bluuebunny/crossref_metadata_2025 huggingface dataset:
Structural diversity of cocrystals formed from acridine and two isomers of hydroxybenzaldehyde: 3-hydroxybenzaldehyde and 4-hydroxybenzaldehyde
Authors: Nowak Patryk , Sikorski Artur
Published: July 2023

Based on experiments carried out using SCXRD, FTIR, and TG/DSC methods, it was demonstrated that acridine forms cocrystals with two isomers of hydroxybenzaldehyde: 3-hydroxybenzaldehyde and 4-hydroxybenzaldehyde in a molar ratio of 1 : 1.
Denitrification activity test of a V modified Mn-based ceramic filter
Authors: Sun Lei , Wang Zhenzhen , Zang Mengxi
Published: July 2023

Vanadium–manganese based ceramic filter (VMA(14)-CCF) with wide active temperature range and good anti-poisoning performance was prepared by V modification.
Effect of lithium doping on the structural, conduction mechanism and dielectric property of MnNbO4
Authors: Aydi Samia , Chkoundali Souad , Oueslati Abderrazek , Aydi Abdelhedi
Published: July 2023

The development of multifunctional materials is an exceptional research area, which is aimed at enhancing the versatility of materials according to their wide fields of application.
Ammonolytic transfer dehydrogenation of amines and amides: a versatile method to valorize nitrogen compounds to nitriles
Authors: Coeck Robin , Houbrechts Margot , De Vos Dirk E.
Published: July 2023

The ammonolytic transfer dehydrogenation of amines has been identified as an efficient method for nitrile synthesis.
Photoluminescent supramolecular gels derived from phenylenediamine hydrochlorides
Authors: Tateishi Kazuki , Tada Tomoya , Sotani Taichi , Suzuki Takeyuki , Sogawa Hiromitsu , Sanda Fumio
Published: July 2023

N-(3,5-Diaminobenzoyl)-l-alanine dodecyl ester dihydrochlorides underwent gelation in tetrahydrofuran and CHCl3. The gel emitted blue fluorescence in the sol state and green fluorescence in the gel state.
High ionic conducting rare-earth silicate electrolytes for sodium metal batteries
Authors: Sivakumaran Abinaya , Samson Alfred Junio , Bristi Afshana Afroj , Surendran Vishnu , Butler Shantel , Reid Samuel , Thangadurai Venkataraman
Published: July 2023

Sodium gadolinium silicate solid electrolyte showed an outstanding sodium plating/stripping performance for 1000 cycles that proves excellent interfacial contact between the sodium anode and solid electrolyte.
Distributed finite‐time control with event triggered mechanism for multi‐agent systems under fixed and switching topologies
Authors: Lv Hui , Li Shibo , Chen Yadong , Hu Guolin , Zheng Wenjing
Published: July 2023

This paper addresses the problem of distributed finite‐time (FT) event‐triggered consensus of multi‐agent systems (MASs) under fixed and switching topologies. To conserve the limited communication resources, a new distributed event‐triggered control protocol is proposed, in which the agents exchange information via discontinuous communication among the follower agents. Then, to solve the FT consensus problem, norm‐normalized sign functions are employed, and sufficient Lyapunov conditions are provided. On this basis, the MASs proves capable of reaching consensus within finite time under fixed and switching topologies. Finally, the effectiveness of the developed algorithm is verified via numerical simulation.
A hierarchical multi‐area capacity planning model considering configuration ratios of renewable energy and energy storage systems with multi‐area coordination
Authors: Li Qingtao , Wang Jianxue , Chen Jie , Ding Tao , Gu Chenjia
Published: July 2023

The continuous growth of renewable energy sources (RESs) has increased the demand for flexibility in managing uncertainties of RES generation. Energy storage systems (ESSs) are recognized as one of the promising methods to address this challenge. For multi‐area power system planning problems, capacity allocations of RESs can vary considerably among areas accounting for the geographic diversities in RES generation and load patterns. This paper presents a hierarchical coordinated planning model considering the interaction of local‐area (LA) planning entities and the system‐wide (SW) planner. A novel multi‐objective LA planning model is proposed to compute optimal capacity configuration ratios of RESs and ESSs based on regional resource characteristics. The SW planner acts as a coordinator and further optimizes specific capacities of generation assets. Optimal configuration ratios produced by LA planning entities are important indices reflecting LA planning preferences and serve as a link between the two planning layers. Numerical results on a modified NREL‐118 test system show that the proposed planning model can reduce carbon emission by an average of 10.5% and improve the RES utilization rate by an average of 1.8% compared with planning models without considering configuration ratios and ESS installations.
The role of plasma β in global coronal models: Bringing balance back to the force
Authors: Brchnelova M. , Kuźma B. , Zhang F. , Lani A. , Poedts S.
Published: July 2023

Context. COolfluid COrona uNstrUcTured (COCONUT) is a global coronal magnetohydrodynamic (MHD) model that was recently developed and will soon be integrated into the ESA Virtual Space Weather Modelling Centre (VSWMC). In order to achieve robustness and fast convergence to a steady state for numerical simulations with COCONUT, several assumptions and simplifications were made during its development, such as prescribing filtered photospheric magnetic maps to represent the magnetic field conditions in the lower corona. This filtering leads to smoothing and lower magnetic field values at the inner boundary (i.e. the solar surface), resulting in an unrealistically high plasma β (greater than 1 in a large portion of the domain).

