bluuebunny/crossref_metadata_2025 huggingface dataset:
Impact of emotional competence on physicians’ clinical reasoning: a scoping review protocol
Authors: Joly Louise , Bardiau Marjorie , Nunes de Sousa Alexandra , Bayot Marie , Dory Valérie , Lenoir Anne-Laure
Published: June 2023

Introduction

Clinical reasoning (CR) is a key competence for physicians and a major source of damaging medical errors. Many strategies have been explored to improve CR quality, most of them based on knowledge enhancement, cognitive debiasing and the use of analytical reasoning. If increasing knowledge and fostering analytical reasoning have shown some positive results, the impact of debiasing is however mixed. Debiasing and promoting analytical reasoning have also been criticised for their lack of pragmatism. Alternative means of increasing CR quality are therefore still needed. Because emotions are known to influence the quality of reasoning in general, we hypothesised that emotional competence (EC) could improve physicians’ CR. EC refers to the ability to identify, understand, express, regulate and use emotions. The influence of EC on CR remains unclear. This article presents a scoping review protocol, the aim of which will be to describe the current state of knowledge concerning the influence of EC on physicians’ CR, the type of available literature and finally the different methods used to examine the link between EC and CR.

Method and analysis

The population of interest is physicians and medical students. EC will be explored according to the model of Mikolajczaket al, describing five major components of EC (identify, understand, express, regulate and use emotions). The concept of CR will include terms related to its processes and outcomes. Context will include real or simulated clinical situations. The search for primary sources and reviews will be conducted in MEDLINE (via Ovid), Scopus and PsycINFO. The grey literature will be searched in the references of included articles and in OpenGrey. Study selection and data extraction will be conducted using the Covidence software. Search and inclusion results will be reported using the Preferred Reporting Items for Systematic Reviews and Meta-analyses extension for scoping review model (PRISMA-ScR).

Ethics and dissemination

There are no ethical or safety concerns regarding this review.

Registration details

OSF Registration DOI:https://doi.org/10.17605/OSF.IO/GM7YD.
Patient engagement in the development and delivery of healthcare services: a systematic scoping review
Authors: Sagen Joachim Støren , Smedslund Geir , Simonsen Ann Elisabeth , Habberstad Andreas , Kjeken Ingvild , Dagfinrud Hanne , Moe Rikke Helene
Published: June 2023

Background

Patient engagement (PE) is required to improve future healthcare services. PE in the development and delivery of healthcare services is likely to be complex but is scarcely described.

Objectives

The objective of this scoping review was to summarise primary studies on mesolevel PE regarding structure, process and outcomes. More specifically, the aim was to explore barriers and facilitators to successful PE, how persons are engaged in the process and summarise reported consequences.

Method

A systematic scoping review was conducted, searching the MEDLINE, EMBASE, Cochrane and PsycINFO databases. Primary studies, published between 7 July 2005 and 4 October 2022, were considered for inclusion. Two reviewers extracted data about PE (eg, attributes of PE settings, facilitators and barriers, and outcomes to PE) and the first author coded the extracted data into structural, processual and outcome themes.

Results

Of 8588 identified records, 37 studies were eligible. Most of the included studies were conducted in Europe (n=19; 51%) and North America (n=13; 35%). Structures that ensure sufficient stakeholder representativeness and PE knowledge through education may facilitate the PE process further, regardless of the environmental setting. Interpersonal relationships with uneven power dynamics were reported as noteworthy processual barriers to meaningful PE, while clearly described roles and tasks were reported as important facilitators. In contrast to hard outcomes with operationalised PE effects, the most noteworthy outcomes of PE were reported as soft processual consequences such as patient representatives improving their self-esteem and feeling valued.

Conclusions

Unfortunately, there is a dearth of studies exploring hard and operationalised PE outcomes on healthcare services and patients receiving healthcare. The PE process may be facilitated by dedicated finances to PE education and by ensuring sufficient stakeholder representativeness.
Comparison of mathematically arterialised venous blood gas sampling with arterial, capillary, and venous sampling in adult patients with hypercapnic respiratory failure: a single-centre longitudinal cohort study
Authors: Davies Michael Gordon , Wozniak Dariusz Rafal , Quinnell Timothy George , Palas Earl , George Susan , Huang Yingchang , Jayasekara Ruwanthi , Stoneman Victoria , Smith Ian Edward , Thomsen Lars Pilegaard , Rees Stephen Edward
Published: June 2023

Background

Accurate arterial blood gas (ABG) analysis is essential in the management of patients with hypercapnic respiratory failure, but repeated sampling requires technical expertise and is painful. Missed sampling is common and has a negative impact on patient care. A newer venous to arterial conversion method (v-TAC, Roche) uses mathematical models of acid–base chemistry, a venous blood gas sample and peripheral blood oxygen saturation to calculate arterial acid–base status. It has the potential to replace routine ABG sampling for selected patient cohorts. The aim of this study was to compare v-TAC with ABG, capillary and venous sampling in a patient cohort referred to start non-invasive ventilation (NIV).

