bluuebunny/crossref_metadata_2025 huggingface dataset:
Synthesis of polyvinylethylene glycols (PVEGs) via polyetherification of vinylethylene carbonate by synergistic catalysis
Authors: Yang Fan , Wang Minghang , Zhang Yong Jian
Published: March 2024

A novel type of polyether called polyvinylethylene glycols (PVEGs) is prepared by effective and controllable polyetherification via synergistic catalysis.
From sensing interactions to controlling the interactions: a novel approach to obtain biological transistors for specific and label-free immunosensing
Authors: Samanta Soumadri , Tiwari Vinay S. , Sadhujan Sumesh , Harilal Sherina , Eisenberg-Lerner Avital , Rotfogel Ziv , Pikhay Evgeny , Shima-Edelstein Ruth , Greental Doron , Bashouti Muhammad Y. , Akabayov Barak , Ron Izhar , Roizin Yakov , Erez Offer , Shalev Gil
Published: March 2024

The MNC biosensor is employed for specific and label-free sensing of AFP from 0.5 μL drops of diluted serum with a limit-of-detection of 10.5 aM and a dynamic range extending over 6 orders of AFP concentration.
Transient control of lytic activity via a non-equilibrium chemical reaction system
Authors: Sato Kohei , Nakagawa Yume , Mori Miki , Takinoue Masahiro , Kinbara Kazushi
Published: March 2024

A non-equilibrium chemical reaction system allows transient control of lytic activity.
Investigating the diastereoselective synthesis of a macrocycle under Curtin–Hammett control
Authors: Yeung Angus , Zwijnenburg Martijn A. , Orton Georgia R. F. , Robertson Jennifer H. , Barendt Timothy A.
Published: March 2024

The Curtin–Hammett principle is used to understand the diastereoselective synthesis of a heterochiral over a homochiral macrocycle, both of which are configurationally stable chiral macrocycles.
Efficient fractionation of pure hemicellulose with high DP from bleached hardwood pulp using LiBr·3H2O and co-production of dissolving pulp
Authors: Gong Runzhu , Liu Chao , Wu Meiyan , Tian Rui , Yu Guang , Luo Xitao , Li Bin , Peng Feng , Tang Yanjun
Published: March 2024

Hemicellulose was efficiently fractionated from BHKP using LBTH with the coproduction of high-quality dissolving pulp. The obtained hemicellulose was pure glucuronoarabinoxylan with high DP (>200) and unique crystalline and nano structure.
EuIII and TbIII upconversion intermediated by interparticle energy transfer in functionalized NaLnF4 nanoparticles
Authors: Nunes Coelho Sergio Fernando , Bispo-Jr Airton Germano , de Oliveira Nagyla Alves , Mazali Italo Odone , Sigoli Fernando Aparecido
Published: March 2024

EuIII and/or TbIII upconversion emission mediated by interparticle energy transfer (IPET) between donor (NaGdF4:YbIII:TmIII) and acceptor (NaGdF4:EuIII, NaGdF4:TbIII or NaGdF4:EuIII:TbIII) nanoparticles functionalized with antenna ligands.
Azasulfur(iv) derivatives of sulfite and sulfinate esters by formal S–S bond insertion of dichloramines
Authors: Wu Peng , Demaerel Joachim , Statham Benjamin J. , Bolm Carsten
Published: March 2024

Starting from N,N-dichloramines and S8 or disulfides, azasulfur(iv) chlorides are prepared, which are easily derivatised by esterification or amidation. The resulting products can be converted to a variety of complex sulfur(vi) compounds.
Questing for homoleptic mononuclear manganese complexes with monodentate O-donor ligands
Authors: Pérez-Bitrián Alberto , Munárriz Julen , Krause Konstantin B. , Schlögl Johanna , Hoffmann Kurt F. , Sturm Johanna S. , Hadi Amiera N. , Teutloff Christian , Wiesner Anja , Limberg Christian , Riedel Sebastian
Published: March 2024

High spin monomeric complexes [MnII(OTeF5)4]2− and [MnIII(OTeF5)5]2− represent novel homoleptic coordination environments at Mn(ii) and Mn(iii) centers with monodentate O-donor ligands.
FGDB‐MLPP: A fine‐grained data‐sharing scheme with blockchain based on multi‐level privacy protection
Authors: Lin Junyu , Feng Libo , Wang Jinli , Qiu Fei , Yu Bei , Cheng Jing , Yao Shaowen
Published: March 2024

In the era of 5G, billions of terminal devices achieve global interconnection and intercommunication, which leads to the generation of massive data. However, the existing cloud‐based data‐sharing mechanism faces challenges such as sensitive information leakage and data islands, which makes it difficult to achieve secure sharing across domains. In this paper, the authors propose a fine‐grained data‐sharing scheme based on blockchain and ciphertext policy attribute‐based encryption, and design a verifiable outsourced computation method to reduce the computational pressure of end users. Second, the authors comprehensively consider the user's identity privacy and transaction privacy, and propose a multi‐level privacy protection method based on ring signature and garbled bloom filter, which enhance the user's data privacy and availability, and prevent the traceability of requests. Finally, the authors design a set of interconnected smart contracts, and verify that their scheme can achieve secure and efficient data sharing through security analysis and performance testing.
A novel federated learning aggregation algorithm for AIoT intrusion detection
Authors: Jia Yidong , Lin Fuhong , Sun Yan
Published: March 2024

