bluuebunny/crossref_metadata_2025 huggingface dataset:
Self-reported MeasUrement of Physical and PsychosOcial Symptoms Response Tool (SUPPORT-dialysis): systematic symptom assessment and management in patients on in-centre haemodialysis – a parallel arm, non-randomised feasibility pilot study protocol
Authors: Gill Jasleen Kaur , Pucci Maria , Samudio Ana , Ahmed Tibyan , Siddiqui Rabail , Edwards Nathaniel , Marticorena Rosa M , Donnelly Sandra , Lok Charmaine , Wentlandt Kirsten , Wolofsky Kayla , Mucsi Istvan
Published: January 2024

Introduction

Patients with kidney failure experience symptoms that are often under-recognised and undermanaged. These symptoms negatively impact health-related quality of life and are associated with adverse clinical outcomes. Regular symptom assessment, using electronic patient reported outcomes measure (ePROMs) linked to systematic symptom management, could improve such outcomes. Clinical implementation of ePROMs have been successful in routine oncology care, but not used for patients on dialysis. In this study, we describe a pilot study of ePROM-based systematic symptom monitoring and management intervention in patients treated with in-centre haemodialysis.

Methods and analysis

This is a parallel-arm, controlled pilot of adult patients receiving in-centre maintenance haemodialysis. Participants in the intervention arm will complete ePROMs once a month for 6 months. ePROMs will be scored real time and the results will be shared with participants and with the clinical team. Moderate-severe symptoms will be flagged using established cut-off scores. Referral options for those symptoms will be shared with the clinical team, and additional symptom management resources will also be provided for both participants and clinicians. Participants in the control arm will be recruited at a different dialysis unit, to prevent contamination. They will receive usual care, except that they will complete ePROMs without the presentation of results to participants of the clinical team. The primary objectives of the pilot are to assess (1) the feasibility of a larger, randomised clinical effectiveness trial and (2) the acceptability of the intervention. Interviews conducted with participants and staff will be assessed using a content analysis approach.

Ethics and dissemination

Ethical approval for this study was obtained from the University Health Network (REB#21-5199) and the William Osler Health System (#23-0005). All study procedures will be conducted in accordance with the standards of University Health Network research ethics board and with the 1964 Helsinki declaration and its later amendments. Results of this study will be shared with participants, patients on dialysis and other stakeholders using lay language summaries, oral presentations to patients and nephrology professionals. We will also be publishing the results in a peer-reviewed journal and at scientific meetings.

Protocol version

4 (16 November 2022).

Trial registration number

NCT05515991.
Designing a Library of Lived Experience for Mental Health: integrated realist synthesis and experience-based co-design study in UK mental health services
Authors: Marshall Paul , Barbrook John , Collins Grace , Foster Sheena , Glossop Zoe , Inkster Clare , Jebb Paul , Johnston Rose , Jones Steven H , Khan Hameed , Lodge Christopher , Machin Karen , Michalak Erin , Powell Sarah , Russell Samantha , Rycroft-Malone Jo , Slade Mike , Whittaker Lesley , Lobban Fiona
Published: January 2024

Objective

Living Library events involve people being trained as living ‘Books’, who then discuss aspects of their personal experiences in direct conversation with attendees, referred to as ‘Readers’. This study sought to generate a realist programme theory and a theory-informed implementation guide for a Library of Lived Experience for Mental Health (LoLEM).

Design

Integrated realist synthesis and experience-based co-design.

Setting

Ten online workshops with participants based in the North of England.

Participants

Thirty-one participants with a combination of personal experience of using mental health services, caring for someone with mental health difficulties and/or working in mental health support roles.

Results

Database searches identified 30 published and grey literature evidence sources which were integrated with data from 10 online co-design workshops conducted over 12 months. The analysis generated a programme theory comprising five context-mechanism-outcome (CMO) configurations. Findings highlight how establishing psychological safety is foundational to productive Living Library events (CMO 1). For Readers, direct conversations humanise others’ experiences (CMO 2) and provide the opportunity to flexibly explore new ways of living (CMO 3). Through participation in a Living Library, Books may experience personal empowerment (CMO 4), while the process of self-authoring and co-editing their story (CMO 5) can contribute to personal development. This programme theory informed the co-design of an implementation guide highlighting the importance of tailoring event design and participant support to the contexts in which LoLEM events are held.

Conclusions

The LoLEM has appeal across stakeholder groups and can be applied flexibly in a range of mental health-related settings. Implementation and evaluation are required to better understand the positive and negative impacts on Books and Readers.

Trial registration number

PROSPERO CRD42022312789.
Early-life diet and risk of inflammatory bowel disease: a pooled study in two Scandinavian birth cohorts
Authors: Guo Annie , Ludvigsson Johnny , Brantsæter Anne Lise , Klingberg Sofia , Östensson Malin , Størdal Ketil , Mårild Karl
Published: January 2024

Objective

We assessed whether early-life diet quality and food intake frequencies were associated with subsequent IBD.

Design

Prospectively recorded 1-year and 3-year questionnaires in children from the All Babies in Southeast Sweden and The Norwegian Mother, Father and Child Cohort Study were used to assess diet quality using a Healthy Eating Index and intake frequency of food groups. IBD was defined as >2 diagnoses in national patient registers. Cox regression yielded HRs adjusted (aHRs) for child’s sex, parental IBD, origin, education level and maternal comorbidities. Cohort-specific results were pooled using a random-effects model.

