bluuebunny/crossref_metadata_2025 huggingface dataset:
CO2 electro-reduction reaction via a two-dimensional TM@TAP single-atom catalyst
Authors: Wang Xiaolin , Zhang Qing , Zhang Shenghai , Wen Mengyu , Jin Shaowei
Published: December 2023

The possibility of the TM@TAP (TM from Sc to Zn, and Y to Cd) monolayer as a catalyst for carbon dioxide reduction reaction (CO2RR) is investigated using first-principles calculations.
Isatin-based benzyloxybenzene derivatives as monoamine oxidase inhibitors with neuroprotective effect targeting neurogenerative disease treatment
Authors: Benny Feba , Oh Jong Min , Kumar Sunil , Abdelgawad Mohamed A. , Ghoneim Mohammed M. , Abdel-Bakky Mohamed Sadek , Kukerti Neelima , Jose Jobin , Kim Hoon , Mathew Bijo
Published: December 2023

Eighteen isatin-based benzyloxybenzaldehyde derivatives from three subseries, ISB, ISFB, and ISBB, were synthesized and their ability to inhibit monoamine oxidase (MAO) was evaluated.
In situ synthesis of g-C3N4/Ti3C2Tx nano-heterostructures for enhanced photocatalytic H2 generation via water splitting
Authors: Tambe Amol B. , Arbuj Sudhir S. , Umarji Govind G. , Kulkarni Sulbha K. , Kale Bharat B.
Published: December 2023

Schematic representation of the photocatalytic water splitting mechanisms of g-C3N4/Ti3C2Tx.
Correction: Functionalized cellulose nanofibrils in carbonate-substituted hydroxyapatite nanorod-based scaffold from long-spined sea urchin (Diadema setosum) shells reinforced with polyvinyl alcohol for alveolar bone tissue engineering
Authors: Jamilludin Muhammad Amir , Dinatha I Kadek Hariscandra , Supii Apri I , Partini Juliasih , Kusindarta Dwi Liliek , Yusuf Yusril
Published: December 2023

Correction for ‘Functionalized cellulose nanofibrils in carbonate-substituted hydroxyapatite nanorod-based scaffold from long-spined sea urchin (Diadema setosum) shells reinforced with polyvinyl alcohol for alveolar bone tissue engineering’ by Muhammad Amir Jamilludin et al., RSC Adv., 2023, 13, 32444–32456, https://doi.org/10.1039/D3RA06165E.
Computationally guided bioengineering of the active site, substrate access pathway, and water channels of thermostable cytochrome P450, CYP175A1, for catalyzing the alkane hydroxylation reaction
Authors: Taher Mohd , Dubey Kshatresh Dutta , Mazumdar Shyamalava
Published: December 2023

Rational design and engineering of the active pocket for access and binding of the substrate, and water channel in a thermostable cytochrome P450 enabled efficient catalysis of a longer chain alkane.
A single phosphorylation mechanism in early metabolism – the case of phosphoenolpyruvate
Authors: Zimmermann Joris , Mayer Robert J. , Moran Joseph
Published: December 2023

A nonenzymatic reaction converting pyruvate to phosphoenolpyruvate (PEP) is shown to proceed through carboxylate phosphorylation, suggesting that only a single phosphorylation mechanism was needed to initiate metabolic networks.
Origin of dielectric polarization suppression in confined water from first principles
Authors: Dufils T. , Schran C. , Chen J. , Geim A. K. , Fumagalli L. , Michaelides A.
Published: December 2023

Atomistic simulations explain recent experimental findings of dielectric polarization suppression in confined water, revealing it originates in an anti-ferroelectric order driven by spontaneous antiparallel alignment of water dipoles at surfaces.
f-Element heavy pnictogen chemistry
Authors: Du Jingzhen , Cobb Philip J. , Ding Junru , Mills David P. , Liddle Stephen T.
Published: December 2023

In this review, the molecular chemistry of the f-elements with heavy pnictogen ligands from phosphorus to bismuth is described.
Valorisation of residual biomass by pyrolysis: influence of process conditions on products
Authors: Vilas-Boas A. C. M. , Tarelho L. A. C. , Oliveira H. S. M. , Silva F. G. C. S. , Pio D. T. , Matos M. A. A.
Published: December 2023

In the context of sustainable residual biomass management, this work explores the pyrolysis process of residual biomass using a bench-scale fixed bed reactor.
Classification of chemically modified red blood cells in microflow using machine learning video analysis
Authors: Baskaran R. K. Rajaram , Link A. , Porr B. , Franke T.
Published: December 2023

We classify native and chemically modified RBCs with an AI based video classifier at high accuracy (>90%). We use chemicals to mimic aspects of typical RBC disorders. This enables a label-free categorization, based on cell shape and flow dynamics.
Highly reproducible self-assembled monolayer based perovskite solar cells via amphiphilic polyelectrolyte
Authors: Liu Shi-Chun , Lin Heng-Yi , Hsu Shih-En , Wu Dong-Tai , Sathasivam Sanjayan , Daboczi Matyas , Hsieh Hsing-Jung , Zeng Chin-Sian , Hsu Ting-Ge , Eslava Salvador , Macdonald Thomas J. , Lin Chieh-Ting
Published: December 2023