Nowadays, the development of Artificial Intelligence of Things (AIoT) is advancing rapidly, and intelligent devices are increasingly exposed to more security risks on the network. Deep learning‐based intrusion detection is an effective security defence approach. Federated learning (FL) is capable of enabling deep learning models to be trained on local clients without uploading their data to a central server. This paper proposes a novel federated learning aggregation algorithm called fed‐dynamic gravitational search algorithm (Fed‐DGSA), which incorporates the GSA algorithm to optimize the weight updating process of FL local models. During the updating process, the decay rate of the gravity coefficient is optimized and random perturbations and dynamic weights are introduced to ensure a more stable and efficient FL aggregation process. The experimental results show that the detection accuracy of Fed‐DGSA has reached about 97.8%, and it is demonstrated that the model trained using Fed‐DGSA achieves higher accuracy compared to Fed‐Avg.
Grid‐side flexibility assessment based on security distance of dispatchable region for AC/DC hybrid system using approximate second‐order cone relaxation
Authors: Wang Feifei , Qin Zhijun
Published: March 2024

The rapid growth of offshore wind power has resulted in a mismatch between generation and demand because of its variability. To quantify the maximum wind power penetration of the transmission network, the dispatchable region is defined as the largest region in the uncertainty space. The security distance is defined as the minimum distance from the operating point to the boundaries of the dispatchable region. System operators can use security distance as a metric to assess the flexibility of the power system. This paper proposes a method to construct the dispatchable region for the AC/DC hybrid system with VSC‐HVDC by outer convex relaxation firstly. The second‐order cone relaxation is employed to reformulate non‐convex and non‐linear power flow equations. Next, a polyhedral approximation is adopted to obtain the convex hull of the dispatchable region. Subsequently, an efficient algorithm known as adaptive constraint generation (Ad‐CG) is introduced to calculate the boundaries of the dispatchable region. Furthermore, solving the Chebyshev centre problem determines the minimal security distance. The modified IEEE 5‐bus and 39‐bus system is used for validating effectiveness of the proposed method and evaluating the impact of the converter reactive power compensation capacity and generation dispatch on the dispatchable region.
Enhancing model‐based acoustic localisation using quantum annealing
Authors: Wezeman Robert , Bontekoe Tariq , von Benda‐Beckmann Sander , Phillipson Frank
Published: March 2024

Model‐based acoustic localisation estimates the locations of underwater objects by comparing sensor measurements with model predictions. To obtain high quality predictions, propagation models need to be run for a large set of environmental parameters. However, real‐time Model‐based acoustic localisation estimations using onboard computational resources are often limited. To address this, the authors propose a Quantum annealing (QA) algorithm for enhancing underwater acoustic localisation. A restricted Boltzmann machine (RBM) is trained to predict the probability distribution of underwater targets. Advantage of this approach is that part of the computation is moved to offline‐training. Moreover, the probability distribution can potentially be sampled efficiently using a quantum annealer possibly enabling real‐time accurate target estimations being made onboard.The RBM is applied to a simplified multi‐sensor horizontal localisation problem where a constant and linear acoustic propagation is assumed. Using simulated annealing the authors show that the RBM is able to learn probability distributions that resemble target locations. Preliminary results show that training and sampling the RBM can be done using QA hardware by D‐Wave Systems.However, there remains room for improvement especially in ranging predictions. Further research into possible benefits of QA RBMs is needed to provide theoretical and practical results of a speed‐up.
Pediatric Mycoplasma Pneumonia: The Radiographic Patterns and Review
of the Literature
Authors: Cinar Hasibe Gokce , Ucan Berna , Fatma Nur ÖZ
Published: March 2024

Purpose The purpose of the present paper was to evaluate the clinical and
chest radiographic features of pediatric patients with serologically proven
Mycoplasma pneumoniae pneumonia.

Materials and methods The clinical records and chest radiographs of 55
consecutive patients (28 male, 27 female) with serologically positive IgG
mycoplasma pneumonia were reviewed. The pneumonic infiltrates were described on
chest radiography into 3 different patterns as a peribronchovascular
infiltration, reticulonodular infiltration and consolidation.

Results More than 91% of patients presented with cough and 70% of patients
had fever. Chest radiographs displayed three different patterns: (i)
peribronchovascular infiltration (n=33, 60%); (ii) reticulonodular infiltration
(n=12, 22%); (iii) consolidation (n=10, 18%). Bilateral peribronchovascular
infiltration in central and middle lung zones were frequently seen (n=33, 60%).
Other radiological features were unilateral lesions in 51% of patients, pleural
effusion in 18%, and hilar lymphadenopathy in 20%.

Conclusion There are various radiological features of mycoplasma pneumonia
in children. Bilateral peribronchovascular infiltration confined to central and
middle lung regions seems to be more closely associated with mycoplasma
infection.
Cannabinoids in the Treatment of Selected Mental Illnesses: Practical Approach and Overview of the Literature
Authors: Müller-Vahl Kirsten R.
Published: March 2024

Although an increasing number of patients suffering from mental illnesses self-medicate with cannabis, current knowledge about the efficacy and safety of cannabis-based medicine in psychiatry is still extremely limited. So far, no cannabis-based finished product has been approved for the treatment of a mental illness. There is increasing evidence that cannabinoids may improve symptoms in autism spectrum disorder (ASD), Tourette syndrome (TS), anxiety disorders, and post-traumatic stress disorder (PTSD). According to surveys, patients often use cannabinoids to improve mood, sleep, and symptoms of attention deficit/hyperactivity disorder (ADHD). There is evidence suggesting that tetrahydrocannabinol (THC) and THC-containing cannabis extracts, such as nabiximols, can be used as substitutes in patients with cannabis use disorder.

