Miracle-dz/UniFAR-FTUs huggingface dataset:
A study in dynamic neural control of semiconductor fabrication processes

This paper describes a generic dynamic control system designed for use in semiconductor fabrication process control. The controller is designed for any batch silicon wafer process that is run on equipment having a high number of variables that are under operator control. These controlled variables include both equipment state variables such as power, temperature, etc., and the repair, replacement, or maintenance of equipment parts, which cause parameter drift of the machine over time. The controller consists of three principal components: 1) an automatically updating database, 2) a neural-network prediction model for the prediction of process quality based on both equipment state variables and parts usage, and 3) an optimization algorithm designed to determine the optimal change of controllable inputs that yield a reduced operation cost, in-control solution. The optimizer suggests a set of least cost and least effort alternatives for the equipment engineer or operator. The controller is a PC-driven software solution that resides outside the equipment and does not mandate implementation of recommendations in order to function correctly. The neural model base continues to learn and improve over time. An example of the dynamic process control tool performance is presented retrospectively for a plasma etch system. In this study, the neural networks exhibited overall accuracy to within 20% of the observed values of . 986, . 938, and . 87 for the output quality variables of etch rate, standard deviation, and selectivity, respectively, based on a total sample size of 148 records. The control unit was able to accurately detect the need for parts replacements and wet clean operations in 34 of 40 operations. The controller suggested chamber state variable changes which either improved performance of the output quality variables or adjusted the input variable to a lower cost level without impairment of output quality.
Making new and integrated sense of heterogeneous pre‐eclampsia

Pre‐eclampsia is a dangerous condition that effects around 3‐8% of all pregnancies. Due to the complexity of its origin, condition and relationships with a host of factors it is colloquially known as the “disease of theories”. Arguably well established reductionist approaches inherent in the domain of disease treatment have as yet been unable to unravel this problem and the only effective treatment currently available is early delivery of the foetus and placenta. Systems Thinking however is claimed as a vehicle for tackling complex problems and as a framework for seeing interrelationships rather than isolated things and events. Elaborating on a new paradigm of systems thinking established from cancer and taking into account other emerging works of new thinking for pre‐eclampsia, proposals are made that might prove useful for the understanding and potential treatment of the condition.
Design, Synthesis, Antibacterial Activity and in Silico Studies of Novel Quinolone Fused with Triazine, Thiadiazole and Oxadiazole Heterocycles

Abstract We have strategically designed and synthesized some novel quinolone fused with hybrid heterocycles 7-chloro-1-ethyl-6-fluoro-4-oxo-N'-(arylcarbonothioyl)-1,4-dihydroquinoline-3-carbohydrazides (3a–m), 7-chloro-1-ethyl-6-fluoro-3-(5-mercapto-4-aryl-4H-1,2,4-triazol-3-yl)quinolin-4-ones (4a–m), 7-chloro-1-ethyl-6-fluoro-3-(5-(arylamino)-1,3,4-thiadiazol-2-yl)quinolin-4(1H)-ones (5a–m) and 7-chloro-1-ethyl-6-fluoro-3-(5-(arylamino)-1,3,4-oxadiazol-2-yl)quinolin-4(1H)-ones (6a–m) and screened them against bacterial strains. Results of antibacterial efficacy revealed that compounds with electron-withdrawing groups like 3b, 3c, 3d, 4c, 4d, 4e, 5b, 5c and 5d showed better activity against different bacterial strains among the synthesized compounds 3a–m, 4a–m, and 5a–m while compounds having electron-donating groups like 6h, 6i, 6j and 6k displayed better activity in synthesized compounds 6a–m. Furthermore, molecular docking against microbial DNA gyrase could throw light into the plausible mechanism of action and thermodynamic interactions governing the binding of these molecules. The article provides various synthetic approaches for strategically designed different hybrid heterocycles which were further evaluated for their biological activities against bacterial strains, to offer the findings for future research and to give a path-breaking lead in designing potent compounds managing the bacterial resistance strains. Graphical Abstract
Influence of Misalignments on EHD Lubrication in Hypoid Gears

The thermal elastohydrodynamic analysis of lubrication is applied to investigate the influence of misalignments of the meshing members on EHD lubrication in hypoid gears. The calculation is based on the simultaneous solution of the Reynolds, elasticity, energy, and Laplace’s equations. The full thermal EHD lubrication analysis is applied, therefore, the oil viscosity variation with respect to pressure and temperature and the density variation with respect to pressure are included. The real shape of the gap existing between the contacting tooth surfaces is treated, based on gear teeth geometry defined by the gear processing method and including the misalignments of mating members. By using the corresponding computer program, the influence of pinion’s running offset and axial adjustment errors, and angular position error of pinion axis on maximum oil film pressure and temperature, EHD load carrying capacity, and on power losses in the oil film is investigated. The obtained results are presented and discussed.Copyright © 2007 by ASME
Weight and cost estimation for spaceborne radar systems

