bluuebunny/crossref_metadata_2025 huggingface dataset:
Pubertal timing in adolescents with ADHD: extension and replication in an all-female sample
Authors: Rosenthal Emily A. , Hinshaw Stephen P.
Published: May 2023

Pubertal timing predicts a miscellany of negative mental and physical health outcomes. Prior work examining pubertal timing in youth with attention-deficit hyperactivity disorder (ADHD) has failed to investigate potential sex specificity of results. Therefore, we aim to extend past findings in a sample of female adolescents with ADHD. We compare pubertal timing (1) between females with and without carefully diagnosed ADHD and (2) between females with ADHD who do vs. do not have a history of stimulant medication use during childhood. We examine 127 adolescent females with childhood-diagnosed ADHD and 82 matched neurotypical peers (Mage: 14.2 years,range:11.3–18.2) from the Berkeley Girls with ADHD Longitudinal Study (Wave 2). We measured pubertal timing using self-reported Tanner staging and age at menarche. Three strategies compared pubertal timing across groups: (1)$${\chi }^{2}$$χ2tests of Tanner Stages, (2)ttests of residuals of pubertal status regressed on age, and (3)ttests of age at menarche. Pubertal timing of girls with and without ADHD did not differ significantly across methods and measures. Yet females with ADHD who had received stimulant medication during childhood menstruated later than those without a stimulant history, potentially related to differences in BMI across groups. On the other hand, no significant differences between medicated vs. non-medicated participants emerged for the two Tanner staging indicators. Our findings extend prior work, suggesting that females with ADHD are developing physically at a similar time as their peers, which parallels findings from previous mixed-sex samples that did not examine effects separately by sex.
Therapeutic and diagnostic applications of exosomal circRNAs in breast cancer
Authors: Gopikrishnan Mohanraj , R Hephzibah Cathryn , R Gnanasambandan , Ashour Hossam M. , Pintus Gianfranco , Hammad Mohamed , Kashyap Manoj Kumar , C George Priya Doss , Zayed Hatem
Published: May 2023

Circular RNAs (circRNAs) are regulatory elements that are involved in orchestrating gene expression and protein functions and are implicated in various biological processes including cancer. Notably, breast cancer has a significant mortality rate and is one of the most common malignancies in women. CircRNAs have been demonstrated to contribute to the pathogenesis of breast cancer including its initiation, progression, metastasis, and resistance to drugs. By acting as miRNA sponges, circRNAs can indirectly influence gene expression by disrupting miRNA regulation of their target genes, ultimately altering the course of cancer development and progression. Additionally, circRNAs can interact with proteins and modulate their functions including signaling pathways involved in the initiation and development of cancer. Recently, circRNAs can encode peptides that play a role in the pathophysiology of breast cancer and other diseases and their potential as diagnostic biomarkers and therapeutic targets for various cancers including breast cancer. CircRNAs possess biomarkers that differentiate, such as stability, specificity, and sensitivity, and can be detected in several biological specimens such as blood, saliva, and urine. Moreover, circRNAs play an important role in various cellular processes including cell proliferation, differentiation, and apoptosis, all of which are integral factors in the development and progression of cancer. This review synthesizes the functions of circRNAs in breast cancer, scrutinizing their contributions to the onset and evolution of the disease through their interactions with exosomes and cancer-related intracellular pathways. It also delves into the potential use of circRNA as a biomarker and therapeutic target against breast cancer. It discusses various databases and online tools that offer crucial circRNA information and regulatory networks. Lastly, the challenges and prospects of utilizing circRNAs in clinical settings associated with breast cancer are explored.
Double-stranded RNA (dsRNA) technology to control forest insect pests and fungal pathogens: challenges and opportunities
Authors: Singewar Kiran , Fladung Matthias
Published: May 2023

Climate change alters the seasonal synchronization between plants and respective pests plus pathogens. The geographical infiltration helps to shift their hosts, resulting in novel outbreaks that damage forests and ecology. Traditional management schemes are unable to control such outbreaks, therefore unconventional and competitive governance is needed to manage forest pests and pathogens. RNA interference (RNAi) mediated double-stranded RNA (dsRNA) treatment method can be implemented to protect forest trees. Exogenous dsRNA triggers the RNAi-mediated gene silencing of a vital gene, and suspends protein production, resulting in the death of targeted pathogens and pests. The dsRNA treatment method is successful for many crop insects and fungi, however, studies of dsRNA against forest pests and pathogens are depleting. Pesticides and fungicides based on dsRNA could be used to combat pathogens that caused outbreaks in different parts of the world. Although the dsRNA has proved its potential, the crucial dilemma and risks including species-specific gene selection, and dsRNA delivery methods cannot be overlooked. Here, we summarized the major fungi pathogens and insect pests that have caused outbreaks, their genomic information, and studies on dsRNA fungi-and pesticides. Current challenges and opportunities in dsRNA target decision, delivery using nanoparticles, direct applications, and a new method using mycorrhiza for forest tree protection are discussed. The importance of affordable next-generation sequencing to minimize the impact on non-target species is discussed. We suggest that collaborative research among forest genomics and pathology institutes could develop necessary dsRNA strategies to protect forest tree species.
Study on the activation of cell death mechanisms: in search of new therapeutic targets in glioblastoma multiforme
Authors: Gaiaschi Ludovica , Favaron Cristina , Casali Claudio , Gola Federica , De Luca Fabrizio , Ravera Mauro , Roda Elisa , Rossi Paola , Bottone Maria Grazia
Published: May 2023

