Miracle-dz/UniFAR-FTUs huggingface dataset:
Radiation dose measurment using MOSFETs

The MOS transistor as a radiation dose detector has been presented. MOS transistors present advantages such as low cost, small volume and weight, robustness, accuracy, large measurable dose range, and sensitivity to low-energy radiation (10 keV). They are useful in real-time measurements or post-irradiation read-out, while they retain information after reading. The sensitivity of unbiased MOSFETs has been improved, and further improvement is possible by increasing the oxide thickness via dual dielectrics or by using ion-implanted oxides and stacked MOSFET configurations. The stacked-transistor configuration is a very promising solution to reach the mRad range (personnel dosimetry). MOSFETs are already used in various application fields with increasing interest for use in specific cases of in-vivo dosimetry.
A Wormhole Attack Defense Strategy of WSN Based on Node Location Information

Wormhole attack is a kind of attack manner in WSN that does not need to crack network encryption key, which has great harm. Aiming at the characteristics of Wormhole attack, a wormhole attack defense strategy based on node location information was presented. The manner computed physical distance between two nodes through extraction of location information in the packets and compared it with stored threshold, so as to determine whether these packets come from normal communication range. WSN network modeling and simulation results based on OMNeT++ indicates that AODV protocol of defense strategy added sensor node location information can implement successfully defense.
Impact of contact resistance on the transconductance and linearity of graphene transistors

Interest in graphene device physics and technology has been growing rapidly, especially for very high frequency transistor applications. However, the predicted intrinsic performance has not been fully realized due to impurity and parasitic issues introduced in device fabrication. Through a self-consistent model, we show that the normalized contact resistance has an exponentially detrimental impact on the peak transconductance, which is a defining transistor parameter. In addition, we reveal that very high current-gate voltage linearity or input invariant transconductance can be achieved in the limit of negligible contact resistances, a desirable feature for linear electronic systems.
Solid Gold: The Popular Record Industry

More than 90 record companies release over 9,000 pop records each year--a staggering total of 52,000 songs. Each one competes for the gold record, the recording industry's symbol of success that certifies $1 million worth of records have been sold. Solid Gold explains why, for each record that succeeds, countless others fail. This book follows the progress of a record through production, marketing, and distribution, and shows how a mistake made at any point can mean its doom. Denisoff suggests that a drastic shift in the demographic makeup of the pop music audience during the sixties has resulted in a broader listening public, including fans at every level of society.
Human-Automation Challenges for the Control of Unmanned Aerial Systems

The continuing proliferation in the use of Unmanned Aerial Systems (UAS) in both civil and military operations has presented a multitude of human factors challenges from how to bridge the gap between the demand and availability of trained operators, to how to organize and present data in meaningful ways. Underlying many of these challenges is the issue of how automation capabilities can best be utilized to assist human operators manage increasing complexity and workload. The purpose of this discussion panel is to examine current research and perspectives on human automation interaction and how it relates to the future of UAS control. The panel is composed of five well-known researchers, all experts in the area of human-automation interaction. The range of topics that the panelists will discuss includes: how automation taxonomies can be applied to UAS design; opportunities to exploit automation capabilities in multi-vehicle contexts; current examples of automation research results, particularly in the area of multiple UAS control, and how they can be applied for future UAS; and how to design automation to maximize UAS mission effectiveness.
Spectroscopic profiling of soluble solids content and acidity of intact grape, lime, and star fruit

Purpose – Visible and near infrared spectroscopy have been applied widely in fruits quality assessment especially on the measurement of soluble solids content (SSC) measured in oBrix and acidity measured in pH. Spectroscopy technique has been applied on three botanically different categories of fruits, that is: imported Californian table grape, Mandarin lime and star fruit. The purpose is to examine the ability of spectroscopy technique to quantify internal quality parameters with very narrow variability due to the characteristics of the raw material analyzed. This work also presents comparative study on peak wavelengths that can best be used to calibrate SSC and pH of different types of fruits.Design/methodology/approach – The effective wavelengths chosen for calibration development are compared with those selected by other researchers in similar experiments. NIR wavelengths 910 nm (C−H band) and 950 nm (O−H band) are the most important wavelengths for the prediction of SSC for all examined fruits while .
Controlling Cell Migration with Micropatterns

