bluuebunny/crossref_metadata_2025_split huggingface dataset:
Emergent second law for non-equilibrium steady states
Authors: Freitas José Nahuel , Esposito Massimiliano 
Published: August 2022

AbstractThe Gibbs distribution universally characterizes states of thermal equilibrium. In order to extend the Gibbs distribution to non-equilibrium steady states, one must relate the self-information $${{{{{{{\mathcal{I}}}}}}}}(x)=-\!\log ({P}_{{{{{{{{\rm{ss}}}}}}}}}(x))$$
I

(

x

)

=
−

log

(

P

ss

(

x

)

)

of microstate x to measurable physical quantities. This is a central problem in non-equilibrium statistical physics. By considering open systems described by stochastic dynamics which become deterministic in the macroscopic limit, we show that changes $${{\Delta }}{{{{{{{\mathcal{I}}}}}}}}={{{{{{{\mathcal{I}}}}}}}}({x}_{t})-{{{{{{{\mathcal{I}}}}}}}}({x}_{0})$$
Δ
I
=
I

(

x

t

)

−
I

(

x

0

)

in steady state self-information along deterministic trajectories can be bounded by the macroscopic entropy production Σ. This bound takes the form of an emergent second law $${{\Sigma }}+{k}_{b}{{\Delta }}{{{{{{{\mathcal{I}}}}}}}}\,\ge \,0$$
Σ
+

k

b

Δ
I

≥

0
, which contains the usual second law Σ ≥ 0 as a corollary, and is saturated in the linear regime close to equilibrium. We thus obtain a tighter version of the second law of thermodynamics that provides a link between the deterministic relaxation of a system and the non-equilibrium fluctuations at steady state. In addition to its fundamental value, our result leads to novel methods for computing non-equilibrium distributions, providing a deterministic alternative to Gillespie simulations or spectral methods.
Investigation of the evolution of Pd-Pt supported on ceria for dry and wet methane oxidation
Authors: Divins Núria. J. , Braga Andrea , Vendrell Xavier , Serrano Isabel , Garcia Xènia , Soler Lluís , Lucentini Ilaria , Danielis Maila , Mussio Andrea , Colussi Sara , Villar-Garcia Ignacio J. , Escudero Carlos , Trovarelli Alessandro , Llorca Jordi 
Published: August 2022

AbstractEfficiently treating methane emissions in transportation remains a challenge. Here, we investigate palladium and platinum mono- and bimetallic ceria-supported catalysts synthesized by mechanical milling and by traditional impregnation for methane total oxidation under dry and wet conditions, reproducing those present in the exhaust of natural gas vehicles. By applying a toolkit of in situ synchrotron techniques (X-ray diffraction, X-ray absorption and ambient pressure photoelectron spectroscopies), together with transmission electron microscopy, we show that the synthesis method greatly influences the interaction and structure at the nanoscale. Our results reveal that the components of milled catalysts have a higher ability to transform metallic Pd into Pd oxide species strongly interacting with the support, and achieve a modulated PdO/Pd ratio than traditionally-synthesized catalysts. We demonstrate that the unique structures attained by milling are key for the catalytic activity and correlate with higher methane conversion and longer stability in the wet feed.
Achieving efficient power generation by designing bioinspired and multi-layered interfacial evaporator
Authors: Sun Zhuangzhi , Han Chuanlong , Gao Shouwei , Li Zhaoxin , Jing Mingxing , Yu Haipeng , Wang Zuankai 
Published: August 2022

AbstractWater evaporation is a natural phase change phenomenon occurring any time and everywhere. Enormous efforts have been made to harvest energy from this ubiquitous process by leveraging on the interaction between water and materials with tailored structural, chemical and thermal properties. Here, we develop a multi-layered interfacial evaporation-driven nanogenerator (IENG) that further amplifies the interaction by introducing additional bionic light-trapping structure for efficient light to heat and electric generation on the top and middle of the device. Notable, we also rationally design the bottom layer for sufficient water transport and storage. We demonstrate the IENG performs a spectacular continuous power output as high as 11.8 μW cm−2 under optimal conditions, more than 6.8 times higher than the currently reported average value. We hope this work can provide a new bionic strategy using multiple natural energy sources for effective power generation.
Self-shrinking soft demoulding for complex high-aspect-ratio microchannels
Authors: Fan Dongliang , Yuan Xi , Wu Wenyu , Zhu Renjie , Yang Xin , Liao Yuxuan , Ma Yunteng , Xiao Chufan , Chen Cheng , Liu Changyue , Wang Hongqiang , Qin Peiwu 
Published: August 2022

