Miracle-dz/UniFAR-FTUs huggingface dataset:
Spell out before you merge

In this paper, I will investigate the relation between the syntactic derivation of sentences and the Spell-Out to PF (Phonetic Form). A problem in the interface between syntax and PF is how computation merges words or constituents and Spells Out them in a bottom-up and cyclic fashion, while PF-representation is linear from left to right (cf. Chomsky 1995, Phillips 2003). The aim of this paper is to show that the problem can be solved if words are Spelled Out before they are Merged. I will argue that lexical items and silent demibeats (cf. Selkirk 1984) are introduced to the working space from top to bottom, and that an extra silent demibeat triggers Merge, which proceeds from bottom to top. This model gives us a new view of the syntax-phonology interface and the architecture of grammar.
Diagnostic value of liver contrast-enhanced ultrasound in early hepatocellular carcinoma: a systematic review and meta-analysis

Background Hepatocellular carcinoma is the sixth most common cancer in the world, and its incidence rate will continue to increase. Contrast-enhanced ultrasound (CEUS) is feasible as a rapid examination for early hepatocellular carcinoma diagnosis. However, considering the possible causes of false positives caused by ultrasound, its diagnostic value is still controversial. Therefore, the study conducted a meta-analysis to evaluate the application value of CEUS in the early diagnosis of hepatocellular carcinoma. Methods The PubMed, Cochrane Library, Embase, Ovid Technologies (OVID), China National Knowledge Infrastructure (CNKI), Chongqing VIP Information (VIP), and Wanfang databases were searched to retrieve articles on the use of CEUS for the early diagnosis of hepatocellular carcinoma. The literature quality assessment was performed using the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) quality assessment tool. The meta-analysis was performed using STATA 17.0 to fit the bivariate mixed effects model, calculated sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and corresponding 95% CI, summary receiver operating characteristic curves (SROC), area under the curve (AUC), and 95% confidence interval (CI). The publication bias of the included literature was evaluated using the DEEK funnel plot. Results Ultimately, 9 articles, comprising 1,434 patients, were included in the meta-analysis. The heterogeneity test found that I2>50%, using a random effects model. The results of the meta-analysis showed that the CEUS had a combined sensitivity of 0.92 (95% CI: 0.86–0.95), a combined specificity of 0.93 (95% CI: 0.56–0.99), a combined PLR of 13.47 (95% CI: 1.51–120.46), a combined NLR of 0.09 (95% CI: 0.05–0.14), a combined DOR of 154.16 (95% CI: 15.93–1,492.02), a diagnostic score of 5.04 (95% CI: 2.77–7.31), and a combined AUC of 0.95 (95% CI: 0.93–0.97). The correlation coefficient of the threshold-effect analysis was 0.13 (P>0.05). The results of the regression analysis showed that the country of publication (P=0.14) and the size of the lesion nodules (P=0.46) were not sources of heterogeneity. Conclusions Liver CEUS has an advantage in the early diagnosis of hepatocellular carcinoma, with high sensitivity and specificity, and has clinical application value.
An evaluation of conventional and deep learning‐based image‐matching methods on diverse datasets

Image matching plays an important role in photogrammetry, computer vision and remote sensing. Modern deep learning‐based methods have been proposed for image matching; however, whether they will surpass and take the place of the conventional handcrafted methods in the remote sensing field still remains unclear. A comprehensive evaluation on stereo remote sensing images is also lacking. This paper comprehensively evaluates the performance of conventional and deep learning‐based image‐matching methods by dividing the matching process into feature point extraction, description and similarity measure on various datasets, including images captured from close‐range indoor and outdoor scenarios, unmanned aerial vehicles (UAVs) and satellite platforms. Different combinations of the three steps are evaluated. The experimental results reveal that, first, the performance of the different combinations varies between individual datasets, and it is difficult to determine the best combination. Second, by using more comprehensive indicators on all of the datasets, that is, the average rank and absolute rank, the combination of scale‐invariant feature transform (SIFT), ContextDesc and the nearest neighbour distance ratio (NNDR), and also the original SIFT, achieve the best results, and are recommended for use in remote sensing. Third, the deep learning‐based Sub‐SuperPoint extractor obtains a good performance, and is second only to SIFT. The learning based ContextDesc descriptor is as effective as the SIFT descriptor, and the learning based SuperGlue matcher is not as stable as NNDR, but leads to a few top‐performing combinations. Finally, the handcrafted methods are generally faster than the deep learning‐based methods, but the efficiency of the latter is acceptable. We conclude that although a full deep learning‐based method/combination has not yet beaten the conventional methods, there is still much room for improvement with the deep learning‐based methods because large‐scale aerial and satellite training datasets remain to be constructed, and specific methods for remote sensing images remain to be developed. The performance of the different combinations of feature extractor, descriptor and similarity measure varies between individual datasets. The combination of SIFT, ContextDesc and NNDR, and also the original SIFT, achieve the best results when using more comprehensive indicators on all the datasets. For extractor, the learning based Sub‐SuperPoint is second only to SIFT; for descriptor, learning‐based ContextDesc is as effective as the SIFT descriptor; and for matcher, learning‐based SuperGlue is not as stable as NNDR.
(A)woke Workplaces

