Full Update Research Articles

Cracking the Code of Lumpy Skin Disease: Identifying Causes, Symptoms and Treatment Options for Livestock Farmers.

The novel bovine viral infection known as lumpy skin disease is common in most African and Middle Eastern countries, with a significant likelihood of disease transfer to Asia and Europe. Recent rapid disease spread in formerly disease-free zones highlights the need of understanding disease limits and distribution mechanisms. Capripox virus, the causal agent, may also cause sheeppox and Goatpox. Even though the virus is expelled through several bodily fluids and excretions, the most common causes of infection include sperm and skin sores. Thus, vulnerable hosts are mostly infected mechanically by hematophagous arthropods such as biting flies, mosquitoes, and ticks. As a result, milk production lowers, abortions, permanent or temporary sterility, hide damage, and mortality occur, contributing to a massive financial loss for countries that raise cattle. These illnesses are economically significant because they affect international trade. The spread of Capripox viruses appears to be spreading because to a lack of effectual vaccinations and poverty in rural areas. Lumpy skin disease has reached historic levels; as a consequence, vaccination remains the only viable option to keep the illness from spreading in endemic as well as newly impacted areas. This study is intended to offer a full update on existing knowledge of the disease's pathological characteristics, mechanisms of spread, transmission, control measures, and available vaccinations.

An Efficient Limited Memory Multi-Step Quasi-Newton Method

This paper is dedicated to the development of a novel class of quasi-Newton techniques tailored to address computational challenges posed by memory constraints. Such methodologies are commonly referred to as “limited” memory methods. The method proposed herein showcases adaptability by introducing a customizable memory parameter governing the retention of historical data in constructing the Hessian estimate matrix at each iterative stage. The search directions generated through this novel approach are derived from a modified version closely resembling the full memory multi-step BFGS update, incorporating limited memory computation for a singular term to approximate matrix–vector multiplication. Results from numerical experiments, exploring various parameter configurations, substantiate the enhanced efficiency of the proposed algorithm within the realm of limited memory quasi-Newton methodologies category.

A novel automatic generation control method with hybrid sampling for multi-area interconnected girds

Introduction: The emerging “net-zero carbon” police will accelerate the large-scale penetration of renewable energies in the power grid, which would bring strong random disturbances due to the unpredictable power output. It would affect the coordinated control performance of the distributed grids.Method: From the quadratic frequency modulation perspective, this paper proposes a fast Q-learning-based automatic generation control (AGC) algorithm, which combines full sampling with full expectation for multi-area coordination. A parameter σ is used to balance the state between the full sampling update and only the expectation update so as to improve the convergence accuracy. Meanwhile, fast Q-learning is incorporated by replacing the historical estimation function with the current state estimation function to accelerate the convergence speed.Results: Simulations on the IEEE two-region load frequency control model and Hubei power grid model in China have been performed to validate that the proposed algorithm can achieve optimal multi-area coordination and improve the control performance of frequency deviations caused by the strong random disturbances.Discussion: The proposed Q-learning-based AGC method outperforms the convergence accuracy, speed, and control performance compared with other reinforcement learning algorithms.

To (b)e or not to (b)e: no electrons at LHCb

We discuss the impact of the recent LHCb update on the two lepton-flavour universality ratios R_K and R_{K^*}, and the CMS update of B({B_s rightarrow mu ^+mu ^-}) regarding the possibility of New Physics in brightarrow sell ^+ell ^- decays. We perform global fits of the New Physics Wilson coefficients defined in the model-independent approach of the Weak Effective Theory at the b-quark mass. We discuss three different frameworks for this analysis: (i) an update limited to the experimental data but using the same theoretical framework as in earlier works, (ii) a full update concerning both the experimental inputs and the theoretical framework, (iii) an analysis without the LHCb results on electron modes. The comparison between these various sets of results allows us to identify the differences stemming from the various components of the analysis: new experimental results, new inputs for the hadronic form factors, the role played by LHCb data on electron modes. As expected, the significance of all New Physics hypotheses gets reduced after the LHCb announcements on R_{K^{(*)}} while the hypothesis of a lepton-flavour-universal contribution to the Wilson coefficient of the semileptonic O_{9ell } operators (possibly with a very small lepton-flavour-universality violating component) is clearly reinforced. We also discuss the possibility of a long-distance charm-loop contribution through a mode-by-mode analysis and we find that the preferred values for the {mathcal C}_{9mu } Wilson coefficient are consistent throughout the different brightarrow smu ^+mu ^- modes and that there is no significant evidence of non-constant q^2 dependencies, which would indicate the presence of a long-distance charm-loop contribution beyond those already included.

