Miracle-dz/UniFAR-FTUs huggingface dataset:
Millimeter-wave characteristics of flip-chip interconnects for multichip modules

Electromagnetic simulation and measurement data of flip-chip transitions are presented. First-order effects are identified and design criteria for millimeter-wave multichip interconnects are derived. Results cover chip detuning and bump geometry as well as simplified modeling. In a coplanar environment, the flip-chip scheme provides interconnects with excellent low-reflective properties. For conductor-backed structures, parasitic modes occur leading to unwanted crosstalk. These effects dominate the behavior so that overall performance of the flip-chip scheme can be evaluated properly only in conjunction with the actual motherboard packaging setup.
Digital time-of-flight measurement for ultrasonic sensors

Ultrasonic sensor measurements are mostly based on the determination of the time of flight (TOF). The authors present the development of a digital algorithm for pulse-echo measurement applications, based on the use of a cross-correlation function to determine the TOF. Some experimental results are presented, and the possibility of realizing a low-cost real-time measurement system is considered. >
Defocus Image Deblurring Network With Defocus Map Estimation as Auxiliary Task

Different from the object motion blur, the defocus blur is caused by the limitation of the cameras’ depth of field. The defocus amount can be characterized by the parameter of point spread function and thus forms a defocus map. In this paper, we propose a new network architecture called Defocus Image Deblurring Auxiliary Learning Net (DID-ANet), which is specifically designed for single image defocus deblurring by using defocus map estimation as auxiliary task to improve the deblurring result. To facilitate the training of the network, we build a novel and large-scale dataset for single image defocus deblurring, which contains the defocus images, the defocus maps and the all-sharp images. To the best of our knowledge, the new dataset is the first large-scale defocus deblurring dataset for training deep networks. Moreover, the experimental results demonstrate that the proposed DID-ANet outperforms the state-of-the-art methods for both tasks of defocus image deblurring and defocus map estimation, both quantitatively and qualitatively. The dataset, code, and model is available on GitHub: https://github.com/xytmhy/DID-ANet-Defocus-Deblurring.
An Efficient Method for Hyperbolic-Based Localization in SAR RFID Systems

Radio frequency identification (RFID) is one of the major wireless communication technologies and has been applied in the supply chain and retail network for a long time. By contrast, the application of RFID in localization emerges in recent years. Besides, neither precision nor real time of existing RFID localization methods is satisfactory enough. In this article, we propose a novel method called HyLoc for localization of RFID tags based on the hyperbolic model. The problem to locate RFID tags is modeled as the solution of hyperbolic equations formed by synthetic aperture radar (SAR). To solve the equations quickly, the linear least-squares (LLS) algorithm is first used to find the approximate solution, and then, the estimation error is corrected by the Taylor series method for higher accuracy. Comparisons of performance with the state-of-the-art methods in SAR RFID localization are carried out through simulations and experiments. The results show that the proposed method is closer to the Cramér–Rao lower bound than the holography method at high noise level and more efficient than the ordinary nonlinear least-squares (NLS) method without loss of accuracy.
Investigating the Temporal Instability in Injury Severity Outcomes of Clear and Adverse Weather Crashes on Rural Mountainous Highways

Analysis of driver injury severity based on weather conditions on rural highways is limited in the literature. Such analyses provide insights useful to policymakers in optimizing the allocation of limited resources based on weather conditions. Furthermore, if there is a possibility of factors exhibiting temporal instability, then an aggregate analysis can lead to erroneous allocation of funds. In this study, separate models for clear and adverse weather conditions were developed for each of the years from 2015 to 2019 using crash data from a rural mountainous highway corridor. A random-intercept Bayesian logistic approach was used to analyze the dichotomous injury severity response and capture the between-crash variance. An efficient Markov chain Monte Carlo sampling technique known as the No-U-Turn Hamiltonian Monte Carlo was employed to sample the posterior distributions of parameter estimates. Likelihood ratio tests provided statistical significance of the temporal instability and also the differences in driver injury severities resulting from clear and adverse weather crashes. While most of the variables demonstrated temporal instability, some factors exhibited temporal stability over a short period of time and only during clear weather conditions. Findings from the separate models suggest that there are major differences in both the combination and magnitude of the significant contributing factors. Implementation of confirmatory warning signs, variable message signs, connected vehicle technology, strict enforcements during different times and locations, and driver awareness programs have been recommended as suitable countermeasures. The findings and recommendations could potentially help in guiding the respective agencies in formulating injury severity mitigation policies and strategies.
In-flight calibration of a helicopter-mounted Daedalus multispectral scanner

