Complex Set Research Articles

A collaborative navigation algorithm for UAV Ad Hoc network based on improved sequence quadratic programming and unscented Kalman filtering in GNSS denied area

In global navigation satellite system (GNSS) denied area, collaborative positioning precision is important for unmanned aerial vehicle (UAV) to perform collaborative tasks in Ad Hoc network. Continuous optimization of algorithm complexity and parameter setting has long been a focal point in the field of collaborative positioning research. An algorithm of UAVs collaborative positioning based on improved sequential quadratic programming (SQP) and unscented kalman filter (UKF) is proposed. By optimizing the parameter constraints of SQP, parameters are controlled within certain conditions. The convergence speed of SQP is improved, and more accurate filtering parameters are obtained. The improved SQP and UKF are combined to optimize the location data of UAVs, which improves the precision of collaborative positioning. The simulation results show that the positioning precision can be greatly enhanced by approximately 25% when using the proposed algorithm, as compared to the traditional algorithm. The influence of the collaborative UAV number also is simulated. The positioning performance improve slowly when more than five UAVs are used for collaborative positioning. Therefore, the positioning performance cannot be improved only by increasing the number of UAVs, but also by improving the performance of collaborative positioning algorithm.

Mapping the associations among task complexity, emotionality, and linguistic complexity in L2 writing

This study explored the relationship between task complexity, textual emotionality, and linguistic complexity in second language (L2) writing. Fifty-eight L2 English learners performed simple and complex versions of an argumentative writing task manipulated along with resource-­directing variables. The essays were first analysed for textual emotionality with sentiment analysis and then examined using a set of lexical and syntactic complexity and cohesiveness indices. Regarding emotionality, the complex task elicited more positive and negative emotions than the simple task. Further, the complex task led to greater lexical complexity and cohesiveness than the simple task, but the two tasks were not statistically different from each other in terms of syntactic complexity features. Varied patterns of correlations were observed between emotionality metrics and indices of different dimensions of linguistic complexity in the two tasks. Our findings focusing on the intersections of cognitive, socio-emotive, and linguistic components suggest that different task complexity manipulations could generate varying cognitive demands, affecting L2 written production. These findings provide theoretical and pedagogical implications for TBLT researchers and L2 writing practitioners.

Pure point diffraction and entropy beyond the Euclidean space

For Euclidean pure point diffractive Delone sets of finite local complexity and with uniform patch frequencies it is well known that the patch counting entropy computed along the closed centred balls is zero. We consider such sets in the setting of σ-compact locally compact Abelian groups and show that the topological entropy of the associated Delone dynamical system is zero. For this we provide a suitable version of the variational principle. We furthermore construct counterexamples, which show that the patch counting entropy of such sets can be non-zero in this context. Other counterexamples will show that the patch counting entropy of such a set cannot be computed along a limit and even be infinite in this setting.

VeriGen: A Large Language Model for Verilog Code Generation

In this study, we explore the capability of Large Language Models (LLMs) to automate hardware design by automatically completing partial Verilog code, a common language for designing and modeling digital systems. We fine-tune pre-existing LLMs on Verilog datasets compiled from GitHub and Verilog textbooks. We evaluate the functional correctness of the generated Verilog code using a specially designed test suite, featuring a custom problem set and testing benches. Here, our fine-tuned open-source CodeGen-16B model outperforms the commercial state-of-the-art GPT-3.5-turbo model with a 1.1% overall increase. Upon testing with a more diverse and complex problem set, we find that the fine-tuned model shows competitive performance against state-of-the-art gpt-3.5-turbo, excelling in certain scenarios. Notably, it demonstrates a 41% improvement in generating syntactically correct Verilog code across various problem categories compared to its pre-trained counterpart, highlighting the potential of smaller, in-house LLMs in hardware design automation. We release our training/evaluation scripts and LLM checkpoints as open-source contributions.