Methods

Recruited patients underwent near simultaneous ABG, capillary blood gas (CBG) and venous blood gas (VBG) sampling at day 0, and up to two further occasions (day 1 NIV and discharge). The primary outcome was the reliability of v-TAC sampling compared with ABG, via Bland-Altman analysis, to identify respiratory failure (via PaCO2) and to detect changes in PaCO2in response to NIV. Secondary outcomes included agreements with pH, sampling success rates and pain.

Results

The agreement between ABG and v-TAC/venous PaCO2was assessed for 119 matched sampling episodes and 105 between ABG and CBG. Close agreement was shown for v-TAC (mean difference (SD) 0.01 (0.5) kPa), but not for CBG (−0.75 (0.69) kPa) or VBG (+1.00 (0.90) kPa). Longitudinal data for 32 patients started on NIV showed the closest agreement for ABG and v-TAC (R2=0.61). v-TAC sampling had the highest first-time success rate (88%) and was less painful than arterial (p<0.0001).

Conclusion

Mathematical arterialisation of venous samples was easier to obtain and less painful than ABG sampling. Results showed close agreement for PaCO2 and pH and tracked well longitudinally such that the v-TAC method could replace routine ABG testing to recognise and monitor patients with hypercapnic respiratory failure.

Trial registration number

NCT04072848;www.clinicaltrials.gov
Tobacco companies, corporate social responsibility and the use of third-party awards: a framing analysis
Authors: Marshman Briony , Wolf Katharina , McCausland Kahlia , Daube Mike , Jancey Jonine
Published: June 2023

Objective

Corporate social responsibility activities, such as third-party awards, provide an opportunity for tobacco companies (TCs) to promote themselves as socially, economically and environmentally responsible organisations. This study aimed to determine how TCs are using third-party awards to frame themselves and their core activities via company-controlled communication channels.

Methods

TC-owned media coverage promoting third-party awards was identified from company-owned media channels, including websites, reports, press releases and Twitter. Using framing theory and thematic analysis, frames and broader themes were identified using a process of inductive coding.

Results

TC-produced media content promoting third-party awards framed the companies as socially and environmentally responsible organisations, which excel at business and are innovative and transformative. Dominant frames identified included excellent workplace culture, championing diversity and inclusion and action on the environment.

Conclusion

TCs are capitalising on the perceived credibility and objectivity of third-party awards using these ‘honours’ as a promotional strategy to justify their continuing role in society and enhance their perceived legitimacy in relation to claims of ethical and responsible behaviour. The results of this study have implications for tobacco control advocacy, as continuing to allow the promotion of these awards appears to contravene or conflict with the WHO Framework Convention on Tobacco Control.
Cheakamus basalt lavas, British Columbia: a Pleistocene record of rapid, continuous eruption within a mountainous drainage system
Authors: Borch Annie , Russell James K. , Barendregt René W.
Published: June 2023

The Cheakamus basalts are a voluminous (1.65 km3) set of Late Pleistocene, valley-filling lavas erupted from a vent situated near present-day Conflict Lake, in the alpine Callaghan Valley near Whistler, British Columbia. Geochemical and petrographic properties suggest these olivine–plagioclase porphyritic basalt lavas derive from a single batch of magma affected by minor sorting of phenocrysts and xenocrystic plagioclase. Thirty-four sites sampled for paleomagnetic directions record a mean pole direction of 345.2°/73.0° (α95 = 1.3°) and show no statistical variation nor drift with stratigraphic position. These data suggest that the Cheakamus basalt lavas were emplaced in a single paleomagnetic moment—a period of time significantly less than 2000 years. 40Ar/39Ar geochronometry on three lava samples returns a weighted mean age estimate of 15.95 ± 7.9 ka (2σ) and field evidence, including well-glaciated lava flow surfaces overlain by till, indicate the eruption coincided with the early stages of the Fraser glaciation (∼20–18 ka). The lavas preserve features indicative of a landscape hosting diverse and dynamic paleoenvironments. Subaerial eruption of basalt lava filled an ice-free Callaghan Creek drainage system before inundating and damming of the paleo-Cheakamus River creating an upstream rising body of water. Periodic overtopping of the lava dam resulted in syn-eruptive intermittent flooding and overtopping of lavas expressed by discontinuous lenses of interflow sediment. Rare instances of enigmatic cooling columns may also indicate localized ice contact with glaciers that partially filled the Cheakamus Valley. The displacement of the modern Cheakamus River and the long-term damming and formation of Callaghan and Conflict lakes remain direct indicators of the control and impact these basaltic eruptions have had on the geomorphology of the present-day Callaghan and Cheakamus valleys.
Electron impact excitation of Sn$$^{2+}$$
Authors: Umer Haadi , Bray Igor , Fursa Dmitry V.
Published: June 2023

The relativistic convergent close-coupling method is applied to calculate integrated cross sections for the electron-impact excitation of Sn$$^{2+}$$

2
+

. Cross sections have been calculated for excitations to all states in the 5s5p, $$5p^2$$

5

p
2

, 5s6s and 5s5d manifolds from the ground state for projectile electron energies ranging from 24 eV to 500 eV. The total discrete inelastic scattering cross section is also presented.