With heightened expectations for a reckoning in response to the broad support for the Black Lives Matter movement after the senseless murder of George Floyd in 2020, employers explored many options to improve racial understanding through discussions with workers. In rejecting any notions of the existence of structural or systemic discrimination, let alone the need to address the consequences of such discrimination, certain groups have begun to oppose BLM by seeking to diminish any social justice actions. One of those key resistance efforts includes labelling in pejorative terms any employers that pursue anti-racism objectives via social justice statements or internal initiatives as being “woke” workplaces. These groups have also criticized employers who adopt diversity, equity, and inclusion training to help workers address racial differences by arguing these sessions apply divisive Critical Race Theory principles that discriminate against and seek to stigmatize white participants. By using CRT and woke labels as weapons, critics leave employers in the unenviable position of determining how to implement antiracism trainings in an environment of BLM reforms and race discrimination concerns. These all-encompassing anti-anti-racism narratives now force employers to show how their DEI trainings and related initiatives do not discriminate against white employees. This Article offers unique insight for employers who pursue DEI measures to achieve racial progress and asserts they may circumvent antianti-racism narratives by continuing to rely on the litigation reforms and stillpresent empirical results that led to the growth of DEI training practices in the 1990s. Many employers had adopted DEI initiatives as good corporate citizens valuing diversity in human resources as a growth of affirmative action in the 1970s. With legal concerns in the 1990s about huge jury verdicts in discrimination lawsuits and empirical indicators of systemic discrimination, employers embraced more comprehensive racial improvement and training steps via written consent decrees and judicially approved settlements. This Article concludes that awoke employers should adopt broader DEI goals and limit training on entry-level racial awareness given empirical data suggesting this particular approach tends to spark backlash without any resulting diversity improvements. Instead, awoke employers understand that most constituents want them to act and lead responsibly regarding comprehensive DEI measures by going beyond legal protections. Training can focus on managers who may subject a company to employment discrimination liability. Awoke training integrates key follow-ups and correlates to measurable DEI results. Focusing on DEI training alone ignores the more important structural change work.
Fuzzy predictive PID controller based on output-errorprediction and its application

As most industrial processes are nonlinear, the proper T-S fuzzy model was obtained by online recursive fuzzy identification method and then applied to describe the complex nonlinear systems. Fuzzy cluster algorithm was used to determine the center input area of the fuzzy rules, and the predefined degree of over lapping between rules was used to determine the input-zone radius for the fuzzy rules. After the rules' consequent parameters were obtained by the recursive least squares(RLS) algorithm, the fuzzy local linearization model was used as a CARIMA-like model. Finally, by combining the principles of the generalized predictive control(GPC) and adaptive FIR filter, a novel predictive PID controller algorithm was developed. The method solves the problem of restriction on the system's order. Simulation results show the effectiveness and practicability of the proposed method.
Alterations in Cortical Morphology after Neonatal Stroke: Compensation in the Contralesional Hemisphere?

Although neonatal arterial ischemic stroke is now well‐studied, its complex consequences on long‐term cortical brain development has not yet been solved. In order to understand the brain development after focal early brain lesion, brain morphometry needs to be evaluated using structural parameters. In this work, our aim was to study and analyze the changes in morphometry of ipsi‐ and contralesional hemispheres in seven‐year‐old children following neonatal stroke. Therefore, we used surface‐based morphometry in order to examine the cortical thickness, surface area, cortical volume, and local gyrification index in two groups of children that suffered from neonatal stroke in the left (n = 19) and right hemispheres (n = 15) and a group of healthy controls (n = 30). Reduced cortical thickness, surface area, and cortical volumes were observed in the ipsilesional hemispheres for both groups in comparison with controls. For the group with left‐sided lesions, higher gyrification of the contralesional hemisphere was observed primarily in the occipital region along with higher surface area and cortical volume. As for the group with right‐sided lesions, higher gyrification was detected in two separate clusters also in the occipital lobe of the contralesional hemisphere, without a significant change in cortical thickness, surface area, or cortical volume. This is the first time that alterations of structural parameters are detected in the “healthy” hemisphere after unilateral neonatal stroke indicative of a compensatory phenomenon. Moreover, findings presented in this work suggest that lesion lateralization might have an influence on brain development and maturation.
Optimized LightGBM model for security and privacy issues in cyber‐physical systems