Results

During 1 304 433 person-years of follow-up, we followed 81 280 participants from birth through childhood and adolescence, whereof 307 were diagnosed with IBD. Compared with low diet quality, medium and high diet quality at 1 year of age were associated with a reduced risk of IBD (pooled aHR 0.75 (95% CI=0.58 to 0.98) and 0.75 (95% CI=0.56 to 1.00)). The pooled aHR per increase of category was 0.86 (0.74 to 0.99). Pooled aHR for children 1 year old with high versus low fish intake was 0.70 (95% CI=0.49 to 1.00) for IBD, and showed association with reduced risk of UC (pooled aHR=0.46; 95% CI=0.21, 0.99). Higher vegetable intake at 1 year was associated with a risk reduction in IBD. Intake of sugar-sweetened beverages was associated with an increased risk of IBD. Diet quality at 3 years was not associated with IBD.

Conclusion

In this Scandinavian birth cohort, high diet quality and fish intake in early life were associated with a reduced risk of IBD.
Chorea-acanthocytosis
Authors: Rashid Sana , Malek Naveed , Krommyda Magdalini
Published: January 2024

A middle-aged Asian man had gait difficulty progressing over several years. His speech had gradually become slurred with involuntary tongue biting. He was the product of a consanguineous marriage with no other relevant family history. MR scan of brain showed bilateral caudate atrophy. Nerve conduction studies showed a predominantly sensory peripheral neuropathy. Serum creatine kinase was slightly elevated but electromyography showed no evidence of myopathy. Three consecutive peripheral blood films were negative for acanthocytes. Whole-genome sequencing confirmed a mutation inVPS13Agene, consistent with autosomal recessive chorea-acanthocytosis.
Gut microbiome and intestinal inflammation in preclinical stages of rheumatoid arthritis
Authors: Gilbert Benoît Thomas P , Tadeo Raul Yhossef Tito , Lamacchia Celine , Studer Olivia , Courvoisier Delphine , Raes Jeroen , Finckh Axel
Published: January 2024

Background

FaecalPrevotellaceae, and other microbes, have been associated with rheumatoid arthritis (RA) and preclinical RA. We have performed a quantitative microbiome profiling study in preclinical stages of RA.

Methods

First-degree relatives of patients with RA (RA-FDRs) from the SCREEN-RA cohort were categorised into four groups: controls, healthy asymptomatic RA-FDRs; high genetic risk, asymptomatic RA-FDRs with two copies of the shared epitope; autoimmunity, asymptomatic RA-FDRs with RA-associated autoimmunity; and symptomatic, clinically suspect arthralgias or untreated new-onset RA.

Faecal samples were collected and frozen. 16S sequencing was performed, processed with DADA2 pipeline and Silva database. Cell counts (cytometry) and faecal calprotectin (enzyme-linked immunosorbent assay, ELISA) were also obtained. Microbial community analyses were conducted using non-parametric tests, such as permutational multivariate analysis of variance (PERMANOVA), Wilcoxon and Kruskal-Wallis, or Aldex2.

Results

A total of 371 individuals were included and categorised according to their preclinical stage of the disease. Groups had similar age, gender and body mass index. We found no significant differences in the quantitative microbiome profiles by preclinical stages (PERMANOVA, R2=0.00798, p=0.56) and, in particular, no group differences inPrevotellaceaeabundance. Results were similar when using relative microbiome profiling data (PERMANOVA, R2=0.0073, p=0.83) or Aldex2 on 16S sequence counts. Regarding faecal calprotectin, we found no differences between groups (p=0.3).

Conclusions

We could not identify microbiome profiles associated with preclinical stages of RA. Only in a subgroup of individuals with the most pronounced phenotypes did we modestly retrieve the previously reported associations.
Kinematic responses of lead-caulked joints for cast iron pipelines subjected to strike-slip faulting
Authors: Li Dian-Qing , Zhao Ning , Du Wenqi , Cao Zi-Jun
Published: January 2024

Buried cast iron pipelines are susceptible to damage at joints under fault movements. In this paper, a new three-dimensional soil-pipe continuum model for segmented pipelines undergoing fault rupture is introduced, in which both the nonlinear behavior of lead-caulked joints and post-peak softening behavior of dense sand are properly characterized. The rationality of the developed numerical model is validated against experimental results reported in the literature. Parametric analyses indicate that ignoring the strain softening behavior of soil would underestimate the maximum joint rotations, and the parameters of fault-pipe intersection angle, cast iron-lead adhesion, and burial depth play a notable role on the magnitude of joint kinematics. Numerical fault rupture analyses are then conducted for cast iron pipelines with nominal diameters ranging from 900 to 1500 mm. Based on the numerical results, predictive solutions are developed for estimating the maximum axial translations and joint rotations under fault movements. The residuals of the proposed solutions are generally unbiased. The proposed solutions can be used to evaluate the maximum joint kinematics in terms of axial translations and joint rotations for large-diameter cast iron pipelines with lead-caulked joints undergoing strike-slip fault ruptures.
Influence of bonding condition of different interfaces on the mechanical responses and failure mode of asphalt pavement
Authors: Yao Kang , Dong Qiao , Chen Xueqin , Wang Xiang , Xie Shengjia , Cheng Zhiqiang
Published: January 2024