Design and development of dynamic Agri‐ontology for IoT interoperability

SummaryIn recent years, the usage and applications of Internet of Things (IoT) have increased exponentially. IoT connects multiple heterogeneous devices like sensors, micro controllers, actuators, smart devices like mobiles, watches, etc. IoT contributes the data produced in the context of data collection, including the domains like military, agriculture, healthcare, etc. The diversity of possible applications at the intersection of the IoT and the web semantics has prompted many research teams to work at the interface between these two disciplines. This makes it possible to collect data and control various objects in transparent way. The challenge lies in the use of this data. Ontologies address this challenge to meet specific data needs in the IoT field. This paper presents the implementation of a dynamic agriculture ontology‐building tool that parses the ontology files to extract full data and update it based on the user needs. The technology is used to create the angular library for parsing the OWL files. The proposed ontology framework would accept user‐defined ontologies and provide an interface for an online updating of the owl files to ensure the interoperability in the agriculture IoT.

Learning-Ability of Discrete-Time Iterative Learning Control Systems with Feedforward

This paper considers the learning-ability for discrete-time iterative learning control (ILC) systems with feedforward. More specifically, the relation between the output realizability and the feedforward matrix is first established. Then, the learning-ability of four ILC systems is considered. It is shown that the proportional type (P-type) update law can only ensure the fully asymptotic learning-ability. By only using the feedforward matrix, a more efficient point-wise P-type update law is developed, which can ensure the fully -step learning-ability, where is the trial length. In the case that the state is measurable and controllable, it is proven that the update law with current state feedback can ensure the fully monotone learning-ability and the fully 2-step learning-ability, respectively. In addition, by only using the output data at the previous trial, a full output feedback update law is proposed, which can respectively ensure the fully 2-step learning-ability and the fully monotonic learning-ability.

Gradient Pursuit Architecture for Reduced Complexity Sparsity Independent CS Recovery

Compressed sensing (CS) tackles the problem of recovering information from measurements acquired at subNyquist rates. Traditional designs based on orthogonal matching pursuit (OMP) are slowed down by its serial nature and high iteration count in noisy acquisitions. Parallel pursuit strategies in the literature are drawn back by their dependence on sparsity prior and hardware complexity. To address these challenges, an improved version of the sparsity independent regularized pursuit (SIRP) algorithm is proposed in this brief that seeks to achieve a better trade-off between hardware resources and recovery speed without significantly impacting reconstruction quality. A pipelined gradient descent inspired least-mean-squares (LMS) architecture is proposed to replace the complex least squares (LS) step in SIRP and incorporates hardware-sharing for the interdependent steps of the algorithm. The proposed design implemented on a Xilinx Virtex Ultrascale device clocks at 143 MHz and reconstructs a 36-sparse signal in <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$185~\mu \text{s}$ </tex-math></inline-formula> which is competitive with state-of-art designs, at significantly lower hardware consumption. Also, an alternate row LMS scheme is introduced in the design requiring no additional hardware resources, reducing the cycles per iteration to improve reconstruction speed by 28% with a slight reduction in the reconstructed signal-to-noise ratio (RSNR) compared to the full row LMS update.