Graphical abstract
Testing of the siderophore deferoxamine amended in hydrogels for the cleaning of iron corrosion
Authors: Cuvillier Luana , Passaretti Arianna , Guilminot Elodie , Joseph Edith
Published: June 2023

Bioderived alternatives to commonly used complexing agents for the cleaning of iron artworks are sought for their natural origin and better biodegradability. Indeed, complexing agents currently used for the removal of undesired corrosion products from iron artworks can be difficult to control and their environmental impact is often overlooked. This paper studies the use of siderophores, focusing on the ability of one of them, deferoxamine, to be employed as an active agent loaded in polysaccharides hydrogels, on corrosion phases. Preliminary tests were conducted on artificially aged steel samples and further studies were performed on naturally corroded steel to assess the most performing application parameters. Long-term behavior of cleaned surface was assessed. Cleaning outcomes were compared with those obtainable with disodium ethylenediaminetetraacetic acid using optical microscopy, colorimetry and atomic absorption spectroscopy as well as Infrared and Raman micro-spectroscopies. Among the different gelling agents evaluated, agar applied when hot and gellan gum prepared at room temperature were the most effective gel formulations and agar left few residues over the treated surfaces. The protocol was then tested on altered steel artifacts belonging to heritage institutions in France. Encouraging outcomes in the removal of iron corrosion phases with green approaches are here presented.

Graphical abstract
Minimizing Maximum Unmet Demand by Transportations Between Adjacent Nodes Characterized by Supplies and Demands
Authors: Asano Tetsuo
Published: June 2023

Suppose we are given a graph with nodes characterized by amounts of supplies and demands of multiple commodities. The amounts of commodities stored at nodes (supplies) are given by positive numbers while those of demands at nodes are given by negative numbers. To meet demands we send commodities from nodes to neighbors by using vehicles, one at each node, with some loading capacity moving to and from neighbors. In this paper we adopt a one-way transportation model in which we just send commodities from a node to one of its neighbors along an edge.

When we choose one neighbor at each node, we have a set of trips which naturally define a graph such that each connected component has at most one cycle, which is known as a pseudoforest. We present a linear-time algorithm for deciding whether there is a set of trips that meet all demands using one-way multi-commodity transportations on a pseudoforest with node degrees bounded by a constant.

Using the algorithm, we first present an efficient algorithm for finding an optimal set of one-way one-commodity trips that minimize the maximum unmet demand on a pseudoforest, and then extend the idea to a multi-commodity problem on a pseudoforest with node degrees bounded by a constant.
Comparison between some machine learning algorithms on predicting the spectra of quark–anti-quark bound states
Authors: Nahool T. A. , Ismail Atef , Elshamndy Samah K. , Yasser A. M.
Published: June 2023

This study is devoted to investigate the implementation of machine learning methodologies in the prediction of Quark–anti-Quark bound state spectrum. Predictions are produced by using variety of machine learning (ML) approaches, such as ridge regression, random forest regression, linear regression and K-nearest neighbors regression methods. The forecasts are then evaluated and contrasted in order to determine the optimal performance. Furthermore, systematic comparison of the considered ML methods in terms of percentage of performance is done. Each of the four strategies yielded comparable results. With accuracy of 99%, the ridge regression model exhibited the highest level of predictive performance.
A High-Efficiency FPGA-Based ORB Feature Matching System
Authors: Huang Bai-Cheng , Zhang Yan-Jun
Published: June 2023

Feature extraction and matching are the basic procedures of the so-called Visual Odometer (VO), Simultaneous Localization and Mapping (SLAM) and many other image processing algorithms. Oriented features from accelerated segment test (FAST) and rotated binary robust independent elementary features (ORB) algorithm are widely used since they are computationally faster. In this paper, we proposed a method to generate a value for a feature, the value is called signature. In the matching step, we only compute Hamming distances of descriptors with the same signatures. Hence, the matching time is shortened. Compared with the original ORB algorithm, features to be matched dropped 69.63% on TUM datasets and 85.7% on VGG datasets by adopting our strategy. In addition, the precision is above 85% on both VGG and TUM datasets. We design a customized hardware architecture for ORB feature extraction and matching based on the proposed method. The hardware structure is implemented on Xilinx ZCU102 evaluation board. The clock frequency is set to 150[Formula: see text]MHz. Our Field Programmable Gate Arrays (FPGA) system achieves 193[Formula: see text]fps on [Formula: see text] images with 1984 features on average and 314[Formula: see text]fps on [Formula: see text] images with 700 features on average, which is more efficient compared to the state-of-the-art works.
Characterization of Dynamic Mechanical Properties of Viscoelastic Damper Based on Physics-Constrained Data-Driven Approach
Authors: Li Qiang-Qiang , Xu Zhao-Dong , Dong Yao-Rong , He Zhen-Hua , Yan Xiao , Wang Bin , Guo Ying-Qing
Published: June 2023

