bluuebunny/crossref_metadata_2025 huggingface dataset:
Barrier methods based on Jordan–Hilbert algebras for stochastic optimization in spin factors
Authors: Alzalg Baha
Published: December 2023

Infinite-dimensional stochastic second-order cone programming involves minimizing linear functions over intersections of affine linear manifolds with infinite-dimensional second-order cones. However, even though there is a legitimate necessity to explore these methods in general spaces, there is an absence of infinite-dimensional counterparts for these methods. In this paper, we present decomposition logarithmic-barrier interior-point methods based on unital Jordan–Hilbert algebras for this class of optimization problems in the infinite-dimensional setting. The results show that the iteration complexity of the proposed algorithms is independent on the choice of Hilbert spaces from which the underlying spin factors are formed, and so it coincides with the best-known complexity obtained by such methods for the finite-dimensional setting. We apply our results to an important problem in stochastic control, namely the two-stage stochastic multi-criteria design problem. We show that the corresponding infinite-dimensional system in this case is a matrix differential Ricatti equation plus a finite-dimensional system, and hence, it can be solved efficiently to find the search direction.
Verändert die Einführung eines präoperativen Gerinnungsbogens die Nachblutungsrate nach Adenotomie?
Authors: Joseph Georges , Georgi Carina , Kress Peter
Published: December 2023

Einleitung Die Adenotomie (AT) stellt eine der ersten und häufigsten Operationen im Kindesalter dar. Mögliche Gerinnungsstörungen (GS) sind zum OP-Zeitpunkt häufig noch nicht diagnostiziert. Im Jahr 2006 empfahlen die Deutschen Gesellschaften für Anästhesiologie & Intensivmedizin sowie Kinder- & Jugendmedizin und HNO-Heilkunde, Kopf- und Hals-Chirurgie, im Rahmen der präoperativen Vorbereitungen für eine AT auf die routinemäßige Blutentnahme zu verzichten und stattdessen einen standardisierten Gerinnungsbogen (GB) zur Abklärung einer GS zu verwenden. Wenn hingegen Auffälligkeiten bestehen, ist die Indikation zur Gerinnungsdiagnostik (GD) indiziert.

Material und Methoden In dieser unizentrischen, nicht randomisierten, retrospektiven Studie erhielten zwischen dem 01.01.2011 und dem 31.12.2018 insgesamt 2633 Kinder zwischen dem 1. und dem 6. Lebensjahr eine AT oder Re-AT, die in die weiteren Analysen eingeschlossen wurden. Es sollte eruiert werden, ob durch die Einführung des GB im Jahr 2014 die Nachblutungsrate nach AT gesenkt werden konnte.

Ergebnisse Von den 2633 Kindern hatten 1451 einen GB und 1182 keinen GB. Es ergab sich eine Nachblutungsrate von 0,83% ohne GB und von 2,08% mit GB. 174 GB waren auffällig, und es erfolgten 169 GD, 164 hiervon waren unauffällig, 2 ergaben ein gesichertes mildes Typ-1-von-Willebrand-Syndrom (vWS) sowie 2 den V.a. ein vWS und eine den V.a. einen Faktor-VII-Mangel. Die Sensitivität des GB betrug 16% und die Spezifität 87,5%. Der positive prädiktive Wert lag bei 2,8% und der negative prädiktive Wert bei 98%.

Schlussfolgerungen Ergebnis dieser Untersuchungen war, dass der GB ein Werkzeug dafür ist, eine mögliche GS zu detektieren, jedoch nicht dafür geeignet ist, die Nachblutungsrate zu senken.
Structure-Based Drug Design for Targeting IRE1: An in Silico
Approach for Treatment of Cancer
Authors: Poustforoosh Alireza , Faramarz Sanaz , Nematollahi Mohammad Hadi , Mahmoodi Mehdi , Azadpour Mahdiyeh
Published: December 2023

Background Endoplasmic Reticulum (ER) stress and Unfolded Protein Response
(UPR) play a key role in cancer progression. The aggregation of incorrectly
folded proteins in the ER generates ER stress, which in turn activates the UPR
as an adaptive mechanism to fix ER proteostasis. Inositol-requiring enzyme 1
(IRE1) is the most evolutionary conserved ER stress sensor, which plays a
pro-tumoral role in various cancers. Targeting its’ active sites is one
of the most practical approaches for the treatment of cancers.