APA Releases Updated Guideline for Treating Eating Disorders

Back to table of contents Next article Clinical & ResearchFull AccessAPA Releases Updated Guideline for Treating Eating DisordersNick ZagorskiNick ZagorskiSearch for more papers by this authorPublished Online:25 Jan 2023https://doi.org/10.1176/appi.pn.2023.02.2.8AbstractThe new practice guideline focuses on evidence-based pharmacological, psychotherapeutic, and other nonpharmacological treatments for eating disorders in adolescents and adults.APA has released an updated practice guideline on how to treat patients with eating disorders— the first full update since 2006.There have been many clinical advances and diagnostic changes related to eating disorders in the past 17 years, noted Laura Fochtmann, M.D., M.B.I., a professor of psychiatry, pharmacological sciences and biomedical informatics at Stony Brook University School of Medicine and the medical editor for APA’s practice guidelines. Fochtmann was also the vice-chair of the writing group for this newest practice guideline.Notably, the publication of DSM-5 in 2013 and DSM-5-TR in 2022 resulted in broader diagnostic criteria for both anorexia nervosa and bulimia nervosa as well as the additions of binge-eating disorder and avoidant/restrictive food intake disorder (ARFID) categories. Binge-eating and avoidant/restrictive food intake disorders are both referenced in the updated guideline: There is a comprehensive section on assessing and treating binge-eating disorder, and there is also information on assessing patients with ARFID, Fochtmann noted. (Due to limited clinical data, there are no specific recommendations for how to treat patients with ARFID.)The fourth edition of APA’s practice guideline for eating disorders includes 16 clinical recommendations or suggestions, depending on the level of scientific evidence. Here are some of the recommendations:Screening for the presence of an eating disorder as part of an initial psychiatric evaluation.Conducting comprehensive patient evaluations, including laboratory tests such as electrocardiograms.Ensuring the treatment plan is patient-centered and culturally sensitive.Setting individualized weight goals for patients with anorexia.Treating patients with anorexia, bulimia, and binge-eating disorders with eating disorder–focused psychotherapy.Including family-based therapy as part of a treatment plan for adolescents with anorexia or bulimia.In addition to the guideline, APA has developed supplemental materials to help both health professionals and patients and families, such as a clinician pocket guide and educational slides. The centerpiece of these resources is an online tool that offers a step-by-step guide on how to assess symptoms and screen patients for a potential eating disorder. This clinical decision tool will be customized for different professionals (for example, psychiatrists, psychologists, and pediatricians) to match their skillsets and the symptoms they might expect when encountering someone with an eating disorder.The development of the online toolkit and other supporting resources was made possible through a grant from the Council of Medical Specialty Societies.The release of this new practice guideline comes at an important juncture for people with eating disorders (“Special Report: Youth With Eating Disorders—Time Is of the Essence in Achieving Remission”). Studies have reported upticks in individuals developing symptoms of and requiring hospitalization for disordered eating since the start of the COVID-19 pandemic in 2020. As noted in the guideline, maintaining a structured plan for meals and snacks is an important component of treatment, and the pandemic disrupted normal routines and increased stress and anxiety.“Early identification and treatment of an eating disorder is critical for achieving positive long-term outcomes,” said Joel Yager, M.D., a professor emeritus of psychiatry at the University of Colorado School of Medicine and the chair of the writing group for all three previous editions of the eating disorder practice guideline. “We hope that this tool will help anyone make an informed diagnosis regardless of their previous experience with eating disorders.” ■“The American Psychiatric Association Practice Guideline for the Treatment of Patients With Eating Disorders, Fourth Edition”Practice Guideline for Treatment of Patients with Eating Disorders. ISSUES NewArchived

Riemannian Stochastic Variance-Reduced Cubic Regularized Newton Method for Submanifold Optimization

