bluuebunny/crossref_metadata_2025 huggingface dataset:
Advancing inclusive innovation policy in the UK’s second-tier city-regions
Authors: Parsons Katherine , Delbridge Rick , Uyarra Elvira , Waite David , Huggins Robert , Morgan Kevin
Published: April 2024

The UK exhibits stark regional economic divides which have been a long running concern for policymakers. With the levelling up agenda taking shape, city-regions in the UK are developing innovation and business support policies in seeking to deliver on a range of goals from traditional productivity concerns to wider social and environmental imperatives. Drawing on interviews with key actors in the city-regions of Cardiff, Manchester and Glasgow, this paper points to an emerging directional change in innovation policy, yet we show that capacities to articulate and implement an inclusive innovation approach vary widely. The uneven landscape for innovation policy within each of the city-regions, in terms of the location of innovation assets but also the varied institutional and social legacies shaping innovation policy, is also brought into view. Central to the reshaping of innovation policy in all cases, however, are agents working in networks, fashioning narratives and marshalling data in efforts to mobilise new ways of practicing innovation policy within what remains a centralised approach to sub-national economic development.
Analysis of aged microplastics: a review
Authors: Shi Yanqi , Shi Linping , Huang Hexinyue , Ye Kefu , Yang Luming , Wang Zeena , Sun Yifan , Li Dunzhu , Shi Yunhong , Xiao Liwen , Gao Shixiang
Published: April 2024

Microplastics are emerging contaminants that undergo progressive aging under environmental conditions such as sunlight irradiation, mechanical forces, temperature variations, and the presence of biological organisms. Since aging modifies microplastic properties, such as their own toxicity and the toxicity of trapped pollutants, advanced methods to analyze microplastics are required. Here we review methods to analyze microplastic aging with focus on the aging process, qualitative identification, quantitative characterization, and chemometrics. Qualitative identification is done by mechanical techniques, thermal techniques, e.g., thermal degradation and gas chromatography–mass spectrometry, and spectral techniques, e.g., infrared, Raman, fluorescent, and laser techniques. Quantitative characterization is done by microscopy and mass spectrometry. Microplastic aging results in a series of surface physical changes, biofilm formation, chemical oxidation, thermal alternation, and mechanical deterioration. Changes in mechanical and thermal properties allow to differentiate aged microplastics. Infrared and Raman spectroscopy are rapid and sensitive for chemical identification of microplastics in complex environmental samples. Combining two techniques is preferable for accurate detection and categorization.
Enhancing urban blue-green landscape quality assessment through hybrid genetic algorithm-back propagation (GA-BP) neural network approach: a case study in Fucheng, China
Authors: Fan Ding , Maliki Nor Zarifah Binti , Yu Siwei , Jin Fengcheng , Han Xinyan
Published: April 2024

This study employs an artificial neural network optimization algorithm, enhanced with a Genetic Algorithm-Back Propagation (GA-BP) network, to assess the service quality of urban water bodies and green spaces, aiming to promote healthy urban environments. From an initial set of 95 variables, 29 key variables were selected, including 17 input variables, such as water and green space area, population size, and urbanization rate, six hidden layer neurons, such as patch number, patch density, and average patch size, and one output variable for the comprehensive value of blue-green landscape quality. The results indicate that the GA-BP network achieves an average relative error of 0.94772%, which is superior to the 1.5988% of the traditional BP network. Moreover, it boasts a prediction accuracy of 90% for the comprehensive value of landscape quality from 2015 to 2022, significantly outperforming the BP network’s approximate 70% accuracy. This method enhances the accuracy of landscape quality assessment but also aids in identifying crucial factors influencing quality. It provides scientific and objective guidance for future urban landscape structure and layout, contributing to high-quality urban development and the creation of exemplary living areas.
Synthesis of Reusable CNF/Ag2Se Films as Visible-Light-Driven Photocatalysts for Photocatalytic Degradation of MB
Authors: Hameed Talaat A. , Salama Ahmed , Nasr Rabab A.
Published: April 2024

In our study’s scenario, flexible films were fabricated from TEMPO-oxidized cellulose nanofibers and silver selenide (CNF/Ag2Se) as efficient membranes for the degradation of methylene blue (MB). Different concentrations of Ag2Se particles were in situ prepared in the presence of CNF. The in-situ synthesis of Ag2Se nanoparticles in the presence of CNF was reported as efficient technique for the formation of submicrosize Ag2Se particles with a narrow size distribution and homogeneous dispersion onto CNF. TEM analysis revealed that the nanofibers had uniform width and diameter, while XRD demonstrated single-phase orthorhombic β-Ag2Se formation. 3D-FESEM showed tiny root measurer values of 28, 30, and 32.56 nm in polymeric films with 2.5, 5, and 10% Ag2Se-filled CNF. Polymeric films had visible-driven-light photocatalytic activity because the band gap fell from 4.61 eV (UV area) to 2.71 eV (visible region). The composite’s photocatalytic performance was assessed by MB degradation. 10% of CNF/Ag2Se demonstrated maximal photocatalytic activity under simulated sunlight for 60 min, pH 9, and 3 g/L composite weight. The factorial design statistical analysis showed that MB dye photodegradation is mostly affected by irradiation time and dye concentration. Environmental, social, and economic factors are all considered, making this study suitable for implementing photocatalysis to large-scale water treatment systems, which is a key component of sustainability.
A fusion of machine learning and cryptography for fast data encryption through the encoding of high and moderate plaintext information blocks
Authors: Shafique Arslan , Mehmood Abid , Alawida Moatsum , Elhadef Mourad , Rehman Mujeeb Ur
Published: April 2024