Aims. We aim to examine the effects of prescribing such filtered magnetograms in global coronal simulations and formulate a method for achieving more realistic plasma β values and improving the resolution of electromagnetic features without losing computational performance.

Methods. We made use of the newly developed COCONUT solver to demonstrate the effects of the highly pre-processed magnetic maps set at the inner boundary and the resulting high plasma β on the features in the computational domain. Then, in our new approach, we shifted the inner boundary to 2 R⊙ from the original 1.01 R⊙ and preserved the prescribed highly filtered magnetic map. With the shifted boundary, the boundary density and pressure were also naturally adjusted to better represent the considered physical location. This effectively reduces the prescribed plasma β and leads to a more realistic setup. The method was applied on a magnetic dipole, a minimum (2008) and a maximum (2012) solar activity case, to demonstrate its effects.

Results. The results obtained with the proposed approach show significant improvements in the resolved density and radial velocity profiles, and far more realistic values of the plasma β at the boundary and inside the computational domain. This is also demonstrated via synthetic white light imaging (WLI) and with the validation against tomography data. The computational performance comparison shows similar convergence to a limit residual on the same grid when compared to the original setup. Considering that the grid can be further coarsened with this new setup, as its capacity to resolve features or structures is superior, the operational performance can be additionally increased if needed.

Conclusions. The newly developed method is thus deemed as a good potential replacement of the original setup for operational purposes, providing higher physical detail of the resolved profiles while preserving a good convergence and robustness of the solver.
ViT VO - A Visual Odometry technique Using CNN-Transformer Hybrid Architecture
Authors: B Jayaraj P. , J Ebin , R Karthik , P N Pournami
Published: July 2023

Localization is one of the main tasks involved in the operation of autonomous agents (e.g., vehicle, robot etc.). It allows them to be able to track their paths and properly detect and avoid obstacles. Visual Odometry (VO) is one of the techniques used for agent localization. VO involves estimating the motion of an agent using the images taken by cameras attached to it. Conventional VO algorithms require specific workarounds for challenges posed by the working environment and the captured sensor data. On the other hand, Deep Learning approaches have shown tremendous efficiency and accuracy in tasks that require high degree of adaptability and scalability. In this work, a novel deep learning model is proposed to perform VO tasks for space robotic applications. The model consists of an optical flow estimation module which abstracts away scene-specific details from the input video sequence and produces an intermediate representation. The CNN module which follows next learn relative poses from the optical flow estimates. The final module is a state-of-the-art Vision Transformer, which learn absolute pose from the relative pose learnt by the CNN module. The model is trained on the KITTI dataset and has obtained a promising accuracy of approximately 2%. It has outperformed the baseline model, MagicVO, in a few sequences in the dataset.
Procrastination Preventor using YOLO
Authors: Jaybhaye Sangita , Patil Saraswati , Loya Riya , Rokade Tejas , Shirodkar Sahil , Suryawanshi Snehal
Published: July 2023

According to research, procrastination is a frequent and damaging type of self-regulation failure. With so many deadlines and pressure to complete their work, students struggle with academic procrastination. As a result, even feeling unwell can delay coursework and affect academic progress. Not even Students do procrastinate as if they have to do something, employees and other people do the same. This delay affects many things. It affects our mental health and leads to stressful lives. To reduce this procrastination, a software model is developed called “Procrastination Preventer using YOLO” that helps to avoid procrastination, reduce stress and help complete a specific task on time. This model also has a pomodoro timer which will also help in managing time efficiently. The intriguing thing about it is that, it has integrated text-to-speech technology. It means that in addition to notifying the user by displaying the text, the timer will also verbally announce it at the same time. This model is built using Python, Jupyter Notebook, OpenCV, Pomodoro timer, Text to Speech converter.
Improving Software Modularity Using Software Remodularization: Challenges and Opportunities
Authors: Naveen  , Singh Randeep , Rathee Amit
Published: July 2023

Long-period maintenance of software often causes the original program modularization to decay, resulting in a degraded quality of the software. Placement of software artifacts, namely code files or classes in a suboptimal manner among software packages is one of the most common causes of this decaying modularization of software. Software remodularization (remodularization) is an old reverse engineering approach that helps in alleviating this issue by improving the quality of software modularization. However, in literature, a multitude of software remodularization approaches exists leaving researchers and developers in a dilemma of choosing appropriate remodularization criteria. Therefore, this paper carries out a Systematic Literature Review (SLR) of the last two decades and presents concise information by answering different relevant research questions important to both developers and researchers of this field. This paper considers 54 research articles as primary studies.
Applications of CNN in leaf diseases: A critical survey
Authors: Satyanarayana L.V. , Chandrasekhar Rao D.
Published: July 2023

