bluuebunny/crossref_metadata_2025 huggingface dataset:
Simulation on two-phase refrigerant compression in the cylinder of rotary compressors using CFD method
Authors: Guo Nini , Lin Jie , Wu Jianhua
Published: March 2024

The two-phase compression process in the rotary compressor often occurs, such as defrosting and startup processes, which has a significant impact on the performance and reliability of air conditioning systems. In this paper, the CFD simulations predicting the two-phase refrigerant compression process in the compressor cylinder are conducted using the commercial software ANSYS Fluent. The dynamic mesh for the fluid domain and phase change model for the refrigerant are considered in the simulation. Effects of initial liquid volume fraction, refrigerant type and compressor type on the two-phase compression characteristics using R290 as refrigerant are carried out. Variations of the pressure, temperature, gas fraction distribution and evaporation rate in the cylinder are discussed. The results show that most liquid accumulates near the leakage gap and the bottom of the compression chamber during the two-phase compression process. The peak pressure during the two-phase compression decreases with the increase of the liquid volume fraction. The evaporation rate of R32 in the cylinder is much higher than that of R290. The maximum pressure of the reciprocating compressor is 2.26 times higher than that of the rotary compressor.
Deep learning analysis of epicardial adipose tissue to predict cardiovascular risk in heavy smokers
Authors: Foldyna Borek , Hadzic Ibrahim , Zeleznik Roman , Langenbach Marcel C. , Raghu Vineet K. , Mayrhofer Thomas , Lu Michael T. , Aerts Hugo J. W. L.
Published: March 2024

Background

Heavy smokers are at increased risk for cardiovascular disease and may benefit from individualized risk quantification using routine lung cancer screening chest computed tomography. We investigated the prognostic value of deep learning-based automated epicardial adipose tissue quantification and compared it to established cardiovascular risk factors and coronary artery calcium.

Methods

We investigated the prognostic value of automated epicardial adipose tissue quantification in heavy smokers enrolled in the National Lung Screening Trial and followed for 12.3 (11.9–12.8) years. The epicardial adipose tissue was segmented and quantified on non-ECG-synchronized, non-contrast low-dose chest computed tomography scans using a validated deep-learning algorithm. Multivariable survival regression analyses were then utilized to determine the associations of epicardial adipose tissue volume and density with all-cause and cardiovascular mortality (myocardial infarction and stroke).

Results

Here we show in 24,090 adult heavy smokers (59% men; 61 ± 5 years) that epicardial adipose tissue volume and density are independently associated with all-cause (adjusted hazard ratios: 1.10 and 1.38; P < 0.001) and cardiovascular mortality (adjusted hazard ratios: 1.14 and 1.78; P < 0.001) beyond demographics, clinical risk factors, body habitus, level of education, and coronary artery calcium score.

Conclusions

Our findings suggest that automated assessment of epicardial adipose tissue from low-dose lung cancer screening images offers prognostic value in heavy smokers, with potential implications for cardiovascular risk stratification in this high-risk population.
A physics-informed deep learning liquid crystal camera with data-driven diffractive guidance
Authors: Shi Jiashuo , Liu Taige , Zhou Liang , Yan Pei , Wang Zhe , Zhang Xinyu
Published: March 2024

Whether in the realms of computer vision, robotics, or environmental monitoring, the ability to monitor and follow specific targets amidst intricate surroundings is essential for numerous applications. However, achieving rapid and efficient target tracking remains a challenge. Here we propose an optical implementation for rapid tracking with negligible digital post-processing, leveraging an all-optical information processing. This work combines a diffractive-based optical nerual network with a layered liquid crystal electrical addressing architecture, synergizing the parallel processing capabilities inherent in light propagation with liquid crystal dynamic adaptation mechanism. Through a one-time effort training, the trained network enable accurate prediction of the desired arrangement of liquid crystal molecules as confirmed through numerical blind testing. Then we establish an experimental camera architecture that synergistically combines an electrically-tuned functioned liquid crystal layer with materialized optical neural network. With integrating the architecture into optical imaging path of a detector plane, this optical computing camera offers a data-driven diffractive guidance, enabling the identification of target within complex backgrounds, highlighting its high-level vision task implementation and problem-solving capabilities.
The functional significance of the RPA- and PCNA-dependent recruitment of Pif1 to DNA
Authors: Kotenko Oleksii , Makovets Svetlana
Published: March 2024

Pif1 family helicases are multifunctional proteins conserved in eukaryotes, from yeast to humans. They are important for the genome maintenance in both nuclei and mitochondria, where they have been implicated in Okazaki fragment processing, replication fork progression and termination, telomerase regulation and DNA repair. While the Pif1 helicase activity is readily detectable on naked nucleic acids in vitro, the in vivo functions rely on recruitment to DNA. We identify the single-stranded DNA binding protein complex RPA as the major recruiter of Pif1 in budding yeast, in addition to the previously reported Pif1-PCNA interaction. The two modes of the Pif1 recruitment act independently during telomerase inhibition, as the mutations in the Pif1 motifs disrupting either of the recruitment pathways act additively. In contrast, both recruitment mechanisms are essential for the replication-related roles of Pif1 at conventional forks and during the repair by break-induced replication. We propose a molecular model where RPA and PCNA provide a double anchoring of Pif1 at replication forks, which is essential for the Pif1 functions related to the fork movement.
Crystallization control of wide-bandgap perovskites for efficient solar cells via adding an anti-solvent into the perovskite precursor
Authors: Liu Zhihai , Wang Lei , Liu Xi , Xie Xiaoyin , Chen Ping
Published: March 2024