Within the domain of image encryption, an intrinsic trade-off emerges between computational complexity and the integrity of data transmission security. Protecting digital images often requires extensive mathematical operations for robust security. However, this computational burden makes real-time applications unfeasible. The proposed research addresses this challenge by leveraging machine learning algorithms to optimize efficiency while maintaining high security. This methodology involves categorizing image pixel blocks into three classes: high-information, moderate-information, and low-information blocks using a support vector machine (SVM). Encryption is selectively applied to high and moderate information blocks, leaving low-information blocks untouched, significantly reducing computational time. To evaluate the proposed methodology, parameters like precision, recall, and F1-score are used for the machine learning component, and security is assessed using metrics like correlation, peak signal-to-noise ratio, mean square error, entropy, energy, and contrast. The results are exceptional, with accuracy, entropy, correlation, and energy values all at 97.4%, 7.9991, 0.0001, and 0.0153, respectively. Furthermore, this encryption scheme is highly efficient, completed in less than one second, as validated by a MATLAB tool. These findings emphasize the potential for efficient and secure image encryption, crucial for secure data transmission in rea-time applications.
Proximal intentions intentionalism
Authors: Tamburini Victor
Published: April 2024

According to a family of metasemantics for demonstratives called intentionalism, the intentions of speakers determine the reference of demonstratives. And according to a sub-family I call proximal intentions (PI) intentionalism, the intention that determines reference is one that occupies a certain place—the proximal one—in a structure of intentions. PI intentionalism is thought to make correct predictions about reference where less sophisticated forms of intentionalism make the wrong predictions. In this article I argue that this is an illusion: PI intentionalism also suffers from predictive inadequacy. In Sect. 1, I present the problem of predictive inadequacy for intentionalism and an ad hoc response to it. In Sect. 2, I sketch a version of PI intentionalism that aims to provide the most principled response to this problem. In Sect. 3, I explain why PI intentionalism cannot solve the problem after all. In Sect. 4, I indicate where I think metasemanticists should go next.
Membrane-based inverse-transition purification facilitates a rapid isolation of various spider-silk elastin-like polypeptide fusion proteins from extracts of transgenic tobacco
Authors: Gruchow H. M. , Opdensteinen P. , Buyel J. F.
Published: April 2024

Plants can produce complex pharmaceutical and technical proteins. Spider silk proteins are one example of the latter and can be used, for example, as compounds for high-performance textiles or wound dressings. If genetically fused to elastin-like polypeptides (ELPs), the silk proteins can be reversibly precipitated from clarified plant extracts at moderate temperatures of ~ 30 °C together with salt concentrations > 1.5 M, which simplifies purification and thus reduces costs. However, the technologies developed around this mechanism rely on a repeated cycling between soluble and aggregated state to remove plant host cell impurities, which increase process time and buffer consumption. Additionally, ELPs are difficult to detect using conventional staining methods, which hinders the analysis of unit operation performance and process development. Here, we have first developed a surface plasmon resonance (SPR) spectroscopy-based assay to quantity ELP fusion proteins. Then we tested different filters to prepare clarified plant extract with > 50% recovery of spider silk ELP fusion proteins. Finally, we established a membrane-based purification method that does not require cycling between soluble and aggregated ELP state but operates similar to an ultrafiltration/diafiltration device. Using a data-driven design of experiments (DoE) approach to characterize the system of reversible ELP precipitation we found that membranes with pore sizes up to 1.2 µm and concentrations of 2–3 M sodium chloride facilitate step a recovery close to 100% and purities of > 90%. The system can thus be useful for the purification of ELP-tagged proteins produced in plants and other hosts.
The SpRY Cas9 variant release the PAM sequence constraint for genome editing in the model plant Physcomitrium patens
Authors: Calbry Julie , Goudounet Guillaume , Charlot Florence , Guyon-Debast Anouchka , Perroud Pierre-François , Nogué Fabien
Published: April 2024

Genome editing via CRISPR/Cas has enabled targeted genetic modifications in various species, including plants. The requirement for specific protospacer-adjacent motifs (PAMs) near the target gene, as seen with Cas nucleases like SpCas9, limits its application. PAMless SpCas9 variants, designed with a relaxed PAM requirement, have widened targeting options. However, these so-call PAMless SpCas9 still show variation of editing efficiency depending on the PAM and their efficiency lags behind the native SpCas9. Here we assess the potential of a PAMless SpCas9 variant for genome editing in the model plant Physcomitrium patens. For this purpose, we developed a SpRYCas9i variant, where expression was optimized, and tested its editing efficiency using the APT as a reporter gene. We show that the near PAMless SpRYCas9i effectively recognizes specific PAMs in P. patens that are not or poorly recognized by the native SpCas9. Pattern of mutations found using the SpRYCas9i are similar to the ones found with the SpCas9 and we could not detect off-target activity for the sgRNAs tested in this study. These findings contribute to advancing versatile genome editing techniques in plants.
Consumer responses to human-AI collaboration at organizational frontlines: strategies to escape algorithm aversion in content creation
Authors: Haupt Martin , Freidank Jan , Haas Alexander
Published: April 2024

