Miracle-dz/UniFAR-FTUs huggingface dataset:
Beyond Crises: The Unending Challenge of Controlling Nuclear Weapons and Materials

Book abstract: At the height of the Cultural Revolution a Chinese long-range nuclear missile is fired within the country, and the nuclear warhead it is carrying detonates. A French nuclear device is exploded in Algeria during a coup there. The Soviet empire has collapsed, and shots are fired at a Russian crowd intent on rushing a nuclear weapons-laden plane straining to remove a stash of nuclear weapons to a safer locale. Pakistani civilian governments are routinely pushed aside by a powerful, nuclear-armed military that observers worry might yet itself fall prey to a faction willing to seize a portion of Pakistanâ€™s nuclear arsenal. This volume reveals previously unknown details on each case and teases out what is to be learned. This book is ideal not only for policymakers and analysts, but for historians and teachers as well.
Design of Compact Photoelectrochemical Cells for Water Splitting

Solar driven water splitting can be achieved by coupling electrolyzers with PhotoVoltaics (PV). Integration of both functions in a compact PhotoElectroChemical (PEC) cell is an attractive option but presents significant scientific challenges. In this work, the design of single- and dual-compartment PEC cells for research purposes is discussed. The fabrication of separator-electrode assemblies is an important aspect, and upscaling of these architectures even to centimeter scale is not trivial. The layout of a new dual-compartment compact PEC cell with in-situ monitoring of pH, temperatures, and oxygen and hydrogen evolution for research purposes is presented. Finally, a prospect of future PEC cells for practical applications is presented.
ENERGY STAR Building Benchmarking Scores: Good Idea, Bad Science

The EPA introduced its ENERGY STAR building rating system 15 years ago. In the intervening years it has not defended its methodology in the peer-reviewed literature nor has it granted access to ENERGY STAR data that would allow outsiders to scrutinize its results or claims. Until recently ENERGY STAR benchmarking remained a confidential and voluntary exercise practiced by relatively few. In the last few years the US Green Building Council has adopted the building ENERGY STAR score for judging energy efficiency in connection with its popular green-building certification programs. Moreover, ten US cities have mandated ENERGY STAR benchmarking for commercial buildings and, in many cases, publicly disclose resulting ENERGY STAR scores. As a result of this new found attention the validity of ENERGY STAR scores and the methodology behind them has elevated relevance. This paper summarizes the author’s 18-month investigation into the science that underpins ENERGY STAR scores for 10 of the 11 conventional building types. Results are based on information from EPA documents, communications with EPA staff and DOE building scientists, and the author’s extensive regression analysis. For all models investigated ENERGY STAR scores are found to be uncertain by 35 points. The oldest models are shown to be built on unreliable data and newer models (revised or introduced since 2007) are shown to contain serious flaws that lead to erroneous results. For one building type the author demonstrates that random numbers produce a building model with statistical significance exceeding those achieved by five of the EPA building models.
Bridging the gap between heuristics and optimization: Capacity expansion case

The competition between heuristic and optimization approaches for process synthesis and process operations problems has caused major controversy in recent years. Heuristics offer fast solutions but no guarantee of optimality. Mathematical programming approaches, on the other hand, offer rigor but suffer from combinatorial explosion of computational requirements. The use of analytical investigations is proposed as a theoretical means to characterize the behavior of heuristics and optimization algorithms and produce a framework that combines the strengths of the two approaches while eliminating their weaknesses. The approach contrasts and complements the current practice in process systems engineering, which is entirely empirical in nature. The proposed paradigm is demonstrated in the context of the multiperiod capacity expansion problem for chemical process networks, a problem having much in common with both process synthesis and operations problems. Analytical investigations for this problem lead to the development of a heuristic that is proved to be asymptotically optimal under standard assumptions about the problem parameters. In the more general context of process synthesis and operations, analytical investigations present a large array of opportunities.
Neural network based CAD model for the design of rectangular patch antennas