We controlled the crystallization process of wide band-gap perovskite films by directly adding an anti-solvent into the perovskite precursor.
Fully printed minimum port flexible interdigital electrode sensor arrays
Authors: Teng Yanyue , Wang Xin , Zhang Zhidong , Mei Shixuan , Nan Xueli , Zhao Yunlong , Zhang Xikuan , Xue Chenyang , Gao Libo , Li Junyang
Published: March 2024

Exploded diagram of the sensor array and its core mechanism. The three-dimensional hierarchical insulation is realized at the intersection of sensor rows and columns, and the minimum port output of the interdigital array sensor array is realized.
Modifying cellular properties via rational chemical design for unnatural oxygen reduction electrocatalysis of a cell
Authors: Niu Yangdi , Guo Gaofu , Xue Deming , Yang Xiaoli , Dai Xianqi , Bai Zhengyu , Yang Lin
Published: March 2024

It is of great theoretical and practical significance to break through the evolution of natural cells and confer new catalytic properties via chemical modification to catalyze unnatural chemical reactions in biocatalytic synthesis.
Tin–lead halide perovskite solar cells with a robust hole transport layer
Authors: Li Chunyan , Zhang Yao , Zhao Haiyan , Yu Zhongxun , Zhang Jixiang , Zhang Peng , Chen Han
Published: March 2024

Cesium carbonate is used to modify the labile PEDOT : PSS into a robust polymer substrate, which suppresses nonradiative recombination and chemical erosion at the buried interface, enabling Sn–Pb perovskite solar cells with >23% efficiency.
Fluorescent nanodiamond immunosensors for clinical diagnostics of tuberculosis
Authors: Le Trong-Nghia , Descanzo Mhikee Janella N. , Hsiao Wesley W.-W. , Soo Po-Chi , Peng Wen-Ping , Chang Huan-Cheng
Published: March 2024

Fluorescent nanodiamonds are utilized as magneto-optical immunosensors for the sensitive detection of tuberculosis. This technology shows promise for early diagnosis and advancement of nanocarbon-based clinical applications.
Layer-by-layer nanoparticle encapsulating all-trans retinoic acid and CpG as a mucosal adjuvant targeting colorectal cancer
Authors: Mi Shiwei , Li Wei , Wen Yixing , Yang Chen , Liu Shuai , Li Jingjiao , Cheng Xingdi , Zhao Yuanyuan , Huo Haonan , Zu Haowei , Lu Xueguang
Published: March 2024

ATRA and CpG are co-delivered by LbL nanoparticles, inducing the homing of activated T cells to the gut. Injecting NPs with OVA peptide effectively inhibits orthotopic colorectal tumor growth in mice without causing noticeable side effects.
Activation of alkyl hydroperoxides by manganese complexes of tmtacn for initiation of radical polymerisation of alkenes
Authors: Eijsink Linda E. , Sardjan Andy S. , Sinnema Esther G. , den Besten Hugo , Zhang Yanrong , Hage Ronald , van den Berg Keimpe J. , Flapper Jitte , Feringa Ben L. , Browne Wesley R.
Published: March 2024

Catalysed activation of alkyl hydroperoxides to generate radicals is a key step in the initiation of radical polymerisations in many applications, not least protective coatings. Manganese complexes show potential as replacements for cobalt catalysts.
Functionalized molybdenum disulfide (MoS2) monolayer as an efficient nanosensor towards toxic nitrogen containing gases
Authors: Alfalasi Wadha , Hussain Tanveer , Tit Nacir
Published: March 2024

Selective detection of toxic nitrogen-containing gases (e.g. NO and NO2) is achieved when special transition metal (TM) atoms are selected in doping molybdenum disulfide (MoS2) monolayer. The change of magnetic state is the secret of that selectivity.
From kitchen scraps to delicacies to food waste
Authors: Knorr Dietrich , Augustin Mary Ann
Published: March 2024

Food loss and waste occur along the whole food supply chain.
Enhanced thermoelectric performance of a wide-bandgap twisted heterostructure of graphene and boron nitride
Authors: Kumar Naveen , Bera Chandan
Published: March 2024

The twisted structure of two-dimensional heterostructure improved thermoelectric properties by enhancing electrical properties and reducing thermal conductivity.
New insights into the charge storage chemistry of polymer cathodes in aqueous Zn batteries
Authors: Yuan Xiangcheng , Wang Zhengjie , Li Yiqing , Gan Mi , Si Chen , Liu Jinzhang
Published: March 2024

The fractions of H+ and Zn2+ uptakes in four different polymer cathodes for aqueous Zn batteries are experimentally determined, and the dominant role of H+ in charge storage process is unveiled.
A short wave radar beam sharpening method based on generalised oblique projection operator with flexible parameter
Authors: Mao Xingpeng , Li Ju , Huang Heyue , Wang Yiming , Lang Junjie
Published: March 2024