Although Artificial Intelligence can offer significant business benefits, many consumers have negative perceptions of AI, leading to negative reactions when companies act ethically and disclose its use. Based on the pervasive example of content creation (e.g., via tools like ChatGPT), this research examines the potential for human-AI collaboration to preserve consumers' message credibility judgments and attitudes towards the company. The study compares two distinct forms of human-AI collaboration, namely AI-supported human authorship and human-controlled AI authorship, with traditional human authorship or full automation. Building on the compensatory control theory and the algorithm aversion concept, the study evaluates whether disclosing a high human input share (without explicit control) or human control over AI (with lower human input share) can mitigate negative consumer reactions. Moreover, this paper investigates the moderating role of consumers’ perceived morality of companies’ AI use. Results from two experiments in different contexts reveal that human-AI collaboration can alleviate negative consumer responses, but only when the collaboration indicates human control over AI. Furthermore, the effects of content authorship depend on consumers' moral acceptance of a company's AI use. AI authorship forms without human control lead to more negative consumer responses in case of low perceived morality (and no effects in case of high morality), whereas messages from AI with human control were not perceived differently to human authorship, irrespective of the morality level. These findings provide guidance for managers on how to effectively integrate human-AI collaboration into consumer-facing applications and advises to take consumers' ethical concerns into account.
Citalopram, an antipsychotic agent, induces G1/G0 phase cell cycle arrest and promotes apoptosis in human laryngeal carcinoma HEP-2 cells
Authors: Salama Mohammed , Ali Abeer , Ibrahim Fawziya A. R. , Elabd Seham
Published: April 2024

Human laryngeal squamous carcinoma (LSCC) is a common malignant tumor in the head and neck. Despite the recently developed therapies for the treatment of LSCC, patients’ overall survival rate still did not enhance remarkably; this highlights the need to formulate alternative strategies to develop novel treatments. The antitumor effects of antidepressant drugs such as citalopram have been reported on several cancer cells; however, they have yet to be investigated against LSCC. The current study was directed to explore the possible antitumor effects of citalopram on human laryngeal carcinoma cell lines (HEP-2). HEP-2 cells were cultured and treated with different doses of citalopram (50–400 µM) for 24, 48, and 72 h. The effects of citalopram on the viability of cancer cells were determined by the MTT assay. In addition, apoptosis and cell cycle analysis were performed by flow cytometry. Moreover, evaluation of the expression of proapoptotic and apoptotic proteins, such as cytochrome c, cleaved caspases 3 and 9, Bcl-2, and BAX, was performed by western blotting analysis. Our results revealed that citalopram significantly suppressed the proliferation of HEP-2 cells through the upregulation of p21 expression, resulting in the subsequent arrest of the cell cycle at the G0/G1 phase. Furthermore, citalopram treatment-induced HEP-2 cell apoptosis; this was indicated by the significant increase of cytochrome c, cleaved caspases 3 and 9, and BAX protein expression. On the contrary, Bcl-2 protein expression was significantly downregulated following treatment with citalopram. The ultrastructure studies were in accordance with the protein expression findings and showed clear signs of apoptosis with ring chromatin condensation upon treatment with citalopram. These findings suggest that citalopram’s anti-tumor activities on HEP-2 cells entailed stimulation of the intrinsic apoptotic pathway, which was mediated via Bcl-2 suppression.
Sleep Behaviors and the Shape of Subcortical Brain Structures in Children with Overweight/Obesity: A Cross-Sectional Study
Authors: Cadenas-Sanchez Cristina , Migueles Jairo H. , Torres-Lopez Lucia V. , Verdejo-Román Juan , Jiménez-Pavón David , Hillman Charles H. , Catena Andrés , Ortega Francisco B.
Published: April 2024

Objectives

To examine the relationship between sleep and subcortical brain structures using a shape analysis approach.

Methods

A total of 98 children with overweight/obesity (10.0 ± 1.1 y, 59 boys) were included in the cross-sectional analyses. Sleep behaviors (i.e., wake time, sleep onset time, total time in bed, total sleep time, sleep efficiency, and wakening after sleep onset) were estimated with wrist-worn accelerometers. The shape of the subcortical brain structures was acquired by magnetic resonance imaging. A partial correlation permutation approach was used to examine the relationship between sleep behaviors and brain shapes.

Results

Among all the sleep variables studied, only total time in bed was significantly related to pallidum and putamen structure, such that those children who spent more time in bed had greater expansions in the right and left pallidum (211–751 voxels, all p’s <0.04) and right putamen (1783 voxels, p = 0.03).