Preliminary evidence also suggests an involvement of the endocannabinoid system (ECS) in the pathophysiology of TS, ADHD, and PTSD. Since the ECS is the most important neuromodulatory system in the brain, it possibly induces beneficial effects of cannabinoids by alterations in other neurotransmitter systems. Finally, the ECS is an important stress management system. Thus, cannabinoids may improve symptoms in patients with mental illnesses by reducing stress.

Practically, cannabis-based treatment in patients with psychiatric disorders does not differ from other indications. The starting dose of THC-containing products should be low (1–2.5 mg THC/day), and the dose should be up-titrated slowly (by 1–2.5 mg every 3–5 days). The average daily dose is 10–20 mg THC. In contrast, cannabidiol (CBD) is mainly used in high doses>400 mg/day.
Ein seltener Fall: Kasabach-Merrit-Syndrom bei
VACTERL-Assoziation
Authors: Le Melanie , Wenke Katharina , Herrmann Jochen , Singer Dominique , Lange Mario
Published: March 2024

Das Kasabach-Merrit-Syndrom ist charakterisiert als Assoziation eines
Gefäßtumors, typischerweise einem kaposiformem Hämangioendotheliom sowie einer
schweren Verbrauchskoagulopathie mit potenziell lebensbedrohlichen
Thrombozytopenien. Die schwere Gerinnungsstörung mit erhöhter Blutungsneigung
muss vor invasiven Eingriffen berücksichtigt werden und erfordert nicht selten
wiederholte Thrombozytenkonzentrat Transfusionen. Wir berichten hierbei über ein
reifes männliches Neugeborenes mit Kasabach-Merrit-Syndrom und
VACTERL-Assoziation. Die VACTERL-Assoziation beschreibt eine Gruppe von
Fehlbildungen. Der Patient wies eine Analatresie (mit rektourethraler Fistel),
zystischen Veränderungen im Spinalkanal (mit tethered cord) und einer
Nierenagenesie links auf. Die VACTERL Assoziation sowie das
Kasabach-Merritt-Syndrom fanden sich bei diesem Patienten als unabhängig
voneinander gewertete Entitäten. Ein gemeinsames Auftreten wurde bisher in der
Literatur nicht beschrieben. Die eingeschränkte Gerinnungssituation durch
schwere Thrombozytopenien erschwerte die operative Anus praeter Anlage sowie
Biopsie Entnahme zur Diagnosesicherung. In unserem Fallbeispiel konnte
schließlich der mTOR Inhibitor Sirolimus erfolgreich zur Verkleinerung des
Gefäßtumors und besonders zur Senkung des Thrombozyten- Verbrauchs eingesetzt
werden.
Electrochemical Generation of Ketyl Radicals and Their Applications
Authors: Xu Kun , Zeng Chengchu , Tan Zhoumei
Published: March 2024

Ketyl radicals display new reactivities beyond the intrinsic electrophilicity of carbonyls. Recent progress in organic electrosynthesis has fueled the generation and utilization of ketyl radicals under ‘greener’ conditions. This graphical review summarizes these electrochemical advancements into three major categories: cross-pinacol couplings, coupling of carbonyls with alkyl radical precursors, and coupling of carbonyls with unsaturated systems (alkenes, alkynes, cyanoarenes, and N-heterocycles).
Heptafluorobutyric Acid Catalyzed Cross-Dehydrogenative Coupling of 7-Aminocoumarins with 1,2,4-Triazines: A Straightforward Pathway to 3-Triazinyl-7-aminocoumarins
Authors: Fatykhov Ramil F. , Khalymbadzha Igor A. , Sharapov Ainur D. , Potapova Anastasia P. , Tsmokalyuk Anton N. , Gaviko Vasiliy S.
Published: March 2024

A protocol for C–H/C–H cross-coupling reaction between 7-aminocoumarins and 1,2,4-triazines has been developed. The reaction was carried out under heptafluorobutyric acid catalysis providing products with yield up to 91%. The applicability and scope of the proposed method was demonstrated on 25 compounds containing different substituents both in the triazine ring and at the nitrogen atom of 7-aminocoumarins. The study of the reaction mechanism by EPR and radical trapping suggests that radicals are involved in this transformation.
The Impact of Pabinafusp Alfa on the Disease Burden in Hunter's Syndrome: Patient-Reported Outcomes
Authors: Martins Ana Maria , Curiati Marco Antônio , Mendes Carmen Curiati , Sakata Edna Tiemi , de Souza Carolina Fischinger Moura , Giugliani Roberto
Published: March 2024

