bluuebunny/crossref_metadata_2025 huggingface dataset:
Bioinformatics approach to spatially resolved transcriptomics
Authors: Krešimir Lukić Ivan
Published: August 2021

Spatially resolved transcriptomics encompasses a growing number of methods developed to enable gene expression profiling of individual cells within a tissue. Different technologies are available and they vary with respect to: the method used to define regions of interest, the method used to assess gene expression, and resolution. Since techniques based on next-generation sequencing are the most prevalent, and provide single-cell resolution, many bioinformatics tools for spatially resolved data are shared with single-cell RNA-seq. The analysis pipelines diverge at the level of quantification matrix, downstream of which spatial techniques require specific tools to answer key biological questions. Those questions include: (i) cell type classification; (ii) detection of genes with specific spatial distribution; (iii) identification of novel tissue regions based on gene expression patterns; (iv) cell–cell interactions. On the other hand, analysis of spatially resolved data is burdened by several specific challenges. Defining regions of interest, e.g. neoplastic tissue, often calls for manual annotation of images, which then poses a bottleneck in the pipeline. Another specific issue is the third spatial dimension and the need to expand the analysis beyond a single slice. Despite the problems, it can be predicted that the popularity of spatial techniques will keep growing until they replace single-cell assays (which will remain limited to specific cases, like blood). As soon as the computational protocol reach the maturity (e.g. bulk RNA-seq), one can foresee the expansion of spatial techniques beyond basic or translational research, even into routine medical diagnostics.
A Proposed Framework for Increasing Racial and Ethnic Diversity in Communication Sciences and Disorders Academic Programs: The REAP Model
Authors: Mohapatra Bijoyaa , Mohan Ranjini
Published: August 2021

Purpose

Despite the growing clinical and research advances in communication sciences and disorders (CSD), health disparities persist by race/ethnicity and socioeconomic status among patients. A diverse CSD workforce can improve access to services and reduce health care disparities for diverse populations. Increasing diversity of the workforce begins with recruiting and training a diverse student body in CSD academic programs. In the absence of relevant literature in CSD, the primary objective of this tutorial is to introduce readers to successful diversity and inclusion programs in health-related disciplines such as nursing, medicine, rehabilitation sciences, public health, and clinical psychology, as well as provide recommendations for developing a racially and ethnically diverse and inclusive CSD academic program.

Conclusions

We group the evidence from other health-related academic programs for increasing diversity and inclusion under three headings—(a) recruitment, (b) inclusion, and (c) retention of underrepresented racial and ethnic minority (UREM) students. Based on this information, we have designed the Recruit–Equip–Access–Progress model to illustrate the strategies for a diverse and inclusive CSD training program. We recommend the following for UREM students in this model—(a) developing pipeline programs, institutional partnerships, and holistic admissions reviews; (b) equipping students with academic and financial supports; (c) providing students access to faculty and peer mentors; and (d) evaluating outcomes and processes associated with student and program success. Given the limited literature concerning successful diversity initiatives in our field, we encourage administrators and educators to implement these strategies, systematically evaluate the outcomes, and publish the results for other programs to adopt.
Vehicle Owner Recognition and Speed Estimation through LPD using Deep learning (VORSELD)
Authors: Shrivastava Mudit , Jadhav Rahul , Singhal Pranjal , Bhosale Savita R.
Published: August 2021

As name characterizes understanding of a number plate accordingly, from past decades the use vehicles expanded rapidly, taking into account of this such a majority number of issues like overseeing and controlling trafficante keeping watch on autos and managing parking area zones to overcome this tag recognizer programming is required. The proposed work aims to detect speed of a moving vehicle through its license plate. It will fetch vehicle owner details with the help of CNN model. In this project the main focus is to detect a moving car whenever it crosses dynamic markings. It uses Tensor-flow with an SSD object detection model to detect cars and from the detection in each frame the license plate gets detected and each vehicle can be tracked across a video and can be checked if it crossed the markings made in program itself and hence speed of that vehicle can be calculated. The detected License plate will be forwarded to trained model where PyTesseract is used, which will convert image to text.
Cost-Effective Disinfection Robot Using UVC Radiation
Authors: Dhikle Mansi , Dharne Vinaya , Gaikar Pankaja , Fakir Kausar
Published: August 2021

Sanitization with human efforts is not an easy task. Chances of contracting infections increases which leads to additional spread of bacteria. Currently, normal cleaning robots are used in most of the places but looking at the current situation the sanitization techniques need to be improved. The robot uses radiation of UV rays to kill the microrganisms. It gives a live video streaming of its surrounding using a Wi-fi based camera. With the help of Bluetooth module and android mobile, we can control the movement of the robot inside the room without being physically present. It is built with PIC Microcontroller and Ultraviolet-C (UVC) Sanitization LED. UV-C has bandwidth range of 200-280nm and is most powerful when it comes to killing pathogens in the room. This allows us to sterilise the room effectively. By killing the germs, the UV light restricts their multiplication by destroying their reproductive system. Thus use of this robot lowers the threat of infection, cost of traditional cleaning and sterilisation and increases security in medical facilities. Thus, we are trying to implement a more efficient way of sanitization by building a Low cost UV sanitization Robot which can be used in small clinics and for household purpose.
Android-based object recognition application for visually impaired
Authors: Salunkhe Akilesh , Raut Manthan , Santra Shayantan , Bhagwat Sumedha
Published: August 2021