Conclusions

These findings suggest that more time in bed was related to expansions on two subcortical brain regions in children with overweight/obesity.
Introduction of the South American slipper limpet Crepipatella dilatata in Europe: Secondary spread in the Northeast Atlantic and first records for the Mediterranean Sea
Authors: Salvi Daniele , Smriglio Carlo , Garzia Matteo , Andreuccci Sarah , Mariottini Paolo
Published: April 2024

The slipper limpet Crepipatella dilatata, native to Chile and Argentina, was introduced in north-western Spain in 2005 and since then has spread to the Galician and Cantabrian coasts. In this work, we provide the first molecularly validated record of an established population of C. dilatata in central Portugal (Aveiro), and of reproductive individuals (i.e. brooding females) of C. dilatata in the Mediterranean Sea, from three Italian mussel farms (in eastern Sardinia and northern Adriatic). DNA barcoding and phylogenetic analyses based on mitochondrial markers indicate that limpets from Italian farms belong to the C. dilatata ‘clade1’, whereas limpets collected in Aveiro cluster within the C. dilatata ‘clade2’. All these limpets share the same COI haplotypes with introduced populations from Galicia. The arrival of C. dilatata to Europe is undoubtedly due to transoceanic live mussel trade from southern Chile to Galicia. Mussel trade and farming are also the most likely drivers for the post-border dispersal of C. dilatata from Spain to Portugal and to Italy. Several countries have a potential role as a hub for the primary and secondary dispersal of slipper limpets towards and within Europe. This calls the attention for future research focused on assessing the current occurrence and ecological impact of established populations of slipper limpets within and nearby mussel farms along the eastern Atlantic and Mediterranean coasts.
Comparative assessment of hydrochemical characterization and groundwater quality for irrigation in an autochthonous karst aquifer with the support of GIS: case study of Altinova, Turkey
Authors: Wani Alex Modi Lomoro , Abunada Ziyad , Yenilmez Firdes , Muhammetoglu Ayse , Muhammetoglu Habib
Published: April 2024

This study aims to present a comparative assessment of hydrochemical characterization and groundwater quality in karst aquifers with the support of GIS which is essential to correlate the source of water with climate and geology, and to evaluate suitability of water for various uses. The study area is the Altinova region in Turkey where intensive agricultural activities prevail and travertine covers 85% of the study area. A total of 25 groundwater wells were monitored by seasonal field measurements and extensive water quality analyses for a period of one year to establish correlation between groundwater quality, its source, regional climate, and geology. A comprehensive analysis was conducted to assess the groundwater's suitability for irrigation based on electrical conductivity, sodium adsorption ratio, sodium percentage, magnesium hazard, permeability index, residual sodium bicarbonate, Kelly’s ratio, and an irrigation water quality (IWQ) index. This multi-parameter evaluation was further integrated with geospatial analysis using ArcGIS, providing a detailed spatial understanding of hydrochemical variations across the area. Major cations and anions dominance were identified as Ca2+ > Na+ > Mg2+ > K+ and HCO3− > Cl− > SO42−, respectively. Spatial mapping identified high concentrations of Ca2+, TDS, TH, and SO42− in non-karstic areas, occasionally exceeding WHO guidelines. Nitrate concentrations displayed varied spatial distribution. The SAR values generally matched C2-S1 and C3-S1 classes, suggesting medium to high salinity risks and low sodium presence. Based on the IWQ index and observed correlations with total dissolved solids, the groundwater in Altinova’s karstic aquifer is considered suitable for irrigation, with salinization largely due to ionic interactions and geology. The presented comparative assessment provides a holistic approach for understanding hydrochemical characteristics of karst aquifers, and analyzing the impacts of natural factors and anthropogenic pollution sources on groundwater quality.
The Effect of Mindfulness-Based Stress Reduction Program on Stress and Quality of Life in Family Caregivers of Patients with Cancer: Randomized Controlled Trial
Authors: Türkoğlu Nihan , Kavuran Esin
Published: April 2024

Objectives

The study aimed to examine the effects of an online Mindfulness-Based Stress Reduction program on stress and quality of life levels of family caregivers of cancer patients.

Method

The study used a randomized controlled trial design with a pre-test (T1), follow-up (T2) and post-test (T3) which was conducted with 104 family caregivers of cancer patients. Data collection was conducted using the Caregiver and Patient Descriptive Information Form, Caregiver’s Stress Scale and The Caregiver Quality of Life Index Cancer Scale. T1 measurements were conducted for experimental (n = 50) and control groups (n = 54). After the 8-week online Mindfulness-Based Stress Reduction program of the experimental group, T2 measurements were taken for both groups. Four weeks later, the T3 measurement was collected for both experimental and control groups.

Results

A statistically significant difference over time was detected between the mean Caregiver’s Stress Scale scores of the experimental group in the T1, T2, and T3. There was no significant difference in the control group over time. A statistically significant difference was detected in the mean Caregiver Quality of Life Index Cancer Scale total score of the experimental group across T1, T2, and T3. When the scale pre-test mean scores were compared between the groups, no significant differences were detected for T1, but a statistically significant difference was found between the T2 and T3 scores.

Conclusion

In the study, it was determined that the online Mindfulness-Based Stress Reduction program had an effect on reducing stress and improving the quality of life.