In this study, a finite element model was established to compute the responses of asphalt pavement with various bonding conditions between the asphalt concrete layers (AC-AC interface) and between the asphalt concrete layer and base (AC-Base interface). The influence of bonding conditions of different interfaces on failure mode of asphalt pavement was discussed. The results indicated that poor bonding condition would increase longitudinal tensile strain at the bottom of the AC layers and vertical compressive strain at the top of subgrade, and the negative effects of two interfaces on pavement would enhance each other. It was observed that insufficient bonding strength would reduce the predicted life of pavement and, more importantly, debonding of AC-AC interface or two interfaces simultaneously would change pavement failure mode. Additionally, it should be noted that the fully-unbonded condition of AC-AC interface would affect the critical location for crack initiation in AC layers.
A Bayesian spatially explicit estimation of daily egg production: application to anchovy in the Bay of Biscay
Authors: Citores Leire , Ibaibarriaga Leire , Santos Maria , Uriarte Andres
Published: January 2024

Biomass estimates of fish resources by the daily egg production method (DEPM) are sensitive to the high variability of the daily egg production ( P0) and egg mortality (Z) in space. This work presents a Bayesian approach to estimate these parameters. A prior distribution of Z based on literature serves to overcome the biologically implausible Z estimates that can result from frequentist approaches. In addition to the classical estimation of a single P0 over the spawning area, the Bayesian framework allows also the modelling of egg densities in space, by including either spatial random effects, smoothing functions, or kriging like models, providing insights into the spatial variability of P0. The Bayesian approach was applied to the Bay of Biscay anchovy DEPM surveys. Results showed that this Bayesian approximation solved the implausible Z problem resulting in tighter credible intervals of both P0 and Z. Overall, spatial models outperformed the non-spatial model in terms of goodness of fit and resulted in slightly different total production estimates across models for each year, with a moderate decrease on uncertainty estimates.
Solution for the null-surface formulation in 2+1 dimensions with radiation source
Authors: Harriott Tina A. , Williams J.G.
Published: January 2024

The null-surface formulation (NSF) of general relativity has three coupled and highly nonlinear field equations whose solution determines (a family of) null surfaces indicated by the variable u. This variable is one of a set of intrinsic coordinates that are defined in terms of the surfaces. The first of the three field equations is called the main metricity condition, and it is by far the most complicated. This work considers the NSF in 2+1 dimensions and presents a solution that is founded on the following strategy: simplify the main metricity condition by requiring the uu-component of the metric tensor to be zero and then search for an additively separable solution formed from a sum of separate terms—each term being linked with a term in a certain differential operator ∂ so as to cause a convenient cancellation. The main motivation for this work is to find an approach that will extend to higher dimensions, where the role of ∂ is played by the eth operator, ð, of Newman and Penrose.
Isomeric decays with multipolarity $$\lambda \ge$$ 3
Authors: Podolyák Zsolt
Published: January 2024

Isomeric decays with multipolarity $$\lambda \ge 3$$

λ
≥
3

are discussed. Parity changing E3, M4, E5 decays are more widespread within the nuclide chart when compared to parity conserving M3, E4 and M5 transitions, which is the consequence of the properties of the nuclear shell model. The E3 transitions around $$^{208}$$

208

Pb are classified depending on their origins. Systematics of M4 and E5 transitions are presented. These provide an excellent test to the study of shell evolution in different parts of the nuclide chart as well as the nature of the effective charges.
Nature-Inspired Optimization with Deep Learning-Enabled Sustainable Predictive Model for Intelligent Systems
Authors: Ge Shan , Liu Hao , Liu Yong , Kong Jian , Shi Jinqiao , Qiu Jin , Deng Wenyang
Published: January 2024

Solar energy can be considered as an alternate solution to conventional energy sources. Short-term Photovoltaic (PV) Power Generation (PVPG) prediction methods are essential stabilize power integration among PV and smart grids. The PVPG generation process is highly dependent on climatic conditions and therefore high intermittent. Highly accurate PVPG prediction of PVPG acts based on the generation, transmission and dispersion of electricity, confirming the stability and dependability of power system. The current progress of Machine Learning (ML) and Deep Learning (DL) approaches enables for designing of accurate PVPG prediction models. In this view, this paper develops a new Badger Optimization with Deep Learning Enabled PV Power Generation Predictive (HBODL-PVPGP) model. The presented HBODL-PVPGP model enables to forecast of the PVPG process. To accomplish this, the HBODL-PVPGP model initially investigates the features depending upon intrinsic characteristics earlier in the learning process. In addition, the Bidirectional Gated Recurrent Unit (BiGRU) model is implemented for forecasting process. The performance of the BiGRU model can be improvised by the design of HBO-based hyperparameter tuning procedure. For ensuring the enhanced performance of the HBODL-PVPGP model, an extensive range of experimental study was effectuated and the results were investigated under various factors. The result highlighted the precipitated performance of the HBODL-PVPGP procedure on the current algorithms.
Gapsets and the k-generalized Fibonacci sequences
Authors: Almeida Filho Gilberto B. , Bernardini Matheus
Published: January 2024

