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The clearance between the die and punch for the trimming operation set could lead to one major defect that is burr formation on the sheet metal component. Hence, controlling this parameter is a necessity for getting a product without defects. Different studies have reported the burr height phenomenon by varying the sheet material and die clearances. From the previous analysis die clearances below 15% suffers formation of burr therefore is a challenging task to control burr formation. In the present study, an effort has been made to reduce the burr formation factor to control/eliminate burr formation while dealing with sheet metal operation for the Front Door Outer (FDO) panel of the vehicle. Four different clearances between the punch and die, that is 12%, 11%, 10%, and 9% are considered for the study. The results of the study suggests that 12% clearance the burr height was within the range of 0.737–0.663 mm. Similarly for 11%, 10% and 9% die clearance, the burr heights are 0.734–0.618 mm, 0.729–0.655 mm and 0.717–0.655 mm respectively. The burr height of 9% clearance die is very close to the acceptable higher range of 0.715 mm, while it maintains to remain within the lower acceptable range of 0.65 mm. The study suggests that trimming with 9% clearance provides better accuracy with a minimum burr within the acceptable range of 0.65–0.715 mm. Further a statistical process control for the process has been done which supports the optimized results. [ABSTRACT FROM AUTHOR]

Penalized Cox regression can efficiently be used for the determination of biomarkers in high-dimensional genomic data related to disease prognosis. However, results of Penalized Cox regression is influenced by the heterogeneity of the samples who have different dependent structure between survival time and covariates from most individuals. These observations are called influential observations or outliers. A robust penalized Cox model (Reweighted Elastic Net-type maximum trimmed partial likelihood estimator, Rwt MTPL-EN) is proposed to improve the prediction accuracy and identify influential observations. A new algorithm AR-Cstep to solve Rwt MTPL-EN model is also proposed. This method has been validated by simulation study and application to glioma microarray expression data. When there were no outliers, the results of Rwt MTPL-EN were close to the Elastic Net (EN). When outliers existed, the results of EN were impacted by outliers. And whenever the censored rate was large or low, the robust Rwt MTPL-EN performed better than EN. and could resist the outliers in both predictors and response. In terms of outliers detection accuracy, Rwt MTPL-EN was much higher than EN. The outliers who "lived too long" made EN perform worse, but were accurately detected by Rwt MTPL-EN. Through the analysis of glioma gene expression data, most of the outliers identified by EN were those "failed too early", but most of them were not obvious outliers according to risk estimated from omics data or clinical variables. Most of the outliers identified by Rwt MTPL-EN were those who "lived too long", and most of them were obvious outliers according to risk estimated from omics data or clinical variables. Rwt MTPL-EN can be adopted to detect influential observations in high-dimensional survival data.

For a very long time, the cannabis plant has been the subject of much scientific research, which has intensified in recent years due to its proven medicinal properties for the treatment of a large number of diseases. Cannabis contains more than a hundred different bio-molecules known as cannabinoids, then terpenes, essential oils and many other active components with proven pharmacological and phytotherapeutic effects that give excellent results in the treatment of many chronic diseases. It is for this reason that the cultivation of cannabis for medicinal purposes (Cannabis Sativa L.) has been legalized in many countries in Europe and around the world. In order to obtain a high-quality product – a dried flower of medical cannabis, a lot of attention must be paid to cultivation, as well as an expert and professional approach to the processing process after its harvest. This stage includes several interrelated processes, namely: trimming, drying, packaging, labeling, transportation and storage. The critical approach and the detailed investigation of all possible potential risk factors of each of these individual procedures has a crucial importance in distributing a high quality product to the consumers themselves. Before starting drying, the process of cutting off the excess sugar leaves and the possible presence of larger leaves left over from the harvesting process itself, i.e. trimming, which can be done mechanically and/or manually on wet or semi-dried biomass at your own choice. Most often, it is safest and best to approach trimming after drying. The most important operation after the completion of the cannabis harvest is the drying process. The correct selection and optimization of drying methods are a very current topic in recent years, which will enable the preservation of the quality of bioactive compounds in medical cannabis. Controlled temperature, relative humidity and drying speed are key to a preserved terpene and cannabinoid profile, good quality and increased shelf life of the finished product. With the development of the industrial production of medical cannabis, drying methods have made great progress from the traditional evaporation of water with hot air to include a freezing process. Which drying method will be chosen depends on several factors, such as: the type, the quantity, the available resources and capacities, and most importantly, the cannabinoid–terpene profile, that we want to obtain. The latest scientific research indicates a great interaction of cannabinoids and the terpenes present in medical cannabis in achieving the pharmacological effect, therefore the choice of the drying method is extremely important to retain all the present components. In addition to drying, all other procedures after the harvest of the plant itself should be analyzed in order to obtain consistent, reliable and high-quality medical cannabis for release on the market. [ABSTRACT FROM AUTHOR]