We propose a stochastic variance-reduced cubic regularized Newton algorithm to optimize the finite-sum problem over a Riemannian submanifold of the Euclidean space. The proposed algorithm requires a full gradient and Hessian update at the beginning of each epoch while it performs stochastic variance-reduced updates in the iterations within each epoch. The iteration complexity of $$O(\epsilon ^{-3/2})$$ to obtain an $$(\epsilon ,\sqrt{\epsilon })$$ -second-order stationary point, i.e., a point with the Riemannian gradient norm upper bounded by $$\epsilon $$ and minimum eigenvalue of Riemannian Hessian lower bounded by $$-\sqrt{\epsilon }$$ , is established when the manifold is embedded in the Euclidean space. Furthermore, the paper proposes a computationally more appealing modification of the algorithm which only requires an inexact solution of the cubic regularized Newton subproblem with the same iteration complexity. The proposed algorithm is evaluated and compared with three other Riemannian second-order methods over two numerical studies on estimating the inverse scale matrix of the multivariate t-distribution on the manifold of symmetric positive definite matrices and estimating the parameter of a linear classifier on the sphere manifold.

On-Chip Frequency Tuning of Fast Resonant MEMS Scanner

The development and characterisation of a piezoelectric actuated high-frequency MEMS scanning mirror with on-chip frequency tuning capability is reported. The resonant scanner operates at frequencies in excess of 140 kHz, generating scan angles of 10° and 6° for two orthogonal movement modes with 40 V actuation. On-chip frequency tuning is achieved through electrothermal actuators fabricated adjacent to the mirror main suspension. The electrothermal actuators produce a global and local temperature increase which changes the suspension stiffness and therefore the resonant frequency. A resonance frequency tuning range of up to 5.5 kHz is achieved, with tuning dominant on only one of the two orthogonal scan movement modes. This opens the possibility for precise tuning of a 2D Lissajous scan pattern using a single resonant MEMS scanner with dual orthogonal resonant modes producing full frame update rates up to 20 kHz while retaining the full angular range of both resonant movement modes.

Comparison of wave diffraction forces on a surface-piercing body for various free-surface grid update schemes

This study analyzed the difference in wave diffraction force of a surface piercing body according to the grid update scheme of free surface nodes in the time integration process. A two-dimensional fully nonlinear numerical wave tank based on potential flow theory and boundary element method was used for numerical analysis. The MEL (mixed Eulerian–Lagrangian) method was used for free surface node treatment. This method was divided into a semi-Lagrangian approach and a full Lagrangian approach (material node approach).The Runge–Kutta 4th-order integration method was used to integrate the free surface boundary condition temporally. In the internal sub-time step of the time integration process, the frozen coefficient scheme and the full update scheme were used according to the node update scheme, respectively. The vertical diffraction forces of each frequency component for node update schemes were compared. The difference in the 2nd-order vertical forces according to wave frequency, wave steepness, time step interval, and node spacing was investigated. A more precise time-domain numerical analysis method was proposed for high-order external forces in the wave-floating body interaction.

Time evolution of an infinite projected entangled pair state: A gradient tensor update in the tangent space

Time evolution of an infinite 2D many body quantum lattice system can be described by the Suzuki-Trotter decomposition applied to the infinite projected entangled pair state (iPEPS). Each Trotter gate increases the bond dimension of the tensor network, $D$, that has to be truncated back in a way that minimizes a suitable error measure. This paper goes beyond simplified error measures -- like the one used in the full update (FU), the simple update (SU), and their intermediate neighborhood tensor update (NTU) -- and directly maximizes an overlap between the exact iPEPS with the increased bond dimension and the new iPEPS with the truncated one. The optimization is performed in a tangent space of the iPEPS variational manifold. This gradient tensor update (GTU) is benchmarked by a simulation of a sudden quench of a transverse field in the 2D quantum Ising model and the quantum Kibble-Zurek mechanism in the same 2D system.