Beamforming is an effective way of resolving target direction and anti‐jamming in short wave (SW) radar systems. In conventional beamforming (CBF) at a certain frequency, to get high resolution, the array aperture should be increased, and this is often not allowed in practical applications. A new narrow beam forming (NBF) method for beam sharpening based on the generalised oblique projection (GOP) filter with a flexible parameter is proposed. This method uses a GOP filter bank to form deep nulls in the undesired azimuth range on the pattern and utilises the logic product process to synthesise the GOP filters’ outputs and thus obtains a narrow beam. Compared to traditional beamforming methods, the result of NBF has the characteristics of narrower beam width and bigger side lobe suppression ratio (SLSR). Especially, a narrower beam can be obtained in the case of a small array aperture, which is valuable for practical applications. Experimental results of the range‐Doppler spectrum of short wave radar show that this narrow beam forming method can achieve super resolution of targets within a wide beam and greatly suppress clutter. Therefore, NBF can improve the azimuth resolution and achieve interference suppression in a conventional beam.
Experimental and numerical investigations of Al 1100 cup using conical die without blank holder
Authors: Kaimkuriya Amit , Balaguru S.
Published: March 2024

In sheet metal forming processes, the wrinkle phenomenon has been one of the main limiting failure factors. Both numerically and experimentally investigations were done using conical cup test method for wrinkling phenomena. This research work aim is to drawing a flat-bottom cylindrical cup from Al 1100 sheet material, with the effect of drawing parameters, including blank shape, blank thickness, load, and dry lubrication, employing both numerical and experimental methods. Simulation results were obtained using ANSYS 19.2 software, while experimental data were acquired through a universal testing machine. The optimization of process parameters led to the formation of a cylindrical cup with a flat bottom and no defects like thinning or wrinkling. This parametric research contributes to the accurate prediction of the final geometry of the sheet blank and the distribution of stresses, crucial for the forming process and the production of high-quality products. The results show that a die angle of 20° and an optimized punch speed of 3.5 mm/sec give the wrinkle-free cup with high compressive strength.
Steady state design and thermal characteristics of a gas turbine blade with lateral holes using finite element analysis
Authors: Sampathkumar Deepak , Azariah Sam Daniel Fenny , Mohankumar Ashokkumar , Mariappan Mathanbabu
Published: March 2024

Turbine blades are the separate components that make up the turbine section of a steam or gas turbine. The blades must transform the high-temperature, high-pressure gas that the combustor produces into energy. In gas turbines, the turbine blades are usually the limiting element. As gas temperatures rise, the amount of heat that reaches the blades will also grow dramatically, leading to their thermal failure. Because gas turbine blades must function in extremely high temperatures, cooling is crucial. After FEA simulation was conducted and radial perforations of 6, 9, and 12 were constructed to allow high-velocity cooling air to pass through, the cooling of the gas turbine blades was improved.
Adaptive PID Control for Autopilot Design of Small Fixed Wing UAVs
Authors: Lohani Tanzil Ahmed , Dixit Abhishek , Agrawal Pooja
Published: March 2024

The development of a flight control system for the class of small fixed wing Unmanned Aerial Vehicle (UAV) imposes a challenge to the designers to achieve acceptable and stable performance characteristics across the defined flight envelope. This paper focuses on developing a dynamic model of the Aerosonde UAV, incorporating it with an adaptive Proportional, Integral and Derivative (PID) control system for designing both lateral and longitudinal autopilots. The PID gains for each control loop are self-tuned based on an analytical approach, making sure that the desired command value is achieved at each time interval as closely as possible. To check the robust nature of the designed control system in the presence of external wind disturbance, a Dryden wind gust model was developed, and the entire simulation results were carried out in MATLAB®/Simulink environment. The proposed adaptive PID controller proves the effectiveness and robustness of the autopilot control system.
Multipurpose Surveillance Robot using Arduino Mega 2560 and Bluetooth Module HC-05
Authors: Bhuiyan MD Zobaer Hossain , Sabina Sabrina Akter
Published: March 2024

Robots are becoming increasingly important for security and surveillance applications. This research paper presents the design and hardware implementation of a low-cost and easy-to-assemble site surveillance robot using an Arduino Mega 2560 microcontroller and a Bluetooth module HC-05. The robot is equipped with various modules and sensors, including a camera and ultrasonic sensors, for capturing images and detecting obstacles, respectively. The Arduino Mega 2560 is used to control the movement of the robot and process sensor data, while the Bluetooth module is used for wireless communication between the robot and an Android device. The robot is capable of patrolling a designated area and sending real-time surveillance footage to an Android device via Wi-Fi. The developed system was tested and evaluated to demonstrate its performance and efficiency. The results showed that the robot is able to patrol a designated area accurately and efficiently and that the real-time surveillance footage is of high quality. The system has the potential to be used in a variety of applications, such as object retrieval, security, and surveillance in residential and commercial areas and spying on certain sites.
Psychoedukation für Patienten mit Migrationshintergrund
Authors: Ueberberg Bianca , Staudt Jonas , Kaaz Tatjana , Bilgin Betül , Goulbourn Alexandra , Koch Eckhard , Assion Hans-Jörg
Published: March 2024

Migration kann persönliche und seelische Belastungen sowie Auswirkungen auf das gesundheitliche Befinden mit sich bringen. Allerdings bestehen für Personen mit Migrationshintergrund Barrieren im Gesundheitssystem und die Anzahl kultursensibler Angebote ist gering. Zudem haben die wenigen kultursensiblen Angebote oftmals nur temporären Bestand und sind stark von einzelnen Protagonisten abhängig. Mit der Entwicklung des Manuals „Interkulturelle Psychoedukation für Menschen mit Migrationshintergrund“ sollte ein kultursensibles Angebot mit dem Ziel der Steigerung der Versorgungsqualität für Migranten geschaffen werden. Dabei steht die Wissensvermittlung über das tägliche Leben in Deutschland, Prävention, soziale Kontakte und Hilfsangebote, aber auch psychische Erkrankungen im Vordergrund. Zur Evaluation dieser interkulturellen Psychoedukation (iP) erfolgten Prä-/Post-Erhebungen evaluierter Fragebögen sowie selbst entwickelter Fragebögen zum Kenntnisgewinn bzw. der Pateientenzufriedenheit. Bei einer hohen Zufriedenheit mit dem Angebot, wurden die Module (Inhalt und sprachliches Verständnis) mit gut bis sehr gut bewertet. Ein signifikant verbesserter Kenntnisstand und eine signifikante Verbesserung in der Offenheit über Problem zu sprechen konnte im Prä-/Post-Vergleich identifiziert werden, während es keine signifikanten Veränderungen in der Selbstwirksamkeit und den Migrationsstressoren gab.

