Restricted Set Research Articles

Multi-layer controlled remote implementation of partially unknown single-qudit operations

Our concern is to investigate controlled remote implementation of partially unknown operations with multiple layers. We first propose a scheme to realize the remote implementation of single-qubit operations belonging to the restricted sets. Then, the proposed scheme is extended to the case of single-qudit operations. As long as the controller and the higher-layer senders consent, the receiver can restore the desired state remotely operated by the sender. It is worth mentioning that the recovery operation is deduced by general formulas which clearly reveal the relationship with the measurement outcomes. For the sake of clarity, two specific examples with two levels are given respectively. In addition, we discuss the influence of amplitude-damping noise and utilize weak measurement and measurement reversal to effectively resist noise.

Estimating the Social Visibility of Abortions in Uganda and Ethiopia Using the Game of Contacts.

Social network-based data collection methods that rely on third-party reporting have emerged as a promising approach for measuring abortion in restrictive settings. In order for these methods to accurately measure abortion incidence, they must also assess the visibility of abortions within social networks. Failure to do so may result in estimates affected by transmission bias, caused by imperfect knowledge of all abortions within one's social network. In this paper, we present exploratory research that uses respondent-driven sampling (RDS) and the game of contacts method to measure abortion visibility in four sites in Uganda and Ethiopia. We assess the existence of potential biases in the game of contacts estimate of abortion visibility in each site by conducting several internal and external validity tests. While these tests provided some promising results, other factors such as the representativeness of the RDS samples, direct versus indirect abortion knowledge transfers, and the generalizability of the study sites may have introduced biases into the final estimates of abortion visibility in this study. We conclude by making recommendations on how applications of this methodology could be improved to better estimate abortion-related transmission bias.

A Data-Driven Model for Rapid CII Prediction

The shipping industry plays a crucial role in global trade, but it also contributes significantly to environmental pollution, particularly in regard to carbon emissions. The Carbon Intensity Indicator (CII) was introduced with the objective of reducing emissions in the shipping sector. The lack of familiarity with the carbon performance is a common issue among vessel operator. To address this aspect, the development of methods that can accurately predict the CII for ships is of paramount importance. This paper presents a novel and simplified approach to predicting the CII for ships, which makes use of data-driven modelling techniques. The proposed method considers a restricted set of parameters, including operational data (draft and speed) and environmental conditions, such as wind speed and direction, to provide an accurate prediction of the CII factor. This approach extends the state of research by applying Deep Neural Networks (DNNs) to provide an accurate CII prediction with a deviation of less than 6% over a considered time frame consisting of different operating states (cruising and maneuvering mode). The result is achieved by using a limited amount of training data, which enables ship owners to obtain a rapid estimation of their yearly rating prior to receiving the annual CII evaluation.

Impact of pandemic-driven online education on student evaluation scores: A comparative study in natural sciences

ABSTRACT The COVID-19 pandemic necessitated the adoption of online systems by educational institutions for infection control. The widespread implementation of online systems presented an opportunity to assess the impact of online education. However, research into the perceptions of students who directly experienced these changes remained relatively underexplored. This study conducted a comparative analysis of student evaluation of teaching scores (SET) before and after the pandemic to examine the impact of accelerated online system adoption on student satisfaction. This study employed a quantitative research design, utilising Ordinary Least Squares regression for the analysis. The analysis utilised SET data from 49,201 students enrolled in the College of Natural Sciences of a top-ranking university in South Korea from 2018 to 2020. The results showed that theory courses that emphasised information delivery demonstrated minimal changes in evaluation scores. By contrast, laboratory courses requiring direct student engagement and controlled environments demonstrated decreased scores. Notably, mathematics, with a conducive online learning environment for laboratory courses, exhibited improved post-pandemic evaluations. Furthermore, the student evaluation of teaching scores decreased in chemistry classes that require restricted laboratory settings. These findings highlight the importance of considering instructional characteristics when integrating modern technologies into educational systems to effectively replace traditional lectures.