We bring the terminology of the Kunz coordinates of numerical semigroups to gapsets and we generalize this concept to m-extensions. It allows us to identify gapsets and, in general, m-extensions with tilings of boards; as a consequence, we present some applications of this identification. Moreover, we present explicit formulas for the number of gapsets with fixed genus and depth, when the multiplicity is 3 or 4, and, in some cases, for the number of gapsets with fixed genus and depth.
RadheDham Ashram: Business Continuity Post Disruption
Authors: Mittal Rajkumari , Sinha Parul , Srivastava Ritu
Published: January 2024

This case highlights the challenges faced by the Religious Tourism sector due to sudden disruptions caused by the COVID-19 pandemic. Although the disruptions affected every trade, the unorganized and budget hotels at various religious destinations in India faced an extended impact. The case is about RadheDham Ashram, an affordable stay offering a religious and spiritual experience at Vrindavan, Uttar Pradesh province of North India. Pandit Shiv Kumar Tripathi, the owner of RadheDham Ashram, was concerned about managing its probable receding operations amidst the disruption caused by the COVID-19 pandemic. RadheDham Ashram was a popular destination to stay in because of its affordability and proximity to the famous Sri Krishna Temple. However, things had changed with the COVID-19 pandemic and predicted lockdowns. As a result, the temples were supposed to close, and the influx of tourists at Ashrams would reduce consequently, as pilgrims would avoid the crowded destinations. Tripathi was worried about the occupancy of the Ashram. His concerns ranged from matching the Ashram service capacity with the uncertain demand to managing yield by adopting strategies such as differential pricing, capacity planning or overbooking when the tourist footfall was uncertain. Due to low customer influx and high demand variability, it was a tough time for Tripathi. He had to select the best possible alternative to bridge the gap between service capacity and demand. The selected alternative must ascertain sufficient yield to RadheDham Ashram along with retention of its goodwill and its loyal customers. All these thoughts made him anxious about the business continuity of his RadheDham Ashram in the upcoming days.
Multi-Objective Last-Mile Vehicle Routing Problem for Fresh Food E-Commerce: A Sustainable Perspective
Authors: Liu Xing , Gou Xunjie , Xu Zeshui
Published: January 2024

Last-mile logistics poses a pivotal challenge for the sustainable prosperity of fresh food e-commerce. However, there has been insufficient research attention towards optimizing the last-mile vehicle routing from three sustainable dimensions simultaneously based on triple-bottom-line. To narrow this gap, this paper proposes a multi-objective last-mile vehicle routing model for fresh food e-commerce, which takes the three sustainable dimensions as independent objectives. The economic and environment objectives are minimizing the total cost and carbon emission, respectively. For social dimension, a nonlinear function is proposed based on the Prospect theory, which quantifies customers’ satisfaction when they perceive delivery time. Then the social objective is described as maximizing customers’ satisfaction. Subsequently, the model is solved by the nondominated sorting genetic algorithm II and validated by a numerical experiment. Based on the experiment results, this paper recommends that logistics enterprises should prioritize the trade-off among the three sustainable dimensions.
On the N-waves hierarchy with constant boundary conditions. Spectral properties
Authors: Gerdjikov Vladimir S. , Grahovski Georgi G.
Published: January 2024

This paper is devoted to [Formula: see text]-wave equations with constant boundary conditions related to symplectic Lie algebras. We study the spectral properties of a class of Lax operators [Formula: see text], whose potentials [Formula: see text] tend to constants [Formula: see text] for [Formula: see text]. For special choices of [Formula: see text], we outline the spectral properties of [Formula: see text], the direct scattering transform and construct its fundamental analytic solutions. We generalize Wronskian relations for the case of CBC — this allows us to analyze the mapping between the scattering data and the [Formula: see text]-derivative of the potential [Formula: see text]. Next, using the Wronskian relations, we derive the dispersion laws for the [Formula: see text]-wave hierarchy and describe the NLEE related to the given Lax operator.
Null cartan geodesic isophote curves in Minkowski 3-space
Authors: Li Zewen , Pei Donghe
Published: January 2024

In this paper, we investigate null Cartan geodesic isophote curves in the Minkowski [Formula: see text]-space, and give examples where such curves actually exist. By categorizing the types of light vectors, we characterize different types of null Cartan geodesic isophote curves. Moreover, we present the relationship between null Cartan geodesic isophote curves and other special curves.
Analytical and numerical solutions for a special nonlinear equation
Authors: Fard Hossein Sahebi , Dastranj Elham , Hejazi Reza , Jajarmi Amin
Published: January 2024

In the most of the option price dynamics in the financial markets, the transaction cost of option is ignored. Considering the transaction costs will lead to the emergence of models with nonlinear PDE. In this paper, transaction cost of option in the assumed market is considered, and the resulting dynamic is a nonlinear PDE, whose exact and numerical solutions have been computed in the present paper. To find the exact solution of the cited nonlinear equation, the Lie group algebra method has been used. The numerical solution has been given using the Chebyshev spectral method. In this method, the solution of the considered equation is approximated using Chebyshev polynomials. The convergence of the obtained polynomials to the solution of the differential equation has been shown, as well.
Effects of differential tectonic activities on overpressure evolution in the deep-water area of the Qiongdongnan Basin: implications for gas hydrate accumulation
Authors: Xu Litao , Wang Ren , Ren Jinfeng , Shi Wanzhong , Xie Xiangyang , He Yulin , Busbey Arthur B. , Du Hao , Zuo Tingna , Xu Xiaofeng
Published: January 2024