The first aim of this study was to calculate the prevalence of painful lesions of the digits (“alarm” lesions; ALs) in Swiss dairy herds and cow–calf operations over a three-year study period. The following ALs were included in the calculation: the M2 stage of digital dermatitis (DD M2), ulcers (U), white line fissures (WLF) of moderate and high severity, white line abscesses (WLA), interdigital phlegmon (IP) and swelling of the coronet and/or bulb (SW). Between February 2020 and February 2023, digit disorders were electronically recorded during routine trimmings by 40 specially trained hoof trimmers on Swiss cattle farms participating in the national claw health programme. The data set used consisted of over 35,000 observations from almost 25,000 cows from 702 herds. While at the herd-level, the predominant AL documented in 2022 was U with 50.3% followed by WLF with 38.1%, at the cow-level, in 2022, it was DD M2 with 5.4% followed by U with 3.7%. During the study period, within-herd prevalences of ALs ranged from 0.0% to a maximum of 66.1% in 2020. The second aim of this study was to determine herd- and cow-level risk factors associated with digital dermatitis (DD), U and white line disease (WL) in dairy cows using data from 2022. While for DD, analysed herd-level factors appeared to have a greater effect on the probability of its occurrence, the presence of U and WL was mainly associated with the analysed cow-level factors. The risk for DD increased with a higher herd trimming frequency. Herds kept in tie stalls had a lower risk for DD and WL and a higher risk for U compared to herds kept in loose housing systems. Herds with predominantly Holstein Friesian cows as well as Holstein Friesian cows had a higher risk for the occurrence of DD compared to herds and cows of other breeds. With increasing parity, cows had a higher risk of developing U and WL, whereas for DD, parity was negatively associated with prevalence. Cows trimmed during the grazing period had a higher risk of U and WL than cows trimmed during the housing period. These findings may contribute to improve management measures affecting the health of the digits in farms with structures similar to those evaluated in the current study, such as small herds with frequent access to pasture. Further research is warranted to demonstrate how measures addressing the current results combined with those of individual herd risk assessments might contribute to an improvement in the health of the digits in the respective dairy herds.

Since entering the era of the experience economy, consumers' attention gradually turns toward gaining a pleasant service process experience. This study addresses the service process problem, aiming to discover the root cause of the service process problem and solve it by analyzing the service touchpoints flow delivery process. A method for solving problems in the service process based on flow trimming is proposed. The trimming method and the stochastic dominance rule are applied to the field of service design, which provides new concepts for service process problem solving. The flow is taken as the entry point of the proposed method. First, a flow model of problematic service touchpoints is constructed based on the service blueprint method to visualize the flow delivery process. Then, service process trimming rules are proposed and used as guidance to trim flow disadvantages, and resource analysis is employed to obtain specific programs. Finally, the stochastic dominance rule is used to rank the programs and select the optimal program. Problem solving in the medical treatment service process was taken as an example to trim the fundamental flow disadvantages of problematic service touchpoints. A series of programs were obtained and the optimal program was selected for presentation based on the stochastic dominance rule, which verified the feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