Den Teilnehmenden konnte im Rahmen der iP die Basis für ein Shared-Decision-Making vermittelt werden. Die Wissens- und Informationsvermittlung verbesserte das Verständnis über die psychischen Störungen, wodurch Rückfälle verhindert und stationäre Behandlungszeiten verkürzt oder vermieden werden können.
Klinische Verläufe und Kosten für Hospitalisierungen von COVID-19-Patienten mit potenziell eingeschränktem Immunsystem in Deutschland
Authors: Häckl Dennis , Pignot Marc , Dang Phi Long , Lauenroth Victoria , Jah Fungwe , Wendtner Clemens-Martin
Published: March 2024

Hintergrund Patienten, die wegen ihrer Erkrankung bzw. Therapie ein erhöhtes Risiko haben, unzureichend auf COVID-19-Impfungen anzusprechen, sind potenziell vulnerabel gegenüber schweren COVID-19-Verläufen. Ziel ist es, ihre Populationsgröße, klinischen Verläufe und Hospitalisierungskosten in Deutschland zu beurteilen.

Methode Die retrospektive Kohortenstudie basiert auf Hochrechnungen einer repräsentativen Stichprobe von GKV-Abrechnungsdaten des Jahres 2020. Klinische COVID-19-Verläufe, Hospitalisierungskosten und -dauern werden zwischen der Gruppe mit erhöhtem Risiko für inadäquate Immunreaktion auf COVID-19-Impfungen (Risikogruppe) und der Gruppe ohne dieses Risiko verglichen.

Ergebnisse Es gibt ca. 1,82 Mio. GKV-Versicherte in der Risikogruppe, von denen schätzungsweise 240 000 Versicherte keine humorale Immunantwort nach 3 COVID-19-Impfungen bilden. Die Risikogruppe zeigt im Vergleich zur Gruppe ohne Risiko höhere Anteile mit COVID-19 (Relatives Risiko [RR] 1,21; 95 %-Konfidenzintervall [95 %-KI] 1,20–1,23), Hospitalisierungen wegen COVID-19 (RR 3,40; 95 %-KI 3,33–3,48), Hospitalisierungen wegen COVID-19 mit intensivmedizinischer Behandlung (RR 1,36; 95 %-KI 1,30–1,42) und Mortalität (RR 5,14; 95 %-KI 4,97–5,33). Zudem sind Hospitalisierungen in der Risikogruppe durchschnittlich 18 % länger (15,36 Tage vs. 13,00 Tage) und 19 % teurer (12 371 € vs. 10 410 €). Die erwarteten Hospitalisierungskosten in der Risikogruppe betragen das Vierfache der Gruppe ohne Risiko (4115 € vs. 1017 €).

Diskussion Die Risikogruppe ist vulnerabel gegenüber COVID-19 und beansprucht zusätzliche Ressourcen im deutschen stationären Sektor. Hieraus resultiert ein Bedarf an weiteren Schutzmöglichkeiten. Weitere Studien sind notwendig, um den Einfluss verschiedener Virusvarianten, aktiver/passiver Immunisierungen und Therapien auf die klinischen COVID-19-Verläufe und deren Kosten zu bewerten.
Zweizeitige mikrochirurgische Weichteilrekonstruktion einer komplexen
sakralen Wunde unter Verwendung eines arteriovenösen Loops
Authors: Geber Benjamin , Landscheidt Kristina , Goertz Ole , Hernekamp Jochen-Frederick
Published: March 2024

Die Weichteilrekonstruktion sakraler Defektwunden ist herausfordernd und verläuft
häufig komplikativ. Wir berichten über die erfolgreiche zweizeitige
dreidimensionale mikrochirurgische Weichteilrekonstruktion eines großflächigen
und tiefen sakralen Defekts unter Anschluss einer freien kombinierten
ALT-/TFL-/Rectus-femoris-Lappenplastik an einen primär angelegten arteriovenösen
(AV-)Loop der ipsilateralen V. saphena magna. Der vorliegende Fall
unterstreicht, dass bei guter Indikationsstellung und klarer perioperativer
Planung aufwendige mikrochirurgische Rekonstruktionen auch in einem schwierigen
Patientengut erfolgversprechend sein können.
Osteotomy Techniques in Preservation Rhinoplasty with an Analysis of a Radix–Skull Base Computed Tomography Series
Authors: Neves José C. , Abdulraheem Maryam , Neves Ligia , Flora Barbara , D'Souza Alwyn
Published: March 2024