Preregistration

The research was registered on http://clinicaltrials.gov (ID:NCT05831293).
Online Mindfulness-Based Intervention Program Improves Mental Health, Well-Being, and Productivity
Authors: Ogino Junya , Maruyama Takashi , Umene-Nakano Wakako , Maeno Takashi
Published: April 2024

Objectives

This study aimed to evaluate the effectiveness of the Intervention program of Mindfulness and Compassion against COVID-19 (IMACOCO), an online mindfulness-based intervention (MBI), in enhancing mindfulness, mental health, well-being, and productivity among working individuals during the COVID-19 pandemic. Additionally, the study examined the program’s efficacy in individuals directly impacted by the pandemic through a randomized controlled trial and pre-post program comparisons.

Method

Three hundred working adults, including office workers, educators, and medical welfare workers, were randomly allocated to the intervention or waiting control group. An 8-week online MBI program, with pre-, interim (4 weeks), and post-program (8 weeks) evaluations, was conducted via the Internet; standardized questionnaires were used to assess mindfulness, psychological distress, life satisfaction, and productivity. After the initial 8-week program, the waiting control group participated in the same program and evaluation surveys for pre-post comparisons.

Results

There were 99 participants in the intervention group and 111 in the control group. Significant increases in mindfulness (FFMQ) and life satisfaction (SWLS) as well as decrease in psychological distress (GHQ-12) were observed primarily in the intervention group (Cohen’s d = 0.18–0.52). Furthermore, the pre-post comparisons with 168 participants demonstrated significant improvements in productivity (Cohen’s d = 0.26), and stratified analysis revealed that participants affected by COVID-19 showed more pronounced benefits in mindfulness and life satisfaction than those who were unaffected.

Conclusions

Implementing an online MBI program (IMACOCO) can be a potent strategy to reduce mental stress and enhance overall well-being and resilience, in a disaster-prone world.

Preregistration

This study is not preregistered.
Fibrin glue mediated direct delivery of radiation sensitizers results in enhanced efficacy of radiation treatment
Authors: Nguyen Jane , Chandekar Akhil , Laurel Sophia , Dosanjh Jazleen , Gupta Keya , Le Justin , Hirschberg Henry
Published: April 2024

Purpose

Radiation therapy (RT) plays an important role in the treatment of glioblastoma multiforme (GBM). However, inherent intrinsic resistance of tumors to radiation, coupled with the need to consider the tolerance of normal tissues and the potential effects on neurocognitive function, impose constraints on the amount of RT that can be safely delivered. A strategy for augmenting the effectiveness of RT involves the utilization of radiation sensitizers (RS). Directly implanting RS-loaded fibrin glue (FG) into the tumor resection cavity would by-pass the blood brain barrier, potentially enhancing the impact of RT on tumor recurrence. This study investigated the ability of FG to incorporate and release, in non-degraded form, the radiation sensitizers 5-Fluorouracil (5FU) and Motexafin gadolinium (MGd).

Methods

FG layers were created in a 24-well plate by combining thrombin, fibrinogen, and 5FU or MGd. Supernatants from these layers were collected at various intervals and added to F98 glioma spheroid cultures in 96-well plates. Radiation was applied either before or after RS application as single or fractionated dosages. Spheroid growth was monitored for 14 days.

Results

Combined treatment of FG-released 5FU and RT significantly inhibited spheroid growth compared to RS or RT as a single treatment. As a free drug, MGd demonstrated its efficacy in reducing spheroid volume, but had diminished potency as a released RS. Fractionated radiation was more effective than single dose radiation.

Conclusion

Non-degraded RS was released from the FG for up to 72 h. FG-released 5FU greatly increased the efficacy of radiation therapy.
Are deep learning classification results obtained on CT scans fair and interpretable?
Authors: Ashames Mohamad M. A. , Demir Ahmet , Gerek Omer N. , Fidan Mehmet , Gulmezoglu M. Bilginer , Ergin Semih , Edizkan Rifat , Koc Mehmet , Barkana Atalay , Calisir Cuneyt
Published: April 2024

Following the great success of various deep learning methods in image and object classification, the biomedical image processing society is also overwhelmed with their applications to various automatic diagnosis cases. Unfortunately, most of the deep learning-based classification attempts in the literature solely focus on the aim of extreme accuracy scores, without considering interpretability, or patient-wise separation of training and test data. For example, most lung nodule classification papers using deep learning randomly shuffle data and split it into training, validation, and test sets, causing certain images from the Computed Tomography (CT) scan of a person to be in the training set, while other images of the same person to be in the validation or testing image sets. This can result in reporting misleading accuracy rates and the learning of irrelevant features, ultimately reducing the real-life usability of these models. When the deep neural networks trained on the traditional, unfair data shuffling method are challenged with new patient images, it is observed that the trained models perform poorly. In contrast, deep neural networks trained with strict patient-level separation maintain their accuracy rates even when new patient images are tested. Heat map visualizations of the activations of the deep neural networks trained with strict patient-level separation indicate a higher degree of focus on the relevant nodules. We argue that the research question posed in the title has a positive answer only if the deep neural networks are trained with images of patients that are strictly isolated from the validation and testing patient sets.
Bilinear sparse domination for oscillatory integral operators
Authors: Mattsson Tobias
Published: April 2024