Human epidermal growth factor receptor (EGFR) is involved in strong association with malignant proliferation, which has been shown to play a central role in the development and progression of non-small cell lung cancer and other solid tumors. The tumor-suppressor protein MIG6 is a negative regulator of EGFR kinase activity by binding at the activation interface of asymmetric dimer of EGFR kinase domain to disrupt EGFR dimerization and then inactivate the kinase. The protein adopts two discrete fragments 1 and 2 to directly interact with EGFR. It is revealed that the MIG6 fragment 2 is intrinsically disordered in free unbound state, but would fold into a well-structured β-hairpin when binding to EGFR, thus characterized by a so-called coupled folding-upon-binding process, which can be regarded as a compromise between favorable direct readout and unfavorable indirect readout. Here, a 23-mer F2P peptide was derived from MIG6 fragment 2, trimmed into a 17-mer tF2P peptide that contains the binding hotspot region of the fragment 2, and then constrained with an ordered hairpin conformation in free unbound state by disulfide stapling, finally resulting in a rationally stapled/trimmed stF2P peptide that largely minimizes the unfavorable indirect readout effect upon its binding to EGFR kinase domain, with affinity improved considerably upon the trimming and stapling/trimming. These rationally designed β-hairpin peptides may be further exploited as potent anti-lung cancer agents to target the activation event of EGFR dimerization. [ABSTRACT FROM AUTHOR]

Fiber-reinforced composites have a wide range of industrial applications owing to their light weight, high modulus, and good specific strength. Trimming using a mechanical punching tool is the fastest way to post process fiber-reinforced composites. However, quantitative analyses of the defects and process parameters are required to analyze the damage mechanisms and achieve high-quality cut surfaces. In this study, we quantitively investigated the defects on the sheared edge of woven glass epoxy laminates subjected to mechanical punching and explored the correlations between these defects and key process parameters, including punch-die clearance, weave alignment angle, and laminate thickness. The results demonstrate the necessity of considering glass fiber burr length and the dimensions of the cracked area simultaneously to evaluate the quality of the sheared surface. This study provides qualitative data on the interfacial damage mechanisms that occur during mechanical punching, which will help to tailor the process parameters of mechanical punching for fiber-reinforced polymers to obtain smooth cut surfaces. [ABSTRACT FROM AUTHOR]

Propensity score (PS) weighting methods are commonly used to adjust for confounding in observational treatment comparisons. However, in the setting of substantial covariate imbalance, PS values may approach 0 and 1, yielding extreme weights and inflated variance of the estimated treatment effect. Adaptations of the standard inverse probability of treatment weights (IPTW) can reduce the influence of extremes, including trimming methods that exclude people with PS values near 0 or 1. Alternatively, overlap weighting (OW) optimizes criteria related to bias and variance, and performs well compared to other PS weighting and matching methods. However, it has not been compared to propensity score stratification (PSS). PSS has some of the same potential advantages; being insensitive extreme values. We sought to compare these methods in the setting of substantial covariate imbalance to generate practical recommendations. Analytical derivations were used to establish connections between methods, and simulation studies were conducted to assess bias and variance of alternative methods. We find that OW is generally superior, particularly as covariate imbalance increases. In addition, a common method for implementing PSS based on Mantel–Haenszel weights (PSS-MH) is equivalent to a coarsened version of OW and can perform nearly as well. Finally, trimming methods increase bias across methods (IPTW, PSS and PSS-MH) unless the PS model is re-fit to the trimmed sample and weights or strata are re-derived. After trimming with re-fitting, all methods perform similarly to OW. These results may guide the selection, implementation and reporting of PS methods for observational studies with substantial covariate imbalance. [ABSTRACT FROM AUTHOR]

The use of propensity score methods has become ubiquitous in causal inference. At the heart of these methods is the positivity assumption. Violation of the positivity assumption leads to the presence of extreme propensity scoreweights when estimating average causal effects, which affects statistical inference. To circumvent this issue, trimming or truncating methods have been widely used. Unfortunately, these methods require that we pre-specify a threshold. There are anumber of alternative methods to deal with the lack of positivity when we estimate the average treatment effect (ATE). However, no other methods exist beyond trimming and truncation to deal with the same issue when the goal is to estimate theaverage treatment effect on the treated (ATT). In this article, we propose a propensity score weight-based alternative for the ATT, called overlap weighted average treatment effect on the treated. The appeal of our proposed method lies in its abilityto obtain similar or even better results than trimming and truncation while relaxing the constraint to choose an a priori threshold (or related measures). The performance of the proposed method is illustrated via a series of Monte Carlo simulationsand a data analysis on racial disparities in health care expenditures. [ABSTRACT FROM AUTHOR]