A convenient technique that has been used to calibrate, in-flight, a helicopter-mounted Daedalus multispectral scanner is described. It used four large canvas panels laid out in a square with a Spectralon panel as a reference. A calibrated Barnes modular multispectral radiometer, carried on a 2.2-m boom, was rotated around a 2.5-m high tripod at the center of the square. The radiometer sampled the four large panels and the Spectralon panel once every two minutes. Atmospheric spectral transmittance measurements were made using a filter radiometer on an autotracking mount during the morning of the flight. The reflectance and optical depth data were used in an atmospheric radiative transfer code to predict the spectral radiances at the scanner. The calibration was completed by comparing the image digital counts to the predicted spectral radiances.
Influence of plasma treatment on the improvement of surface energy [packaging]

Surface treatment is increasingly important in electronic packaging. Reasons for this development are increasing demands on the reliability of component packaging and the application of different materials with either high-energy or low-energy surfaces. High-energy materials include metals, metal oxides and inorganic compounds. Low-energy materials include organic materials and water. The surface tension of a liquid or the surface energy of a solid material is a key factor to the quality and reliability of electronic packaging. It influences the wettability, spreading and adhesion of polymers and metals. Good wettability during soldering or good adhesion between polymer tapes depends on the surface finish. For example, oxide layers and organic contamination lead to a lower surface energy of metals. The surface energy of a solid material can be influenced by chemical, thermal and mechanical methods. The influence of plasma treatment on the surface energy of solid materials is under investigation at the Electronics Technology Laboratory. Surface energies calculated on the base of measuring the contact angle are determined and the differences between untreated and plasma-treated materials are discussed. Conclusions can be drawn about the wettability and adhesion of the surfaces. The paper presents a short overview of the theoretical fundamentals of contact angle measurement and surface energy as well as practical results with different materials.
Validation of a wavelet algorithm implemented in a fixed-point DSP for detection and analysis of electrical transients

In this work we develop an on-line algorithm to detect and classify transients produced in capacitor buses during connection and disconnection. The algorithm was implemented in a Blackfin ® BF-535 Processor. Transients are modeled as an oscillation modulated in amplitude by an exponential decay. The detection process consists in detecting the transient's onset, while the classification consists in measuring the oscillation frequency and decay parameters. Two validations were performed, one against a database of simulated transients and the other with a database of experimental signals. In the last case, as no gold standard is available, we assessed the degree of agreement against an off-line algorithm implemented in a PC. The algorithm performed good in onset detection, where the absolute error was under 1 ms. Also exhibited good performance in frequency classification, where the global relative error was under 1.8%. In contrast, the τ parameter classification relative error only reached an overall range under the 22%. This motivated future improvements in this aspect.
A Review of Nanomaterial Based Scintillators

Recently, nanomaterial-based scintillators are newly emerging technologies for many research fields, including medical imaging, nuclear security, nuclear decommissioning, and astronomical applications, among others. To date, scintillators have played pivotal roles in the development of modern science and technology. Among them, plastic scintillators have a low atomic number and are mainly used for beta-ray measurements owing to their low density, but these types of scintillators can be manufactured not in large sizes but also in various forms with distinct properties and characteristics. However, the plastic scintillator is mainly composed of C, H, O and N, implying that the probability of a photoelectric effect is low. In a gamma-ray nuclide analysis, they are used for time-related measurements given their short luminescence decay times. Generally, inorganic scintillators have relatively good scintillation efficiency rates and resolutions. And there are thus widely used in gamma-ray spectroscopy. Therefore, developing a plastic scintillator with performance capabilities similar to those of an inorganic scintillator would mean that it could be used for detection and monitoring at radiological sites. Many studies have reported improved performance outcomes of plastic scintillators based on nanomaterials, exhibiting high-performance plastic scintillators or flexible film scintillators using graphene, perovskite, and 2D materials. Furthermore, numerous fabrication methods that improve the performance through the doping of nanomaterials on the surface have been introduced. Herein, we provide an in-depth review of the findings pertaining to nanomaterial-based scintillators to gain a better understanding of radiological detection technological applications.
A voltage model flux observer design requiring no stator resistance or voltage signal information

Stator flux estimation using the voltage model flux observer requires voltage sensors and is highly sensitive to the stator resistance variation, especially at low speed. This paper designs a new sliding mode voltage model flux observer (SMVMFO). This closed loop SMVMFO is based on the current estimation error and the sliding mode functions are derivative of the stator flux along /spl alpha/ and /spl beta/ axes respectively. Therefore, when the sliding mode occurs, the stator flux can be estimated by a mere integration of the sliding mode functions without requiring any voltage signal and the stator resistance information. Thus the proposed observer does not require any voltage signal information, either command or measured one, and is also completely insensitive to the stator resistance variation. The observer stability is verified. Simulation and experimental results for a direct field oriented induction motor drive system are presented to validate the proposed algorithm.
Economics of Young Female Management

