bluuebunny/crossref_metadata_2025 huggingface dataset:
Enhancing luciferase activity and stability through generative modeling of natural enzyme sequences
Authors: Xie Wen Jun , Liu Dangliang , Wang Xiaoya , Zhang Aoxuan , Wei Qijia , Nandi Ashim , Dong Suwei , Warshel Arieh
Published: November 2023

The availability of natural protein sequences synergized with generative AI provides new paradigms to engineer enzymes. Although active enzyme variants with numerous mutations have been designed using generative models, their performance often falls short of their wild type counterparts. Additionally, in practical applications, choosing fewer mutations that can rival the efficacy of extensive sequence alterations is usually more advantageous. Pinpointing beneficial single mutations continues to be a formidable task. In this study, using the generative maximum entropy model to analyze
Renilla
luciferase (RLuc) homologs, and in conjunction with biochemistry experiments, we demonstrated that natural evolutionary information could be used to predictively improve enzyme activity and stability by engineering the active center and protein scaffold, respectively. The success rate to improve either luciferase activity or stability of designed single mutants is ~50%. This finding highlights nature's ingenious approach to evolving proficient enzymes, wherein diverse evolutionary pressures are preferentially applied to distinct regions of the enzyme, ultimately culminating in an overall high performance. We also reveal an evolutionary preference in RLuc toward emitting blue light that holds advantages in terms of water penetration compared to other light spectra. Taken together, our approach facilitates navigation through enzyme sequence space and offers effective strategies for computer-aided rational enzyme engineering.
Chemical and spatial dual-confinement engineering for stable Na-S batteries with approximately 100% capacity retention
Authors: Zhang Yong , Guo Xinyi , Yang Qi , Shao Yuan , Du Yadong , Qi Jun , Zhao Ming , Shang Zhengjie , Hao Yuhan , Tang Yongchao , Li Ying , Zhang Riguang , Wang Baojun , Qiu Jieshan
Published: November 2023

Sodium-sulfur (Na-S) batteries are attracting intensive attention due to the merits like high energy and low cost, while the poor stability of sulfur cathode limits the further development. Here, we report a chemical and spatial dual-confinement approach to improve the stability of Na-S batteries. It refers to covalently bond sulfur to carbon at forms of C-S/N-C=S bonds with high strength for locking sulfur. Meanwhile, sulfur is examined to be S
1
-S
2
small species produced by thermally cutting S
8
large molecules followed by sealing in the confined pores of carbon materials. Hence, the sulfur cathode achieves a good stability of maintaining a high-capacity retention of 97.64% after 1000 cycles. Experimental and theoretical results show that Na
+
is hosted via a coordination structure (N···Na···S) without breaking the C-S bond, thus impeding the formation and dissolution of sodium polysulfide to ensure a good cycling stability. This work provides a promising method for addressing the S-triggered stability problem of Na-S batteries and other S-based batteries.
Recognising Yarrie Lingo, the creole language of Yarrabah community in far north-eastern Queensland
Australia
Authors: Yeatman Bernadine , Angelo Denise
Published: November 2023

Yarrie Lingo is the local name for the English-lexified creole language spoken in the Aboriginal community of
Yarrabah in far north-eastern Queensland, Australia. This creole has only recently been gaining recognition but it is the main
language of everyday interactions in Yarrabah. This study describes the recognitional trajectory of Yarrie Lingo and what has
fostered this language awareness. With a focus on the experiences of the local Aboriginal educator, language activist and
researcher, Bernadine Yeatman, we showcase a range of grounded methodologies, including devices like language posters, interviews
and illustrative stories, along with maps, timelines and cartoons developed in conjunction with a linguist, Denise Angelo. This
shines a light onto the practical ‘how to’ of language awareness for under-recognised language communities and the potential
support a linguist can provide. It exemplifies a research approach which engages linguistic knowledge with local language
expertise to co-design materials for community members, educators and service providers.
Animal Welfare for Therapy Dogs in Correctional Settings
Authors: Eaton-Stull Yvonne
Published: November 2023

For some people, visiting a locked facility like a jail or prison causes concern and anxiety. Yet, volunteers and workers who choose to engage in this line of work realize the potential risks and deem them acceptable in relation to the potential benefits. Therapy dogs, however, do not have these same choices. Therefore, it is up to the professionals and handlers to assure that any and all risks and concerns be adequately addressed to make sure the animal’s physical and emotional wellbeing is protected at all times. Various animal welfare challenges specifically related to therapy dogs that can present in jails, prisons, and juvenile facilities, along with strategies to manage and mitigate such risks, will be discussed.