The application of a PFN-Br layer in SAM-based Perovskite Solar Cells (PSCs) effectively reduces nanometer-scale voids at the buried interface, significantly enhancing device reproducibility and efficiency.
Lanthanide contraction effect on the alkaline hydrogen evolution and oxidation reactions activity in platinum–rare earth nanoalloys
Authors: Campos-Roldán Carlos A. , Chattot Raphaël , Pailloux Frédéric , Zitolo Andrea , Rozière Jacques , Jones Deborah J. , Cavaliere Sara
Published: December 2023

The lanthanide contraction effect on the alkaline hydrogen electrochemistry.
Local descriptors-based machine learning model refined by cluster analysis for accurately predicting adsorption energies on bimetallic alloys
Authors: Usuga A. F. , Praveen C. S. , Comas-Vives A.
Published: December 2023

The CatBoost method, combined with cluster filtering, accurately predicts adsorption energies on metal alloys. The approach uses local chemical descriptors to understand chemisorption on metal alloys, which is essential for catalytic applications.
Advancements in cathode materials for potassium-ion batteries: current landscape, obstacles, and prospects
Authors: Masese Titus , Kanyolo Godwill Mbiti
Published: December 2023

This perspective highlights progress in the development of cathode materials for potassium-ion batteries, whilst providing valuable insights into unexplored compositional spaces that can be pursued for high-performance electrode materials.
Peer-Mediated Intervention for Socially Isolated Preschoolers: An Early-Stage Feasibility Study
Authors: Foster Tiffany J. , Xiao Nan , Pelfrey G. Logan , Villasanti Hugo Gonzalez , Brock Matthew , Justice Laura
Published: December 2023

Purpose:

A common goal of peer-mediated interventions is to train peers to successfully initiate and maintain social and linguistic interactions with a target child in the classroom. Ample evidence indicates that peer-mediated interventions improve social and linguistic outcomes for students in the primary and later grades with developmental disabilities; however, relatively little work has focused on applying these approaches to socially isolated preschoolers who are vulnerable to academic and social challenges. In this early-stage feasibility study, we examined the potential of Promoting Early Engagement, Relationships, and Socialization (PEERS), a peer-mediated intervention designed to support socially isolated preschoolers. The main goal was to consider whether the intervention showed promise for improving the social and linguistic experiences of young, isolated children and was appropriate for implementation in a preschool setting.

Method:

In one preschool classroom, two peers who were well connected to their classmates were trained via storybook-based activities to provide social support to an isolated classmate. In-person and sensing technology observations were used to examine the target student's incoming peer interactions, outgoing peer interactions, and physical proximity to peers.

Results:

In-person observations showed a trend toward increased interactions; sensing technology data, which provided longer snapshots of classroom experiences, were more variable. In addition, teachers perceived PEERS to be appropriate and effective.

Conclusion:

The findings of this study support further investigation of storybook-based peer-mediated interventions in preschool settings to improve the social and linguistic experiences of children who are socially isolated.
A dynamic alignment and illumination‐aware convolution for shadow removal
Authors: Wang Xingqi , Dai Jialai , Chen Bin , Wei Dan , Shao Yanli
Published: December 2023

Shadow removal is a challenging task because the variety of shadows is influenced by surface texture and lighting. This paper proposes a dynamic alignment and illumination‐aware convolution (DAIC), which consists of a Feature Alignment Module (FAM) and a Dynamic Weight Module (DWM). FAM aligns the downsampled deep features with the original features and helps to extract the optimal local information to ensure that the object texture features are not corrupted. DWM generates weights according to different lighting variations for a better shadow removal result. The shadow removal approach is based on an image decomposition algorithm using a multi‐exposure image fusion model. Here, the shadow removal network and refinement network use U‐Net framework, and the transposed convolution operations are replaced with DAIC in the decoder part of U‐Net to improve the performance of the network. The experiments are conducted on two large shadow removal datasets, ISTD+ and SRD. Compared to state‐of‐the‐art methods, this model achieves optimal performance in terms of Root Mean Square Error (RMSE) for the non‐shadow region. It also achieves performance comparable to the state‐of‐the‐art method in terms of RMSE for the shadow region and structural similarity index measurement for the entire image.
Intelligent design of network multimedia using big data and virtual Artificial Intelligence technology
Authors: Zhang Xin
Published: December 2023

In recent years, with the rapid development of the Internet of Things and communication technology, the application of network multimedia has become increasingly popular. At present, network multimedia has become a new type of mass media. Due to its interchangeability and extensive dissemination, it creates favourable conditions for information dissemination and acceptance in terms of vision, hearing, touch etc. However, at the same time, there are also some problems. The network multimedia does not have enough original information and the information retrieval is not intelligent, so this has caused great trouble to users. In order to solve these problems, the authors attempted to use the combination of Big Data (BD) and virtual Artificial Intelligence (AI) technology to realise the intelligent design of network multimedia. Therefore, based on the theoretical analysis, the authors also verified the effect of BD and virtual AI technology on the intelligent design of network multimedia. It was found that the intelligent design method proposed by the authors had good application effect in network multimedia, and could effectively improve the information retrieval speed of network multimedia. The query time of this method was 1.87 s less than that of the traditional method when the amount of information was 1000 and 18.16 s less than that of the traditional method when the amount of information was 40,000. At the same time, this method could also improve the accuracy of network multimedia information recommendation, and make network multimedia have better sharing, so as to provide more services for users. In addition, the discussion of BD and virtual AI technology in network multimedia intelligent design could also broaden the application scope of the Internet of Things and promote its better development.
Joint transceive beamforming for multistatic radar system by semi‐definite relaxation method
Authors: Li Haoran , Geng Jun , Xie Junhao
Published: December 2023