Malignant primary brain tumors remain among the most difficult cancers to treat, in particular, Glioblastoma Multiforme (GBM) is the deadliest brain tumor. The standard therapies currently used are not efficient enough in improving patients’ survival and quality of life. Cisplatin (CDDP), a platinum-based drug, has shown efficacy against different solid neoplasms, but it is also associated to different forms of off-target toxicity. To overcome the limitation in the use of CDDP in the treatment of GBM patients, fourth generation platinum compounds are been synthesized, one of them is the Pt(IV)Ac-POA, a prodrug with a medium-chain fatty acid as axial ligand, which acts as a histone 3 deacetylase inhibitor. Moreover, recently, the antioxidant effects of medicinal mushrooms have been shown to induce a lowering of the toxicity of chemotherapy drugs, inducing greater therapeutic efficiency, thus the combined therapy of chemotherapy and micotherapy could be helpful in the treatment of GBM reducing the adverse effects of the former thanks to phytotherapy’s antioxidant, anti-inflammatory, immunomodulatory and antitumoral activities. Here, through immunoblotting, ultrastructural and immunofluorescence analysis, we evaluated the contribution in the activation of different cell death pathway of Micotherapy U-Care, a medicinal blend supplement, used together with platinum-based compounds on human glioblastoma U251 cells.
Agreement of wall shear stress distribution between two core laboratories using three-dimensional quantitative coronary angiography
Authors: Kageyama Shigetaka , Tufaro Vincenzo , Torii Ryo , Karamasis Grigoris V. , Rakhit Roby D. , Poon Eric K. W. , Aben Jean-Paul , Baumbach Andreas , Serruys Patrick W. , Onuma Yoshinobu , Bourantas Christos V.
Published: May 2023

Wall shear stress (WSS) estimated in models reconstructed from intravascular imaging and 3-dimensional-quantitative coronary angiography (3D-QCA) data provides important prognostic information and enables identification of high-risk lesions. However, these analyses are time-consuming and require expertise, limiting WSS adoption in clinical practice. Recently, a novel software has been developed for real-time computation of time-averaged WSS (TAWSS) and multidirectional WSS distribution. This study aims to examine its inter-corelab reproducibility. Sixty lesions (20 coronary bifurcations) with a borderline negative fractional flow reserve were processed using the CAAS Workstation WSS prototype to estimate WSS and multi-directional WSS values. Analysis was performed by two corelabs and their estimations for the WSS in 3 mm segments across each reconstructed vessel was extracted and compared. In total 700 segments (256 located in bifurcated vessels) were included in the analysis. A high intra-class correlation was noted for all the 3D-QCA and TAWSS metrics between the estimations of the two corelabs irrespective of the presence (range: 0.90–0.92) or absence (range: 0.89–0.90) of a coronary bifurcation, while the ICC was good-moderate for the multidirectional WSS (range: 0.72–0.86). Lesion level analysis demonstrated a high agreement of the two corelabls for detecting lesions exposed to an unfavourable haemodynamic environment (WSS > 8.24 Pa, κ = 0.77) that had a high-risk morphology (area stenosis > 61.3%, κ = 0.71) and were prone to progress and cause events. The CAAS Workstation WSS enables reproducible 3D-QCA reconstruction and computation of WSS metrics. Further research is needed to explore its value in detecting high-risk lesions.
Tail-dependence, exceedance sets, and metric embeddings
Authors: Janßen Anja , Neblung Sebastian , Stoev Stilian
Published: May 2023

There are many ways of measuring and modeling tail-dependence in random vectors: from the general framework of multivariate regular variation and the flexible class of max-stable vectors down to simple and concise summary measures like the matrix of bivariate tail-dependence coefficients. This paper starts by providing a review of existing results from a unifying perspective, which highlights connections between extreme value theory and the theory of cuts and metrics. Our approach leads to some new findings in both areas with some applications to current topics in risk management.

We begin by using the framework of multivariate regular variation to show that extremal coefficients, or equivalently, the higher-order tail-dependence coefficients of a random vector can simply be understood in terms of random exceedance sets, which allows us to extend the notion of Bernoulli compatibility. In the special but important case of bivariate tail-dependence, we establish a correspondence between tail-dependence matrices and $$L^1$$

L
1

- and $$\ell _1$$

ℓ
1

-embeddable finite metric spaces via the spectral distance, which is a metric on the space of jointly 1-Fréchet random variables. Namely, the coefficients of the cut-decomposition of the spectral distance and of the Tawn-Molchanov max-stable model realizing the corresponding bivariate extremal dependence coincide. We show that line metrics are rigid and if the spectral distance corresponds to a line metric, the higher order tail-dependence is determined by the bivariate tail-dependence matrix.