A new method of calculation of patch dimensions of a rectangular microstrip patch antennas using Artificial Neural Network (ANN) has been adopted in this paper. An ANN model has been developed and tested for rectangular patch antenna design. It transforms the data containing the dielectric constant (�r), thickness of the substrate (h), and antenna’s dominant-mode resonant frequency (fr) to the patch dimensions that is, length (l) and width (w) of the patch. The results obtained using ANNs are compared with the simulation findings. The simulated values are obtained by designing the microstrip antenna using IE3D electromagnetic simulator. The ANNs results are more in agreement with simulation findings.
Comparison and Analysis of Various Artificial Neural Networks for Software Effort Estimation

Inspite of the several software effort estimation models developed over the last 30 years, providing accurate estimates of the software project under development is still unachievable goal. Failures in software are mainly due to the erroneous project management practices; one of them is effort estimation. Therefore, many researchers are working on the development of new models and the improvement of the existing ones using artificial intelligence techniques. Dynamic scenarios of software development technology make effort estimation more challenging. Ability of ANN (Artificial Neural Network) to model a complex set of relationship between the dependent variable (effort) and the independent variables (cost drivers) makes it as a budding tool for estimation. This paper presents a performance analysis of different ANNs and compare the results of various ANN models in effort estimation.
Fusion of Manual Control and BCI Using Long Term and Short Term Quality Measures

This work presents a hybrid BCI approach where two different input signals (joystick and BCI) are monitored and only one of them is chosen as a control signal at a time. A game-like feedback was used as an application where users could move a car to collect coins and avoid obstacles via either joystick or BCI control. For both types four different quality measures were constantly applied to evaluate the quality of the signal. As soon as the quality dropped below a certain threshold the system would switch to the other control mode and vice versa.
An experimental investigation into the validity of Leeson's equation for low phase noise oscillator design

In 1966, D.B. Leeson presented his model on phase noise in a letter entitled A Simple Model of Feedback Oscillator Noise Spectrum. This model usually requires an additional effective noise figure in order to conform with measured results. (This effective noise figure has to be determined by means of curve-fitting Leeson’s model with the measured results.) The model is, however, relatively simple to use, compared with other more accurate phase noise models that have since been developed and which can only be solved numerically with the aid of computers. It also gives great insight regarding component choices during the design process. Therefore several experiments were conducted in order to determine conditions under which Leeson’s model may be considered valid and accurate. These experiments, as well as the conclusions drawn from their results, are discussed in this document.
Connectome-based predictive modeling of cognitive reserve using task-based functional connectivity

Cognitive reserve supports cognitive function in the presence of pathology or atrophy. Functional neuroimaging may enable direct and accurate measurement of cognitive reserve which could have considerable clinical potential. The present study aimed to develop and validate a measure of cognitive reserve using task-based fMRI data that could then be applied to independent resting-state data. Connectome-based predictive modeling with leave-one-out cross-validation was applied to predict a residual measure of cognitive reserve using task-based functional connectivity from the Cognitive Reserve/Reference Ability Neural Network studies (n = 220, mean age = 51.91 years, SD = 17.04 years). Three network-strength predicted cognitive reserve measures were generated that accurately predicted the residual measures of unseen participants. The theoretical validity of these measures was established via a positive correlation with a socio-behavioural proxy of cognitive reserve (verbal intelligence) and a positive correlation with global cognition, independent of brain structure. This fitted model was then applied to external test data: resting-state functional connectivity data from The Irish Longitudinal Study on Ageing (TILDA, n = 294, mean age = 68.3 years, SD = 7.18 years). The network-strength predicted measures were not positively associated with a residual measure of cognitive reserve nor with measures of verbal intelligence and global cognition. The present study demonstrated that task-based functional connectivity data can be used to generate theoretically valid measures of cognitive reserve. Further work is needed to establish if, and how, measures of cognitive reserve derived from task-based functional connectivity can be applied to independent resting-state data.
Effectiveness of planning and control systems: An empirical study of US and Japanese firms