AbstractMicrochannels are the essential elements in animals, plants, and various artificial devices such as soft robotics, wearable sensors, and organs-on-a-chip. However, three-dimensional (3D) microchannels with complex geometry and a high aspect ratio remain challenging to generate by conventional methods such as soft lithography, template dissolution, and matrix swollen processes, although they are widespread in nature. Here, we propose a simple and solvent-free fabrication method capable of producing monolithic microchannels with complex 3D structures, long length, and small diameter. A soft template and a peeling-dominant template removal process are introduced to the demoulding process, which is referred to as soft demoulding here. In combination with thermal drawing technology, microchannels with a small diameter (10 µm), a high aspect ratio (6000, length-to-diameter), and intricate 3D geometries are generated. We demonstrate the vast applicability and significant impact of this technology in multiple scenarios, including soft robotics, wearable sensors, soft antennas, and artificial vessels.
Translational challenges and opportunities in biofilm science: a BRIEF for the future
Authors: Highmore C. J. , Melaugh G. , Morris R. J. , Parker J. , Direito S. O. L. , Romero M. , Soukarieh F. , Robertson S. N. , Bamford N. C. 
Published: August 2022

AbstractBiofilms are increasingly recognised as a critical global issue in a multitude of industries impacting health, food and water security, marine sector, and industrial processes resulting in estimated economic cost of $5 trillion USD annually. A major barrier to the translation of biofilm science is the gap between industrial practices and academic research across the biofilms field. Therefore, there is an urgent need for biofilm research to notice and react to industrially relevant issues to achieve transferable outputs. Regulatory frameworks necessarily bridge gaps between different players, but require a clear, science-driven non-biased underpinning to successfully translate research. Here we introduce a 2-dimensional framework, termed the Biofilm Research-Industrial Engagement Framework (BRIEF) for classifying existing biofilm technologies according to their level of scientific insight, including the understanding of the underlying biofilm system, and their industrial utility accounting for current industrial practices. We evidence the BRIEF with three case studies of biofilm science across healthcare, food & agriculture, and wastewater sectors highlighting the multifaceted issues around the effective translation of biofilm research. Based on these studies, we introduce some advisory guidelines to enhance the translational impact of future research.
Longitudinal corpus callosum microstructural decline in early-stage Parkinson’s disease in association with akinetic-rigid symptom severity
Authors: Amandola Matthew , Sinha Agniva , Amandola Mark J. , Leung Hoi-Chung 
Published: August 2022

AbstractPrevious diffusion tensor imaging (DTI) studies of Parkinson’s disease (PD) show reduced microstructural integrity of the corpus callosum (CC) relative to controls, although the characteristics of such callosal degradation remain poorly understood. Here, we utilized a longitudinal approach to identify microstructural decline in the entire volume of the CC and its functional subdivisions over 2 years and related the callosal changes to motor symptoms in early-stage PD. The study sample included 61 PD subjects (N = 61, aged 45–82, 38 M & 23 F, H&Y ≤ 2) from the Parkinson’s Progressive Markers Initiative database (PPMI). Whole-brain voxel-wise results revealed significant fractional anisotropy (FA) and mean diffusivity (MD) changes in the CC, especially in the genu and splenium. Using individually drawn CC regions of interest (ROI), our analysis further revealed that almost all subdivisions of the CC show significant decline in FA to certain extents over the two-year timeframe. Additionally, FA seemed lower in the right hemisphere of the CC at both time-points, and callosal FA decline was associated with FA and MD decline in widespread cortical and subcortical areas. Notably, multiple regression analysis revealed that across-subject akinetic-rigid severity was negatively associated with callosal FA at baseline and 24 months follow-up, and the effect was strongest in the anterior portion of the CC. These results suggest that callosal microstructure alterations in the anterior CC may serve as a viable biomarker for akinetic-rigid symptomology and disease progression, even in early PD.
A scheme to create and verify scalable entanglement in optical lattice
Authors: Zhou You , Xiao Bo , Li Meng-Da , Zhao Qi , Yuan Zhen-Sheng , Ma Xiongfeng , Pan Jian-Wei 
Published: August 2022