Detecting objects in real-time and converting them into an audio output was a challenging task. Recent advancement in computer vision has allowed the development of various real-time object detection applications. This paper describes a simple android app that would help the visually impaired people in understanding their surroundings. The information about the surrounding environment was captured through a phone’s camera where real-time object recognition through tensorflow’s object detection API was done. The detected objects were then converted into an audio output by using android’s text-to-speech library. Tensorflow lite made the offline processing of complex algorithms simple. The overall accuracy of the proposed system was found to be approximately 90%.
Identification of Lost Children using Face Aging with Conditional GAN
Authors: Pupala Amisha , Mokal Samruddhi , Pandit Neha , Bharne Smita
Published: August 2021

Face recognition technology is a big area that consists of the many features in it but it also comes with some of the factors which affect this technology, one of the factors is Face aging which makes face recognition more difficult. As in India, a large number of children go missing every year. Also just using a photograph is not enough for the process to proceed smoothly and it results in a huge percentage of the missing child cases remain untraced. This paper presents a novel use of face recognition with face aging to overcome the limitation of existing systems. The proposed system has a portal where the public can upload an image of a suspected child and also have a feature where searching for any lost child is possible. The proposed system has mainly concentrated on an Age Conditional generative adversarial network (C-GAN) algorithm for face aging and the FaceNet algorithm for face feature extraction and face recognition.
Offline handwritten signature verification using various Machine Learning Algorithms
Authors: Lokare Chinmay , Patil Rachana , Rane Saloni , Kathirasen Deepakkumar , Mistry Yogita
Published: August 2021

In today’s world it is necessary to protect one’s authenticity in order to ensure the protection of personal information that only the authenticate credentials of a person can have access to. Nowadays there is an increase in number of malpractices like signature forgery to access the important information of a person. To encounter signature verification problem, there have been a number of advances in verifying the authenticity of signature using various techniques including Machine Learning and Deep Learning. This paper introduces a novel approach to verify the signatures using difference of gaussian filtering technique, gray level co-occurrence matrix feature extraction technique, principle component analysis and kernel principal component analysis associated with various machine learning algorithms. The publicly available Kaggle offline handwritten signature dataset is used for training. This article compares the accuracy of the dataset on various machine learning algorithms. After training datasets the lowest accuracy achieved is 56.66% for Naive Bayes algorithm. The highest accuracy achieved is 82% for K-Nearest Neighbour (KNN) and 81.66% for Random Forest using principle components and kernel principle components of the dataset.
SpeakQL Natural Language to SQL
Authors: Shah Dhairya , Das Aniruddha , Shahane Aniket , Parikh Dharmik , Bari Pranit
Published: August 2021

Incorporating SQL questions from normal language is a long-standing open issue and has been drawing in extensive intrigue as of late. Natural Language Interface (NLI) is the confluence of Natural Language Processing (NLP) and Human-Computer Interaction, which allows interaction between humans and computers through the utilization of Natural Language. Here we are gonna deal with the problem of automatic generation of Structured Query Language (SQL) queries. SQL is a database language for querying and manipulating relational databases. Despite the spectacular rise in the acceptance of relational databases, there is a fundamental limitaion to the ability to fetch data from those databases. One of the major reasons for this is the fact that the users of these relational databases need to comprehend convoluted structured query languages. In this body of work, we present an interface that allows users to interact with the databases using Natural Lanaguage as opposted to the conventional structure query languages.
Deep Learning based Automatic Extraction of Student Performance from Gazette Assessment Data
Authors: Nikam Rohan , Pardeshi Ritesh , Patel Yash , Sarda Ekta
Published: August 2021

Everyday millions of files are generated worldwide containing humongous amounts of data in an unstructured format. Most of us come across at least one new document every week, which tells the large volume of data associated with documents. All the data in these documents is in unstructured format which makes it difficult for further processing. The extraction of data from this documents still remains largely a manual effort resulting in higher processing time. A system that could extract the required fields from documents and store them in a structured format automatically will be of much significance. In this paper, we have described an approach for extracting the data from Exam Result Gazette document and then storing it in a CSV file. Mask RCNN model having a backbone of ResNeXt-101-32x8d and Feature Pyramid Network(FPN) has been hypertuned for detecting the required fields. Then PyTesseract Optical Character Recognition System has been used for extracting the data from detected fields. Our proposed system is trained on custom data set created by us and then evaluated on test data to extract the required fields. The overall accuracy of our system is 98.69%. The results indicate that the system could be used for efficiently extracting the required fields from given exam result gazette document.
A Framework for Secure Storage and Sharing of Electronic Health Records using Blockchain Technology
Authors: Gharat Anurag , Aher Pratik , Chaudhari Punit , Alte Bhavana
Published: August 2021