The joint transmit and receive beamforming algorithm has been envisioned to optimise the target's signal‐to‐interference‐plus‐noise ratio by co‐designing the transmit and receive beamforming vectors simultaneously. However, the traditional design concepts for this algorithm only consider the monostatic radar system, which may not work as well for the multistatic radar system. The authors present a novel transmit and receive beamforming algorithm for the multistatic radar system that includes a common transmitter and multiple receivers. The transmit beamforming vector can directly influence the output signal‐to‐interference‐plus‐noise ratio of each radar subsystem. To ensure the balanced performance of the subsystems, the authors propose a weighted sum of the signal‐to‐interference‐plus‐noise ratio optimisation problem to co‐design the transmit and receive beamforming. The proposed problem is non‐convex, and the authors construct an iterative algorithm to solve it using semi‐definite relaxation and slack‐variable replacement techniques. By using pre‐determined weights, the output performance of each radar subsystem can be effectively regulated. The simulation results confirm that the proposed algorithm can ensure better output signal‐to‐interference‐plus‐noise ratio for the entire multistatic radar system than the conventional joint transmit and receive beamforming algorithm.
Multi-objective optimization of the high electron mobility transistor
Authors: Amar Abdelhamid , El Maani Rabii , Radi Bouchaïb , El Hami Abdelkhalak
Published: December 2023

In this paper, we present a new approach to improve the thermo-mechanical performance of the HEMT (high electron mobility transistor) technology. This study aims to solve two optimization problems. The first one is the optimization of the thermal behavior of the HEMT, through the optimization of its maximum operating temperature which influences the electrical characteristics such as electron mobility, and also influences the mechanical behavior of its structure. While the second problem will be the optimization of the mechanical behavior of the same technology, through the optimization of the stresses distribution that also influence the electrical characteristics and reliability of the HEMT structure. The resolution of these two optimization problems will be done, by the multi-objective optimization approach thanks to numerical tools such as Comsol multiphysics and Matlab software, which allows to solve these two problems simultaneously by taking into consideration the imposed constraints. The results obtained have optimized the thermo-mechanical behavior of the HEMT, which proves the efficiency of this approach to solve complex optimization problems.
Lebensstilempfehlungen bei Typ-2-Diabetes – Herausforderungen
und Umsetzung
Authors: Kohl Jan , Hohberg Vivien
Published: December 2023

Die Bewegungs- und Ernährungsempfehlungen bei Typ-2-Diabetes wurden in
den vergangenen Jahren detaillierter und ließen gleichzeitig mehr
Spielraum für individuelle Bedürfnisse. Die praktische Umsetzung
der Empfehlungen stellt jedoch nach wie vor eine Herausforderung dar.
Personalisierte Empfehlungen und Verhaltensänderungsstrategien bieten
zukünftig Chancen, den Lebensstil von Menschen mit Typ-2-Diabetes
nachhaltig positiv zu beeinflussen.
Study on the influence of electrode materials on energy storage power station in lithium battery
Authors: Zhang Ruopeng , Xue Shouhong , Wang Huanwei , Yang Yaoguo , Wu Lixia
Published: December 2023

Lithium batteries are promising techniques for renewable energy storage attributing to their excellent cycle performance, relatively low cost, and guaranteed safety performance. The performance of the LiFePO4 (LFP) battery directly determines the stability and safety of energy storage power station operation, and the properties of the internal electrode materials are the core and key to determine the quality of the battery. In this work, two kinds of commercial LFP batteries were studied by analyzing the electrical properties and material properties of the electrodes. After performing the rate and cycle performance tests of the battery cell, differential scanning calorimetry, scanning electron microscope, x-ray diffraction, and inductively coupled plasma were used to explore the performance of electrode materials to establish the correlation between the battery performance and the electrochemical reaction law of the internal materials and further to judge the influence of the key material properties on the battery performance. This work opens up an avenue for technical supervision of energy storage power stations.
On the synergy of biomicrofluidic technologies and real-time 3D tracking: A perspective
Authors: Hong Liu , Chamorro Leonardo P.
Published: December 2023

Particle image velocimetry and particle tracking velocimetry have played pivotal roles in flow and particle characterization, owing to their non-invasive and accurate data collection methods. However, their broader application in the biomicrofluidics field is constrained by challenges, such as intensive calibration, high post-processing costs, and optical compatibility issues, especially in settings where space is a bottleneck. This article describes recent advancements in non-iterative ray tracing that promise more streamlined post-capture calibration and highlights examples of applications and areas that merit further technological investigation. The development and adoption of these techniques may pave the way for new innovations.
Numerical simulation of dry laser derusting process based on SPH method
Authors: Liu Xiaoqiang , Du Weigang
Published: December 2023