Finally, the correspondence between $$\ell _1$$

ℓ
1

-embeddable metric spaces and tail-dependence matrices allows us to revisit the realizability problem, i.e. checking whether a given matrix is a valid tail-dependence matrix. We confirm a conjecture of Shyamalkumar and Tao (2020) that this problem is NP-complete.
An unlikely bifurcation: history of sustainable (but not Green) chemistry
Authors: Krasnodębski Marcin
Published: May 2023

The concept of green chemistry dominated the imagination of environmentally-minded chemists over the last thirty years. The conceptual frameworks laid by the American Environmental Protection Agency scholars in the 1990s constitute today the core of a line of thinking aimed at transforming chemistry into a sustainable science. And yet, in the shadow of green chemistry, a broader, even if less popular, concept of sustainable chemistry started taking shape. Initially, it was either loosely associated with green chemistry or left undefined as a distinct but generaly different approach. In such a vague form, it was endorsed by the organizations such as OECD and the IUPAC in the late 1990s. It was not until the 2010s however, when it solidified as a separate more embracing and more overarching tradition that could compete with green chemistry by offering insights that the latter lacked. Sustainable chemistry seeks to transcend the narrow focus on chemical synthesis and embrace a much more holistic view of chemical activities including social responsibility and sustainable business models. Due to an interesting historical coincidence, it was in Germany where sustainable chemistry took roots and became institutionalized for the first time. It was thanks to German exceptionalism and the unwillingness of German scholars to embrace the “green” terminology originating from the US, the concept of sustainable chemistry could safely mature and develop in the German-speaking world, before reaching a high degree of formalization with dedicated journals, founding articles, and programmatic principles aspiring to transform the entire chemical enterprise in the years to come.
Hydrogeological Properties of Till Amended with Green Liquor Dregs (GLD): Recycling of an Industrial Residue for Reclamation of Acid Generating Mine Sites
Authors: Nigéus Susanne , Maurice Christian , Lindblom Jenny
Published: May 2023

The oxidation of sulfide minerals in mine wastes is a possible threat to the environment as it might have potential to generate acid rock drainage (ARD). A common method to reduce ARD is to apply a dry cover on the mine waste deposit. Considering the massive amounts of mine waste produced in Sweden (104-million-ton in year 2018) there is a great need for suitable dry cover materials. Using non-hazardous industrial residues in the dry cover would be beneficial for both the mining industry and the providing industry as stricter waste management legislation incentivizes them to develop their waste management strategies. The objective of this study was to investigate if an addition of Green Liquor Dregs (GLD), a residue from pulp production, can decrease the hydraulic conductivity and increase the water retention capacity (WRC) of three different tills, with the purpose of improving the performance of a dry cover material on a mine waste deposit. Another objective was to investigate how the hydraulic conductivity and WRC are affected by the contents of fines and clays in the tills. The study concludes that the water retention capacity of the tills improves with GLD addition, however, the hydraulic conductivity did not decrease enough to reach the in Sweden required < 10−8 m/s. Even though, GLD could still successfully be used in the reclamation of mine sites as the high WRC can be seen as the most important factor in deterring acid rock drainage by keeping the sealing layer close to saturation. This study further indicates that there are other factors than the particle size distribution of the materials that controls the hydraulic conductivity of the mixtures, such as initial water content, dry density, and compaction effort.
A Formal Theory of Choreographic Programming
Authors: Cruz-Filipe Luís , Montesi Fabrizio , Peressotti Marco
Published: May 2023

Choreographic programming is a paradigm for writing coordination plans for distributed systems from a global point of view, from which correct-by-construction decentralised implementations can be generated automatically. Theory of choreographies typically includes a number of complex results that are proved by structural induction. The high number of cases and the subtle details in some of these proofs has led to important errors being found in published works. In this work, we formalise the theory of a choreographic programming language in Coq. Our development includes the basic properties of this language, a proof of its Turing completeness, a compilation procedure to a process language, and an operational characterisation of the correctness of this procedure. Our formalisation experience illustrates the benefits of using a theorem prover: we get both an additional degree of confidence from the mechanised proof, and a significant simplification of the underlying theory. Our results offer a foundation for the future formal development of choreographic languages.
Continuous perioperative heart rate variability monitoring in video-assisted thoracoscopic surgery lobectomy—a pilot study
Authors: Frandsen Mikkel Nicklas , Huang Lin , Petersen René Horsleben , Foss Nicolai Bang , Mehlsen Jesper , Kehlet Henrik
Published: May 2023

Heart rate variability (HRV) is a measure of cardiac autonomic modulation and is potentially related to hypotension, postoperative atrial fibrillation, and orthostatic intolerance. However, there is a lack of knowledge on which specific time points and indices to measure. To improve future study design, there is a need for procedure-specific studies in an enhanced recovery after surgery (ERAS) video-assisted thoracic surgery (VATS) lobectomy setting, and for continuous measurement of perioperative HRV. HRV was measured continuously from 2 days before until 9 days after VATS lobectomy in 28 patients. After VATS lobectomy, with median length of stay = 4 days, the standard deviation between normal-to-normal beats and the total power of HRV were reduced for 8 days during the night and day times, while low-to-high frequency variation and detrended fluctuation analysis were stable. This is the first detailed study to show that HRV measures of total variability were reduced following ERAS VATS lobectomy, while other measures were more stable. Further, preoperative HRV measures showed circadian variation. The patch was well tolerated among participants, but actions should be taken to ensure proper mounting of the measuring device. These results demonstrate a valid design platform for future HRV studies in relation to postoperative outcomes.
Population pharmacokinetic and pharmacokinetic-pharmacodynamic modeling of bempedoic acid and low-density lipoprotein cholesterol in healthy subjects and patients with dyslipidemia
Authors: Jadhav Satyawan B. , Amore Benny M. , Bockbrader Howard , Crass Ryan L. , Chapel Sunny , Sasiela William J. , Emery Maurice G.
Published: May 2023