Public Healthcare issues have been the main focus of any governing body for the last decade. Each day a large amount of Healthcare data is generated by individual and Medical Organizations. This information is considered highly sensitive and private, which needed to be securely stored and protected against unauthorized access. In a traditional system, all the data is stored in a centralized system which comes with lots of drawbacks. This where blockchain technology comes in because of its Peer-To-Peer nature and Security. Several studies highlight the importance of blockchain and how it can be implemented in Electronic Medical Record(EMR) systems which face problems regarding privacy,security,decentralization and confidentiality.In this paper, We explain how blockchain technology may be utilised to improve EMR systems and how it could be a solution to these problems. We offer a framework for implementing blockchain technology in the healthcare industry for EMR.The aim of our proposed framework is first to implement blockchain technology for EHR and secondly to provide secure storage of electronic records by defining granular access rules for the users of the proposed framework. Moreover,this framework provides the EHR system with the benefits of a blockchain-based solution that is scalable, secure, and integrated.
Movie Posters’ Classification into Multiple Genres
Authors: Narawade Vaibhav , Potnis Aneesh , Ray Vishwaroop , Rathor Pratik
Published: August 2021

Our project intends to classify movies into the three most probable genres that they belong to, from a predefined set of 25 genres, based on only one image i.e the movie poster. We have made use of Convolutional Neural Networks (CNN) to realize this project as we believe it would be of help to extract the features and visual information from the image. Instead of a multi-class classification problem in which the input is classified into any one class, this project would be more correctly described as a multilabel classification problem as a movie belongs to more than one genre. In this project we see a comparative study of different architectures and tune them to yield the best result based on the metric of accuracy. We have applied various techniques such as data augmentation and L2 regularization to comparatively deduce the model that performs best from all the tested models.
A unified schedule policy of distributed machine learning framework for CPU-GPU cluster
Authors: Zhu Ziyu , Tang Xiaochun , Zhao Quan
Published: August 2021

With the widespread using of GPU hardware facilities, more and more distributed machine learning applications have begun to use CPU-GPU hybrid cluster resources to improve the efficiency of algorithms. However, the existing distributed machine learning scheduling framework either only considers task scheduling on CPU resources or only considers task scheduling on GPU resources. Even considering the difference between CPU and GPU resources, it is difficult to improve the resource usage of the entire system. In other words, the key challenge in using CPU-GPU clusters for distributed machine learning jobs is how to efficiently schedule tasks in the job. In the full paper, we propose a CPU-GPU hybrid cluster schedule framework in detail. First, according to the different characteristics of the computing power of the CPU and the computing power of the GPU, the data is divided into data fragments of different sizes to adapt to CPU and GPU computing resources. Second, the paper introduces the task scheduling method under the CPU-GPU hybrid. Finally, the proposed method is verified at the end of the paper. After our verification for K-Means, using the CPU-GPU hybrid computing framework can increase the performance of K-Means by about 1.5 times. As the number of GPUs increases, the performance of K-Means can be significantly improved.
Multi-UAVs task assignment method considering expected destruction probability of target
Authors: Zhou Qian , Gao Shesheng , Gao Zhaohui , Xia Juan , Hong Genyuan
Published: August 2021

To solve the combat task assignment of reconnaissance unmanned aerial vehicle (RUAV)/unmanned combat aerial vehicle(UCAV), this paper proposed an efficient task assignment method that takes into account the expected destruction probability of target. This method improves the utility function and constraint of the model that based on the goal of destroying the total sum of the target value. The adjustment factor is added to the model to achieve a balanced distribution of RUAVs/UCAVs resources; the expected destruction probability of target is introduced as a constraint to prevent the excessive distribution of RUAVs/UCAVs resources. Subsequently, a greedy algorithm based on maximizing marginal-return is designed to solve the proposed model. The simulation results show that the improved algorithm not only meets the combat effectiveness but also improves the economic performance on the basis of real-time task allocation.
Dynamic modelling of vacuum circulation process for steel decarburization
Authors: Kleimt B. , Köhle S.
Published: August 2021

A dynamic matbematical model of the vacuum circulation process for steel decarburization was developed. [t comprises the process parts of steel circulation decarburization reaction, adjustment of vessel pressure with its influence on the carbon equilibrium content, and the oxygen pickup from the ladle slag.

