bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effectiveness of nature-based walking interventions in improving mental health in adults: a systematic review
Authors: Ma Jingni , Lin Peilin , Williams Joanne 
Published: August 2023

AbstractNature-based walking interventions represent a low-cost, eco-friendly activity, designed to assist people in maintaining physical well-being and improving their mental-health status. This systematic review aims to evaluate the evidence regarding the effectiveness of nature-based walking interventions in the improvement of mental health outcomes in adults. This paper draws upon Applied Social Sciences Index & Abstracts (ASSIA), PsycINFO, MEDLINE, EMBASE, the Web of Science Core Collection, Doctoral thesis databases (ProQuest), and manual searches. Due to the heterogeneity of the eligible studies, a narrative synthesis was employed. The present review includes 1,209 adult participants, of whom 336 were female; it also involves 17 discrete studies. The evidence from this systematic review suggests that nature-based walking interventions can indeed improve adults’ moods, sense of optimism, mental well-being, and nature connectedness. They simultaneously mitigate stress, anxiety, and negative rumination. In addition, compared with urban walking, nature-based walking interventions may bring greater benefits vis-à-vis anxiety and rumination. This review contributes to the synthesis of evidence for nature-based walking interventions, and identifies several research gaps around the topic. In clinical practice, nature-based interventions may be used to relieve one’s negative mood, stress, and anxiety. To enhance treatment efficacy, however, they should be combined with formal modes of psychotherapy.
The role of pyroptosis-related lncRNA risk signature in ovarian cancer prognosis and immune system
Authors: Wu Yanling , Liang Lei , Li Qin , Shu Lilu , Wang Peter , Huang Shufeng 
Published: August 2023

AbstractOvarian cancer is a leading cause of death in females with gynecologic cancers. Pyroptosis is a relatively new discovered programmed cell death that is believed to be associated with inflammation. However, studies on pyroptosis-related lncRNAs in ovarian cancer are limited. In this study, we identified 29 pyroptosis-related genes and screened out 72 pyroptosis-related lncRNAs. Furthermore, the 72 lncRNAs were eliminated to 2 survival-related lncRNAs using Cox regression and Lasso regression to build an ovarian cancer prognostic prediction signature and were further validated on the test set. We adopted a riskscore from the two-gene signature, and the survival in low-risk group was higher than the high-risk group. Functional enrichment analysis indicated that the differentially expressed genes (DEGs) between two risk groups were associated with tumor immunity. This study implies that pyroptosis-related genes are closely related to tumor immunity and could be potential therapeutic factors for ovarian cancer treatment.
Classification and function of γδT cells and its research progress in anti-glioblastoma
Authors: Zhao Yujuan , Zhu Renhong , Wang Yashu , Wang Keqiang 
Published: August 2023

AbstractHuman peripheral blood T lymphocytes are classified into alpha–beta T (αβΤ) cells and gamma–delta T (γδΤ) cells based on the difference in T cell receptors (TCRs). αβT cells are crucial for the acquired immune response, while γδΤ cells, though only a small subset, can recognize antigenic substances. These antigens do not need to be processed and presented and are not restricted by MHC. This distinguishes γδΤ cells from αβT cells and highlights their distinct role in innate immunity. Despite their small number, γδΤ cells hold significant significance in anti-tumor, anti-infection and immune regulation. Glioblastoma (GBM) represents one of the most prevalent malignant tumors within the central nervous system (CNS). Surgical resection alone proves to be an ineffective method for curing this type of cancer. Even with the combination of surgical resection, radiotherapy, and chemotherapy, the prognosis of some individuals with glioblastoma is still poor, and the recurrence rate is high. In this research, the classification, biological, and immunological functions of γδT cells and their research progress in anti-glioblastoma were reviewed.
Heat and shear stability of particle stabilised foams for application in gluten-free bread
Authors: Schmid T. , Leue-Rüegg R. , Müller N. 
Published: August 2023