Information

© The Author 2023
Ab initio molecular dynamics study of the local structures and migration behaviors of liquid Sb-based alloys
Authors: Li Zongbo , Li Yaxing , Feng Yun , Feng Yan , Wen Yufeng , Wang Richu , Peng Chaoqun , Cai Zhiyong
Published: November 2023

High-purity Sb is widely applied in the semiconductor industry, infrared detection and non-volatile memory. An in-depth knowledge of the local structure and related properties in liquid Sb-based alloys proves to be highly advantageous in the purification of Sb. In this work, an ab initio molecular dynamics simulation was used to study the local structures, dynamical properties, electronic structures and migration behaviors of liquid X-containing (X = As, Bi, Cu, Fe) Sb-based alloys. Among these solute atoms, the distribution coefficient of As/Bi is much larger than that of Cu/Fe. The results showed that the local structures around As/Bi are looser than those around Cu/Fe. The local structure around As/Bi contains a higher fraction of low-index bond pairs than that around Cu/Fe, and its local topological order of triples is closer to pure Sb melt. The coordination polyhedrons using As/Bi as the centered atom have more relaxed short-range order clusters than those using Cu/Fe as the centered atom. Different local structures and chemical effects may lead to different migration behaviors of solute atoms in the Sb melt.
Autonomous and intelligent optical tweezers for improving the reliability and throughput of single particle analysis
Authors: Teixeira Joana , Moreira Felipe C , Oliveira João , Rocha Vicente , Jorge Pedro A S , Ferreira Tiago , Silva Nuno A
Published: November 2023

Optical tweezers are an interesting tool to enable single cell analysis, especially when coupled with optical sensing and advanced computational methods. Nevertheless, such approaches are still hindered by system operation variability, and reduced amount of data, resulting in performance degradation when addressing new data sets. In this manuscript, we describe the deployment of an automatic and intelligent optical tweezers setup, capable of trapping, manipulating, and analyzing the physical properties of individual microscopic particles in an automatic and autonomous manner, at a rate of 4 particle per min, without user intervention. Reproducibility of particle identification with the help of machine learning algorithms is tested both for manual and automatic operation. The forward scattered signal of the trapped PMMA and PS particles was acquired over two days and used to train and test models based on the random forest classifier. With manual operation the system could initially distinguish between PMMA and PS with 90% accuracy. However, when using test datasets acquired on a different day it suffered a loss of accuracy around 24%. On the other hand, the automatic system could classify four types of particles with 79% accuracy maintaining performance (around 1% variation) even when tested with different datasets. Overall, the automated system shows an increased reproducibility and stability of the acquired signals allowing for the confirmation of the proportionality relationship expected between the particle size and its friction coefficient. These results demonstrate that this approach may support the development of future systems with increased throughput and reliability, for biosciences applications.
A first principle +U correction to the investigation of intrinsic vacancy and zinc vacancy-cluster induced magnetism in w-ZnO
Authors: Ahmed Eliyash , Senthilkumar K
Published: November 2023

Pure ZnO shows the probable origin of the magnetic nature. Microscopic correlation to point defect VO and the cluster VZn is obtained by first-principle calculation and +U interaction energy of the p-d orbital subjected to improve band and DOS. Hydrogen contribution to the magnetic moment (MM) due to the coupling of vacancy and 1 s electron correlates with the experimental outcomes. Intrinsic vacancy modulates Fermi surface electron density, leading to the stoner criterion. A higher-order magnetic moment is associated with the cluster vacancy, and the change in the MM has accounted for the +U adjustment to the relevant orbital impact. Nonlinear relations are due to cluster vacancy complexes VZn-x/Oi-x (x = H, 2H), and the FM and AFM exchange has been analyzed. The material encloses large grains; hence, it is advantageous for VZn to develop near the grain edge, and in O-rich environments, chemisorbed O2 is formed near the grain surface.
Force field study of catechol dimers and catechol-(H2O)n clusters
Authors: Obeid Emil , Murshid Nimer , Arayro Jack , Abu-samha Mahmoud
Published: November 2023

Force field parameters were developed for catechol and used to produce optimized structures of catechol dimers and catechol-(H2O)n clusters. The force field optimized structures for the catechol dimer and catechol-(H2O)n (with n = 1 and 2) clusters are benchmarked against quantum chemistry calculations at the B3LYP and w97XD levels of theory; with the quantum chemistry calculations taking into account basis set superposition error. The force field predicts, in agreement with B3LYP and w97XD reasonable structures and relative binding energies for two dimer structures and six catechol-(H2O)n clusters (with n = 1, 2). The developed forcefield parameters are then used to conduct molecular dynamics (MD) simulations for catechol-(H2O)15 cluster to highlight the effect of increased coordination number on the H-bond network around catechol with potential impact on the reactivity of catechol towards ozone in wet conditions. The result of MD simulations suggests that water molecules form a cage of H-bonds network around the hydroxyl groups of catechol, thereby blocking the active sites on catechol.
Two (w, ω, n) weighted threshold quantum secret sharing schemes on d-level single quantum systems
Authors: Guan Feiting , Guo Jiansheng , Li Lele
Published: November 2023

Quantum secret sharing occupies an important position in quantum cryptography. In this paper, we propose two