Severe mucopolysaccharidosis type II (MPS-II) patients present with progressive mental impairment and reduced life expectancy. While current available treatment cannot cross the blood–brain barrier, the enzyme replacement therapy with pabinafusp alfa (a recombinant iduronate-2-sulfatase fused to an antihuman transferrin receptor antibody) was designed to penetrate it using transferrin receptor-mediated transcytosis. In this cross-sectional retrospective study, we aimed to report the impact of this new therapy using patient-reported outcomes. Data were collected using standardized questionnaire replied by patients or their caregivers (as proxies). Nine patients received intravenous administration of pabinafusp alfa for at least 104 weeks. All patient showed improvements in behavior (mainly aggressiveness), speech, motor ability, muscle strength, facial expression, breathing, and cognitive skills. Gait improvement was also found in 78% of participants. Caregivers also reported improvements in emotion demonstration as ability to smile, establish eye contact, and give hugs. Collectively, our results indicate a positive impact of pabinafusp alfa on quality of life of individuals with MPS-II and their relatives/caregivers. Future studies are warranted to elucidate the mechanisms underlying these beneficial effects.
An Overview of the Synthesis of Hexafluoroisopropanol and Its Key Intermediates
Authors: Luo Guihua , Su Weike
Published: March 2024

Hexafluoroisopropanol (HFIP, 1,1,1,3,3,3-hexafluoro-2-propanol) is a fluorine-containing alcohol, which can be used in the preparation of fluorine-containing fine chemical, pharmaceutical, and pesticide ingredient. It is a widely used solvent in organic reactions that is miscible with water and many organic reagents. Hexafluoroacetone (HFA) is a key intermediate in the synthesis of HFIP. In this work, six methods for synthesizing HFA are discussed based on the different raw materials used. In addition, three methods of synthesizing HFIP, and the applications of HFIP are also reviewed.
Variable Performance of D-dimer Testing by Hemostasis Laboratories: The Australasian/Asia-Pacific Experience
Authors: Favaloro Emmanuel J. , Arunachalam Sandya , Dean Elysse
Published: March 2024

D-dimers represent the breakdown products of fibrin. Thus, elevated plasma D-dimers will arise following a thrombotic event, such as a deep vein thrombosis or a pulmonary embolism, and therefore, a nonelevated D-dimer is used to effectively exclude such events. D-dimers are also elevated in a range of other conditions, for example, during disseminated intravascular coagulation. D-dimer levels may also be associated with prognostic value. For example, highly raised D-dimer levels can be associated with worsening clinical features in coronavirus disease 2019. Thus, D-dimer testing represents a commonly requested hemostasis test, often performed in 24/7 laboratories. Unfortunately, D-dimer testing is neither standardized nor harmonized across manufacturers or laboratories. Indeed, considering reporting units and the magnitude of units, up to 28 different combinations may be reported by laboratories. We provide updated findings for D-dimer testing in our geographic region, using recent data from the Royal College of Pathologists of Australasia Quality Assurance Programs, an international external quality assessment program, currently with over 450 participants in the D-dimer module. Data show a wide variety of assays in use and variable outcomes in reported numerical values when assessing proficiency samples. D-dimer testing mostly comprised reagents from three main manufacturing suppliers, with a small number of users of reagents from other manufacturers. Reported results showed important differences in numerical values for the same homogeneous tested samples when normalized to a single reporting unit (e.g., mg/L). Nevertheless, despite using different test reagents and reporting, most participants uniformly identified D-dimer values as below or above a “detection” cut-off for samples that were constructed to be below or above most cut-off values. As expected, mixed findings were reported for samples containing levels around expected cut-off values. We hope that our findings, reflecting on the heterogeneity of test reagents and test data, help improve diagnostic testing for D-dimer testing and facilitate harmonization and standardization, in the future.
Artificial intelligence and religious freedom: divergent paths converging on economic expansion
Authors: He Yugang
Published: March 2024

In the current era, the symbiotic relationship between artificial intelligence, religious freedom, and economic growth remains a topic of paramount importance. This study embarks on an in-depth exploration of these dynamics across 26 countries from 2000 to 2021. Utilizing the panel vector auto-regression model, the findings underscore a significant positive correlation between artificial intelligence, religious freedom, and economic growth. The forecast-error variance decomposition highlights the growing importance of both variables. It projects their increasing relevance in future economic landscapes. Furthermore, the study reaffirms the indomitable role of traditional growth drivers, specifically labor and capital inputs. The Toda-Yamamoto Granger causality analysis bolsters the validity and reliability of these findings. In summary, this research strengthens established economic paradigms and reveals new interactions, offering important implications for academics, policymakers, and stakeholders.
Consequential insights for advancing informal STEM learning and outcomes for students from historically marginalized communities
Authors: Ludwig Claudia McLaughlin , Howsmon Rebecca A. , Stromholt Shelley , Valenzuela Jacob J. , Calder Rachel , Baliga Nitin S.
Published: March 2024

Consequential STEM experiences in informal settings can address issues of equity by fully engaging historically marginalized high school students in complex socio-scientific issues. However, inclusive and effective programs are in high demand, and there is little research on what specific aspects, context, and timeframes are most important when scaling these experiences. Using a mixed method approach, this study demonstrates that students make significant gains, in the short and long term, through in-person and remote informal programs ranging between 22-h and 320-h. Progress across STEM learning constructs is attributed to authentic research experiences, students’ connections to STEM professionals, direct hands-on participation in projects, and group work. Relative to formal education settings, research-based informal STEM programs can be implemented with minimal resources, can maintain effectiveness while scaling, and work towards addressing the societal challenge of improving STEM learning and outcomes for high school students from historically marginalized communities.
Impacting life expectancies of incarcerated people through dialogic scientific gatherings and dialogic scientific workshops in prisons
Authors: Novo-Molinero Maria-Teresa , Morla-Folch Teresa , Jimenez Esteller Laureano , Molina Roldan Silvia , Gomez Gonzalez Aitor
Published: March 2024

