bluuebunny/crossref_metadata_2025 huggingface dataset:
Integrated Algorithm for High‐Resolution Crustal‐Scale Imaging Using Complementary OBS and Streamer Data
Authors: Zand Toktam , Górszczyk Andrzej
Published: February 2024

We present an integrated algorithm for high‐resolution crustal‐scale imaging utilizing long‐offset wide‐angle ocean‐bottom seismometer (OBS) data and short‐offset multichannel streamer (MCS) data. The algorithm adopts a two‐step imaging strategy, initially using the OBS data to enhance deep structure imaging and capture long‐wavelength features of the migration velocity. Subsequently, the MCS data are migrated to recover detailed short‐wavelength components and shallow structures using the migration velocity model modified by the OBS result. Both steps employ the least‐squares reverse time migration (LSRTM) method with appropriate regularization techniques. The algorithm is implemented using the Bregmanized operator splitting (BOS) approach, known for its efficiency and adaptability in handling non‐smooth regularization, such as total‐variation (TV) constraints. To improve computational efficiency, compressed sensing is employed to store incident wavefields at half their actual size and reconstruct them accurately when required. Convergence is expedited through the use of preconditioners and the Anderson acceleration method. The proposed algorithm is validated through large‐scale numerical examples, demonstrating its robustness even with an initially imprecise velocity model. Results showcase improved resolution and accuracy achieved through the integration of OBS and MCS data. This study offers a comprehensive framework for crustal‐scale imaging, addresses computational complexities, and provides enhanced imaging capabilities.
Global Precipitation Correction Across a Range of Climates Using CycleGAN
Authors: McGibbon J. , Clark S. K. , Henn B. , Kwa A. , Watt‐Meyer O. , Perkins W. A. , Bretherton C. S.
Published: February 2024

Accurate precipitation simulations for various climate scenarios are critical for understanding and predicting the impacts of climate change. This study employs a Cycle‐generative adversarial network (CycleGAN) to improve global 3‐hr‐average precipitation fields predicted by a coarse grid (200 km) atmospheric model across a range of climates, morphing them to match their statistical properties with those of reference fine‐grid (25 km) simulations. We evaluate its performance on both the target climates and an independent ramped‐SST simulation. The translated precipitation fields remove most of the biases simulated by the coarse‐grid model in the mean precipitation climatology, the cumulative distribution function of 3‐hourly precipitation, and the diurnal cycle of precipitation over land. These results highlight the potential of CycleGAN as a powerful tool for bias correction in climate change simulations, paving the way for more reliable predictions of precipitation patterns across a wide range of climates.
Lightning Characteristics Associated With Storm Modes Observed During RELAMPAGO
Authors: Rocque Marquette N. , Deierling Wiebke , Rasmussen Kristen L. , Albrecht Rachel I. , Medina Bruno L.
Published: February 2024

Global satellite studies show a maximum in deep convection and lightning downstream of the Andes in subtropical South America. The Remote sensing of Electrification, Lightning, And Mesoscale/microscale Processes with Adaptive Ground Observations (RELAMPAGO) field campaign was designed to investigate the physical processes that contribute to the rapid development of deep convection and mesoscale convective systems (MCSs) in Argentina. A lightning mapping array (LMA) was deployed to Argentina as part of RELAMPAGO to collect lightning observations from extreme storms in the region. This study combines lightning data from the LMA and the Geostationary Lightning Mapper onboard GOES‐16 with 1‐km gridded radar data to examine the electrical characteristics of a variety of convective storms throughout their life cycle observed during RELAMPAGO. Results from the full campaign show 48% of flashes are associated with deep convection that occurs along the eastern edge of the Sierras de Córdoba (SDC) overnight. These flashes are 65 km2 smaller on average compared to stratiform flashes, which occur most frequently 50–100 km east of the SDC in the early morning hours, consistent with the upscale growth of MCSs off the terrain. Analysis of the 13–14 December MCS shows that sharp increases in flash rates correspond to deep and wide convective cores that have high graupel and hail mass, 35‐dBZ volume, and ice water path. This work validates previous satellite studies of lightning in the region, but also provides higher spatial and temporal resolution information across the convective life cycle that has not been available in previous studies.
MarkerMap: nonlinear marker selection for single-cell studies
Authors: Gregory Wilson , Sarwar Nabeel , Kevrekidis George , Villar Soledad , Dumitrascu Bianca
Published: February 2024

Single-cell RNA-seq data allow the quantification of cell type differences across a growing set of biological contexts. However, pinpointing a small subset of genomic features explaining this variability can be ill-defined and computationally intractable. Here we introduce MarkerMap, a generative model for selecting minimal gene sets which are maximally informative of cell type origin and enable whole transcriptome reconstruction. MarkerMap provides a scalable framework for both supervised marker selection, aimed at identifying specific cell type populations, and unsupervised marker selection, aimed at gene expression imputation and reconstruction. We benchmark MarkerMap’s competitive performance against previously published approaches on real single cell gene expression data sets. MarkerMap is available as a pip installable package, as a community resource aimed at developing explainable machine learning techniques for enhancing interpretability in single-cell studies.
Advanced methods for insect nets: red-colored nets contribute to sustainable agriculture
Authors: Tokumaru Susumu , Tokushima Yoshiaki , Ito Shun , Yamaguchi Terumi , Shimoda Masami
Published: February 2024

