bluuebunny/crossref_metadata_2025_split huggingface dataset:
Artificially controlled nanoscale chemical reduction in VO2 through electron beam illumination
Authors: Zhang Yang , Wang Yupu , Wu Yongshun , Shu Xinyu , Zhang Fan , Peng Huining , Shen Shengchun , Ogawa Naoki , Zhu Junyi , Yu Pu 
Published: July 2023

AbstractChemical reduction in oxides plays a crucial role in engineering the material properties through structural transformation and electron filling. Controlling the reduction at nanoscale forms a promising pathway to harvest functionalities, which however is of great challenge for conventional methods (e.g., thermal treatment and chemical reaction). Here, we demonstrate a convenient pathway to achieve nanoscale chemical reduction for vanadium dioxide through the electron-beam illumination. The electron beam induces both surface oxygen desorption through radiolytic process and positively charged background through secondary electrons, which contribute cooperatively to facilitate the vacancy migration from the surface toward the sample bulk. Consequently, the VO2 transforms into a reduced V2O3 phase, which is associated with a distinct insulator to metal transition at room temperature. Furthermore, this process shows an interesting facet-dependence with the pronounced transformation observed for the c-facet VO2 as compared with the a-facet, which is attributed to the intrinsically different oxygen vacancy formation energy between these facets. Remarkably, we readily achieve a lateral resolution of tens nanometer for the controlled structural transformation with a commercial scanning electron microscope. This work provides a feasible strategy to manipulate the nanoscale chemical reduction in complex oxides for exploiting functionalities.
A survey of water utilities’ digital transformation: drivers, impacts, and enabling technologies
Authors: Daniel Ivo , Ajami Newsha K. , Castelletti Andrea , Savic Dragan , Stewart Rodney A. , Cominola Andrea 
Published: July 2023

AbstractClimate change and urbanization challenge utilities’ pursuit of water security worldwide. While water utilities are directly impacted by climate change, their operations also contribute to greenhouse gas emissions. Digital technologies have proven effective in improving utilities’ operations, leading to a more sustainable urban water cycle. However, the global progress of digital water transformation remains largely understudied. Here, we present the results of an online survey involving 64 utilities from 28 countries investigating the impacts of digital transformation on the water utility sector, its drivers, and key-enabling technologies. We found that the water distribution system is the entry point to further adoption of digital technologies in the whole urban water cycle. Furthermore, technology adoption is driven primarily by economic benefits, followed by government regulation and hydroclimatic factors. Starting from the survey results, we point out avenues for further research targeting a better understanding of the influence of regulation, corporate mindset, and consumer involvement for successful digital transformation.
High-resolution gridded population datasets for Latin America and the Caribbean using official statistics
Authors: McKeen Tom , Bondarenko Maksym , Kerr David , Esch Thomas , Marconcini Mattia , Palacios-Lopez Daniela , Zeidler Julian , Valle R. Catalina , Juran Sabrina , Tatem Andrew J. , Sorichetta Alessandro 
Published: July 2023

Abstract“Leaving no one behind” is the fundamental objective of the 2030 Agenda for Sustainable Development. Latin America and the Caribbean is marked by social inequalities, whilst its total population is projected to increase to almost 760 million by 2050. In this context, contemporary and spatially detailed datasets that accurately capture the distribution of residential population are critical to appropriately inform and support environmental, health, and developmental applications at subnational levels. Existing datasets are under-utilised by governments due to the non-alignment with their own statistics. Therefore, official statistics at the finest level of administrative units available have been implemented to construct an open-access repository of high-resolution gridded population datasets for 40 countries in Latin American and the Caribbean. These datasets are detailed here, alongside the ‘top-down’ approach and methods to generate and validate them. Population distribution datasets for each country were created at a resolution of 3 arc-seconds (approximately 100 m at the equator), and are all available from the WorldPop Data Repository.
Application of error classification model using indices based on dose distribution for characteristics evaluation of multileaf collimator position errors
Authors: Sheen Heesoon , Shin Han-Back , Kim Hojae , Kim Changhwan , Kim Jihun , Kim Jin Sung , Hong Chae-Seon 
Published: July 2023