The scientific literature has presented evidence that participants in dialogic scientific gatherings (DSGs) transform their scientific interest in science. DSGs are based on a dialogical perspective, where egalitarian dialogue and the co-creation of knowledge are the two corner pieces that allow the development of new meanings for participants, improving their scientific literacy. There is a clear gap in scientific studies regarding DSGs in prison. This is the first research to address the impact of DSG and dialogic scientific workshops in prisons. The study presents the positive impact of the DSGs and scientific activities in promoting scientific interest in incarcerated people. A communicative case study was conducted in a Catalonian (Spain) prison between February and April 2022. Nineteen males who were incarcerated aged between 29 and 44 participated in twenty-one DSGs and twelve scientific workshops following a communicative approach. Data were collected through fifteen communicative observations during the application of the DSG and eight interviews with incarcerated people and two interviews with prison workers involved in implementing the DSG. The activities conducted and analysed in this study demonstrate that bringing science closer to all people, including the traditionally excluded population, is possible. The results show that the persons who experience incarceration’s motivation to participate in these scientific activities, which fostered their awareness of and interest in science, gave meaning to their learning and transformed their interactions in and out of prison.
Evidence of grade inflation in bachelor of business administration degrees in Turkey for the period from 2002 to 2022
Authors: Karadag Engin , Dortyol Ibrahim Taylan
Published: March 2024

The study analysed the change in the proportion of business management undergraduate programme graduates in Turkey who received honours (>2.99) over the past two decades. It also investigated the factors that contribute to grade inflation and the distribution of course grades. The research employed various statistical methods, including the random effects estimator, ANOVA, t-test, and ANCOVA, to examine the GPAs and 515,739 student grades from 12,579 courses taken by 46,416 graduates of business management undergraduate programmes at 40 universities between 2002 and 2022. According to our findings, the percentage of undergraduate business management students graduating with honours (>2.99) has increased from 11% in 2002 to 56% in 2022. The most significant increases occurred in 2021 and 2022, which coincided with the COVID-19 pandemic. Our research also revealed grade inflation, with a significant increase of 28% after controlling for variables that may affect graduation grades in Turkish undergraduate business management programmes. The factors that affect course grades include the student’s gender, grade level, language of instruction, instructor title, and course content. According to our findings, it can be concluded that the rapid expansion of undergraduate business management programmes in Turkey has resulted in a decline in qualifications. This, in turn, has led to a rise in grades.
Ultra-short-term wind power forecasting based on feature weight analysis and cluster dynamic division
Authors: Chang Chen , Meng Yuyu , Huo Jiuyuan , Xu Jihao , Xie Tian
Published: March 2024

Accurate and reliable ultra-short-term wind power forecasting (WPF) is of great significance to the safe and stable operation of power systems, but the current research is difficult to balance the prediction accuracy, timeliness, and applicability at the same time. Therefore, this paper proposes a ultra-short-term WPF model based on feature weight analysis and cluster dynamic division. The model introduces an analytic hierarchy process and an entropy weight method to analyze the subjective and objective weight of the influencing features of wind power, respectively, then the subjective and objective weight ratio is determined by the quantum particle swarm optimization (QPSO) algorithm to obtain a more reasonable comprehensive weight of each feature. On this basis, it uses the K-Medoids algorithm to dynamically divide the wind power clusters into class regions by cycles. Then, the class region is used as the prediction unit to establish the TCN-BiLSTM model based on temporal convolutional networks (TCN) and bi-directional long short-term memory (BiLSTM) for training and prediction and optimizes the hyper-parameters of the model by the QPSO algorithm. Finally, the regional predictions are summed to obtain the final ultra-short-term power prediction. In addition, in order to verify the performance of the model, the actual operation data of a power field in Xinjiang, China, are selected for the example validation. The results show that the proposed model can ensure the prediction accuracy while minimizing the training time of the model and outperforms other existing methods in terms of prediction accuracy, timeliness, and applicability.
Improved reference condition independent method for output performance estimation of PV modules under varying operating conditions
Authors: Li Guorong , Zhang Yunpeng , Ma Jiao , Zhou Hai , Wu Ji , Sun Shumin , You Daning , Zhang Yuanpeng
Published: March 2024