The model allows to simulate the behaviour of all important process values with good accuracy and can be used for optimization of plant construction and operation as well as for improvement of process control.
Kinetics of decarburization in the RH degasser at Sollac Dunkerque
Authors: Nuss C. , Gaggioli A. , Ritt J. P. , Gaye H. , Zbaczyniak Y. , Vromen C. , Butaye J.
Published: August 2021

At Sollac-Dunkerque, a characterization of the present RH process for production of ultra-low carbon steels was performed. A study of the decarburization kinetics was possible thanks to gas analysis. As a first result, the treatment time can safely be reduced by three minutes. Moreover, in the ultra-low carbon range, the decarburization kinetics is strongly slowed down due to the suppression of the boiling mechanism.
La filiere de consommation : un modèle dynamique d'analyse des marchés de métaux
Authors: Ndiaye N.
Published: August 2021

La saturation et la segmentation des marchés de biens durables et d'équipement, le morcellement des marchés d'application finale des métaux, l'intensification de la concurrence entre matériaux sont autant de phénomènes devenus majeurs, après les chocs pétroliers, que des modèles simples sont incapables de prendre en compte. Le modèle d'analyse fonctionnelle, fondé sur le concept de filière de consommation, permet de prendre en compte, dans l'analyse des dynamiques de marchés, l'ensemble des facteurs déterminants sur toute la chaîne de transformation et d'utilisation des métaux.
Photoinduced nonlinear magnetoelectric effect detection in Zn2Y hexaferrite
Authors: Shepelytskyi Yurii , Li Tao , Grynko Oleksandr , Reznik Alla , Grynko Vira , Hane Francis T. , Albert Mitchell S.
Published: August 2021

The photoinduced nonlinear magnetoelectric effect was investigated in the single-crystal Y-type Ba2Zn2Fe12O22 (Zn2Y) hexaferrite under ultraviolet radiation. We observed a downshift of the ferromagnetic resonance frequency caused by decreasing the effective saturation magnetization. The maximum observed shift of the resonance frequency was equal to 110 MHz corresponding to effective saturation magnetization decrease by 256 G. A strong nonlinear change in effective saturation magnetization was observed as the result of the photoinduced nonlinear magnetoelectric effect. The strength of the photoinduced nonlinear magnetoelectric effect was found to be up to 85% higher compared to the strength of the nonlinear magnetoelectric effect. The results demonstrate the possibility of optical tuning of the ferromagnetic resonance frequency and the mechanism of using the single-crystal Zn2Y for radiation detection.
Influence of the carrier behaviors in p-GaN gate on the threshold voltage instability in the normally off high electron mobility transistor
Authors: Chen Xin , Zhong Yaozong , Zhou Yu , Su Shuai , Yan Shumeng , Guo Xiaolu , Gao Hongwei , Zhan Xiaoning , Ouyang Sihua , Zhang Zihui , Bi Wengang , Sun Qian , Yang Hui
Published: August 2021

Threshold voltage (VTH) instability has been studied in the as-fabricated p-GaN gated enhancement-mode high electron mobility transistors (p-GaN E-HEMTs) under a positive gate stress. A negative VTH shift (ΔVTH) obtained by dynamic measurement has been observed more severely when compared to the static one. The VTH deviation is attributed to the complicated influence of carrier transport behaviors in the p-GaN gate. The impacts of hole accumulation, trapping, and consumption on the VTH instability and drain current variation can be effectively distinguished according to the transfer characteristics obtained from the pulse I–V measurement. Moreover, the density of hole traps in the p-GaN gate is estimated to be around ∼2 × 1011 cm−2 by the capacitance–voltage measurement, and the energy level is calculated to be around EV + 0.62 eV by fitting the recovery curve of gate current after positive gate bias. This study focusing on the in-depth influence of different carrier behaviors on the gate performance can help with the understanding and further improvement of the dynamic instability and reliability of the GaN-based HEMTs.
An extended autoencoder model for reaction coordinate discovery in rare event molecular dynamics datasets
Authors: Frassek M. , Arjun A. , Bolhuis P. G.
Published: August 2021

The reaction coordinate (RC) is the principal collective variable or feature that determines the progress along an activated or reactive process. In a molecular simulation using enhanced sampling, a good description of the RC is crucial for generating sufficient statistics. Moreover, the RC provides invaluable atomistic insight into the process under study. The optimal RC is the committor, which represents the likelihood of a system to evolve toward a given state based on the coordinates of all its particles. As the interpretability of such a high dimensional function is low, a more practical approach is to describe the RC by some low-dimensional molecular collective variables or order parameters. While several methods can perform this dimensionality reduction, they usually require a preselection of these low-dimension collective variables (CVs). Here, we propose to automate this dimensionality reduction using an extended autoencoder, which maps the input (many CVs) onto a lower-dimensional latent space, which is subsequently used for the reconstruction of the input as well as the prediction of the committor function. As a consequence, the latent space is optimized for both reconstruction and committor prediction and is likely to yield the best non-linear low-dimensional representation of the committor. We test our extended autoencoder model on simple but nontrivial toy systems, as well as extensive molecular simulation data of methane hydrate nucleation. The extended autoencoder model can effectively extract the underlying mechanism of a reaction, make reliable predictions about the committor of a given configuration, and potentially even generate new paths representative for a reaction.
Renormalized site density functional theory for models of ion hydration
Authors: Chuev Gennady N. , Fedotova Marina V. , Valiev Marat
Published: August 2021