AbstractThis study aims to evaluate the specific characteristics of various multileaf collimator (MLC) position errors that are correlated with the indices using dose distribution. The dose distribution was investigated using the gamma, structural similarity, and dosiomics indices. Cases from the American Association of Physicists in Medicine Task Group 119 were planned, and systematic and random MLC position errors were simulated. The indices were obtained from distribution maps and statistically significant indices were selected. The final model was determined when all values of the area under the curve, accuracy, precision, sensitivity, and specificity were higher than 0.8 (p < 0.05). The dose–volume histogram (DVH) relative percentage difference between the error-free and error datasets was examined to investigate clinical relations. Seven multivariate predictive models were finalized. The common significant dosiomics indices (GLCM Energy and GLRLM_LRHGE) can characterize the MLC position error. In addition, the finalized logistic regression model for MLC position error prediction showed excellent performance with AUC > 0.9. Furthermore, the results of the DVH were related to dosiomics analysis in that it reflects the characteristics of the MLC position error. It was also shown that dosiomics analysis could provide important information on localized dose-distribution differences in addition to DVH information.
Nomogram for predicting the likelihood of liver metastases at initial diagnosis in patients with Siewert type II gastroesophageal junction adenocarcinoma
Authors: Zhang Min , Yang Wenwen , Yang Yanjiang , Cai Chengfeng , Zhao Dan , Han Biao 
Published: July 2023

AbstractThe liver is one of the most ordinary metastatic sites of gastroesophageal junction adenocarcinoma and significantly affects its prognosis. Therefore, this study tried to construct a nomogram that can be applied to predict the likelihood of liver metastases from gastroesophageal junction adenocarcinoma. 3001 eligible patients diagnosed with gastroesophageal junction adenocarcinoma between 2010 and 2015 in the Surveillance, Epidemiology, and End Results (SEER) database were involved in the analysis. Patients were randomly divided into a training cohort and an internal validation cohort using R software, with an allocation ratio of 7:3. According to the consequences of univariate and multivariate logistic regression, we constructed a nomogram for predicting the risk of liver metastases. The discrimination and calibration ability of the nomogram was appraised by the C-index, ROC curve, calibration plots, and decision curve analysis (DCA). We also used Kaplan–Meier survival curves to compare differences in overall survival in patients with gastroesophageal junction adenocarcinoma with and without liver metastases. Liver metastases developed in 281 of 3001 eligible patients. The overall survival of patients with gastroesophageal junction adenocarcinoma with liver metastases before and after propensity score matching (PSM) was obviously lower than that of patients without liver metastases. Six risk factors were finally recognized by multivariate logistic regression, and a nomogram was constructed. The C-index was 0.816 in the training cohort and 0.771 in the validation cohort, demonstrating the good predictive capacity of the nomogram. The ROC curve, calibration curve, and decision curve analysis further demonstrated the good performance of the predictive model. The nomogram can accurately predict the likelihood of liver metastases in gastroesophageal junction adenocarcinoma patients.
Phenotypic consequences of a nanophthalmos-associated TMEM98 variant in human and mouse
Authors: Hassall Mark M. , Javadiyan Shari , Klebe Sonja , Awadalla Mona S. , Sharma Shiwani , Qassim Ayub , White Melissa , Thomas Paul Q. , Craig Jamie E. , Siggs Owen M. 
Published: July 2023