Home Healthcare Staffing, Routing, and Scheduling Problem With Multiple Shifts and Emergency Considerations

ABSTRACTEffective planning of human resources is critical in designing an efficient home healthcare system. In this study, we present a novel home healthcare staffing, routing, and scheduling problem inspired by a real‐world application. The proposed problem addresses a set of patients, with varying daily visit requirements, being served by a set of caregivers with different qualification levels over a multi‐day multi‐shift planning horizon. The problem aims to minimize the number of extra shifts for caregivers, maximize the allocation of caregivers to emergencies, and minimize the sum of route durations over the planning horizon. These objectives are optimized hierarchically while considering a set of restrictions, including time windows, skill matching, synchronization, care continuity, and labor regulations. To tackle the problem, we introduce a mixed‐integer linear programming model. The model is then extended and two sets of valid inequalities are incorporated to enhance its tightness. Computational experiments are conducted on a set of 20 instances. The results highlight the efficiency of the proposed extension in increasing both the number of instances that can be solved to optimality and the number of instances for which a feasible solution is found.

Right-angled links in thickened surfaces

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Harnessing Ascidians as Model Organisms for Environmental Risk Assessment

Environmental Risk Assessment (ERA) often relies on a restricted set of species as bio-indicators, introducing uncertainty when modeling complex environmental variables. This may lead to oversimplified or erroneous risk assessments. Ascidians, marine filter-feeding sessile chordates, are valuable models for scientific research in various biological fields such as stem cell biology, embryogenesis, regeneration, innate immunity, and developmental biology. Their global distribution, sensitivity to pollutants, high abundance, mass sexual reproduction, and habitation in coastal areas impacted by anthropogenic pollution make them excellent indicators for monitoring marine pollution and global environmental changes, including biological invasions and species diversity diminution cases. Despite their potential as environmental bioindicators, ascidians remain underutilized in ERAs (≤0.13% of ERA studies), particularly in the field of chemical pollution impact assessment, primarily due to a lack of standardization. This underrepresentation poses a challenge for accurate modeling, especially in models relying on a broad range of species (e.g., Species Sensitivity Distributions). Given these constraints, expanding the use of ascidians in ERAs could improve the comprehension and precision of environmental changes and their assessments. This underscores the necessity for future research to establish standardized testing protocols and choose the most suitable ascidian species for inclusion in ERAs.

Children’s Experiences of Police Custody and the Implications for Trauma-Informed Policing

The development of a trauma-informed Scotland is an ambitious and important agenda, but not without its challenges and limitations. In restrictive settings that rely on the application of power and control as part of their modus operandi, genuinely trauma-informed practice may be difficult to achieve. Drawing on interviews with 11 children, this article maps their experiences of police custody to trauma-informed practice principles. The gap between the espoused policies and the realities of custom and practice outlines the boundaries of trauma-informed practice in justice settings. The article concludes that police custody is antithetical to the concept of trauma-informed practice.

Clinical Practice Guideline for Diabetes Management in the Post-Acute and Long-Term Care Setting

The newly revised Clinical Practice Guideline (CPG) for Diabetes Management in the Post-Acute and Long-Term Care (PALTC) Setting is an extremely useful resource that incorporates new evidence and perspectives related to overall goals in diabetes care. The CPG provides detailed information in usable Tables for how to use and manage the increasing number of medication alternatives for PALTC patients with diabetes. In addition, the CPG addresses the critical roles of all members of the interprofessional team for the optimal management of older adults living with diabetes.The primary goal of care as described in the CPG is to make diabetes management individualized and consistent with the patient's/resident's goals of care, and to optimize quality of life and the ability to live in the least restrictive setting possible. To achieve this, the CPG emphasizes the importance of understanding the patients’ overall health status, what their preferences and values are, their life expectancy, the clinical benefit of tight versus more liberal control of glucose, risk of hypoglycemia, and impact of treatment on quality of life and ability to live in a certain setting of care (e.g., if injectable therapy is possible). As with other PALTmed CPGs, this new CPG takes the team through the process of recognition, assessment, treatment and monitoring. Implementation of the Diabetes Management in PALTC Settings CPG can help those working in these settings ensure that their patients and residents are getting the most appropriate and current evidence-based treatment for this challenging clinical problem.