Shear cutting processes have a detrimental effect on fatigue of high strength metal components. The effect tends to increase with material grade, counteracting the task of reducing weight in chassis components using higher strength materials. Base material fatigue data are often available, but assessment of components with cut edges often require additional costly and time-consuming testing. This paper provides a methodology for estimation of fatigue life reduction by using residual stresses obtained from process simulations, and measured surface roughness in the cut edge. A stress relaxation criterion is applied to handle reduction of the initial local residual stresses. Two complex phase steels and one aluminum alloy are studied for validating the approach. Polished fatigue data is reduced to estimate S–N curves of trimmed and punched specimens at different load ratios. Good agreement between the model and test results are found for all cases. The needed data for the predictions are only a high cycle S–N relationship for polished material, uniaxial tensile properties, and the cut edge fracture surface residual stress and roughness without any parameter fitting, making it a convenient tool for estimating the reduction in fatigue life and for parameter studies. • A method to estimate HCF life of shear cut specimens. • Surface roughness, residual stresses and load ratio are considered. • No further calibration is needed if the S–N curve for the base material is known. • Cyclic stress relaxation is accounted for. • Validated with fatigue testing of polished and shear cut specimens. [ABSTRACT FROM AUTHOR]

The process of brain cutting followed by trimming is quite important to make adequate specimens for sufficient neuropathological observations. The protocol described herein is recommended as an optimized implementation for suitable preparation, which inevitably leads to an accurate neuropathological diagnosis. To obtain neuropathological cues, macroscopic observation of the brain before cutting presents an important opportunity. Gross examination provides a clue to the neuropathological diagnosis and shows clinicopathological correlations. Brain cutting should be preceded by a careful review of the clinical notes and consideration of the possible pathological diagnosis. Therefore, the medical staff associated with the patient should attend the procedure to provide clinical information. The process involves removing the brainstem and cerebellum from the cerebrum, sectioning the cerebrum, removing the cerebellum from the brainstem, and sectioning the cerebellum, brainstem and spinal cord followed by trimming. Trimming should be performed in accordance with the internationally accepted guidelines for the pathological diagnosis of different types of neurodegenerative diseases. In each stage acquiring clear photographs is significant, the observations must be concisely recorded, and which side of the specimen is to be sliced and stained has to be indicated. Additionally, it is necessary to photograph all trimmed tissues to assist with orientation of the brain in later assessments. The three‐dimensional structure and individual differences have to be considered. These skills are essential, and knowledge of neuropathology, neurology and neuroanatomy is required for appropriately cutting and trimming of the brain. [ABSTRACT FROM AUTHOR]

Given a large data graph, trimming techniques can reduce the search space by removing vertices without outgoing edges. One application is to speed up the parallel decomposition of graphs into strongly connected components (SCC decomposition), which is a fundamental step for analyzing graphs. We observe that graph trimming is essentially a kind of arc-consistency problem, and AC-3, AC-4, and AC-6 are the most relevant arc-consistency algorithms for application to graph trimming. The existing parallel graph trimming methods require worst-case O (n m) time and worst-case O (n) space for graphs with n vertices and m edges. We call these parallel AC-3-based as they are much like the AC-3 algorithm. In this work, we propose AC-4-based and AC-6-based trimming methods. That is, AC-4-based trimming has an improved worst-case time of O (n + m) but requires worst-case space of O (n + m) ; compared with AC-4-based trimming, AC-6-based has the same worst-case time of O (n + m) but an improved worst-case space of O (n) . We parallelize the AC-4-based and AC-6-based algorithms to be suitable for shared-memory multi-core machines. The algorithms are designed to minimize synchronization overhead. For these algorithms, we also prove the correctness and analyze time complexities with the work-depth model. In experiments, we compare these three parallel trimming algorithms over a variety of real and synthetic graphs on a multi-core machine, where each core corresponds to a worker. Specifically, for the maximum number of traversed edges per worker by using 16 workers, AC-3-based traverses up to 58.3 and 36.5 times more edges than AC-6-based trimming and AC-4-based trimming, respectively. That is, AC-6-based trimming traverses much fewer edges than other methods, which is meaningful especially for implicit graphs. In particular, for the practical running time, AC-6-based trimming achieves high speedups over graphs with a large portion of trimmable vertices. [ABSTRACT FROM AUTHOR]