A simplified method is presented for making preliminary weight and cost estimates of spaceborne radar satellites and constellations for the detection of airborne moving targets. The power-aperture product requirement of a single spaceborne radar for a given area coverage rate and target size is written as a function of satellite altitude. Using this, the satellite weight and cost are estimated. The number of satellites required for continuous Earth coverage (satellite constellation) is determined as a function of satellite altitude. Combining the number of satellites in the constellation, and their weights and costs results in equations for weight and cost estimation.
Analysis of Purity and Concentration of Isolated DNA in Making Raw DNA of Rat Species

Analysis of the purity and concentration of isolated DNA in the manufacture of standard rat DNA was carried out to see whether the isolation carried out could produce good quality DNA. The purpose of this study is to provide information on the manufacture of raw DNA in species DNA testing where the raw material that has been purchased so far made from synthetic materials can be more economical if using DNA material derived from the meat raw material of the target species. The DNA extraction method used is the column spin method or column centrifuge using the Intron Patho Gene-Spin (Viral DNA/RNA) extraction kit. Analysis method of concentration and purity of isolated DNA was analyzed based on the average value of concentration and purity which was read using a nanophotometer. Based on the results of the research conducted, the results of the isolated DNA concentration values ​​were in the concentration range of 41,250 ng/ mL to 42,300 ng/mL, with the average concentration of isolated DNA was 41,777 ng/mL. For the value of the purity of the isolated DNA whose absorbance was read using a nanophotometer at a wavelength of A260/A280, the results were between 2,301 to 2,384 with the average value of purity being at 2,326. This study concludes that all the extracted samples that showed the results of the DNA analysis produced were included in the good DNA category.
Degradation analysis on trend gamma process

Manufactures always face a big challenge to obtain the sufficient reliability information for high‐quality products when only a relatively short time period is available for an internal life testing. Fortunately, if QCs exists, whose degradation over time can be related to reliability, an approach is suggested to collect sufficient degradation data for estimating the product's lifetime distribution more accurately. In numerical applications, the gamma process (GP) is commonly used when the degradation path is strictly increasing. However, in some circumstances, the GP is not able to successfully capture the degradation path. One resolution to tackle this problem is to consider the random effect into the GP model. In this paper, we propose a trend gamma process (TGP), which integrated the merits of trend function into a GP model, as an alternative approach to overcome this obstacle. The proposed TGP model is a generalized formulation of GP model, and it is attempted to transform a monotonic stochastic process into a GP. The results based on simulation studies and real data examples illustrate that our proposed TGP model is suitable for widely use when the degradation path is monotonically increasing.
Bias and W/L dependence of capacitive coupling coefficients in floating gate memory cells

In this paper, a complete study of capacitive coupling coefficients dependence on bias and W/L will be presented, including a review on classic methods to extract their value from electrical characterization. Capacitive coupling ratios have been usually adopted to model floating gate (FG) memory cells, in particular to deduce the value of FG potential. Now they re determined by means of a new model (recently proposed in the literature), starting from a new procedure to evaluate the FG potential. Results obtained with the new model will be compared to classic values. Particularly, their bias dependence (during write/read/erase of Flash memory cells) will be deeply investigated, thus demonstrating the limits of considering them constants, as is usually done. by analyzing their W/L dependence, we will deduce useful information on the effects of scaling and the role played by fringing capacitances. The most important methods reported in the literature to estimate the control gate and drain capacitive coupling ratios will be accurately reviewed, thus showing that such procedures are often cumbersome and inaccurate. It is worth noting that for the first time, /spl alpha//sub B/ and /spl alpha//sub S/ will be studied in detail.
Towards spatializing consumer energy sustainability. Empirical findings about the policy and practice of energy conservation and poverty in Barcelona and North Macedonia

ABSTRACT The way citizens make meaning, take decisions, and act differs from expert-informed expectations encapsulated in policies. Inspired by spatial theory, we explore the divide between official and everyday framings of consumer energy sustainability that is potentially limiting citizen engagement. Our argument draws from contrasting official and everyday framings encountered in narratives and practices related to (a) energy conservation in commercial buildings in Barcelona, and (b) household energy poverty in North Macedonia. Our interpretation reveals a major difference between official and everyday framings, whereby the former decontextualize practices and the latter knock down spatial borders to engage with energy through a wide array of material interventions and social structures that are not specific to intervention sites and policy matters. Everyday narratives reveal a spatial critique of the inconsistencies in official policy and practice that highlights the existence of systemic unequal participation, inequalities, and injustice. The appraisal of these inconsistencies limits the legitimacy of government and corporations, as well as the appeal of official policies and practices. The spatialization of energy consumption according to everyday epistemologies, whereby practices are appraised in their socio-material context calls for re-politicizing energy consumption in accordance with conceptions of energy citizenship – i.e. embracing its original grounding on bottom-up knowledge formation and political struggle.
Control of surfaces in confined spaces : Tab-aileron control system development