Objective In this study, we aimed to use the structure of 4μ8C as
a template to produce newly designed compounds as IRE1 inhibitors.

Methods Various functional groups were added to the 4μ8C, and
their binding affinity to the target sites was assessed by conducting a covalent
molecular docking study. The potential of the designed compound for further in
vitro and in vivo studies was evaluated using ADMET analysis.

Results Based on the obtained results, the addition of hydroxyl groups to
4μ8C enhanced the binding affinity of the designed compound to the
target efficiently. Compound 17, which was constructed by the addition of one
hydroxyl group to the structure of 4μ8C, can construct a strong covalent
bond with Lys907. The outcomes of ADMET analysis indicated that compound 17
could be considered a drug-like molecule.

Conclusion Our results revealed that designed compound 17 could inhibit
IRE1 activity. Therefore, this designed compound is a remarkable inhibitor of
IRE1 and introduces a promising therapeutic strategy for cancer treatment.
Maternal COVID-19 Infection Associated with Fetal Systemic Inflammatory Complications in COVID-19-Negative Neonates: A Case-Series
Authors: McKissic Devin , Perez Francisco A. , Puia-Dumitrescu Mihai , Ryan Ramah , Hendrixson D Taylor , Billimoria Zeenia , DiGeronimo Robert , Sawyer Taylor
Published: December 2023

Objective This study aimed to examine fetal and neonatal inflammatory and neurologic complications associated with maternal coronavirus disease 2019 (COVID-19) infection.

Study Design Case-series using a convenience sample of neonates cared for in a large referral-based children's hospital neonatal intensive care unit between September 2021 and May 2022.

Results We identified seven neonates with exposure to maternal severe acute respiratory syndrome related coronavirus 2 (SARS-CoV-2) and a presentation consistent with inflammatory complications. All had some degree of neurologic injury with neuroimaging findings including restricted diffusion indicating injury in the white matter, cortex, deep gray structures, and splenium of the corpus callosum as well as intracranial hemorrhage. In addition, many infants had cytopenia and abnormal coagulation studies. Placental pathology, when available, revealed inflammation, clot with calcifications, and hematomas with associated infarcts.

Conclusion Neonates born to mothers with SARS-CoV-2, even when negative for the virus themselves, may have complications consistent with a systemic inflammatory syndrome. Placental pathology as well as neurologic imaging in infants with neurologic findings may help to support this diagnosis.

Key Points
Encephalocele within the Lateral Wall of the Sphenoid Sinus Presenting with Recurrent Meningitis and Cerebrospinal Fluid Rhinorrhea Repaired via Endoscopic Transnasal Transpterygoid Approach
Authors: Masege Dipuo , Ouma John
Published: December 2023

The sphenoid sinus is an uncommon site for an encephalocele. It usually presents with cerebrospinal fluid (CSF) leak through the nasal cavity. Sternberg's canal (SC), which is a weak spot on the skull base, is one of the causes of spontaneous CSF leak. It is due to incomplete fusion of the greater wing of the sphenoid bone with the basisphenoid. Repairing these defects is challenging as the traditional external approach carries a high morbidity and a high complication rate. We present the case of a 27-year-old nonobese female patient who was diagnosed with persistent SC defect, which was repaired via an endoscopic transnasal transpterygoid approach. She has not had any recurrence following 18 months of outpatient department visits.
Age Considerations in Four-Corner Arthrodesis and Proximal Row Carpectomy: A Review
Authors: Heifner John J. , Karadimas Thomas , DeVito Paul M. , Gomez Osmanny , Kolovich Gregory P.
Published: December 2023

Purpose Although indications for four-corner arthrodesis (4CA) and proximal row carpectomy (PRC) are not completely aligned, the surgeon is often tasked with deciding between these options which vary in the surgical technique and complication profile. Patient age is often discussed as a determining factor for treatment; however, outcome data for these procedures are rarely stratified by patient age. Our objective was to perform a systematic review on the age-specific outcomes for 4CA and PRC.