Integrating physical, computational, and networking resources are the goal of cyber‐physical systems, also known as smart‐embedded systems. By investing in a solid foundation, we can improve the usefulness and timeliness of the services we rely on in every facet of our lives and ultimately live more elegantly. Regarding modern technology, data security is a significant factor that must be considered. The complexity of cyber‐physical systems' interacting components and middleware presents serious hurdles when it comes to protecting them from cyber‐attacks without negatively impacting their performance. This article proposes a unique, efficient encryption technique for anticipating cyber assaults in cyber‐physical systems, which addresses these concerns. The suggested method uses Bayesian optimization techniques to fine‐tune the LightGBM algorithm's hyper‐parameters. This proposed algorithm has been implemented on the intrusion detection dataset (UNR‐IDD) from the University of Nevada. Reno has been used to test the suggested approach. The proposed system achieved 99.17% accuracy, 0.9918 precision, and 0.9922 recall values. Our empirical evaluation demonstrates that the algorithm successfully increases accuracy and AUC value, making the cyber‐physical system more secure. In turn, the suggested methodology may offer robust assurance for user data safety.
Organic Milk Production and Dairy Farming Constraints and Prospects under the Laws of the European Union

Simple Summary Consumers are increasingly choosing organic farming products. Such behavior is mainly dictated by the conviction that organic farms do not use pesticides or antibiotics, and that animals are provided with the best living conditions. This review discusses issues related to the comparison between organic and conventional dairy cattle housing systems in terms of welfare assessment, breed selection, and product quality. It has been shown that cows kept in organic systems usually have better welfare compared to conventional breeding. However, it is worth bearing in mind that conventional farms can also provide better animal welfare through, for example, the use of pasture grazing, which is voluntary in conventional farming, but mandatory in organic farming. The pasture feeding of cows has been shown to affect the taste of milk, but regarding consumer preference, this is a personal preference. Reducing the use of antibiotics in ecology has a positive impact on the technological quality of milk; it is also an additional incentive to use preventive measures to reduce the incidence of mastitis. In the future, it is expected that the proportion of land that is unsuitable for the production of crops for human consumption will increasingly be used for cow grazing. Abstract In recent years, there has been rapid development in organic farming. When choosing organic livestock products, consumers are guided by the conviction that animals are provided with the highest welfare standards and access to pasture. The purpose of this article was to trace the principles of organic farming prevailing in the EU with regard to milk production and cattle breeding. The principles of organic production are universal and their application is not limited to certified farms. Organic certification is intended to assure the consumer of the quality and method of production. Due to additional requirements imposed by law, organic cows are usually kept in better welfare conditions compared to conventional cattle, but this is not the rule. The altered taste and texture of organic milk and its products compared to conventional products mainly depends on the presence of pasture greens in the cows’ diet. Therefore, milk from conventionally kept, pasture-grazed cows may have similar characteristics and composition. Organic farms tend to have lower milk yields compared to conventional farms due to the lower consumption of concentrate feed. In the future, it is expected that the proportion of land that is unsuitable for the production of crops for human consumption will increasingly be used for cow grazing.
The European Southern Observatory planetary search program: Preliminary results

We report on the progress of a program to search for extra-solar planets using high precision radial velocity (RV) measurements taken at the European Southern Observatory. Instrumental errors in the radial velocity measure are minimized by placing a temperature stabilized molecular iodine absorption cell in front of the entrance slit to the spectrograph. This imposes an iodine absorption spectrum on top of the stellar spectrum. All stellar radial velocity shifts are measured with respect to the iodine absorption spectrum. The current program consists of a sample of 26 F, G, and K dwarfs and 1 dMe star. Radial velocity measurements taken since November 1992 indicate that a typical long-term radial velocity precision for this program is about 18 m s−1. One of our program stars, τ Cet, shows constant radial velocity variability with a scatter of 6 m s−1. Representative radial velocity measurements are given for three stars showing no significant radial velocity variations, three stars showing variations indicative of low mass companions, and for the triple system α Cen. The radial velocity measurements of α Cen A and B are consistent with the astrometric orbital solution, although the data points have a slightly steeper slope than the calculated orbit. Continued radial velocity monitoring of this star should eventually result in a better orbital solution.
Narrow-gap single-pole heads