Laser cleaning is an efficient, environmental-friendly, and non-contact surface treatment technology. Laser radiation and heating cause the surface material to heat up and gasify, separating it from the substrate. Traditional mesh-based numerical methods are difficult to effectively simulate the evolution of erosion crater and the splashing phenomenon. In this study, a meshfree method, the smoothed particle hydrodynamics (SPH) method, is used to establish the numerical model of the interaction between the laser beam and the targeted material and to investigate the removal process of the rust layer under different laser operating conditions. In consideration of the coupling effect of laser absorption, heat transfer, and material phase change, the SPH modeling procedure and corresponding numerical scheme for heat transfer and heat-absorption-induced phase change are introduced. Additionally, a surface particle detection algorithm and surface normal vector calculation method are proposed to accurately compute the complex surface geometry of the erosion crater, which realizes the dynamic coupling of laser-energy absorption and laser-beam direction. The established SPH model is then used to simulate the temperature distribution of the rust layer under the action of a laser beam, and the influence of laser energy, beam overlap rate, and beam direction on the removal efficiency is analyzed. This study applies the meshfree SPH method to the study of laser rust removal process, verifies the accuracy of the surface detection algorithm, captures the spatter behavior of material particles after phase change, and reflects the advantages of the meshfree method in solving such problems.
Assessing the impact of triaxial strain on carrier mobility and dielectric properties in cubic CsBCl3 (B = Pb, Sn, or Ge) perovskites: A first principles study
Authors: Yadav Kiran , Ray Nirat
Published: December 2023

Investigating the strain and pressure dependence of perovskite materials can provide valuable insights into their structural and electronic responses, enabling the fine-tuning of their properties for various technological applications. This study investigates the influence of controlled lattice compression and expansion on the acoustic phonon-limited carrier mobility in CsBCl3 (B = Pb, Sn, Ge) perovskites, revealing tunable electronic bandgaps ranging from 0.3 to 1.2 eV by varying the B cation type and applied triaxial strain. The research demonstrates significant and monotonic carrier mobility modulation under pressure, with changes of up to 124% even at modest strain levels of −2%, along with linearly increasing exciton binding energy with lattice parameter expansion.
STI-X: a novel approach to STI testing in rural and regional Victoria, Australia
Authors: Evans David , Cowen Kim , Fairley Christopher , Randall Claire , Hocking Jane , Ludwick Teralynn , Tomnay Jane
Published: December 2023

Accessing testing for sexually transmissible infections (STI) in regional and rural areas can be challenging for many people. Innovative solutions are necessary to ensure that barriers are minimised for populations who are often disadvantaged by the health system. STI-X, our STI test vending machine brings testing to local communities in areas where accessing a clinical service can be difficult due to extended wait times or where there is concern about privacy. Providing the option of a free, quick and easy STI test aims to reduce the prevalence of STIs and the burden on the primary care system.
Rex1BD and the 14-3-3 protein control heterochromatin organization at tandem repeats by linking RNAi and HDAC
Authors: Gao Jinxin , Sun Wenqi , Li Jie , Ban Hyoju , Zhang Tuokai , Liao Junwei , Kim Namho , Lee Soon Hoo , Dong Qianhua , Madramootoo Robert , Chen Yong , Li Fei
Published: December 2023

Tandem DNA repeats are often organized into heterochromatin that is crucial for genome organization and stability. Recent studies revealed that individual repeats within tandem DNA repeats can behave very differently. How DNA repeats are assembled into distinct heterochromatin structures remains poorly understood. Here, we developed a genome-wide genetic screen using a reporter gene at different units in a repeat array. This screen led to identification of a conserved protein Rex1BD required for heterochromatin silencing. Our structural analysis revealed that Rex1BD forms a four-helix bundle structure with a distinct charged electrostatic surface. Mechanistically, Rex1BD facilitates the recruitment of Clr6 histone deacetylase (HDAC) by interacting with histones. Interestingly, Rex1BD also interacts with the 14-3-3 protein Rad25, which is responsible for recruiting the RITS (RNA-induced transcriptional silencing) complex to DNA repeats. Our results suggest that coordinated action of Rex1BD and Rad25 mediates formation of distinct heterochromatin structure at DNA repeats via linking RNAi and HDAC pathways.
In vivo three-dimensional brain imaging with chemiluminescence probes in Alzheimer’s disease models
Authors: Zhang Jing , Wickizer Carly , Ding Weihua , Van Richard , Yang Liuyue , Zhu Biyue , Yang Jun , Wang Yanli , Wang Yongle , Xu Yulong , Zhang Can , Shen Shiqian , Wang Changning , Shao Yihan , Ran Chongzhao
Published: December 2023