The lack of data on the complex tectonics of the Qiongdongnan Basin has thus far restricted our understanding of the overpressure, deep hydrocarbon and shallow gas hydrate distribution. We therefore combined integrated seismic, well and borehole test data with basin models to clarify the relationship between tectonic activity and overpressure evolution, as well as the potential effects of the subsurface pressure on gas hydrate accumulation. The results show differences in tectonic activity and pressure characteristics between the eastern and western basins. Large numbers of faults and magmatic intrusions have developed in the post-rift layer of the eastern basin (the Baodao to Changchang sub-basins) since the Late Miocene (
c.
10.5 Ma), although they seldom formed in the western basin (the Lengdong to Lingshui sub-basins). Correspondingly, the eastern basin was characterized by lower overpressures (up to 40 MPa) and the western basin displayed higher overpressures (up to 110 MPa). The results indicate that tectonic activity since
c.
10.5 Ma caused the relief of overpressure in the eastern basin. In stark contrast, the overpressure in the western basin increased significantly due to the lack of structural conduits and rapid sedimentation of the thick Pliocene and Quaternary deposits. Numerical models reveal that the faults and gas chimneys associated with the intrusions constituted shallow plumbing systems through which deep natural gas was able to migrate upwards. The formation of gas hydrates relied on the migration of deep gas to the hydrate stability zone below the seafloor. The relatively lower overpressured zones due to pressure relief in the eastern basin are therefore considered the next areas potentially favourable for the formation of gas hydrates.

Thematic collection:
This article is part of the Emerging knowledge on the tectonics of the South China Sea collection available at:
https://www.lyellcollection.org/topic/collections/south-china-sea
Multi-view Image Fusion Using Ensemble Deep Learning Algorithm For MRI And CT Images
Authors: N. Thenmoezhi , B. Perumal , A. Lakshmi
Published: January 2024

Medical image fusions are crucial elements in image-based health care diagnostics or therapies and generic applications of computer visions. However, the majority of existing methods suffer from noise distortion that affects the overall output. When pictures are distorted by noises, classical fusion techniques perform badly. Hence, fusion techniques that properly maintain information comprehensively from multiple faulty pictures need to be created. This work presents Enhanced Lion Swarm Optimization (ESLO) with Ensemble Deep Learning (EDL) to address the aforementioned issues. The primary steps in this study include image fusions, segmentation, noise reduction, feature extraction, picture classification, and feature selection. Adaptive Median Filters are first used for noise removal in sequence to enhance image quality by eliminating noises. The MRIs and CT images are then segmented using the Region Growing–based
k
-Means Clustering (RKMC) algorithm to separate the images into their component regions or objects. Images in black and white are divided into image. In the white image, the RKMC algorithm successfully considered the earlier tumour probability. The next step is feature extraction, which is accomplished by using the Modified Principal Component Analysis (MPCA) to draw out the most informative aspects of the images. Then the ELSO algorithm is applied for optimal feature selection, which is computed by best fitness values. After that, multi-view image fusions of multi modal images derive lower-, middle-, and higher-level image contents. It is done by using Deep Convolution Neural Network (DCNN) and the Tissue-Aware Conditional Generative Adversarial Network (TAcGAN) algorithm, which fuses the multi-view features and relevant image features, and it is used for real-time applications. ELSO +EDL algorithm gives better results in terms of accuracy, Peak Signal-To-Noise Ratio (PSNR), and lower Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE) when compared to other existing algorithms.
Ranking the causal impact of recommendations under collider bias in k-spots recommender systems
Authors: Ruiz De villa Aleix , Sottocornola Gabriele , Coba Ludovik , Lucchesi Federico , Skorulski Bartłomiej
Published: January 2024

The first objective of recommender systems is to provide personalized recommendations for each user. However, personalization may not be its only use. Past recommendations can be further analyzed to gain global insights into users’ behavior with respect to recommended items. Such insights can help to answer design-related questions such as which items’ recommendations are the most impactful in terms of users’ utility, which type of recommendations are the most followed ones, which items could be dropped from the catalog, or which recommendations are under-performing compared to what one would expect. In order to answer those questions, we need to rank item recommendations’ performances in terms of their causal impact on some user-related outcome measures. Unfortunately, in previous work leveraging causal inference for recommendation systems, the attention is fully focused on correcting confounding bias and not on the collider bias. This bias is particularly relevant in the recommender context, where multiple items are simultaneously recommended. Indeed, when there is a fixed number of available spots (i.e.,
k
-spots) and recommendations need to be provided at each session, we argue that it is not possible to estimate the causal impacts of recommendations but only the differences between them. Therefore, in this article, we provide an unbiased estimator of the differences in the impacts of items’ recommendations, that work for any outcome of interest, and any type of recommender system as long as it has some degree of randomization. We apply our results both in a simulated environment and in a real-world offline environment leveraging logged data for recommended items in a digital healthcare app.
Winols: A Large-Tiling Sparse Winograd CNN Accelerator on FPGAs
Authors: Xie Kunpeng , Lu Ye , He Xinyu , Yi Dezhi , Dong Huijuan , Chen Yao
Published: January 2024