This work addresses the recording physics of narrow-gap single-pole heads (SPH) in perpendicular recording. It is found that narrow-gap SPHs have reduced sensitivity with respect to nonzero skew angles. It is shown that while the efficiency of a narrow-gap SPH is generally reduced, even for the case of a gapless SPH, the efficiency differs from the efficiency of a 1-/spl mu/m-thick gap SPH only by a factor of two. The design parameter space for a narrow-gap SPH is investigated.
THE EFFECT OF DIET SHOF (SIXTEEN HOUR OF FASTING) ON TRIGLYCERIDE LEVELS IN OVERWEIGHT ADOLESCENTS

Body weight exceeding normal body weight (Overweight) is a cause of increased triglyceride levels. High triglyceride levels (hypertriglyceridemia) are a risk for coronary heart disease and diabetes mellitus. Efforts that can be made to reduce hypertriglyceridemia is to reduce the number of meals with the shof diet (sixteen hours of fasting). During fasting triglycerides will be mobilized to produce energy or synthesized into glucose. The aim of this study was to determine the effect of the shof diet on reducing triglyceride levels in overweight adolescents. The research design used the Pre-Experiment One Group Pretest-Postest Design with a population of all female students of the Faculty of Health Sciences who experienced overwight as much as 25. The number of samples was 20 with a sampling technique using purposive sampling. The research instrument uses an observation sheet. Data were analyzed using the Wilcoxon test with a P value ≤ α (α = 0.05). The results showed that the value of P = 0.646, which means that there was no effect of the shof diet on reducing triglyceride levels. However, in terms of quantity, there was a decrease in triglyceride levels in most of the respondents. The shof diet can reduce triglyceride levels by controlling food consumption during the fasting window.
Living on Video: Insights on the User Perspective of Video-Based AAL Technology

: Research on video-based Ambient Assisted Living (AAL) technologies is increasing due to their potential of providing abundant sensory information about a person in need of support. Acceptance of these visual sensors is limited among potential users as perceptions of barriers persist, most importantly privacy concerns. The current study aimed to investigate potential users’ behavioural intention to use video-based AAL and their evaluations of relevant benefits and barriers during activities of daily living in their own homes. Special focus was on exploring the influences of individual differences (demographics and psychometrics) on evaluation patterns. In total, evaluations of 122 participants (age range: 17-81 years) were assessed through an online survey. The results are in line with previous findings on perceived benefits and barriers and their relevance to the acceptance of AAL technology. Beyond that, the results revealed significant relationships and impacts of individual differences, i.e., privacy perception, self-consciousness, and body consciousness, on the perceived barriers and indirectly also on the acceptance of video-based AAL technology. Further, three clusters of potential users were identified, differing significantly in their evaluation of video-based AAL technology as well as in their individual characteristics, i.e., privacy perception and self-consciousness. The findings of this study are useful to derive recommendations for user-tailored development and communication of video-based AAL technology.
The data double standard

Conservation planning requires extensive amounts of data, yet data collection is expensive, and there is often a trade‐off between the quantity and quality of data that can be collected. Researchers are increasingly turning to community science programs to meet their biodiversity data needs, yet the reliability of such data sources is still a common source of debate. Here, we argue that professionally collected data are subject to many of the limitations and biases present in community science datasets. We explore four common criticisms of community science data, and comparable issues that exist in data collected by experts: spatial biases, observer variability, taxonomic biases and the misapplication of data. We then outline solutions to these problems that have been developed to make better use of community science data, but can (and should) be equally applied to both kinds of data. We highlight four main solutions based on research using community science data that can be applied across all biodiversity data collection and research. Statistical techniques that have been developed for processing community science data can equally help account for spatial biases and observer variation in professional datasets. Benchmarking or vetting one dataset against another can strengthen evidence and uncover unknown sources of biases. Professional and community science datasets can be used together to fill knowledge gaps that are unique to each. Careful study design that accounts for the collection of relevant and important covariate data can help statistically account for sources of bias. Currently, a double standard exists in how researchers view data collected by professionals versus those collected by community scientists. Our aim is to ensure that valuable community science data are given the prominent place they deserve, and that data collected by experts are appropriately vetted and biases accounted for using all the tools at our disposal.
Energy education policy analysis of China: A perspective of multiple streams theory

Since the 1970s, energy education (EE) has become one of the effective ways to solve the energy crisis in developed countries. China’s increasingly severe energy issue requires China to strengthen energy conservation while establishing a conservation-oriented society and to draw on international experience in solving energy questions by vigorously developing EE. The development of EE in China commences late. Although some achievements have been made, there is a lack of legislative protection and platform support in further promoting EE. This paper analyzes China’s EE policy using the multiple streams theory, examines the reality of problematic policy and political streams of China’s EE policy, discusses the issue of addressing the three main streams in China’s EE development, summarizes the necessary conditions fbr opening the EE policy window, and puts forward suggestions fbr erecting China’s EE system.