• We propose a data clustering algorithm that simultaneously identifies outliers and clusters points. • The algorithm can be applied to either single- or multi-membership data. • The algorithm performs competitively on single membership data with outliers and multi-membership data without outliers. • The algorithm outperforms other methods on multi-membership data with outliers. Clustering is a fundamental tool in unsupervised learning, used to group objects by distinguishing between similar and dissimilar features of a given data set. One of the most common clustering algorithms is k -means. Unfortunately, when dealing with real-world data many traditional clustering algorithms are compromised by lack of clear separation between groups, noisy observations, and/or outlying data points. Thus, robust statistical algorithms are required for successful data analytics. Current methods that robustify k -means clustering are specialized for either single or multi-membership data, but do not perform competitively in both cases. We propose an extension of the k -means algorithm, which we call Robust Trimmed k -means (RTKM) that simultaneously identifies outliers and clusters points and can be applied to either single- or multi-membership data. We test RTKM on various real-world datasets and show that RTKM performs competitively with other methods on single membership data with outliers and multi-membership data without outliers. We also show that RTKM leverages its relative advantages to outperform other methods on multi-membership data containing outliers. [ABSTRACT FROM AUTHOR]

Product innovation is often a process for improving existing products. Low-end disruptive innovation (LDI) enables a product to meet the most price-sensitive customers in the low-end market. The existing LDI methods are mainly based on unnecessary characteristics of disruptive innovations. Thus, they cannot easily identify and respond to the LDI design needs. This study proposes a hybrid method for the product LDI in two levels of the product design based on the summarized definition and essential characteristics of LDI. Feasible areas of the product LDI are determined using a hybrid relational function model to identify the maturity of dominant technologies. The technologies are identified through the technical search and evaluation of the feasible area for innovation to form an initial LDI scheme. Then, the product function is optimized using the trimming concept of theory of inventive problem solving based on the characteristics of LDI. The final LDI scheme is formed and evaluated based on the essential characteristics of the product LDI. The feasibility of the proposed method is verified in the design of a new dropping pill machine. [ABSTRACT FROM AUTHOR]

The nuclear ribosomal RNA (rRNA) internal transcribed spacer (ITS) regions are commonly used to identify fungi and other eukaryotic taxa in amplicon sequencing. The highly conserved rRNA regions flanking the ITS are often trimmed before being used for taxonomic assignment. The Python software package ITSxpress rapidly trims single-end or paired-end sequences in FASTQ format for use in amplicon sequence variant clustering methods like DADA2. This new major release of ITSxpress improves the paired-end merging method, simplifies installation of the QIIME 2 ITSxpress plugin, removes major dependencies, adds use cases, and is compatible with newer compression formats. This article discusses the modifications to ITSxpress that improve the output and user experience, leading to a major version increase.IMPORTANCEITSxpress is a sequence trimming method applied to internal transcribed spacer (ITS) amplicon sequences before calling amplicon sequence variants (ASVs). The ITS region is used to understand the composition of eukaryotic microbial communities. ITS sequences provide good taxonomic resolution due to their hypervariability, but are flanked by conserved regions that allow their primers to be more universal. Amplicons generated with such primers contain regions with different evolutionary rates, and trimming these conserved regions results in better taxonomic classification and a more valid set of ASVs. This package can be used for most amplicon sequencing methods including for newer long-read sequencing formats, such as PacBio. ITSxpress can be installed from Bioconda, used as a Docker image, or installed from source code. The package works well with high-performance computing clusters or laptops due to its low-resource requirements.

While inverse probability of treatment weighting (IPTW) is a commonly used approach for treatment comparisons in observational data, the resulting estimates may be subject to bias and excessively large variance under lack of overlap. By smoothly down-weighting units with extreme propensity scores, i.e., those that are close (or equal) to zero or one, overlap weighting (OW) can help mitigate the bias and variance issues associated with IPTW. Although theoretical and simulation results have supported the use of OW with continuous and binary outcomes, its performance with survival outcomes remains to be further investigated, especially when the target estimand is defined based on the restricted mean survival time (RMST). We combine propensity score weighting and inverse probability of censoring weighting to estimate the restricted mean counterfactual survival times, and provide computationally-efficient variance estimators when the propensity scores are estimated by logistic regression and the censoring process is estimated by Cox regression. We conduct simulations to compare the performance of weighting methods in terms of bias, variance, and 95% interval coverage, under various degrees of overlap. Under moderate and weak overlap, we demonstrate the advantage of OW over IPTW, trimming and truncation, with respect to bias, variance, and coverage when estimating RMST., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