Both researchers and practitioners have investigated the effectiveness of manufacturing planning and control systems (MPCS) in an attempt to justify the investment in MPCS. This study uses the Wight's (1981) detailed questionnaire to measure the degree of planning and control implementation in a manufacturing system, which is referred to as MPCS rating. The MPCS rating is then used to study the relationship between the self-assessed manufacturing competitiveness (cost, quality, delivery and flexibility) and the objective performance measures of manufacturing performance such as production cost, productivity change, customer reject percent, manufacturing lead time, etc. The results show that there is a strong relationship between MPCS ratings and objective performance measures as well as self-assessed competitiveness in both Japanese and US firms. The results are important since they indicate that fundamental manufacturing planning and control procedures improve a firm's performance on both its internal operations as well as external competitiveness goals.
AN INNOVATIVE APPROACH OF HIGH PERFORMANCE CMOS CURRENT CONVEYOR - II FOR ANALOG SIGNAL PROCESSING APPLICATIONS

The purpose of this paper is to present a CMOS current conveyor circuit suitable for implementation of low- voltage, low-power, high bandwidth circuits. This circuit can be operated for a power supply of fraction of volt so as to achieve the bandwidth of current transfer function of MHz range and a power consumption of milli-watts range. Firstly, a class A current conveyor circuit that operates from a single supply of fraction of volt with a high voltage swing capability is discussed and then the same circuit can be modified to work as a class AB with a low voltage power supply in the fraction of volt range, while maintaining the same voltage swing capability. This current conveyor realization is insensitive to the threshold voltage variation caused by the body effect, which minimizes the layout area and makes both circuits a valuable addition to the analog signal processing applications. The proposed structure operates as linear circuit element and has the required performance in terms of a bandwidth using level 3 CMOS technology which is established with the help of 0.3 um simulation using PSpice software. This proposed current conveyor circuit has lot many applications in the field of analog signal processing. The proposed circuit operates satisfactorily at 0.2 µm with high performance with the desired applications. PSpice simulation with the modeled parameters confirms the desired properties & performance of the proposed circuit.
Measurement of Service Quality and its Relationship with the Client's Satisfaction Through SERVQUAL Model in the Gas Company

Abstarct: This paper examines the measurement of service quality on the basis of SERVQUAL model in Mashhad Gas Company and its relationship with the clients satisfaction. The group under study is all the clients of Mashhad Gas Company that use the gas services of these three regions. All stages of assessment of sample volume, has been done by statistical PASS software, version 2004. With respect to the goals of research and initial data concerning the research group, it shows that the correlation coefficient between service quality and satisfaction of; clients is 27/2 percent, with ninety five percent assurance, at least 141 people as the sample volume was estimated. After collecting the information, they were processed and after that the research assumptions were tested and by statistical methods and using the SPSS software, version 11/5 were analyzed. By using the gathered information, the assumptions under study were tested. The test results of the main assumption and related assumptions to it, shows that at the level of certainty 95 percent between service quality and the satisfaction of clients, there is a positive and significant relationship and also at the certainty level of 95 percent, there is a significant relationship between the constituent factors of SERVQUAL.
Increased Functional Connectivity of the Precuneus in Individuals with a Family History of Alzheimer’s Disease

First‐degree relatives of individuals with late‐onset Alzheimer’s Disease (AD) have increased risk for AD, with children of affected parents at an especially high risk. We sought to test how structural or functional abnormalities in the default mode network (DMN) during the brain’s “resting state” characterized individuals at risk for AD.
Spiral transmission-line baluns for RF multichip module packages