Optical three-dimensional (3D) molecular imaging is highly desirable for providing precise distribution of the target-of-interest in disease models. However, such 3D imaging is still far from wide applications in biomedical research; 3D brain optical molecular imaging, in particular, has rarely been reported. In this report, we designed chemiluminescence probes with high quantum yields, relatively long emission wavelengths, and high signal-to-noise ratios to fulfill the requirements for 3D brain imaging in vivo. With assistance from density-function theory (DFT) computation, we designed ADLumin-Xs by locking up the rotation of the double bond via fusing the furan ring to the phenyl ring. Our results showed that ADLumin-5 had a high quantum yield of chemiluminescence and could bind to amyloid beta (Aβ). Remarkably, ADLumin-5’s radiance intensity in brain areas could reach 4 × 10
7
photon/s/cm
2
/sr, which is probably 100-fold higher than most chemiluminescence probes for in vivo imaging. Because of its strong emission, we demonstrated that ADLumin-5 could be used for in vivo 3D brain imaging in transgenic mouse models of Alzheimer’s disease.
Potassium jarosite seeding of soils decreases lead and arsenic bioaccessibility: A path toward concomitant remediation
Authors: Sowers Tyler D. , Blackmon Matthew D. , Betts Aaron R. , Jerden Marissa L. , Scheckel Kirk G. , Bradham Karen D.
Published: December 2023

Soils are common sources of metal(loid) contaminant exposure globally. Lead (Pb) and arsenic (As) are of paramount concern due to detrimental neurological and carcinogenic health effects, respectively. Pb and/or As contaminated soils require remediation, typically leading to excavation, a costly and environmentally damaging practice of removing soil to a central location (e.g., hazardous landfill) that may not be a viable option in low-income countries. Chemical remediation techniques may allow for in situ conversion of soil contaminants to phases that are not easily mobilized upon ingestion; however, effective chemical remediation options are limited. Here, we have successfully tested a soil remediation technology using potted soils that relies on converting soil Pb and As into jarosite-group minerals, such as plumbojarosite (PLJ) and beudantite, possessing exceptionally low bioaccessibility [i.e., solubility at gastric pH conditions (pH 1.5 to 3)]. Across all experiments conducted, all new treatment methods successfully promoted PLJ and/or beudantite conversion, resulting in a proportional decrease in Pb and As bioaccessibility. Increasing temperature resulted in increased conversion to jarosite-group minerals, but addition of potassium (K) jarosite was most critical to Pb and As bioaccessibility decreases. Our methods of K-jarosite treatment yielded <10% Pb and As bioaccessibility compared to unamended soil values of approximately 70% and 60%, respectively. The proposed treatment is a rare dual remediation option that effectively treats soil Pb and As such that potential exposure is considerably reduced. Research presented here lays the foundation for ongoing field application.
Detection of intact amino acids with a hypervelocity ice grain impact mass spectrometer
Authors: Burke Sally E. , Auvil Zachary A. , Hanold Karl A. , Continetti Robert E.
Published: December 2023

Astrobiology studies are a top priority in answering one of the most fundamental questions in planetary science: Is there life beyond Earth? Saturn’s icy moon Enceladus is a prime target in the search for life in our solar system, identified by NASA as the second-highest priority site for a flagship mission in the next decade. The orbital sampling technique of impact ionization mass spectrometry indicated the presence of complex organics in the small icy plume particles ejected by Enceladus encountered previously by Cassini. However, high interaction velocities caused ambiguity as to the origin and identity of the organics. Laboratory validation of this technique is needed to show that biosignature molecules can survive an impact at hypervelocity speeds for detection. Here, we present results on the hypervelocity impact of organic-laden submicron ice grains for in situ mass spectrometric characterization with the first technique to accurately replicate this plume sampling scenario: the Hypervelocity Ice Grain Impact Mass Spectrometer. Our results show good agreement with Cassini data at comparable compositions. We show that amino acids entrained in ice grains can be detected intact after impact at speeds up to 4.2 km/s and that salt reduces their detectability, validating the predictions from other model systems. Our results provide a benchmark for this orbital sampling method to successfully detect signs of life and for the interpretation of past and future data. This work has implications not only for a potential Enceladus mission but also for the forthcoming Europa Clipper mission.
Setting research priorities for English as an Additional Language
Authors: Chalmers Hamish , Faitaki Faidra , Murphy Victoria A.
Published: December 2023

We report a priority setting partnership (PSP), which sought to establish the priorities for new research among research users (educators, parents, and learners) in the field of English as an Additional Language (EAL). A steering committee consisting of members of these research user groups was established to oversee the project. An online ‘uncertainty questionnaire’ was distributed to research users inviting them to identify areas of their practice about which they are uncertain. These ‘raw’ uncertainties were consolidated and converted into a list of research questions, which was then distributed to the same groups to rank in order of priority. The 25 highest ranked questions were then discussed and debated in a workshop, consisting of research user representatives, to collectively and democratically produce a final Top 10 list of questions. The Top 10 shows what EAL research users regard as priorities, which we hope will inform research agendas and funding decisions.
Temperature gradient and asymmetric steady state correlations in dissipatively coupled cascaded optomechanical systems
Authors: Pellitteri Claudio , Palma G Massimo , Lorenzo Salvatore
Published: December 2023