Crop diseases can significantly impact crop yield and overall productivity, posing challenges for farmers in increasing output and market prices. Early detection of these diseases is crucial for preventing further spread and reducing their impact. To overcome this, researchers have utilized image processing technology, including deep learning techniques such as convolutional neural networks (CNNs), to detect crop diseases. In this critical survey, we provide a comprehensive review of recent studies and developments in the use of CNNs for identifying leaf diseases in agricultural plants. We discuss the benefits and drawbacks of different deep learning techniques and image processing methods for disease diagnosis and management in agriculture. Our research highlights the potential of CNNs and deep learning to significantly advance the field of agricultural research and development. We also analyze the factors affecting the outcomes of each technique, including the accuracy, precision. Our study emphasizes the need for further research and development to optimize the use of CNNs in agricultural applications, particularly for improving disease management and crop productivity.
Enhancing Performance of End-to-End Gujarati Language ASR using combination of Integrated Feature Extraction and Improved Spell Corrector Algorithm
Authors: Bhagat Bhavesh , Dua Mohit
Published: July 2023

A number of intricate deep learning architectures for effective End-to-End (E2E) speech recognition systems have emerged due to recent advancements in algorithms and technical resources. The proposed work develops an ASR system for the publicly accessible dataset on Gujarati language. The approach provided in this research combines features like Mel frequency Cepstral Coefficients (MFCC) and Constant Q Cepstral Coefficients (CQCC) at front-end feature extraction methodologies. Enhanced spell corrector with BERT-based algorithm and Gated Recurrent Units (GRU) based DeepSpeech2 architecture are used to implement the back end portion of the proposed ASR system. The proposed study shown that combining the MFCC features and CQCC features extracted from speech with the GRU-based DeepSpeech2 model and the upgraded or enhanced spell corrector improves the Word Error Rate (WER) by 17.46% when compared to the model without post processing.
Simulated uav dataset for object detection
Authors: Sama Avinash Kaur , Sharma Akashdeep
Published: July 2023

Unmanned Aerial Vehicles (UAVs) have become increasingly popular for various applications, including object detection. Novel detector algorithms require large datasets to improve, as they are still evolving. Additionally, in countries with restrictive drone policies, simulated datasets can provide a cost-effective and efficient alternative to real-world datasets for researchers to develop and test their algorithms in a safe and controlled environment. To address this, we propose a simulated dataset for object detection through a Gazebo simulator that covers both indoor and outdoor environments. The dataset consists of 11,103 annotated frames with 27,412 annotations, of persons and cars as the objects of interest. This dataset can be used to evaluate detector proposals for object detection, providing a valuable resource for researchers in the field. The dataset is annotated using the Dark Label software, which is a popular tool for object annotation. Additionally, we assessed the dataset’s performance using advanced object detection systems, with YOLOv3 achieving 86.9 mAP50-95, YOLOv3-tiny achieving 79.5 mAP50-95, YOLOv5 achieving 82.2 mAP50-95, YOLOv7 achieving 61.8 mAP50-95 and YOLOv8 achieving 87.8 mAP50-95. Overall, this simulated dataset is a valuable resource for researchers working in the field of object detection.
Myxozoan survey of thicklip grey mulletChelon labrosusreinforces successful radiation ofMyxobolusin mugiliform hosts
Authors: Guimarães José , Casal Graça , Alves Ângela , Araújo Catarina , Rocha Sónia
Published: July 2023

A myxozoan survey was performed on specimens of thicklip grey mulletChelon labrosus(Risso) captured from the Douro River estuary, northern Portugal. Eleven new species, all belonging to the genusMyxobolusBütschli, 1882 (M. abdominalisn. sp.,M. aestuariumn. sp.,M. caudalisn. sp.,M. chelonarin. sp.,M. cucurbitiformisn. sp.,M. douroensisn. sp.,M. intestinicolan. sp.,M. invictusn. sp.,M. labicolan. sp.,M. peritonaein. sp., andM. pinnulan. sp.) are described based on microscopic and molecular data, confirming the known high radiation of these myxozoans in mullets. Additionally,Myxobolus pupkoiGuptaet al., 2022 is reported for the first time fromC. labrosus, bringing forth a novel case of morphological plasticity between geographic isolates. We consider that molecular-based comparisons are imperative for the description of mugiliform-infectingMyxobolus, with distance estimation further matching two of the novelMyxobolusspp. with sphaeractinomyxon types previously reported from another Portuguese estuary. This finding supports sphaeractinomyxon as specific life cycle counterparts ofMyxobolusthat infect mullets. Phylogenetic analyses of 18S rDNA retrieved a monophyletic clade of mugiliform-infecting myxobolids comprising well-supported lineages of species parasitizing mullets from the generaChelon,Mugil,Crenimugil, andPlaniliza. The existence of more than oneChelon- andPlaniliza-infecting lineage reveals that myxobolids parasitized members of these genera multiple times during their evolution. Lastly, the elevated number of unmatched sphaeractinomyxon sequences included in theChelon-infecting lineages clearly shows thatMyxobolusdiversity hosted by this genus remains underrated.
4 Schulen der Iridologie
Authors: Biechele Hermann , Jahn Claus
Published: July 2023