Traditional physics-based mathematical models of viscoelastic (VE) damper often exhibit different degrees of prediction errors under complex working conditions, whereas data-driven approaches have shown significant potential for overcoming such problems, and have not been introduced into any study to describe the dynamic mechanical properties of VE damper. In this paper, the architecture of microsphere model is adopted to represent the spatial distribution of molecular chain structure of VE damping material, which is categorized into free chains and elastic chains. Then, the physics-informed neural network surrogates are introduced to describe the statistical stress–strain behaviors of free chains and elastic chains. Finally, by constructing the physics-constrained loss function based on the combination of physics-based model and data-driven model, a physics-constrained data-driven model is proposed to characterize the dynamic mechanical behaviors of VE damper used for structure vibration control. Based on the existing experimental data, the prediction ability and robustness of the proposed model are comparatively verified, the results reveal that the proposed model can accurately reflect the stiffness and energy dissipation of VE damper under different ambient temperatures, excitation frequencies, and deformation conditions. This study proves the potential of physics-informed neural network theory in characterizing the complex mechanical behaviors of VE damper.
An Efficient Finite Element Method and Error Analysis Based on Dimension Reduction Scheme for the Fourth-Order Elliptic Eigenvalue Problems in a Circular Domain
Authors: Wang Caiqun , Tan Ting , An Jing
Published: June 2023

In this paper, we propose an effective finite element method for the fourth order elliptic eigenvalue problems in a circular domain. First, by using polar coordinates transformation and the orthogonal property of Fourier basis functions, the original problem is turned into a series of equivalent one-dimensional eigenvalue problems. Second, according to the properties of Laplace operator in polar coordinate, we deduce the polar conditions and introduce suitable weighted Sobolev space. Based on the polar conditions and weighted Sobolev space, we establish the weak form and the corresponding discrete form. Third, we prove the error estimates of approximation eigenvalues and eigenvectors by means of the spectral theory of compact operators for each one-dimensional eigenvalue system. Finally, we provide some numerical experiments to show the validity of the algorithm and the correctness of the theoretical results.
Tensor Completion with Provable Consistency and Fairness Guarantees for Recommender Systems
Authors: Nguyen Tung , Uhlmann Jeffrey
Published: June 2023

We introduce a new consistency-based approach for defining and solving nonnegative/positive matrix and tensor completion problems. The novelty of the framework is that instead of artificially making the problem well-posed in the form of an application-arbitrary optimization problem, e.g., minimizing a bulk structural measure such as rank or norm, we show that a single property/constraint: preserving unit-scale consistency, guarantees the existence of both a solution and, under relatively weak support assumptions, uniqueness. The framework and solution algorithms also generalize directly to tensors of arbitrary dimensions while maintaining computational complexity that is linear in problem size for fixed dimensiond. In the context of recommender system (RS) applications, we prove that tworeasonableproperties that should be expected to hold for any solution to the RS problem are sufficient to permit uniqueness guarantees to be established within our framework. This is remarkable because it obviates the need for heuristic-based statistical or AI methods despite what appear to be distinctly human/subjective variables at the heart of the problem. Key theoretical contributions include a general unit-consistent tensor-completion framework with proofs of its properties, e.g., consensus-order and fairness, and algorithms with optimal runtime and space complexities, e.g.,O(1) term-completion with preprocessing complexity that is linear in the number of known terms of the matrix/tensor. From a practical perspective, the seamless ability of the framework to generalize to exploit high-dimensional structural relationships among key state variables, e.g., user and product attributes, offers a means for extracting significantly more information than is possible for alternative methods that cannot generalize beyond direct user-product relationships. Finally, we propose our consensus ordering property as an admissibility criterion for any proposed RS method.
Recent Advances in Natural Language Processing via Large Pre-trained Language Models: A Survey
Authors: Min Bonan , Ross Hayley , Sulem Elior , Veyseh Amir Pouran Ben , Nguyen Thien Huu , Sainz Oscar , Agirre Eneko , Heintz Ilana , Roth Dan
Published: June 2023

Large, pre-trained language models (PLMs) such as BERT and GPT have drastically changed the Natural Language Processing (NLP) field. For numerous NLP tasks, approaches leveraging PLMs have achieved state-of-the-art performance. The key idea is to learn a generic, latent representation of language from a generic task once, then share it across disparate NLP tasks. Language modeling serves as the generic task, one with abundant self-supervised text available for extensive training. This article presents the key fundamental concepts of PLM architectures and a comprehensive view of the shift to PLM-driven NLP techniques. It surveys work applying the pre-training then fine-tuning, prompting, and text generation approaches. In addition, it discusses PLM limitations and suggested directions for future research.
Echoes of Intelligence
Authors: Videla Alvaro
Published: June 2023

We are now in the presence of a new medium disguised as good old text, but that text has been generated by an LLM, without authorial intention—an aspect that, if known beforehand, completely changes the expectations and response a human should have from a piece of text. Should our interpretation capabilities be engaged? If yes, under what conditions? The rules of the language game should be spelled out; they should not be passed over in silence.
The Design Space of Kirchhoff Rods
Authors: Hafner Christian , Bickel Bernd
Published: June 2023

The Kirchhoff rod model describes the bending and twisting of slender elastic rods in three dimensions and has been widely studied to enable the prediction of how a rod will deform, given its geometry and boundary conditions. In this work, we study a number of inverse problems with the goal of computing the geometry of a straight rod that will automatically deform to match a curved target shape after attaching its endpoints to a support structure. Our solution lets us finely control the static equilibrium state of a rod by varying the cross-sectional profiles along its length.