Development of advanced pest control methods that do not rely on insecticides is an important issue for sustainable agriculture. Particularly with regards to micro pests that are not only highly resistant to various insecticides but also because we are running out of options for which insecticide to use against them, resulting in enormous economic damage worldwide. Here we report that the effectiveness of the conventional insect net can be greatly advanced by changing their color to red that helps significantly reduce pesticide use. We demonstrate the red effect using Onion thrips, Thrips tabaci a main vector of Iris Yellow Spot Virus (IYSV) and Tomato Spotted Wilt Virus (TSWV) that cause serious damage to various vegetables. New red nets succeeded in suppressing the invasion rates and damages (white spots on the leaves) in a Welsh onion greenhouse with minimum use of pesticides. We discuss how red nets are compatible with labor-saving, sustainable agriculture and the future potential of “optical pest control” based on insect color vision and its behavioral response.
Novel hybrid kepler optimization algorithm for parameter estimation of photovoltaic modules
Authors: Mohamed Reda , Abdel-Basset Mohamed , Sallam Karam M. , Hezam Ibrahim M. , Alshamrani Ahmad M. , Hameed Ibrahim A.
Published: February 2024

The parameter identification problem of photovoltaic (PV) models is classified as a complex nonlinear optimization problem that cannot be accurately solved by traditional techniques. Therefore, metaheuristic algorithms have been recently used to solve this problem due to their potential to approximate the optimal solution for several complicated optimization problems. Despite that, the existing metaheuristic algorithms still suffer from sluggish convergence rates and stagnation in local optima when applied to tackle this problem. Therefore, this study presents a new parameter estimation technique, namely HKOA, based on integrating the recently published Kepler optimization algorithm (KOA) with the ranking-based update and exploitation improvement mechanisms to accurately estimate the unknown parameters of the third-, single-, and double-diode models. The former mechanism aims at promoting the KOA’s exploration operator to diminish getting stuck in local optima, while the latter mechanism is used to strengthen its exploitation operator to faster converge to the approximate solution. Both KOA and HKOA are validated using the RTC France solar cell and five PV modules, including Photowatt-PWP201, Ultra 85-P, Ultra 85-P, STP6-120/36, and STM6-40/36, to show their efficiency and stability. In addition, they are extensively compared to several optimization techniques to show their effectiveness. According to the experimental findings, HKOA is a strong alternative method for estimating the unknown parameters of PV models because it can yield substantially different and superior findings for the third-, single-, and double-diode models.
The role of strategic visibility in shaping wayfinding behavior in multilevel buildings
Authors: Gath-Morad Michal , Grübel Jascha , Steemers Koen , Sailer Kerstin , Ben-Alon Lola , Hölscher Christoph , Aguilar Leonel
Published: February 2024

In this paper, we explore the mutual effect of prior background expectations and visibility afforded by the 3D configuration of the physical environment on wayfindingefficiencyandstrategyin multilevel buildings. We perform new analyses on data from 149 participants who performed six unaided and directed wayfinding tasks in virtual buildings with varying degrees of visibility. Our findings reveal that the interaction between visibility and prior background expectations significantly affects wayfinding efficiency and strategy during between-floor wayfinding tasks. We termed this interaction effectstrategic visibility, which emphasizes the importance of the strategic allocation of visibility towards actionable building elements in promoting efficient wayfinding and shaping wayfinding strategy. Our study highlights the significance ofstrategic visibilityin promoting inclusive and accessible built environments for neurodiversity. Finally, we provide an open-source dataset that can be used to develop and test new wayfinding theories and models to advance research in the emerging field of human-building interaction.
Analysis of the transplacental transmission of SARS CoV-2 virus and antibody transfer according to the gestational age at maternal infection
Authors: Lucot-Royer Louise , Nallet Camille , Vouga Manon , Puyraveau Marc , Mauny Frederic , Marty-Quinternet Solène , Bertholdt Charline , Bory Jean-Paul , Devalland Christine , Canaguier Margaux , Copolla Camille , Eszto Marie-Laure , Montoya Yohny , Roesch Marion , Reviron Sandrine , Riethmuller Didier , Rufenacht Emma , Simon Emmanuel , Mottet Nicolas
Published: February 2024

To quantify transplacental transmission of SARS-CoV-2 virus and antibody transfer in pregnant women and their newborns according to the gestational age at maternal infection. A prospective observational multicenter study including pregnant women with a positive RT-PCR or a positive serology for SARS-CoV-2 and compatible symptoms, from April to December 2020, in 11 French maternities. The study was designed to obtain a systematic collection of mother-infant dyad’s samples at birth. SARS-CoV-2 viral load was measured by RT-PCR. IgG and IgM antibodies against the SARS-CoV-2 spike protein were measured by enzyme-linked immunosorbent assay. Antibody concentrations and transplacental transfer ratios were analyzed according to the gestational age at maternal infection. The primary outcome was the rate of SARS CoV-2 materno-fetal transmission at birth. The secondary outcome was the quantification of materno-fetal antibody transfer. Maternal and neonatal outcomes at birth were additionally assessed. Among 165 dyads enrolled, one congenital infection was confirmed {n = 1 (0.63%) IC95% [0.02%; 3.48%]}. The average placental IgG antibody transfer ratio was 1.27 (IC 95% [0.69–2.89]). The transfer ratio increased with increasing time between the onset of maternal infection and delivery (P Value = 0.0001). Maternal and neonatal outcomes were reassuring. We confirmed the very low rate of SARS-CoV-2 transplacental transmission (< 1%). Maternal antibody transfer to the fetus was more efficient when the infection occurred during the first and second trimester of pregnancy.
Exponential super-twisting control for nonlinear systems with unknown polynomial perturbations
Authors: Liu Jianghua , Zhu Jiang , Khayati Karim , Zhong Dong , Jiang Jinguang
Published: February 2024