Die Autoren geben einen Überblick über 4 Schulen der Iridologie
Diverse and vulnerable: experiences of private allied health practices managing through the coronavirus (COVID-19) pandemic. Implications for the financial viability of Australian primary care
Authors: Petrozzi M. John , Wright Michael , Hoffman Rebekah , Goodger Brendan , Wise Sarah
Published: July 2023

Background The majority of allied health services are delivered by small, private practices in the primary care setting with limited government funding. During the coronavirus disease 2019 (COVID-19) lockdowns these practices were subject to the same health orders as any other private business with only ‘essential services’ permitted to remain open. Research aim We set out to understand the impact of the COVID-19 pandemic, and associated public health measures, on the financial viability of private allied health practices. Methods Thirteen semi-structured interviews were conducted with primary care allied health practice owners and managers in Sydney. Data were analysed thematically. Findings All of the interviewees reported experiencing the stress of balancing precarious finances caused by reduced and/or fluctuating patient demand. Patients’ reluctance to seek care was compounded by ambiguity around whether allied health services were ‘essential’. Manual therapies were particularly vulnerable to financial stress because their capacity to transition to telehealth and access to government funding were limited. Conversely, psychologists reported demand for their services exceeded what they could provide. Study implications The findings are indicative of primary care allied health’s peripheral status in Australia’s primary care landscape. Greater priority to the funding and integration of primary care allied health is needed in primary care policy.
DNA-binding, multivalent interactions and phase separation in transcriptional activation
Authors: Smith Ngaio C. , Matthews Jacqueline M.
Published: July 2023

Transcription is an essential process in biology whereby gene-specific transcription factors target sites on DNA to recruit the basal transcription machinery that will produce messenger RNA (mRNA). It is a highly regulated multi-step process that involves many proteins and protein complexes. Transcription factors, the proteins that mark genes for activation, and other transcriptional regulators are highly enriched in low-complexity disordered regions, which are strongly linked to multivalent binding and phase separation. These disordered regions can form multivalent dynamic complexes that are essential for many aspects of transcription. Many of these proteins can phase separate in vitro and show evidence of phase separation in vivo. Whether these interactions represent biologically relevant phase separation in vivo is controversial. However, what these events do demonstrate is that many transcriptional proteins co-cluster with other factors in vivo, forming multivalent dynamic clusters that contribute to transcriptional events. We review some of these recently investigated events and consider how they contribute to our understanding of transcription.
Is the laboratory report dead? AI and ChatGPT
Authors: Wang Jack T. H.
Published: July 2023

The launch of ChatGPT and artificial intelligence (AI) platforms capable of generating written responses to a vast range of text-based queries has transformed the conceptualisation of assessment in education. Apart from its potential for misuse in test and examinations, the laboratory report in Science Education may be vulnerable to AI-disruption. This article outlines five text-based prompts that educators can use to assess the quality of AI-generated output in scientific writing. When used to query the freely accessible version of ChatGPT (GPT-3.5) in June 2023, these prompts revealed its ability to produce written work that showcases high-level organisation of concepts relevant to a scientific topic. However, these AI-generated responses remain generalised, lacking specificity and without effective integration of peer-reviewed scientific literature. As these generative AI platforms continue to improve, educators can use this series of prompts to evaluate the quality of AI output and adapt the assessment criteria for this new era in scientific writing.
Extremely low-frequency electromagnetic field exposure alters DNA methylation levels in the endometrium of pigs during the peri-implantation period
Authors: Wydorski Pawel Jozef , Kozlowska Wiktoria , Drzewiecka Ewa Monika , Zmijewska Agata , Franczak Anita
Published: July 2023

Context Extremely low-frequency electromagnetic field (ELF-EMF) emission is increasing due to substantial technological progress. The results of previous research provided evidence that ELF-EMF may exert changes in molecular mechanisms that control female reproduction. Aims We hypothesised that short-term ELF-EMF treatment alters the DNA methylation level of genes in the endometrium. Hence, the research aimed to determine the methylation level of selected genes whose expression was altered in response to ELF-EMF radiation in the endometrium of pigs during the peri-implantation period (days 15–16 of pregnancy). Methods Porcine endometrial slices (100 ± 5 mg) were collected during the peri-implantation period and exposed to ELF-EMF at a frequency of 50 Hz for 2 h in vitro. The control endometrium was not exposed to ELF-EMF. The level of DNA methylation in the promoter regions of EGR2, HSD17B2, ID2, IL1RAP, MRAP2, NOS3, PTGER4, SERPINE1, VDR and ZFP57 was tested using qMS-PCR. Key results In the endometrium exposed to ELF-EMF, the level of methylation of HSD17B2, MRAP2, SERPINE1, VDR and ZFP57 was not altered; the level of methylation of EGR2, ID2 and PTGER4 increased, and the level of methylation of IL1RAP and NOS3 decreased. Conclusions ELF-EMF may alter the level of DNA methylation in the endometrium during the peri-implantation period. Implications Changes in the DNA methylation induced by ELF-EMF may affect the transcriptomic profile of the endometrium and disturb physiological processes accompanying implantation and embryo development.
“I want my children to become global citizens”
Authors: Joo Sun Jung , Chik Alice , Djonov Emilia
Published: July 2023