(
w
,
ω
,
n
)

weighted threshold quantum secret sharing schemes on d-level single quantum systems that share classical information and quantum states, respectively. The dealer Alice distributes the secret share to each participant using the Chinese Remainder Theorem(CRT) for a polynomial ring, which can realize secret sharing among participants with different weights. In classical information sharing, the dealer can share multiple secrets in one round of the protocol and the participants can verify the correctness of the recovered secrets. In quantum state sharing, the dealer can share multiple single quantum states in one round of protocol. Finally, we demonstrate that our scheme is resistant to common external and internal attacks and compare it with related schemes.
Some connections between galois group and free group
Authors: Zeng Ziyu
Published: November 2023

Free Group and Galois Theory are both new contents of modern mathematics with being widely studied, while there are few studies about the connections between them. We can find that the automorphisms in the definition of Galois Group is like the symbols in free group. The structure of subgroups in free groups is a significant subject which is originated from the Group Theory. Thus, this paper will introduce some basic theorems of Galois Group, free group and give a proof of the set of every subfield of a field is isomorphic to a free Galois Group.
A quantitative analysis on the influence of temperature on head loss along PVC pipe and the choice of pipe diameter
Authors: Wu Yutian
Published: November 2023

PVC pipe is widely used in engineering. For instance, it can be used to transport hot water. However, in the process of transmission, a certain head loss will be produced, and the cost problem will be considered in the choice of pipe diameter [1]. Through the controlling of variable, this paper introduces and deduces the formula used to calculate the influence of temperature on head loss. By listing the results and making a graph after calculation, the influence of temperature parameter change on the head loss of PVC pipe is explored, and a reasonable pipe diameter selection scheme is discussed. The formulas and parameters used in this paper are all from the research of other scholars and experts. The results show that the head loss in PVC pipe decreases gradually and stably with the increase of temperature. In addition, with the increase of pipe diameter, the head loss will be reduced, the power consumption of the pump will be reduced, but the material cost will be increased. In conclusion, the water temperature can be increased in a certain range to reduce the head loss. When the distance of pipe distribution is short, a larger pipe diameter can be selected to reduce the power consumption cost. For longer distances, smaller pipe diameters can be selected to reduce material costs.
Congruences and subdirect decompositions in universal algebra
Authors: Zhao Ranran
Published: November 2023

In this paper, we will focus on the topic of congruences and factorizations in universal algebra. We will first provide an introduction to universal algebra by defining lattices, algebras, congruences and other core structures. Next, we will explore the congruence and factorization properties of an algebra. Then, Birkhoff theorem indicates that every algebra can be embedded into a product of subdirectly irreducible algebras. Based on these fundamental concepts, Heyting algebra will be discussed as a typical example in universal algebra. The one-to-one correspondence between filters and congruences of a Heyting algebra will be proved. Lastly, we will show a specific way to justify the subdirectly irreducibility of a Heyting algebra.
Real model for micro swimmer and the study of the relationship between the swimming speed, pitch angle, and rotation rate for the flagellum
Authors: Ren Zhezheng
Published: November 2023

This study focuses on the fluid mechanics of a microswimmer and explores the relationship between speed, pitch angle, and rotation rate for the flagellar during bacterial swimming. Based on the simulation using MATLAB, it is concluded that when the pitch angle of the flagellar helix is in the range of 0 to 90 degrees, the value of swimming speed increases firstly and decreases. When the angle reaches 46.83 degrees, the speed reaches the maximum point. The radius of the body of the microswimmer is determined by the Buckingham Pi theory. After calculating by using the equations in the related paper and measuring by the real model, we derive that the relationship between swimming speed and the rotation rate for the flagellar filament should be proportional at the low rotation rate so that it can be obtained to optimize the artificial micro swimming device with higher swimming efficiency.
Design of a 5.94 FO4 absolute-value detector based on hybrid logic technique
Authors: Zhang Longyang
Published: November 2023

With the development of neural signal acquisition systems, spike sorting algorithms have become a hot topic in related fields. The delay of the spike detection system largely determines the speed of the overall signal acquisition system. This paper designs a low-delay Absolute-value Detector based on the GDI technique to improve the timeliness of the neural signal acquisition system. The final circuit has only 20 logic gates-56 transistors. According to the logical effort methodology, the final path delay is 5.94 FO4. This research can provide a reference for the design of future portable ultra-low delay neural signal acquisition systems.
Approaches to NMR sensitivity enhancement based on theoretical analysis
Authors: Du Meining
Published: November 2023

Nuclear magnetic resonance (NMR) has been broadly investigated and applied in many industries (e.g., medical treatment, food safety and materials) as a powerful approach to explore the internal structure and composition of substances. However, the need for more sensitivity has been one of the most severe problems hindering the practical application of NMR. This paper suggests various approaches to deal with this defect, from adjusting factors based on the theoretical principle to the progressive hyperpolarization method. Classified by polarization sources, several representative sub-fields of hyperpolarization are further interpreted and analyzed, including Dynamic Nuclear Polarization (DNP), Optical Pumping (OP) and Parahydrogen Induced Polarization (PHIP). Based on the analysis and prospect of the aforementioned feasible methods, the main factors that restrict the sensitivity of NMR will be identified. Moreover, the prospects and new technologies brought by the methods based on different theoretical foundations have been considered to improve these factors and make NMR apply to a broader range of fields. Overall, these results not only indicate the current research status but also shed light on guiding further exploration of methods of enhancing NMR sensitivity and usability.
Research on seismic behavior of prefabricated concrete beam-column joints
Authors: Song Zirui
Published: November 2023