Evolving multi-label fuzzy classifier

Multi-label classification has attracted much attention in the machine learning community to address the problem of assigning single samples to more than one (not necessarily non-overlapping) class at the same time. We propose an evolving multi-label fuzzy classifier (EFC-ML) which is able to self-adapt and self-evolve its structure with new incoming multi-label samples in an incremental, single-pass manner. It is based on a multi-output Takagi–Sugeno type architecture, where for each class a separate consequent hyper-plane is defined, which yields flexibility for partially approximating the respective classes in a binary [0,1]-regression context. The learning procedure embeds a locally weighted incremental correlation-based algorithm combined with (conventional) recursive fuzzily weighted least squares and Lasso-based regularization. Locality is important to avoid the out-masking effect of single class labels in one or more rules; the correlation-based part ensures that the interrelations between class labels, a specific well-known property in multi-label classification for improved performance, are preserved properly; the Lasso-based regularization reduces the curse of dimensionality effects in the case of a higher number of inputs. Antecedent learning is achieved by product-space clustering and conducted for all class labels together, which yields a single rule base (opposed to related techniques such as one-versus-rest or classifier chaining, achieving multiple different rule bases, one per class), allowing a compact knowledge view and thus enabling better interpretable insights. Furthermore, our approach comes with an online active learning (AL) strategy for updating the classifier on just a (smaller) number of selected samples, which in turn makes the approach applicable for scarcely labelled streams in applications, where the annotation effort is typically expensive. It is based on three essential concepts: novelty content in the antecedent space, uncertainty due to ambiguity in the consequent (output) space and parameter instability reduction, and these in combination with an upper-allowed selection budget (which could be predefined by a user). Our approach was evaluated on several data sets from the MULAN repository and showed significantly improved classification accuracy and average precision trend lines compared to (evolving) one-versus-rest or classifier chaining concepts. A significant result was that, due to the online AL method, a 90% reduction in the number of samples used for classifier updates had little effect on the accumulated accuracy trend lines compared to a full update in most data set cases.

Scaling Effect on the Behaviour and Design of Prestressed Stayed Steel Columns

This study presents the results of a small-scale experimental campaign on prestressed stayed steel columns, subsequent numerical model validation and design guideline development. The majority of previous experimental studies have focused on large-scale systems, which are expensive and can be difficult to perform due to the required specialised experimental set-up, whereas small-scale experiments are less restrictive with both space and experimental set-up requirements. Also, existing design guidelines were developed from a single system scale, so have not been shown to be applicable to changes in geometric scale. Thus, the scaling effect on prestressed stayed steel columns was investigated to promote the use of small-scale experiments in the study of large-scale prestressed stayed steel column systems and update design guidelines for change in geometric scale. A total of 17 prestressed stayed steel columns and a control column with no cross-arms were tested. These tests investigated the symmetric and antisymmetric buckling behaviour as well as the interactive post-buckling phenomenon. These tests were designed to investigate the scaling effect on the behaviour of the system and to determine the optimal prestress level of prestressed stayed steel columns close to the transition point. A numerical model was also validated by the experimental results to perform a full geometric scaling comparison study and update existing design guidelines. It was found that small-scale structures are capable of representing the behaviour of large-scale prestressed stayed steel columns. Furthermore, it was shown that the highest efficiency in terms of the weight of materials is found close to the transition point between symmetric and antisymmetric buckling behaviour. Various scale systems were modelled numerically, and the results compared with existing guidelines, which resulted in low levels of accuracy. Therefore, existing design guidelines were updated using the validated numerical model and shown to yield more accurate results for the L/400 and L/200 imperfection levels.