Taro Toyota1,2,3, Yuichi Wakamoto2,3, Kumiko Hayashi4 and Kiyoshi Ohnuma5 1Department of Basic Science, Graduate School of Arts and Sciences The University of Tokyo 2Research Center for Complex Systems Biology, The University of Tokyo 3Precursory Research of Embryonic Science and Technology (PRESTO) Japan Science and Technology Agency (JST) 4Department of Applied Physics, Graduate School of Engineering Tohoku University 5Top Runner Incubation Center for Academia-Industry Fusion Nagaoka University of Technology Japan
Liberal Arts Colleges

The Accounting Education Change Commission (AECC), a product of public accounting firms and the accounting academy, was formed in 1989 as an agent for facilitating change in accounting education. A consensus that accounting education had not kept pace with changes in the accounting profession provided the impetus for forming the AECC. With its emphasis on rule memorization and report preparation, accounting education was not adequately preparing students for the challenges practicing accountants typically face. Accounting education needed to change, placing greater emphasis on developing critical thinking, problem solving, and communication skills. Much of the literature on this change in accounting education has focused on financial accounting education. This paper examines the effect of this change on tax education. The thesis advanced is that change in tax education represents an opportunity for accounting educators at Christian liberal arts colleges. First, when making the case for a liberal arts education it is often-cited that a liberal arts education enjoys a comparative advantage in the development of critical thinking, problem solving, and communication skills. These skills are emphasized and developed when tax courses are taught from the user perspective, allowing user perspective tax courses to play to the strengths of a liberal arts education. Second, when making the case for a Christian education an often-cited advantage is the explicit, intentional integration of faith and learning. Among other emphases, user perspective tax courses focus on understanding how taxes affect economic behavior. Within this framework of understanding how taxes affect economic behavior it is straightforward to incorporate a Christian understanding of tax policy, allowing user perspective tax courses to play to the strengths of a Christian education.
The EFSUMB Guidelines and Recommendations for Musculoskeletal Ultrasound – Part II: Joint Pathologies, Pediatric Applications, and Guided Procedures

Abstract The second part of the Guidelines and Recommendations for Musculoskeletal Ultrasound (MSUS), produced under the auspices of EFSUMB, following the same methodology as for Part 1, provides information and recommendations on the use of this imaging modality for joint pathology, pediatric applications, and musculoskeletal ultrasound-guided procedures. Clinical application, practical points, limitations, and artifacts are described and discussed for every joint or procedure. The document is intended to guide clinical users in their daily practice.
Methods for managing uncertainly in material selection decisions : robustness of early stage life cycle assessment

Utilizing alternative materials is an important tactic to improve the environmental performance of products. Currently a growing array of materials candidates confronts today’s product designer. While life-cycle assessment (LCA) methods provide quantitative input into this selection decision, their implementations are evolving and disparate. The goal of this paper is to explore several major analytical variations of LCA implementations and the implications of these variants across a range of application contexts. Specifically, this thesis examines analytical variations in valuation method and treatment of recycling by exploring allocation methods that affect product end-of-life. An abstracted case study across a range of materials is presented, including materials that exhibit a spectrum in variation of environmental performance and material degradation between primary and secondary applications. To date, research has shown that the amount of recycled material delivered by, or used in, the life cycle of a product will affect the environmental burdens of other product life cycles. However, explicit consideration has not been given to the question of whether end-of-life allocation methods can lead to different materials selection decisions in early stage product development cycles. Similarly stemming from this question is the issue of, if so, how do these allocation methods differentially favor certain material classes? Results indicate that the choice of analytical method as well as its underlying parameters can have substantial impact on individual metrics that determine environmentally preferred material and that there are sets of analytical variation over which strategic results are strongly affected. Thesis Supervisor: Randolph E. Kirchain Assistant Professor of Materials Science and Engineering, and the Engineering Systems Division
A Decade in Review: A Systematic Review of Virtual Reality Interventions for Emotional Disorders

ABSTRACT Research is increasingly demonstrating the therapeutic benefits of virtual reality interventions for various mental health conditions, though these rarely translate from research to application in clinical settings. This systematic review aims to examine the efficacy of current virtual reality interventions for emotional disorders, with a focus on clinical and technological features that influence translation of treatments from research to clinical practice. A comprehensive systematic literature search was conducted following PRISMA guidelines, for studies including the application of a virtual reality intervention to a clinical population of adults with an emotional disorder. Thirty-seven eligible studies were identified, appraised, and assessed for bias. Treatment effects were typically large across studies, with virtual reality being considered an efficacious treatment modality for various anxiety disorders and post-traumatic stress disorder. Virtual reality interventions were typically used for delivering exposure in cognitive behavioural therapy approaches. Considerable variability was seen in cost, technological specifications, degree of therapist involvement, delivery format, dosage, duration, and frequency of treatment. Suboptimal methodological rigour was identified in some studies. Remote use of virtual reality was rare, despite increasing options for in home use. Virtual reality interventions have the potential to overcome barriers to care and better meet the needs of consumers. Future research should examine the efficacy of virtual reality for treatment of depressive disorders and obsesive compulsive disorder. Improved methodological reporting and development of transdiagnostic and remotely delivered virtual reality interventions, will likely increase the translation of this treatment modality.
Labour mobility, related variety and the performance of plants : A Swedish study