Traditional methods for estimating output property of the photovoltaic (PV) modules are strongly influenced by the selection of reference condition and transforming equations, which determine the calculated physical parameters under real operating conditions. The differences in the carrier transport properties of PV cells under varying operating conditions, such as the number and velocity of minority carriers at the junction edge and their recombination speed, lead to large deviations in the estimation of the output characteristics, especially under low irradiance conditions. To enhance the accuracy of performance estimation, we propose an improved method that is independent of reference condition. This method eliminates the impact of reference conditions and improves the transformation equations under all irradiance levels. Transformation equations of single diode model are established in different irradiance intervals based on the dependence of physical parameter on irradiance and temperature. Especially in the low irradiance range, all effects of irradiance and temperature are considered for each physical parameter in improved transformation equations. To optimize the unknown parameters in the transformation equations, the artificial hummingbird algorithm is used to fit experimental I–V data. The experimental results of six different types PV modules under a wide range of operating conditions are used to verify the effectiveness of the proposed method. The proposed method offers immediate benefits, including independence from reference condition and a more precise relationship between physical parameters and environmental factors in the estimation of PV output properties. Comparing the results to the traditional method by Laudani, the proposed method demonstrates superior capability in estimating I–V characteristics and accurately identifies the maximum power point under various operating conditions, which is of significant value for engineering applications.
Quantifying predictive uncertainty in damage classification for nondestructive evaluation using Bayesian approximation and deep learning
Authors: Li Zi , Deng Yiming
Published: March 2024

Magnetic flux leakage (MFL), a widely used nondestructive evaluation (NDE) method, for inspecting pipelines to prevent potential long-term failures. However, during field testing, uncertainties can affect the accuracy of the inspection and the decision-making process regarding damage conditions. Therefore, it is essential to identify and quantify these uncertainties to ensure the reliability of the inspection. This study focuses on the uncertainties that arise during the inverse NDE process due to the dynamic magnetization process, which is affected by the relative motion of the MFL sensor and the material being tested. Specifically, the study investigates the uncertainties caused by sensing liftoff, which can affect the output signal of the sensing system. Due to the complexity of describing the forward uncertainty propagation process, this study compared two typical machine learning (ML)-based approximate Bayesian inference methods, convolutional neural network and deep ensemble, to address the input uncertainty from the MFL response data. Besides, an autoencoder method is applied to tackle the lack of experimental data for the training model by augmenting the dataset, which is constructed with the pre-trained model based on transfer learning. Prior knowledge learned from large simulated MFL signals can fine-tune the autoencoder model which enhances the subsequent learning process on experimental MFL data with faster generalization. The augmented data from the fine-tuned autoencoder is further applied for ML-based defect size classification. This study conducted prediction accuracy and uncertainty analysis with calibration, which can evaluate the prediction performance and reveal the relation between the liftoff uncertainty and prediction accuracy. Further, to strengthen the trustworthiness of the prediction results, the decision-making process guided by uncertainty is applied to provide valuable insights into the reliability of the final prediction results. Overall, the proposed framework for uncertainty quantification offers valuable insights into the assessment of reliability in MFL-based decision-making and inverse problems.
Manufacturing and characterization of CMOS-MEMS magnetic field microsensors with isolated cavities
Authors: Dai Ching-Liang , Zhu Zhang-Li , Chang Chun-Yi , Hsu Cheng-Chih
Published: March 2024

The study investigates a magnetic field (MF) microsensor with isolated cavities manufactured utilizing complementary metal oxide semiconductor (CMOS)-microelectromechanical system technology. This microsensor, which is a type of magnetic transistor, comprises four identical magnetic sensing elements, each featuring an emitter, a base, two collectors, and an additional collector. The magnetic transistor operates on the principles of the Lorentz force. This force is employed to modulate the electrical properties of the transistor, responding to changes in the surrounding MF. The MF microsensor chip is fabricated using the commercial CMOS process. Upon completing the CMOS process, post-processing is employed to etch the silicon substrate of the microsensor chip, generating isolated cavities on the silicon substrate. These isolated cavities effectively mitigate substrate leakage current, enhancing the sensitivity of the MF microsensor. The experimental results reveal that the sensitivity of the microsensor without isolated cavities is 60 mV T−1. In contrast, the microsensor with isolated cavities exhibits a sensitivity of 121 mV T−1. A comparison between microsensors with and without isolated cavities depicts that the sensitivity of the MF microsensor with isolated cavities doubled.
Shape-interaction dualism: unraveling complex phase behavior in triangular particle monolayers
Authors: Akimenko S S , Gorbunov V A , Myshlyavtsev A V , Myshlyavtseva M D , Podgornyi S O
Published: March 2024

This paper examines the effect of finite attractive and repulsive interactions on the self-assembly of triangular-shaped particles on a triangular lattice. The ground state analysis of the lattice model has revealed an infinite sequence of ordered structures, a phenomenon referred to as the ‘devil’s staircase’ of phase transitions. The model has been studied at finite temperatures using both the transfer-matrix and tensor renormalization group methods. The concurrent use of these two methods lends credibility to the obtained results. It has been demonstrated that the initial ordered structures of the ‘devil’s staircase’ persist at non-zero temperatures. Further increase of the attraction between particles or a decrease of the temperature induces the appearance of subsequent ordered structures of the ‘devil’s staircase’. The corresponding phase diagram of the model has been calculated. The phase behavior of our model agrees qualitatively with the phase behavior of trimesic acid adsorption layer on single crystal surfaces.
Permutation fuzzy entropy based ICEEMDAN de-noising for inertial sensors
Authors: Tian Su , Wang Chenglong , Gong Xiaoying , Huang Dingfa
Published: March 2024