Hierarchical Controlled Joint Remote Implementation of the Partially Unknown Operations of m Qudits via m High-Dimensional Entangled States.

We present a protocol for the hierarchical controlled joint remote implementation of the partially unknown operations of m qudits belonging to some restricted sets by using m multiparticle high-dimensional entangled states as the quantum channel. All the senders share the information of the partially unknown operations and cooperate with each other to implement the partially unknown operations on the remote receiver's quantum system. The receivers are hierarchized in accordance with their abilities to reconstruct the desired state. The agents in the upper grade need only cooperate with one of the lower-grade agents, and the agents in the lower grade need the cooperation of all the other agents. The protocol has the advantage of having high channel capacity by using a high-dimensional entangle state as the quantum channel for the hierarchial controlled joint remote implementation of partially unknown quantum operations of m qudits.

Integrating Kalman filter noise residue into U-Net for robust image denoising: the KU-Net model

In low-level image processing, where the main goal is to reconstruct a clean image from a noise-corrupted version, image denoising continues to be a critical challenge. Although recent developments have led to the introduction of complex architectures to improve denoising performance, these models frequently have more parameters and higher computational demands. Here, we propose a new, simplified architecture called KU-Net, which is intended to achieve better denoising performance while requiring less complexity. KU-Net is an extension of the basic U-Net architecture that incorporates gradient information and noise residue from a Kalman filter. The network’s ability to learn is improved by this deliberate incorporation, which also helps it better preserve minute details in the denoised images. Without using Image augmentation, the proposed model is trained on a limited dataset to show its resilience in restricted training settings. Three essential inputs are processed by the architecture: gradient estimations, the predicted noisy image, and the original noisy grey image. These inputs work together to steer the U-Net’s encoding and decoding stages to generate high-quality denoised outputs. According to our experimental results, KU-Net performs better than traditional models, as demonstrated by its superiority on common metrics like the Structural Similarity Index (SSIM) and Peak Signal-to-Noise Ratio (PSNR). KU-Net notably attains a PSNR of 26.60 dB at a noise level of 50, highlighting its efficacy and potential for more widespread use in image denoising.

Legal provisions on medical aid in dying encode moral intuition.

In recent decades, many jurisdictions have moved toward legalizing euthanasia and assisted suicide, alongside a near-universal increase in public acceptance of medical aid in dying. Here, we draw on a comprehensive quantitative review of current laws on assisted dying, experimental survey evidence, and four decades of time-series data to explore the relationship between these legislative transitions and change in moral attitudes. Our analyses reveal that existing laws on medical aid in dying impose a common set of eligibility restrictions, based on the patient's age, decision-making capacity, prognosis, and the nature of their illness. Fulfillment of these eligibility criteria elevates public moral approval of physician-assisted death, equally in countries with (i.e., Spain) and without (i.e., the United Kingdom) assisted dying laws. Finally, historical records of public attitudes toward euthanasia across numerous countries uncovered anticipatory growth in moral approval leading up to legalization, but no accelerated growth thereafter. Taken together, our findings suggest that the enactment of medical aid in dying laws, and their specific provisions, crystallize patterns in moral intuition.

Regression Approaches to Assess Effect of Treatments That Arrest Progression of Symptoms.