AbstractTo achieve scalable quantum information processing, great efforts have been devoted to the creation of large-scale entangled states in various physical systems. Ultracold atom in optical lattice is considered as one of the promising platforms due to its feasible initialization and parallel manipulation. In this work, we propose an efficient scheme to generate and characterize global entanglement in the optical lattice. With only two-layer quantum circuits, the generation utilizes two-qubit entangling gates based on the superexchange interaction in double wells. The parallelism of these operations enables the generation to be fast and scalable. To verify the entanglement of this non-stabilizer state, we mainly design three complementary detection protocols which are less resource-consuming compared to the full tomography. In particular, one just needs two homogenous local measurement settings to identify the entanglement property. Our entanglement generation and verification protocols provide the foundation for the further quantum information processing in optical lattice.
Socioeconomic roots of academic faculty
Authors: Morgan Allison C. , LaBerge Nicholas , Larremore Daniel B. , Galesic Mirta , Brand Jennie E. , Clauset Aaron 
Published: August 2022

AbstractDespite the special role of tenure-track faculty in society, training future researchers and producing scholarship that drives scientific and technological innovation, the sociodemographic characteristics of the professoriate have never been representative of the general population. Here we systematically investigate the indicators of faculty childhood socioeconomic status and consider how they may limit efforts to diversify the professoriate. Combining national-level data on education, income and university rankings with a 2017–2020 survey of 7,204 US-based tenure-track faculty across eight disciplines in STEM, social science and the humanities, we show that faculty are up to 25 times more likely to have a parent with a Ph.D. Moreover, this rate nearly doubles at prestigious universities and is stable across the past 50 years. Our results suggest that the professoriate is, and has remained, accessible disproportionately to the socioeconomically privileged, which is likely to deeply shape their scholarship and their reproduction.
Assessment of blood perfusion quality in laparoscopic colorectal surgery by means of Machine Learning
Authors: Arpaia Pasquale , Bracale Umberto , Corcione Francesco , De Benedetto Egidio , Di Bernardo Alessandro , Di Capua Vincenzo , Duraccio Luigi , Peltrini Roberto , Prevete Roberto 
Published: August 2022

AbstractAn innovative algorithm to automatically assess blood perfusion quality of the intestinal sector in laparoscopic colorectal surgery is proposed. Traditionally, the uniformity of the brightness in indocyanine green-based fluorescence consists only in a qualitative, empirical evaluation, which heavily relies on the surgeon’s subjective assessment. As such, this leads to assessments that are strongly experience-dependent. To overcome this limitation, the proposed algorithm assesses the level and uniformity of indocyanine green used during laparoscopic surgery. The algorithm adopts a Feed Forward Neural Network receiving as input a feature vector based on the histogram of the green band of the input image. It is used to (i) acquire information related to perfusion during laparoscopic colorectal surgery, and (ii) support the surgeon in assessing objectively the outcome of the procedure. In particular, the algorithm provides an output that classifies the perfusion as adequate or inadequate. The algorithm was validated on videos captured during surgical procedures carried out at the University Hospital Federico II in Naples, Italy. The obtained results show a classification accuracy equal to $$99.9\%$$

99.9
%

, with a repeatability of $$1.9\%$$

1.9
%

. Finally, the real-time operation of the proposed algorithm was tested by analyzing the video streaming captured directly from an endoscope available in the OR.
Genomic epidemiology and emergence of SARS-CoV-2 variants of concern in the United Arab Emirates
Authors: Alsafar Habiba , Albreiki Mohammed , Mousa Mira , Azman Syafiq Kamarul , Vurivi Hema , Waasia Fathimathuz , Ruta Dymitr , Alhosani Farida , Almazrouei Shereena , Abuyadek Rowan , Selvaraj Francis , Chaves-Coira Irene , Zvereff Val , Abdel-Malek Mohamed A. Y. , Alkaabi Nawal , Uddin Maimunah , Al Awadhi Tayba , Al Marzouqi Nada , Al Attar Fatma , Al Shamsi Safeiya , Al Shehhi Fatima , Alteneiji Hala , Mohamed Kalthoom , Al Muhairi Noor , AlRand Hussain , Fikri Asma , Henschel Andreas 
Published: August 2022