This study aims to explain our experience with dorsal preservation osteotomies, focusing on transverse, lateral, and dorsal aesthetic lines (DAL) osteotomies. We describe the utilization of a variety of surgical instruments, including osteotomes, saws, burrs, and piezo. This paper describes our concept of transcutaneous ultrasonic osteotomy, microedged-specific osteotomy, applying drills for lateral wall reshaping, and integrating piezo technology to establish new DAL. Furthermore, we present a radix–skull base computed tomography series analysis to evaluate the safety of transverse and radix osteotomies.
Beyond trade statistics: how much do exports actually contribute to domestic value added?
Authors: Llop Maria
Published: March 2024

Koopman et al. (2014) and Los et al. (2016) decomposed gross exports into various value-added components by adopting the input–output assumption of disconnection between production and final demand. Such an assumption, however, neglects the ability of production inflows to generate income and consumption, and therefore additional impacts on production. To achieve a more complete understanding of the role played by trade, this article presents a method for quantifying the value added of exports that reflects the linkages between production and private consumption. In the tradition of Miyazawa (1968, 1976) and Sonis and Hewings (1973), the proposed model endogenously defines household consumption in the output determination, thus improving the way in which the interdependencies between income and output generation processes are revealed. The proposal is directly applicable empirically through available world trade databases.
Assessment of financial and social disclosure level of Ethiopian commercial banks
Authors: Chanie Degu Kefale , Malhotra Keshav , Aggarwal Monika
Published: March 2024

Disclosures given by corporations are an important tool used as a communication mechanism between insiders and outsiders either investors or regulators who are seeking information for their decision-making. The study’s objective was to assess the level of financial and social disclosure by Ethiopian commercial banks. To achieve the objective 6 years of secondary data was collected from seventeen banks, mainly from the annual reports of banks. To measure the disclosure level of banks unweighted disclosure index measurement approach was used. To evaluate and analyse the level of financial and social disclosure descriptive statistics (such as mean, standard deviations, and independent t-test) were used. The analysis revealed that the average financial disclosure level of Ethiopian commercial banks during the study was 64.1%, whereas social disclosure was 50.8%. During the study period, both financial and social disclosure showed an increasing trend from year to year. However, the increasing trend of financial disclosure level is higher than the social disclosure level. Further, the independent t-test result showed that there is a statistically insignificant difference between the mean value of public and private banks’ disclosure levels. The study concludes that commercial banks in Ethiopia have a moderate level of financial and social disclosure. From the result, it is recommended that Ethiopian commercial banks should disclose more financial and social information to improve their disclosure level.
Applying machine learning algorithms to predict the stock price trend in the stock market – The case of Vietnam
Authors: Phuoc Tran , Anh Pham Thi Kim , Tam Phan Huy , Nguyen Chien V.
Published: March 2024

The aims of this study are to predict the stock price trend in the stock market in an emerging economy. Using the Long Short Term Memory (LSTM) algorithm, and the corresponding technical analysis indicators for each stock code include: simple moving average (SMA), convergence divergence moving average (MACD), and relative strength index (RSI); and the secondary data from VN-Index and VN-30 stocks, the research results showed that the forecasting model has a high accuracy of 93% for most of the stock data used, demonstrating the appropriateness of the LSTM model and the test set data is used to evaluate the model’s performance. The research results showed that the forecasting model has a high accuracy of 93% for most of the stock data used, demonstrating the appropriateness of the LSTM model in analyzing and forecasting stock price movements on the machine learning platform.
Green public procurement in the most visited European museums: a comparison and a mapping
Authors: Plaček Michal , Rosell Jordi , Valentinov Vladislav , Křápek Milan
Published: March 2024

While scholarly research on green public procurement (GPP) keeps growing, until now it has paid little attention to museums that must make decisions about GPP implementation. This paper breaks new ground by exploring GPP implementation in the most visited European museums. The proposed conceptual framework allows a comparison and a mapping of museums’ GPP implementation levels while taking account of how these levels are related to the national GPP performance. Complementing this framework with the analysis of the up-to-date data from the Tender Electronic Daily database yields two central findings. First, museums that formalized their GPP policies in their strategic organizational documents exhibit higher levels of GPP implementation than other museums that have not done so. Second, the majority of the investigated museums follow national trends of GPP implementation, with examples of exceeding or falling below these trends being rare. The article is important for policy makers and practitioners as it highlights the importance of the factor of institutionalization of green procurement in individual organizations, which is crucial for successful implementation of green procurement.
Assessing scale reliability in citizen science motivational research: lessons learned from two case studies in Uganda
Authors: Ashepet Mercy Gloria , Vranken Liesbet , Michellier Caroline , Dewitte Olivier , Mutyebere Rodgers , Kabaseke Clovis , Twongyirwe Ronald , Kanyiginya Violet , Kagoro-Rugunda Grace , Huyse Tine , Jacobs Liesbet
Published: March 2024