The interaction between a light mode and a mechanical oscillator via radiation pressure in optomechanical systems is an excellent platform for a multitude of applications in quantum technologies. In this work we study the dynamics of a pair of optomechanical systems interacting dissipatively with a wave guide in a unidirectional way. Focusing on the regime where the cavity modes can be adiabatically eliminated, we derive an effective coupling between the two mechanical modes and explore the classical and quantum correlations established between the modes in both the transient and the stationary regime, highlighting their asymmmetrical nature due to the unidirectional coupling. Noteworthy, we find that a constant amount of steady correlations can exist at long times. Furthermore we show that this unidirectional coupling establishes a temperature gradient between the mirrors, depending on the frequencies’ detuning. We additionally analyze the power spectrum of the output guide field and we show how, thanks to the chiral coupling, from such spectrum it is possible to reconstruct the spectra of each single mirror.
Diameter-dependent ultra-high thermoelectric performance of ZnO nanowires
Authors: Nie 聂 Yinan 祎楠 , Tang 唐 Guihua 桂华 , Li 李 Yifei 一斐 , Zhang 张 Min 敏 , Zhao 赵 Xin 欣
Published: December 2023

Zinc oxide (ZnO) shows great potential in electronics, but its large intrinsic thermal conductivity limits its thermoelectric applications. In this work, we explore the significant carrier transport capacity and diameter-dependent thermoelectric characteristics of wurtzite-ZnO 〈0001〉 nanowires based on first-principles and molecular dynamics simulations. Under the synergistic effect of band degeneracy and weak phonon–electron scattering, P-type (ZnO)73 nanowires achieve an ultra-high power factor above 1500 μW⋅cm−1⋅K−2 over a wide temperature range. The lattice thermal conductivity and carrier transport properties of ZnO nanowires exhibit a strong diameter size dependence. When the ZnO nanowire diameter exceeds 12.72 Å, the carrier transport properties increase significantly, while the thermal conductivity shows a slight increase with the diameter size, resulting in a ZT value of up to 6.4 at 700 K for P-type (ZnO)73. For the first time, the size effect is also illustrated by introducing two geometrical configurations of the ZnO nanowires. This work theoretically depicts the size optimization strategy for the thermoelectric conversion of ZnO nanowires.
Quantum control based on three forms of Lyapunov functions
Authors: Yu 俞 Guo-Hui 国慧 , Yang 杨 Hong-Li 洪礼
Published: December 2023

This paper introduces the quantum control of Lyapunov functions based on the state distance, the mean of imaginary quantities and state errors. In this paper, the specific control laws under the three forms are given. Stability is analyzed by the LaSalle invariance principle and the numerical simulation is carried out in a 2D test system. The calculation process for the Lyapunov function is based on a combination of the average of virtual mechanical quantities, the particle swarm algorithm and a simulated annealing algorithm. Finally, a unified form of the control laws under the three forms is given.
Driver–passenger guidance model for Chinese freeway service areas based on path selection and parking delay
Authors: Li Xia , Liang Yaxin , Guo Peilun , Ma Xinwei , Liu Yimei
Published: December 2023

The driver–passenger guidance model proposed in this article is designed for large-scale freeway service areas that integrate various services such as shopping, leisure and catering. The model focuses on analyzing the impact of perceived travel distance and parking delay on path selection and parking space selection to optimize passenger flow efficiency. A perceived travel distance function is used to construct a pedestrian path selection model whose parameters are calibrated by a stated preference survey. An optimal parking space selection model is established based on the analytic hierarchy process-technique for order of preference based on similarity to the ideal solution method and considers parking distance, outdoor walking distance, indoor perceived travel distance after parking, and the impact of pedestrian crossings on parking delays. The model also calculates the vehicle arrival rate with parking time and the critical gap to ensure pedestrian safety. A parking delay calculation model is established based on the acceptable gap theory. The model is verified using the Yihezhuang service area of the Xiongan freeway as an example. The results show that the pedestrian path selection model improves passenger flow balance and reduces the variance in road passenger flow by 12% and per capita travel time by 9%. The proposed parking delay calculation model reduces parking delays by 30 s compared to models that do not consider pedestrian crossings, indicating its smoothness and convenience.
Conformational gap and heat capacity peaks of short lattice polymers
Authors: Tanouye Fernando Takeshi
Published: December 2023

From a simple and exact approach, we investigated the thermodynamic behavior of short HP-polymers (composed of hydrophobic and polar coarse-grained monomers) on the square lattice, for lengths N < 20 residues. In particular, we analyzed the heat capacity excitation peak, showing the strong correlation between its occurrence, at low temperatures, and a sharp conformational gap from ground states to first excited states (

Ω

1

/

Ω

0

≫
1

). This relation is observed for both homopolymers and heteropolymers.
Optimizing deep learning-based piled-up pulse height correction method for high radiation-field application
Authors: Kim W. , Ko K. , Lee S. , Park J. , Song G. , Lim K. , Cho G.
Published: December 2023