Population pharmacokinetics (popPK) of bempedoic acid and the popPK/pharmacodynamic (popPK/PD) relationship between bempedoic acid concentrations and serum low-density lipoprotein cholesterol (LDL-C) from baseline were characterized. A two-compartment disposition model with a transit absorption compartment and linear elimination best described bempedoic acid oral pharmacokinetics (PK). Multiple covariates, including renal function, sex, and weight, had statistically significant effects on the predicted steady-state area under the curve. Mild (estimated glomerular filtration rate (eGFR) 60 to < 90 mL/min vs. ≥ 90 mL/min) and moderate (eGFR 30 to < 60 mL/min vs. ≥ 90 mL/min) renal impairment, female sex, low (< 70 kg vs. 70–100 kg) and high (> 100 kg vs. 70–100 kg) body weight were predicted to have a 1.36-fold (90% confidence interval (CI) 1.32, 1.41), 1.85-fold (90% CI 1.74, 2.00), 1.39-fold (90% CI 1.34, 1.47), 1.35-fold (90% CI 1.30, 1.41), and 0.75-fold (90% CI 0.72, 0.79) exposure difference relative to their reference populations, respectively. An indirect response model described changes in serum LDL-C with a model-predicted 35% maximal reduction and bempedoic acid IC50 of 3.17 µg/mL. A 28% reduction from LDL-C baseline was predicted for a steady-state average concentration of 12.5 µg/mL after bempedoic acid (180 mg/day) dosing, accounting for approximately 80% of the predicted maximal LDL-C reduction. Concurrent statin therapy, regardless of intensity, reduced the maximal effect of bempedoic acid but resulted in similar steady-state LDL-C levels. While multiple covariates had statistically significant effects on PK and LDL-C lowering, none were predicted to warrant bempedoic acid dose adjustment.
Energy bounds for vertex operator algebra extensions
Authors: Carpi Sebastiano , Tomassini Luca
Published: May 2023

Let V be a simple unitary vertex operator algebra and U be a (polynomially) energy-bounded unitary subalgebra containing the conformal vector of V. We give two sufficient conditions implying that V is energy-bounded. The first condition is that U is a compact orbifold $$V^G$$

V
G

for some compact group G of unitary automorphisms of V. The second condition is that V is exponentially energy-bounded and it is a finite direct sum of simple U-modules. As a consequence of the second condition, we prove that if U is a regular energy-bounded unitary subalgebra of a simple unitary vertex operator V, then V is energy-bounded. In particular, every simple unitary extension (with the same conformal vector) of a simple unitary affine vertex operator algebra associated with a semisimple Lie algebra is energy-bounded.
Effects of electromagnetic waves on the moisture content of cones and the quality of extracted seeds in the Norway spruce and European larch
Authors: Aniszewska Monika , Gendek Arkadiusz , Tulska Ewa , Zięba-Kawecka Aleksandra , Malaťák Jan , Tamelová Barbora , Malaťáková Jitka , Krilek Jozef
Published: May 2023

The publication describes research investigating the effects of microwaves on seeds extracted from Norway spruce (Picea abies) and European larch (Larix decidua) cones. The objective of the conducted experiments was to determine how electromagnetic radiation influences the quality of those seeds. The study material was heated in a microwave-emitting device for 7 or 10 s at four power settings (800, 620, 440, or 130 W). The evaluated parameters included changes in the moisture content and weight of the studied cones following the applied time and power variants of exposure to microwaves, as well as the quality of the obtained seeds expressed in terms of germination energy (GE) and capacity (GC). Increasing the power of microwaves resulted in a greater decrease in the moisture content of cones, but it was not possible to find such a relationship for larch cones, especially for large cones. In most cases, the irradiation of larch cones with electromagnetic waves resulted in class I seeds, in contrast to spruce seeds, which could not be assigned to any class. Our findings show that for optimum results larch cones may be exposed to microwaves at a power not greater than 620 W and for a time not longer than 10 s. Spruce cones were found to be very sensitive to radiation; in their case no microwave treatment should be applied as it adversely affects seed viability.
Ph.D. publication productivity: the role of gender and race in supervision in South Africa
Authors: Rossello Giulia , Cowan Robin , Mairesse Jacques
Published: May 2023