Citizen science (CS) is gaining global recognition for its potential to democratize and boost scientific research. As such, understanding why people contribute their time, energy, and skills to CS and why they (dis)continue their involvement is crucial. While several CS studies draw from existing theoretical frameworks in the psychology and volunteering fields to understand motivations, adapting these frameworks to CS research is still lagging and applications in the Global South remain limited. Here we investigated the reliability of two commonly applied psychometric tests, the Volunteer Functions Inventory (VFI) and the Theory of Planned Behaviour (TPB), to understand participant motivations and behaviour, in two CS networks in southwest Uganda, one addressing snail-borne diseases and another focused on natural hazards. Data was collected using a semi-structured questionnaire administered to the CS participants and a control group that consisted of candidate citizen scientists, under group and individual interview settings. Cronbach’s alpha, as an a priori measure of reliability, indicated moderate to low reliability for the VFI and TPB factors per CS network per interview setting. With evidence of highly skewed distributions, non-unidimensional data, correlated errors and lack of tau-equivalence, alpha’s underlying assumptions were often violated. More robust measures, McDonald’s omega and Greatest lower bound, generally showed higher reliability but confirmed overall patterns with VFI factors systematically scoring higher, and some TPB factors—perceived behavioural control, intention, self-identity, and moral obligation—scoring lower. Metadata analysis revealed that most problematic items often had weak item–total correlations. We propose that alpha should not be reported blindly without paying heed to the nature of the test, the assumptions, and the items comprising it. Additionally, we recommend caution when adopting existing theoretical frameworks to CS research and propose the development and validation of context-specific psychometric tests tailored to the unique CS landscape, especially for the Global South.
Risk spillovers of carbon emissions in international trade: the role of disembodied technology communications
Authors: Liu Shun Jia , Li Jianping , Wu Dengsheng , Zhu Xiaoqian , Xu Xin Long
Published: March 2024

Carbon emission reduction is an important means of achieving climate policy goals. However, the literature has neglected consideration of the carbon emission reduction mechanism from the perspective of technology risk spillovers in international trade. To explore this mechanism, this paper expands the classical linear model of foreign trade technology risk spillovers into a nonlinear spatial Durbin model. We construct a novel technology risk spillover index to forecast the magnitude of carbon emissions in agricultural trade across different regions. To validate our model, we consider the dual connotation of the spatial diffusion of disembodied technology communication (DTC) to map the relationships between different geographic and economic regions that are adjacent. The results suggest that disembodied technology risk spillover could promote carbon emission reductions. Specifically, technology risk spillovers from agricultural trade reduce agricultural carbon emissions by 0.79–1.16% in the local region. Disembodied technology risk spillovers also reduce agricultural carbon emissions by 2.85–11.57% in geographically adjacent regions and 4.9% in economically adjacent regions. Based on these conclusions, this paper proposes improving the closed and backward situation of rural areas in China’s central and western regions, promoting the transition toward the high end of the global agricultural industry chain and developing productive agricultural services and the rural cultural tourism industry to expand rural employment channels and stabilize farmers’ income.
Advance optimum design of multi-layer compound cylinders
Authors: Es-saheb Mahir H. , Alsubaie Abdulrahman , Fouad Yasser
Published: March 2024

The purpose of this work is to find the optimum design for two-layer compound cylinders of the same material with an open end condition by using the elimination method. The optimization method depends on reducing the number of design variables with a simultaneous yield hypothesis for all layers of the compound cylinder. A combination of von Mises and Tresca criteria is used as a yield criterion, and the superposition principle is used to evaluate the equivalent stresses for each cylinder. By considering the working pressure and the internal diameter of the inner cylinder as the design parameters (constants during optimization) and the total thickness of the compound cylinder as the objective function, the optimization algorithm has been programmed in C# with a user-friendly graphical interface. The optimization results (outer diameter, interference diameter, and shrinkage pressure) are obtained for different working pressures and compared with the optimum design, which is based only on the Tresca criterion. The total mass of the compound cylinder can be reduced by up to 50% by using the von Mises–Tresca combination criterion. The optimized results are validated numerically by using finite element analysis in the ANSYS Workbench. The theoretical result and the FEA result agree with each other with errors of about 2%. The behavior of the optimized parameters for different working pressures is also observed and presented.
Classical and Bayesian inference of inverted modified Lindley distribution based on progressive type-II censoring for modeling engineering data
Authors: Hasaballah Mustafa M. , Tashkandy Yusra A. , Bakr M. E. , Balogun Oluwafemi Samson , Ramadan Dina A.
Published: March 2024

This paper investigates statistical inferences for product lifetimes following the inverted modified Lindley distribution, utilizing progressive Type-II censored data. The estimation of model parameters employs the maximum likelihood method, complemented by the construction of approximate confidence intervals. Bayesian estimates are also explored, incorporating squared error and linear exponential loss functions with noninformative priors. To approximate Bayes estimates, the proposal presents Gibbs sampling based on the MCMC algorithm. This results in the generation of the greatest posterior density credible intervals for the parameters. A real data analysis is conducted to validate the accuracy of all the models and methods discussed. Finally, computational studies using Monte Carlo simulations are presented to compare the suggested estimators.
Multiple retinal isomerizations during the early phase of the bestrhodopsin photoreaction
Authors: Kaziannis Spyridon , Broser Matthias , van Stokkum Ivo H. M. , Dostal Jakub , Busse Wayne , Munhoven Arno , Bernardo Cesar , Kloz Miroslav , Hegemann Peter , Kennis John T. M.
Published: March 2024