The study focuses on the control of nonlinear dynamic systems in the presence of parameter uncertainties, unmodeled dynamics, and external disturbances. The lumped perturbation is assumed to be bounded within a polynomial in the system state with the polynomial parameters and degrees unknown a priori such that it accommodates a quite wider range dynamic systems. Based on the studies in recent super-twisting algorithm designs and the idea from adaptive sliding mode control for nonlinear systems with uncertainties, we propose a novel adaptive super-twisting algorithm with exponential reaching law, or exponential super-twisting algorithm (ESTA), for the high-stability and acceptable accuracy control of the aimed nonlinear dynamics. The stability analysis and practical finite-time (PFT) convergence are proven using Lyapunov theory and an intuitive analysis of the control behaviour. Simulations are performed to compare the proposed ESTA with the existing super-twisting method and the traditional proportional integral differential control. The simulation results demonstrate the effectiveness of the proposed ESTA in terms of the fastest settling time and the smallest overshoot.
Gut microbiome signature of metabolically healthy obese individuals according to anthropometric, metabolic and inflammatory parameters
Authors: Lee Ho-Kyoung , Kim Nam-Eun , Shin Cheol Min , Oh Tae Jung , Yoon Hyuk , Park Young Soo , Kim Nayoung , Won Sungho , Lee Dong Ho
Published: February 2024

In this study, we investigated the characteristics of gut microbiome in the metabolically healthy obese (MHO) patients, and how they correlate with metabolic and inflammatory profiles. A total of 120 obese people without metabolic comorbidities were recruited, and their clinical phenotypes, metabolic and inflammatory parameters were analysed. The faecal microbial markers originating from bacterial cell and extracellular vesicle (EV) were profiled using 16S rDNA sequencing. The total study population could be classified into two distinct enterotypes (enterotype I: Prevotellaceae-predominant, enterotype II: Akkermansia/Bacteroides-predominant), based on their stool EV-derived microbiome profile. When comparing the metabolic and inflammatory profiles, subjects in enterotype I had higher levels of serum IL-1β [false discovery rate (FDR) q = 0.050] and had a lower level of microbial diversity than enterotype II (Wilcoxon rank-sum test p < 0.01). Subjects in enterotype I had relatively higher abundance of Bacteroidetes, Prevotellaceae and Prevotella-derived EVs, and lower abundance of Actinobacteria, Firmicutes, Proteobacteria, Akkermansia and Bacteroides-derived EVs (FDR q < 0.05). In conclusion, HMO patients can be categorised into two distinct enterotypes by the faecal EV-derived microbiome profile. The enterotyping may be associated with different metabolic and inflammatory profiles. Further studies are warranted to elucidate the long-term prognostic impact of EV-derived microbiome in the obese population.
Mental health disorders among medical students during the COVID-19 pandemic in the area with no mandatory lockdown: a multicenter survey in Tanzania
Authors: Bintabara Deogratius , Singo Joseph B. , Mvula Mathew , Jofrey Sichone , Shayo Festo K.
Published: February 2024

The COVID-19 pandemic brought about a major public health concern worldwide. It forced many countries to enforce lockdowns, leading to the closure of higher learning institutions. The abrupt shift in the lifestyle of students had a profound impact on their mental health. This study aims to determine the prevalence and factors associated with mental health conditions among university students in Tanzania during the COVID-19 pandemic. A sample of 425 students from six medical universities and colleges in Tanzania completed an online survey and was included in the analysis. The questionnaire consisted of validated Depression, Anxiety and Stress Scale—21 Items (DASS-21) questions (Cronbach’s alpha = 0.92) assessing the presence of mental health symptoms: depression, anxiety, and stress. Multivariable logistic regression models were fitted to explain the factors associated with mental health conditions. A P-value < 0.05 was considered statistically significant in all inferential analyses. The median age (interquartile range) of the participants was 24 (22–26). The prevalence of mental health conditions was 28.94%, 54.12%, and 15.06% for depression, anxiety, and stress, respectively, while the prevalence of having any mental health condition was 58.59%. In an adjusted regression model, being in the fourth and fifth years of study and living with a spouse were significantly associated with increased odds of depression: AOR = 5.99 (1.31–27.47), AOR = 5.52 (1.18–25.81), and AOR = 1.84 (1.08–3.15), respectively. Moreover, studying in private universities and living with a spouse were significantly associated with an increased likelihood of anxiety: AOR = 2.35 (1.72–2.76), and AOR = 2.32 (1.20–4.50), respectively. The likelihood of stress was only among participants studying in private universities; AOR = 2.90 (1.60–5.27). The study revealed alarmingly high rates of mental health conditions among medical students in Tanzania during the COVID-19 pandemic. The findings suggest the need for regular checkups for medical students regarding their mental health status. Additionally, it recommends that the government and other stakeholders establish mental health services within the universities for the effective prevention of the rising burden of mental health problems among universities in Tanzania and other countries with similar settings.
Battery deactivation with redox shuttles for safe and efficient recycling
Authors: Mikita Riho , Suzumura Akitoshi , Kondo Hiroki
Published: February 2024