We study whether student-advisor gender and race composition matters for publication productivity of Ph.D. students in South Africa. We consider all Ph.D. students in STEM graduating between 2000 and 2014, after the recent systematic introduction of doctoral programs in this country. We investigate the joint effects of gender and race for the whole sample and looking separately at the sub-samples of (1) white-white; (2) black-black; and (3) black-white student-advisor couples. We find significant productivity differences between male and female students. These disparities are more pronounced for female students working with male advisors when looking at the joint effects of gender and race for the white-white and black-black student-advisor pairs. We also explore whether publication productivity differences change significantly for students with a high, medium, or low “productivity-profile”. We find that female productivity gaps are U-shaped over the range of productivity. Female students working with male advisors have more persistent productivity gaps over the productivity distribution, while female students with a high (or low) “productivity-profile” studying with female advisors are as productive as male students with similar “productivity-profile” studying with male advisors.
Does local government corruption inhibit entrepreneurship?
Authors: Wittberg Emanuel , Erlingsson Gissur Ó. , Wennberg Karl
Published: May 2023

The
dominant ‘sand in the wheels’ view holds that entrepreneurship is strongly inhibited by corruption. Challenging this, the ‘grease the wheels’ view maintains that corruption might increase entrepreneurship in highly regulated economies. We extend the basic predictions of these theories by examining entrepreneurs’ start-up decisions, as well as their location choices, in a seemingly low-corruption environment: Swedish municipalities. Combining a validated index of corruption perceptions in local government with population data on new entrepreneurs, nested logit models reveal that even in a low-corruption setting such as Sweden, perceptions of corruption can deter latent entrepreneurs. We also find that a minority of entrepreneurs relocate from their home municipalities to establish their start-ups elsewhere. Surprisingly and contrary to expectations, these relocating entrepreneurs often relocate from relatively low-corruption municipalities to others that are more corrupt. Implications for future research and public policy are discussed.
Improved clonal selection algorithm based on the directional update strategy
Authors: Yang Chao , Huang Zijing , Jiang Bibo , Zhu Menglian , Luo Aoran , He Jianfeng
Published: May 2023

At present, many cloning selection algorithms have been studied, and improvements have been made to the cloning, mutation and selection steps. However, there is a lack of research on the optimization of the updating operation steps. The clonal selection algorithm is traditionally updated through a random complement of antibodies, which is a blind and uncertain process. The added antibodies may gather near a local optimal solution, resulting in the need for more iterations to obtain the global optimal solution. To solve this problem, our improved algorithm introduces a crowding degree factor in the antibody updating stage to determine whether there is crowding between antibodies. By eliminating antibodies with high crowding potential and poor affinity, the improved algorithm guides the antibodies to update in the direction of the global optimal solution and ensures stable convergence with fewer iterations. Experimental results show that the overall performance of the improved algorithm is 1% higher than that of the clonal selection algorithm and 2.2% higher than that of the genetic algorithm, indicating that the improved algorithm is effective. The improved algorithm is also transplanted to other improved clonal selection algorithms, and the overall performance is improved by 0.97%, indicating that the improved algorithm can be a beneficial supplement to other improved clonal selection algorithms.
On the Challenge of Obtaining an Accurate Solvation Energy Estimate in Simulations of Electrocatalysis
Authors: Kirchhoff Björn , Jónsson Elvar Ö. , Jacob Timo , Jónsson Hannes
Published: May 2023

The effect of solvation on the free energy of reaction intermediates adsorbed on electrocatalyst surfaces can significantly change the thermochemical overpotential, but accurate calculations of this are challenging. Here, we present computational estimates of the solvation energy for reaction intermediates in oxygen reduction reaction (ORR) on a B-doped graphene (BG) model system where the overpotential is found to reduce by up to 0.6 V due to solvation. BG is experimentally reported to be an active ORR catalyst but recent computational estimates using state-of-the-art hybrid density functionals in the absence of solvation effects have indicated low activity. To test whether the inclusion of explicit solvation can bring the calculated activity estimates closer to the experimental reports, up to 4 layers of water molecules are included in the simulations reported here. The calculations are based on classical molecular dynamics and local minimization of energy using atomic forces evaluated from electron density functional theory. Data sets are obtained from regular and coarse-grained dynamics, as well as local minimization of structures resampled from dynamics simulations. The results differ greatly depending on the method used and the solvation energy estimates are deemed untrustworthy. It is concluded that a significantly larger number of water molecules is required to obtain converged results for the solvation energy. As the present system includes up to 139 atoms, it already strains the limits of computational feasibility, so this points to the need for a hybrid simulation approach where efficient simulations of much larger number of solvent molecules is carried out using a lower level of theory while retaining the higher level of theory for the reacting molecules as well as their near neighbors and the catalyst. The results reported here provide a word of caution to the computational catalysis community: activity predictions can be inaccurate if too few solvent molecules are included in the calculations.
Multi-view Consistent Generative Adversarial Networks for Compositional 3D-Aware Image Synthesis
Authors: Zhang Xuanmeng , Zheng Zhedong , Gao Daiheng , Zhang Bang , Yang Yi , Chua Tat-Seng
Published: May 2023