AbstractNanophthalmos is characterised by shorter posterior and anterior segments of the eye, with a predisposition towards high hyperopia and primary angle-closure glaucoma. Variants in TMEM98 have been associated with autosomal dominant nanophthalmos in multiple kindreds, but definitive evidence for causation has been limited. Here we used CRISPR/Cas9 mutagenesis to recreate the human nanophthalmos-associated TMEM98 p.(Ala193Pro) variant in mice. The p.(Ala193Pro) variant was associated with ocular phenotypes in both mice and humans, with dominant inheritance in humans and recessive inheritance in mice. Unlike their human counterparts, p.(Ala193Pro) homozygous mutant mice had normal axial length, normal intraocular pressure, and structurally normal scleral collagen. However, in both homozygous mice and heterozygous humans, the p.(Ala193Pro) variant was associated with discrete white spots throughout the retinal fundus, with corresponding retinal folds on histology. This direct comparison of a TMEM98 variant in mouse and human suggests that certain nanophthalmos-associated phenotypes are not only a consequence of a smaller eye, but that TMEM98 may itself play a primary role in retinal and scleral structure and integrity.
Non-autonomous zinc–methylimidazole oscillator and the formation of layered precipitation structures in a hydrogel
Authors: Német Norbert , Lawson Hugh Shearer , Holló Gábor , Valletti Nadia , Rossi Federico , Schuszter Gábor , Lagzi István 
Published: July 2023

AbstractOscillations are one of the intrinsic features of many animate and inanimate systems. The oscillations manifest in the temporal periodic change of one or several physical quantities describing the systems. In chemistry and biology, this physical quantity is the concentration of the chemical species. In most chemical oscillatory systems operating in batch or open reactors, the oscillations persist because of the sophisticated chemical reaction networks incorporating autocatalysis and negative feedback. However, similar oscillations can be generated by periodically changing the environment providing non-autonomous oscillatory systems. Here we present a new strategy for designing a non-autonomous chemical oscillatory system for the zinc–methylimidazole. The oscillations manifested in the periodic change of the turbidity utilizing the precipitation reaction between the zinc ions and 2-methylimidazole (2-met) followed by a partial dissolution of the formed precipitate due to a synergetic effect governed by the ratio of the 2-met in the system. Extending our idea spatiotemporally, we also show that these precipitation and dissolution phenomena can be utilized to create layered precipitation structures in a solid agarose hydrogel.
Recurrence prediction in clear cell renal cell carcinoma using machine learning of quantitative nuclear features
Authors: Matsubara Shuya , Saito Akira , Tokuyama Naoto , Muraoka Ryu , Hashimoto Takeshi , Satake Naoya , Nagao Toshitaka , Kuroda Masahiko , Ohno Yoshio 
Published: July 2023

AbstractThe recurrence of non-metastatic renal cell carcinoma (RCC) may occur early or late after surgery. This study aimed to develop a recurrence prediction machine learning model based on quantitative nuclear morphologic features of clear cell RCC (ccRCC). We investigated 131 ccRCC patients who underwent nephrectomy (T1-3N0M0). Forty had recurrence within 5 years and 22 between 5 and 10 years; thirty-seven were recurrence-free during 5–10 years and 32 were for more than 10 years. We extracted nuclear features from regions of interest (ROIs) using a digital pathology technique and used them to train 5- and 10-year Support Vector Machine models for recurrence prediction. The models predicted recurrence at 5/10 years after surgery with accuracies of 86.4%/74.1% for each ROI and 100%/100% for each case, respectively. By combining the two models, the accuracy of the recurrence prediction within 5 years was 100%. However, recurrence between 5 and 10 years was correctly predicted for only 5 of the 12 test cases. The machine learning models showed good accuracy for recurrence prediction within 5 years after surgery and may be useful for the design of follow-up protocols and patient selection for adjuvant therapy.
WormSwin: Instance segmentation of C. elegans using vision transformer
Authors: Deserno Maurice , Bozek Katarzyna 
Published: July 2023

AbstractThe possibility to extract motion of a single organism from video recordings at a large-scale provides means for the quantitative study of its behavior, both individual and collective. This task is particularly difficult for organisms that interact with one another, overlap, and occlude parts of their bodies in the recording. Here we propose WormSwin—an approach to extract single animal postures ofCaenorhabditis elegans(C. elegans) from recordings of many organisms in a single microscope well. Based on transformer neural network architecture our method segments individual worms across a range of videos and images generated in different labs. Our solutions offers accuracy of 0.990 average precision ($$\hbox {AP}_{0.50}$$AP0.50) and comparable results on the benchmark image dataset BBBC010. Finally, it allows to segment challenging overlapping postures of mating worms with an accuracy sufficient to track the organisms with a simple tracking heuristic. An accurate and efficient method forC. eleganssegmentation opens up new opportunities for studying of its behaviors previously inaccessible due to the difficulty in the worm extraction from the video frames.
Additive manufacturing in compact high-gain wideband antennas operating in mm-wave frequencies
Authors: Vaquero Álvaro F. , Rebollo Alejandro , Arrebola Manuel 
Published: July 2023