As one of the critical factors affecting the accuracy of inertial navigation system (INS) positioning, random noise will lead to the accumulation of INS positioning errors, even the failure of the system. Previous studies mainly focus on achieving noise reduction by adopting either the wavelet decomposition method or some relevant methods of the empirical mode decomposition (EMD). However, the former is limited by Heisenberg’s uncertainty principle when processing non-stationary signals, and the latter exhibits numerous mode-mixing phenomena during the decomposition process. In this paper, a permutation fuzzy entropy (PFE) based improved complete ensemble EMD with adaptive noise (ICEEMDAN) de-noising method is proposed to utilize the ICEEMDAN method for signal decomposition, and the PFE as an index to distinguish the effective intrinsic mode functions (IMFs) and the noisy IMFs during the decomposition process. In addition, simulated signals with different noise levels and field data with different durations are utilized to design a group of experiments to test the de-noising performance of the PFE-based ICEEMDAN de-noising method. The experimental results demonstrate that the advantages of our proposed method consists of three main parts: (1) The ICEEMDAN method more effectively alleviates the mode-mixing problem compared to the complete ensemble EMD with adaptive noise (CEEMDAN), thereby enhancing the accuracy of inertial measurement unit (IMU) signal reconstruction; (2) the PFE is more preferable than the permutation entropy for classify IMFs decomposed by the ICEEMDAN method; (3) our proposed method can effectively reduce IMU signal noise and improve the positioning accuracy of inertial sensor.
Research on sensing characteristics of microfluidic sensor based on photonic crystal fiber
Authors: Wang Zhan , Wang Shuai , Luo Yanhua , Xue Qi , Wang PengFei , Sun XiaoHong
Published: March 2024

To address the challenges associated with sample injection into the air hole of photonic crystal fiber (PCF) and collimation, in this paper, we assemble a single-mode photonic crystal single-mode fiber structure sensor chip based on the Mach–Zehnder interference principle using microfluidic chip processing technology. The sensing principle is analyzed mathematically and the sensing characteristics are verified theoretically and experimentally. The temperature sensitivity of the sensor is −1.3325 nm °C−1, and the refractive index sensitivity is 1666.2 nm RIU−1. This structure solves the difficulty of filling and coupling PCFs. Furthermore, it introduces a novel research methodology for the design and assembly of high-performance biosensors based on PCFs.
An improvement on the electrocatalytic performance of ZIF-67 by in situ self-growing CNTs on surface
Authors: Tang Miao , Sun Jintao , Naibao Huang , Wang Bin , Ge Xiaowen , Dong Wenjing , Li Wanting , Sun Xiannian
Published: March 2024

Efficient and robust oxygen reduction reaction (ORR) catalysts are essential for the development of high-performance anion-exchange membrane fuel cells (AEMFC). To enhance the electrochemical performance of metal–organic frameworks of cobalt-based zeolite imidazolium skeleton (ZIF-67), this study reported a novel ZIF-67-4@CNT by in situ growing carbon nanotubes (CNTs) on the surface of ZIF-67 via a mild two-step pyrolysis/oxidation treatment. The electrochemical results showed that the as-prepared ZIF-67-4@CNT after CTAB modification exhibited excellent catalytic activity with good stability, with Eonset, E1/2, and Ilimit, respectively were 0.98 V (versus RHE), 0.87 V (versus RHE) and 6.04 mA cm−2@1600 rpm, and a current retention rate of about 94.21% after polarized at 0.80 V for 10 000 s, which were all superior to that of the commercial 20 wt% Pt/C. The excellent ORR catalytic performance was mainly attributed to the large amount of the in situ growing CNTs on the surface, encapsulated with a wide range of valence states of metallic cobalt.
The Kresling origami spring: a review and assessment
Authors: Masana Ravindra , Dalaq Ahmed S , Khazaaleh Shadi , Daqaq Mohammed F
Published: March 2024

Structures inspired by the Kresling origami pattern have recently emerged as a foundation for building functional engineering systems with versatile characteristics that target niche applications spanning different technological fields. Their light weight, deployability, modularity, and customizability are a few of the key characteristics that continue to drive their implementation in robotics, aerospace structures, metamaterial and sensor design, switching, actuation, energy harvesting and absorption, and wireless communications, among many other examples. This work aims to perform a systematic review of the literature to assess the potential of the Kresling origami springs as a structural component for engineering design keeping three objectives in mind: (i) facilitating future research by summarizing and categorizing the current literature, (ii) identifying the current shortcomings and voids, and (iii) proposing directions for future research to fill those voids.
Classical and quantum cost of measurement strategies for quantum-enhanced auxiliary field quantum Monte Carlo
Authors: Kiser Matthew , Schroeder Anna , Anselmetti Gian-Luca R , Kumar Chandan , Moll Nikolaj , Streif Michael , Vodola Davide
Published: March 2024

Quantum-enhanced auxiliary field quantum Monte Carlo (QC-AFQMC) uses output from a quantum computer to increase the accuracy of its classical counterpart. The algorithm requires the estimation of overlaps between walker states and a trial wavefunction prepared on the quantum computer. We study the applicability of this algorithm in terms of the number of measurements required from the quantum computer and the classical costs of post-processing those measurements. We compare the classical post-processing costs of state-of-the-art measurement schemes using classical shadows to determine the overlaps and argue that the overall post-processing cost stemming from overlap estimations scales like