We describe a design method and lumped model for a circular spiral transmission-line balun. All lumped values are extracted from the geometric parameters of the balun. From simulation, the design parameters with well predicted characteristics are defined. The balun is fabricated using multi-chip module processing technology, which is suitable for integration in RF packages. Measurements show a wide bandwidth of 1.5-4.1 GHz and excellent balanced outputs. Amplitude imbalance less than 0.5 dB and phase imbalance less than 4/spl deg/ are achieved. The simulation results are compared with the measurement. The model captures all important properties of the balun with reasonably high accuracy.
Non-volatile Si quantum memory with self-aligned doubly-stacked dots

We investigate a novel Si quantum memory, in which floating gates are self-aligned doubly stacked Si dots. It is experimentally shown that the self-aligned double dot memory shows excellent charge retention. The retention improvement is explained by a theoretical model considering quantum confinement and Coulomb blockade in the lower Si dot. It is also shown that charge retention is improved remarkably by lower dot size scaling without losing high-speed write/erase.
Designing a Battlefield Fire Support System Using Adaptive Neuro-Fuzzy Inference System Based Model

Fire support of the maneuver operation is a continuous process. It begins with the receiving the task by the maneuver commander and continues until the mission is completed. Yet it is a key issue in combat in the way gain success. Therefore, a real-time mannered solution to fire support problem is a vital component of tactical warfare to the sequence that auxiliary forces or logistic support arrives at the theatre. A new method for deciding on combat fire support is proposed using adaptive neuro-fuzzy inference system (ANFIS) in this paper. This study addresses the design of an ANFIS as an efficient tool for real-time decision-making in order to produce the best fire support plan in battlefield. Initially, criteria that are determined for the problem are formed by applying ANFIS method. Then, the ANFIS structure is built up by using the data related to selected criteria. The proposed method is illustrated by a sample fire support planning in combat. Results showed us that ANFIS is valid especially for small unit fire support planning and is useful to decrease the decision time in battlefield.
Irradiation alone or combined with other alternative treatments to control postharvest diseases

The postharvest diseases are considered worldwide as the most significant issue for postharvest facilities. Although there are various methods to decrease postharvest losses, consumers are looking for agricultural product free of chemicals. It is therefore necessary to develop alternatives to synthetic chemical control to reduce environmental risks and raise consumer confidence. Several alternatives such as food irradiation show promise, but none alone is as effective as fungicides. A strategy must be developed that combines several of these alternatives to enhance their effectiveness. Therefore, there is a need for a method combining couple of methods together. A combination for this purpose can be irradiation with other treatment such as, heating, cooling and sodium carbonate/sodium bicarbonate treatment. The safety of irradiated food is declared by joint FAO/JAEA/WHO Expert Committee for food irradiation. In this study, advantages and disadvantages of irradiation, and combination with various other treatments were evaluated and recommendations were provided to minimize the postharvest losses.
Development of Trivex friction stir welding tool Part 2 – three-dimensional flow modelling

Abstract This paper describes the application of the computational fluid dynamics (CFD) code, FLUENT, to modelling the metal flow in friction stir welding (FSW). Building on a two-dimensional model, and preliminary trials with a novel 'Trivex' tool design, discussed in the companion paper immediately before this one, a full three-dimensional model was developed. The model predicted the temperature, and the traversing and down forces, which were compared against experiments. The model incorporated a novel 'slip' boundary condition, based on that developed in two dimensions. A conventional 'Triflute' tool was modelled and compared with the new 'Trivex' tool design. The model correctly predicted that the Trivex tool had lower traversing and down forces than its Triflute counterpart. To assist understanding of the material flow, streamlines around each of the tools were plotted. Ultimately the technique could be used to size the pin features reducing the need for costly experiments.
Glitter in the darkness? Non‐fibrillar β‐amyloid plaque components significantly impact the β‐amyloid PET signal