It is important to understand the effects of hoof trimming on hoof and limb conformation to maximize its benefits on the health of the appendicular skeleton of horses, thus promoting improvements in athletic performance and sporting longevity with regard to athletic horses. There is little information on possible changes in the angulation of the thoracic limb joints after hoof trimming and correlations between the angulation of the thoracic limb joints with hoof measurements. To that purpose, nineteen Mangalarga mares received routine hoof trimming. Visual recordings (photographs) were taken before and after the procedure. Differences (p < 0.05) were found in hoof length, toe angle, heel angle, medial heel height, and metacarpophalangeal angle. Before trimming, correlations were found between frog length and scapulohumeral angle (SH) (r = −0.457; p = 0.049), and between toe length and shoulder-ground angle (SG) (r = −0.553; p = 0.049). A correlation was also seen between the distance from the frog to the lateral wall and the SH angle (r = 0.690; p = 0.001). After trimming, there was a correlation between humeroradial (HR) and SH joint angles (r = 0.669; p = 0.002), and the SG and SH angles (r = 0.488; p = 0.034). This study showed an immediate effect of trimming on the toe angle and heel angle and on the metacarpophalangeal joint angle, in addition to correlations between the hoof and proximal joint angles, following trimming, thus evidencing the relevance of trimming not only in hoof morphology, but also in the conformation of the appendicular skeleton of horses.

The yeast Sup35 protein misfolds into the infectious [PSI+] prion, which is then propagated by the severing activity of the molecular chaperone, Hsp104. Unlike other yeast prions, this prion is unique in that it is efficiently cured by the overexpression as well as the inactivation of Hsp104. However, it is controversial whether curing by overexpression is due to the dissolution of the prion seeds by the trimming activity of Hsp104 or the asymmetric segregation of the prion seeds between mother and daughter cells which requires cell division. To answer this question, we conducted experiments and found no difference in the extent of curing between mother and daughter cells when half of the cells were cured by Hsp104 overexpression in one generation. Furthermore, curing was not affected by the lack of Sir2 expression, which was reported to be required for asymmetric segregation of the [PSI+] seeds. More importantly, when either hydroxyurea or ethanol were used to inhibit cell division, the extent of curing by Hsp104 overexpression was not significantly reduced. Therefore, the curing of [PSI+] by Hsp104 overexpression is not due to asymmetric segregation of the prion seeds, but rather their dissolution by Hsp104.

Carbon fiber–reinforced plastic (CFRP) is becoming more popular in the aerospace industry due to its high strength-to-weight ratio and low weight. Machining CFRP to achieve the required surface quality, on the other hand, remains a challenge. High temperature in the cutting zone area affects the tool life and surface quality of the machined part. A thermally affected matrix makes an inaccurate interpretation of the surface quality. Then, the roughness parameters cannot be an appropriate indicator for surface evaluation of the CFRP. In the aerospace industry, however, ensuring the acceptable surface quality of a part is essential. Minimizing and controlling tool wear are necessary to avoid degrading the finished surface and losing the dimensional accuracy of the final part. Early detection of tool wear and appropriate surface quality in finishing operations can be achieved using online tool condition monitoring. Cutting forces and electric current signals related to the spindle during machining are very responsive to cutting conditions and can accurately represent tool condition changes. Fractal analysis, as a new approach in the online tool condition monitoring, can assess the tool condition during machining. This research investigates the fractal analysis of the spindle electric current signal and the total cutting force signal while trimming CFRP using a CVD end mill through three different tool life conditions, e.g. new tool, moderately worn tool, and severely worn tool. The empirical fractal index is also introduced to assess the tool condition and ensure the acceptable surface qualities in the finishing operations. The effectiveness of fractal analysis as a decision-making method in the tool condition monitoring was successfully proven in this study. [ABSTRACT FROM AUTHOR]