We also show that the set of physically realizable equilibrium states admits a concise geometric description in terms of linear line complexes, which leads to very efficient computational design algorithms. Implemented in an interactive software tool, they allow us to convert three-dimensional hand-drawn spline curves to elastic rods and give feedback about the feasibility and practicality of a design in real time. We demonstrate the efficacy of our method by designing and manufacturing several physical prototypes with applications to interior design and soft robotics.
Dynamic Bin Packing with Predictions
Authors: Liu Mozhengfu , Tang Xueyan
Published: June 2023

The MinUsageTime Dynamic Bin Packing (DBP) problem aims to minimize the accumulated bin usage time for packing a sequence of items into bins. It is often used to model job dispatching for optimizing the busy time of servers, where the items and bins match the jobs and servers respectively. It is known that the competitiveness of MinUsageTime DBP has tight bounds of Θ(√, log μ) and Θ(μ) in the clairvoyant and non-clairvoyant settings respectively, where μ is the max/min duration ratio of all items. In practice, the information about items' durations (i.e., job lengths) obtained via predictions is usually prone to errors. In this paper, we study the MinUsageTime DBP problem with predictions of items' durations. We find that an existing O(√ log μ)-competitive clairvoyant algorithm, if using predicted durations rather than real durations for packing, does not provide any bounded performance guarantee when the predictions are adversarially bad. We develop a new online algorithm with a competitive ratio of {O(∈2 √ log(∈2 μ)}, O(μ) (where ε is the maximum multiplicative error of prediction among all items), achieving O(√ log μ) consistency (competitiveness under perfect predictions where ∈ = 1) and O(μ) robustness (competitiveness under terrible predictions), both of which are asymptotically optimal.
Each at its Own Pace: Third-Party Dependency and Centralization Around the World
Authors: Kumar Rashna , Asif Sana , Lee Elise , Bustamante Fabián E.
Published: June 2023

We describe the results of a large-scale study of third-party dependencies around the world based on regional top-500 popular websites accessed from vantage points in 50 countries, together covering all inhabited continents. This broad perspective shows that dependencies on a third-party DNS, CDN or CA provider vary widely around the world. The critical dependencies of websites -- where the site depends on a single third-party provider -- are equally spread. Even more concerning, these differences persist a year later with increasing dependencies, particularly for DNS and CDNs. We briefly explore various factors that may help explain the differences and similarities in degrees of third-party dependency across countries, including economic conditions, Internet development, economic trading partners, categories, home countries, and traffic skewness of the country's top-500 sites.
Malcolm: Multi-agent Learning for Cooperative Load Management at Rack Scale
Authors: Hossein Abbasi Abyaneh Ali , Liao Maizi , Zahedi Seyed Majid
Published: June 2023

We consider the problem of balancing the load among servers in dense racks for microsecond-scale workloads. To balance the load in such settings, tens of millions of scheduling decisions have to be made per second. Achieving this throughput while providing microsecond-scale latency is extremely challenging. To address this challenge, we design a fully decentralized load-balancing framework, which allows servers to collectively balance the load in the system. We model the interactions among servers as a cooperative stochastic game. To find the game's parametric Nash equilibrium, we design and implement a decentralized algorithm based on multi-agent-learning theory. We empirically show that our proposed algorithm is adaptive and scalable while outperforming state-of-the art alternatives. The full paper of this abstract can be found at https://doi.org/10.1145/3570611.
Network Monitoring on Multi-Pipe Switches
Authors: Chiesa Marco , Verdi Fábio L.
Published: June 2023

Programmable switches have been widely used to design network monitoring solutions that operate in the fast data-plane level, e.g., detecting heavy hitters, super-spreaders, computing flow size distributions and their entropy. Existing works assume packets access the same memory region in a switch. However, high-speed ASIC switches deploy multiple packet processing pipes, each equipped with its own independent memory.

In this work, we first quantify the accuracy degradation due to splitting a monitoring data structure across multiple pipes (e.g., up to 3000x worse flow-size estimation average error). We then present PipeCache, a system that adapts existing data-plane mechanisms to multi-pipe switches by storing monitoring information for a traffic class into a single pipe. PipeCache stores monitoring information into a cache and piggybacks this information onto existing data packets to the correct pipe. Our implementation shows a 2-20x memory reduction to achieve an accuracy similar to single-pipe deployments.
On the Stochastic and Asymptotic Improvement of First-Come First-Served and Nudge Scheduling
Authors: Van Houdt Benny
Published: June 2023

Recently it was shown that, contrary to expectations, the First-Come-First-Served (FCFS) scheduling algorithm can be stochastically improved upon by a scheduling algorithm called Nudge for light-tailed job size distributions. Nudge partitions jobs into 4 types based on their size, say small, medium, large and huge jobs. Nudge operates identical to FCFS, except that whenever a small job arrives that finds a large job waiting at the back of the queue, Nudge swaps the small job with the large one unless the large job was already involved in an earlier swap.