Materials and Methods A PubMed database search for 4CA and PRC was performed according to Preferred Reporting Items for Systematic Reviews and Meta-analysis guidelines. The inclusion criteria required individual case reporting of patient age, surgical intervention, and appropriate outcome measures. The data were stratified by procedure and by patients older and younger than 45 years.

Results Within the 4CA group, the relative risk for a disabilities of the arm, shoulder, and hand (DASH) score above 30 was 1.94 (95% confidence interval, 1.1–3.67) in patients over 45 years compared with patients under 45 years. Within the PRC group, grip strength as a percentage of the contralateral side was higher in the over 45 age group (mean 75%) compared to the under 45 age group (mean 61%) but did not reach the level of significance.

Conclusion Despite satisfactory results for 4CA in aggregate, the distribution of scores indicates the need for setting expectations when treating younger adult patients with 4CA. The current results demonstrate increased disability based on DASH score following 4CA in patients under 45 years compared with patients over 45 years. Although outcomes were comparable between younger and older adults following PRC, recovery of grip strength may occur less frequently in younger adults.

Level of evidence IV systematic review.
Collagen Application in Pediatric Superficial Burns: The Right Time!
Authors: Fidvi Al-Iqyan Juzar , Patil Surendra Kumar , Baraskar Aniket Jaiprakash , Jadhav Ganesh Deepak , Kankam Adarsh Kumar
Published: December 2023

Introduction Delayed presentation of burn patients, in a developing country with the patient being referred from one center to another higher one, is a common occurrence. Efficient management of such delayed burn wounds thus becomes critical to decrease the morbidity of the patient within economic constraints. The advantages of collagen dressing are numerous. However, there is scarce literature on the timing of its application. Traditionally, it is thought that collagen sheets should be applied within 24 hours of burns as the wound is still sterile. This thus becomes ironical as patients are presenting late. Hence, we studied retrospectively the result of collagen application in delayed presentation of burns.

Methods A retrospective study was conducted in which records of pediatric patients of less than 10 years with less than 30% total body surface area scald burns were considered. Collagen dressing was done in all these patients. Presentation time from burns, timing of collagen application, status of wound at various check dresses, complication of burn wound, and total healing times were recorded. Appropriate statistical formulas were used to calculate significance levels for continuous and categorical variables.

Result Fifty-three patients, 33 male and 20 female were studied. The most common cause of scald was hot water spillage from baths and cooking, with the anterior trunk being the most involved site. The mean time of presentation of the patient from burns is 71.74 hours and that of collagen application was 76.4 hours. Fourteen (25.4%) patients had wound complications in the form of soakage, fever, and pus. Eight patients had their collagen removed. The average healing time for patients with intact collagen was 12.15 days and that for those on daily dressing was 21.9 days.