Motivated by a small sample example in neonatal onset multisystem inflammatory disease (NOMID), we propose a method that can be used when the interest is testing for an association between a changes in disease progression with start of treatment compared to historical disease progression prior to treatment. Our method estimates the longitudinal trajectory of the outcome variable and adds an interaction term between an intervention indicator variable and the time since initiation of the intervention. This method is appropriate for a situation in which the intervention slows or arrests the effect of the disease on the outcome, as is the case in our motivating example. By simulation in small samples and restricted sets of treatment initiation times, we show that the generalized estimating equations (GEE) formulation with small sample adjustments can bound the Type I error rate better than GEE and linear mixed models without small sample adjustments. Permutation tests (permuting the time of treatment initiation) is another valid approach that can also be useful. We illustrate the methodology through an application to a prospective cohort of NOMID patients enrolled at the NIH clinical center.

Seasonal dynamics in microbial trace metals transporters during phytoplankton blooms in the Southern Ocean.

Trace metals are required as cofactors in metalloproteins that are essential in microbial metabolism and growth. The microbial requirements of diverse metals and the capabilities of prokaryotic taxa to acquire these metals remain poorly understood. We present here results from metagenomic observations over an entire productive season in the region off Kerguelen Island (Indian Sector of the Southern Ocean). We observed seasonal patterns in the abundance of prokaryotic transporters of seven trace elements (zinc [Zn], manganese [Mn], nickel [Ni], molybdenum [Mo], tungsten [W], copper [Cu] and cobalt [Co]) and the consecutive spring and summer phytoplankton blooms were strong drivers of these temporal trends. Taxonomic affiliation of the functional genes revealed that Rhodobacteraceae had a broad repertoire of trace metal transporters (Mn, Zn, Ni, W and Mo) and a more restricted set was observed for other prokaryotic groups, such as Flavobacteriaceae (Zn), Nitrincolaceae (Ni and W) and Thioglobaceae (Mo). The prevalence of trace metal transporters within a prokaryotic group, as determined on the family level, was overall confirmed in representative metagenome-assembled genomes. We discuss the potential involvement of prokaryotic groups in processes related to organic matter utilisation that require these metals and the consequences on carbon and trace metal cycling in surface waters of the Southern Ocean.

Effects of velocity regularization on neural network performance in processing particle images

Recent studies have witnessed remarkable progress in harnessing convolutional neural networks (CNNs) to overcome the inherent limitations of conventional particle image velocimetry (PIV) methods. Traditional PIV techniques often suffer from compromised resolution and precision, hindering their ability to capture the complexities of fluid dynamics within the observation frame. While CNNs offer promise in addressing these challenges, they face obstacles such as limited accuracy, weak generalization, and a dearth of physical interpretability. In our prior research, we presented a CNN architecture that incorporates optical flow algorithms as supplementary physical constraints, thereby bolstering the model interpretability and precision. Nevertheless, the practical implications of this approach, especially when dealing with multi-dimensional, low-quality particle image data and restricted training sets, have yet to be fully explored. To address this knowledge gap, we have assembled a comprehensive dataset that simulates a wide array of experimental scenarios. We have systematically assessed the influence of velocity regularization on neural network performance, taking into account variations in image quality and the size of training datasets. The results underscore the pivotal importance of velocity regularization in enhancing the predictive prowess of neural networks, particularly when dealing with poor image quality and smaller data sizes. This study provides useful insights into the effective application of CNNs with velocity regularization in the field of experimental fluid dynamics.