In this paper, we show that FCFS can be stochastically improved upon under far weaker conditions. We consider a system with 2 job types and limited swapping between type-1 and type-2 jobs, but where a type-1 job is not necessarily smaller than a type-2 job. More specifically, we introduce and study the Nudge-K scheduling algorithm which allows type-1 jobs to be swapped with up to K type-2 jobs waiting at the back of the queue, while type-2 jobs can be involved in at most one swap. We present an explicit expression for the response time distribution under Nudge-K when both job types follow a phase-type distribution. Regarding the asymptotic tail improvement ratio (ATIR), we derive a simple expression for the ATIR, as well as for the K that maximizes the ATIR. We show that the ATIR is positive and the optimal K tends to infinity in heavy traffic as long as the type-2 jobs are on average longer than the type-1 jobs.
Online Resource Allocation under Horizon Uncertainty
Authors: Balseiro Santiago , Kroer Christian , Kumar Rachitesh
Published: June 2023

We study stochastic online resource allocation: a decision maker needs to allocate limited resources to stochastically-generated sequentially-arriving requests in order to maximize reward. At each time step, requests are drawn independently from a distribution that is unknown to the decision maker. Online resource allocation and its special cases have been studied extensively in the past, but prior results crucially and universally rely on the strong assumption that the total number of requests (the horizon) is known to the decision maker in advance. In many applications, such as revenue management and online advertising, the number of requests can vary widely because of fluctuations in demand or user traffic intensity. In this work, we develop online algorithms that are robust to horizon uncertainty. In sharp contrast to the known-horizon setting, no algorithm can achieve even a constant asymptotic competitive ratio that is independent of the horizon uncertainty. We introduce a novel generalization of dual mirror descent which allows the decision maker to specify a schedule of time-varying target consumption rates, and prove corresponding performance guarantees. We go on to give a fast algorithm for computing a schedule of target consumption rates that leads to near-optimal performance in the unknown-horizon setting. In particular, our competitive ratio attains the optimal rate of growth (up to logarithmic factors) as the horizon uncertainty grows large. Finally, we also provide a way to incorporate machine-learned predictions about the horizon which interpolates between the known and unknown horizon settings.
Robust Multi-Agent Bandits Over Undirected Graphs
Authors: Vial Daniel , Shakkottai Sanjay , Srikant R.
Published: June 2023

We consider a multi-agent multi-armed bandit setting in which n honest agents collaborate over a network to minimize regret but m malicious agents can disrupt learning arbitrarily. Assuming the network is the complete graph, existing algorithms incur O((m + K/n) log (T) / Δ) regret in this setting, where K is the number of arms and Δ is the arm gap. For m << K, this improves over the single-agent baseline regret of O(K log(T)/Δ). In this work, we show the situation is murkier beyond the case of a complete graph. In particular, we provide an instance for which honest agents using the state-of-the-art algorithm suffer (nearly) linear regret until time is doubly exponential in n. In light of this negative result, we propose a new algorithm for which the i-th agent has regret O((dmal (i) + K/n) log(T)/Δ) on any connected and undirected graph, where dmal (i) is the number of i's neighbors who are malicious. Thus, we generalize existing regret bounds beyond the complete graph and show the effect of malicious agents is entirely local.
Streaming Algorithms for Constrained Submodular Maximization
Authors: Cui Shuang , Han Kai , Tang Jing , Huang He , Li Xueying , Li Zhiyu
Published: June 2023

Due to the pervasive "diminishing returns" property appeared in data-intensive applications, submodular maximization problems have aroused great attention from both the machine learning community and the computation theory community. During the last decades, a lot of algorithms have been proposed for submodular maximization subject to various constraints [4, 6, 8], and these algorithms can be used in numerous applications including sensor placement [9], clustering [5], network design [13], and so on.

The existing algorithms for submodular maximization can be roughly classified into offline algorithms and streaming algorithms; the former assume full access to the whole dataset at any time (e.g.,[4, 10]), while the latter only require an amount of space which is nearly linear in the maximum size of a feasible solution (e.g., [1, 7]). Apparently, streaming algorithms are more useful in big data applications, as the whole data set is usually too large to be fit into memory in practice. However, compared to the offline algorithms, the existing streaming algorithms for submodular maximization generally have weaker capabilities in that they handle more limited problem constraints or achieve weaker performance bounds, due to the more stringent requirements under the streaming setting. Another classification of the existing algorithms is that they concentrate on either monotone or non-monotone submodular functions. As monotone submodular function is a special case of non-monotone submodular function, we will concentrate on non-monotone submodular maximization in this paper.
From the President: Can You Imagine?
Authors: Botte Gerardine G.
Published: June 2023

Can you imagine a world where fertilizer production is thoroughly sustainable and recycled, thus enabling global food access that meets population growth? Where waste is considered a resource and has value; where buildings monitor air and water to keep us safe; where pathogen-destroying coatings are integrated into fabrics and clothing; where sensors are noninvasive, continuously monitoring our health while personalizing and advancing medicine and treatment; where plastics are upcycled; where the manufacture of chemicals and materials is decarbonized, distributed, circular, modular, with a small footprint and multiple processing steps integrated into a single unit that implements alternative energy sources… Can you imagine?
Podcasts of Note - Summer 2023
Authors: Suroviec Alice
Published: June 2023

Summer 2023 Podcasts of Note selected for you by Alice Suroviec
Current and Emerging Electrochemical Approaches for Chemical Manufacturing
Authors: Biddinger Elizabeth J. , Kenis Paul J. A.
Published: June 2023