AbstractBread forms an integral part of the daily diet in many cultures worldwide. At the same time, a significant number of people try to avoid wheat-based products for either health reasons or due to personal preferences. The absence of a protein network in gluten free bread affects its structure, taste, texture and shelf-life. This paper suggests a technological solution to this issue that uses a pre-foamed mass of gluten free raw materials which is mixed with the bread’s ingredients, then kneaded and baked to form a high quality gluten free bread. To survive the high shear stresses during kneading and temperature increase during baking, the foam requires exceptional stability. This stability was achieved through particle stabilisation of the bubble interfaces. Both of the tested foams (with and without particles) exhibited thermal stability up to 80 °C. However, resistance to shear stresses was higher in the particle stabilised foams. Of all the tested particles, linseed press cake and banana powder led to the best results. In conclusion, particle stabilised foams seem very well suited to applications in gluten free baked goods. Further application potential is seen for vegan foamed desserts.
Biosynthesis of magnesium oxide nanoparticles using Hagenia abyssinica female flower aqueous extract for characterization and antibacterial activity
Authors: Hirphaye Belete Yilma , Bonka Nafikot Berhanu , Tura Alemu Mekonnen , Fanta Gada Muleta 
Published: August 2023

AbstractThe present study deals with the biosynthesis of magnesium oxide nanoparticles using the Hagenia abyssinica female flower aqueous extract. The prepared MgO NPs were characterized by visual observation, UV–Vis, XRD, FTIR, and SEM studies. Optimum parameters such as plant extract volume (25 mL), temperature (60 ℃), pH (12), precursor concentration (1 mM), reaction time (120 min), and the formation of the MgO NPs in the colloidal solution were monitored by a UV–Vis spectrophotometer. XRD patterns of MgO NPs confirmed the face-centered cubic structure and average crystallite size of NPs at 12.8 nm. The FTIR spectra depicted a peak at 407 cm−1, which corresponds to the stretching vibration of MgO and is the characteristic peak for MgO NPs. SEM confirms spherical morphology, and the overall size of MgO NPs ranges from 10 to 40 nm. The antibacterial activity of synthesized MgO NPs was determined by the agar-well-diffusion method, which found that nanoparticles have significant antibacterial activity zone of inhibition against Staphylococcus aureus (27 ± 0.28 mm) and against Escherichia coli (15 ± 0 mm).
Mechanisms Linking Physical Activity with Psychiatric Symptoms Across the Lifespan: A Systematic Review
Authors: Nguyen Ho Phuong Thuy , Ha Pham Bich Tram , Tong Thao , Bramer Wichor M. , Hofman Amy , Lubans David Revalds , Vernooij Meike W. , Rodriguez-Ayllon María 
Published: August 2023

Abstract
Background
Physical activity has been suggested as a protective factor against psychiatric symptoms. While numerous studies have focused on the magnitude of physical activity’s effect on psychiatric symptoms, few have examined the potential mechanisms.

Objective
The current review aimed to synthesize scientific evidence of the mechanisms through which physical activity might reduce psychiatric symptoms across the lifespan.

Methods
We included articles that were published before March 2022 from five electronic databases (MEDLINE, Web of Science, PsycINFO, Embase, and Cochrane). A qualitative synthesis of studies was conducted. The risk of bias assessment was performed using The Joanna Briggs Institute Critical Appraisal Tool for Systematic Reviews. Studies were included if they explored the possible mechanisms through which physical activity influences psychiatric symptoms (i.e., internalizing and externalizing symptoms) across the lifespan.

Results
A total of 22 articles were included (three randomized controlled trials, four non-randomized controlled trials, three prospective longitudinal studies, and 12 cross-sectional studies). Overall, most of the studies focused on children, adolescents, and young adults. Our findings showed that self-esteem, self-concept, and self-efficacy were the only consistent paths through which physical activity influences psychiatric symptoms (specifically depressive and anxiety symptoms) across the lifespan. There were insufficient studies to determine the role of neurobiological mechanisms.

Conclusions
Overall, future physical activity interventions with the purpose of improving mental health should consider these mechanisms (self-esteem, self-concept, self-efficacy) to develop more effective interventions.
Clinical Trial Registration: The protocol of this study was registered in the PROSPERO database (registration number CRD42021239440) and published in April 2022.
Idempotent set-theoretical solutions of the pentagon equation
Authors: Mazzotta Marzia 
Published: August 2023