This thesis forms part of the Control Surfaces in Confined Spaces (CoSICS) project conducted at Stellenbosch University. The aim of this project is reduction of control surface actuator footprints on the existing wing structures of commercial airliners such as the Airbus A320 and A330. This is achieved by reducing control surface hinge moments through the application of trailing edge tabs. This results in smaller actuator requirements. The first tier of the project focussed on the geometric optimisation of the tab applied to an aileron. This thesis focusses on the development of dynamic control of the aileron through either tab-only or concurrent tab and aileron actuation. In the effort to develop dynamic control, a fully coupled generalised dynamic model of the tab and aileron is derived and presented. Through linearisation of this model, linear controllers are developed. Two distinctly different controllers are presented; the first controller makes use of classical methods for control of the tab-only actuated aileron and the second controller makes use of modern control techniques such as full state feedback to facilitate controlled concurrent tab and aileron actuation. Each proposed controller is evaluated in terms of dynamic performance, robustness, disturbance rejection and noise immunity. Based on the controller development, a summary of dynamic actuator requirements is given. Practical verification of the model and the controller performance is then undertaken. The development of the necessary hardware and software is also presented. The concept of aileron control through tab-only actuation and concurrent tab and aileron actuation is then validated. Conclusion are then drawn about the accuracy of the theoretical model and the practical performance of the controllers. The thesis is concluded with recommendations for future work to increase the fidelity of the model. Important aspects about the practical implementation of the concept on commercial jetliners are also summarised.
Factors associated with the weight change trend in the first year of the COVID-19 pandemic: the case of Turkey

BACKGROUND/OBJECTIVES To determine the weight change trend among the adult Turkish population after 1 yr of the coronavirus disease 2019 (COVID-19) pandemic and factors associated with weight change. MATERIALS/METHODS This cross-sectional study was conducted between 26 February and 6 March 2021 using an online questionnaire that included questions for sociodemographic variables, eating habits, stress level, and the Three-Factor Eating Questionnaire-R18. Those who weighed themselves 1–2 weeks before the pandemic was declared in Turkey and remembered their weight were invited to participate in the study. Trends in weight and body mass index (BMI) change were calculated. The variables associated with a 1% change in BMI were assessed using hierarchical regression analysis. RESULTS The study was conducted with 1,630 adults (70.25% female) with a mean age of 32.09 (11.62) yrs. The trend of weight change was found to increase by an average of 1.15 ± 6.10 kg (female +0.72 ± 5.51, male +2.16 ± 7.22 kg) for the first year of the COVID-19 pandemic. The rate of participants with a normal BMI (18.50–24.99 kg/m2) decreased to 51.91% from 55.75%. Consuming an "Increased amount of food compared to before the pandemic" was found to be the independent variable that had the strongest association with a 1% increase in BMI (β = 0.23 P < 0.001). The average change in the BMI was higher in older individuals than in those who were younger. A high stress level was associated with a decrease in BMI (β = –0.04 P = 0.048). CONCLUSIONS In this study, the factors associated with weight change after 1 yr of the pandemic in the Turkish population was reported for the first time. A high stress level and increased weight gain trend still occur in Turkey after 1 yr of the pandemic.
Exciting Magnetic Dipole Mode of Split-Ring Plasmonic Nano-Resonator by Photonic Crystal Nanocavity

On-chip exciting electric modes in individual plasmonic nanostructures are realized widely; nevertheless, the excitation of their magnetic counterparts is seldom reported. Here, we propose a highly efficient on-chip excitation approach of the magnetic dipole mode of an individual split-ring resonator (SRR) by integrating it onto a photonic crystal nanocavity (PCNC). A high excitation efficiency of up to 58% is realized through the resonant coupling between the modes of the SRR and PCNC. A further fine adjustment of the excited magnetic dipole mode is demonstrated by tuning the relative position and twist angle between the SRR and PCNC. Finally, a structure with a photonic crystal waveguide side-coupled with the hybrid SRR–PCNC is illustrated, which could excite the magnetic dipole mode with an in-plane coupling geometry and potentially facilitate the future device application. Our result may open a way for developing chip-integrated photonic devices employing a magnetic field component in the optical field.
LOW LATENCY DEEP LEARNING INFERENCE MODEL FOR DISTRIBUTED INTELLIGENT IOT EDGE CLUSTERS