Robust Multivariate Functional Control Chart

In modern Industry 4.0 applications, a huge amount of data is acquired during manufacturing processes and is often contaminated with outliers, which can seriously reduce the performance of control charting procedures, especially in complex and high-dimensional settings. In the context of profile monitoring, we propose a new framework that is referred to as robust multivariate functional control chart (RoMFCC) to monitor a multivariate functional quality characteristic while being robust to both functional casewise and componentwise outliers. In the former case, observations of the quality characteristic are contaminated in all functional variables or components, while, in the latter, the contamination affects one or more components independently. The RoMFCC relies on (I) a functional filter to identify componentwise outliers to be replaced by missing components; (II) a robust multivariate functional data imputation method; (III) a casewise robust dimensionality reduction; (IV) a monitoring strategy for the quality characteristic. Through a Monte Carlo simulation study, the RoMFCC is compared with competing schemes that have already appeared in the literature. A case study is finally presented where the proposed framework is used to monitor a resistance spot welding process in the automotive industry. RoMFCC is implemented in the R package funcharts, available online on CRAN.

Kinematic reconstruction of active tectonic and halokinetic structures in the 2021 NW Palagruža earthquake area (Central Adriatic)

In March 2021, a compressional earthquake sequence (mainshock Mw 5.2) occurred in the Central Adriatic Sea, offshore Croatia. The struck area is characterized by a complex tectonic settings due to due interaction between tectonic and halokinetic structures. Former studies in this region, mostly based on geophysical and seismological data, do not provide a comprehensive description of the geological complexities of the area, caused by the presence of different types of active structures. Following the interpretation and depth conversion of a set of seismic reflection profiles, we present a kinematic restoration to obtain the shortening rates for the last 6 Myr. We highlight the presence of three main types of active structures: i) shallow thrusts and related folds deforming the seafloor, ii) deep thrusts promoting large-scale deformation, iii) halokinetic structures deforming, at least, the Messinian. We highlight how the structural setting of the area is more complex than previously interpreted, with a possible decoupling of shallow and deep structures and an interaction between tectonic and halokinetic structures. This work opens new perspectives about the role of halokinetic processes in active seismogenic areas.

Testing the Relationship of Linguistic Complexity to Second Language Learners’ Comparative Judgment on Text Difficulty

AbstractThis study examined the relationship of linguistic complexity, captured using a set of lexical richness, syntactic complexity, and discoursal complexity indices, to second language (L2) learners’ perception of text difficulty, captured using L2 raters’ comparative judgment on text comprehensibility and reading speed. Testing materials were 180 texts abridged from college English coursebooks, and raters were 90 advanced Chinese learners of L2 English. Forty‐five raters read paired texts and determined which text was harder to understand in each pair, and another 45 raters read paired texts and determined which text they read faster in each pair. Two stepwise linear regression models containing lexical, syntactic, and discoursal features explained 48.1% and 54.6% of the variance in L2 learners’ estimates of text comprehensibility and reading speed, respectively, outperforming four commonly used language readability models. These findings contribute useful insights into the relationship between linguistic complexity and L2 learners’ perception of text difficulty.

Structure and agency in resistance to schooling: Class, race, and the reproduction of unequal outcomes

For low-income and marginalized racialized minority youth, declining prospects of mobility can undermine favorable attitudes toward schooling if adolescents anticipate limited utility in schooling. We find that adolescents' awareness of race and class inequality affects a complex set of attitudes toward schooling, and that these attitudes contribute to outcomes varying by race/ethnicity and class. We capitalize on a unique longitudinal dataset with a random stratified sample of 1428 Black and White high school graduates from a large school system. Using surveys and administrative data, we show how structural factors and student characteristics shape educational attitudes; and then how these attitudes, school structural features, student, family, and neighborhood factors predict educational outcomes. We find the common ground between Willis' resistance theory emphasizing class and Ogbu’s cultural-ecological model focusing on race. Results provide greater conceptual clarity for core constructs associated with both theories of resistance.

Is it time for a precision health approach to the management of newborn hyperbilirubinemia?

Newborn hyperbilirubinemia during the first two weeks of lifeis one of most common problems requiring management decisions by a pediatrician. However, high bilirubin levels in the circulation have been associated with neurologic injury under a variety of conditions encountered in the newborn infant, such as hemolysis. The risk for developing dangerous hyperbilirubinemia is multifactorial and is determined by a complex set of factors related to a newborn infant's genetic capacities as well as intra- and extrauterine exposures. To this end, a precision health approach based on the integration of prenatal genetic and postnatal diagnostic measures might improve the management of neonatal hyperbilirubinemia.