Bestrhodopsins constitute a class of light-regulated pentameric ion channels that consist of one or two rhodopsins in tandem fused with bestrophin ion channel domains. Here, we report on the isomerization dynamics in the rhodopsin tandem domains of
Phaeocystis antarctica
bestrhodopsin, which binds all-trans retinal Schiff-base (RSB) absorbing at 661 nm and, upon illumination, converts to the meta-stable P540 state with an unusual 11-
cis
RSB. The primary photoproduct P682 corresponds to a mixture of highly distorted 11
-cis
and 13-
cis
RSB directly formed from the excited state in 1.4 ps. P673 evolves from P682 in 500 ps and contains highly distorted 13-
cis
RSB, indicating that the 11-
cis
fraction in P682 converts to 13-
cis
. Next, P673 establishes an equilibrium with P595 in 1.2 µs, during which RSB converts to 11-
cis
and then further proceeds to P560 in 48 µs and P540 in 1.0 ms while remaining 11-
cis
. Hence, extensive isomeric switching occurs on the early ground state potential energy surface (PES) on the hundreds of ps to µs timescale before finally settling on a metastable 11-
cis
photoproduct. We propose that P682 and P673 are trapped high up on the ground-state PES after passing through either of two closely located conical intersections that result in 11-
cis
and 13-
cis
RSB. Co-rotation of C11=C12 and C13=C14 bonds results in a constricted conformational landscape that allows thermal switching between 11
-cis
and 13-
cis
species of highly strained RSB chromophores. Protein relaxation may release RSB strain, allowing it to evolve to a stable 11-
cis
isomeric configuration in microseconds.
Some Modified Equations of the Sine-Hilbert Type
Authors: Yan 闫 Ling-Juan 铃娟 , Liu 刘 Ya-Jie 亚杰 , Hu 胡 Xing-Biao 星标
Published: March 2024

Three modified sine-Hilbert (sH)-type equations, i.e., the modified sH equation, the modified damped sH equation, and the modified nonlinear dissipative system, are proposed, and their bilinear forms are provided. Based on these bilinear equations, some exact solutions to the three modified equations are derived.
Configurations of dipoles, moving charges and currents for dynamic spherical multipoles
Authors: Majic Matt , Geris Sophia
Published: March 2024

Configurations of dipoles, moving point charges and current loops are presented for the dynamic spherical multipoles of the electric and magnetic type, whose fields are the vector spherical wave functions (VSWFs). The configurations produce the VSWFs of a specific degree and order in the limit that they become infinitely small. We find frequency independent configurations for up to degree n = 5 or higher in some cases, which exceeds the current range of configurations in the literature for up to n = 3, and our configurations for n = 3 are simpler. We also investigate the link with anapoles and toroidal multipoles.
Voltage control of electromagnetic properties in antiferromagnetic materials
Authors: Xu Xinyi , Semenov Yuriy G , Wook Kim Ki
Published: March 2024

Dynamic modulation of electromagnetic responses is theoretically examined in dielectric antiferromagnets (AFMs). While both magneto-electric and magneto-elastic coupling can achieve robust electrical control of magnetic anisotropy, the latter is considered in a bilayer structure with a piezoelectric material. Numerical calculations based on the frequency-dependent permeability tensor clearly illustrate that the anisotropy profile in the typical dielectric AFMs such as NiO and Cr2O3 can be modified sufficiently to induce a shift in the resonance frequency by as much as tens of percent in the sub-mm wavelength range (thus, an electrically tunable bandwidth over 10’s of GHz). The polarization of the electromagnetic response is also affected due to the anisotropic nature of the effect, offering a possibility to encode the signal. The intrinsic delay in switching may be minimized to the ns level by using a sufficiently thin AFM. Application to specific devices such as a bandpass filter further illustrates the validity of the concept.
Visualizing pursed lips breathing of patients with chronic obstructive pulmonary disease through evaluation of global and regional ventilation using electrical impedance tomography
Authors: Yang Lin , Gao Zhijun , Cao Xinsheng , Wang Chunchen , Wang Hang , Dai Jing , Liu Yang , Qin Yilong , Dai Meng , Zhang Binghua , Zhao Ke , Zhao Zhanqi
Published: March 2024

Objective. This study aims to explore the possibility of using electrical impedance tomography (EIT) to assess pursed lips breathing (PLB) performance of patients with chronic obstructive pulmonary disease (COPD). Methods. 32 patients with COPD were assigned equally to either the conventional group or the EIT guided group. All patients were taught to perform PLB by a physiotherapist without EIT in the conventional group or with EIT in the EIT guided group for 10 min. The ventilation of all patients in the final test were continuously monitored using EIT and the PLB performances were rated by another physiotherapist before and after reviewing EIT. The global and regional ventilation between two groups as well as between quite breathing (QB) and PLB were compared and rating scores with and without EIT were also compared. Results. For global ventilation, the inspiratory depth and the ratio of expiratory-to-inspiratory time during PLB was significantly larger than those during QB for both group (P < 0.001). The inspiratory depth and the ratio of expiratory-to-inspiratory time during PLB in the EIT guided group were higher compared to those in the conventional group (P < 0.001), as well as expiratory flow expiratory uniformity and respiratory stability were better (P < 0.001). For regional ventilation, center of ventilation significantly decreased during PLB (P < 0.05). The expiratory time constant during PLB in the EIT guided group was greater than that in the conventional group (P < 0.001). Additionally, Bland–Altman plots analysis suggested a high concordance between subjective rating and rating with the help of EIT, but the score rated after EIT observation significantly lower than that rated subjectively in both groups (score drop of −2.68 ± 1.1 in the conventional group and −1.19 ± 0.72 in the EIT guided group, P < 0.01). Conclusion. EIT could capture the details of PLB maneuver, which might be a potential tool to quantitatively evaluate PLB performance and thus assist physiotherapists to teach PLB maneuver to patients.
The effective field theory approach to the strong coupling issue in f(T) gravity with a non-minimally coupled scalar field
Authors: Hu Yu-Min , Yu Yang , Cai Yi-Fu , Gao Xian
Published: March 2024