In this paper, we prove bilinear sparse domination bounds for a wide class of Fourier integral operators of general rank, as well as oscillatory integral operators associated to Hörmander symbol classes $$S^m_{\rho ,\delta }$$

S

ρ
,
δ

m

for all $$0\le \rho \le 1$$

0
≤
ρ
≤
1

and $$0\le \delta < 1$$

0
≤
δ
<
1

, a notable example is the Schrödinger operator. As a consequence, one obtains weak (1, 1) estimates, vector-valued estimates, and a wide range of weighted norm inequalities for these classes of operators.
A Computational Investigation of the Influence of Seafloor Conditions on the Turbulent Flow Characteristics of an Autonomous Underwater Vehicle
Authors: Tabatabaei Malazi Mahdi , Tumse Sergen , Ozgoren Muammer , Sahin Besir
Published: April 2024

The effect of the seabed on the hydrodynamics of three-dimensional autonomous underwater vehicles (AUVs) varies according to the physical conditions of the place where AUVs interact with the environmental conditions. This study examines the hydrodynamics of an AUV resembling a torpedo model while taking the influence of the seabed surface as a function of the dimensionless distances (G/D) between the torpedo and the seabed. Reynolds numbers, varying from 1 × 104 to 8 × 104, were considered. These Reynolds numbers were associated with various seabed distances falling within 0.25 ≤ G/D ≤ 1.5. To perform the simulations, governing equations were utilized and incorporated with the k–ω SST turbulence model. It has been observed that when AUVs or torpedo models operate in close proximity to the seabed surface, several key hydrodynamic parameters and flow characteristics are affected. These include the pressure coefficient (Cp), drag coefficient (CD), overall flow structures, maneuverability, and performance of the torpedo model. As the AUV or torpedo model approaches the seabed surface, the symmetrical flow pattern deteriorates. This deterioration is associated with changes in vortical flow structures under the influence of seabed surfaces. Additionally, the intensity of the shear stress (τ) near the seabed surface gradually increases as the AUV or torpedo model gets closer to it. In summary, the proximity of AUVs or torpedo models to the seabed surface causes disruptions in the flow patterns, increased shear stress, and alterations in key hydrodynamic parameters, ultimately affecting the system's performance and behavior.
Event Ethnography to study the global negotiations on the treaty to end plastic pollution: dataset from the first session of negotiations (INC-1)
Authors: Cowan Emily
Published: April 2024

Plastics and their associated chemical pollution have emerged as a global threat. This recognition materialized in March 2022 with the adoption of a groundbreaking mandate among United Nations (UN) Member States, signaling the commencement of negotiations for a comprehensive treaty aimed at ending plastic pollution, encompassing the entire lifecycle. The first session of negotiations convened at the International Negotiating Committee (INC-1) in Punta del Este, Uruguay from November 28th–December 2nd, 2022, from there, four other negotiation sessions have either convened or will, with the expected conclusion in December 2024. The current study introduces a methodology for systematically observing and documenting global agreement-making. It utilizes a dataset from the first session of negotiations to explore the event ethnography (EE) methodology for following Multilateral Environmental Agreements (MEA). This paper aims to inspire and guide researchers in employing EE, recognizing its efficacy in navigating the complexities of the extensive Global Plastics Treaty (GPT) negotiations and promoting collaborative efforts for a comprehensive understanding of the process. EE is a method increasingly recognised to study multilateral international negotiations within the science-policy nexus to examine emerging obstacles, trends, power dynamics, and actors (both state and non-state) in action within the negotiations. Finally, a dataset is presented from INC-1 through a practical Excel document; the article then demonstrates one example of how the dataset can be employed to enhance comprehension of the negotiators and observers influencing the GPT negotiations.
Sex differences in Parkinson’s disease-related non motor symptoms: a focus on sleep problems
Authors: Bovenzi Roberta , Conti Matteo , De Franco Valentino , Pierantozzi Mariangela , Schirinzi Tommaso , Cerroni Rocco , Stefani Alessandro , Mercuri Nicola Biagio , Liguori Claudio
Published: April 2024

Parkinson’s disease (PD) symptomatology differs between females and males, yet the contribution of sex on sleep problems needs further analysis. Here, we aimed to investigate sex-specific patterns in the relationship between sleep problems, assessed using the Parkinson’s disease sleep scale (PDSS-2), non motor symptoms (NMS), measured by the NMS scale (NMSS), and health-related quality of life (HR-QoL), evaluated by the Parkinson’s disease questionnaire (PDQ-39), in a large cohort of PD patients. One-hundred-fifty-four PD patients were included in the study. Female PD patients (n = 62) exhibited a higher prevalence of sleep problems than males (n = 92), with nocturnal motor-related sleep issues being the most frequent. Sleep disturbances differently correlated with a range of NMS between the two sexes. In females, sleep problems mostly correlated with pain; on the other hand, sleep disturbances were linked to a frailer phenotype characterized by global dysautonomia, perception disturbances, and impaired cognitive function in males. Whether female PD patients experienced a lower HR-QoL than males, sleep disturbances were associated with a worse HR-QoL in both sexes. In conclusion, sleep problems in PD differently burden the two sexes, suggesting possible different etiopathogenesis, diagnostic investigations, and possibly tailored approaches.
Unravelling the complexities of depression with medical intelligence: exploring the interplay of genetics, hormones, and brain function
Authors: Heyat Md Belal Bin , Akhtar Faijan , Munir Farwa , Sultana Arshiya , Muaad Abdullah Y. , Gul Ijaz , Sawan Mohamad , Asghar Waseem , Iqbal Sheikh Muhammad Asher , Baig Atif Amin , de la Torre Díez Isabel , Wu Kaishun
Published: April 2024