The development of accurate statistical mechanics models of molecular liquid systems is a problem of great practical and fundamental importance. Site-density functional theory (SDFT) is one of the promising directions in this area, but its success hinges upon the ability to efficiently reconcile the co-existence of two distinct intra- and inter-molecular interaction regimes in a molecular liquid. The renormalized formulation of SDFT (RSDFT), which we have recently developed, resolves this problem by introducing an additional potential field variable that decouples two interaction scales and maps the molecular liquid problem onto the effective simple liquid mixture. This work provides a critical assessment of RSDFT for the hydrated ion system—a problem that historically has always been one of the most difficult cases for SDFT applications. Using a two-site model of water, we perform a comprehensive analysis of hydrated alkali metal and halogen ions, including both structural and free energy based characteristics. The results indicate that RSDFT provides a significant improvement over conventional three-dimensional reference interaction site model implementations and may prove useful in coarse grained simulations based on two-site solvent models.
Ultra-low thermal conductivity of nanoparticle chains: A nanoparticle based structure for thermoelectric applications
Authors: Henadeera Pasan , Samaraweera Nalaka , Ranasinghe Chathura , Wijewardane Anusha
Published: August 2021

Nanostructured semiconductors are promising candidates for thermoelectric materials owing to their superior thermal insulating properties over their bulk counterparts. In this study, a one-dimensional, crystalline nanostructure synthesized by sintering Si nanoparticles, called Nano Particle Chain (NPC) structures, is proposed. The structure is systematically analyzed for its thermal transport properties and compared with the nanowire counterparts. Both classical molecular dynamics and lattice dynamics tools were employed to evaluate lattice thermal conductivity (k) and to perform phonon mode level decomposition. A marked reduction in the phonon relaxation time of the NPC structure was observed indicating possible effects of phonon-boundary/constriction scatterings. This has resulted in a two-order reduction in k in NPC structures over bulk Si. Further, one order reduction of k of NPC structures was attained with respect to a nanowire of the same constriction size, indicating the effectiveness of the mismatch of particle and constriction diameters as an efficient thermal suppression mechanism. With the addition of a second material of different mass, the NPC structures can be further diversified to core/shell configurations. It was also identified that a non-monotonic variation of k exists, with a minimum in core/shell NPC structures. This effect is materialized by using a Ge-like fictitious material to coat the original Si nanoparticles, owing to competing effects of two phonon suppression mechanisms. Moreover, these core/shell NPC structures are compared with previously reported diameter modulated core/shell nanowire structures [E. Blandre et al., Phys. Rev. B, 91, 115404 (2015)] to highlight their capability to enhance the thermoelectric performance over conventional one-dimensional nanostructure configurations.
A new carnivorous plant lineage (Triantha) with a unique sticky-inflorescence trap
Authors: Lin Qianshi , Ané Cécile , Givnish Thomas J. , Graham Sean W.
Published: August 2021

Significance

Since Darwin’s ground-breaking monograph on carnivorous plants, scientists have recognized only 11 independent origins of plant carnivory. We report the discovery of a new lineage of carnivorous plants, represented by the North American flowering plantTriantha occidentalis. Among monocots,Triantharepresents the only instance of a sticky-trap mechanism and a clearly documented case of holocarnivory, marked by enzymatic secretion consistent with prey digestion. Its trap is unique among carnivorous plants and, unexpected based on theory, in placing all of its prey-capture sites next to its insect-pollinated flowers. Given the existence ofTrianthain close proximity to major urban centers on the Pacific coast, our study serves as a vivid reminder that other cryptic carnivores may yet remain to be discovered.
In situ three-dimensional spider web construction and mechanics
Authors: Su Isabelle , Narayanan Neosha , Logrono Marcos A. , Guo Kai , Bisshop Ally , Mühlethaler Roland , Saraceno Tomás , Buehler Markus J.
Published: August 2021

Significance

Spiders, silks, and webs have survived and prospered for millions of years, making them an evolutionary success. Learning how spiders used their silks and webs to adapt to environmental pressures have fascinated many fields of research such as biomedicine, biology, and engineering. Because of silk’s nanoscale size and the complex web architecture, little is known about the architecture and mechanics of three-dimensional (3D) spider webs during construction. This work comprehensively investigates the structure, mechanics, and functionality of a 3D spider web under construction, using consistent imaging and computational simulations methods. This work could inspire efficient spider-inspired fabrication sequences or fiber geometries in engineered materials, as demonstrated here for 3D-printed prototype materials.
Building behavior does not drive rates of phenotypic evolution in spiders
Authors: Wolff Jonas O. , Wierucka Kaja , Uhl Gabriele , Herberstein Marie E.
Published: August 2021

Do animals set the course for the evolution of their lineage when manipulating their environment? This heavily disputed question is empirically unexplored but critical to interpret phenotypic diversity. Here, we tested whether the macroevolutionary rates of body morphology correlate with the use of built artifacts in a megadiverse clade comprising builders and nonbuilders—spiders. By separating the inferred building-dependent rates from background effects, we found that variation in the evolution of morphology is poorly explained by artifact use. Thus natural selection acting directly on body morphology rather than indirectly via construction behavior is the dominant driver of phenotypic diversity.
Mercury abundance and isotopic composition indicate subaerial volcanism prior to the end-Archean “whiff” of oxygen
Authors: Meixnerová Jana , Blum Joel D. , Johnson Marcus W. , Stüeken Eva E. , Kipp Michael A. , Anbar Ariel D. , Buick Roger
Published: August 2021