AbstractA set-theoretical solution of the pentagon equation on a non-empty set X is a function $$s:X\times X\rightarrow X\times X$$

s
:
X
×
X
→
X
×
X

satisfying the relation $$s_{23}\, s_{13}\, s_{12}=s_{12}\, s_{23}$$

s
23

s
13

s
12

=

s
12

s
23

, with $$s_{12}=s\times \,{{\,\textrm{id}\,}}_X$$

s
12

=
s
×

id

X

, $$s_{23}={{\,\textrm{id}\,}}_X \times \, s$$

s
23

=

id

X

×

s

and $$s_{13}=({{\,\textrm{id}\,}}_X\times \, \tau )s_{12}({{\,\textrm{id}\,}}_X\times \,\tau )$$

s
13

=

(

id

X

×

τ
)

s
12

(

id

X

×

τ
)

, where $$\tau :X\times X\rightarrow X\times X$$

τ
:
X
×
X
→
X
×
X

is the flip map given by $$\tau (x,y)=(y,x)$$

τ
(
x
,
y
)
=
(
y
,
x
)

, for all $$x,y\in X$$

x
,
y
∈
X

. Writing a solution as $$s(x,y)=(xy,\theta _x(y))$$

s

(
x
,
y
)

=
(
x
y
,

θ
x

(
y
)

)

, where $$\theta _x: X \rightarrow X$$

θ
x

:
X
→
X

is a map, for every $$x\in X$$

x
∈
X

, one has that X is a semigroup. In this paper, we study idempotent solutions, i.e., $$s^2=s$$

s
2

=
s

, by showing that the idempotents of X have a crucial role in such an investigation. In particular, we describe all such solutions on monoids having central idempotents. Moreover, we focus on idempotent solutions defined on monoids for which the map $$\theta _1$$

θ
1

is a monoid homomorphism.
Novel intuitionistic fuzzy Aczel Alsina Hamy mean operators and their applications in the assessment of construction material
Authors: Hussain Abrar , Wang Haolun , Ullah Kifayat , Pamucar Dragan 
Published: August 2023

AbstractAggregation operators (AOs) are utilized to overcome the effects of attributes under some specific degree of weight in the decision-making (DM) process. The AOs have a large capacity to deal with uncertain and unpredictable information in multi-attribute decision-making (MADM) problems. The Hamy mean (HM) aggregation tools are well-known aggregation models, which are utilized to define correlation among different input arguments adequately. The intuitionistic fuzzy (IF) sets (IFS) can express unpredictable and vague information. The Aczel Alsina aggregation expressions are extensions of triangular norms. Recently, Aczel Alsina aggregation tools attained a lot of attentions from numerous research scholars. By inspiring the robustness and reliability of Aczel Alsina aggregation tools, we expose some appropriate operations of Aczel Alsina expressions under consideration of IF information. In this manuscript, we developed an intuitionistic fuzzy Aczel Alsina HM (IFAAHM) and an intuitionistic fuzzy Aczel Alsina weighted HM (IFAAWHM) operator. We also expressed the theory of Dual HM (DHM) tools and established a series of new approaches including intuitionistic fuzzy Aczel Alsina Dual HM (IFAADHM) and intuitionistic fuzzy Aczel Alsina weighted Dual HM (IFAAWDHM) operators. Some reliable characteristics and special cases of our derived approaches are also presented. The authors solved an application of a MADM technique under consideration of our derived approaches. To check the reliability and dependency of our derived mythologies, we gave an experimental case study to evaluate a desirable construction material based on some specific criteria of different Alternatives. To see the advantages and compatibility of our derived approaches, by comparing the results of existing approaches with the results of currently discussed AOs.
A two-stage multiobjective evolutionary ensemble learning for silicon prediction in blast furnace
Authors: Li Qiang , Zhang Jingchuan , Wang Wenhao , Wang Xianpeng 
Published: August 2023