This paper analyses the impact of skill portfolios and labour mobility on plant performance by means of a unique database that connects attributes of individuals to features of plants for the whole Swedish economy. We found that a portfolio of related competences at the plant level increases significantly productivity growth of plants, in contrast to plant portfolios consisting of either similar or unrelated competences. Based on the analysis of 101,093 job moves, we found that inflows of skills that are related to the existing knowledge base of the plant had a positive effect on plant performance, while the inflow of new employees with skills that are already present in the plant had a negative impact. Our analyses show that inflows of unrelated skills only contribute positively to plant performance when these are recruited in the same region. Labour mobility across regions only has a positive effect on productivity growth of plants when this concerns new employees with related skills.
Discovery of Autoantibodies Targeting Nephrin in Minimal Change Disease Supports a Novel Autoimmune Etiology

Significance Statement Although corticosteroids are an effective first-line therapy for minimal change disease, relapse, steroid dependence, and intolerance are common in this podocytopathy of unknown etiology. The efficacy of B cell–targeted therapies in some patients suggests an autoantibody-mediated etiology. This study describes the novel discovery in both adults and children with minimal change disease of autoantibodies targeting nephrin, a critical component of the podocyte slit diaphragm that ensures integrity of the glomerular filtration barrier. This observation aligns with the established proteinuric effect of antinephrin antibodies demonstrated in animal models. These findings identify an important autoimmune mechanism in a subset of patients with minimal change disease and provide a framework for the application and development of precision medicine strategies in this condition. Visual Abstract Background Failure of the glomerular filtration barrier, primarily by loss of slit diaphragm architecture, underlies nephrotic syndrome in minimal change disease. The etiology remains unknown. The efficacy of B cell–targeted therapies in some patients, together with the known proteinuric effect of anti-nephrin antibodies in rodent models, prompted us to hypothesize that nephrin autoantibodies may be present in patients with minimal change disease. Methods We evaluated sera from patients with minimal change disease, enrolled in the Nephrotic Syndrome Study Network (NEPTUNE) cohort and from our own institutions, for circulating nephrin autoantibodies by indirect ELISA and by immunoprecipitation of full-length nephrin from human glomerular extract or a recombinant purified extracellular domain of human nephrin. We also evaluated renal biopsies from our institutions for podocyte-associated punctate IgG colocalizing with nephrin by immunofluorescence. Results In two independent patient cohorts, we identified circulating nephrin autoantibodies during active disease that were significantly reduced or absent during treatment response in a subset of patients with minimal change disease. We correlated the presence of these autoantibodies with podocyte-associated punctate IgG in renal biopsies from our institutions. We also identified a patient with steroid-dependent childhood minimal change disease that progressed to end stage kidney disease; she developed a massive post-transplant recurrence of proteinuria that was associated with high pretransplant circulating nephrin autoantibodies. Conclusions Our discovery of nephrin autoantibodies in a subset of adults and children with minimal change disease aligns with published animal studies and provides further support for an autoimmune etiology. We propose a new molecular classification of nephrin autoantibody minimal change disease to serve as a framework for instigation of precision therapeutics for these patients.
Opening Space Research: Dreams, Technology, and Scientific Discovery

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Rainfalls sprinkle cloud bacterial diversity while scavenging biomass.