In high-radiation environments, measured pile-up pulses can lead to unavoidable issues such as total count loss and spectrum distortion. Additionally, the recording of large volumes of data within a short period makes real-time processing difficult. In this study, a deep learning-based pulse height estimation (PHE) method was optimized to perform pile-up signal correction in high-radiation fields. First, we adopted a previous deep-learning-based PHE method that allows for fast correction without being restricted to specific detectors. However, the peak-finding method was slightly modified to improve the count restoration rate. Moreover, the input data length of the deep learning model was optimized for convolutional neural networks (CNN) and deep neural networks (DNN) to achieve the maximum correction performance using minimal input data. A series of single pulses was experimentally obtained from a LaBr3 detector with a short decay time to prepare a dataset for training the deep learning models. The pile-up signals were generated by randomly synthesizing single pulses. Samples around their peaks were sliced using the peak-finding method and used as input data for the deep learning models. As a result of the optimization, the modified peak-finding method improved the count restoration rate compared to the previous method by effectively detecting the peaks of tail pile-up, and peak pile-up pulses. Furthermore, the input data length and region were optimized based on the performance evaluation of each deep learning model. Despite having a simpler architecture than the CNN model, the DNN model demonstrated excellent PHE performance. The results of this study showed the efficient and practical considerations necessary for applying pile-up signal correction in high-radiation fields.
Reconciling roles of the South China Sea summer monsoon and ENSO in prediction of the Indian Ocean dipole
Authors: Zhang Yazhou , Li Jianping , Diao Yina , Wang Qiuyun , Wu Renguang , Liu Ting , Jin Yishuai , Hou Zhaolu , Wang Haili
Published: December 2023

The Indian Ocean dipole (IOD) is a remarkable interannual variability in the tropical Indian Ocean. The improved prediction of IOD is of a great value because of its large socioeconomic impacts. Previous studies reported that both El Niño-Southern Oscillation (ENSO) and South China Sea summer monsoon (SM) play a dominant role in the western and eastern pole of the IOD, respectively. They can be used as predictors of the IOD at 3 month lead beyond self-persistence. Here, we develop an empirical model of multi-factors in which the western pole is predicted by ENSO and persistence and the eastern pole is predicted by SM and persistence. This new empirical model outperforms largely the average level of the dynamical models from the North American multi-model ensemble (NMME) project in predicting the peak IOD in boreal autumn, with a correlation coefficient of ∼0.86 and a root mean square error of ∼0.24 °C. Furthermore, the hit rate of positive culminated IOD in this new empirical model is equivalent to that in current NMME models (above 65%), much higher than that for negative culminated IOD. This improvement of skill using the empirical model suggests a perspective for better understanding and predicting the IOD.
Another ‘Bleak House’—the decision of the German Federal Supreme Court on the inadmissibility of intra-EU ICSID arbitrations
Authors: Scherpf Georg , Hermes Simon
Published: December 2023

The decision of the German Federal Supreme Court of 27 July 2023 has sparked intense discussions. Unexpectedly, the Court granted a declaration of inadmissibility of intra-EU ICSID proceedings under section 1032(2) of the German Code of Civil Procedure. The decision is of significant practical relevance and yet another push against intra-EU Investor–State Dispute Resolution. After a short introduction (i), we will describe the legal and factual background of the decision (ii) and summarize the Court’s reasoning (iii). Thereafter, we will comment on the decision (iv) and conclude by pointing out possible implications for future intra-EU ICSID proceedings (v).
MESPool: Molecular Edge Shrinkage Pooling for hierarchical molecular representation learning and property prediction
Authors: Xu Fanding , Yang Zhiwei , Wang Lizhuo , Meng Deyu , Long Jiangang
Published: December 2023

Identifying task-relevant structures is important for molecular property prediction. In a graph neural network (GNN), graph pooling can group nodes and hierarchically represent the molecular graph. However, previous pooling methods either drop out node information or lose the connection of the original graph; therefore, it is difficult to identify continuous subtructures. Importantly, they lacked interpretability on molecular graphs. To this end, we proposed a novel Molecular Edge Shrinkage Pooling (MESPool) method, which is based on edges (or chemical bonds). MESPool preserves crucial edges and shrinks others inside the functional groups and is able to search for key structures without breaking the original connection. We compared MESPool with various well-known pooling methods on different benchmarks and showed that MESPool outperforms the previous methods. Furthermore, we explained the rationality of MESPool on some datasets, including a COVID-19 drug dataset.
Integrative approaches based on genomic techniques in the functional studies on enhancers
Authors: Wang Qilin , Zhang Junyou , Liu Zhaoshuo , Duan Yingying , Li Chunyan
Published: December 2023

With the development of sequencing technology and the dramatic drop in sequencing cost, the functions of noncoding genes are being characterized in a wide variety of fields (e.g. biomedicine). Enhancers are noncoding DNA elements with vital transcription regulation functions. Tens of thousands of enhancers have been identified in the human genome; however, the location, function, target genes and regulatory mechanisms of most enhancers have not been elucidated thus far. As high-throughput sequencing techniques have leapt forwards, omics approaches have been extensively employed in enhancer research. Multidimensional genomic data integration enables the full exploration of the data and provides novel perspectives for screening, identification and characterization of the function and regulatory mechanisms of unknown enhancers. However, multidimensional genomic data are still difficult to integrate genome wide due to complex varieties, massive amounts, high rarity, etc. To facilitate the appropriate methods for studying enhancers with high efficacy, we delineate the principles, data processing modes and progress of various omics approaches to study enhancers and summarize the applications of traditional machine learning and deep learning in multi-omics integration in the enhancer field. In addition, the challenges encountered during the integration of multiple omics data are addressed. Overall, this review provides a comprehensive foundation for enhancer analysis.
PICAFlow: a complete R workflow dedicated to flow/mass cytometry data, from pre-processing to deep and comprehensive analysis
Authors: Régnier Paul , Marques Cindy , Saadoun David
Published: December 2023

PICAFlow is a R-written integrative workflow dedicated to flow/mass cytometry data handling, from pre-processing to deep and comprehensive analysis. It is designed as a powerful all-in-one tool which contains all the necessary functions and packages presented in a user-friendly and ease-to-use fashion. PICAFlow also includes important features that are very frequently lacking in other close software, such as interactive R Shiny applications for real-time data transformation and compensation as well as normalization methods aiming to remove batch effects and unwanted inter- and intra-group heterogeneity. It also allows to perform dimensionality reduction, cell clustering (using different available approaches), as well as complementary statistical analyses and export different support for data interpretation and visualization.