AbstractSilicon content of molten iron is an important indicator in the blast furnace ironmaking process. Accurate prediction of silicon content is very important for monitoring the operating condition of the blast furnace and the quality of the molten iron. However, accurate and effective online prediction of silicon content is a challenging task due to the complex and high-dimensional nonlinear relationship between silicon content and process variables. Therefore, a two-stage multiobjective evolutionary ensemble learning algorithm is proposed to achieve a high-accuracy and low-complexity prediction model using support vector machine (SVR) as the base learner. In the first stage, a non-dominated sorting differential evolution algorithm with dynamic resource allocation (DRA-NSDE) is proposed to generate a set of non-dominated solutions (SVRs) with the objectives of accuracy and complexity. In the second stage, a stacking method based on clustering and differential evolution (CDE-Stacking) is proposed to select base learners with better diversity and construct the ensemble model. The effectiveness of the proposed DRA-NSDE and CDE-Stacking strategies is verified through a series of numerical experiments. The experimental results show that the proposed algorithm outperforms the rival methods on both the UCI benchmark data set and the actual blast furnace data set. In addition, the analysis of model complexity shows that the proposed model can achieve higher prediction accuracy with relatively low model complexity, which indicates that the algorithm is very suitable for the online prediction of silicon content in actual blast furnace ironmaking process.
Boosting of fruit choices using machine learning-based pomological recommendation system
Authors: Dutta Monica , Gupta Deepali , Juneja Sapna , Shah Asadullah , Shaikh Asadullah , Shukla Varun , Kumar Mukesh 
Published: August 2023

AbstractPomology, also known as fruticulture, is a significant contributor to the economies of many nations worldwide. While vertical farming methods are not well-suited for fruit cultivation, substrate-based cultivation is commonly practiced. Vertical farming methods use no soil for cultivation of the plants, and the cultivation is done in vertically stacked layers. Therefore, smaller herbs are best suited for such cultivation, whereas, the majority of the fruit trees are big and woody. Therefore, vertical farming methods are not well suited for fruit trees. However, to maximize fruit production, smarter substrate cultivation methods are needed. Utilizing remote sensing techniques, such as Internet of Things (IoT) devices, agriculture sensors, and cloud computing, allows for precision agriculture and smart farming in autonomous systems. Nevertheless, a lack of understanding of fruit nutrient requirements, growing conditions, and soil health conditions can result in reduced fruit production. To address these challenges, this paper proposes an intelligent model based on machine learning that recommends the best fruit to grow based on prevailing soil and climatic conditions. The system is trained on a dataset that includes details on eleven different fruits, such as Nitrogen (N), Phosphorous (P), Potassium (K), temperature, humidity, pH, and rainfall. The model takes into account the soil type and nutrient contents to recommend the most suitable fruit to grow in the prevailing climate. To enhance the model's efficiency, two novel techniques, Gradient-based Side Sampling (GOSS) and Exclusive Feature Bundling (EFB), have been incorporated. The results show that the proposed system has achieved 99% accuracy in recommending the right fruit based on the given environmental conditions. As a result, this system has the potential to significantly improve the profitability of the pomology industry and boost national economies.
Modeling and Simulation of Dynamics in Soft Robotics: a Review of Numerical Approaches
Authors: Qin Longhui , Peng Haijun , Huang Xiaonan , Liu Mingchao , Huang Weicheng 
Published: August 2023

Abstract

Purpose of review

In this review, we briefly summarize the numerical methods commonly used for the nonlinear dynamic analysis of soft robotic systems. The underlying mechanical principles as well as the geometrical treatment tailored for soft robots are introduced with particular emphasis on one-dimensional models. Additionally, the review encompasses three-dimensional frameworks, available simulation packages, and various types of interaction models, shedding light on the design, actuation, motion control, and internal and external forces of soft robots.

Recent findings

Reduced-order models can offer high efficiency in characterizing nonlinear deformations, allowing convenient tailoring based on specific structural and material configurations. For pursuing high simulation accuracy and detailed mechanics, the finite element method proves to be a valuable tool through numerous off-the-shelf platforms. Furthermore, machine learning has emerged as a promising tool to effectively address the challenges within the mechanics community.

Summary

A wide range of kinematic and dynamic numerical models is available for simulating the behaviors of soft robots, offering exceptional adaptability to different geometries and structures based on existing modeling theories and numerical solution algorithms. However, the trade-off between computational complexity and simulation accuracy remains a challenge in achieving fast, accurate, and robust control of soft robots in complex environments.
The (in-)visibility of difference: gay and lesbian identities and the German police
Authors: Staller Mario S. , Koerner Swen , Wilkes Rachel 
Published: August 2023