Depression is a multifactorial disease with unknown etiology affecting globally. It’s the second most significant reason for infirmity in 2020, affecting about 50 million people worldwide, with 80% living in developing nations. Recently, a surge in depression research has been witnessed, resulting in a multitude of emerging techniques developed for prediction, evaluation, detection, classification, localization, and treatment. The main purpose of this study is to determine the volume of depression research conducted on different aspects such as genetics, proteins, hormones, oxidative stress, inflammation, mitochondrial dysfunction, and associations with other mental disorders like anxiety and stress using traditional and medical intelligence (medical with AI). In addition, it also designs a comprehensive survey on detection, treatment planning, and genetic predisposition, along with future recommendations. This work is designed through different methods, including a systematic mapping process, literature review, and network visualization. In addition, we also used VOSviewer software and some authentic databases such as Google Scholar, Scopus, PubMed, and Web of Science for data collection, analysis, and designing comprehensive picture of the study. We analyzed 60 articles related to medical intelligence, including 47 from machine learning with 513,767 subjects (mean ± SD = 10,931.212 ± 35,624.372) and 13 from deep learning with 37,917 subjects (mean ± SD = 3159.75 ± 6285.57). Additionally, we also found that stressors impact the brain's cognitive and autonomic functioning, resulting in increased production of catecholamine, decreased cholinergic and glucocorticoid activity, with increased cortisol. These factors lead to chronic inflammation and hinder the brain's normal functioning, leading to depression, anxiety, and cardiovascular disorders. In the brain, reactive oxygen species (ROS) production is increased by IL-6 stimulation and mitochondrial cytochrome c oxidase is inhibited by nitric oxide, a potent inhibitor. Proteins, lipids, oxidative phosphorylation enzymes, and mtDNA are further disposed to oxidative impairment in the mitochondria. Consequently, mitochondrial dysfunction exacerbates oxidative stress, impairs mitochondrial DNA (mtDNA) or deletions of mtDNA, increases intracellular Ca2+ levels, changes in fission/fusion and mitochondrial morphology, and lastly leads to neuronal death. This study highlights the multidisciplinary approaches to depression with different aspects using traditional and medical intelligence. It will open a new way for depression research through new emerging technologies.
Development of a Tube-Based Elastocaloric Regenerator Loaded in Compression: A Review
Authors: Dall’Olio Stefano , Ahčin Žiga , Žerovnik Andrej , Kabirifar Parham , Brojan Miha , Tušek Jaka
Published: April 2024

In recent years, devices based on the elastocaloric effect (eCE) have emerged as one of the most promising alternatives to vaporcompression cooling and heating systems. After a brief overview of elastocaloric materials and elastocaloric devices developed to date, this paper reviews our recent activities in the development of tube-based elastocaloric regenerators loaded in compression. These include the evaluation of novel elastocaloric thermodynamic cycles, the characterization of the elastocaloric and fatigue behavior of Ni–Ti tubes, the thermo-hydraulic evaluation of a tube-based geometry to be applied as an elastocaloric regenerator, the buckling analysis of Ni–Ti tube in compression, and finally the development, numerical modeling, and testing of a tube-based elastocaloric regenerator in both cooling and heat-pumping modes. The developed regenerator shows a durable operation with more than 300,000 cycles, a maximum temperature span of more than 31 K at zero thermal load, and a heating power of more than 60 W at a temperature span of 10 K using only 13.7 g of elastocaloric material. In addition, further improvements of the tube-based elastocaloric regenerators related to a lower thermal mass of the regenerator’s housing are shown and discussed.
Asymmetric effects of macro policies on women’s and men’s incomes. An empirical investigation of the eurozone crisis in a gender perspective
Authors: Cirillo Valeria , Corsi Marcella , D’Ippoliti Carlo , Gobbi Lucio
Published: April 2024

We study how macro policies affected women’s and men’s incomes during the financial crisis in Europe. We consider the monetary stance, proxied by benchmark interest rates, and the fiscal stance, measured by the variation in public expenditures and public revenues, and investigate how they are associated to women’s and men’s labor and capital incomes, using microdata for 27 European countries between 2008 and 2016. We individualize household-level data by considering four scenarios of intra-household sharing of resources. We also explore how and to what extent macro-policies affect the distribution of labour incomes for men and women by applying a conditional quantile regression approach. Results highlight that the ECB’s expansionary policies had a positive effect on both labor and capital incomes for both men and women, while austerity policies had a mixed impact. Reductions in public expenditure had the effect of reducing labor incomes for both men and women, particularly at the median of the wage and labor distributions. In contrast, increases in public revenues benefited capital incomes, for all income quantiles.
Perovskite Oxides Toward Oxygen Evolution Reaction: Intellectual Design Strategies, Properties and Perspectives
Authors: Liu Lin-Bo , Yi Chenxing , Mi Hong-Cheng , Zhang Song Lin , Fu Xian-Zhu , Luo Jing-Li , Liu Subiao
Published: April 2024