Proceedings, The Range Beef Cow SymposiumXVII December 11, 12 and 13, 2001 Casper, Wyoming Economics of Young Female Management By Dillon M. Feuz University of Nebraska Panhandle Research and Extension Center Scottsbluff, NE INTRODUCTION What is the value of a heifer calf, a bred heifer, or a re-bred 2
Printed Flexible LC Filter Using Additive Micro-Dispensing With Silver Conductive Paste and ECA for Component Attachment

Filters are used in a variety of signal processing applications in commercial and defense electronics. The use of additively printed electronics in high-frequency applications requires an understanding of the process-performance interactions versus frequency of operation. Assembly of filters for integration into existing circuits requires additively printed metallization traces in addition to component attachment methods. Comparison of frequency response of the additively-printed filtering circuits vs conventional filters subtractively-fabricated on rigid substrates is needed to determine the performance parity of additive fabrication methods. In this paper, a micro-dispensing device is used to print conductive traces and electrically conductive adhesive (ECA) pads for the attachment of components. The effect of different print parameters on the width and height of the trace has been studied. Mechanical and electrical properties also play an important role in the study of different sintering conditions. Optimized parameters from the printing process and sintering analysis are used to print and compare commercially available LC filter circuitry using the Bode plot.
A consistent model for the thickness dependence of intrinsic breakdown in ultra-thin oxides

A consistent model for the intrinsic time dependent dielectric breakdown (TDDB) of thin oxides is introduced. This model links the existing anode hole injection and the electron trap generation models together and describes wearout as a hole induced generation of electron traps. Breakdown is defined as conduction via these traps from one interface to the other. Implementing the model in a simulator, the oxide thickness dependence of the Weibull slope of the Q/sub BD/-distribution is predicted, and, using the unique relationship between hole fluence and generated electron trap density, the decrease of the critical hole fluence with oxide thickness is explained.
Scheduling of Pavement Maintenance To Minimize Traffic Delays

Traffic delays caused by pavement maintenance activities are a major concern to transportation engineers. There is a need to carefully plan and schedule such activities in order to minimize traffic delays. Unfortunately, this is a complex problem that cannot be easily solved by means of conventional optimization tools. A scheduling methodology is presented that uses genetic algorithms (GAs) to minimize traffic delays subject to constraints of maintenance operational requirements. The flexibility in problem modeling and the robust search capability of the GA technique make it a practical analytical tool for this problem. Pavement distress conditions, traffic flow data, and maintenance requirements are the major input parameters of the problem. Based on Singapore’s maintenance practice and traffic delay models for four-lane two-way primary roads, a computer program has been developed. This program is applied to solve a hypothetical numerical example problem to illustrate the formulation and solution procedure of the proposed methodology.
Accelerating pre-formulation investigations in early drug product lifecycle using predictive methodologies and computational algorithms.

Precisely developed computational methodologies can allow the drug product lifecycle process to be time-efficient, cost-effective and reliable through a thorough fundamental understanding at the molecular level. Computational methodologies include computational simulations, virtual screening, mathematical modeling and predictive tools. In light of current trends and increased expectations of product discovery in early pharmaceutical development, we have discussed different case studies. These case studies clearly demonstrate the successful application of predictive tools alone or in combination with analytical techniques to predict the physicochemical properties of drug substances and drug products, thereby shortening research and development timelines. The overall goal of this report is to summarize unique predictive methodologies, which can assist pharmaceutical scientists in achieving time-sensitive research goals and avoiding associated risks that can potentially affect the drug product quality.
Single-input three-output variable Q and 𝛚0 filters using universal voltage conveyors

This article presents the possible usage of the universal voltage conveyor (UVC) for the design of a Kerwin–Huelsman–Newcomb-equivalent filter working in the voltage mode. When compared with the known solution using operational amplifiers, the proposed structure embodies new advantages. To support the theoretical results, the behaviour of the structure designed has been verified by PSpice-OrCAD simulations and furthermore by experimental measurements using the UVC-N1C active element.
Genome-wide DNA methylation profiling in chronic lymphocytic leukaemia