In recent years, with the development of society, the construction method of cast-in-place has been unable to fully adapt to the needs of social development. The construction industry has ushered in new development opportunities, gradually to technology, energy-saving and pollution-free development. Prefabricated buildings have been promoted by reducing construction pollution, saving energy and improving labor efficiency. Different types of joints will directly affect the stability and seismic resistance of the whole structure, and also determine the progress of the prefabricated building. Therefore, the prefabricated reinforced concrete beam and column joints are very necessary to study the seismic performance. In this paper, the seismic performance of assembled concrete frame beam and column joints, assembled concrete beam-buckling column-steel restrained support joints and a new kind of prefabricated pin concrete beam-column joints are summarized and analyzed.
Research on the interaction mechanism of multiple vortices in biological wake flow field
Authors: Zhou Jianhan
Published: November 2023

The vortex-ring interaction of synchronous jets has been paid more attention by predecessors, while the research of asynchronous jets (i.e. there is a time difference between the start of jets) of parallel dual nozzles has been studied less. Therefore, the interaction between vortex rings and the vortex structure evolution of the dual-nozzle asynchronous jets with different time differences (Δt) is studied in this paper. Numerical results obtained can be divided into four intervals: 1. Synchronous jets (Δt = 0); 2. Critical interval (Δt < 0.1t, where t is the jet time), having similar vortex structure evolution modes and dynamic characteristics as the synchronous jet; 3. Strong interaction interval (0.2t ≤ Δt ≤ 0.4t), in which the main vortex ring shows obvious acceleration, and the streamwise vortex structure is found in the wake; 4. weak interaction interval (Δt ≥ 0.6t), in which the interaction between vortex rings is much less strong and the streamwise vortex structure also appears in the wake. In addition, it is found that pressure on the nozzle outlet plane increases and the vortex dissipation in the downstream flow field slows down significantly due to the vortex-ring interaction on the condition of asynchronous jets.
Image deblurring: comparison and analysis
Authors: Yu Zhiyi
Published: November 2023

Technological advancements and the advent of digital devices and media make images an important part of today’s social life. Image blurring is a common challenge that results from multiple factors such as object movement, camera shake, and raindrops, among others. Image deblurring has progressively become an important field of image restoration as directed by research findings. After research for more than five decades, significant research efforts have yielded useful technologies of image deblurring. This article provides an overview of the current knowledge on image deblurring technology by focusing on the classical methods and modern trends in the field. The article reviews the conventional methods and achievements made in past studies using evidence from 34 scholarly articles. The article also examines the application of algorithms in specific deblurring methodologies adopted in recent works. It covers the recent trend of learning-based models used to restore images and their effectiveness. They include Convolutional Neural Networks, Recurrent Neural Networks and Graph Convolutional Networks. Novel deep-learning deblurring techniques are also explored. Based on the findings, issues of concerns, opportunities and direction for future research are provided to advance image deblurring technologies.
A review on reconstruction algorithms and hardware implementation in electrical impedance tomography
Authors: Jia Yuheng
Published: November 2023

The current medical imaging techniques can only be used in a few diagnostic scenarios after the development of qualitative lesions, and they frequently include the use of radiation, among other things. Electrical impedance tomography, in contrast, uses no radiation and is non-invasive. Electric impedance tomography (EIT), which has these benefits, is frequently utilized for the early stages of disease detection and treatment. This study discusses the research advancements, image reconstruction methods, hardware system design, and clinical applications of EIT in the treatment of lung disorders for the application of EIT in the treatment of lung lesions. The intricacy of EIT systems and their solutions is explained by looking at and introducing a few key components of EIT technology. This provides research ideas for future studies and confirms the technology’s extensive development prospects. The outcome demonstrates that EIT is still in a relatively early stage of development and that image reconstruction algorithms are now being utilized to improve imaging resolution. The accuracy of data collection and processing is increasing, and hardware technology is also advancing quickly. EIT is also employed in clinical settings for pathology in the bladder, brain, and lungs. Future uses of EIT in medicine have a lot of potential for real-time, long-term monitoring and early diagnosis.
Comparison of improved variational autoencoder models for human face generation
Authors: He Lijie
Published: November 2023

The variational autoencoder (VAE) model has evolved a number of VAE improved models in the past 10 years, including CVAE, WAE, NVAE, etc. These models have greatly improved the calculation speed of VAE and the resolution of generated images. The main goal of this paper is to compare the principles of these different models and the effect of generating images. The principle analysis method is mainly used to study the improvement direction of the VAE model in different papers. The main ideas for improving the VAE model include optimizing the loss function, optimizing the objective function, introducing other parameters, or improving code efficiency. Some models even add many algorithms in computer vision in for improving image effect. In the experiments in this paper, results show the image results processed by different models. In the current optimal model NVAE, this algorithm has solved most of the VAE image blur problems, and has achieved perfection in image details. The improvement of the VAE model in the future may require innovative ideas. Under the current principle and model structure, the room for improvement of the VAE model is relatively limited. The final experiment shows that to improve the quality of VAE generated images, it is required to optimize the objective function, optimize the algorithm and add image visual processing, and then the generated images will be significantly improved.
Optimization approach in quadratic assignment and graph isomorphism
Authors: Liu Ruyi
Published: November 2023