Increasing globalisation has spurred a flow of migrants worldwide. These movements include exchanges of migrants’ linguistic repertoires across regions, transforming the ways in which they define themselves in a multilingual society. Unlike identity categories such as ethnic identity, the contested concept of citizenship identity has remained underexplored in heritage language (HL) research. Focusing on Korean migrant families in Australia, this study extends the limited knowledge about the roles of citizenship in HL maintenance across different generations. Specifically, drawing on interviews with six Korean-speaking parents and their children, this study compares the ways in which migrant parents and their primary and secondary school-aged children relate a HL to their citizenship status. Thematic analysis reveals that while HL-speaking children tend to associate their language with national or ethnic identities, migrant parents are more likely to identify their children as global citizens whose HL competencies are essential for their future career and economic advantage. The study contributes to scholarship at the intersection of HL, citizenship, and globalisation.
Anthropomorphism, anthropocentrism, and human-orientation in environmental discourse
Authors: Schmitt Casey R.
Published: July 2023

This article surveys and reflects upon the influence of anthropomorphism in environmental and sustainability discourses. It summarizes key perspectives on and tensions surrounding anthropomorphizing rhetorics, ultimately arguing that such rhetorics need not be anthropocentric. The article first defines core concepts and terminology, including anthropomorphism and anthropocentrism. It then provides an ideological history of environmental communication’s tension between humanism and more-than-humanism, highlighting the role of communication and symbolism in shaping (or constraining) perspectives and making a case for a middle path of human-oriented (rather than human-centered) appeals, before concluding with recommendations for future work.
Modal particles in ironic utterances
Authors: Härtl Holden , Thimm Jana-Maria
Published: July 2023

This study contributes to theorizing about the semantic characteristics of verbal irony. Specifically, we
investigate the function of the modal particles ja (lit. ‘yes’) and aber (lit. ‘but’) that often
occur in ironic utterances in German, cf. Das war aber ein aufregender Film (‘That was prt a thrilling
movie’). Our main claim is that modal particles are used in ironic utterances to reflect the speaker’s intention to pretend
surprise and produce a mockery effect by manifesting the utterance as an echo. Modal particles require some mutual knowledge to be
contained in the common ground, and we link this notion to the interplay between echoic mention and pretense in interpreting an
utterance as ironic. In an empirical approach to our claim, we report on results from an online questionnaire study, in which we
test whether the presence of a modal particle leads to a higher perception of pretense in ironic reactions. While the data
generally confirm our prediction, we found that only aber affects pretense perception but not
ja, which can be explained by the former’s contrastive nature. The view we pursue implies that attitudinal
content is a graded feature and that such a notion is applicable to surprise and pretense involved in verbal irony.
Morphology transformation of stainless steel 316L powder from spheres to flakes using high-energy ball milling and the investigation of transformation behaviour
Authors: Lee Dong Hoon , Han Seungheon , Park Man-Ho , Yun Jung-Yeul , Ji Myeongjun , Lee Young-In
Published: July 2023

Today, microfiltration plays the most significant role in removing fine particulate impurities in gas streams used in high-tech industries. However, the current SS316L gas filter has a limitation in enhancing performance due to the trade-off relationship between filterability and permeability. This limitation can be overcome by the geometrical effect of the gas filter that maximises inertial impaction and diffusion interception due to complex flow channels using small flake particles. However, since the smaller the particle size, the yield strength higher, there are few reports of preparing the small flake particles by plastic deformation. This study used a high-energy ball milling process to demonstrate the preparation method for small stainless steel 316L flake particles. Furthermore, the process parameters are systematically optimised to fully transform the spherical particles into thin platelets without fracture and cold welding, and the transformation behaviour is discussed in detail.
Design and analysis of a photonic crystal-based biosensor for the detection of chikungunya virus
Authors: Gowdhami D , Balaji V R
Published: July 2023

A two-dimensional photonic crystal biosensor is theoretically demonstrated and investigated based on refractive index sensing. It detects the chikungunya virus (CHIKV) in the various blood components with high sensitivity of 421.5 nm/RIU. Simulation and various analyses are done with both normal and infected blood constituents (uric acid, platelets and plasma) to detect CHIKV. The sensor operates within the wavelength range of 1230–1560 nm. The important optical parameters such as sensitivity and quality factor are analyzed and numerical investigations are done with the finite difference time domain method. The sensor is built with a circular array of holes etched on a silicon slab in a hexagonal lattice pattern. A nanohole resonant sensing cavity is placed at the center of two waveguides, enhancing the light–matter interaction of the analyte and trapping the optical mode at the nanohole of the sensor. When the sensor is completely submerged in blood constituents infected with CHIKV (plasma, platelets and uric acid), the resonating modes undergo a shift as the refractive index of each analyte is unique. The sensor has a very high sensitivity of 421.5 nm RIU−1, and a good quality factor of 229.68 for the different blood constituents is obtained. A maximum transmission of 89.25% with a detection limit of 0.01 are obtained and reported in this work.
New wormhole model with quasi-periodic oscillations exhibiting conformal motion in
f(,T)
gravity
Authors: Mustafa G , Errehymy Abdelghani , Maurya S K , Jan Munsif
Published: July 2023