Timing and origin of the Lomagundi-Jatuli Event: Insights from U[sbnd]Pb geochronology, C-O-Fe isotopes and REE compositions from the Jingshan Group, North China Craton

The Lomagundi-Jatuli Event (LJE) represents perhaps the largest and longest positive carbon isotope excursion of Earth history. However, the synchroneity, scale, and linkage of the LJE to Earth's early history of atmospheric oxygenation remain controversial. Strata of the Paleoproterozoic Jingshan Group of the North China Craton that preserve the isotopic record of the LJE excursion in marble layers and abundant graphite deposits provide an opportunity to elucidate the significance of the LJE. Carbon isotopic values (δ13CV-PDB) of the LJE based on analysis of 20 samples of the Lugezhuang Formation, lower Jingshan Group, range from −0.8 to +9.6 ‰ and display positive co-variance with stable oxygen isotope values (δ18OV-PDB). The positive carbon isotope excursion is constrained to 2140.6 ± 8.5 Ma (MSWD = 0.82, n = 25) based on magmatic zircon UPb geochronology of biotite granulite. Variation of facies-dependent carbon isotope values, the presence of graphite deposits of the Douya Formation, upper Jingshan Group, and the absence of a Ce anomaly in PAAS normalized REE patterns of marble samples suggest that the positive carbon isotope excursion is not linked to a marked increase of organic carbon burial and associated significant atmosphere oxygenation. Elevated concentrations of iron and PAAS-normalized middle REE enrichment of analyzed Jingshan Group marble samples point to anoxic and ferruginous oceanic conditions during accumulation of Jingshan Group carbonate. A positive Eu anomaly (average = 1.58), low La (average = 0.23), (Nd/Yb)N (average = 1.27), and Y/Ho (average = 36.6) anomalies, and negative iron isotope values (average δ56Fe = −0.12 ‰) are consistent with accumulation of Paleoproterozoic Jingshan Group carbonate in a restricted marine setting that was affected by high temperature hydrothermal fluids. Enrichment of the studied samples in heavy carbon isotope suggests elevated bio-productivity in the restricted, redox stratified marine setting in which Jingshan Group carbonate accumulated. Thus, it is likely that the positive stable carbon isotope excursion associated with Jingshan Group strata as well as other contemporaneous isotope excursions are local signals that are linked to a global perturbation of the carbon cycle.

A project and lift approach for a 2-commodity flow relocation model in a time expanded network

We deal here with a general 2-commodity flow model over a time expanded network designed for the management of a shared mobility systems. The model involves an integral flow vector that represents carriers together with an integral flow vector that represents the items transported by those carriers. It simultaneously copes with temporal and resource issues, and is difficult to handle in the practice. So we propose here a Project and Lift approach to handle it. We start by projecting the time expanded network model on the original transit network to obtain a simpler two-commodity flow projected model. In order to make this projected model consistent with the original problem, we introduce some complex constraints, prove that these constraints can be separated in polynomial time and discuss the experimental behavior of the related Branch-and-Cut algorithm. Next, we introduce the Lift issue about the way one may turn an optimal solution of our projected model into a solution of the original problem. Finally, we thoroughly study a somewhat restrictive Strong Lift setting of this Lift issue, design and test an exact mixed integer programming Strong Lift model, and discuss some flexible alternative approaches.

Comparison of B Cell Variable Region Gene Segment Characteristics in Neuro-autoantibodies.

Autoimmune pediatric neurologic diseases have variable phenotypes and presentations, making diagnosis challenging. The pathologic mechanisms are also distinct, including cell-mediated and Ab-mediated autoimmunity, paraneoplastic syndromes, and postinfectious processes. In recent years a number of studies have described the characteristics of the autoantibodies involved in a number of these diseases. Some of the described Abs use a restricted set of variable gene segments. We sought to compare the Ab characteristics of autoantibodies related to some of the more common disorders to discover whether specific Ab signatures are universally associated with neuroautoimmune diseases. We initially performed a literature review to summarize the Ab characteristics of autoantibodies related to some of the more common disorders, including N-methyl-d-aspartate receptor (NMDAR) and leucine-rich, glioma-inactivated 1 (LGI-1). Next, we performed data analysis from selected studies that sequenced Ig genes to further characterize NMDAR and LGI-1 autoantibodies including CDR3 length distribution, variable gene sequence usage, and isotype use. We found that CDR3 length of NMDAR autoantibodies was normally distributed whereas the CDR3 length distribution of LGI-1 autoantibodies was skewed, suggesting that there is no global structural restriction on types of autoantibodies that can cause encephalitis. We also found that IgG1-IgG3 were the main NMDAR autoantibody isotypes detected, while IgG4 was the major isotype used in autoantibodies from LGI-1 encephalitis. These findings are useful for our understanding of autoimmune encephalitis and will help facilitate better diagnosis and treatment of these conditions in the future.