Convolutional Neural Networks (CNNs) can benefit from the computational reductions provided by the Winograd minimal filtering algorithm and weight pruning. However, harnessing the potential of both methods simultaneously introduces complexity in designing pruning algorithms and accelerators. Prior studies aimed to establish regular sparsity patterns in the Winograd domain, but they were primarily suited for small tiles, with domain transformation dictating the sparsity ratio. The irregularities in data access and domain transformation pose challenges in accelerator design, especially for larger Winograd tiles. This paper introduces “Winols,” an innovative algorithm-hardware co-design strategy that emphasizes the strengths of the large-tiling Winograd algorithm. Through a spatial-to-Winograd relevance degree evaluation, we extensively explore domain transformation and propose a cross-domain pruning technique that retains sparsity across both spatial and Winograd domains. To compress pruned weight matrices, we invent a relative column encoding scheme. We further design an FPGA-based accelerator for CNN models with large Winograd tiles and sparse matrix-vector operations. Evaluations indicate our pruning method achieves up to 80% weight tile sparsity in the Winograd domain without compromising accuracy. Our Winols accelerator outperforms dense accelerator by a factor of 31.7× in inference latency. When compared with prevailing sparse Winograd accelerators, Winols reduces latency by an average of 10.9×, and improves DSP and energy efficiencies by over 5.6× and 5.7×, respectively. When compared with the CPU and GPU platform, Winols accelerator with tile size 8× 8 achieves 24.6× and 2.84× energy efficiency improvements, respectively.
Discriminative Action Snippet Propagation Network for Weakly Supervised Temporal Action Localization
Authors: Dang Yuanjie , Huang Chunxia , Chen Peng , Zhao Dongdong , Gao Nan , Liang Ronghua , Huan Ruohong
Published: January 2024

Weakly supervised temporal action localization (WTAL) aims to classify and localize actions in untrimmed videos with only video-level labels. Recent studies have attempted to obtain more accurate temporal boundaries by exploiting latent action instances in ambiguous snippets or propagating representative action features. However, empirically handcrafted ambiguous snippet extraction and the imprecise alignment of representative snippet propagation lead to challenges in modeling the completeness of actions for these methods. In this article, we propose a Discriminative Action Snippet Propagation Network (DASP-Net) to accurately discover ambiguous snippets in videos and propagate discriminative instance-level features throughout the video for improving action completeness. Specifically, we introduce a novel discriminative feature propagation module for capturing the global contextual attention and propagating the action concept across the whole video by perceiving the discriminative action snippets with instance information from the same video. Simultaneously, we incorporate denoised pseudo-labels as supervision, where we correct the controversial prediction based on the feature space distribution during training, thereby alleviating false detection caused by noise background features. Furthermore, we design an ambiguous feature mining module, which maximizes the feature affinity information of action and background in ambiguous snippets to generate more accurate latent action and background snippets and learns more precise action instance boundaries through contrastive learning of action and background snippets. Extensive experiments show that DASP-Net achieves state-of-the-art results on THUMOS14 and ActivityNet1.2 datasets.
A Comparative Study of Degradation Behaviors of LiFePO4, LiMn2O4, and LiNi0.8Mn0.1Co0.1O2 in Different Aqueous Electrolytes
Authors: Zhang Yuxin , Hu Anyang , Hou Dong , Kwon Gihan , Xia Dawei , Li Luxi , Lin Feng
Published: January 2024

Aqueous Li-ion batteries (ALIBs) are an important class of battery chemistries owing to the intrinsic non-flammability of aqueous electrolytes. However, water is detrimental to most cathode materials and could result in rapid cell failure. Identifying the degradation mechanisms and evaluating the pros and cons of different cathode materials are crucial to guide the materials selection and maximize their electrochemical performance in ALIBs. In this study, we investigate the stability of LiFePO4 (LFP), LiMn2O4 (LMO) and LiNi0.8Mn0.1Co0.1O2 (NMC) cathodes, without protective coating, in three different aqueous electrolytes, i.e., salt-in-water, water-in-salt, and molecular crowding electrolytes. The latter two are the widely reported “water-deficient electrolytes.” LFP cycled in the molecular crowding electrolyte exhibits the best cycle life in both symmetric and full cells owing to the stable crystal structure. Mn dissolution and surface reduction accelerate the capacity decay of LMO in water-rich electrolyte. On the other hand, the bulk structural collapse leads to the degradation of NMC cathodes. LMO demonstrates better full-cell performance than NMC in water-deficient aqueous electrolytes. LFP is shown to be more promising than LMO and NMC for long-cycle-life ALIB full cells, especially in the molecular crowding electrolyte. However, none of the aqueous electrolytes studied here provide enough battery performance that can compete with conventional non-aqueous electrolytes. This work reveals the degradation mechanisms of olivine, spinel, and layered cathodes in different aqueous electrolytes and yields insights into improving electrode materials and electrolytes for ALIBs.
Effects of interleukin-15 on autophagy regulation in the skeletal muscle of mice
Authors: Tanaka Minoru , Sugimoto Ken , Akasaka Hiroshi , Yoshida Shino , Takahashi Toshimasa , Fujimoto Taku , Xie Keyu , Yasunobe Yukiko , Yamamoto Koichi , Hirabayashi Takumi , Nakanishi Ryosuke , Fujino Hidemi , Rakugi Hiromi
Published: January 2024