To safely recycle spent lithium-ion batteries (LIBs), their deactivation as a pretreatment is essential. However, the conventional deactivation methods, mainly inducing an external short circuit, cannot be applied to LIBs with disconnected electrical circuits or Li deposited, despite their safety risk. Here, we propose a deactivation method using redox shuttles (RSs). The addition of an RS with redox potentials located between the two electrode potentials into a LIB electrochemically induces an internal short circuit with or without disconnected electrical circuits. A fully charged LIB discharges to approximately 0 V when a deactivation agent containing ferrocene or phenothiazine as an RS is added. Moreover, we demonstrate that RSs introduced into LIB can simultaneously dissolve Li deposited on the negative electrode surface and return it to the positive electrode as mobile ions. These characteristics of our method contribute to the improvement in safety and collection rate of Li in the recycling processes, promoting the sustainability of LIBs.
Spatial transcriptomics reveals alterations in perivascular macrophage lipid metabolism in the onset of Wooden Breast myopathy in broiler chickens
Authors: Wang Ziqing , Khondowe Paul , Brannick Erin , Abasht Behnam
Published: February 2024

This study aims to use spatial transcriptomics to characterize the cell-type-specific expression profile associated with the microscopic features observed in Wooden Breast myopathy. 1 cm3 muscle sample was dissected from the cranial part of the right pectoralis major muscle from three randomly sampled broiler chickens at 23 days post-hatch and processed with Visium Spatial Gene Expression kits (10X Genomics), followed by high-resolution imaging and sequencing on the Illumina Nextseq 2000 system. WB classification was based on histopathologic features identified. Sequence reads were aligned to the chicken reference genome (Galgal6) and mapped to histological images. Unsupervised K-means clustering and Seurat integrative analysis differentiated histologic features and their specific gene expression pattern, including lipid laden macrophages (LLM), unaffected myofibers, myositis and vasculature. In particular, LLM exhibited reprogramming of lipid metabolism with up-regulated lipid transporters and genes in peroxisome proliferator-activated receptors pathway, possibly through P. Moreover, overexpression of fatty acid binding protein 5 could enhance fatty acid uptake in adjacent veins. In myositis regions, increased expression of cathepsins may play a role in muscle homeostasis and repair by mediating lysosomal activity and apoptosis. A better knowledge of different cell-type interactions at early stages of WB is essential in developing a comprehensive understanding.
Post-COVID-19 patients suffer from chemosensory, trigeminal, and salivary dysfunctions
Authors: Rogn Åsmund , Jensen Janicke Liaaen , Iversen Per Ole , Singh Preet Bano
Published: February 2024

Recent literature indicates that post-COVID-19 patients suffer from a plethora of complications, including chemosensory dysfunction. However, little attention has been given to understand the interactions between chemosensory, trigeminal, and salivary dysfunctions in these patients. The aims of this study were (1) to investigate the prevalence and combinations of chemosensory, trigeminal, and salivary dysfunctions, (2) to identify the odorants/tastants that are compromised, and (3) to explore possible associations between the four dysfunctions in post-COVID-19 patients. One hundred post-COVID-19 patients and 76 healthy controls (pre-COVID-19) were included in this cross-sectional, case-controlled study. Participants' smell, taste, trigeminal, and salivary functions were assessed. The patients had a significantly higher prevalence of parosmia (80.0%), hyposmia (42.0%), anosmia (53.0%), dysgeusia (34.0%), complete ageusia (3.0%), specific ageusia (27.0%), dysesthesia (11.0%) and dry mouth (18.0%) compared to controls (0.0% for all parameters, except 27.6% for hyposmia). Complete loss of bitter taste was the most prevalent specific ageusia (66.7%) and coffee was the most common distorted smell (56.4%). Seven different combinations of dysfunction were observed in the patients, the most common being a combination of olfactory and gustatory dysfunction (48.0%). These findings indicate that post-COVID-19 patients experience a range of chemosensory, trigeminal, and salivary disturbances, occurring in various combinations.
Crystal structures, phase transitions, thermodynamics, and molecular dynamics of organic–inorganic hybrid crystal [NH(CH3)3]2ZnCl4
Authors: Kim A Young , Na Changyub , Lim Ae Ran
Published: February 2024