Bacteria circulate in the atmosphere, through clouds and precipitation to surface ecosystems. Here we conducted a coordinated study of bacteria assemblages in clouds and precipitation at two sites distant of ∼800 m in elevation in a rural vegetated area around puy de Dôme Mountain, France, and analyzed them in regard to meteorological, chemical and air masses' history data. In both clouds and precipitation, bacteria generally associated with vegetation or soil dominated. Elevated ATP-to-cell ratio in clouds compared with precipitation suggested a higher proportion of viable cells and/or specific biological processes. The increase of bacterial cell concentration from clouds to precipitation indicated strong below-cloud scavenging. Using ions as tracers, we derive that 0.2 to 25.5% of the 1.1×107 to 6.6×108 bacteria cell m-2 h-1 deposited with precipitation originated from the source clouds. Yet, the relative species richness decreased with the proportion of inputs from clouds, pointing them as sources of distant microbial diversity. Biodiversity profiles thus differed between clouds and precipitation in relation with distant/local influencing sources, and potentially with bacterial phenotypic traits. Notably Undibacterium, Bacillus and Staphylococcus were more represented in clouds, while epiphytic bacteria such as Massilia, Sphingomonas, Rhodococcus and Pseudomonas were enriched in precipitation.
New Dual-Mode FSE Suitable for High-Order QAM Signals

In the digital transmission system, constant modulus algorithm (CMA) is a famous blind equalization to overcome the inter-symbol interference without the aid of training sequences. But for the non-constant modulus signals such as higher-order QAM signals, the CMA just achieve moderate steady-state mean square error (MSE). So a new dual-mode fractionally-spaced equalization (FSE) suitable for high-order QAM signals is proposed, which makes full use of the character which is that the high-order QAM signals have the different modulus. This algorithm uses the FSE based on CMA as the basal mode and in the second mode it uses the FSE based on variable modulus algorithm. The simulation results show that compared with CMA the proposed algorithm has faster convergence rate and lower steady-state mean square error.
Stress-induced leakage current of tunnel oxide derived from flash memory read-disturb characteristics

This paper describes the characteristics of the stress-induced leakage current of tunnel oxide derived from flash memory read-disturb characteristics. The following three items were newly observed. First, the threshold voltage shift (/spl Delta/V/sub th/) of the memory cell under the gate bias condition (read disturb condition) consists of two regions, a decay region and a steady-state region. The decay region is due to both the initial trapping or detrapping of the carriers in the tunnel oxide and the decay of the stress-induced leakage current of the tunnel oxide. The steady-state region is determined by the saturation of the stress-induced leakage current of the tunnel oxide. Second, the read disturb life time is mainly determined by the steady-state region for the oxide thickness of 5.7-10.6 nm investigated here. Third, a high-temperature (125/spl deg/C) write/erase operation degrades the steady-state region characteristics in comparison with room temperature (30/spl deg/C) operation. Therefore, accelerated write/erase tests can be carried out at higher operation temperatures.
Classification of Adolescent Psychiatric Patients at High Risk of Suicide Using the Personality Assessment Inventory by Machine Learning

Objective There are growing interests on suicide risk screening in clinical settings and classifying high-risk groups of suicide with suicidal ideation is crucial for a more effective suicide preventive intervention. Previous statistical techniques were limited because they tried to predict suicide risk using a simple algorithm. Machine learning differs from the traditional statistical techniques in that it generates the most optimal algorithm from various predictors. Methods We aim to analyze the Personality Assessment Inventory (PAI) profiles of child and adolescent patients who received outpatient psychiatric care using machine learning techniques, such as logistic regression (LR), random forest (RF), artificial neural network (ANN), support vector machine (SVM), and extreme gradient boosting (XGB), to develop and validate a classification model for individuals with high suicide risk. Results We developed prediction models using seven relevant features calculated by Boruta algorithm and subsequently tested all models using the testing dataset. The area under the ROC curve of these models were above 0.9 and the RF model exhibited the best performance. Conclusion Suicide must be assessed based on multiple aspects, and although Personality Assessment Inventory for Adolescent assess an array of domains, further research is needed for predicting high suicide risk groups.
3D object recognition using coded light projection for robot assembly applications

This paper describes the algorithms needed to allow automatic recognition of components in three dimensions (3-D) using a novel active range sensor based on liquid crystal technology, which is programmed to project coded lighting sequences onto a pallet of workpieces within a flexible manufacturing cell. A range map with up to 1200/spl times/1200 range points is constructed using a sequence of binary image captures from a single robot head camera. Calibration of the vision sensor head is achieved using a grid of black squares on a white mat placed on the pellet prior to on-line operation and accuracy of 0.33% in height measurement are achieved over a working area of 100/spl times/100 cm. The range data is processed on a digital signal processing image analyser and construction solid geometry (CSG) surfaces are matched to the data sets to extract surface models of the components. The surface model is stored in an object database and used to recognise the position of workpieces in the robot coordinate frame.