AbstractA wideband dual-reflector 3D-printed antenna is proposed to operate in the mm-Wave band. The design is based on a Cassegrain reflector optics but including a dielectric piece for merging the feeding system and the support structure of the subreflector. The operational principle of this antenna is presented, as well as the design parameters. Then, a prototype to operate at Ka-band is manufactured combining a 3D-printed technique using PLA as printable material and a spray to coating the antenna, providing a low-cost affordable solution. The different pieces of the antenna are evaluated, and the antenna is also measured in a spherical compact range. An excellent agreement between simulations and measurements is obtained, resulting in a $$48.2\%$$

48.2
%

of operational bandwidth. These results validate the use of coating procedures and the design technique at these demanding frequencies. Its operation shows a stable gain in the entire Ka-band (including $$28$$

28

and $$39 \mathrm{GHz}$$

39
GHz

), which makes the antenna as a suitable light, low-cost, and broadband solution for mm-Wave applications.
ENSO-driven abrupt phase shift in North Atlantic oscillation in early January
Authors: Geng Xin , Zhao Jiuwei , Kug Jong-Seong 
Published: July 2023

AbstractEl Niño-Southern Oscillation (ENSO) teleconnections exhibit a strong dependency on seasonally and intraseasonally varying mean states, leading to impactful short-term variations in regional climate. The North Atlantic Oscillation (NAO)-ENSO relation is a typical example, in that its phase relationship reverses systematically between the early and late winter. Here based on observations and an ensemble of atmosphere-only climate model simulations, we reveal that this NAO phase reversal occurs synchronously in early January, showing strong abruptness. We demonstrate that this abrupt NAO phase reversal is caused by the change in ENSO-induced Rossby wave-propagating direction from northeastward to southeastward over the northeastern North American region, which is largely governed by a climatological alteration of the local jet meridional shear. We also provide evidence that the North Atlantic intrinsic eddy–low-frequency flow feedback further amplifies the NAO responses. This ENSO-related abrupt NAO change offers an avenue for intraseasonal climate forecasting in the Euro-Atlantic region.
Genome analysis of Parmales, the sister group of diatoms, reveals the evolutionary specialization of diatoms from phago-mixotrophs to photoautotrophs
Authors: Ban Hiroki , Sato Shinya , Yoshikawa Shinya , Yamada Kazumasa , Nakamura Yoji , Ichinomiya Mutsuo , Sato Naoki , Blanc-Mathieu Romain , Endo Hisashi , Kuwata Akira , Ogata Hiroyuki 
Published: July 2023

AbstractThe order Parmales (class Bolidophyceae) is a minor group of pico-sized eukaryotic marine phytoplankton that contains species with cells surrounded by silica plates. Previous studies revealed that Parmales is a member of ochrophytes and sister to diatoms (phylum Bacillariophyta), the most successful phytoplankton group in the modern ocean. Therefore, parmalean genomes can serve as a reference to elucidate both the evolutionary events that differentiated these two lineages and the genomic basis for the ecological success of diatoms vs. the more cryptic lifestyle of parmaleans. Here, we compare the genomes of eight parmaleans and five diatoms to explore their physiological and evolutionary differences. Parmaleans are predicted to be phago-mixotrophs. By contrast, diatoms have lost genes related to phagocytosis, indicating the ecological specialization from phago-mixotrophy to photoautotrophy in their early evolution. Furthermore, diatoms show significant enrichment in gene sets involved in nutrient uptake and metabolism, including iron and silica, in comparison with parmaleans. Overall, our results suggest a strong evolutionary link between the loss of phago-mixotrophy and specialization to a silicified photoautotrophic life stage early in diatom evolution after diverging from the Parmales lineage.
Current capabilities and future perspectives of FCS: super-resolution microscopy, machine learning, and in vivo applications
Authors: Sankaran Jagadish , Wohland Thorsten 
Published: July 2023

