bluuebunny/crossref_metadata_2025 huggingface dataset:
eXtreme Gradient Boosting-based method to classify patients with COVID-19
Authors: Ramón Antonio , Torres Ana Maria , Milara Javier , Cascón Joaquín , Blasco Pilar , Mateo Jorge
Published: July 2022

Different demographic, clinical and laboratory variables have been related to the severity and mortality following SARS-CoV-2 infection. Most studies applied traditional statistical methods and in some cases combined with a machine learning (ML) method. This is the first study to date to comparatively analyze five ML methods to select the one that most closely predicts mortality in patients admitted with COVID-19. The aim of this single-center observational study is to classify, based on different types of variables, adult patients with COVID-19 at increased risk of mortality. SARS-CoV-2 infection was defined by a positive reverse transcriptase PCR. A total of 203 patients were admitted between March 15 and June 15, 2020 to a tertiary hospital. Data were extracted from the electronic medical record. Four supervised ML algorithms (k-nearest neighbors (KNN), decision tree (DT), Gaussian naïve Bayes (GNB) and support vector machine (SVM)) were compared with the eXtreme Gradient Boosting (XGB) method proposed to have excellent scalability and high running speed, among other qualities. The results indicate that the XGB method has the best prediction accuracy (92%), high precision (>0.92) and high recall (>0.92). The KNN, SVM and DT approaches present moderate prediction accuracy (>80%), moderate recall (>0.80) and moderate precision (>0.80). The GNB algorithm shows relatively low classification performance. The variables with the greatest weight in predicting mortality were C reactive protein, procalcitonin, glutamyl oxaloacetic transaminase, glutamyl pyruvic transaminase, neutrophils, D-dimer, creatinine, lactic acid, ferritin, days of non-invasive ventilation, septic shock and age. Based on these results, XGB is a solid candidate for correct classification of patients with COVID-19.
Chronicling the chronic: narrating the meaninglessness of chronic pain
Authors: van Hout Femke , van Rooden Aukje , Slatman Jenny
Published: July 2022

This article proposes a way of narrating chronic pain: the telling of achronicle. Recent work in the medical humanities has been critical of traditional approaches to illness narratives. In line with this criticism, we argue that the experience of chronic pain resists internally coherent, plot-driven—in other words, Aristotelian—narrative. Drawing on phenomenological studies, we state that chronic pain is an utterly meaningless experience due to its relentless continuation over time. It therefore defies any narrative search for a higher meaning or purpose as well as the search for a coherent and progressive ‘plot’. However, we reject the idea that chronic pain could therefore only be captured in the form of a meaningless, unshareable and chaotic anti-narrative. Instead, we propose that chronic pain could be borne witness to through the speech act ofchronicling—an ongoing telling about ongoing suffering. Building on work of contemporary philosophers Philippe Lacoue-Labarthe and Jean-Luc Nancy, we examine what the chronicle entails by touching on three themes: time, meaning, and the body. First, we argue that chronicling allows people to bear witness to chronic pain’s purposeless continuation over time, thereby affirming the utter meaninglessness of the experience. Second, we argue that it is precisely in the affirmation of this meaninglessness that adifferent kind of meaningcan be experienced: a meaning which cannot be detached from the sensory experience of telling and listening itself. Third, we examine how chronicling chronic pain could allow the muted and painful body to once again meaningfully express itself to others.
Pragmatic guide to peripheral nerve disease and the role of clinical biomarkers
Authors: Keh Ryan Yann Shern , Shah Sachit , Lilleker James B , Lavin Tim , Morrow Jasper , Carr Aisling S , Lunn Michael P
Published: July 2022

In clinical neurology practice, there are few sensitive, specific and responsive serological biomarkers reflecting pathological processes affecting the peripheral nervous system. Instead, we rely on surrogate multimodality biomarkers for diagnosis and management. Correct use and interpretation of the available tests is essential to ensure that appropriate treatments are used and adjusted in a timely fashion. The incorrect application or interpretation of biomarkers can result in misdiagnosis and delays in appropriate treatment. Here, we discuss the uses and limitations of such biomarkers and discuss possible future developments.
Cancer centre supportive oncology service: health economic evaluation
Authors: Stewart Eleanor , Tavabie Simon , McGovern Caroline , Round Alex , Shaw Laura , BAss Stephen , Herriott Rob , Savage Emily , Young Katie , Bruun Andrea , Droney Joanne , Monnery Daniel , Wells Geoffrey , White Nicola , Minton Ollie
Published: July 2022

Objectives

There have been many models of providing oncology and palliative care to hospitals. Many patients will use the hospital non-electively or semielectively, and a large proportion are likely to be in the last years of life. We describe our multidisciplinary service to treatable but not curable cancer patients at University Hospitals Sussex. The team was a mixture of clinical nurse specialists and a clinical fellow supported by dedicated palliative medicine consultant time and oncology expertise.

Methods

We identified patients with cancer who had identifiable supportive care needs and record activity with clinical coding. We used a baseline 2019/2020 dataset of national (secondary uses service) data with discharge code 79 (patients who died during that year) to compare a dataset of patients seen by the service between September 2020 and September 2021 in order to compare outcomes. While this was during COVID-19 this was when the funding was available.