R&D on electrochemical approaches for chemical manufacturing is experiencing a renaissance, the direct result of society’s desire to reduce greenhouse gas emissions of the chemical industry, aiming to be carbon neutral by 2050. Two such processes have been performed for decades at scale: the chlor-alkali process that produces chlorine from aqueous sodium chloride, and the production of adiponitrile, an intermediate in the production nylon-6,6. Water electrolysis for hydrogen production is also being deployed now at scale. This report summarizes some of the many efforts to electrify chemical conversions, often using renewable feeds like water, CO2, and biomass-derived adducts, or waste-streams from other processes. Beyond efforts to reduce emissions, a very active research community also pursues a broad range of electro-organic conversions, some of which have major advantages over conventional reaction chemistries. Overarching challenges of implementing electrochemical manufacturing approaches are also discussed (e.g., limited familiarity with electrochemical processes in chemical engineering practice, insufficient availability of electrical power, and the variability of various renewable feeds).
Extraterrestrial Electrochemistry - Challenges and Opportunities for Electrolytic in-situ Resource Utilization (ISRU) on Mars
Authors: Sankarasubramanian Shrihari , Chambers Bradley , Wilson Cheyenne
Published: June 2023

The sustained, long-term exploration of other heavenly bodies in the solar system necessitates the development of technological solutions that will free these missions from the constraints of resupply from Earth. Herein, we focus on electrochemical solutions for in-situ resource utilization (ISRU) that will enable “living off the land” on Mars with a particular focus on life-support and fuel production. The constraints imposed by the operational environment and available resources are examined and some existing (demonstrated) electrolysis solutions are discussed. Building on this, knowledge gaps are identified, and a roadmap is proposed for future research focus at the component and device level.
Considerations for Electrochemical Phosphorus Precipitation: A Figures of Merit Approach
Authors: Wolfe Kody D. , Zanganeh Ardavan , Arthur Richard N. , Trembly Jason P. , Daramola Damilola A.
Published: June 2023

Electrochemical phosphorus precipitation (EPP) from wastewater is a promising emerging technology for recovering valuable nutrients. While there are significant advantages of EPP compared to traditional phosphorus recovery, large gaps in reported performance exist between EPP methods and between EPP and industrial methods. Herein we discuss Figures of Merit (FOM) to normalize and report EPP performance at low-to-intermediate technology readiness levels (TRLs). The appropriate use of FOM in electrochemical engineering enables better comparison between technologies, enhanced understanding of electrochemical and mass transport phenomena, and faster scale-up and adoption of nascent technologies.¬ FOM specific to EPP are discussed along with important considerations and adaptations from traditional electrochemical engineering FOM. Importantly, this FOM approach may be adapted for many different electrochemical processes and technologies, aiding in the push toward and adoption of electrification in chemical processing.
Editors’ Choice—Luminescent Oxygen Sensors: Valuable Tools for Spatiotemporal Exploration of Metabolism in In Vitro Systems
Authors: Sodia Tyler Z. , Cash Kevin J.
Published: June 2023

A common biological theme on Earth is the importance of oxygen, regardless of an organism’s metabolic capabilities. This commonality makes the quantification of O2 essential in understanding life as we know it. There are many sensing methods that enable researchers to measure this important analyte, but not all sensors are compatible with every system. This perspective highlights common O2 sensing formats (and recent innovations) with the goal of guiding the reader towards a sensor choice for their desired application. We emphasize the importance of exploring unfamiliar metabolic processes, commercializing new sensors, and establishing collaborations for maximizing innovation and accelerating discovery.
Lipophilic statins inhibit YAP coactivator transcriptional activity in HCC cells through Rho-mediated modulation of actin cytoskeleton
Authors: Benhammou Jihane N. , Qiao Bo , Ko Arthur , Sinnett-Smith James , Pisegna Joseph R. , Rozengurt Enrique
Published: June 2023

Statins are widely used for the treatment of cardiovascular diseases. Recently, their use has been associated with a decrease in the incidence of hepatocellular carcinoma (HCC); however, their mechanism(s) has remained elusive. In this study, we delineate the mechanism by which statins affect the Yes-associated protein (YAP), which has emerged as a key oncogenic pathway in HCC. We investigate each step of the mevalonate pathway and demonstrate that statins regulate YAP via Rho GTPases.
Gamma secretase activating protein promotes end-organ dysfunction after bacterial pneumonia
Authors: Gwin Meredith S. , Alexeyev Mikhail F. , Geurts Aron M. , Lee Ji Young , Zhou Chun , Yang Xi-Ming , Cohen Michael V. , Downey James M. , Barrington Robert A. , Spadafora Domenico , Audia Jonathon P. , Frank Dara W. , Voth Sarah , Pastukh Viktoriya V. , Bell Jessica , Ayers Linn , Tambe Dhananjay T. , Nelson Amy R. , Balczon Ron , Lin Mike T. , Stevens Troy
Published: June 2023