AbstractSince the declaration of SARS-CoV-2 outbreak as a pandemic, the United Arab Emirates (UAE) public health authorities have adopted strict measures to reduce transmission as early as March 2020. As a result of these measures, flight suspension, nationwide RT-PCR and surveillance of viral sequences were extensively implemented. This study aims to characterize the epidemiology, transmission pattern, and emergence of variants of concerns (VOCs) and variants of interests (VOIs) of SARS-CoV-2 in the UAE, followed by the investigation of mutations associated with hospitalized cases. A total of 1274 samples were collected and sequenced from all seven emirates between the period of 25 April 2020 to 15 February 2021. Phylogenetic analysis demonstrated multiple introductions of SARS-CoV-2 into the UAE in the early pandemic, followed by a local spread of root clades (A, B, B.1 and B.1.1). As the international flight resumed, the frequencies of VOCs surged indicating the January peak of positive cases. We observed that the hospitalized cases were significantly associated with the presence of B.1.1.7 (p < 0.001), B.1.351 (p < 0.001) and A.23.1 (p = 0.009). Deceased cases are more likely to occur in the presence of B.1.351 (p < 0.001) and A.23.1 (p = 0.022). Logistic and ridge regression showed that 51 mutations are significantly associated with hospitalized cases with the highest proportion originated from S and ORF1a genes (31% and 29% respectively). Our study provides an epidemiological insight of the emergence of VOCs and VOIs following the borders reopening and worldwide travels. It provides reassurance that hospitalization is markedly more associated with the presence of VOCs. This study can contribute to understand the global transmission of SARS-CoV-2 variants.
Efficient enumeration-selection computational strategy for adaptive chemistry
Authors: Guo Yachong , Werner Marco , Baulin Vladimir A. 
Published: August 2022

AbstractDesign problems of finding efficient patterns, adaptation of complex molecules to external environments, affinity of molecules to specific targets, dynamic adaptive behavior of chemical systems, reconstruction of 3D structures from diffraction data are examples of difficult to solve optimal design or inverse search problems. Nature inspires evolution strategies to solve design problems that are based on selection of successful adaptations and heritable traits over generations. To exploit this strategy in the creation of new materials, a concept of adaptive chemistry was proposed to provide a route for synthesis of self-adapting molecules that can fit to their environment. We propose a computational method of an efficient exhaustive search exploiting massive parallelization on modern GPUs, which finds a solution for an inverse problem by solving repetitively a direct problem in the mean field approximation. One example is the search for a composition of a copolymer that allows the polymer to translocate through a lipid membrane at a minimal time. Another example is a search of a copolymer sequence that maximizes the polymer load in the micelle defined by the radial core-shell potentials. The length and the composition of the sequence are adjusted to fit into the restricted environment. Hydrogen bonding is another pathway of adaptation to the environment through reversible links. A linear polymer that interacts with water through hydrogen bonds adjusts the position of hydrogen bonds along the chain as a function of the concentration field around monomers. In the last example, branching of the molecules is adjusted to external fields, providing molecules with annealed topology, that can be flexibly changed by changing external conditions. The method can be generalized and applied to a broad spectrum of design problems in chemistry and physics, where adaptive behavior in multi-parameter space in response to environmental conditions lead to non-trivial patterns or molecule architectures and compositions. It can further be combined with machine learning or other optimization techniques to explore more efficiently the parameter space.
The increased analgesic efficacy of cold therapy after an unsuccessful analgesic experience is associated with inferior parietal lobule activation
Authors: Choi Jae Chan , Park Hae-Jeong , Park Jeong A. , Kang Dae Ryong , Choi Young-Seok , Choi SoHyun , Lee Hong Gyu , Choi Jun-Ho , Choi In-Ho , Yoon Min Woo , Lee Jong-Min , Kim Jinhee 
Published: August 2022