Results

We demonstrated a reduction in length of stay by an average of 1.43 days per admission and a reduction of 0.95 episodes of readmission rates. However, the costs of those admissions were found to be marginally higher. Even with the costs of the service, there is a clear return on investment with a benefit cost ratio of 1.4.

Conclusions

A supportive oncology service alongside or allied to acute oncology but in conjunction with palliative care is feasible and cost-effective. This would support investment in such a service and should be nationally commissioned in conjunction with palliative care services seeing all conditions.
Single dose of budesonide/formoterol turbuhaler compared to salbutamol pMDI for speed of bronchodilator onset in asthma: a randomised cross-over trial
Authors: Kearns Nethmi , Williams Mathew , Bruce Pepa , Black Melissa , Kearns Ciléin , Sparks Jenny , Braithwaite Irene , Weatherall Mark , Beasley Richard
Published: July 2022

Objective

To compare bronchodilator response after to salbutamol and budesonide/formoterol in adults with stable asthma.

Methods

A double-blind, cross-over, single-centre, placebo-controlled, non-inferiority trial. Adults with stable asthma were randomised to different orders of two treatment regimens: two actuations of placebo via MDI and one actuation of budesonide/formoterol 200/6 µg via turbuhaler; and one actuation of placebo turbuhaler and two actuations of salbutamol 100 µg via MDI. The primary outcome measure was FEV1after 2 min. Secondary outcome measures included FEV1, mBorg Dyspnoea Scale score and visual analogue score for breathlessness over 30 min.

Results

Forty-nine of 50 potential participants were randomised. One participant withdrew following the first intervention visit and another could not be randomised due to COVID-19 restrictions. The mean (SD) change from baseline FEV12 min after treatment administration for budesonide/formoterol and salbutamol was 0.08 (0.14) L, n=49, and 0.17 (0.18) L, n=48, respectively, mean (95% CI) paired difference of −0.097 L (−0.147 to −0.047), p=0.07, against a non-inferiority bound of −0.06 L. In the secondary analysis, FEV1over 30 min was lower for budesonide/formoterol compared with salbutamol, difference (95% CI): −0.10 (−0.12 to −0.08) L, p<0.001. There were no differences in Visual Analogue Scale score or mBorg Dyspnoea Scale score between treatments.

Conclusion

The results do not support the primary hypothesis of non-inferiority at the boundary of −0.06 L for the difference between budesonide/formoterol 200/6 µg compared with salbutamol 200 µg for FEV1at 2 min, and could be consistent with inferiority with a p value of 0.07. For the secondary analysis of FEV1measurements over time, the FEV1was higher with salbutamol.

Trial registration number

Australian and New Zealand Clinical Trials Registry (ACTRN 12619001387112).
Development of local density perturbation scheme in f(R) gravity to identify cracking points
Authors: Noureen I. , Arshad N. , Mardan S. A.
Published: July 2022

In this work, the extension of concept of cracking in modified f(R) theory of gravity is presented for spherically symmetric compact objects. We develop general framework to observe the instabilities in self-gravitating spherical system through cracking with anisotropic inner matter configuration. For this purpose, the local density perturbation is applied on the hydrostatic equilibrium equation to identify cracking points/intervals. The physical viability of developed technique is tested on the data of three different stars namely 4U 1820-30, Her X-1 and SAX J1808.4-3658, presented in f(R) model developed in Zubair and Abbas (Astrophys Space Sci 361:342, 2016). It is concluded that these objects exhibit cracking in different interior regions and identification of cracking points refine the stability analysis of the system by extracting instabilities.
Measuring sustainable tourism with online platform data
Authors: Hoffmann Felix J. , Braesemann Fabian , Teubner Timm
Published: July 2022

Sustainability in tourism is a topic of global relevance, finding multiple mentions in the United Nations Sustainable Development Goals. The complex task of balancing tourism’s economic, environmental, and social effects requires detailed and up-to-date data. This paper investigates whether online platform data can be employed as an alternative data source in sustainable tourism statistics. Using a web-scraped dataset from a large online tourism platform, a sustainability label for accommodations can be predicted reasonably well with machine learning techniques. The algorithmic prediction of accommodations’ sustainability using online data can provide a cost-effective and accurate measure that allows to track developments of tourism sustainability across the globe with high spatial and temporal granularity.
Casimir energy for N superconducting cavities: a model for the YBCO (GdBCO) sample to be used in the Archimedes experiment
Authors: Allocca Annalisa , Avino Saverio , Balestrieri Sergio , Calloni Enrico , Caprara Sergio , Carpinelli Massimo , D’Onofrio Luca , D’Urso Domenico , De Rosa Rosario , Errico Luciano , Gagliardi Gianluca , Grilli Marco , Mangano Valentina , Marsella Maria , Naticchioni Luca , Pasqualetti Antonio , Pepe Giovanni Piero , Perciballi Maurizio , Pesenti Luca , Puppo Paola , Rapagnani Piero , Ricci Fulvio , Rosa Luigi , Rovelli Carlo , Rozza Davide , Ruggi Paolo , Saini Naurang , Sequino Valeria , Sipala Valeria , Stornaiuolo Daniela , Tafuri Francesco , Tagliacozzo Arturo , Tosta e Melo Iara , Trozzo Lucia
Published: July 2022

In this paper we study the Casimir energy of a sample made by N cavities, with $$N\gg 1$$