Availability

PICAFlow is available as a R-written package hosted at the following GitHub repository: https://github.com/PaulRegnier/PICAFlow and is complemented by a fully detailed tutorial available at the following URL: https://paul-regnier.fr/tutoriel-picaflow/.
Modular brain network in volitional eyes closing: enhanced integration with a marked impact on hubs
Authors: Zhang Yi , Han Xiao , Ge Xuelian , Xu Tianyong , Wang Yanjie , Mu Jiali , Liu Fan
Published: December 2023

Volitional eyes closing would shift brain’s information processing modes from the “exteroceptive” to “interoceptive” state. This transition induced by the eyes closing is underpinned by a large-scale reconfiguration of brain network, which is still not fully comprehended. Here, we investigated the eyes-closing-relevant network reconfiguration by examining the functional integration among intrinsic modules. Our investigation utilized a publicly available dataset with 48 subjects being scanned in both eyes closed and eyes open conditions. It was found that the modular integration was significantly enhanced during the eyes closing, including lower modularity index, higher participation coefficient, less provincial hubs, and more connector hubs. Moreover, the eyes-closing-enhanced integration was particularly noticeable in the hubs of network, mainly located in the default-mode network. Finally, the hub-dominant modular enhancement was positively correlated to the eyes-closing-reduced entropy of BOLD signal, suggesting a close connection to the diminished consciousness of individuals. Collectively, our findings strongly suggested that the enhanced modular integration with substantially reorganized hubs characterized the large-scale cortical underpinning of the volitional eyes closing.
Expanding options of supportive care in IgA nephropathy
Authors: Maixnerova Dita , Hartinger Jan , Tesar Vladimir
Published: December 2023

Immunoglobulin A nephropathy (IgAN) is the most common primary glomerulonephritis worldwide, with a potentially serious prognosis. At present, management of IgAN is primarily based on therapeutic lifestyle changes, and excellent blood pressure control and maximized supportive treatment with the combination of inhibition of the renin–angiotensin–aldosterone system with either inhibitors of angiotensin-converting enzyme or angiotensin II receptor blockers and inhibitors of sodium-glucose cotransporter-2, and possibly in the future also with endothelin antagonists. Supportive care currently represents the cornerstone of treatment of IgAN. Targeted-release formulation of budesonide should replace systemic corticosteroids in patients with higher proteinuria and active histological lesions.

New treatment options are aimed at immunopathogenesis of IgAN including depletion or modulation of Galactose-deficient-Immunoglobulin A1–producing B cells, plasma cells, and the alternate and/or lectin pathway of complement. The exact place of monoclonal antibodies and complement inhibitors will need to be determined.

This article reviews potential supportive therapies currently available for patients with IgAN.
Understanding patient needs and predicting outcomes in IgA nephropathy using data analytics and artificial intelligence: a narrative review
Authors: Schena Francesco Paolo , Manno Carlo , Strippoli Giovanni
Published: December 2023

This narrative review explores two case scenarios related to immunoglobulin A nephropathy (IgAN) and the application of predictive monitoring, big data analysis and artificial intelligence (AI) in improving treatment outcomes. The first scenario discusses how online service providers accurately understand consumer preferences and needs through the use of AI-powered big data analysis. The author, a clinical nephrologist, contemplates the potential application of similar methodologies, including AI, in his medical practice to better understand and meet patient needs. The second scenario presents a case study of a 20-year-old man with IgAN. The patient exhibited recurring symptoms, including gross haematuria and tonsillitis, over a 2-year period. Through histological examination and treatment with renin–angiotensin system blockade and corticosteroids, the patient experienced significant improvement in kidney function and reduced proteinuria over 15 years of follow-up. The case highlights the importance of individualized treatment strategies and the use of predictive tools, such as AI-based predictive models, in assessing treatment response and predicting long-term outcomes in IgAN patients. The article further discusses the collection and analysis of real-world big data, including electronic health records, for studying disease natural history, predicting treatment responses and identifying prognostic biomarkers. Challenges in integrating data from various sources and issues such as missing data and data processing limitations are also addressed. Mathematical models, including logistic regression and Cox regression analysis, are discussed for predicting clinical outcomes and analysing changes in variables over time. Additionally, the application of machine learning algorithms, including AI techniques, in analysing big data and predicting outcomes in IgAN is explored. In conclusion, the article highlights the potential benefits of leveraging AI-powered big data analysis, predictive monitoring and machine learning algorithms to enhance patient care and improve treatment outcomes in IgAN.