This analysis explores the new wormhole (WH) solution in the background of teleparallel gravity with minimal matter coupling. To complete this study, we consider the conformal symmetry with non-zero Killing vectors. The exact shape function is computed by considering the linear equation of state with the phantom regime. The energy conditions are investigated for the calculated shape function with the equation of state parameter. The presence of exotic matter is confirmed due to the violation of the null energy condition. The current study also explores the physical properties of the epicyclic frequencies with quasi-periodic oscillations. In the astrophysical, epicyclic frequencies are extensively employed to explore the self-gravitating system. It is concluded that a stable WH solution is acceptable for WH geometry.
Machine learning based priors for Bayesian inversion in MR imaging
Authors: Marschall Manuel , Wübbeler Gerd , Schmähling Franko , Elster Clemens
Published: July 2023

The Bayesian approach allows the incorporation of informative prior knowledge to effectively enable and improve the solution of inverse problems. Obtaining prior information in probabilistic terms is, however, a challenging task. Recently, machine learning has been applied for the training of generative models to facilitate the translation of historically or otherwise available data to a prior distribution. In this work, we apply this methodology to undersampled magnetic resonance imaging. In particular, we employ an autoencoder as part of a generative model to statistically regularise and solve the high-dimensional inverse problem using Bayesian inversion. Comparison with a classical Gaussian Markov random field prior is performed and numerical examples highlight the possible advantages of data-driven priors.
Integrability of planar-algebraic models
Authors: Poncini Xavier , Rasmussen Jørgen
Published: July 2023

The quantum inverse scattering method is a scheme for solving integrable models in

1
+
1

dimensions, building on an R-matrix that satisfies the Yang–Baxter equation (YBE) and in terms of which one constructs a commuting family of transfer matrices. In the standard formulation, this R-matrix acts on a tensor product of vector spaces. Here, we relax this tensorial property and develop a framework for describing and analysing integrable models based on planar algebras, allowing non-separable R-operators satisfying generalised YBEs. We also re-evaluate the notion of integrals of motion and characterise when an (algebraic) transfer operator is polynomial in a single integral of motion. We refer to such models as polynomially integrable. In an eight-vertex model, we demonstrate that the corresponding transfer operator is polynomial in the natural Hamiltonian. In the Temperley–Lieb loop model with loop fugacity

β
∈

C

, we likewise find that, for all but finitely many β-values, the transfer operator is polynomial in the usual Hamiltonian element of the Temperley–Lieb algebra

T
L

n

(
β
)

, at least for

n
⩽
17

. Moreover, we find that this model admits a second canonical Hamiltonian, and that this Hamiltonian also acts as a polynomial integrability generator for small n and all but finitely many β-values.
Design and Implementation of the Simulated EEPROM for the SFP56 Optical Module
Authors: Dou Hu
Published: July 2023

There is usually no EEPROM in MCU, and EEPROM inside the SFP56 optical module is usually implemented by MCU and EEPROM chip, which not only increases the cost but also occupies the PCB area. To solve the above problems, I2C peripheral, FLASH, and RAM are used to implement the simulated EEPROM. Aiming at the difference between EEPROM and FLASH, a RAM + FLASH method is proposed to implement the simulated EEPROM. The results show that the simulated EEPROM can meet the writing and reading byte time of the EEPROM stipulated by the SFF-8431 protocol. The simulated EEPROM not only saves PCB area but also reduces SFP56 optical module cost.
Design of DSP-Based Reactive Power Compensation Controller
Authors: Shen Jiuzhi , Qiu Bingjun , Fu Zhifang , Chen Naichao
Published: July 2023

The DSPTMS320F28335, which is utilized as the main control chip, aims to measure the system power factor and current voltage, control the switching capacitor, improve the accuracy of the capacity of the switching capacitor and reduce the regulation time. The hardware circuit of the system is designed and the experimental model is built. According to the experimental results, the reactive power compensation controller with DSP as the main control chip can quickly compensate the power factor to more than 0.9 even under the condition of load change and harmonic influence.
A Design Method for Controlling the Safe Distance of Convolution Image Recognition Based on FPGA
Authors: Li Bingkun , Zhao Xinxin , Wei Chaofei , Li Lele , Wang Shuai , Jiang Kai
Published: July 2023

This is an FPGA-based image recognition system. It is built on the FPGA-SOC platform, which uses less power and operates more quickly. This method can be used to remind people inside to maintain a safe distance to stop the coronavirus from spreading. The system can ensure a high accuracy rate and identification speed. At the same time, the system detects the safe distance and issues pertinent prompts according to the training of the private data set. Finally, the system’s implementation is appropriate for tiny IoT devices with extremely low power consumption. The system is implemented by utilizing a custom CPU on an FPGA. The RISC-V architecture used in the self-developed CPU allows for 32-bit embedded CPU performance and operating effectiveness at the expense of an 8-bit CPU. An HD camera and an infrared camera that work together are put on it. The upgraded Tiny YOLO2 algorithm in the CPU can help the infrared camera process the HD camera’s data and perform recognition and judgments. Finally, it is possible to implement data collection based on 720p resolution, which precisely determines whether the direct distance between individuals is a safe distance and then sends the appropriate reminders. Its power usage is 1.3 W. It can address the issue of preventing epidemics and the security risks brought on by a large population density in public areas.
Simulation and Research of Railway Foreign Body Invasion System Based on Single Chip Microcomputer
Authors: He Zhengyi , Li Ningzhou , Wei Xiaojuan
Published: July 2023