N
≫
1

, across the transition from the metallic to the superconducting phase of the constituting plates. After having characterised the energy for the configuration in which the layers constituting the cavities are made by dielectric and for the configuration in which the layers are made by plasma sheets, we concentrate our analysis on the latter. It represents the final step towards the macroscopical characterisation of a “multi-cavity” (with N large) necessary to fully understand the behaviour of the Casimir energy of a YBCO (or a GdBCO) sample across the transition. Our analysis is especially useful to the Archimedes experiment, aimed at measuring the interaction of the electromagnetic vacuum energy with a gravitational field. To this purpose, we aim at modulating the Casimir energy of a layered structure, the multi-cavity, by inducing a transition from the metallic to the superconducting phase. After having characterised the Casimir energy of such a structure for both the metallic and the superconducting phase, we give an estimate of the modulation of the energy across the transition.
Platycodin D Inhibits Vascular Endothelial Growth Factor-Induced Angiogenesis by Blocking the Activation of Mitogen-Activated Protein Kinases and the Production of Interleukin-8
Authors: Son Ju-Ah , Lee Sun Kyoung , Park Junhee , Jung Min Ju , An So-Eun , Yang Hye Ji , Son Seung Hwa , Kim Ki Rim , Park Kwang-Kyun , Chung Won-Yoon
Published: July 2022

Platycodin D is a major constituent in the root of Platycodon grandiflorum and has diverse pharmacologic activities, including anti-inflammatory, anti-allergic, and antitumor activities. Vascular endothelial growth factor (VEGF) and interleukin-8 (IL-8) are potent angiogenic factors and contribute to tumor angiogenesis by directly and indirectly promoting angiogenic processes, including the proliferation, adhesion, migration, and tube formation of endothelial cells. Here, we found that platycodin D at noncytotoxic concentrations inhibited VEGF-induced proliferation, adhesion to the extracellular matrix proteins fibronectin and vitronectin, chemotactic motility, and tube formation of human umbilical vein endothelial cells (HUVECs). Platycodin D reduced the phosphorylation of extracellular signal-regulated kinase (ERK), p38, and c-Jun N-terminal kinase (JNK) and the secretion of IL-8 in VEGF-stimulated HUVECs. Moreover, platycodin D inhibited tube formation and the phosphorylation of ERK and p38 in IL-8-stimulated HUVECs. The in vitro anti-angiogenic activity of platycodin D was confirmed by in vivo experimental models. Platycodin D inhibited the formation of new blood vessels into mouse Matrigel plugs with VEGF or IL-8. In mice injected with MDA-MB-231 human breast cancer cells, orally administered platycodin D inhibited tumor growth, the number of CD34 [Formula: see text]vessels, and the expression of VEGF and IL-8. Taken together, platycodin D directly and indirectly prevents VEGF-induced and IL-8-induced angiogenesis by blocking the activation of mitogen-activated protein kinases (MAPKs). Platycodin D may be beneficial for the prevention or treatment of tumor angiogenesis and angiogenesis-related human diseases.
A study of charged stellar structure in modified f (R,ϕ,χ) gravity
Authors: Malik Adnan , Mofarreh Fatemah , Ali Akram , Hamid Mah Rukh
Published: July 2022

The aim of this paper is to investigate and analyze the behavior of charged compact stars in the modified [Formula: see text] theory of gravity. When solving the field equations, we assume that Krori– Barua space-time describes the geometry of the inner space [K. Krori and J. Barua, A singularity-free solution for a charged fluid sphere in general relativity, J. Phys. A Math. Gen.  8 (1975) 508]. We further analyzed various physical characteristics for our model, including energy density, pressure components, anisotropy parameter, mass function, compactness element, and redshift through their graphical representations. Additionally, we have checked the equilibrium position by taking Tolman–Oppenheimer–Volkoff equation and stability by using Abreu’s criterion [H. Abreu, H. Hernandez, and L. Nunez, Sound speeds, cracking and the stability of self-gravitating anisotropic compact objects, Class. Quantum Grav.  24 (2007) 4631] and relativistic adiabatic index. For our study, we choose Hercules XI, Centaurus XIII, EXO 1785-248, LMC XIV stars for analysis.
On a geometric description of time-dependent singular Lagrangians with applications to biological systems
Authors: Garai Sudip , Ghose-Choudhury A. , Guha Partha
Published: July 2022

In this paper, we consider certain analytical features of a stochastic model that can explain competition among species and simultaneous predation on the competing species from a geometric perspective. This allows us to build a systematic description of models admitting singular Lagrangians. The model equations are shown to admit a Jacobi Last Multiplier which allows us to construct an appropriate Lagrangian. Due to the singular nature of the Lagrangian, the Hamiltonian formalism may be shown to exist in a submanifold of the cotangent space under certain minimal regularity conditions. In this communication, the Hamiltonian description of the model is constructed via the introduction of Dirac brackets and explicit results for the “Kill the winner” model and its reductions are presented.
Cretaceous magmatism in the Antarctic Peninsula and its tectonic implications
Authors: Bastias Joaquin , Spikings Richard , Riley Teal , Chew David , Grunow Anne , Ulianov Alexey , Chiaradia Massimo , Burton-Johnson Alex
Published: July 2022