Significance

Earth’s atmosphere became oxygenated around 2.4 billion years ago, and this event was preceded by at least one short-lived “whiff” of free O
2
gas nearly 100 million years earlier. The cause of this whiff has so far been difficult to identify. Here, we present mercury concentrations and isotope ratios across the whiff interval and find evidence for significant subaerial volcanism immediately preceding oxygenation. We propose that subaerial weathering of fresh volcanic rocks acted as a fertilizer that stimulated biological productivity and O
2
production in the surface ocean. Our results indicate another strong linkage between planetary magmatic processes and the evolution of Earth’s atmosphere.
A national figure as a memory site: reinterpretations of Ilia Chavchavadze in the 1910s–1940s
Authors: Chkhaidze Irakli , Kakitelashvili Ketevan
Published: August 2021

The paper deals with the multifaceted representation of Georgian public figure Ilia Chavchavadze (1837–1907). Paradoxically, he is treated as a great and gifted son of Georgia by various and sometimes drastically different segments of modern Georgian society. In the framework of memory studies, Ilia is a stunning example of how certain historical figures are manipulated by different regimes to legitimize their power and/or to stake their political claims. For the Soviet regime, he was a fighter for equality and revolutionary changes. By researching different attitudes towards Ilia from the historical perspective and using theories of cultural memory, numerous questions related to controversial interpretations of Ilia Chavchavadze’s activities will be answered. The aim of the given research is to analyze the narrative dynamics surrounding Ilia Chavchavadze’s personality and to analyze the struggle between narratives which ended in the complete triumph of the official policy of memory within a strict ideological framework. We focus on the nature and reasons for the dramatic transformations of Ilia Chavchavadze’s image in different political and social contexts.
GW approximation for open-shell molecules: a first-principles study
Authors: Mansouri Masoud , Casanova David , Koval Peter , Sánchez-Portal Daniel
Published: August 2021

A prerequisite to characterize magnetic materials is the capability to describe systems containing unpaired electrons. In this study, we benchmark the one-shot GW (G
0
W
0) on top of different unrestricted mean-field solutions for open-shell molecules using Dunning’s correlation-consistent basis sets expanded in terms of Gaussian functions. We find that the G
0
W
0 correction to hybrid functionals provides reasonably accurate results for the ionization energies of open-shell systems when compared to those obtained from high-level ab initio methods. Moreover, the quality of the G
0
W
0 exchange–correlation approximation is evaluated by the discrepancy between the ionization energy of the neutral molecules and the electron affinity of the corresponding cations. Furthermore, we assess the capability of the GW to reproduce the correct energy ordering of molecular spin–orbitals. To such an aim, we thoroughly discuss three open-shell molecules CN, NH2, and O2, for which approximate functionals fail to correctly capture the single-electron spectrum. Particularly, we demonstrate that the overestimation of the exchange energy in the studied spin–orbitals is reduced by the GW dynamic correlation term, restoring the molecular orbital ordering. Interestingly, we find that deviations of the exchange and correlation energies, in comparison with our ab initio reference, can be very different for molecular orbitals with different symmetry, e.g. σ and π-type orbitals.
Design and simulation of double-heterojunction solar cells based on Si and GaAs wafers
Authors: Hossain Jaker
Published: August 2021

This article demonstrates the novel designs of Si and GaAs wafer-based double-heterojunction (DH) solar cells using SCAPS-1D simulator. Simple five-layer solar cells are proposed here: cells comprised of a cathode metal layer, three layers of semiconductor materials in the III–V, II–VI and group IV families--and a layer of anode metal. The device structures have been optimized for the analysis of the power-conversion efficiency (PCE) of the Si and GaAs solar cells considering high defect densities at and near each heterojunction. The PCEs predicted are 38% and 38.9% for n-ZnSe/p-Si/p
+-Al0.8Ga0.2Sb and n-ZnSe/p-GaAs/p
+-AlAs0.9Sb0.1 cells, respectively which stay entirely within the PCE limits set by the Shockley–Queisser theory of multi-junction cell. These results reveal that high efficiency and hence cost-effective Si and GaAs wafer-based DH solar cells can be fabricated in the near future.
Aggregate formation in crystalline blends of α-sexithiophene and para-sexiphenyl
Authors: Bhagat Shubham , Leal William D , Majewski Marek B , Simbrunner Josef , Hofer Sebastian , Resel Roland , Salzmann Ingo
Published: August 2021