Conclusion Collagen should be preferred even when the patient presents after 24 hours of burns. A thoroughly washed wound is a necessary prerequisite before collagen application. Burn patients presenting after 3 days have a higher incidence of wound infection. No such time stamp of application of collagen sheets within 24 hours can thus be given for its use as the advantages of adhered and successful collagen dressings outweigh those on daily dressings.
High-speed metasurface modulator using perfectly absorptive bimodal plasmonic resonance
Authors: Zhang Jiaqi , Kosugi Yuji , Ogasawara Makoto , Ariu Koto , Otomo Akira , Yamada Toshiki , Nakano Yoshiaki , Tanemura Takuo
Published: December 2023

Free-space electro-optic (EO) modulators operating at gigahertz and beyond are attractive for a wide range of emerging applications, including high-speed imaging, free-space optical communication, microwave photonics, and diffractive computing. Here, we experimentally demonstrate a high-speed plasmonic metasurface EO modulator operating in a near-infrared wavelength range with a gigahertz modulation bandwidth. To achieve efficient intensity modulation of reflected light from an ultrathin metasurface layer, we utilize the bimodal plasmonic resonance inside a subwavelength metal–insulator–metal grating, which is precisely tuned to satisfy the critical coupling condition. As a result, perfect absorption of −27 dB (99.8%) and a high quality (Q) factor of 113 are obtained at a resonant wavelength of 1650 nm. By incorporating an EO polymer inside the grating, we achieve a modulation depth of up to 9.5 dB under an applied voltage of ±30 V. The 3-dB modulation bandwidth is confirmed to be 1.25 GHz, which is primarily limited by the undesired contact resistance and the output impedance of the driver. Owing to the high electrical conductivity of metallic gratings and a compact device structure with a minimal parasitic capacitance, the demonstrated device can potentially operate at several tens of gigahertz, which opens up exciting opportunities for ultrahigh-speed active metasurface devices in various applications.
Collisionless shock acceleration of protons in a plasma slab produced in a gas jet by the collision of two laser-driven hydrodynamic shockwaves
Authors: Marquès J.-R. , Lancia L. , Loiseau P. , Forestier-Colleoni P. , Tarisien M. , Atukpor E. , Bagnoud V. , Brabetz C. , Consoli F. , Domange J. , Hannachi F. , Nicolaï P. , Salvadori M. , Zielbauer B.
Published: December 2023

We have recently proposed a new technique of plasma tailoring by laser-driven hydrodynamic shockwaves generated on both sides of a gas jet [Marquès et al., Phys. Plasmas 28, 023103 (2021)]. In a continuation of this numerical work, we study experimentally the influence of the tailoring on proton acceleration driven by a high-intensity picosecond laser in three cases: without tailoring, by tailoring only the entrance side of the picosecond laser, and by tailoring both sides of the gas jet. Without tailoring, the acceleration is transverse to the laser axis, with a low-energy exponential spectrum, produced by Coulomb explosion. When the front side of the gas jet is tailored, a forward acceleration appears, which is significantly enhanced when both the front and back sides of the plasma are tailored. This forward acceleration produces higher-energy protons, with a peaked spectrum, and is in good agreement with the mechanism of collisionless shock acceleration (CSA). The spatiotemporal evolution of the plasma profile is characterized by optical shadowgraphy of a probe beam. The refraction and absorption of this beam are simulated by post-processing 3D hydrodynamic simulations of the plasma tailoring. Comparison with the experimental results allows estimation of the thickness and near-critical density of the plasma slab produced by tailoring both sides of the gas jet. These parameters are in good agreement with those required for CSA.
Unsupervised embedding of trajectories captures the latent structure of scientific migration
Authors: Murray Dakota , Yoon Jisung , Kojaku Sadamori , Costas Rodrigo , Jung Woo-Sung , Milojević Staša , Ahn Yong-Yeol
Published: December 2023