Periods of cessation, resumption and enhanced arc activity are recorded in the Cretaceous igneous rocks of the Antarctic Peninsula. We present new geochronological (laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) zircon U–Pb) analyses of 36 intrusive and volcanic Cretaceous rocks, along with LA-ICP-MS apatite U–Pb analyses (a medium-temperature thermochronometer) of 28 Triassic–Cretaceous igneous rocks of the Antarctic Peninsula. These are complemented by new zircon Hf isotope data along with whole-rock geochemistry and isotope (Nd, Sr and Pb) data. Our results indicate that the Cretaceous igneous rocks of the Antarctic Peninsula have geochemical signatures consistent with a continental arc setting and were formed during the interval
c.
140–79 Ma, whereas the main peak of magmatism occurred during
c.
118–110 Ma. Trends in

ε

Hf
t
(zircon) combined with elevated heat flow that remagnetized rocks and reset apatite U–Pb ages suggest that Cretaceous magmatism formed within a prevailing extensional setting that was punctuated by periods of compression. A noteworthy compressive period probably occurred during
c.
147–128 Ma, triggered by the westward migration of South America during opening of the South Atlantic Ocean. Cretaceous arc rocks that crystallized during
c.
140–100 Ma define a belt that extends from southeastern Palmer Land to the west coast of Graham Land. This geographical distribution could be explained by (1) a flat slab with east-dipping subduction of the Phoenix Plate, or (2) west-dipping subduction of the lithosphere of the Weddell Sea, or (3) an allochthonous origin for the rocks of Alexander Island. A better understanding of the geological history of the pre-Cretaceous rocks of Alexander Island and the inaccessible area of the southern Weddell Sea is required.

Supplementary material:
A description of the methods used in this study and the complete dataset are available at
https://doi.org/10.6084/m9.figshare.c.6089274
A Blockchain-Based Access Control Scheme for Zero Trust Cross-Organizational Data Sharing
Authors: Gai Keke , She Yufeng , Zhu Liehuang , Choo Kim-Kwang Raymond , Wan Zhiguo
Published: July 2022

Multi-organization data sharing is becoming increasingly prevalent due to the interconnectivity of systems and the need for collaboration across organizations (e.g., exchange of data in a supply chain involving multiple upstream and downstream vendors). There are, however, data security concerns due to lack of trust between organizations that may be located in jurisdictions with varying security and privacy legislation and culture (also referred to as a zero trust environment). Hence, in such a zero trust setting, one should introduce strengthened, yet efficient, access control mechanisms to facilitate cross-organizational data access and exchange requests. Contemporary access control schemes generally focus on protecting a single objective rather than multiple parties, due to higher security costs. In this article, we propose a blockchain-based access control scheme, designed to facilitate lightweight data sharing among different organizations. Specifically, our approach utilizes the consortium blockchain to establish a trustworthy environment, in which a
Role-Based Access Control
(RBAC) model is then deployed using our proposed multi-signature protocol and smart contract methods. Evaluation of our proposed approach is performed on the HyperLedger Fabric consortium blockchain platform using both
Caliper
and
BFT-SMaRT
benchmarks, and the findings demonstrate the utility of our approach.
Runtime Complexity Bounds Using Squeezers
Authors: Ish-Shalom Oren , Itzhaky Shachar , Rinetzky Noam , Shoham Sharon
Published: July 2022

Determining upper bounds on the time complexity of a program is a fundamental problem with a variety of applications, such as performance debugging, resource certification, and compile-time optimizations. Automated techniques for cost analysis excel at bounding the resource complexity of programs that use integer values and linear arithmetic. Unfortunately, they fall short when the complexity depends more intricately on the evolution of data during execution. In such cases, state-of-the-art analyzers have shown to produce loose bounds, or even no bound at all.

We propose a novel technique that generalizes the common notion of recurrence relations based on ranking functions. Existing methods usually unfold one loop iteration and examine the resulting arithmetic relations between variables. These relations assist in establishing a recurrence that bounds the number of loop iterations. We propose a different approach, where we derive recurrences by comparing
whole traces
with
whole traces
of a lower rank, avoiding the need to analyze the complexity of intermediate states. We offer a set of global properties, defined with respect to whole traces, that facilitate such a comparison and show that these properties can be checked efficiently using a handful of local conditions. To this end, we adapt
state squeezers
, an induction mechanism previously used for verifying safety properties. We demonstrate that this technique encompasses the reasoning power of bounded unfolding, and more. We present some seemingly innocuous, yet intricate, examples that previous tools based on
cost relations
and control flow analysis fail to solve, and that our squeezer-powered approach succeeds.
Curriculum Pre-training Heterogeneous Subgraph Transformer for Top-NRecommendation
Authors: Wang Hui , Zhou Kun , Zhao Xin , Wang Jingyuan , Wen Ji-Rong
Published: July 2022

To characterize complex and heterogeneous side information in recommender systems, the heterogeneous information network (HIN) has shown superior performance and attracted much research attention. In HIN, the rich entities, relations, and paths can be utilized to model the correlations of users and items; such a task setting is often calledHIN-based recommendation. Although HIN provides a general approach to modeling rich side information, it lacks special consideration on the goal of the recommendation task. The aggregated context from the heterogeneous graph is likely to incorporate irrelevant information, and the learned representations are not specifically optimized according to the recommendation task. Therefore, there is a need to rethink how to leverage the useful information from HIN to accomplish the recommendation task.