Earlier reports on rod-like conjugated molecules of similar shape and size such as α-sexithiophene (6T) and para-sexiphenyl (6P) indicated mixed crystal growth in equimolar blends. The spectral overlap between the 6P fluorescence and 6T absorption might there give rise to resonant energy transfer between the two species. In marked contrast to H-type aggregation found for 6T bulk crystals, isolated monolayers of 6T as well as 6T monolayers sandwiched between 6P multilayers have been reported to show pronounced green (instead of red) fluorescence, which has been attributed to J-type aggregation. Here, we investigate whether these altered optical properties of 6T translate from the monolayer to a bulk equimolar blend with 6P. Insight into the mixed crystal structure for vacuum co-deposited films of 6T + 6P is provided by using synchrotron grazing-incidence x-ray diffraction on different substrates. By correlating the optical properties of the pure and the mixed systems using absorption and photoluminescence spectroscopy we identify the green emission known from 6T monolayers to prevail in the blend. Our analysis indicates the formation of aggregates which are promoted by the molecular arrangement in the mixed crystal structure highlighting that the remarkable optical properties of 6T/6P heterostacks translate into mixed crystalline films. This study underlines that tuning the opto-electronic properties of organic semiconductors by blending species of similar shape but distinct opto-electronic properties is a promising pathway to achieve altered material properties.
Relationship Between the Accumulation of Metabolic Syndrome Components and Orthostatic Hypotension
Authors: Cai Xiao-qi , Gao Xin-lei , Wang Ting-jun , Shen Yi-hua , Xu Guo-yan , Han Ying , Xie Liang-di
Published: August 2021

Background

To investigate the relationship between the accumulation of metabolic syndrome (MS) components and orthostatic hypotension (OH).

Methods

A total of 2,201 subjects were enrolled and divided into 0 component (n = 199), 1–2 components (n = 1,003), and 3–4 components (n = 999) groups based on the number of MS components according to the criteria of 2018 Chinese Guidelines for Prevention and Management of Hypertension. Stratified analyses and binary logistic regression analysis were performed.

Results

The incidence of OH was significantly increased with the number of MS components (5.0% in 0 component group, 13.5% in 1–2 components group, and 17.9% in 3–4 components group, P < 0.05). Compared with subjects without OH, the incidence of MS in those with OH was significantly elevated (55.2% vs. 43.7%, P < 0.05). The incidence of OH in the elderly subjects was significantly higher than that in the young and middle-aged subjects (22.3% vs. 10.9%, P < 0.01). Binary logistic regression analysis showed that the number of MS components was associated with OH in all subjects, and the risk of OH was increased with the increment of MS components. Compared with the subjects without any MS component, the risk of OH increased by 2.3 times in the subjects with 4 MS components (odds ratio = 3.274, 95% confidence interval 1.626–6.594, P < 0.05). Stratified analyses found that the number of MS components was independently associated with OH in young to middle-age, female and non-MS subjects.

Conclusions

The incidence of OH is elevated with accumulations of MS components, especially in young to middle-age, female and non-MS subjects.
Molecular cloning and characterization of common marmoset SULT1C subfamily members that catalyze the sulfation of thyroid hormones
Authors: Kurogi Katsuhisa , Manabe Yoko , Liu Ming-Cheh , Suiko Masahito , Sakakibara Yoichi
Published: August 2021

Cytosolic sulfotransferase SULT1C subfamily is one of the most flexible gene subfamilies during mammalian evolution. The physiological functions of SULT1C enzymes still remain to be fully understood. In this study, common marmoset (Callithrix jacchus), a promising primate animal model, was used to investigate the functional relevance of the SULT1C subfamily. Gene database search revealed 3 intact SULT1C genes and a pseudogene in its genome. These 4 genes were named SULT1C1, SULT1C2, SULT1C3P, and SULT1C5, according to the sequence homology and gene location. Since SULT1C5 is the orthologous gene for human SULT1C2P, we propose, here, to revisit the designation of human SULT1C2P to SULT1C5P. Purified recombinant SULT1C enzymes showed sulfating activities toward a variety of xenobiotic compounds and thyroid hormones. Kinetic analysis revealed high catalytic activities of SULT1C1 and SULT1C5 for 3,3′-T2. It appears therefore that SULT1C isoforms may play a role in the thyroid hormone metabolism in common marmoset.
Reading Covered Faces
Authors: Pavlova Marina A , Sokolov Arseny A
Published: August 2021

Covering faces with masks, due to mandatory pandemic safety regulations, we can no longer rely on the habitual daily-life information. This may be thought-provoking for healthy people, but particularly challenging for individuals with neuropsychiatric and neurodevelopmental conditions. Au fait research on reading covered faces reveals that: 1) wearing masks hampers facial affect recognition, though it leaves reliable inferring basic emotional expressions; 2) by buffering facial affect, masks lead to narrowing of emotional spectrum and dampen veridical evaluation of counterparts; 3) masks may affect perceived face attractiveness; 4) covered (either by masks or other veils) faces have a certain signal function introducing perceptual biases and prejudices; 5) reading covered faces is gender- and age-specific, being more challenging for males and more variable even in healthy aging; 6) the hampering effects of masks on social cognition occur over the globe; and 7) reading covered faces is likely to be supported by the large-scale assemblies of the neural circuits far beyond the social brain. Challenges and limitations of ongoing research and parallels to the Reading the Mind in the Eyes Test are assessed. Clarification of how masks affect face reading in the real world, where we deal with dynamic faces and have entrée to additional valuable social signals such as body language, as well as the specificity of neural networks underlying reading covered faces calls for further tailored research.
Functional Connectivity of the Developing Mouse Cortex
Authors: Rahn Rachel M , Brier Lindsey M , Bice Annie R , Reisman Matthew D , Dougherty Joseph D , Culver Joseph P
Published: August 2021