AbstractPrior experiences of successful and failed treatments are known to influence the efficacy of a newly applied treatment. However, whether that carry-over effect applies to non-pharmacological treatments is unknown. This study investigated how a failed treatment history with placebo analgesic cream affected the therapeutic outcomes of cold-pack treatment. The neural correlates underlying those effects were also explored using functional magnetic resonance imaging. The effect of the placebo analgesic cream was induced using placebo conditioning with small (44.5 °C to 43.7 °C, negative experience) and large (44.5 °C to 40.0 °C, positive experience) thermal stimuli changes. After the placebo conditioning, brain responses and self-reported evaluations of the effect of subsequent treatment with a cold-pack were contrasted between the two groups. The negative experience group reported less pain and lower anxiety scores in the cold-pack condition than the positive experience group and exhibited significantly greater activation in the right inferior parietal lobule (IPL), which is known to be involved in pain relief. These findings suggest that an unsatisfying experience with an initial pain-relief treatment could increase the expectations for the complementary treatment outcome and improve the analgesic effect of the subsequent treatment. The IPL could be associated with this expectation-induced pain relief process.
Comprehensive characterization of flavonoid derivatives in young leaves of core-collected soybean (Glycine max L.) cultivars based on high-resolution mass spectrometry
Authors: Lee Suji , Kim Heon-Woong , Lee So-Jeong , Kwon Ryeong Ha , Na Hyemin , Kim Ju Hyung , Choi Yu-Mi , Yoon Hyemyeong , Kim Yong-Suk , Wee Chi-Do , Yoo Seon Mi , Lee Sang Hoon 
Published: August 2022

AbstractMost previous studies have been focused on isoflavone profile with biological activities from soybean seed and its related products. However, in the present study, eighty-three flavonoid derivatives (55 flavonols, 9 flavones and 19 isoflavones) were comprehensively identified and quantified from young leaves of 21 core-collected soybean cultivars based on ultra-performance liquid chromatography-diode array detector with quadrupole time of flight/mass spectrometry (UPLC-DAD-QToF/MS). Among total flavonoids from soybean leaves (SLs), the abundant flavonols (83.6%) were primarily composed of di- and tri- glycosides combined to the aglycones (K, kaempferol; Q, quercetin; I, isorhamnetin). Particularly, K-rich SLs (yellow coated seed), Nongrim 51 (breeding line) and YJ208-1 (landrace) contained mainly kaempferol 3-O-(2″-O-glucosyl-6″-O-rhamnosyl)galactoside and 3-O-(2″,6″-di-O-rhamnosyl)galactoside, and were expected to be superior cultivars by their higher flavonoids. Besides, the new tri-I-glycosides (soyanins I–V) were presented as predominant components in Junyeorikong (landrace, black). Thus, this study suggest that the SLs can be considered as valuable edible resources due to their rich flavonoids. Also, these detailed profiles will support breeding of superior varieties with excellent biological activities as well as relationship with seed anthocyanins production, and contribute to perform metabolomics approach to investigate the changes of SLs flavonols during the leaf growth and fermentation in further research.
Distribution of SOCD along different offshore distances in China's fresh-water lake-Chaohu under different habitats
Authors: Yao Xiaojie , Wang Jingjing , Xie Xinyun , Jiang Dan , Xu Xiaoniu 
Published: August 2022

AbstractCarbon storage in wetland ecosystems is an important part of the carbon cycle of terrestrial ecosystems and provides important ecosystem services. Chaohu Wetland is a typical freshwater lake wetland in China. In this study, soil and plant samples were collected every 500 m through three sample lines of different vegetation habitats (estuarine banks, woodlands and shrub beaches) and different offshore distances, revealing the spatial distribution characteristics of soil organic carbon density (SOCD) in Chaohu wetland. The overall SOCD of Chaohu wetland was low, with different habitats ranking as Woodland > Estuary and riverside > Shrub and beach. SOCD of different offshore distances had no obvious law, and the SOCD decreased significantly with soil depth. The plant biomass was significantly higher at the woodland habitat than at other habitats. Most of soil nutrient indicators were the highest at the woodland habitat, while the estuary-riverside habitat had the highest N and P contents. Soil and plant nutrients at different offshore distances had no obvious change patterns. The contents of soil K, Ca, Mg, and N were significantly positively correlated with SOCD, but soil bulk density and pH were significantly negatively correlated with SOCD, and vegetation P content was significantly negatively correlated with SOCD. The spatial pattern of SOCD changes in this lake coastal wetland was determined by the combined effects of plant nutrients, biomass, and soil physical and chemical properties. Our results indicate Chaohu wetlands may have been experiencing serious degradation. The SOCD of Chaohu wetland is lower than that of other wetlands in China, which is mainly affected by human activities. Different offshore distances and habitat heterogeneity are the main factors affecting the soil carbon cycle of the wetland.