IL-15 gene deficiency can decrease autophagy induction. However, although IL-15 overexpression induced a decrease in muscle mass, it led to an improvement in muscle quality. Based on these results, understanding the role of IL-15 in regulating autophagy pathways within skeletal muscle may lead to the development of therapies for the autophagy-induced regulation of skeletal muscle mass and cellular quality control.
Metabolic underpinnings of cancer-related fatigue
Authors: Zhang Xinyi , Perry Rachel J.
Published: January 2024

Cancer-related fatigue (CRF) is one of the most prevalent and detrimental complications of cancer. Emerging evidence suggests that obesity and insulin resistance are associated with CRF occurrence and severity in cancer patients and survivors. In this narrative review, we analyzed recent studies including both preclinical and clinical research on the relationship between obesity and/or insulin resistance and CRF. We also describe potential mechanisms for these relationships, though with the caveat that because the mechanisms underlying CRF are incompletely understood, the mechanisms mediating the association between obesity/insulin resistance and CRF are similarly incompletely delineated. The data suggest that, in addition to their effects to worsen CRF by directly promoting tumor growth and metastasis, obesity and insulin resistance may also contribute to CRF by inducing chronic inflammation, neuroendocrinological disturbance, and metabolic alterations. Furthermore, studies suggest that patients with obesity and insulin resistance experience more cancer-induced pain and are at more risk of emotional and behavioral disruptions correlated with CRF. However, other studies implied a potentially paradoxical impact of obesity and insulin resistance to reduce CRF symptoms. Despite the need for further investigation utilizing interventions to directly elucidate the mechanisms of cancer-related fatigue, current evidence demonstrates a correlation between obesity and/or insulin resistance and CRF, and suggests potential therapeutics for CRF by targeting obesity and/or obesity-related mediators.
Blueberry anthocyanins improve liver fibrosis by regulating NCOA4 ubiquitination through TRIM7 to affect ferroptosis of hepatic stellate cells
Authors: Liu Likun , Du Jinhui , Fan Haiqing , Yu Yue , Luo Yilin , Gu Fang , Yu Hui , Liao Xin
Published: January 2024

This was the first study to demonstrate that anthocyanins can improve the progression of liver fibrosis by promoting hepatic stellate cell (HSC) ferroptosis. Anthocyanins could affect the content of Fe2+ by promoting ferroautophagy in HSCs, thereby promoting the level of ferroptosis. This study demonstrates for the first time that anthocyanins can inhibit the expression of TRIM7 and then affect the ubiquitination of NCOA4 to regulate the level of ferritin autophagy and ferroptosis.
Plasma KL-6 as a Potential Biomarker for Bronchopulmonary Dysplasia in Preterm Infants
Authors: Radulova Petya , Boncheva Margaritka , Nachev Gencho , Slancheva Boriana , Dimitrova Violeta
Published: January 2024

Background. KL-6 is a biomarker of interstitial lung injury and increases during repair. Aim. Our aim was to determine the predictive value of plasma KL-6 for the development of bronchopulmonary dysplasia (BPD) in preterm infants. Methods. Ninety-five extremely preterm infants (EPIs), born at <28 gestational age (GA), were divided into two main BPD groups as follows: the moderate/severe and the no/mild group. KL-6 was analyzed on days 7 and 14. Binary logistic regression analyses and ROC curve analyses were performed. Results. Infants <26 + 0 weeks’ GA have higher mean KL-6 than infants >25 + 6 weeks’ GA on 7 and 14 days (335 vs. 286 U/ml and 378 vs. 260 U/ml; p=0.005 and 0.018, respectively). In the binary regression model at KL-6 day 7, three of the prognostic factors remained significant—mechanical ventilation OR: 10.38 (95% CI: 3.57–30.14), PDA OR: 6.39 (95% CI: 0.87–46.74), and KL-6 OR: 4.98 (95% CI: 1.54–16.08). The AUC was 0.86 with a sensitivity and specificity of 79% at a cutoff value ≥0.34. In the binary regression model at KL-6 day 14, six of the prognostic factors were significant—PDA OR: 23.34 (95% CI: 2.14–254.24), KL-6 OR: 13.59 (95% CI: 3.19–57.96), GA OR: 4.58 (95% CI: 1.16–18.06), mechanical ventilation OR: 4.45 (95% CI: 1.23–16.16), antenatal steroids OR: 0.19 (95% CI: 0.04–0.95), and gender (female OR: 0.30 (95% CI 0.08–1.12)). The AUC was 0.91, and the sensitivity and accuracy for a cutoff ≥0.37 were 89% and 85%, respectively. Conclusion. KL-6 could be a useful screening biomarker for early detection of infants at increased risk for developing BPD.
Real-Time Frequency-Tracking Method Based on Interpolated Kalman Filter Using Vibration and Surface Noise
Authors: Li Chengcheng , Wan Yuan , Pan Pingheng , Hu Bian , Zhang Junhao
Published: January 2024