Graph matching problem, also known as quadratic assignment problem (QAP) in a practical context, aims at finding the best correspondence between two given graphs. If two nodes are connected in one graph, it would be ideal if their corresponding images are connected in the other. The optimal solution should maximize the number of matches between the two graphs, while minimizing the weight of mismatches. Graph isomorphism is a particular case where an exact correspondence with no mismatches could be found. The quadratic assignment problem itself is hard to solve due to its high computational complexity. In this paper, the researcher analyzes two optimization approaches in detail: convex relaxation and the Fast Approximate QAP algorithm, both trying to solve the problem with lower computational effort. The performances of these two methods are further compared through numerical experiments. This paper focuses on pairs of equal-sized undirected graphs. ρ correlated graphs are constructed to simulate the noise in inexact graph matching problems. After comparing two existing methods, we propose an even faster optimization approach with comparable accuracy. This new approach provides a particular way to approximate an ideal initialization for the traditional Fast Approximate QAP algorithm. The significant reduction in the runtime makes obtaining good correspondence between large graphs feasible.
Continuous-bag-of-words and Skip-gram for word vector training and text classification
Authors: Xia Haowen
Published: November 2023

Natural language processing is one of the most challenging parts in the study of artificial intelligence and is widely used in real-life applications. One of the basic questions is how to calculate the probability of a particular text sequence appearing in a certain context. Word2Vec is a powerful tool that provides a solution to the question for its ability to transform words into word vectors, and to train in high efficiency on large datasets and corpora. It has many models of which Continuous-Bag-Of-Words and Skip-gram are of great significance and also known to many people. Furthermore, some extended techniques related to the models are also proposed in order to simultaneously decrease required training time and increase the rate of accuracy for the training. Even though there are now a number of papers that describe these fundamental concepts, the quality vary greatly. To better understand the models and their extensions, and how well they behave when used for real tasks, different combinations of the models and techniques are made in this paper so as to compare their performance in processing large input data and the ability for correct prediction in the task of text classification. This is done as it could lead to more provision of details and understandings of the model for subsequent researches on this field of study.
Can machine recognize a long-missed old friend? A test to the FaceNet face recognition algorithm
Authors: Dong Yuxuan
Published: November 2023

Facial recognition receives heated discussion in recent years. Given the increasing demand for portable and easy-to-use face recognition programs, several coding libraries have been developed that includes the algorithm for identifying and classifying faces. One example of such libraries, the “face_recognition” library developed by Adam Geitgey allows fast execution for face recognition tasks and requires only 1 photo as training input. It adopts the Convolutional Neural Network (CNN) from OpenFace, which is built based on the FaceNet algorithm. Although the study claims that the algorithm has a high base on tests from common face dataset, it is not clear whether the algorithm can identify people consistently when they are in their different ages. In this paper, a face dataset is constructed by collecting publicly available photos from celebrities that can be traced to a certain date of taken. These photos are grouped by 5 pieces per person with each photo taken roughly 4 years apart from the previous one. Then, experiments are conducted to test the effectiveness of face_recognition library on identifying the person from these groups of photos. The results report an over 75% success rate for the algorithm on image identification tasks, indicating a good ability for the face encoding to resist the gap of time.
Numerical simulation of the mold filling process of the brake lever for an electric multiple unit
Authors: Cao Xia , Ma Yunan
Published: November 2023

The brake lever for an electric multiple unit (EMU) of a train is an important supporting component that directly affects the usability and safety of EMU. In this study, the mold filling, solidification, and shrinkage processes of the brake lever of the EMU were simulated using Anycasting software, and the distributions of the mold filling speed, mold filling temperature, and shrinkage defects were analyzed. The results show that the brake lever for the EMU exhibits casting defects such as shrinkage porosity and shrinkage cavities. To eliminate these casting defects, a chilled-iron process was developed; however, the appearance of cementite increased the brittleness of the castings, which deteriorated their strength and plastic toughness. Hence, a snap-chilling sheet process was designed to fabricate the brake lever for the EMU, and a numerical simulation of the process was performed using the Anycasting software. The shrinkage defects of the castings were effectively eliminated; simultaneously, the cementite disappeared, and the microstructure of the thick parts of the brake lever showed no obvious changes. The prepared brake lever satisfied the requirements of the EMU.
Detailed high quality surface-based mouse CAD model suitable for electromagnetic simulations
Authors: Serano Peter , Makaroff Sergey , Ackerman Jerome L , Nummenmaa Aapo , Noetscher Gregory M
Published: November 2023