To address the above issues, we propose a Curriculum pre-training based HEterogeneous Subgraph Transformer (calledCHEST) with newdata characterization,representation model,andlearning algorithm. Specifically, we consider extracting useful information from HIN to compose the interaction-specific heterogeneous subgraph, containing highly relevant context information for recommendation. Then, we capture the rich semantics (e.g., graph structure and path semantics) within the subgraph via a heterogeneous subgraph Transformer, where we encode the subgraph into multi-slot sequence representations. Besides, we design a curriculum pre-training strategy to provide an elementary-to-advanced learning process. The elementary course focuses on capturing local context information within the subgraph, and the advanced course aims to learn global context information. In this way, we gradually capture useful semantic information from HIN for modeling user-item interactions. Extensive experiments conducted on four real-world datasets demonstrate the superiority of our proposed method over a number of competitive baselines, especially when only limited training data is available.
A Collective Adaptive Approach to Decentralised k-Coverage in Multi-robot Systems
Authors: Pianini Danilo , Pettinari Federico , Casadei Roberto , Esterle Lukas
Published: July 2022

We focus on the online multi-object
k
-coverage problem (OMOkC), where mobile robots are required to sense a mobile target from
k
diverse points of view, coordinating themselves in a scalable and possibly decentralised way. There is active research on OMOkC, particularly in the design of decentralised algorithms for solving it. We propose a new take on the issue: Rather than classically developing new algorithms, we apply a macro-level paradigm, called
aggregate computing
, specifically designed to directly program the global behaviour of a whole
ensemble
of devices at once. To understand the potential of the application of aggregate computing to OMOkC, we extend the Alchemist simulator (supporting aggregate computing natively) with a novel toolchain component supporting the simulation of mobile robots. This way, we build a software engineering toolchain comprising language and simulation tooling for addressing OMOkC. Finally, we exercise our approach and related toolchain by introducing new algorithms for OMOkC; we show that they can be expressed concisely, reuse existing software components and perform better than the current state-of-the-art in terms of coverage over time and number of objects covered overall.
Multimodality: Reshaping Anthropology
Authors: Westmoreland Mark R.
Published: July 2022

Multimodality offers anthropologists an inflection on the way we do research, produce scholarship, teach students, and relate to diverse publics. Advancing an expanding array of tools, practices, and concepts, multimodality signals a change in the way we pay attention and attend to the diverse possibilities for understanding the human experience. Multimodality recognizes the way smartphones, social media, and digital software transform research dynamics in unprecedented ways, while also drawing upon long-standing practices of recording and presenting research through images, sounds, objects, and text. Rather than flatten out ethnographic participant observation into logocentric practices of people-writing, multimodal ethnographies diversify their modes of inquiry to produce more-than-textual mediations of sensorial research experiences. By emphasizing kaleidoscopic qualities that give shape to an emergent, multidimensional, and diversifying anthropology, multimodality proposes alternatives to enduring and delimiting dichotomies, particularly text/image. These new configurations invite unrealized disciplinary constellations and research collaborations to emerge, but also require overhauling the infrastructures that support training, dissemination, and assessment.
Lipid Transport Across Bacterial Membranes
Authors: Giacometti Sabrina I. , MacRae Mark R. , Dancel-Manning Kristen , Bhabha Gira , Ekiert Damian C.
Published: July 2022

The movement of lipids within and between membranes in bacteria is essential for building and maintaining the bacterial cell envelope. Moving lipids to their final destination is often energetically unfavorable and does not readily occur spontaneously. Bacteria have evolved several protein-mediated transport systems that bind specific lipid substrates and catalyze the transport of lipids across membranes and from one membrane to another. Specific protein flippases act in translocating lipids across the plasma membrane, overcoming the obstacle of moving relatively large and chemically diverse lipids between leaflets of the bilayer. Active transporters found in double-membraned bacteria have evolved sophisticated mechanisms to traffic lipids between the two membranes, including assembling to form large, multiprotein complexes that resemble bridges, shuttles, and tunnels, shielding lipids from the hydrophilic environment of the periplasm during transport. In this review, we explore our current understanding of the mechanisms thought to drive bacterial lipid transport.
Why People Do What They Do: An Interdisciplinary Synthesis of Human Action Theories
Authors: Eyster Harold N. , Satterfield Terre , Chan Kai M.A.
Published: July 2022

Understanding why people do what they do is central to advancing equitable and sustainable futures. Yet, theories about human action are fragmented across many social science disciplines, each with its own jargon and implicit assumptions. This fragmentation has hindered theory integration and accessibility of theories relevant to a given challenge. We synthesized human action theories from across the humanities and social sciences. We developed eight underlying assumptions—metatheories—that reveal a fundamental organization of human action theories. We describe each metatheory and the challenges that it best elucidates (illustrated with climate change examples). No single metatheory addresses the full range of factors and problems; only one treats interactions between factors. Our synthesis will help researchers, policymakers, and practitioners gain a multifaceted understanding of human action.
Marshes and Mangroves as Nature-Based Coastal Storm Buffers
Authors: Temmerman Stijn , Horstman Erik M. , Krauss Ken W. , Mullarney Julia C. , Pelckmans Ignace , Schoutens Ken
Published: July 2022