The variation of frequency is a significant indicator of the operation status of rotating machinery. Generally, the frequency is extracted and tracked in real-time based on the vibration signal produced by the rotating machinery. However, various interferences generated from contact sampling and transmitting result in difficulty in obtaining the frequency correctly in real-time from the vibration. To solve this problem, this paper presents an interpolated Kalman filter (IKF) based on the vibration and surface noise signals for real-time frequency tracking. First, the cross-correlation operation is performed on the vibration and surface noise signals sampled synchronously to enhance the energy concentration. After that, a frequency search procedure is carried out to calculate the input of the tracking task. Finally, an IKF-based frequency lock procedure is applied to eliminate the interferences and track the frequency in real time. Besides, a correction procedure is added to prevent the measurement process from tracking the frequency incorrectly. The performance of the proposed method is verified by the experiments based on an ARM-based test bench using standard signals and actual test signals.
Estimating Total Organic Carbon (TOC) Content and Porosity of the Ranikot Formation in the Central Indus Basin, Pakistan, Using Seismic Inversion and Well Log Analysis
Authors: Ehsan Muhsan , Zaheer Abdul Moiz , Abbasi Mehboob Ul Haq
Published: January 2024

An approach is proposed to improve modeling for shale gas reservoirs, integrating key parameters such as total organic carbon (TOC) and porosity. Seismic inversion uses seismic reflection data and well-log information to improve geological and geophysical interpretation and estimate rock properties with high-resolution subsurface acoustic impedance, including low and high frequencies. The Ranikot Formation in the Central Indus Basin, Pakistan, is a Paleocene-age formation with the potential to act as reservoir, seal, and source rock. The porosity of the Lower Ranikot reservoir in the Mehar Block was calculated using seismic inversion analysis with the Mehar-02 well. The petrophysical analysis yielded an effective porosity of 5.8%. Similarly, when calculated using seismic inversion, the porosity fell within the 5.5%–6.0% range. Determining the TOC content is crucial in evaluating unconventional shale resources. Petrophysical approaches, such as the ΔlogR method, offer a fast, convenient, and cost-effective means of estimating TOC from well logs. This method is commonly used in conventional source rock evaluation and applied to unconventional resource play evaluation. On the other hand, seismic inversion techniques were used to conduct TOC analysis in the absence of core data in order to estimate the source potential of the Upper Ranikot Formation. To estimate the TOC log for the Upper Ranikot shales in the Mehar Block, the Passey equation was used on the well logs of the Mehar-02 well. The estimated TOC for the Upper Ranikot shales is around 2.0%, which falls within the fair TOC range.
The Multisensor Data Fusion Method Based on Improved Fuzzy Evidence Theory in the Coal Mine Environment
Authors: Wang Lei , Fu Chenyan , Qi Junyan
Published: January 2024

An enhanced evidence theory-based multisensor data fusion technique is presented to address the problem of poor data fusion caused by an unknown interference in the fully automated mining face multisensor system of a coal mine. Initially, the set of all measurement values is considered as the identification framework, and the principles of fuzzy mathematics are applied to introduce the membership function. This leads to the proposal of a novel method for calculating mutual support among multiple sensors. Furthermore, the basic belief assignment (BBA) in evidence theory is determined by measuring the confidence distance between sensors. Subsequently, a divergence measure is employed to assess the level of conflict and difference between BBA functions, which serves as an indicator of their credibility. The credibility of BBA functions is further adjusted by calculating their information volume using Shannon entropy. This adjustment aims to increase the weight of BBA functions that exhibit less conflict with other BBA functions. Ultimately, the fusion result is obtained through an evidence combination rule based on a conflict allocation. The numerical experimental results demonstrate that the proposed approach achieves higher accuracy, better robustness, and generality compared to the existing methods.
Multiobjective Optimization of Composite Material Seat Plate for Mortar Based on the Hybrid Surrogate Model
Authors: Wang Fengfeng , Xu Chundong , Li Lei
Published: January 2024

As an important force transmission component of mortars, the seat plate affects some core indicators of mortars such as range, shooting accuracy, and maneuverability. In order to withstand huge impact loads, the seat plate was previously made of metal, which accounts for approximately 30%–45% of the total weight of the gun. The drawbacks of the heavy weight of the seat plate, which are not conducive to transportation and transfer, run counter to the current direction of the mortar’s lightweight development. The application of composite materials can greatly reduce the weight of the seat plate, but it exacerbates the contradiction between the mobility and combat effectiveness of mortars. In order to achieve the best match between mortar stability and maneuverability, a multiobjective optimization of composite material layers for seat plates is proposed, utilizing the designability of composite material layers. First, a fiber continuity model based on dropout sequence is adopted to solve the problems existing in the design of inherent continuity classes for composite layered fibers. Second, a hybrid surrogate model that considers the composite material seat plate quality, structural strength, shooting stability, shooting accuracy, and various working conditions is considered. Then, in order to improve the optimization efficiency and robustness of the algorithm, a multiobjective optimization algorithm based on the Chebyshev combination pattern is used to solve the mixed surrogate model. Finally, the optimization results are comprehensively evaluated against the optimization objectives. Research has shown that the method proposed in this article can effectively solve the time‐consuming problem of multiobjective optimization, improve the accuracy of hybrid surrogate models, and meet the expected requirements of multiobjective optimization of composite material seat plates. While ensuring shooting stability, the weight of the seat plate is reduced by 18.43% compared to the metal seat plate, which has important application value for lightweight design of mortars.