Catalytic and Base-free Suzuki-type α-Arylation of Cyclic 1,3-Dicarbonyls via a Cyclic Iodonium Ylide Strategy.

To date, it remains challenging to achieve a general and catalytic α-arylation of cyclic 1,3-dicarbonyls, particularly ubiquitous heteroaromatic ones. In most cases, the preparation of their medically significant arylated derivatives requires multistep synthetic sequences. Herein, we introduce a new, convenient strategy involving the conversion of cyclic 1,3-dicarbonyls to cyclic iodonium ylides (CIYs), followed by rhodium-catalyzed α-arylation with arylboronic reagents via carbene coupling. This approach is mild, operationally simple, base-free, biocompatible, and exhibits broad substrate scope (>100 examples), especially with respect to various heteroaromatic 1,3-dicarbonyls and ortho-substituted or base-sensitive arylboronic acids. Importantly, owing to the excellent compatibility with various arylboronic acids or boronate esters (ArBpin, ArBneop, or ArBF3K), this method allows the late-stage installation of heterocyclic 1,3-dicarbonyl motifs in highly complex settings. The utility of this transformation is further demonstrated through significantly simplifying the synthesis of several bioactive molecules and natural products.

Catalytic and Base‐free Suzuki‐type α‐Arylation of Cyclic 1,3‐Dicarbonyls via a Cyclic Iodonium Ylide Strategy

AbstractTo date, it remains challenging to achieve a general and catalytic α‐arylation of cyclic 1,3‐dicarbonyls, particularly ubiquitous heteroaromatic ones. In most cases, the preparation of their medically significant arylated derivatives requires multistep synthetic sequences. Herein, we introduce a new, convenient strategy involving the conversion of cyclic 1,3‐dicarbonyls to cyclic iodonium ylides (CIYs), followed by rhodium‐catalyzed α‐arylation with arylboronic reagents via carbene coupling. This approach is mild, operationally simple, base‐free, biocompatible, and exhibits broad substrate scope (>100 examples), especially with respect to various heteroaromatic 1,3‐dicarbonyls and ortho‐substituted or base‐sensitive arylboronic acids. Importantly, owing to the excellent compatibility with various arylboronic acids or boronate esters (ArBpin, ArBneop, or ArBF3K), this method allows the late‐stage installation of heterocyclic 1,3‐dicarbonyl motifs in highly complex settings. The utility of this transformation is further demonstrated through significantly simplifying the synthesis of several bioactive molecules and natural products.

Perspectives on the Public Interest and Social Justice in Planning

“Social justice” and “public interest” have traditionally been fundamental concepts for most planning theories. The planning literature about these concepts has become a complex set of interpretations that make it difficult to explain the relationship between the two concepts. The current article attempts to shed light on this conceptual confusion about the relationship between these concepts by using the meta-synthesis method. This meta-synthesis leads to the identification of four distinct perspectives “Utilitarians,” “Democratic Proceduralists,” “Structuralists,” and “Post-structuralists.” Each of which places them in different positions from each other according to their distinct definitions of these concepts.

An Enterprise View for Artificial Intelligence Capability and Governance: A System Dynamics Approach

The government “enterprise” consists of a complex set of organizations with a multitude of goals and values, serving an equally diverse group of constituents. Because of this complexity, governing technology and data to support artificial intelligence (AI) capability has proven to be a difficult task that—according to experts—requires a systems perspective in its design and implementation. In this article, we take a conceptual approach to respond to this call from experts by providing working definitions of both enterprise data governance and a systems approach to management. Using these working definitions and data from municipal governments in Mexico, we develop a system dynamics model to explore some potential tradeoffs in the process of developing an enterprise view of information systems and data to create capability to develop AI applications in government. Simulation experiments suggest that an emphasis on governance of IT may create a strong foundation for the development of AI capability.

"But at a certain point, the lights literally went out": A qualitative study exploring midlife women's experiences of health, wellbeing, and functioning in relation to paid work.