This paper studies compositional 3D-aware image synthesis for both single-object and multi-object scenes. We observe that two challenges remain in this field: existing approaches (1) lack geometry constraints and thus compromise the multi-view consistency of the single object, and (2) can not scale to multi-object scenes with complex backgrounds. To address these challenges coherently, we propose multi-view consistent generative adversarial networks (MVCGAN) for compositional 3D-aware image synthesis. First, we build the geometry constraints on the single object by leveraging the underlying 3D information. Specifically, we enforce the photometric consistency between pairs of views, encouraging the model to learn the inherent 3D shape. Second, we adapt MVCGAN to multi-object scenarios. In particular, we formulate the multi-object scene generation as a “decompose and compose” process. During training, we adopt the top-down strategy to decompose training images into objects and backgrounds. When rendering, we deploy a reverse bottom-up manner by composing the generated objects and background into the holistic scene. Extensive experiments on both single-object and multi-object datasets show that the proposed method achieves competitive performance for 3D-aware image synthesis.
Thermodynamic Evaluation and Optimization of the Ag-As-S system
Authors: Kidari Oumaima , Chartrand Patrice
Published: May 2023

A critical evaluation of all available phase diagram and thermodynamic data has been performed for Ag-As, Ag-S, As-S and Ag-As-S systems, including a detailed review of the gaseous species involved in the As-S system. Thermodynamic assessments over the whole composition range for these four systems are presented using the CALPHAD method. To predict thermodynamic properties and phase equilibria, the Modified Quasichemical Model for short range ordering was used for the liquid phases, and the Compound Energy Formalism was used for the solid solutions. For the As-S binary system, natural logarithm terms for the temperature dependence of the excess Gibbs energy of the liquid solution have been used. This led to a significant improvement compared with the previous assessment of this system. The optimization of Ag-As-S systems is in good agreement with the existing experimental data.
Stability and Bifurcation Analysis of Two-Immiscible Liquids Film Down an Inclined Slippery Solid Substrate
Authors: Zakaria Kadry , Sirwah Magdy A.
Published: May 2023

In this work, the dynamic behavior of linear and nonlinear waves propagating at the separating surface between two thin layers of viscous Newtonian fluids is studied in the presence of the effect of insoluble surface surfactant. The two liquids are confined between two infinite rigid parallel plates and assumed to have different densities and viscosities. The equations of evolution for surface-wave elevation and concentration of surfactant are derived using the lubrication approximation. In the linear stage, by utilizing the normal mode approach, we have derived the dispersion relation that relates the wave angular frequency to the wave number and other parameters that is solved numerically to inspect the influences of some selected parameters on the stability criteria of the fluid flow. Also, analytical expressions for the growth rate as well as its maximum value with corresponding wave number are obtained in the special case of long-wave limiting. It is concluded that the Marangoni number$$\text {Ma}$$Mahas acquired a significant stabilizing influence on the fluid flow, whereas the inverse of the slippery length of substrate plate$$\beta$$β, resorts to the destabilize the motion of the interfacial waves. Consequently, both of the Marangoni number and the substrate slippy coefficient can be utilized to control the film flow regime, where they preserve the film laminar flow and tend to prevent the film breakdown. These can be useful in many industrial applications such as coating processes, heat exchangers, cooling microelectronic devices, chemical reactors, food processing, thermal protection design of combustion chambers in rocket engines and operation of Laser cutting and heavy casting production processes.
Activating the Hippo pathway by nevadensin overcomes Yap-drived resistance to sorafenib in hepatocellular carcinoma
Authors: Shi Hewen , Zou Ying , Wang Xiaoxue , Wang Guoli , Gao Yijia , Yi Fan , Xu junqing , Yin Yancun , Li Defang , Li Minjing
Published: May 2023

Background

Hepatocellular carcinoma (HCC) is a highly malignant type of tumor that is insensitive to cytotoxic chemotherapy and often develops drug resistance. Nevadensin, a bioflavonoid, exhibits anti-cancer properties in some cancers. However, the precise underlying mechanism of nevadensin against liver cancer are poorly understood. We aim to evaluate the efficacy as well as the molecular mechanism of nevadensin in the treatment of liver cancer.

Methods

Effects of nevadensin on HCC cell proliferation and apoptosis were detected using EdU labeling and flow cytometry assays. The molecular mechanism of nevadensin on HCC was determined using RNAseq. The effects of nevadensin on hippo-Yap signaling were verified using western blot and RT-PCR.

Results

In this study, we show that nevadensin significantly inhibits growth of HCC cells via inducing cell cycle arrest and apoptosis. RNAseq analysis showed that nevadensin regulates multiple functional signaling pathways associated with cancer including Hippo signaling. Western Blot analysis revealed that nevadensin notably induces activation of the MST1/2- LATS1/2 kinase in HCC cells, further resulting in the primary effector molecule YAP phosphorylation and subsequent degradation. These results indicated that nevadensin might exert its anti-HCC activity through the Hippo-ON mechanism. Moreover, nevadensin could increase the sensitivity of HCC cells to sorafenib by down-regulating YAP and its downstream targets.