With the accelerating growth of railway operating mileage in China, ensuring the safety of railway operations has become a critical problem. According to some previous studies, the railway foreign body invasion limit is a major threat to the safe operation of the railway. As the current stage mainly adopts the combination of manual inspection and video monitoring, it has some disadvantages, such as being time-consuming, laborious, and inefficient. Meanwhile, it cannot timely detect potential danger. Therefore, the research on the simulation of railway foreign body intrusion systems based on single-chip microcomputers is carried out. The program is compiled in C language and uses the microcontroller to achieve real-time foreign object detection and alarm for encroachment. This paper mainly introduces the principle of the system and uses Proteus software to design and simulate the circuit. Last but not least, welding is carried out according to the circuit diagram, and the physical test is carried out to verify the feasibility of the design.
Research on Reducing the Overall Reflectivity of the Electric Wave Anechoic Chamber
Authors: He Zibin , Xing Hao , Zhang Huiru , Song Deqiang , Song Shujuan , Wu Mengjuan , Chen Quan , Wang Heying
Published: July 2023

In this paper, a cylindrical trimming method is applied to fit the hemisphere, and the total reflectivity on a certain boundary is analyzed through a series of derivations and calculations. An equation that is used to calculate the reflectivity of the trimming cylindrical anechoic chamber is obtained, and obviously, it has no relationship with the spherical coordinate radius r and can be utilized to optimize the trimming size. The proposed scheme of the non-standard anechoic chamber is proved to be a simplified and effective way to optimize the anechoic chamber. An anechoic chamber is constructed to illustrate the correctness of the theory. The simulation results show that S
11 has achieved good results in most frequency bands.
Design of Pairing Mechanisms for the Device-to-Device Communication System
Authors: Ma Lizhi , Liu Guangyu , Liu Shuo
Published: July 2023

The potential of device-to-device (D2D) communication lies in improving system performance and user experience. Thus, D2D communication is widely concerned. For the D2D communication system, this work investigates the D2D pairing problem to maximize the sum rate of all D2D pairs. To comprehensively compare the performance of different algorithms, three pairing mechanisms are proposed based on the graph theory and the matching theory. The simulation results show the impact of the network scale on the optimized results. And for small and large network scales, the Hungary algorithm and the minimum distance matching algorithm are selected as the D2D pairing mechanism, respectively.
Maximum Exposure Evaluation for MIMO Based on Optimization Algorithm
Authors: Zhang Xuejun , Zhou Yinfeng , Li Huirong
Published: July 2023

IEC/IEEE FDIS 63195-2 requires the maximum exposure evaluation to determine if the product meets the radiation limit requirements specified by ICNIRP. The miniaturization and integration of millimeter wave antennas make it possible to deploy antenna arrays supporting Multiple-Input Multiple-Output (MIMO) technology in mobile terminals, which brings challenges to traditional exposure compliance testing. This is caused by the complex electromagnetic environment generated around the equipment by beam focusing technology and the difficulty in determining the maximum exposure of electromagnetic exposure dose by traditional measurement methods. However, mathematical model-based evaluation methods may produce overly conservative results, limiting the maximum allowable transmit power of 5G devices and resulting in wasted system performance. In this study, we take advantage of the optimization algorithm in searching for globally optimal solutions under multivariate constraints, and its search strategy is improved to evaluate the largest exposure of millimeter wave MIMO antenna arrays in the target region.
Background reduction in PET by double Compton scattering of quantum entangled annihilation photons
Authors: Kim Donghwan , Rachman Agus Nur , Taisei Ueki , Uenomachi Mizuki , Shimazoe Kenji , Takahashi Hiroyuki
Published: July 2023

The reduction of background events, such as random and scatter events, can improve
positron emission tomography (PET) images quantitatively. The quantum entanglement property of
annihilation photons has been theoretically studied and experimentally validated. Recently,
simulation studies on PET image reconstruction using the quantum entanglement property of
annihilation photons and studies on the measurement of entanglement and polarization properties
with scintillation crystal arrays demonstrated that PET images with less background can be
achieved. This study utilized the quantum entanglement property of annihilation photons
in a typical PET system with block detectors. A data acquisition method for
quantum entanglement PET (QEPET) and system response modelling for QEPET image reconstruction were
proposed and implemented. An experimental study was conducted using a small animal PET system
composed of Ce:GAGG scintillation crystals whose dimensions are 2.5 × 2.5 ×
4mm3. The diameter of the system was 79.3 mm. Signals from all individual
crystals were processed parallelly and independently; thus, Compton scatter and absorption
crystals within a module were obtained directly. The 28 MBq experiment result revealed the random
background ratio of QEPET was approximately 20% lower than that of PET and the count rate of
QEPET was approximately 0.1% that of PET. Evaluation on reconstructed images from the 28 MBq
experiment revealed that the signal-to-background ratio of QEPET was approximately two times
better than that of PET while the signal-to-noise ratio of QEPET was about 77% of that of
PET. The method proposed in this study is expected to improve PET images with high background,
such as those with a high activity and high background gamma rays and improve range verification
in proton therapy.
Parametrization of electron sheath expansion for Langmuir probe I-V traces
Authors: Jin Chenyao , Yip Chi-Shung , Ghim Young-chul , Zhang Wei , Jiang Di , Xu Guo Sheng
Published: July 2023