Understanding the physical properties of organic–inorganic hybrid [NH(CH3)3]2ZnCl4 is necessary for its potential application in batteries and fuel cells due to its environmentally-friendly, and highly stable character. Here, we determine its overall properties in detail, such as its orthorhombic crystal structure, and phase transition temperatures associated with five different phases. Structural geometry was studied by the chemical shifts caused by the local field around 1H. No changes were observed for the environment around 1H for CH3, whereas the 1H chemical shifts around NH in the cation were shown due to the change in the hydrogen bond N‒H···Cl. This is related to the change in Cl around Zn in the anion. In addition, the coordination geometry of 14N and 1H around 13C exhibited increased symmetry at high temperatures. Finally, we were able to understand its molecular dynamics by the significant change with temperature observed from the spin–lattice relaxation time T1ρ values, which represent the energy transfer for the 1H and 13C atoms of the cation. The activation energies obtained from the T1ρ results were 3–4 times large at phase I (> 348 K) than at phase V and IV (< 286 K). The relaxations show that the energy barriers in phases IV and V are related to the reorientation of methyl groups around the triple symmetry axis, while the reorientation of methyl groups of the cation in phase I is related to as a whole.
Assessing heatwave effects on disabled persons in South Korea
Authors: Kang Yeji , Baek Ingul , Park Jongchul
Published: February 2024

This study investigated the risk of heatwaves for people with disabilities and other socioeconomic attributes using Health Care Bigdata in South Korea. The Health Care Bigdata provides detailed information on heat-related illness (HRI) patients in 2011–2020 from seven major cities. We employed the Distributed Lag Nonlinear Model (DLNM) to measure heat waves' relative risk. Our findings are four-fold. First, the relative risk (RR) of disabled people was 5.075 (95% confidence interval 4.476–5.674), significantly surpassing that of non-disabled people, 3.296 (2.517–4.075). Second, among various personal characteristics studied, disability influenced RR the most, exceeding impacts from elderly (4.457: 3.748–5.166), low-income (3.909: 3.004–4.813), and outdoor (4.052: 2.940–5.164). Third, the disabled young group (5.305: 4.414–6.195) was more vulnerable than the non-disabled elderly group (4.287: 3.576–4.999). Lastly, no significant difference in relative risk was observed between the mild (4.413: 3.855–4.971) and severe disabled groups (4.013: 3.121–4.905).
A machine learning model to predict privacy fatigued users from social media personalized advertisements
Authors: Alwafi Ghadeer , Fakieh Bahjat
Published: February 2024

The increasing use of social media platforms as personalized advertising channels is a double-edged sword. A high level of personalization on these platforms increases users’ sense of losing control over personal data: This could trigger the privacy fatigue phenomenon manifested in emotional exhaustion and cynicism toward privacy, which leads to a lack of privacy-protective behavior. Machine learning has shown its effectiveness in the early prediction of people’s psychological state to avoid such consequences. Therefore, this study aims to classify users with low and medium-to-high levels of privacy fatigue, based on their information privacy awareness and big-five personality traits. A dataset was collected from 538 participants via an online questionnaire. The prediction models were built using the Support Vector Machine, Naïve Bayes, K-Nearest Neighbors, Decision Tree, and Random Forest classifiers, based on the literature. The results showed that awareness and conscientiousness trait have a significant relationship with privacy fatigue. Support Vector Machine and Naïve Bayes classifiers outperformed the other classifiers by attaining a classification accuracy of 78%, F1 of 87%, recall of 100% and 98%, and precision of 78% and 79% respectively, using five-fold cross-validation.
Structure–activity relationships for the G-quadruplex-targeting experimental drug QN-302 and two analogues probed with comparative transcriptome profiling and molecular modeling
Authors: Ahmed Ahmed Abdullah , Chen Shuang , Roman-Escorza Maria , Angell Richard , Oxenford Sally , McConville Matthew , Barton Naomi , Sunose Mihiro , Neidle Dan , Haider Shozeb , Arshad Tariq , Neidle Stephen
Published: February 2024

The tetrasubstituted naphthalene diimide compound QN-302 binds to G-quadruplex (G4) DNA structures. It shows high potency in pancreatic ductal adenocarcinoma (PDAC) cells and inhibits the transcription of cancer-related genes in these cells and in PDAC animal models. It is currently in Phase 1a clinical evaluation as an anticancer drug. A study of structure–activity relationships of QN-302 and two related analogues (CM03 and SOP1247) is reported here. These have been probed using comparisons of transcriptional profiles from whole-genome RNA-seq analyses, together with molecular modelling and molecular dynamics simulations. Compounds CM03 and SOP1247 differ by the presence of a methoxy substituent in the latter: these two compounds have closely similar transcriptional profiles. Whereas QN-302 (with an additional benzyl-pyrrolidine group), although also showing down-regulatory effects in the same cancer-related pathways, has effects on distinct genes, for example in the hedgehog pathway. This distinctive pattern of genes affected by QN-302 is hypothesized to contribute to its superior potency compared to CM03 and SOP1247. Its enhanced ability to stabilize G4 structures has been attributed to its benzyl-pyrrolidine substituent fitting into and filling most of the space in a G4 groove compared to the hydrogen atom in CM03 or the methoxy group substituent in SOP1247.
Stress and strain analysis and parameter optimization of pipe truss tower connection of super-large tower crane based on FEM
Authors: Zeng Guang , Chen Kun , Wang Yupeng , Liu Yuanpeng , Zhang Qian , Zhang Yalong
Published: February 2024