The Hamiltonian analysis for f(T) gravity implies the existence of at least one
scalar-type degree of freedom (DoF). However, this scalar DoF of f(T) gravity does not manifest
in linear perturbations around a cosmological background, which indicates an underlying strong
coupling problem. In this work we expand the scope by introducing an extra scalar field
non-minimally coupled to f(T) gravity, aiming to address or alleviate the aforementioned strong
coupling problem. Employing the effective field theory (EFT) approach, we provide a class of
torsional EFT forms up to second order operators, avoiding the Ostrogradsky ghost. To illustrate
this phenomenon, we study a simple model and perform a detailed analysis of its linear scalar
perturbations. The results demonstrate that the coupling terms in this toy model are necessary to
avoid the initial degenerate situation. The complete avoidance of new constraints requires more
coupling terms. Once this vanishing scalar DoF starts propagating in cosmological background at
linear level, this phenomenon will demand a revisit of the strong coupling issue that arises in
 f(T) gravity, particularly in the presence of matter coupling.
Cloud Identification and Reconstruction from All-sky Camera Images Based on Star Photometry Estimation
Authors: Zhi 支 Hui 挥 , Wang 王 Jianfeng 建峰 , Zhang 张 Xiaoming 晓明 , Ge 葛 Jiayi 家驿 , Zeng 曾 Xianqun 显群 , Xie 谢 Haiwen 海闻 , Wang 王 Jia-Qi 佳琪 , Jiang 姜 Xiao-Jun 晓军
Published: March 2024

Cloud cover significantly influences ground-based optical astronomical observations, with nighttime astronomy often relying on visible light all-sky cameras for cloud detection. However, existing algorithms for processing all-sky cloud images typically require extensive manual intervention, posing challenges in identifying clouds with pronounced extinction characteristics. Furthermore, there is a lack of effective means for detailed visualization of cloud cover. To address these issues, this paper proposes a method that reconstructs the cloud distribution and thickness from all-sky images through star identification and photometry. Specifically, a high-precision star coordinate to the pixel position imaging model calibration method based on the star recognition for fisheye lenses is investigated, resulting in an all-sky rms error of less than 0.87 pixels. Based on the comprehensive reference star catalog, an optimized star extraction method based on SExtractor is developed to handle the difficulty of image source detection in all-sky cloud images. The optical thickness and distribution of cloud layers is calculated through star matching and extinction measurements. Finally, contingent upon the capability of camera and catalog star density, seven cloud layer reconstruction methods are proposed based on meshing and machine learning techniques, achieving a reconstruction accuracy of up to 1.°8. The processing results from real observed images indicate that the proposed method offers a straightforward calibration process and delivers excellent cloud cover extraction and reconstruction outcomes, thereby providing practical value in telescope dynamic scheduling, site characterization and the development of observation strategies.
Optical PAM-4/PAM-8 generation via dual-Raman process in Rydberg atoms
Authors: Song 宋 Xiao-Yun 晓云 , Yin 尹 Zheng 政 , Ren 任 Guan-Yu 冠宇 , Han 韩 Ming-Zhi 明志 , Yang 杨 Ai-Hong 艾红 , Qi 祁 Yi-Hong 义红 , Peng 彭 Yan-Dong 延东
Published: March 2024

A scheme of optical four-level pulse amplitude modulation (PAM-4) is proposed based on dual-Raman process in Rydberg atoms. A probe field counter-propagates with a dual-Raman field which drives the ground and the excited states transition, respectively, and the Rydberg transition is driven by a microwave (MW) field. A gain peak appears in the probe transmission and is sensitive to the MW field strength. Optical PAM-4 can be achieved by encoding an MW signal and decoding the magnitude of a probe signal. Simulation results show that the differential nonlinearity and the integral nonlinearity of the proposed scheme can be reduced by 5 times and 6 times, respectively, compared with the counterparts of previous scheme, and the ratio of level separation mismatch is close to the ideal value 1. Moreover, the scheme is extended to optical PAM-8 signal, which may further improve the spectral efficiency.
WT-FCTGN: A wavelet-enhanced fully connected time-gated neural network for complex noisy traffic flow modeling
Authors: Liao 廖 Zhifang 志芳 , Sun 孙 Ke 轲 , Liu 刘 Wenlong 文龙 , Yu 余 Zhiwu 志武 , Liu 刘 Chengguang 承光 , Song 宋 Yucheng 禹成
Published: March 2024

Accurate forecasting of traffic flow provides a powerful traffic decision-making basis for an intelligent transportation system. However, the traffic data’s complexity and fluctuation, as well as the noise produced during collecting information and summarizing original data of traffic flow, cause large errors in the traffic flow forecasting results. This article suggests a solution to the above mentioned issues and proposes a fully connected time-gated neural network based on wavelet reconstruction (WT-FCTGN). To eliminate the potential noise and strengthen the potential traffic trend in the data, we adopt the methods of wavelet reconstruction and periodic data introduction to preprocess the data. The model introduces fully connected time-series blocks to model all the information including time sequence information and fluctuation information in the flow of traffic, and establishes the time gate block to comprehend the periodic characteristics of the flow of traffic and predict its flow. The performance of the WT-FCTGN model is validated on the public PeMS data set. The experimental results show that the WT-FCTGN model has higher accuracy, and its mean absolute error (MAE), mean absolute percentage error (MAPE) and root mean square error (RMSE) are obviously lower than those of the other algorithms. The robust experimental results prove that the WT-FCTGN model has good anti-noise ability.