult task. This paper presents a practical approach to assist decision makers to decide whether a complex critical system (e.g., a safety critical computerbased system) can be put into operational service. This approach can provide a synthetic view, in the form of a probability distribution for a global utility function. It also helps the decision maker to pinpoint the most critical issues, and gives the possibility to focus and zoom on these issues. The models supporting the approach can be used to evaluate the effects of various improvement actions, in order to identify the most appropriate and effective ones.
Genomic analysis reveals geography rather than culture as the predominant factor shaping genetic variation in northern Kenyan human populations

Objectives The aim of this study was to characterize the genetic relationships within and among four neighboring populations in northern Kenya in light of cultural relationships to understand the extent to which geography and culture shape patterns of genetic variation. Materials and Methods We collected DNA and demographic information pertaining to aspects of social identity and heritage from 572 individuals across the Turkana, Samburu, Waso Borana, and Rendille of northern Kenya. We sampled individuals across a total of nine clans from these four groups and, additionally, three territorial sections within the Turkana and successfully genotyped 376 individuals. Results Here we report that geography predominately shapes genetic variation within and among human groups in northern Kenya. We observed a clinal pattern of genetic variation that mirrors the overall geographic distribution of the individuals we sampled. We also found relatively higher rates of intermarriage between the Rendille and Samburu and evidence of gene flow between them that reflect these higher rates of intermarriage. Among the Turkana, we observed strong recent genetic substructuring based on territorial section affiliation. Within ethnolinguistic groups, we found that Y chromosome haplotypes do not consistently cluster by natal clan affiliation. Finally, we found that sampled populations that are geographically closer have lower genetic differentiation, and that cultural similarity does not predict genetic similarity as a whole across these northern Kenyan populations. Discussion Overall, the results from this study highlight the importance of geography, even on a local geographic scale, in shaping observed patterns of genetic variation in human populations.
No Teacher Left Behind: How to Teach with Technology

26 With the infusion of technology into all aspects of daily life, students are becoming more and more adept at using technology as an educational resource. Many faculty, however, are not keeping pace with their students. Additionally, faculty feel increasingly unprepared to integrate technology into the classroom.1 “Little has been done to prepare reluctant technology users for the networked computers flooding into their rooms,” according to Jamie McKenzie, editor of the Web-based journal From Now On.2 Many institutions of higher learner now offer technology courses to faculty to bridge this gap, helping them master the intricacies of PowerPoint or learn to post materials in a course management system. These courses help to an extent, but classes in using technology do not prepare faculty to effectively incorporate technology into their teaching.3 At the United States Military Academy at West Point, we have had the luxury of operating in a technology-rich, standardized environment since the mid1980s. This has enabled us to develop slowly in our understanding and use of technology for instruction. Nevertheless, the faculty development issue is probably the most challenging and one that the academy’s Department of Behavioral Sciences and Leadership has addressed during the past three years. We believe that our experience offers an instructive model for faculty development in incorporating technology into the classroom. This article provides an overview of a three-phase program that when implemented will assist both veteran and novice instructors in incorporating available technology into the classroom to achieve a richer educational experience for students. This article highlights the practical steps that nearly any department can adopt (or adapt) to get a program running at its own institution.
RUMBLING TOWARD SAFETY

Single-vehicle run-off-road crashes represent a large share of accidents in the U.S. The category is large in part because it covers such a broad range of roadway departures. Included are intentional departures to avoid other vehicles or objects; involuntary departures due to tire blowout, ice, hydroplaning, or trailer sway; and driver error from distractions or drowsiness. Within this category is a much smaller, more lethal crash type, known as drift-off-road crashes, caused by drivers who drift off the road due to drowsiness, inattention, or distraction, and are responsible for a disproportionate share of severe run-off-road crashes. This article discusses findings from a Michigan study indicating that rumble strip design and placement can significantly reduce the incidence of drift-off-the-road crashes.
Hypothalamic Neurochemical Changes in Long-Term Recovered Bilateral Subdiaphragmatic Vagotomized Rats

Background Vagus nerve is one of the crucial routes in communication between the immune and central nervous systems. The impaired vagal nerve function may intensify peripheral inflammatory processes. This effect subsides along with prolonged recovery after permanent nerve injury. One of the results of such compensation is a normalized plasma concentration of stress hormone corticosterone – a marker of hypothalamic-pituitary-adrenal (HPA) axis activity. In this work, we strive to explain this corticosterone normalization by studying the mechanisms responsible for compensation-related neurochemical alterations in the hypothalamus. Materials and Methods Using microarrays and high performance liquid chromatography (HPLC), we measured genome-wide gene expression and major amino acid neurotransmitters content in the hypothalamus of bilaterally vagotomized rats, 1 month after surgery. Results Our results show that, in the long term, vagotomy affects hypothalamic amino acids concentration but not mRNA expression of tested genes. Discussion We propose an alternative pathway of immune to CNS communication after vagotomy, leading to activation of the HPA axis, by influencing central amino acids and subsequent monoaminergic neurotransmission.
Turning Up the Heat on Energy Monitoring in the Home

The use of domestic electrical energy monitoring systems is becoming more common however gas usage has received comparatively little attention. This paper presents a new technique for monitoring gas-powered heating and hot water usage in the home integrated into a prototype energy monitoring platform. Compared to usual meter-based approaches this technique provides finer-grained usage data and uses simple temperature sensors. The main motivation for this work is to provide more meaningful energy information to users for inclusion in novel mobile and embedded applications. This is part of ongoing work which aims to reduce energy use among teenagers in the UK and make lasting attitude changes. The development and findings from a prototype deployed in a typical UK house over 7 days are presented. The findings highlight the utility of the technique and simplicity of the sensing approach. The novel requirements that inspired the development of this technique are also presented.
Nanometer CMOS ICs: From Basics to ASICs

CMOS technologies account for almost 90% of all integrated circuits (ICs). This book provides an essential introduction to nanometer CMOS ICs. The contents of this book are based upon several previous publications and editions entitled 'MOS ICs' and 'Deep-Submicron CMOS ICs'. Nanometer CMOS ICs is fully updated and is not just a copy-and-paste of previous material. It includes aspects of scaling up to and beyond 32nm CMOS technologies and designs. It clearly describes the fundamental CMOS operating principles and presents substantial insight into the various aspects of design implementation and application. In contrast to other works on this topic, the book explores all associated disciplines of nanometer CMOS ICs, including physics, design, technology, yield, packaging, less-power design, variability, reliability and signal integrity. Finally it also includes extensive discussions on the trends and challenges for further scaling. The text is based upon in-house Philips and NXP Semiconductors courseware, which, to date, has been completed by more than 3000 engineers working in a large variety of related disciplines: architecture, design, test, process, packaging, failure analysis and software. Carefully structured and enriched by in-depth exercises, hundreds of colour figures and photographs and many references, the book is well-suited for the purpose of self-study.