In the Netherlands, the fact that midlife women constitute a considerable segment of the working population is relatively new. Generally paid work contributes to midlife women's wellbeing, but they also report health challenges, such as work-related fatigue and the menopause. The objective of this study is to understand how midlife women themselves perceive their health, wellbeing, and functioning in relation to paid work. In this exploratory qualitative study, 28 women participated in five ethnically homogeneous focus group discussions (FGDs). De FGDs were recorded, transcribed verbatim, and thematically analyzed using MAXQDA. We identified exhaustion as central to our analysis. During midlife, exhaustion seems to occur once a certain limit has been reached, both physically and mentally, with women feeling to have reached the end of their rope. Besides obvious physiological challenges, we identified two major themes in which we discuss challenges both in paid work and private life: (1) work environment and working conditions, and (2) burdens in private life. Participants took various measures to manage and try to reduce exhaustion, including finding a new job or negotiating different job tasks, and reducing work hours. This study indicates that the extent to which women experience exhaustion is associated with challenges in both paid work and private life. The underlying processes do not seem to reflect individual problems, but reflect a complex set of factors at the structural level. Nevertheless, women take several individual measures to reduce their exhaustion, including reducing their participation in paid work.

PENGARUH GAYA KEPEMIMPINAN DAN KEPUASAN KERJA TERHADAP KINERJA PERAWAT DI RUANG RAWAT INAP A RSUP DR. SOERADJI TIRTONEGORO KLATEN

Inpatient services of RSUP Dr. Soeradji Tirtonegoro Klaten is a complex set of services and giving major contribution in determining the quality of service. Nurses play an important role as the spearhead of the longest and energy dealing with patients. Nurses activities reflect the image of the hospital, nurses' performance is inseparable from leadership and job satisfaction. The purpose of research is knowing the influence the effect of leadership style and job satisfaction toward performance. The type of research is quantitative research with a cross sectional design. Independent variable leadership style and job satisfaction, the dependent variable is the performance of nurses. The registered nurse population as a civil servant ( PNS ), amounting to 75 people, collecting sampling techniques total sampling. Analysis techniques of Multiple linear regression. The results is Significance value of leadership style of 0.022 (Sig.< 0,05) and job satisfaction 0.132 (Sig.> 0,05). Test results of F 15.779 with significance level of 0.000. Adjusted R2 coefficient of 28.5 %. The conclusion is 1) leadership style effect a significant toward the nurses performance, 2) job satisfaction variable does not affect the nurses performance, and 3) Leadership Style And Job Satisfaction simultaneously influence toward the nurse performance of inpatient ard A RSUP Dr. Soeradji Tirtonegoro Klaten.

AI-guided histopathology predicts brain metastasis in lung cancer patients.

Brain metastases can occur in nearly half of patients with early and locally advanced (stage I-III) non-small cell lung cancer (NSCLC). There are no reliable histopathologic or molecular means to identify those who are likely to develop brain metastases. We sought to determine if deep learning (DL) could be applied to routine H&E-stained primary tumor tissue sections from stage I-III NSCLC patients to predict the development of brain metastasis. Diagnostic slides from 158 patients with stage I-III NSCLC followed for at least 5 years for the development of brain metastases (Met+, 65 patients) versus no progression (Met-, 93 patients) were subjected to whole-slide imaging. Three separate iterations were performed by first selecting 118 cases (45 Met+, 73 Met-) to train and validate the DL algorithm, while 40 separate cases (20 Met+, 20 Met-) were used as the test set. The DL algorithm results were compared to a blinded review by four expert pathologists. The DL-based algorithm was able to distinguish the eventual development of brain metastases with an accuracy of 87% (p < 0.0001) compared with an average of 57.3% by the four pathologists and appears to be particularly useful in predicting brain metastases in stage I patients. The DL algorithm appears to focus on a complex set of histologic features. DL-based algorithms using routine H&E-stained slides may identify patients who are likely to develop brain metastases from those who will remain disease free over extended (>5 year) follow-up and may thus be spared systemic therapy. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Trust in autonomous vehicles: insights from a Swedish suburb

ABSTRACT This paper investigates elements of trust in autonomous vehicles (AVs). We contextualise autonomous vehicles as part of people's everyday settings to extend previous understandings of trust and explore trust in autonomous vehicles in concrete social contexts. We conducted online co-creation workshops with 22 participants, using design probes to explore trust and AVs in relation to people's everyday lives. Using a socio-technical perspective, we show how trust and acceptance depend not only on the underlying AV technology but also – if not more so – on human-to-human relationships and real-life social circumstances. We argue that when investigating issues of trust and automation, the scope of analysis needs to be broadened to include a more complex socio-technical set of (human and non-human) agents, to extend from momentary human-computer interactions to a wider timescale, and be situated in concrete spaces, social networks, and situations.