The multiscale perturbation method for two-phase reservoir flow problems

In this work we formulate and test a new procedure, the Multiscale Perturbation Method for Two-Phase Flows (MPM-2P), for the fast, accurate and naturally parallelizable numerical solution of two-phase, incompressible, immiscible displacement in porous media approximated by an operator splitting method. The proposed procedure is based on domain decomposition and combines the Multiscale Perturbation Method (MPM) [Ali, et al., Appl. Math. and Comput., 387 (2020) pp. 125023] with the Multiscale Robin Coupled Method (MRCM) [Guiraldello, et al., J. Comput. Phys., 355 (2018) pp. 1-21]. When an update of the velocity field is called for by the operator splitting algorithm, the MPM-2P may provide, depending on the magnitude of a dimensionless algorithmic parameter, an accurate and computationally inexpensive approximation for the velocity field by reusing previously computed multiscale basis functions. Thus, a full update of all multiscale basis functions required by the MRCM for the construction of a new velocity field is avoided.There are two main steps in the formulation of the MPM-2P. Initially, for each subdomain one local boundary value problem with trivial Robin boundary conditions is solved (instead of a full set of multiscale basis functions, that would be required by the MRCM). Then, the solution of an inexpensive interface problem provides the velocity field on the skeleton of the decomposition of the domain. The resulting approximation for the velocity field is obtained by downscaling.We consider challenging two-phase flow problems, with high-contrast permeability fields and water-oil finger growth in homogeneous media. Our numerical experiments show that the use of the MPM-2P gives exceptional speed-up - almost 90% of reduction in computational cost - of two-phase flow simulations. Hundreds of MRCM solutions can be replaced by inexpensive MPM-2P solutions, and water breakthrough can be simulated with very few updates of the MRCM set of multiscale basis functions.

Evidence-Based Challenges to the Continued Recommendation and Use of Peroxidatively-Susceptible Polyunsaturated Fatty Acid-Rich Culinary Oils for High-Temperature Frying Practises: Experimental Revelations Focused on Toxic Aldehydic Lipid Oxidation Products.

In this manuscript, a series of research reports focused on dietary lipid oxidation products (LOPs), their toxicities and adverse health effects are critically reviewed in order to present a challenge to the mindset supporting, or strongly supporting, the notion that polyunsaturated fatty acid-laden frying oils are “safe” to use for high-temperature frying practises. The generation, physiological fates, and toxicities of less commonly known or documented LOPs, such as epoxy-fatty acids, are also considered. Primarily, an introduction to the sequential autocatalytic peroxidative degradation of unsaturated fatty acids (UFAs) occurring during frying episodes is described, as are the potential adverse health effects posed by the dietary consumption of aldehydic and other LOP toxins formed. In continuance, statistics on the dietary consumption of fried foods by humans are reviewed, with a special consideration of French fries. Subsequently, estimates of human dietary aldehyde intake are critically explored, which unfortunately are limited to acrolein and other lower homologues such as acetaldehyde and formaldehyde. However, a full update on estimates of quantities derived from fried food sources is provided here. Further items reviewed include the biochemical reactivities, metabolism and volatilities of aldehydic LOPs (the latter of which is of critical importance regarding the adverse health effects mediated by the inhalation of cooking/frying oil fumes); their toxicological actions, including sections focussed on governmental health authority tolerable daily intakes, delivery methods and routes employed for assessing such effects in animal model systems, along with problems encountered with the Cramer classification of such toxins. The mutagenicities, genotoxicities, and carcinogenic potential of aldehydes are then reviewed in some detail, and following this the physiological concentrations of aldehydes and their likely dietary sources are considered. Finally, conclusions from this study are drawn, with special reference to requirements for (1) the establishment of tolerable daily intake (TDI) values for a much wider range of aldehydic LOPs, and (2) the performance of future nutritional and epidemiological trials to explore associations between their dietary intake and the incidence and severity of non-communicable chronic diseases (NCDs).

Dynamic Complexity of Parity Exists Queries

Given a graph whose nodes may be coloured red, the parity of the number of red nodes can easily be maintained with first-order update rules in the dynamic complexity framework DynFO of Patnaik and Immerman. Can this be generalised to other or even all queries that are definable in first-order logic extended by parity quantifiers? We consider the query that asks whether the number of nodes that have an edge to a red node is odd. Already this simple query of quantifier structure parity-exists is a major roadblock for dynamically capturing extensions of first-order logic. We show that this query cannot be maintained with quantifier-free first-order update rules, and that variants induce a hierarchy for such update rules with respect to the arity of the maintained auxiliary relations. Towards maintaining the query with full first-order update rules, it is shown that degree-restricted variants can be maintained.