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per walker throughout the algorithm. With further numerical simulations, we compare the variance behavior of the classical shadows when randomizing over different ensembles, e.g. Cliffords and (particle-number restricted) matchgates beyond their respective bounds, and uncover the existence of covariances between overlap estimations of the AFQMC walkers at different imaginary time steps. Moreover, we include analyses of how the error in the overlap estimation propagates into the AFQMC energy and discuss its scaling when increasing the system size.
Phonon heat removal from metal nanoparticles and dynamics of nanoparticle cooling at low temperatures
Authors: Bezuglyj A I , Davydov L N
Published: March 2024

The theoretical analysis of the energy relaxation of an electron–phonon system of metal nanoparticles embedded in a dielectric matrix is usually based on semiphenomenological dynamic equations for electron and phonon temperatures (two-temperature model), which does not take into account the nonthermal nature of the phonon distribution function. In this work, we use a microscopic model that describes the dynamics of the electron–phonon system of metal nanorods and metal spherical nanoparticles in terms of the kinetic equation for the phonon distribution function. We focus on the size effect in the transfer of heat from a nanoparticle to a dielectric matrix. If the dimensions of the nanoparticle are much larger than the phonon-electron mean free path, then the heat transfer is determined by the properties of the interface between the nanoparticle and the matrix. In the opposite case, heat removal is determined solely by the parameters of the electron–phonon interaction in a metal nanoparticle. The dynamics of cooling of nanoparticles is also considered and the dependence of the electron temperature on time is obtained.
Cooperative properties of multiple quantum scattering: I quantum nutation
Authors: Enaki Nicolae A
Published: March 2024

The cooperative models of the bimodal field in the multiple quantum scattering nutations are discussed and proposed for possible detections in open cavities. We proposed two types of cooperation between the converted photon processes in these multiple steps of scattering nutation in the cavity. One of them takes into consideration the cooperative process between the photons of each step of the multiple steps of Raman conversion. The second cooperative process takes place between the photons belonging to different steps of multiple scattering conversions. The proposed novel bimodal entangled sources take into consideration both the coherence and collective phenomena between the photons belonging to the system of the bimodal field obtained in multiple scattering emissions. The application of higher-order multiple Raman bimodal coherent field in quantum information is proposed.
Weibel- and non-resonant Whistler wave growth in an expanding plasma in a 1D simulation geometry
Authors: Dieckmann M E , Palodhi L , Fegan C , Borghesi M
Published: March 2024

Ablating a target with an ultraintense laser pulse can create a cloud of collisionless plasma. A density ramp forms, in which the plasma density decreases and the ion’s mean speed increases with distance from the plasma source. Its width increases with time. Electrons lose energy in the ion’s expansion direction, which gives them a temperature anisotropy. We study with one-dimensional particle-in-cell simulations the expansion of a dense plasma into a dilute one, yielding a density ramp similar to that in laser-plasma experiments and a thermal-anisotropy-driven instability. Non-propagating Weibel-type wave modes grow in the simulation with no initial magnetic field. Their magnetic field diffuses across the shock and expands upstream. Circularly polarized propagating Whistler waves grow in a second simulation, in which a magnetic field is aligned with the ion expansion direction. Both wave modes are driven by non-resonant instabilities, they have similar exponential growth rates, and they can leave the density ramp and expand into the dilute plasma. Their large magnetic amplitude should make them detectable in experimental settings.
Three-dimensional, time-dependent simulation of tapered EUV FELs with phase shifters
Authors: Kalitenko A M
Published: March 2024

In this article, we have developed and evaluated a method for obtaining extreme ultraviolet (EUV) radiation by amplifying the third harmonic of the free-electron laser (FEL) radiation using phase shifters and tapering. Simulations of self-amplified spontaneous emission (SASE) FELs and seeding schemes are presented. We have demonstrated that the combination of phase shifts and tapering results in a more efficient technique that reduces electron beam energy by half. The stability of the scheme in relation to phase shift errors has been analyzed, and the implementation of the method has been discussed. The proposed FEL design enables a decrease in facility energy and a reduction in the cost of both new and existing projects in the EUV band.
High performance Co3O4/Sn-ZnO nanocomposite photocatalyst for removal of methylene blue dye
Authors: Zena Zewdu Weldemichael , Andoshe Dinsefa Mensur , Tufa Lemma Teshome , Gemta Abebe Belay , Dejene Francis Birhanu
Published: March 2024

Methylene blue is a toxic, carcinogenic, and non-biodegradable synthetic dye discharged from factories and industries that causes severe harm to human health and environmental pollution. Therefore, in this work, Co3O4/Sn-ZnO nanocomposite was synthesized using a simple sol–gel method for efficient photocatalytic removal of methylene blue dye in an aqueous basic medium. The structural, optical, photoluminescence, morphological, and compositional properties were studied. The XRD result revealed that the crystal size increases as the full width at half maxima (FWHM) decreases when Co3O4 are coupled with Sn-ZnO. From UV-visible diffusive reflectance and photoluminescence spectroscopies, a narrowing of the band gap and a reduction of the charge carrier’s recombination rate were observed, respectively. The photocatalytic efficiency and degradation rate constant of 95.1% and 0.03251 min−1 were recorded for methylene blue dye upon the use of optimized catalyst dosage of 60 mg Co3O4/Sn-ZnO nanocomposite catalyst under an irradiation time of 100 min at room temperature for optimized pH value of 9 in an aqueous basic medium.