Transcranial magnetic stimulation (TMS) studies with small animals can provide useful knowledge of activating regions and mechanisms. Along with this, functional magnetic resonance imaging (fMRI) in mice and rats is increasingly often used to draw important conclusions about brain connectivity and functionality. For cases of both low- and high-frequency TMS studies, a high-quality computational surface-based rodent model may be useful as a tool for performing supporting modeling and optimization tasks. This work presents the development and usage of an accurate CAD model of a mouse that has been optimized for use in computational electromagnetic modeling in any frequency range. It is based on the labeled atlas data of the Digimouse archive. The model includes a relatively accurate four-compartment brain representation (the ‘whole brain’ according to the original terminology, external cerebrum, cerebellum, and striatum [9]) and contains 21 distinct compartments in total. Four examples of low- and high frequency modeling have been considered to demonstrate the utility and applicability of the model.
Preliminary insight into the relationship between bioaerosols and urban environment obtained from the COVID-19 self-quarantine period in the Tokyo metropolitan area
Authors: Murata Kotaro , Okochi Hiroshi , Kamogawa Masashi
Published: November 2023

Anthropogenic activities and meteorological conditions influence the composition of urban bioaerosols. The COVID-19 epidemic drastically reduced anthropogenic activities in the metropolitan areas of Japan in 2020. This study examined inter-day fluctuations in airborne bacterial and fungal compositions in Tokyo, Japan, between April and June 2020, under exceptionally unusual conditions where the movement of people and economic activity had been greatly reduced. The result showed, as expected, that local meteorological factors, especially wind and precipitation, substantially impacted emissions and changes in bacterial and fungal aerosols. However, we found that variations in the composition of urban bioaerosols could potentially be affected by anthropogenic influences, such as the concentrations of nitrogen oxides, ozone, and particulate matter, and human density. Although such factors are not as influential as wind and precipitation, it was shown for the first time that drastic changes in human activities within an area can affect the dynamics of bioaerosols. This could be a finding that should be considered for public health issues related to air quality in changing urban areas such as fast-growing cities.
Computational investigation towards highly efficient Sb2Se3 based solar cell with a thin WSe2 BSF layer
Authors: Ebon Md Islahur Rahman , Ali Md Hasan , Haque Md Dulal , Touhidul Islam Abu Zafor Md
Published: November 2023

A novel structure of chalcogenide-based antimony selenide (Sb2Se3) which is the most promising absorber materials in the field of thin film solar cells with a tungsten diselenide (WSe2) back surface field (BSF) has been proposed in this paper. Antimony selenide (Sb2Se3) with a BSF has been observed by one-dimensional solar cell capacitance simulator (SCAPS-1D). Its recognizable properties make it one of the most usable for non-toxic solar cell absorbers. This paper demonstrated the planning and modeling of Al/FTO/n-TiO2/p-Sb2Se3/Ni (without BSF) and Al/FTO/n-TiO2/p-Sb2Se3/p+-WSe2/Ni (with BSF) structures. The capability of Al/FTO/n-TiO2/p-Sb2Se3/p+-WSe2/Ni heterojunction solar cell structure shows the promising performances. We have numerically simulated and observed the performance parameters such as power conversion efficiency (PCE), open circuit voltage (VOC), short circuit current density (JSC) and fill factor (FF) by tuning the different parameters such as thickness, doping concentration, defect density, the interface defect density, surface recombination velocity, series and shunt resistances along with temperature. The PCE of 20.61% with an absorber’s thickness of 800 nm for without BSF has been achieved. By inserting the WSe2 BSF with thickness of 100 nm, highly improving efficiency of 32.35% has been demonstrated. Our simulation and numerical analysis also provide valuable and important information that is very effective for further implementation and achieving high efficiency of thin film solar cell.
On varimax asymptotics in network models and spectral methods for dimensionality reduction
Authors: Cape J
Published: November 2023

Varimax factor rotations, while popular among practitioners in psychology and statistics since being introduced by Kaiser (1958), have historically been viewed with skepticism and suspicion by some theoreticians and mathematical statisticians. Now, work by Rohe & Zeng (2023) provides new, fundamental insight: varimax rotations provably perform statistical estimation in certain classes of latent variable models when paired with spectral-based matrix truncations for dimensionality reduction. We build on this new-found understanding of varimax rotations by developing further connections to network analysis and spectral methods rooted in entrywise matrix perturbation analysis. Concretely, this paper establishes the asymptotic multivariate normality of vectors in varimax-transformed Euclidean point clouds that represent low-dimensional node embeddings in certain latent space random graph models. We address related concepts including network sparsity, data denoising and the role of matrix rank in latent variable parameterizations. Collectively, these findings, at the confluence of classical and contemporary multivariate analysis, reinforce methodology and inference procedures grounded in matrix factorization-based techniques. Numerical examples illustrate our findings and supplement our discussion.
Global benchmarks in primary robotic bariatric surgery redefine quality standards for Roux-en-Y gastric bypass and sleeve gastrectomy
Authors: Giudicelli Guillaume , Gero Daniel , Romulo Lind , Chirumamilla Vasu , Iranmanesh Pouya , Owen Christopher K , Bauerle Wayne , Garcia Amador , Lucas Lisa , Mehdorn Anne-Sophie , Pandey Dhananjay , Almuttawa Abdullah , Cabral Francisco , Tiwari Abhishek , Lambert Virginia , Pascotto Beniamino , De Meyere Celine , Yahyaoui Marouan , Haist Thomas , Scheffel Oliver , Robert Maud , Nuytens Frederiek , Azagra Santiago , Kow Lilian , Prasad Arun , Vaz Carlos , Vix Michel , Bindal Vivek , Beckmann Jan H , Soussi David , Vilallonga Ramon , El Chaar Maher , Wilson Erik B , Ahmad Arif , Teixeira Andre , Hagen Monika E , Toso Christian , Clavien Pierre-Alain , Puhan Milo , Bueter Marco , Jung Minoa K
Published: November 2023