This article presents an energy-efficient dual- $RC$ frequency reference intended for wireless sensor nodes. It consists of a digital frequency-locked loop (FLL) in which the frequency of a digitally controlled oscillator (DCO) is locked to a temperature-independent phase shift derived from two different $RC$ poly-phase filters (PPFs). Phase shifts with complementary temperature coefficients (TCs) are generated by using PPFs made from different resistor types (p-poly and silicided p-poly). The phase shift of each filter is determined by a zero-crossing (ZC) detector and then digitized by a digital phase-domain $\Delta \Sigma $ modulator ($\Phi $ - $\Delta \Sigma \text{M}$). The results are then combined in the digital domain via fixed polynomials to produce a temperature-independent phase shift. This highly digital architecture enables the use of a sub-1-V supply voltage and enhances energy and area efficiency. The 28-MHz frequency reference occupies 0.06 mm2 in a 65-nm CMOS process. It achieves a period jitter of 7 ps ($1\sigma $) and draws $142~\mu \text{W}$ from a 0.9-V supply, which corresponds to an energy consumption of 5 pJ/cycle. Furthermore, it achieves ±200 ppm inaccuracy from $- 40\,\,^\circ \text{C}$ to $85~^\circ \text{C}$ after a two-point trim. [ABSTRACT FROM AUTHOR]

We introduce a new command, robustate, that executes the inverseprobability weighting estimation and inference for the average treatment effect with robustness against limited overlap (that is, weak satisfaction of the common support condition). This command produces estimates, standard errors, p -values, and confidence intervals for the average treatment effect. The utility of the command is demonstrated with both simulated and real data of right heart catheterization. These illustrations show that the proposed estimator implemented by the robustate command indeed exhibits more robustness against limited overlap than the traditional inverse-probability weighting estimator. The main method of the command is proposed in Sasaki and Ura (2022, Econometric Theory 38: 66–112). [ABSTRACT FROM AUTHOR]

The inverse probability of treatment weighting (IPTW) approach is popular for evaluating causal effects in observational studies, but extreme propensity scores could bias the estimator and induce excessive variance. Recently, the overlap weighting approach has been proposed to alleviate this problem, which smoothly down-weights the subjects with extreme propensity scores. Although advantages of overlap weighting have been extensively demonstrated in literature with continuous and binary outcomes, research on its performance with time-to-event or survival outcomes is limited. In this article, we propose estimators that combine propensity score weighting and inverse probability of censoring weighting to estimate the counterfactual survival functions. These estimators are applicable to the general class of balancing weights, which includes IPTW, trimming, and overlap weighting as special cases. We conduct simulations to examine the empirical performance of these estimators with different propensity score weighting schemes in terms of bias, variance, and 95% confidence interval coverage, under various degrees of covariate overlap between treatment groups and censoring rates. We demonstrate that overlap weighting consistently outperforms IPTW and associated trimming methods in bias, variance, and coverage for time-to-event outcomes, and the advantages increase as the degree of covariate overlap between the treatment groups decreases. [ABSTRACT FROM AUTHOR]

Reverse bandgaps generate PVT-independent reference voltages by means of the sums of pairs of currents over individual matched resistors: one (CTAT) current is proportional to VEB; the other one (PTAT) is proportional to VT (Thermal voltage). Design guidelines and techniques for a CMOS low-power reverse bandgap reference are presented and discussed in this paper. The paper explains firstly how to design the components of the bandgap branches to minimize circuit current. Secondly, error amplifier topologies are studied in order to reveal the best one, depending on the operation conditions. Finally, a low-voltage bandgap in 65 nm CMOS with 5 ppm/°C, with a DC PSR of −91 dB, with power consumption of 5.2 μW and with an area of 0.0352 mm2 developed with these techniques is presented.

The paper presents a 0.5 V, ultra-low power current, and voltage reference circuit in a single block, giving reference values of 90.7 pA and 288 mV. The proposed block uses proper addition of CTAT and PTAT curves, resulting in an excellent temperature coefficient of 15.2 ppm/°C and 36.8 ppm/°C for compensated current and voltage values, respectively, at a nominal supply of 0.5 V for a wide temperature range of −55 °C to 100 °C. Usage of gate leakage transistors in place of resistors helps in reducing the power and area of the circuit to 0.087 mm2. The circuit is implemented in 90 nm technology and operates effectively across a wide voltage range of 0.5 V–2.6 V with a supply sensitivity of 0.028 %/V and 0.154 %/V for current and voltage reference, respectively. The entire circuit takes a power of 275.26 pW at nominal conditions. [ABSTRACT FROM AUTHOR]