Clamping bushing structure is an internode connection mechanism designed for the standard section of tubular truss tower. In this paper, the clamping bushing structure of the connecting mechanism of super-large tower crane is taken as the research object, a three-dimensional model of clamping bushing structure is established and imported into ABAQUS, and its multi-body contact model is further constructed to study the contact and bearing relationship of the structure under multiple working conditions, and the accuracy of the calculation results of the model is verified by the experimental stress test under tensile working conditions. In addition, this study is based on the control variable method, and through the design of orthogonal test table, the influence degree of five variable parameters of clamping bushing on the bearing capacity of the structure is investigated. Finally, through the range analysis, the optimal horizontal combination of variables and parameters of clamping bushing structure is obtained, and the optimal matching relationship between the shape of the tower connecting mechanism and the bearing capacity is obtained. The results show that, compared with the original model, the stress concentration at the most dangerous section of the optimized joint and the bushing is obviously alleviated, in which the stress peaks of the upper and lower joints are kept below 500 MPa, and the stress peaks of the bushing groove are also reduced to between 573 and 722 MPa. Moreover, the designed and optimized lower joint can reduce the maximum equivalent plastic strain of the joint root circumference by 56.05% under the original maximum tensile condition, and the overall distribution trend of equivalent plastic strain is more uniform, and a more reliable structural design is obtained, which plays an important guiding role in the design, optimization and analysis of the connecting mechanism of the tower body of large tower crane.
Convergent evolution of BRCA2 reversion mutations under therapeutic pressure by PARP inhibition and platinum chemotherapy
Authors: Walmsley Charlotte S. , Jonsson Philip , Cheng Michael L. , McBride Sean , Kaeser Christopher , Vargas Herbert Alberto , Laudone Vincent , Taylor Barry S. , Kappagantula Rajya , Baez Priscilla , Richards Allison L. , Noronha Anne Marie , Perera Dilmi , Berger Michael , Solit David B. , Iacobuzio-Donahue Christine A. , Scher Howard I. , Donoghue Mark T. A. , Abida Wassim , Schram Alison M.
Published: February 2024

Reversion mutations that restore wild-type function of the BRCA gene have been described as a key mechanism of resistance to Poly(ADP-ribose) polymerase (PARP) inhibitor therapy in BRCA-associated cancers. Here, we report a case of a patient with metastatic castration-resistant prostate cancer (mCRPC) with a germline BRCA2 mutation who developed acquired resistance to PARP inhibition. Extensive genomic interrogation of cell-free DNA (cfDNA) and tissue at baseline, post-progression, and postmortem revealed ten unique BRCA2 reversion mutations across ten sites. While several of the reversion mutations were private to a specific site, nine out of ten tumors contained at least one mutation, suggesting a powerful clonal selection for reversion mutations in the presence of therapeutic pressure by PARP inhibition. Variable cfDNA shed was seen across tumor sites, emphasizing a potential shortcoming of cfDNA monitoring for PARPi resistance. This report provides a genomic portrait of the temporal and spatial heterogeneity of prostate cancer under the selective pressure of a PARP inhibition and exposes limitations in the current strategies for detection of reversion mutations.
Recreational mobility prior and during the COVID-19 pandemic
Authors: Ghadiri Zahra , Mashhadi Afra , Timme Marc , Ghanbarnejad Fakhteh
Published: February 2024

The COVID-19 pandemic and the resulting economic recession negatively affected many people’s physical, social, and psychological health and has been shown to change population-level mobility, but little attention has been given to park visitations as an indicator. Estimating the frequency of park visitations from aggregated mobility data of all the parks in Washington State (USA), we study trends in park use one year prior to and two years during the COVID-19 pandemic. Our findings indicate that the gravity model is a robust model for the park visitation behavior in different spatial resolutions of city level and state level and different socio-economical classes. Incorporating network structure, our detailed analysis highlights that high-income level residents changed their recreational behavior by visiting their local parks more and a broader recreational options outside of their local census area; whereas the low-income residents changed their visitation behavior by reducing their recreational choices.
Machine learning reveals features of spinon Fermi surface
Authors: Zhang Kevin , Feng Shi , Lensky Yuri D. , Trivedi Nandini , Kim Eun-Ah
Published: February 2024

With rapid progress in simulation of strongly interacting quantum Hamiltonians, the challenge in characterizing unknown phases becomes a bottleneck for scientific progress. We demonstrate that a Quantum-Classical hybrid approach (QuCl) of mining sampled projective snapshots with interpretable classical machine learning can unveil signatures of seemingly featureless quantum states. The Kitaev-Heisenberg model on a honeycomb lattice under external magnetic field presents an ideal system to test QuCl, where simulations have found an intermediate gapless phase (IGP) sandwiched between known phases, launching a debate over its elusive nature. We use the correlator convolutional neural network, trained on labeled projective snapshots, in conjunction with regularization path analysis to identify signatures of phases. We show that QuCl reproduces known features of established phases. Significantly, we also identify a signature of the IGP in the spin channel perpendicular to the field direction, which we interpret as a signature of Friedel oscillations of gapless spinons forming a Fermi surface. Our predictions can guide future experimental searches for spin liquids.
Influence of size, volume concentration and aggregation state on magnetic nanoparticle hyperthermia properties versus excitation conditions
Authors: Ferrero Riccardo , Vicentini Marta , Manzin Alessandra
Published: February 2024