AbstractFluorescence correlation spectroscopy (FCS) is a single molecule sensitive tool for the quantitative measurement of biomolecular dynamics and interactions. Improvements in biology, computation, and detection technology enable real-time FCS experiments with multiplexed detection even in vivo. These new imaging modalities of FCS generate data at the rate of hundreds of MB/s requiring efficient data processing tools to extract information. Here, we briefly review FCS’s capabilities and limitations before discussing recent directions that address these limitations with a focus on imaging modalities of FCS, their combinations with super-resolution microscopy, new evaluation strategies, especially machine learning, and applications in vivo.
Order–order assembly transition-driven polyamines detection based on iron−sulfur complexes
Authors: Zhang Yahui , Zhao Xiangyu , Qin Yue , Li Xiaopei , Chang Yongxin , Shi Zhenqiang , Song Mengyuan , Sun Wenjing , Xiao Jie , Li Zan , Qing Guangyan 
Published: July 2023

AbstractInnovative modes of response can greatly push forward chemical sensing processes and subsequently improve sensing performance. Classical chemical sensing modes seldom involve the transition of a delicate molecular assembly during the response. Here, we display a sensing mode for polyamine detection based on an order–order transition of iron–sulfur complexes upon their assembly. Strong validation proves that the unique order–order transition of the assemblies is the driving force of the response, in which the polyamine captures the metal ion of the iron–sulfur complex, leading it to decompose into a metal–polyamine product, accompanied by an order–order transition of the assemblies. This mechanism makes the detection process more intuitive and selective, and remarkably improves the detection efficiency, achieving excellent polyamines specificity, second-level response, convenient visual detection, and good recyclability of the sensing system. Furthermore, this paper also provides opportunities for the further application of the iron–sulfur platform in environment-related fields.
Robust control for affine nonlinear system with unknown time‐varying uncertainty under reinforcement learning framework
Authors: Guo Wenxin , Qin Weiwei , Hu Chen , Liu Jieyu 
Published: July 2023

AbstractThis paper investigates the adaptive robust control problem based on reinforcement learning for an affine nonlinear system with unknown time‐varying uncertainty. Inspired by the ability to estimate uncertainty of neural network, a novel policy iteration algorithm is proposed which alternates between the value evaluation, uncertainty estimation, and policy update steps until the adaptive robust control law is obtained. Especially during the step of uncertainty estimation, the unknown time‐varying uncertainty is approximated by a radial basis function neural network and introduce it into the reinforcement learning framework. By designing an appropriate utility function, the algorithm improves both convergence rate and final approximate error comparing with existing reinforcement learning algorithm. The Lyapunov stability theorem provides theoretical demonstrations of the stability and convergence. Furthermore, the uniformly ultimately bounded stability of the affine nonlinear system is demonstrated with unknown time‐varying uncertainty. Finally, the performance of the proposed algorithm is demonstrated through a torsion pendulum system.
Design of variable frequency dual transponder system for fixed point ranging
Authors: Xiaoxu Guo , Zhaobin Xu , Jiacheng Dai , Zhonghe Jin 
Published: July 2023

AbstractAiming at the problems of high system cost, complex ranging process, low ranging accuracy, and limited measurement distance in commonly used methods for ground fixed point distance measurement journals, a variable frequency microwave ranging system based on a dual transponder architecture is proposed in this letter. The system uses carrier dual transponder as an active forwarding architecture, utilizing the digital phase‐locked loop to obtain the high‐precision phase difference between two signals, and resolving the ambiguity through microwave frequency sweep within a certain range. The simulation results show that the system can quickly obtain the unambiguous distance between two fixed points, besides, driven by a high‐stability crystal oscillator, submillimetre accuracy can be achieved in km‐level ranging.