Sustainable manufacturing, maintenance policies, prognostics and health management: A literature review

The increasing complexity of industrial processes, the continuing search for higher profits, and increasingly demanding production constraints call for the implementation of a proactive and sustainable maintenance policy. Adapting maintenance policies that integrate the concepts and obligations of so-called sustainable development is a real challenge for companies. This can concern proactive maintenance operations aimed at providing a balance in the social dimension as well as the environmental and economic dimensions. Such a policy requires the introduction of substantial upstream analysis and the establishment of tools to be able to validate process performance continuity. Consequently, and in an Industry 4.0 context, being able to anticipate a system breakdown based on the estimation of its degradation while proposing a time window for a maintenance intervention has become essential. This anticipation aims to avoid failure situations with particularly significant impacts. Approaches and methods for prognostics and health management provide many answers. This paper provides a full update on the various indicators and methods that may respond to the proposed theme. The presentation of knowledge-based methods and data analysis will guide the reader through the research process.

Time evolution of an infinite projected entangled pair state: Neighborhood tensor update

The simple update (SU) and full update (FU) are the two paradigmatic time evolution algorithms for a tensor network known as the infinite projected entangled pair state (iPEPS). They differ by an error measure that is either, respectively, local or takes into account full infinite tensor environment. In this paper we test an intermediate neighborhood tensor update (NTU) accounting for the nearest neighbor environment. This small environment can be contracted exactly in a parallelizable way. It provides an error measure that is Hermitian and non-negative down to machine precision. In the 2D quantum Ising model NTU is shown to yield stable unitary time evolution following a sudden quench. It also yields accurate thermal states despite correlation lengths that reach up to 20 lattice sites. The latter simulations were performed with a manifestly Hermitian purification of a thermal state. Both were performed with reduced tensors that do not include physical (and ancilla) indices. This modification naturally leads to two other schemes: a local SVD update (SVDU) and a full tensor update (FTU) being a variant of FU.

LOCATE: a prospective evaluation of the value of Leveraging Ongoing Citation Acquisition Techniques for living Evidence syntheses

BackgroundLiving systematic reviews (LSRs) can expedite evidence synthesis by incorporating new evidence in real time. However, the methods needed to identify new studies in a timely manner are not well established.ObjectivesTo explore the value of complementary search approaches in terms of search performance, impact on results and conclusions, screening workload, and feasibility compared to the reference standard.MethodsWe developed three complementary search approaches for a systematic review on treatments for bronchiolitis: Automated Full Search, PubMed Similar Articles, and Scopus Citing References. These were automated to retrieve results monthly; pairs of reviewers screened the records and commented on feasibility. After 1 year, we conducted a full update search (reference standard). For each complementary approach, we compared search performance (proportion missed, number needed to read [NNR]) and reviewer workload (number of records screened, time required) to the reference standard. We investigated the impact of the new trials on the effect estimate and certainty of evidence for the primary outcomes. We summarized comments about feasibility.ResultsVia the reference standard, reviewers screened 505 titles/abstracts, 24 full texts, and identified four new trials (NNR 127; 12.4 h). Of the complementary approaches, only the Automated Full Search located all four trials; these were located 6 to 12 months sooner than via the reference standard but did not alter the results nor certainty in the evidence. The Automated Full Search was the most resource-intensive approach (816 records screened; NNR 204; 17.1 h). The PubMed Similar Articles and Scopus Citing References approaches located far fewer records (452 and 244, respectively), thereby requiring less screening time (9.4 and 5.2 h); however, each approach located only one of the four new trials. Reviewers found it feasible and convenient to conduct monthly screening for searches of this yield (median 15–65 records/month).ConclusionsThe Automated Full Search was the most resource-intensive approach, but also the only to locate all of the newly published trials. Although the monthly screening time for the PubMed Similar Articles and Scopus Citing Articles was far less, most relevant records were missed. These approaches were feasible to integrate into reviewer work processes.Systematic review registrationOpen Science Framework. https://doi.org/10.17605/OSF.IO/6M28H.