Pneumonia is a common cause of end-organ dysfunction, both during and in the aftermath of infection. In particular, pneumonia is a common cause of lung injury, increased risk of myocardial infarction, and neurocognitive dysfunction, although the mechanisms responsible for such increased risk are unknown. Here, we reveal that gamma-secretase activating protein, which contributes to the amyloidogenic pathway, is important for end-organ dysfunction following infection.
Estimation of Finite Population Mean under Probability‐Proportional‐to‐Size Sampling in the Presence of Extreme Values
Authors: Ayinzoya Richard , Jakperik Dioggban
Published: June 2023

This article developed an estimator for finite population mean under probability‐proportional‐to‐size sampling in the presence of extreme values. Theoretical properties such as bias, variance, and consistency are derived. Monte Carlo simulations were performed to assess the consistency and efficiency of the proposed estimator. It is found that the proposed estimator is more efficient than the competing estimators for all values of c between 0 and 1. The gain in precision of the proposed estimator is much higher than that of its competitors for small values of c. Empirical applications of the proposed estimator are illustrated using three real data sets, and the results revealed that the proposed estimator performed better than the conventional and Sarndal (1972) estimators.
Length-Weight Relationships of Eight Fish Species in the World’s Largest Water Diversion Project
Authors: Wang Shulei , Wang Yingcai , Sun Heying , Tang Jianfeng
Published: June 2023

The study provides the length-weight relationships (LWRs) for eight fish species, viz. Hemiculter bleekeri, H. leucisculus, Opsariichthys bidens (Xenocyprididae), Carassius auratus, Cyprinus carpio (Cyprinidae), Pseudorasbora parva (Gobionidae), Acanthorhodeus chankaensis, and Rhodeus ocellatus (Acheilognathidae), in the world’s largest water diversion project, namely, the middle route of South-to-North Water Diversion Project (SNWDP). Fish specimens were sampled by benthic fyke-nets, gillnets, multimesh gillnets, and electrofishing equipment seasonally from 2015 to 2020. The coefficient of determination (r2) was ranging from 0.964 (R. ocellatus) to 0.986 (H. leucisculus), and the b values for the eight species were within range of 2.5–3.5. Also, our study updates the information on the maximum total length for four species (H. bleekeri, H. leucisculus, A. chankaensis, and O. bidens).
Asteroid Hyalosis Migration into the Anterior Chamber during Cataract Surgery
Authors: Saeed Omar , Bloom Jeffrey , Mihok Brian
Published: June 2023

A 70-year-old male presented for cataract surgery in the right eye with pre-operative assessment significant for nuclear sclerotic cataract and asteroid hyalosis. Upon irrigation and aspiration during cataract surgery, yellow-white spheres consistent with asteroid hyalosis were visualized circulating into the anterior chamber despite an intact capsule and no apparent zonular weakness. The asteroides particles were completely aspirated by the irrigation and aspiration ports, and an intraocular lens was implanted into the capsular bag. Postoperatively, the patient did well with final visual acuity of 20/20 and no vitreous prolapse, retinal tears, or detachments noted. There are only four cases in the literature of asteroid hyalosis migrating in the anterior chamber; none of these cases are associated with migration during intraocular surgery. We hypothesize that the asteroid hyalosis migrated anteriorly and around the zonules due to the synuretic nature of the vitreous and microscopic gaps in the zonular fibers. This case demonstrates the importance of the cataract surgeon to be aware of potential migration of asteroid hyalosis into the anterior chamber during surgery.
Intraocular Spread of Ocular Surface Squamous Neoplasia Presenting as a Postoperative Anterior Chamber Opacity after Excisional Biopsy
Authors: Pike Sarah , Engelhard Stephanie B , Sibug Saber Maria E , Mathew Anna J , In Gino K , Berry Jesse L
Published: June 2023

We describe a rare case of ocular surface squamous neoplasia (OSSN) with intraocular spread after excisional biopsy which presented as a postoperative anterior chamber (A/C) opacity, initially thought to be a hypopyon. A 60-year-old female with history of a right (OD) conjunctival mass involving the cornea, surgically excised and diagnosed as OSSN, presented 2 months postoperatively with an A/C opacity concerning for infection. The patient was prescribed prednisolone acetate and ofloxacin drops postoperatively; topical chemotherapy was not given. When the opacity did not respond to 3 weeks of topical treatment, they were referred to an ocular oncologist for management. Intraoperative records from biopsy were unavailable; use of cryotherapy is unknown. On presentation, the patient had reduced vision OD. On slit-lamp exam, a white plaque in the A/C was seen, obscuring the iris. Given concern for postoperative intraocular cancer spread and extent of disease, enucleation with extended conjunctival excision was done. Gross pathology revealed an A/C mass with a diffuse hazy membrane. Histopathology diagnosed moderately differentiated OSSN with extensive intraocular invasion; a full-thickness limbal defect was visualized. Disease was confined to the globe, without residual conjunctival malignancy. This case emphasizes the importance of taking surgical precaution when excising conjunctival lesions, especially large lesions which obscure ocular anatomy, to maintain scleral integrity and Bowman’s layer with limbal lesions. Intraoperative cryotherapy and postoperative chemotherapy should also be employed. If a patient with history of ocular surface malignancy displays symptoms concerning postoperative infection, this case highlights the importance of considering invasive disease.