Tidal marshes and mangroves are increasingly valued for nature-based mitigation of coastal storm impacts, such as flooding and shoreline erosion hazards, which are growing due to global change. As this review highlights, however, hazard mitigation by tidal wetlands is limited to certain conditions, and not all hazards are equally reduced. Tidal wetlands are effective in attenuating short-period storm-induced waves, but long-period storm surges, which elevate sea levels up to several meters for up to more than a day, are attenuated less effectively, or in some cases not at all, depending on storm conditions, wetland properties, and larger-scale coastal landscape geometry. Wetlands often limit erosion, but storm damage to vegetation (especially mangrove trees) can be substantial, and recovery may take several years. Longer-term wetland persistence can be compromised when combined with other stressors, such as climate change and human disturbances. Due to these uncertainties, nature-based coastal defense projects need to adopt adaptive management strategies.
Review—Ionic Liquids Applications in Flow Batteries
Authors: Xue Bing , Wu Xiangkun , Guo Yawei , Zhang Chi , Qian Weiwei , Zhang Lan
Published: July 2022

Increasing energy demand throughout the world produces great environmental issues, therefore, renewable and clean energy sources, such as tidal energy, wind energy, solar energy and geothermal energy, are desirable request. Meanwhile, developing a new critical energy storage technology to balance the instantaneous energy supply and demand of arranged electric energy is urgent. Rechargeable flow batteries are solutions for storing electricity in form of chemical energy, containing positive and negative electrodes reserved in two separate containers, which have the advantages of low self—discharge and independent scaling of power, therefore considered as promising energy storage technologies. Ionic liquids (ILs) have been widely studied and used in energy storage devices, such as lithium ion battery, for their unique prospective properties. Herein, the key role of ILs and their applications in supporting electrolytes, separators and additives in flow batteries are highlighted in this review. The approaches and challenges in developing ILs supported flow batteries are discussed, and a significative overview of the opportunities of ILs promote flow batteries are finally provided, which is expected to help achieving further improvements in flow batteries.
γ-Alumina Supported Copper Oxide Nanostructures Promoted with Ruthenium Oxide (RuO2-CuO/Al2O3) and Palladium Oxide (PdO-CuO/Al2O3): Efficient Electrodes for Heterogeneous Catalysis of Ammonia Electrooxidation
Authors: Khan Safia , Shah Syed Sakhawat , Ahmad Awais , Bayrakçeken Yurtcan Ayse , Katubi Khadijah Mohammedsaleh , Janjua Naveed Kausar
Published: July 2022

RuO2 and PdO promoted CuO/Al2O3 mixed metal oxide nanostructures synthesized via co-impregnation technique demonstrated a robust electrocatalytic activity towards ammonia electro-oxidation (AEO). Physio-chemically characterized RuO2-CuO/Al2O3 and PdO-CuO/Al2O3 catalyst powders exhibited high electrochemical active surface area (ECSA), highest being shown by 1% RuO2-CuO/Al2O3. All fabricated electrodes displayed pleasing electroactive response towards AEO but ternary metal oxides showed superior and promoted catalytic output owing to their larger ECSA, higher current densities (j), larger diffusion coefficients (D°), greater apparent rate constants (kapp), and lower charge transfer resistance (Rct) values. Lower values of Rct obtained from EIS indicated the facilitation of electro-oxidation process over modified electrodes. The finest catalysis performance is expressed by 1% RuO2-CuO/Al2O3 producing the maximum oxidation current. All the promoted CuO/Al2O3 mixed metal oxide exhibited excellent stability and reproducibility in analyte solution. Consequently, γ-Al2O3 supported metal oxide electrocatalysts can be of great socio-economic significance by enhancing the energy production kinetics thereby achieving a higher energy output.
Electroless Deposition of Pure Co on TaN Substrate for Interconnect Metallization
Authors: Qiu Li-Na , Ni Zi-Hong , Wang Ying-Jie , Hu Chun-Feng , Qu Xin-Ping
Published: July 2022

This work explores the electroless deposition of pure Co film on TaN substrate using Ti3+ as a reducing agent for interconnect metallization. Continuous and dense electroless-deposited (ELD) Co thin films with low surface roughness are obtained on the blanket and patterned structures using colloidal Sn/Pd activation. The effects of the Pd activation process on the Co nucleation, growth mechanisms, and the properties of the deposited Co films have been investigated in detail. The properties of the activated Pd nuclei decide the morphology and quality of the ELD Co films. The XPS results indicate that the ELD Co film is nearly pure Co film, with the metallic Co concentration of 99.2 at% and 99.4 at% for the as-deposited and annealed films, respectively. The resistivity of the Co film in 60 nm thick is as low as 13.6 μΩ·cm. Our results reveal that the ELD Co film is nanocrystalline with a mixture of the HCP and FCC structures. Further, the conformal ELD Co layer with good step coverage is deposited into the nanoscale trenches.
Kir5.1 channels: potential role in epilepsy and seizure disorders
Authors: Staruschenko Alexander , Hodges Matthew R. , Palygin Oleg
Published: July 2022