Conclusions

The present study indicates that nevadensin could be a potential effective approach to treating HCC, and overcoming sorafeni resistance via inducing activation of Hippo signaling.
Regional flood frequency analysis using data-driven models (M5, random forest, and ANFIS) and a multivariate regression method in ungauged catchments
Authors: Esmaeili-Gisavandani Hassan , Zarei Heidar , Fadaei Tehrani Mohammad Reza
Published: May 2023

Flooding is recognized worldwide joined of the most expensive natural hazards. To adopt proper structural and nonstructural measurements for controlling and mitigating the rising flood risk, the availability of streamflow values along a river is essential. This raises concerns in the hydrological assessment of poorly gauged or ungauged catchments. In this regard, several flood frequency analysis approaches have been conducted in the literature including index flow method (IFM), square grids method (SGM), hybrid method (HM), as well as the conventional multivariate regression method (MRM). While these approaches are often based on assumptions that simplify the complex nature of the hydrological system, they might not be able to address uncertainties associated with the complexity of the system. One of the powerful tools to deal with this issue is data-driven model that can be easily adopted in complex systems. The objective of this research is to utilize three different data-driven models: random forest (RF), adaptive neuro-fuzzy inference system (ANFIS), and M5 decision tree algorithm to predict peak flow associated with various return periods in ungauged catchments. Results from each data-driven model were assessed and compared with the conventional multivariate regression method. Results revealed all the three data-driven models performed better than the multivariate regression method. Among them, the RF model not only demonstrated the superior performance of peak flow prediction compared to the other algorithms but also provided insight into the complexity of the system through delivering a mathematical formulation.
Antibody responses after sequential vaccination with PCV13 and PPSV23 in kidney transplant recipients
Authors: Mülling Nils , van de Sand Lukas , Völk Kim , Aufderhorst Ulrich Wilhelm , van der Linden Mark , Horn Peter A. , Kribben Andreas , Wilde Benjamin , Krawczyk Adalbert , Witzke Oliver , Lindemann Monika
Published: May 2023

Purpose

Vaccination against Streptococcus pneumoniae is recommended in transplant recipients to reduce the morbidity and mortality from invasive pneumococcal disease. Previous studies indicate that transplant recipients can produce specific antibodies after vaccination with the 13-valent pneumococcal conjugate vaccine Prevenar 13 (PCV13) or the pneumococcal polysaccharide vaccine Pneumovax 23 (PPSV23). National guidelines recommend sequential vaccination with PCV13 followed by PPSV23 in kidney transplant patients. However, there are currently no data on the serological response in kidney transplant recipients, who received a sequential vaccination with PCV13 and PPSV23.

Methods

In the current study, we sequentially vaccinated 46 kidney transplant recipients with PCV13 and PPSV23 and determined global and serotype-specific anti-pneumococcal antibody responses in the year following vaccination.

Results

Serotype-specific and global anti-pneumococcal antibody concentrations were significantly higher compared to baseline. We observed that serotype-specific antibody responses varied by serotype (between 2.2- and 2.9-fold increase after 12 months). The strongest responses after 12 months were detected against the serotypes 9N (2.9-fold increase) and 14 (2.8-fold increase). Global antibody responses also varied with respect to immunoglobulin class. IgG2 revealed the highest increase (2.7-fold), IgM the lowest (1.7-fold). Sequential vaccination with both vaccines achieved higher antibody levels in comparison with a historical cohort studied at our institute, that was vaccinated with PCV13 alone. During the 12-months follow-up period, none of the patients developed pneumococcal-associated pneumonia or vaccination-related allograft rejection.

Conclusion

In conclusion, we strongly recommend sequential vaccination over single immunization in kidney transplant recipients.
Weighted fractional stochastic integro-differential equation with infinite delay
Authors: Arioui Fatima Zahra
Published: May 2023

In this paper, we consider a weighted fractional stochastic integro-differential equation with infinite delay and nonzero initial values involving a Riemann–Liouville fractional derivative of order $$1/2<\alpha <1$$

1
/
2
<
α
<
1

. The existence of a mild solution is investigated using fractional calculus, stochastic analysis, and the fixed point theorem. An example is also provided to illustrate the obtained result.
Chinese university students showed less disordered eating during the COVID-19 campus lockdown
Authors: Duan Wei , Ding Qiuwei , Peng Sufang , Kang Qing , Guo Lei , Zhang Lei , Wei Yaohui , Xiao Zeping , Fan Juan , Chen Jue
Published: May 2023

Objective

The rapid spread of the Omicron variant of COVID-19 in China had resulted in campus lockdown in many universities since February 2022, profoundly affecting students’ daily lives. Campus lockdown conditions differ considerably from home quarantine, so that the eating patterns of university students may be different. Thus, the current study aimed to: (1) investigate university students’ eating patterns during campus lockdown; (2) identify factors associated with their disordered eating.

Method

An online survey about recent life changes, disordered eating, stress, depression, and anxiety was carried out from April 8th to May 16th, 2022. A total of 2541 responses from 29 provinces/cities of China were received.

Results

2213 participants were included in the main analysis, and other 86 participants were analyzed separately as a subgroup due to their diagnosis of eating disorder. Participants who were undergoing campus lockdown (the lockdown group) showed less disordered eating than those who had never been in campus lockdown (the never-lockdown group), as well as those who had experienced campus lockdown before (the once-lockdown group). However, they perceived more stress and felt more depressed. Being female, higher BMI, gaining weight, increasing exercise, spending more time on social media, higher level of depression and anxiety were all related to disordered eating in the lockdown group.

Conclusions

Disordered eating among Chinese university students was less prevalent during campus lockdown due to the strict and regular diet. However, there is a potential risk of “revenge eating” after campus lockdown ends. Thus, there should be further tracking and related prevention.