A micromagnetic model is used to evaluate the heating properties of Fe3O4 nanoparticles versus size, concentration, aggregation order, and AC magnetic field parameters. The obtained data can guide nanoparticle design in view of hyperthermia application.
Formation of an instantaneous nick for highly efficient adenylation of oligonucleotides by ligase without subsequent jointing
Authors: Hu Kunling , Sun Wenhua , Chen Hui , Luo Jian , Song Ziting , An Ran , Komiyama Makoto , Liang Xingguo
Published: February 2024

By forming a nick instantaneously, nucleic acids are efficiently adenylated by T4 DNA ligase without further ligation.
Exploring solar energy systems: A comparative study of optimization algorithms, MPPTs, and controllers
Authors: Güven Aykut Fatih
Published: February 2024

This study elucidates the use of optimization algorithms to identify the controller parameters employed in adjusting the current and voltage values of loads powered by solar energy systems and battery groups. Parameters for these controllers were independently derived using a combination of ant colony optimization with Levy flight, hybrid firefly‐particle swarm optimization, hybrid gravitation search algorithm‐particle swarm optimization, alongside the implementation of Jaya and whale optimization algorithms. The results from each method were juxtaposed for thorough analysis. In addition, three distinct Maximum Power Point Tracker (MPPT) algorithms were employed in the system: perturbation and observation, open circuit voltage, and incremental conductance (IC). To assess the system’s adaptability to real‐world conditions, it was tested against varying temperatures and sunlight levels. Moreover, potential changes in the loads were considered by varying the load. The efficacy of the controllers was examined by altering both the environment and load. The effectiveness of the controllers was examined by referring to the integral of time‐weighted absolute error value. The system was simulated using MATLAB/Simulink software. This study demonstrates that the fractional‐order PID controller achieves the most effective results, the Jaya algorithm provides the best controller parameters, and the IC technique exhibits the highest performance in MPPT.
Ab initio simulations of neutron stars’ oblique electrospheres with realistic neutron star parameters
Authors: Mottez F.
Published: February 2024

Context. Electrospheres are environments with the same origin as pulsars; a highly magnetized rotating neutron star. In pulsars, a cascade of electron-positron pair creation enriches the plasma. The plasma surrounding an electrosphere consists only of particles that have escaped from the neutron star’s surface. Electrospheres with a magnetic axis aligned with the rotation axis have been well described for decades. Models of electrospheres with an oblique magnetic axis relative to the rotation axis have resisted most theoretical investigations. Some electrospheres and pulsars have been simulated using particle-in-cell codes, but the numerical constraints did not allow the use of realistic neutron star parameters.

Aims. We aimed to develop a numerical simulation code optimized for understanding the physics of electrospheres and pulsars, with realistic neutron star parameters. As a first step, presented in this paper, we focused on the simulation of oblique electrospheres with realistic physical parameters.

Methods. A specific code was developed for the computation of stationary solutions. The resolution of Maxwell’s equations was based on spectral methods. Particle motions included their finite inertia. No hypothesis was made in relation to the force-free behavior of the electrospheric plasma. The numerical code is called Pulsar ARoMa (pulsar asymmetric rotating magnetosphere).

Results. Various numerical simulations were conducted using realistic neutron star parameters. We find that oblique electrospheres possess the same global structure as aligned force-free electrospheres, with two domes of electrons and a torus of positively charged particles. The domes are not centered on the magnetic axis; nor are they symmetric. Yet, the solutions do not exhibit a force-free behavior.

Conclusions. The simulations performed with the Pulsar ARoMa code require modest resources and little computing time. This code will be upgraded for more ambitious investigations into pulsar physics.
The Astrochemistry Low-energy Electron Cross-Section (ALeCS) database
Authors: Gaches Brandt A. L. , Grassi Tommaso , Vogt-Geisse Stefan , Bovolenta Giulia M. , Vallance Claire , Heathcote David , Padovani Marco , Bovino Stefano , Gorai Prasanta
Published: February 2024

Context. Electron–molecule interaction is a fundamental process in radiation-driven chemistry in space, from the interstellar medium to comets. Therefore, knowledge of interaction cross sections is key. There have been a plethora of both theoretical and experimental studies of total ionization cross sections spanning from diatomics to complex organics. However, the data are often spread over many sources or are not public or readily available.

Aims. We introduce the Astrochemistry Low-energy Electron cross-section (ALeCS) database. This is a public database for electron interaction cross sections and ionization rates for molecules of astrochemical interest. In particular, we present here the first data release, comprising total ionization cross sections and ionization rates for over 200 neutral molecules.

Methods. We include optimized geometries and molecular orbital energies at various levels of quantum chemistry theory. Furthermore, for a subset of the molecules, we have calculated ionization potentials. We computed the total ionization cross sections using the binary-encounter Bethe model and screening-corrected additivity rule, and we computed ionization rates and reaction network coefficients for molecular cloud environments.