Inwardly rectifying potassium (Kir) channels are broadly expressed in many mammalian organ systems, where they contribute to critical physiological functions. However, the importance and function of the Kir5.1 channel (encoded by the KCNJ16 gene) have not been fully recognized. This review focuses on the recent advances in understanding the expression patterns and functional roles of Kir5.1 channels in fundamental physiological systems vital to potassium homeostasis and neurological disorders. Recent studies have described the role of Kir5.1-forming Kir channels in mouse and rat lines with mutations in the Kcnj16 gene. The animal research reveals distinct renal and neurological phenotypes, including pH and electrolyte imbalances, blunted ventilatory responses to hypercapnia/hypoxia, and seizure disorders. Furthermore, it was confirmed that these phenotypes are reminiscent of those in patient cohorts in which mutations in the KCNJ16 gene have also been identified, further suggesting a critical role for Kir5.1 channels in homeostatic/neural systems health and disease. Future studies that focus on the many functional roles of these channels, expanded genetic screening in human patients, and the development of selective small-molecule inhibitors for Kir5.1 channels, will continue to increase our understanding of this unique Kir channel family member.
Early-life dietary exposures mediate persistent shifts in the gut microbiome and visceral fat metabolism
Authors: Newman Tiffany M. , Clear Kenysha Y. J. , Wilson Adam S. , Soto-Pantoja David R. , Ochs-Balcom Heather M. , Cook Katherine L.
Published: July 2022

In utero dietary exposures are linked to the development of metabolic syndrome in adult offspring. These dietary exposures can potentially impact gut microbial composition and offspring metabolic health. Female BALB/c mice were administered a lard, lard + flaxseed oil, high sugar, or control diet 4 wk before mating, throughout mating, pregnancy, and lactation. Female offspring were offered low-fat control diet at weaning. Fecal 16S sequencing was performed. Untargeted metabolomics was performed on visceral adipose tissue (VAT) of adult female offspring. Immunohistochemistry was used to determine adipocyte size, VAT collagen deposition, and macrophage content. Hippurate was administered via weekly intraperitoneal injections to low-fat and high-fat diet-fed female mice and VAT fibrosis and collagen 1A (COL1A) were assessed by immunohistochemistry. Lard diet exposure was associated with elevated body and VAT weight and dysregulated glucose metabolism. Lard + flaxseed oil attenuated these effects. Lard diet exposures were associated with increased adipocyte diameter and VAT macrophage count. Lard + flaxseed oil reduced adipocyte diameter and fibrosis compared with the lard diet. Hippurate-associated bacteria were influenced by lard versus lard + flax exposures that persisted to adulthood. VAT hippurate was increased in lard + flaxseed oil compared with lard diet. Hippurate supplementation mitigated VAT fibrosis pathology. Maternal high-fat lard diet consumption resulted in long-term metabolic and gut microbiome programming in offspring, impacting VAT inflammation and fibrosis, and was associated with reduced VAT hippurate content. These traits were not observed in maternal high-fat lard + flaxseed oil diet-exposed offspring. Hippurate supplementation reduced VAT fibrosis. These data suggest that detrimental effects of early-life high-fat lard diet exposure can be attenuated by dietary omega-3 polyunsaturated fatty acid supplementation.
Pathophysiological impact of the adhesion G protein-coupled receptor family
Authors: Einspahr Jeanette M. , Tilley Douglas G.
Published: July 2022

G protein-coupled receptors (GPCRs) represent one of the most targeted drug classes in the human genome, accounting for greater than 40% of all Food and Drug Administration-approved drugs. However, the second-largest family of GPCRs, known as adhesion GPCRs (aGPCR), have yet to serve as a clinical target despite increasing evidence of their physiological and pathological functions, which suggests an opportunity toward the development of novel therapeutics. To date, the pathophysiological function of aGPCRs is associated with a plethora of diseases including cancer, central nervous system disorders, immunity and inflammation, and others. To highlight their potential as pharmacological targets, we will review three distinct aGPCR members (ADGRG1, ADGRE5, and ADGRF5), highlighting their molecular mechanisms of action and contributions to the development of pathophysiology.
The influence of nutrients on mechanical overload-induced changes to skeletal muscle mRNA content
Authors: Laskin Grant R. , Gordon Bradley S.
Published: July 2022

Mechanical overload and nutrients influence skeletal muscle phenotype, with the combination sometimes having a synergistic effect. Muscle phenotypes influenced by these stimuli are mediated in part by changes to the muscle mRNA signature. However, the mechanical overload-sensitive gene programs that are influenced by nutrients remain unclear. The purpose of this study was to identify mechanical overload-sensitive gene programs that are influenced by nutrients and identify potential transcription factors that may differentiate the change in mRNA in response to mechanical overload versus nutrients. Nutrient-deprived 12-wk-old male mice were randomized to remain fasted or allowed access to food. All mice underwent a single bout of unilateral high force contractions of the tibialis anterior (TA). Four hours postcontractions TA muscles were extracted and the content of 12 contraction-sensitive mRNAs was analyzed. The mRNA content of genes associated with transcription, PI3K-Akt signaling pathway, Z-disc, intracellular signal transduction, cell cycle, and amino acid transport was altered by contractions without the influence of nutrient consumption. Conversely, the mRNA content of genes associated with transcription, cell cycle, FoxO signaling pathway, and amino acid transport was altered by contractions with nutrition consumption influencing the change. We identified the signal transducer and activator of transcription 3 (STAT3) and activator protein 1 (AP-1) as transcription factors common among mRNAs that were primarily altered by mechanical overload regardless of feeding. Overall, these data provide a deeper molecular basis for the specific muscle phenotypes exclusive to mechanical overload versus those regulated by the addition of nutrients.
Leveraging a Neuroevolutionary Approach for Classifying Violent Behavior in Video
Authors: Flores-Munguía Carlos , Ortiz-Bayliss José C. , Terashima-Marín Hugo
Published: July 2022