Strategy for optimizing outpatient access for chronic patients in a health insurance company

ABSTRACT The last decades have been marked by significant population transformations in several nations. The demographic transition, resulting from the significant reduction in birth rates and the increase in life expectancy, has resulted in a further ageing population. Knowing how to prioritize and optimize the allocation of resources becomes, therefore, a prerequisite for managers decision-making. Strategies that reduce hospital costs while improving the quality of care are essential for the sector, mainly because they allow integrated processes and greater accessibility to users. Proximity and ease of access to health services are essential to ensure continuity of care and improve patient engagement with suggested treatment. The objective of this article is to demonstrate a viable solution for the allocation of chronic patients in the outpatient units of a Brazilian health insurance company in a regionalized manner and based on a set of criteria and restrictions. The study used Integer Programming, an optimization technique of Operations Research, to determine the outpatient units. As a result, it was possible to identify and suggest practical improvements in the care coordination process, offering a concrete contribution to the effectiveness and operational efficiency of the decision-making process.

Investigation of the distribution patterns in moinids (Crustacea: Cladocera: Moinidae) forming ephippia with two resting eggs

During last two decades, morphological and genetic studies of the microcrustaceans from the family Moinidae Goulden, 1968 (Crustacea: Branchiopoda: Cladocera) were intensified. However, species diversity within this family remains underestimated. It refers to both subtropical and tropical areas of different continents that have traditionally been less studied compared with Central Europe and some other Palaearctic regions. In addition to this, only a restricted set of morphological characteristics is used for the discrimination of species within the genus Moina Baird, 1850. Most common moinid taxa are considered species complexes rather than single species, making any biogeographic reconstruction difficult. Here, we present an investigation of distribution patterns in moinids that form ephippia with two resting eggs based on both a reexamination of data from the literature and from specimens in museum and personal collections. Also, we redescribed morphology of poorly known taxa from the arid regions of the Old World—Moina belli Gurney, 1904 and M. kaszabi Forró, 1988 and clarify their diagnostic morphological characters and distributional ranges. We found that M. belli and M. kaszabi are morphologically very similar. In both species, setae 1 and 2 of thoracic limb I are armed bilaterally by fine, densely located short setulae. Reliable differences between M. belli and M. kaszabi concern armature of the valve posteroventral portion. Among the moinids with two resting eggs in the ephippium, M. belli and M. kaszabi are morphologically closer to M. macrocopa (Straus, 1820) and M. americana Goulden, 1968. All these species have: (1) a dorsal head pore; (2) fine long hairs on head, valve and preanal margin of postabdomen; (3) thoracic limb I of male with a long exopodite. In general, an investigated group of moinids includes both species with relatively compact and very broad distributional ranges. We concluded that maximum diversity of the moinids forming ephippia with two resting eggs is characteristic of southern portions of Palaearctic and Nearctic zoogeographical regions and approximately corresponds to subtropical climate zone. We need to underline that M. macrocopa and M. americana have a great invasive potential. Both species were anthropogenically introduced in South America and have been successfully naturalized there. Their distribution in tropical regions of the Old World and Australia requires new precise investigations. A group of moinids forming ephippia with two resting eggs can be considered as a convenient model for biogeographical reconstructions, including studies on changes in aquatic ecosystems due to global climate warming, eutrophication and the introduction of non-native species. There is no doubt that subsequent joint application of morphological and genetic data will shed more light on the global phylogeographic structure of the entire family Moinidae.