Level of evidence

IV, uncontrolled trials without any interventions.
Fine‐Scale Characteristics and Dominant Synoptic Factors of Spring Precipitation Over Complex Terrain of the Southeastern Tibetan Plateau
Authors: Zhao Yin , Li Jian , Ren Liwen , Li Nina , Li Puxi
Published: May 2023

Spring precipitation over the southeastern Tibetan Plateau (SETP) produces more than 34% of annual precipitation, which is comparable to summer precipitation. This pre‐monsoon rainfall phenomenon, influenced synthetically by atmospheric circulations and topography, makes the SETP an exception to its surroundings. Here, fine‐scale characteristics and typical synoptic backgrounds of this unique phenomenon have been investigated. The spring precipitation over the SETP is characterized by high frequency at hourly scale, with a single diurnal peak at night or early morning. Event‐based analysis further demonstrates that the spring precipitation is dominated by long‐lasting nocturnal rainfall events. From early to late spring, the dominant synoptic factor evolves from terrain‐perpendicular low‐level winds to atmospheric moisture, influencing the spatial heterogeneity and fine characteristics of the spring precipitation. The westerly dominated type, featured by lower geopotential height over the TP and enhanced westerlies along the Himalayas, produces limited‐area precipitation at those stations located at topography perpendicular to low‐level winds. In contrast, the moisture‐dominated type is featured by an anomalous cyclone over the Bay of Bengal and induces widespread precipitation around the SETP, which is the leading contributor to the spring precipitation there. Accumulated precipitation amount of long‐lasting nocturnal events is the largest under moisture‐dominated type, which has a large portion of weak precipitation due to weak thermal instability. Findings revealed in this study complete the picture of spring precipitation influenced by different dominant synoptic factors over the SETP, which deepen the current understanding of the joint influence of circulation and topography on the hydrological cycle of complex terrains.
Lithospheric Loading Model for Large Impact Basins Where a Mantle Plug Is Present
Authors: Deng Qingyun , Zhong Zhen , Ye Mao , Zhang Wensong , Qiu Denggao , Zheng Chong , Yan Jianguo , Li Fei , Barriot Jean‐Pierre
Published: May 2023

Characterizing the thermophysical properties of the lithosphere is critical for studying its evolution. We determine the elastic thickness of the lithosphere by modeling mass‐related loads and lithospheric deflection and analyzing gravity and topography data. In impact basins region where a mantle plug is present, the correlation between topography and gravity can be low, and the admittance can change quickly, making it difficult to develop accurate models without considering mantle uplift. In this study, we developed a lithospheric loading model for large impact basins that take advantage of a high‐resolution crustal thickness model and does not require the assuming compensation. Since the mantle uplift formed by super‐isostatic adjustment following the impact, the elastic thickness obtained by fitting the observed data reflects the lithospheric temperature at the end of the super‐isostatic process. Sensitivity analysis suggests that modeling the impact‐induced load is critical to reproduce how the mascon is expressed in the correlation and admittance data. Our mantle loading model provides a better fit to the observed admittance spectrum compared to previous research. The larger elastic thicknesses obtained for the Hellas basin indicate a longer duration of mascon formation or a faster cooling of the lithosphere. Models that consider a denser upper crust and an elastic thickness of about 0 km fit the observed admittance of the Utopia basin. The elastic thickness of the Argyre and Isidis basins cannot be precisely inferred without additional constraints on the load ratio.
Pattern Analyses of Lunar Penetrating Radar Images at Chang'E‐3, 4, and 5 Landing Sites: A New Insight Into the Evolution of Lunar Regolith
Authors: Liu Sijing , Santos Landerlei Almeida , Ning Song , Zhou Feng , Liu Hai , Hu Xiangyun
Published: May 2023

An “atlas” of the Lunar penetrating radar (LPR) patterns is organized and a comprehensive interpretation of the lunar subsurface layers in the areas of the Chang'E (CE) mission is proposed. There are three layers inferred by the LPR high‐frequency profiles of the CE‐3 and CE‐4. The first two layers (i.e., the fine regolith and the ejecta layer) at CE‐3 and CE‐4 sites have the same strata type but differ in internal structure and thickness. The third layer at the CE‐3 site is inferred as the paleoregolith, while at the CE‐4 site, it is inferred as the alternating layer with fine materials, ejecta, and fragments. Due to the limited penetration depth of the CE‐5 LPR, the data disclose only the fine regolith, with support from the empirical ejecta distribution model. The thicknesses, physical properties, and equivalent growth rates of lunar regolith at three landing sites are estimated and discussed in detail. The lunar regolith thicknesses inferred by the CE‐3 and CE‐5 LPR data are both approximately 1.0 m. In contrast, the thickness of the lunar regolith at the CE‐4 site is 10.0 m, which is greater than that at the other two landing sites. However, the equivalent growth rate of the regolith at the CE‐3 and CE‐5 landing sites is four times greater than that at the CE‐4 landing site. This illustrates that with the increase in lunar regolith thickness, the influence of small impact gardening events on the lunar regolith reconstruction gradually weakened, and the self‐buffering effect avoids the fast growth of lunar regolith.