Cross-sectional studies have established a variety of structural, synaptic, and cell physiological changes corresponding to critical periods in cortical development. However, the emergence of functional connectivity (FC) in development has not been fully characterized, and hemodynamic-based measures are vulnerable to any neurovascular coupling changes occurring in parallel. We therefore used optical fluorescence imaging to trace longitudinal calcium FC in the awake, resting-state mouse cortex at 5 developmental timepoints beginning at postnatal day 15 (P15) and ending in early adulthood at P60. Calcium FC displayed coherent functional maps as early as P15, and FC significantly varied in connections between many regions across development, with the developmental trajectory’s shape specific to the functional region. Evaluating 325 seed–seed connections, we found that there was a significant increase in FC between P15 and P22 over the majority of the cortex as well as bilateral connectivity and node degree differences in frontal, motor, and retrosplenial cortices after P22. A rebalancing of inter- and intrahemispheric FC and local-distal FC dominance was also observed during development. This longitudinal developmental calcium FC study therefore provides a resource dataset to the field and identifies periods of dynamic change which cross-sectional studies may target for examination of disease states.
Severe Acute Respiratory Syndrome Coronavirus 2 Viremia Is Associated With Coronavirus Disease 2019 Severity and Predicts Clinical Outcomes
Authors: Jacobs Jana L , Bain William , Naqvi Asma , Staines Brittany , Castanha Priscila M S , Yang Haopu , Boltz Valerie F , Barratt-Boyes Simon , Marques Ernesto T A , Mitchell Stephanie L , Methé Barbara , Olonisakin Tolani F , Haidar Ghady , Burke Thomas W , Petzold Elizabeth , Denny Thomas , Woods Chris W , McVerry Bryan J , Lee Janet S , Watkins Simon C , St Croix Claudette M , Morris Alison , Kearney Mary F , Ladinsky Mark S , Bjorkman Pamela J , Kitsios Georgios D , Mellors John W
Published: August 2021

Background

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral RNA (vRNA) is detected in the bloodstream of some patients with coronavirus disease 2019 (COVID-19), but it is not clear whether this RNAemia reflects viremia (ie, virus particles) and how it relates to host immune responses and outcomes.

Methods

SARS-CoV-2 vRNA was quantified in plasma samples from observational cohorts of 51 COVID-19 patients including 9 outpatients, 19 hospitalized (non–intensive care unit [ICU]), and 23 ICU patients. vRNA levels were compared with cross-sectional indices of COVID-19 severity and prospective clinical outcomes. We used multiple imaging methods to visualize virions in plasma.

Results

SARS-CoV-2 vRNA was detected in plasma of 100%, 52.6%, and 11.1% of ICU, non-ICU, and outpatients, respectively. Virions were detected in plasma pellets using electron tomography and immunostaining. Plasma vRNA levels were significantly higher in ICU > non-ICU > outpatients (P < .0001); for inpatients, plasma vRNA levels were strongly associated with higher World Health Organization (WHO) score at admission (P = .01), maximum WHO score (P = .002), and discharge disposition (P = .004). A plasma vRNA level >6000 copies/mL was strongly associated with mortality (hazard ratio, 10.7). Levels of vRNA were significantly associated with several inflammatory biomarkers (P < .01) but not with plasma neutralizing antibody titers (P = .8).

Conclusions

Visualization of virus particles in plasma indicates that SARS-CoV-2 RNAemia is due, at least in part, to viremia. The levels of SARS-CoV-2 RNAemia correlate strongly with disease severity, patient outcome, and specific inflammatory biomarkers but not with neutralizing antibody titers.
A case report of mass and pressure: the utility of contrast echocardiography
Authors: Sharma Bharti , Kenny Louise , Alphonso Nelson , Anderson Benjamin
Published: August 2021

Background

Diagnostic dilemmas in an unwell neonate can require the use of enhanced imaging modalities, especially in post-operative cardiac disease.

Case summary

A neonate presented a diagnostic challenge following the repair of complex transposition of the great arteries, when an echogenic mass was noted in the region of the left atrial appendage on two-dimensional echocardiography, in the context of a monitoring line (left atrial line) inserted directly through this area. Although the pressure monitoring on this line suggested elevated left atrial pressure, the neonate was clinically and haemodynamically stable. Contrast echocardiography was used to investigate this further and found the mass to be extracardiac.

Conclusion

Contrast echocardiography is a simple and readily available tool for further echocardiographic delineation of structures, although needs to be performed carefully and the results interpreted logically.