The Langmuir probe is a common plasma diagnostic widely
utilized in various fields of plasma physics, and its associated
methods of data analysis remains in active development. In this
work, we present an attempt using a power law parametrization model
similar to Sheridan's empirical formulation is to describe the
sheath expansion effect on electron current in an argon plasma. The
fitting results using the power law parametrization method show
observably better consistency compared to those using conventional
interception method and inflection method. It is also observed that
when used to fit the electron saturation current at probe bias
voltages well beyond the plasma potential plus the argon ionization
energy, resultant curve fitted by power law parametrization, as with
that by linear fitting, deviates significantly from the curve fitted
at lower bias voltages, albeit the saturation obtained fitted using
the power law method remained consistent with that fitted at lower
probe bias voltages. Probable causes of this deviation include anode
glow or spots near the probe and the changes of the global plasma
parameters via electron absorption at very high probe bias. The fact
that the resultant electron saturation current remained consistent
hints that these non-trival effects can also be approximated by
power law parametrization.
SiPM signal processing via multiple linear regression
Authors: Schmailzl Wolfgang , Piemonte Claudio , Garutti Erika , Hansch Walter
Published: July 2023

This paper presents a novel approach using multiple linear regression to process transient signals from silicon photomultipliers.
The method provides excellent noise suppression and pulse detection in scenarios with a high pulse count rate and superimposed pulses.
Insights into its implementation and benchmark results are presented.
We also show how this approach can be used to automatically detect the pulse shape from a given transient signal, providing good detection for count rates up to 90 MHz.
Experimental data are used to present an application where this algorithm improves charge spectrum resolution by an order of magnitude.
Performance comparison of water Cherenkov detectors with different geometries
Authors: Bisconti F. , Chiavassa A.
Published: July 2023

In the framework of the development of the SWGO experiment,
we have performed a detailed study of the single unit of an
extensive air shower observatory based on an array of water
Cherenkov detectors. Indeed, one of the possible water Cherenkov
detector unit configurations for SWGO consists of tanks, and to
reach a high detection efficiency and discrimination capability
between gamma-ray and hadronic air showers, different tank designs
are under investigation. In this study, we consider and compare
double-layer tanks with several sizes, shapes and number of
photo-multiplier tubes (PMTs). Muons, electrons, and gamma-rays with
energies typical of secondary particles in extensive air showers
have been simulated entering the tanks with zenith angles from 0 to
60 deg. The comparison between different tank geometries was
evaluated considering the number of photoelectrons produced by the
PMTs, the detection efficiency, and the time resolution of the
measurement of the first photon. We will show that with circular and
hexagonal tanks better performance can be obtained than with the
square ones, and that it improves for smaller tanks as expected.
The footprint of human-induced climate change on heat-related deaths in the summer of 2022 in Switzerland
Authors: Vicedo-Cabrera Ana M , de Schrijver Evan , Schumacher Dominik L , Ragettli Martina S , Fischer Erich M , Seneviratne Sonia I
Published: July 2023

Human-induced climate change is leading to an increase in the intensity and frequency of extreme weather events, which are severely affecting the health of the population. The exceptional heat during the summer of 2022 in Europe is an example, with record-breaking temperatures only below the infamous 2003 summer. High ambient temperatures are associated with many health outcomes, including premature mortality. However, there is limited quantitative evidence on the contribution of anthropogenic activities to the substantial heat-related mortality observed in recent times. Here we combined methods in climate epidemiology and attribution to quantify the heat-related mortality burden attributed to human-induced climate change in Switzerland during the summer of 2022. We first estimated heat-mortality association in each canton and age/sex population between 1990 and 2017 in a two-stage time-series analysis. We then calculated the mortality attributed to heat in the summer of 2022 using observed mortality, and compared it with the hypothetical heat-related burden that would have occurred in absence of human-induced climate change. This counterfactual scenario was derived by regressing the Swiss average temperature against global mean temperature in both observations and CMIP6 models. We estimate 623 deaths [95% empirical confidence interval (95% eCI): 151–1068] due to heat between June and August 2022, corresponding to 3.5% of all-cause mortality. More importantly, we find that 60% of this burden (370 deaths [95% eCI: 133–644]) could have been avoided in absence of human-induced climate change. Older women were affected the most, as well as populations in western and southern Switzerland and more urbanized areas. Our findings demonstrate that human-induced climate change was a relevant driver of the exceptional excess health burden observed in the 2022 summer in Switzerland.