AbstractWhile modern police organizations have included diversity in their portfolio of guiding orientations, there has been little research on the sexual identity of police officers and their perceptions in Germany. Based on current scientific discourses on the construction and impact of human categories, this article provides an explorative empirical-qualitative analysis of views, perceptions, and experiences of German police officers with gay and lesbian sexual identities. We conducted in-depth semi-structured interview with officers who identified themselves as gay or lesbian (n = 8). Applying a reflexive thematic approach to data analysis, the results point to an internal police dominance of a two-gender identity concept, in which heterosexual masculinity forms the guiding value and third possibilities remain largely invisible. The findings offer a reason to critically reflect on the existing dominance of heterosexually formatted distinctions and thus to further expand German police organization’s claim to diversity.
ANOTHER LOOK AT A SENSIBLE FISCAL POLICY FOR THE SHARP RISE IN GOVERNMENT DEBT
Authors: Capie Forrest , Chapman Meyrick , Marsh Chris , Wood Geoffrey 
Published: August 2023

Abstract
This paper weighs possible medium-term responsible policy choices to the extraordinary expansion of government spending in response to the COVID-19 outbreak. The paper is divided into two parts. In part 1 of the paper, we look at conventional debt sustainability and question whether conventional rules created during a period of high interest rates and high inflation remain relevant. Current and future conditions support a case for government debt/GDP to remain elevated compared to history, conditional upon limited state interference in the economy to allow appropriate allocation of capital and resources. In part 2, we consider the historical experience of the United Kingdom. History shows the country had several examples of rapid, large-scale expansion of government debt relative to the size of the economy. On each occasion, the elevated level of debt-to-GDP was later reduced by a combination of relatively benign factors, including commitment to low inflation and sound monetary system. This supported the financial probity of the UK government and allowed it to continue to borrow unimpeded.
Investigation of Under‐Ice Phytoplankton Growth in the Fully‐Coupled, High‐Resolution Regional Arctic System Model
Authors: Clement Kinney Jaclyn , Frants Marina , Maslowski Wieslaw , Osinski Robert , Jeffery Nicole , Jin Meibing , Lee Younjoo J. 
Published: August 2023

AbstractIn July 2011, observations of a massive phytoplankton bloom in the ice‐covered waters of the western Chukchi Sea raised questions about the extent and frequency of under‐ice phytoplankton growth and its contribution to the carbon budget in the Arctic Ocean. To address some of these questions, we use the fully‐coupled, high‐resolution Regional Arctic System Model to simulate Arctic marine biogeochemistry over a 30‐year period. Our results demonstrate the presence of extensive under‐ice phytoplankton growth in the western Arctic (WA) in summer. In addition, similar growth, yet of lower magnitude, occurs annually in the eastern Arctic (EA). We investigate the critical levels of nitrate concentration and photosynthetically available radiation (PAR) that are necessary for under‐ice phytoplankton growth to occur. Our results show that while the majority of ice‐covered Arctic waters have sufficient surface nitrate levels to sustain growth, PAR reaching the ocean surface through the sea ice in early summer only exceeds critical levels in the WA. We therefore conclude that the EA high chlorophyll‐a concentrations shown in our simulations did not develop under sea ice, but were instead, at least in part, formed in open waters upstream and subsequently advected by ocean currents beneath the sea ice.
Observational Estimates of Turbulence Parameters in the Atmospheric Surface Layer of Landfalling Tropical Cyclones
Authors: Ming Jie , Zhang Jun A. , Li Xin , Pu Zhaoxia , Momen Mostafa 
Published: August 2023

AbstractThis study analyzes observations collected by multilevel towers to estimate turbulence parameters in the atmospheric surface layer of two landfalling tropical cyclones (TCs). The momentum flux, turbulent kinetic energy (TKE) and dissipation rate increase with the wind speed independent of surface types. However, the momentum flux and TKE are much larger over land than over the coastal ocean at a given wind speed range. The vertical eddy diffusivity is directly estimated using the momentum flux and strain rate, which more quickly increases with the wind speed over a rougher surface. Comparisons of the eddy diffusivity estimated using the direct flux method and that using the friction velocity and height show good agreement. On the other hand, the traditional TKE method overestimates the eddy diffusivity compared to the direct flux method. The scaling coefficients in the TKE method are derived for the two different surface types to better match with the vertical eddy diffusivity based on the direct flux method. Some guidance to improve vertical diffusion parameterizations for TC landfall forecasts in weather simulations are also provided.