Progress Toward Rubella and Congenital Rubella Syndrome Elimination - Worldwide, 2012-2022.

Rubella virus is a leading cause of vaccine-preventable birth defects. Infection during pregnancy can result in miscarriage, fetal death, stillbirth, or a constellation of birth defects, including cataracts, deafness, heart defects, and developmental delay, known as congenital rubella syndrome (CRS). A single dose of rubella-containing vaccine can provide lifelong protection against rubella. The Global Vaccine Action Plan 2011-2020 included a target to achieve elimination of rubella in at least five of the six World Health Organization (WHO) regions by 2020, and rubella elimination is a critical goal of the Immunization Agenda 2030. This report updates a previous report and describes progress toward rubella and CRS elimination during 2012-2022. During 2012-2022, among 194 WHO countries, the number that included rubella-containing vaccine (RCV) in their immunization schedules increased from 132 (68%) to 175 (90%) and the percentage of the world's infants vaccinated against rubella increased from 40% to 68%. Reported rubella cases declined 81%, from 93,816 in 2012 to 17,407 in 2022. Verification of rubella elimination was achieved in 98 (51%) of 194 countries by 2022, an increase from 84 (43%) countries in 2019. Despite significant progress in the introduction of RCV into routine immunization programs worldwide, approximately 25 million infants annually still do not have access to RCV. Nevertheless, even in complex settings, the increasing number of countries that have achieved and sustained rubella elimination demonstrates progress toward global rubella elimination.

On the Magnetic Field Properties of Protostellar Envelopes in Orion

We present 870 μm polarimetric observations toward 61 protostars in the Orion molecular clouds with ∼400 au (1″) resolution using the Atacama Large Millimeter/submillimeter Array. We successfully detect dust polarization and outflow emission in 56 protostars; in 16 of them the polarization is likely produced by self-scattering. Self-scattering signatures are seen in several Class 0 sources, suggesting that grain growth appears to be significant in disks at earlier protostellar phases. For the rest of the protostars, the dust polarization traces the magnetic field, whose morphology can be approximately classified into three categories: standard-hourglass, rotated-hourglass (with its axis perpendicular to outflow), and spiral-like morphology. A total of 40.0% (±3.0%) of the protostars exhibit a mean magnetic field direction approximately perpendicular to the outflow on several × 102–103 au scales. However, in the remaining sample, this relative orientation appears to be random, probably due to the complex set of morphologies observed. Furthermore, we classify the protostars into three types based on the C17O (3–2) velocity envelope’s gradient: perpendicular to outflow, nonperpendicular to outflow, and unresolved gradient (≲1.0 km s−1 arcsec−1). In protostars with a velocity gradient perpendicular to outflow, the magnetic field lines are preferentially perpendicular to outflow, with most of them exhibiting a rotated hourglass morphology, suggesting that the magnetic field has been overwhelmed by gravity and angular momentum. Spiral-like magnetic fields are associated with envelopes having large velocity gradients, indicating that the rotation motions are strong enough to twist the field lines. All of the protostars with a standard-hourglass field morphology show no significant velocity gradient due to the strong magnetic braking.

Application of Complex Neutrosophic Graphs in Hospital Infrastructure Design

Complex neutrosophic graphs are created by combining complex neutrosophic sets with graph theory ideas. This provides a flexible framework for tackling complex problem-solving circumstances. Various processes, such as union, join, and composition, are thoroughly investigated to improve the administration of complicated neutrosophic graphs. This research also looks into the area of complicated neutrosophic graph homeomorphisms, investigating the transformations and mappings that occur inside these structures. This investigation advances our knowledge of the intrinsic features and linkages found in complicated neutrosophic graphs. Finally, our methodology’s practical usefulness is demonstrated by its use in the design of hospital infrastructure. We illustrate the effectiveness of complicated neutrosophic graphs in addressing difficult design concerns and optimizing infrastructure solutions for practical deployment in this real-world scenario.