Edge computing is a new paradigm enabling intelligent applications for the Internet of Things (IoT) using mobile, low-cost IoT devices embedded with data analytics. Due to the resource limitations of Internet of Things devices, it is essential to use these resources optimally. Therefore, intelligence needs to be applied through an efficient deep learning model to optimize resources like memory, power, and computational ability. In addition, intelligent edge computing is essential for real-time applications requiring end-to-end delay or response time within a few seconds. We propose decentralized heterogeneous edge clusters deployed with an optimized pre-trained yolov2 model. In our model, the weights have been pruned and then split into fused layers and distributed to edge devices for processing. Later the gateway device merges the partial results from each edge device to obtain the processed output. We deploy a convolutional neural network (CNN) on resource-constraint IoT devices to make them intelligent and realistic. Evaluation was done by deploying the proposed model on five IoT edge devices and a gateway device enabled with hardware accelerator. The evaluation of our proposed model shows significant improvement in terms of communication size and inference latency. Compared to DeepThings for 5 X 5 fused layer partitioning for five devices, our proposed model reduces communication size by ~ 14.4% and inference latency by ~16%.
Single-Chip 77GHz Radar Sensor and its Automotive Applications

This paper describes the development of a compact and low cost millimeter wave Doppler radar sensor (77GHz band), which can measure the vehicle ground speed precisely. The sensor has three unique features: First, all the radio frequency components are integrated into a single chip, including a millimeter wave transceiver and an on-chip antenna. Then, the chip package is made of plastic resin without use of expensive ceramic. Finally, a tiny dome-shaped resin lens is attached to the chip to collimate waves. These technologies enable the sensor to measure 53 × 71 × 65 mm3, to weight 115 grams. Compared to a conventional optical measuring instrument for example, the sensor weights only about fifteenth and is onefifth of the size, while the measurement accuracy is almost comparable. So this sensor seems to have a variety of potential applications. In this paper, we also considered the feasibility of some other applications than just measuring ground speed. One is the yaw rate detection by using two sensors mounted on both sides of the vehicle. It can be calculated from differential speed between sensors. From the experimental results, we found that the detection was possible and the limit of sensitivity depended on the speed measurement accuracy which is under 2% variation. The other possible application is detecting obstruction. Although it was difficult to cover from 0 meters to far side with one sensor because of its narrow beam shape, we confirmed from experiments that the sensor was able to detect vehicles in the next lane in the range from at least 10 to 60 meters. Language: en
AUV survey design applied to oceanic deep convection

Oceanic processes are characterized by both temporal evolution and spatial variability. For surveys carried out using autonomous underwater vehicles (AUVs), compromises between resolution, total survey time, total survey area, and vehicle speed must be made. In this paper, quantitative tools for optimizing surveys are demonstrated in the context of mapping open-ocean deep convection. The survey performance is measured by a metric of total survey error, given by the squared difference between the true and reconstructed field. The convective ocean model is represented by a rectangular volume of water volume. Cooling at the top surface introduces convection which is characterized by spatially distributed convective plumes. The authors focus on reconstructing a synoptic map on the plume scale (1 km) utilizing single or multiple AUVs. It is shown that the most dramatic gain in error reduction come from using multiple vehicles.
Risk-Scoring System for Prediction of Non-Curative Endoscopic Submucosal Dissection Requiring Additional Gastrectomy in Patients with Early Gastric Cancer

Purpose When patients with early gastric cancer (EGC) undergo non-curative endoscopic submucosal dissection requiring gastrectomy (NC-ESD-RG), additional medical resources and expenses are required for surgery. To reduce this burden, predictive model for NC-ESD-RG is required. Materials and Methods Data from 2,997 patients undergoing ESD for 3,127 forceps biopsy-proven differentiated-type EGCs (2,345 and 782 in training and validation sets, respectively) were reviewed. Using the training set, the logistic stepwise regression analysis determined the independent predictors of NC-ESD-RG (NC-ESD other than cases with lateral resection margin involvement or piecemeal resection as the only non-curative factor). Using these predictors, a risk-scoring system for predicting NC-ESD-RG was developed. Performance of the predictive model was examined internally with the validation set. Results Rate of NC-ESD-RG was 17.3%. Independent pre-ESD predictors for NC-ESD-RG included moderately differentiated or papillary EGC, large tumor size, proximal tumor location, lesion at greater curvature, elevated or depressed morphology, and presence of ulcers. A risk-score was assigned to each predictor of NC-ESD-RG. The area under the receiver operating characteristic curve for predicting NC-ESD-RG was 0.672 in both training and validation sets. A risk-score of 5 points was the optimal cut-off value for predicting NC-ESD-RG, and the overall accuracy was 72.7%. As the total risk score increased, the predicted risk for NC-ESD-RG increased from 3.8% to 72.6%. Conclusions We developed and validated a risk-scoring system for predicting NC-ESD-RG based on pre-ESD variables. Our risk-scoring system can facilitate informed consent and decision-making for preoperative treatment selection between ESD and surgery in patients with EGC.