Results. We present the cross sections and reaction rates for >200 neutral molecules ranging from diatomics to complex organics, with the largest being C14H10. We find that the screening-corrected additivity rule cross sections generally significantly overestimate experimental total ionization cross sections. We demonstrate that our binary-encounter Bethe cross sections agree well with experimental data. We show that the ionization rates scale roughly linearly with the number of constituent atoms in the molecule.

Conclusions. We introduce and describe the public ALeCS database. For the initial release, we include total ionization cross sections for >200 neutral molecules and several cations and anions calculated with different levels of quantum chemistry theory, the chemical reaction rates for the ionization, and network files in the formats of the two most popular astrochemical networks: the Kinetic Database for Astrochemistry, and UMIST. The database will be continuously updated for more molecules and interactions.
Discovery of the first olivine-dominated A-type asteroid family
Authors: Galinier M. , Delbo M. , Avdellidou C. , Galluccio L.
Published: February 2024

The classical theory of differentiation states that due to the heat generated by the decay of radioactive elements, some asteroids form an iron core, an olivine-rich mantle, and a crust. The collisional breakup of these differentiated bodies is expected to lead to exposed mantle fragments, creating families of newly-formed asteroids. Among these new objects, some are expected to show an olivine-rich composition in spectroscopic observations. However, several years of spectrophotometric surveys have led to the conclusion that olivine-rich asteroids are rare in the asteroid main belt, and no significant concentration of olivine-rich bodies in any asteroid family has been detected to date. Using ESA’s Gaia DR3 reflectance spectra, we show that the family (36256) 1999 XT17 presents a prominence of objects that are likely to present an olivine-rich composition (A-type spectroscopic class). If S-complex asteroids as the second most prominent spectroscopic class in the family are real family members, then arguably the 1999 XT17 family has originated from the break-up of a partially differentiated parent body. Alternatively, if the S-complex asteroids are interlopers, then the 1999 XT17 family could have originated from the breakup of an olivine-rich body. This body could have been part of the mantle of a differentiated planetesimal, which may have broken up in a different region of the Solar System, and one of its fragments (i.e. the parent body of the 1999 XT17 family) could have been dynamically implanted in the main belt.
Research on skid resistance performance assessment and rehabilitation decision-making technology of asphalt pavement
Authors: Yan Chunyu , Zhang Zhenwei , Zhang Yuanpeng
Published: February 2024

In view of the lack of skid resistance of asphalt pavement of some highways, the representative section of a road were selected, combined with the analysis results of basic data and road condition data, field tests and laboratory tests were carried out to analyze the reasons for the decline of skid resistance. The attenuation law of asphalt pavement performance with traffic load was simulated by using the detection method at different positions of the road. According to the attenuation characteristics of different indexes, the evaluation methods of asphalt pavement skid resistance performance are refined. Based on the conclusions of special testing and analysis, the skid resistance performance evaluation model, road condition decay model and maintenance decision model were developed to carry out long-term maintenance planning for the road, keep the annual maintenance mileage stable during the planning period, and avoid the maintenance pressure concentrating on a few years. Combined with the current situation of road condition and attenuation law, the road condition in the planning period is predicted to prove the results of long-term maintenance planning under the decision model, which ensures the stability of the road condition level in the planning period.
The power of protest in the media: examining portrayals of climate activism in UK news
Authors: Scheuch Eric G. , Ortiz Mark , Shreedhar Ganga , Thomas-Walters Laura
Published: February 2024

Over the last several years, the United Kingdom has seen a wave of environmental movements demanding action on the climate crisis. While aligned in their goals, the groups undertaking this activism often diverge on the question of tactics. One such divergence occurred in January 2023, when Extinction Rebellion (XR) declared “We Quit”, ending actions that were disruptive to the general public. Peer groups Just Stop Oil and Animal Rising continued disruptive actions, viewing them as the best way to gain media coverage for their causes. Despite the urgency of addressing climate change and the growing prominence of direct action in British life, little research has examined how the news media covers and reacts to different climate actions. News media plays a vital role in influencing the public’s perception of the climate crisis and “appropriate” responses. We assembled a unique dataset of British news coverage of climate actions over a 7 month period, covering both before and after XR’s “We Quit” statement. Our results reveal that conservative publications cover climate actions more unfavorably and more inaccurately than other publications. Legal actions are generally covered more favorably than illegal ones in both conservative and non-conservative outlets and receive more coverage. Actions that target industry attract more coverage than those that target other actors, while actions that target the public are covered more favorably than those that do not. These results contribute to the scholarly debates surrounding the interaction between social movements and news media, especially on how different strategies potentially influence the extent and affective nature of coverage. They have implications for strategies adopted by climate advocates, depending on whether their goal is merely to draw attention to an issue or if it is to generate positive coverage.
Understanding how radial extracorporeal shockwave therapy reduces pain and aids in recovery
Authors: Shapiro Maura
Published: February 2024

Researchers fill the information gap regarding the treatment’s mechanism by analyzing the shockwaves in water.
Explaining super-resolution properties of contact microspheres
Authors: Thompson Avery
Published: February 2024

Using microspheres to achieve a resolution below the diffraction limit has been a microscopy technique for nearly a decade, but a theoretical explanation had remained elusive.