Developing electrochemical energy storage and conversion devices (e.g., water splitting, regenerative fuel cells and rechargeable metal-air batteries) driven by intermittent renewable energy sources holds a great potential to facilitate global energy transition and alleviate the associated environmental issues. However, the involved kinetically sluggish oxygen evolution reaction (OER) severely limits the entire reaction efficiency, thus designing high-performance materials toward efficient OER is of prime significance to remove this obstacle. Among various materials, cost-effective perovskite oxides have drawn particular attention due to their desirable catalytic activity, excellent stability and large reserves. To date, substantial efforts have been dedicated with varying degrees of success to promoting OER on perovskite oxides, which have generated multiple reviews from various perspectives, e.g., electronic structure modulation and heteroatom doping and various applications. Nonetheless, the reviews that comprehensively and systematically focus on the latest intellectual design strategies of perovskite oxides toward efficient OER are quite limited. To bridge the gap, this review thus emphatically concentrates on this very topic with broader coverages, more comparative discussions and deeper insights into the synthetic modulation, doping, surface engineering, structure mutation and hybrids. More specifically, this review elucidates, in details, the underlying causality between the being-tuned physiochemical properties [e.g., electronic structure, metal–oxygen (M–O) bonding configuration, adsorption capacity of oxygenated species and electrical conductivity] of the intellectually designed perovskite oxides and the resulting OER performances, coupled with perspectives and potential challenges on future research. It is our sincere hope for this review to provide the scientific community with more insights for developing advanced perovskite oxides with high OER catalytic efficiency and further stimulate more exciting applications.

Graphical Abstract
Encouraging Positive Bystander Responses to Bias-Based Bullying in Primary Schools Through a Serious Game Approach: A Non-Randomized Controlled Evaluation of the ‘GATE-BULL’ Program
Authors: Willems Roy A. , Sapouna Maria , De Amicis Leyla , Völlink Trijntje , Dehue Francine , Dimakos Ioannis , Priovolou Konstantina , Nikolaou Georgios , Rosinský Rastislav
Published: April 2024

Bias-based bullying is a serious public health issue, negatively impacting on the well-being of children with socially devalued identities or attributes. The aim of the GATE-BULL project was to develop and evaluate a serious game supplemented by a series of classroom-based lesson plans to encourage positive bystander responses in weight-, ethnicity-, and religion-based bullying situations. The program was a 4-week school-based intervention targeted at 9–13-year-olds and tested using a quasi-experimental design. In total, 578 children from the Netherlands, Scotland and Greece were included in the analyses. The evaluation suggested that the GATE-BULL program improved the intention to intervene in weight-based bullying situations in Scotland and marginally contributes to a reduction in intergroup anxiety among majority group children with respect to Muslim children in the Netherlands. No positive effects were found in Greece. While the program showed limited evidence of effectiveness, several important lessons have been learned for future development of interventions targeting bias-based bullying.
Cn2a-capsnet: a capsule network and CNN-attention based method for COVID-19 chest X-ray image diagnosis
Authors: Zhang Hui , Lv Ziwei , Liu Shengdong , Sang Zhenlong , Zhang Zehua
Published: April 2024

Due to its high infectivity, COVID-19 has rapidly spread worldwide, emerging as one of the most severe and urgent diseases faced by the global community in recent years. Currently, deep learning-based diagnostic methods can automatically detect COVID-19 cases from chest X-ray images. However, these methods often rely on large-scale labeled datasets. To address this limitation, we propose a novel neural network model called CN2A-CapsNet, aiming to enhance the automatic diagnosis of COVID-19 in chest X-ray images through efficient feature extraction techniques. Specifically, we combine CNN with an attention mechanism to form the CN2A model, which efficiently mines relevant information from chest X-ray images. Additionally, we incorporate capsule networks to leverage their ability to understand spatial information, ultimately achieving efficient feature extraction. Through validation on a publicly available chest X-ray image dataset, our model achieved a 98.54% accuracy and a 99.01% recall rate in the binary classification task (COVID-19/Normal) on a six-fold cross-validation dataset. In the three-class classification task (COVID-19/Pneumonia/Normal), it attained a 96.71% accuracy and a 98.34% recall rate. Compared to the previous state-of-the-art models, CN2A-CapsNet exhibits notable advantages in diagnosing COVID-19 cases, specifically achieving a high recall rate even with small-scale datasets.
How Does It Feel to Leave Your Protest?
Authors: Ratkos Thom
Published: April 2024

Social justice movements, protests, marches, and direct action are collective events including many people. Although organizers should carefully plan the goals and strategies of these actions broadly, and behavior analysts have made significant progress to systems level analyses of social and cultural practices, it is important to continue to include analyses of the individuals involved and how the contingencies of protest may encourage or discourage continued involvement. One critical aspect of these contingencies, I argue, is how the action ends. Two protest actions are analyzed as a participant with a focus on how the protest ended and if the operant “attending a protest” was reinforced or punished.