Realizing packaged state-of-the-art performance of monolithic microwave integrated circuits (MMICs) operating at millimeter wavelengths presents significant challenges in terms of electrical interface circuitry and physical construction. For instance, even with the aid of modern electromagnetic simulation tools, modeling the interaction between the MMIC and its package embedding circuit can lack the necessary precision to achieve optimum device performance. Physical implementation also introduces inaccuracies and requires iterative interface component substitution that can produce variable results, is invasive and risks damaging the MMIC. This paper describes a novel method for in situ optimization of packaged millimeter-wave devices using a pulsed ultraviolet laser to remove pre-selected areas of interface circuit metallization. The method was successfully demonstrated through the optimization of a 183 GHz low noise amplifier destined for use on the MetOp-SG meteorological satellite series. An improvement in amplifier output return loss from an average of 12.9 dB to 22.7 dB was achieved across an operational frequency range of 175–191 GHz and the improved circuit reproduced. We believe that our in situ tuning technique can be applied more widely to planar millimeter-wave interface circuits that are critical in achieving optimum device performance. [ABSTRACT FROM AUTHOR]

A method of machining titanium-aluminum intermetallic compounds TiAl 45XD was proposed by combining WEDM and WECM. During the WECM, the recast layers were removed by first "pass", and the possible intergranular corrosions were eliminated by second "pass". The electrochemical characteristics of the cast TiAl 45XD mechanical polished surfaces and the WEDM surfaces were studied respectively. It is found that both of the surfaces have passivation in water-based solutions (WBS), and there are almost no obvious passivation in glycol-based solutions (GBS). Compared with the WBS, both of the surfaces are more susceptible to corrosion in the GBS, and the WEDM surfaces are more corroded than that of the polished surfaces. Then the effects of feed speed and cutting depth on surface integrity were analyzed, the testing results show that when the feed speed of first "pass" is as 25 µm/s and the cutting depth is as 20 µm, the feed speed of second "pass" is as 60 µm/s and the cutting depth is as 0, the recast layers are removed, the intergranular corrosions are eliminated, the surface roughness value is reduced to 1.6 µm, and the average feed speed is as 17.65 µm/s, which proves that the use of WEDM for rough forming, WECM with GBS for trimming is a feasible method for machining straight-grained titanium-aluminum intermetallic compound components with high surface integrity. [ABSTRACT FROM AUTHOR]

Abstract Converting customer needs into specific forms and providing consumers with services are crucial in product design. Currently, conversion is no longer difficult due to the development of modern technology, and various measures can be applied for product realization, thus increasing the complexity of analysis and evaluation in the design process. The focus of the design process has thus shifted from problem solving to minimizing the total amount of information content. This paper presents a New Hybrid Axiomatic Design (AD) Methodology based on iteratively matching and merging design parameters that meet the independence axiom and attribute constraints by applying trimming technology, the ideal final results, and technology evolution theory. The proposed method minimizes the total amount of information content and improves the design quality. Finally, a case study of a rehabilitation robot design for hemiplegic patients is presented. The results indicate that the iterative matching and merging of related attributes can minimize the total amount of information content, reduce the cost, and improve design efficiency. Additionally, evolutionary technology prediction can ensure product novelty and improve market competitiveness. The methodology provides an excellent way to design a new (or improved) product.

Since entering the era of the experience economy, consumers’ attention gradually turns toward gaining a pleasant service process experience. This study addresses the service process problem, aiming to discover the root cause of the service process problem and solve it by analyzing the service touchpoints flow delivery process. A method for solving problems in the service process based on flow trimming is proposed. The trimming method and the stochastic dominance rule are applied to the field of service design, which provides new concepts for service process problem solving. The flow is taken as the entry point of the proposed method. First, a flow model of problematic service touchpoints is constructed based on the service blueprint method to visualize the flow delivery process. Then, service process trimming rules are proposed and used as guidance to trim flow disadvantages, and resource analysis is employed to obtain specific programs. Finally, the stochastic dominance rule is used to rank the programs and select the optimal program. Problem solving in the medical treatment service process was taken as an example to trim the fundamental flow disadvantages of problematic service touchpoints. A series of programs were obtained and the optimal program was selected for presentation based on the stochastic dominance rule, which verified the feasibility of the proposed method.