β‐amyloid PET (Aβ‐PET) is an important tool for quantification of amyloidosis in the brain of suspected Alzheimer’s disease (AD) patients and transgenic AD mouse models. Despite the excellent correlation of Aβ‐PET with gold standard immunohistochemical assessments, the relative contributions of fibrillar and non‐fibrillar Aβ components to the in vivo Aβ‐PET signal remain unclear. Thus, we obtained two murine cerebral amyloidosis models that present with distinct Aβ plaque compositions and performed regression analysis between immunohistochemistry and Aβ PET to determine the biochemical contributions to Aβ‐PET signal in vivo.
Process Mapping: How to Reengineer Your Business Processes

Do You Need a Roadmap? Reengineer Your Business Processes. Role of Process Mapping in Reengineering. Do You Really Understand Your Processes? Process Mapping Success Stories. IDEF Process Mapping Methodology. Create a Process Mapping Team. Process Mapping Software Tool Selection. How to Collect Data for Process Mapping. Process Map Implementation. Change It! Notes. Suggested Reading. Acronyms. Points of Contact. Glossary. Index.
VREED

The paper introduces a multimodal affective dataset named VREED (VR Eyes: Emotions Dataset) in which emotions were triggered using immersive 360° Video-Based Virtual Environments (360-VEs) delivered via Virtual Reality (VR) headset. Behavioural (eye tracking) and physiological signals (Electrocardiogram (ECG) and Galvanic Skin Response (GSR)) were captured, together with self-reported responses, from healthy participants (n=34) experiencing 360-VEs (n=12, 1--3 min each) selected through focus groups and a pilot trial. Statistical analysis confirmed the validity of the selected 360-VEs in eliciting the desired emotions. Preliminary machine learning analysis was carried out, demonstrating state-of-the-art performance reported in affective computing literature using non-immersive modalities. VREED is among the first multimodal VR datasets in emotion recognition using behavioural and physiological signals. VREED is made publicly available on Kaggle1. We hope that this contribution encourages other researchers to utilise VREED further to understand emotional responses in VR and ultimately enhance VR experiences design in applications where emotional elicitation plays a key role, i.e. healthcare, gaming, education, etc.
RFTemp: Monitoring Microwave Oven Leakage to Estimate Food Temperature

Microwave ovens have been widely used in recent years to heat food quickly and efficiently. Users estimate the time to heat the food by prior knowledge or by trial and error process. However, this often results in the food being over-heated or under-heated, destroying the nutrients. In this paper, we present RFTemp, a system that can monitor microwave oven leakage to estimate the temperature of the food that is being heated and thus estimate the accurate time when the food has reached the targeted temperature. To design such a system, we propose an innovative microwave leakage sensing procedure and a novel water-equivalent food model to estimate food temperature. To evaluate the real-world performance of RFTemp we build a prototype using software defined radios and conducted experiments on various food items using household microwave ovens. We show that RFTemp can estimate the temperature of the food with a mean error of 5◦C , 2x improvement over contactless infrared thermometer and sensors.
Winect: 3D Human Pose Tracking for Free-form Activity Using Commodity WiFi

WiFi human sensing has become increasingly attractive in enabling emerging human-computer interaction applications. The corresponding technique has gradually evolved from the classification of multiple activity types to more fine-grained tracking of 3D human poses. However, existing WiFi-based 3D human pose tracking is limited to a set of predefined activities. In this work, we present Winect, a 3D human pose tracking system for free-form activity using commodity WiFi devices. Our system tracks free-form activity by estimating a 3D skeleton pose that consists of a set of joints of the human body. In particular, we combine signal separation and joint movement modeling to achieve free-form activity tracking. Our system first identifies the moving limbs by leveraging the two-dimensional angle of arrival of the signals reflected off the human body and separates the entangled signals for each limb. Then, it tracks each limb and constructs a 3D skeleton of the body by modeling the inherent relationship between the movements of the limb and the corresponding joints. Our evaluation results show that Winect is environment-independent and achieves centimeter-level accuracy for free-form activity tracking under various challenging environments including the none-line-of-sight (NLoS) scenarios.