Background

Whether the benefits of the robotic platform in bariatric surgery translate into superior surgical outcomes remains unclear. The aim of this retrospective study was to establish the ‘best possible’ outcomes for robotic bariatric surgery and compare them with the established laparoscopic benchmarks.

Methods

Benchmark cut-offs were established for consecutive primary robotic bariatric surgery patients of 17 centres across four continents (13 expert centres and 4 learning phase centres) using the 75th percentile of the median outcome values until 90 days after surgery. The benchmark patients had no previous laparotomy, diabetes, sleep apnoea, cardiopathy, renal insufficiency, inflammatory bowel disease, immunosuppression, history of thromboembolic events, BMI greater than 50 kg/m2, or age greater than 65 years.

Results

A total of 9097 patients were included, who were mainly female (75.5%) and who had a mean(s.d.) age of 44.7(11.5) years and a mean(s.d.) baseline BMI of 44.6(7.7) kg/m2. In expert centres, 13.74% of the 3020 patients who underwent primary robotic Roux-en-Y gastric bypass and 5.9% of the 4078 patients who underwent primary robotic sleeve gastrectomy presented with greater than or equal to one complication within 90 postoperative days. No patient died and 1.1% of patients had adverse events related to the robotic platform. When compared with laparoscopic benchmarks, robotic Roux-en-Y gastric bypass had lower benchmark cut-offs for hospital stay, postoperative bleeding, and marginal ulceration, but the duration of the operation was 42 min longer. For most surgical outcomes, robotic sleeve gastrectomy outperformed laparoscopic sleeve gastrectomy with a comparable duration of the operation. In robotic learning phase centres, outcomes were within the established benchmarks only for low-risk robotic Roux-en-Y gastric bypass.

Conclusion

The newly established benchmarks suggest that robotic bariatric surgery may enhance surgical safety compared with laparoscopic bariatric surgery; however, the duration of the operation for robotic Roux-en-Y gastric bypass is longer.
First successful implementation of subintimal transcatheter withdrawal technique in intravascular ultrasound–guided tip detection antegrade dissection and reentry: a case report
Authors: Kitani Shunsuke , Tsuchikane Etsuo , Yamaki Masaru , Igarashi Yasumi
Published: November 2023

Background

Antegrade dissection and reentry (ADR) is an effective technique for wire passage in chronic total occlusion (CTO), and in recent years, the effectiveness of intravascular ultrasound (IVUS)–guided tip detection (TD)-ADR has been reported. However, the expansion of the subintimal space serves as a significant obstacle to the success of ADR, posing a limitation to the procedure.

Case summary

We present the first case of using IVUS-guided TD-ADR with the subintimal transcatheter withdrawal (STRAW) technique. The patient was a 68-year-old Asian female with effort angina pectoris and a CTO in the middle section of the right coronary artery (RCA). Two previous attempts at percutaneous coronary intervention (PCI) for the RCA at another hospital were unsuccessful. During the third attempt PCI, the antegrade wire migrated into the subintimal space. To address this, we performed IVUS-guided TD-ADR using the Conquest Pro 12 Sharpened Tip (CP12ST; Asahi Intecc, Aichi, Japan) wire. However, due to the expansion of the subintimal space, we were unable to puncture the true lumen. To reduce the subintimal space, we employed the STRAW technique, which allowed successful puncture of the true lumen using the CP12ST wire. Finally, stenting was performed, resulting in satisfactory antegrade blood flow.

Discussion

Intravascular ultrasound–guided TD provides accurate guidance for puncturing in ADR procedures, but the expansion of the subintimal space remains a significant challenge. The STRAW technique offers a solution by reducing the subintimal space and enabling successful puncture of the true lumen during IVUS-guided TD-ADR.
Decolonial Gazing and Hermeneutic Resistance: Black German Challenges to White German Cultural Hegemony in the Museum
Authors: Gallagher Maureen O
Published: November 2023