Background: DNA methylation aberrations are widespread among the malignant B lymphocytes of patients with chronic lymphocytic leukaemia (CLL), suggesting that DNA methylation might contribute to the pathogenesis of CLL. Aim: We aimed to explore the differentially methylated positions (DMPs) associated with CLL and screen the differentially methylated and expressed genes (DMEGs) by combining public databases. We aimed to observe the direction of each DMEG in CLL based on the DMPs in the promoter and the body region respectively to narrow down DMEGs. We also aimed to explore the methylation heterogeneity of CLL subgroups and the effect of B cells maturation on CLL. Methods: In this population-based case control study, we reported a genome-wide DNA methylation association study using the Infinium HumanMethylation450 BeadChip, profiling the DNA methylation of CD19+ B Cells from 48 CLL cases and 28 healthy controls. By integrating methylation data and expression data from public databases, gene sets were jointly screened, and then the relationship between methylation sites in promoter and body region and expression of each gene was explored. In addition, support vector machine (SVM) classification algorithm was used to identify subgroups of CLL cases based on methylation pattern, and the effect of B-cell differentiation related methylation sites on CLL-related sites was observed. Results: We identified 34,797 DMPs related to CLL across the genome, most of which were hypomethylated; the majority were located in gene body regions. By combining these DMPs with published DNA methylation and RNA sequencing data, we detected 26,244 replicated DMPs associated with 1,130 genes whose expression were significantly different in CLL cases. Among these DMEGs, nine low expressed DMEGs were selected with hypermethylated in promoter and hypomethylated in body region, and 83 high expressed DMEGs were selected with both hypomethylated in promoter and body region. The 48 CLL cases were divided into 3 subgroups based on methylation site by SVM algorithm. Over 92% of CpGs associated with B cell subtypes were found in CLL-related DMPs. Conclusion: The DNA methylation pattern was altered across the genome in CLL patients. The methylation of ZAP70, FMOD, and ADAMTS17 was significantly different between CLL cases and controls. Further studies are warranted to confirm our findings and identify the underlying mechanisms through which these methylation markers are associated with CLL.
Implementing Lean in Health Care: Making the Link Between the Approach, Readiness and Sustainability

This paper draws on the findings of three evaluations, two Hospitals and a Mental Health Trust in England, on the implementation of Lean within Health Care. The paper analyses the case studies not only to assess if the approach taken was process or continuous improvement but also to evaluate the degree to which conditions of readiness related to Lean were present. Organisational readiness factors include understanding of the process/system view, customer view, data and engaging the staff to ensure that Lean is not just about making poor processes more efficient by focusing on the tools. The paper introduces a typology of Lean implementation which could be used to situate organisations to understand their relationship between the approach taken and, the state of the conditions of readiness thus the level of sustainability which could be achieved.
Comparative Analysis of Tariffs-Restricted Trade Wars between the United States and China Under the Recent Past Four Presidents: Did they Achieve Their Objectives?

This paper provides a comparative analysis of the tariffs-restricted trade wars between the United States and China under the recent past four presidents of the United States by using the difference-in-differences estimator framework. The overarching objective of three of the four presidential administrations that engaged in trade wars was to reduce the United States’ trade deficits with China. This raised some research questions. Did each administration achieve its objective of reducing the trade deficits with China? If so, which administration more effectively reduced the trade deficits in comparison to their immediate predecessor? What lessons can future administrations and governments around the world draw from the outcomes of the tariffs-restricted trade wars between the United States and China? To determine which president – Trump, Obama, and Bush – most effectively utilized import tariffs to reduce the trade deficits with China, we specified and tested three different sets of hypotheses. In sync with a controlled experiment, we tested another three sets of hypotheses in which we compared Presidents Trump, Obama, and Bush to President Clinton who did not impose tariffs on China. Based on our estimated results, we rejected all the null hypotheses in favor of the alternative hypotheses, which suggest that Presidents Trump, Obama, and Bush did not achieve any significant reduction in the United States’ trade deficits with China through the use of tariffs relative to President Clinton. The important lesson drawn from these findings is that tariffs are counterproductive and ineffective policy strategy.
Theoretical Study on Ethylene Polymerization Catalyzed by Half-Titanocenes Bearing Different Ancillary Groups

Half-titanocenes are well known to show high activity for ethylene polymerization and good capability for copolymerization of ethylene with other olefins, and the ancillary ligands can crucially affect the catalytic performance. In this paper, the mechanisms of ethylene polymerization catalyzed by three half-metallocenes, (η5-C5Me5)TiCl2(O-2,6-iPr2C6H3) (1), (η5-C5Me5)TiCl2(N=CtBu2) (2) and [Me2Si(η5-C5Me4)(NtBu)]TiCl2 (3), have been investigated by density functional theory (DFT) method. At the initiation stage, a higher free energy barrier was determined for complex 1, probably due to the presence of electronegative O atom in phenoxy ligand. At the propagation stage, front-side insertion of the second ethylene is kinetically more favorable than back-side insertion for complexes 1 and 2, while both side insertion orientations are comparable for complex 3. The energy decomposition showed that the bridged cyclopentadienyl amide ligand could enhance the rigidity of the active species as suggested by the lowest deformation energy derived from 3. At the chain termination stage, β-H transfer was calculated to be a dominant chain termination route over β-H elimination, presumably owing to the thermodynamic perspective.