Security has become a critical issue for complex and expensive systems and day-to-day situations. In this regard, the analysis of surveillance cameras is a critical issue usually restricted to the number of people devoted to such a task, their knowledge and judgment. Nonetheless, different approaches have arisen to automate this task in recent years. These approaches are mainly based on machine learning and benefit from developing neural networks capable of extracting underlying information from input videos. Despite how competent those networks have proved to be, developers must face the challenging task of defining both the architecture and hyperparameters that allow such networks to work adequately and optimize the use of computational resources. In short, this work proposes a model that generates, through a genetic algorithm, neural networks for behavior classification within videos. Two types of neural networks evolved as part of this work, shallow and deep, which are structured on dense and 3D convolutional layers. Each network requires a particular type of input data: the evolution of the pose of people in the video and video sequences, respectively. Shallow neural networks use a direct encoding approach to map each part of the chromosome into a phenotype. In contrast, deep neural networks use indirect encoding, blueprints representing entire networks, and modules to depict layers and their connections. Our approach obtained relevant results when tested on the Kranok-NV dataset and evaluated with standard metrics used for similar classification tasks.
3D Assembly Model Retrieval Method for a Multiassembly Interface
Authors: Qiao Hu , Wang Xufan , Xu Tianhang , Wei Zhenxing , Xiang Ying
Published: July 2022

3D model retrieval is increasingly becoming a hot topic in today’s research. The existing model retrieval methods are limited to the retrieval between similar models, while the matching retrieval for models with assembly relationships is neglected. They cannot realize the prediction of the virtual assembly and make the assemblers to spend extensive time detecting when there are assembly errors in the model. This work proposes a 3D assembly model retrieval method for multiassembly interface, which can retrieve the parts or subassemblies that can be assembled with the input model. In this work, a method for the reuse of the 3D assembly mode is also provided. The method here involves a series of steps, which includes an attribute adjacency graph to express the 3D assembly models, followed by the definition of a conjugated subgraph, and the serialization of the vertices of the graph for the Atlas of the assembly model. Finally, the frequent subgraph mining method is improved, and the 3D assembly model that satisfies the multiassembly interface is extracted. The article claims through the obtained results that this method not only allows the performance of the 3D assembly model retrieval of multiassembly interfaces but also the extraction of the 3D model required by designers, improving, at the same time, the product design efficiency.
A Slope Stability Based Realm Optimization Analysis for an Open Pit Mine in Cold Region: Taking Jiguanshan Molybdenum Mine for Example
Authors: Hu Yongyue , Li Changhong , Li Juzhou , Long Dayu , Wang Yu
Published: July 2022

Open pit mines have a direct impact on the production efficiency and sustainable development of the enterprise by realm optimization. In the case of changing mining technology conditions and market demand, the original design realm of the mine needs to be optimized in time for the study. Therefore, based on the slope stability analysis, this paper changes the slope angle by changing the working platform size and step and section, and forms a total of four Programs I, II, III, and IV. Geostudio software was utilized to analyze the slope stability of four scenarios and obtain the slope safety coefficients under different scenarios, and the results show that Programs I, II, and III all meet the requirements of reasonable safety coefficients. Furthermore, the geological model of the slope in C profile in Program III was constructed, and the changes of slope stress and displacement during the step-by-step excavation process were analyzed, with a maximum of stress 3.5 MPa, total displacement 12.9 cm, shear should be incremental, plastic zone change is small, and the results showed that the slope structure parameters of Program III were reasonable. The geological drilling data of Jiguanshan molybdenum mine was processed with 3DMine software, the geological database was constructed, the ore body model was established, and the mine boundary optimization study was conducted, Program III was finally determined as the optimal option. The result of the boundary optimization improves the final slope angle by 1°, which can enable the mine to extract 13.334 million tons more ore, reduce the stripping ratio to 1.07m3/m3, and generate economic benefits of $116 million.
Effect of Industrial Robots on Employment in China: An Industry Level Analysis
Authors: Zhao Yantong , Said Rusmawati , Ismail Normaz Wana , Hamzah Hanny Zurina
Published: July 2022

China has been the world’s largest market for industrial robots since 2013. Industrial robots improve accuracy, safety, and efficiency in industrial production but have a substantial impact on the labor market. This investigation uses the task-based model to explore the relationship between industrial robots and employment across industries. This study uses industrial robot data from the International Federation of Robotics and employment data from the China Statistical Yearbook from 2010 to 2019 to examine robot applications’ influencing mechanisms on labor demand in different industries in China. The results show a significant positive correlation between robots’ exposure and labor demand for IT, health and social services, science research and technical services, and management of water conservancy and environmental industries. Based on the results, the use of robots promotes high-skilled talent employment and some third-sector employment, like education, food and beverages, utilities, household appliances, and transport. However, multiple regression analysis reveals that the use of robots has reduced employment in traditional industries such as agriculture and mining.