In this article, I highlight the ways that Black Europeans challenge universalizing notions of cultural heritage to emphasize decolonial possibilities. Focusing on the German context, I show how Black artists, intellectuals and activists interrogate the collection, display and spectatorship of museum objects in majority-white contexts using the strategies of decolonial gazing and hermeneutic resistance. I use the Berlin Ethnological Museum in its former and current iterations as a representative example of debates about collecting and looking at museums, showing how scholars like Fatima El-Tayeb and initiatives like No Humboldt21! challenge universalizing discourses and reflect the gaze back on whiteness. Finally, I offer a reading of a literary challenge to white hegemony within and beyond the museum in Sharon Dodua Otoo’s 2021 novel Adas Raum [Ada’s Realm].
MetGENE: gene-centric metabolomics information retrieval tool
Authors: Srinivasan Sumana , Maurya Mano R , Ramachandran Srinivasan , Fahy Eoin , Subramaniam Shankar
Published: November 2023

Background

Biomedical research often involves contextual integration of multimodal and multiomic data in search of mechanisms for improved diagnosis, treatment, and monitoring. Researchers need to access information from diverse sources, comprising data in various and sometimes incongruent formats. The downstream processing of the data to decipher mechanisms by reconstructing networks and developing quantitative models warrants considerable effort.

Results

MetGENE is a knowledge-based, gene-centric data aggregator that hierarchically retrieves information about the gene(s), their related pathway(s), reaction(s), metabolite(s), and metabolomic studies from standard data repositories under one dashboard to enable ease of access through centralization of relevant information. We note that MetGENE focuses only on those genes that encode for proteins directly associated with metabolites. All other gene–metabolite associations are beyond the current scope of MetGENE. Further, the information can be contextualized by filtering by species, anatomy (tissue), and condition (disease or phenotype).

Conclusions

MetGENE is an open-source tool that aggregates metabolite information for a given gene(s) and presents them in different computable formats (e.g., JSON) for further integration with other omics studies. MetGENE is available at https://bdcw.org/MetGENE/index.php.
Variability analysis of LC-MS experimental factors and their impact on machine learning
Authors: Rehfeldt Tobias Greisager , Krawczyk Konrad , Echers Simon Gregersen , Marcatili Paolo , Palczynski Pawel , Röttger Richard , Schwämmle Veit
Published: November 2023

Background

Machine learning (ML) technologies, especially deep learning (DL), have gained increasing attention in predictive mass spectrometry (MS) for enhancing the data-processing pipeline from raw data analysis to end-user predictions and rescoring. ML models need large-scale datasets for training and repurposing, which can be obtained from a range of public data repositories. However, applying ML to public MS datasets on larger scales is challenging, as they vary widely in terms of data acquisition methods, biological systems, and experimental designs.

Results

We aim to facilitate ML efforts in MS data by conducting a systematic analysis of the potential sources of variability in public MS repositories. We also examine how these factors affect ML performance and perform a comprehensive transfer learning to evaluate the benefits of current best practice methods in the field for transfer learning.

Conclusions

Our findings show significantly higher levels of homogeneity within a project than between projects, which indicates that it is important to construct datasets most closely resembling future test cases, as transferability is severely limited for unseen datasets. We also found that transfer learning, although it did increase model performance, did not increase model performance compared to a non-pretrained model.
Compound probiotics can improve intestinal health by affecting the gut microbiota of broilers
Authors: Liu Xuan , Ma Zhenhua , Wang Yanfei , Li Li , Jia Hao , Zhang Lihuan
Published: November 2023

Probiotics, as a widely used additive, have played a unique advantage in replacing antibiotic products. As a result, the probiotic effects on broiler development, intestinal flora, intestinal barrier, and immunity were assessed by this investigation. Four hundred and eighty 1-day-old Arbor Acres broilers were randomly allotted to 4 groups of 5 replicates with 24 broilers each. The control was fed only a basal corn–soybean meal diet. Probiotics I, probiotics II, and probiotics III were fed basal diet and 1, 5, and 10 g/kg compound probiotics (Lactobacillus casei: Lactobacillus acidophilus: Bifidobacterium = 1:1:2), respectively. We found that broilers in the compound probiotic group exhibited better growth performance and carcass characteristics compared with control, especially among probiotics III group. The intestinal barrier-related genes relative expression of Claudin, Occludin, MUC2, and ZO-1 mRNA in the probiotic group increased at 21 and 42 d compared with control, especially among probiotics III group (P < 0.05). The early gut immune-related genes (TLR2, TLR4, IL-1β, and IL-2) mRNA increased compared with control, while the trend at 42 d was completely opposite to that in the earlier stage (P < 0.05). Among them, probiotics III group showed the most significant changes compared to probiotics II group and probiotics I group. Select probiotics III group and control group for 16S rDNA amplicon sequencing analysis. The 16S rDNA amplicon sequencing results demonstrated that probiotics increased the relative abundance of beneficial microbes such as o_Bacteroidales, f_Rikenellaceae, and g_Alistipes and improved the cecum’s gut microbiota of 42-day-old broilers. Additionally, adding the probiotics decreased the relative abundance of harmful microbes such as Proteobacteria. PICRUSt2 functional analysis revealed that most proteins were enriched in DNA replication, transcription, and glycolysis processes. Therefore, this study can provide theoretical reference value for probiotics to improve production performance, improve intestinal barrier, immunity, intestinal flora of broilers, and the application of probiotics.