Human migration and mobility drives major societal phenomena including epidemics, economies, innovation, and the diffusion of ideas. Although human mobility and migration have been heavily constrained by geographic distance throughout the history, advances, and globalization are making other factors such as language and culture increasingly more important. Advances in neural embedding models, originally designed for natural language, provide an opportunity to tame this complexity and open new avenues for the study of migration. Here, we demonstrate the ability of the model word2vec to encode nuanced relationships between discrete locations from migration trajectories, producing an accurate, dense, continuous, and meaningful vector-space representation. The resulting representation provides a functional distance between locations, as well as a “digital double” that can be distributed, re-used, and itself interrogated to understand the many dimensions of migration. We show that the unique power of word2vec to encode migration patterns stems from its mathematical equivalence with the gravity model of mobility. Focusing on the case of scientific migration, we apply word2vec to a database of three million migration trajectories of scientists derived from the affiliations listed on their publication records. Using techniques that leverage its semantic structure, we demonstrate that embeddings can learn the rich structure that underpins scientific migration, such as cultural, linguistic, and prestige relationships at multiple levels of granularity. Our results provide a theoretical foundation and methodological framework for using neural embeddings to represent and understand migration both within and beyond science.
Engineering contact curved interface with high-electronic-state active sites for high-performance potassium-ion batteries
Authors: Li Xuan , Wang Yaxin , Wu Junxiong , Tong Lijuan , Wang Shuling , Li Xiaoyan , Li Chuanping , Wang Manxi , Li Manxian , Fan Weiwei , Chen Xiaochuan , Chen Qinghua , Wang Guoxiu , Chen Yuming
Published: December 2023

Potassium-ion batteries (PIBs) have attracted ever-increasing interest due to the abundant potassium resources and low cost, which are considered a sustainable energy storage technology. However, the graphite anodes employed in PIBs suffer from low capacity and sluggish reaction kinetics caused by the large radius of potassium ions. Herein, we report nitrogen-doped, defect-rich hollow carbon nanospheres with contact curved interfaces (CCIs) on carbon nanotubes (CNTs), namely CCI-CNS/CNT, to boost both electron transfer and potassium-ion adsorption. Density functional theory calculations validate that engineering CCIs significantly augments the electronic state near the Fermi level, thus promoting electron transfer. In addition, the CCIs exhibit a pronounced affinity for potassium ions, promoting their adsorption and subsequently benefiting potassium storage. As a result, the rationally designed CCI-CNS/CNT anode shows remarkable cyclic stability and rate capability. This work provides a strategy for enhancing the potassium storage performance of carbonaceous materials through CCI engineering, which can be further extended to other battery systems.
HEI10 is subject to phase separation and mediates RPA1a degradation during meiotic interference-sensitive crossover formation
Authors: Wang Tianyi , Wang Hongkuan , Lian Qichao , Jia Qian , You Chenjiang , Copenhaver Gregory P. , Wang Cong , Wang Yingxiang
Published: December 2023

Reciprocal exchanges of DNA between homologous chromosomes during meiosis, or crossovers (COs), shuffle genetic information in gametes and progeny. In many eukaryotes, the majority of COs (class I COs) are sensitive to a phenomenon called interference, which influences the occurrence of closely spaced double COs. Class I COs depend on a group of factors called ZMM (Zip, Msh, Mer) proteins including HEI10 (Human Enhancer of Invasion-10). However, how these proteins are recruited to class I CO sites is unclear. Here, we show that HEI10 forms foci on chromatin via a liquid–liquid phase separation (LLPS) mechanism that relies on residue Ser70. A HEI10
S70F
allele results in LLPS failure and a defect in class I CO formation. We further used immunoprecipitation–mass spectrometry to identify RPA1a (Replication Protein A 1) as a HEI10 interacting protein. Surprisingly, we find that RPA1a also undergoes phase separation and its ubiquitination and degradation are directly regulated by HEI10. We also show that HEI10 is required for the condensation of other class I CO factors. Thus, our results provide mechanistic insight into how meiotic class I CO formation is controlled by HEI10 coupling LLPS and ubiquitination.
Infectious virus shedding duration reflects secretory IgA antibody response latency after SARS-CoV-2 infection
Authors: Miyamoto Sho , Nishiyama Takara , Ueno Akira , Park Hyeongki , Kanno Takayuki , Nakamura Naotoshi , Ozono Seiya , Aihara Kazuyuki , Takahashi Kenichiro , Tsuchihashi Yuuki , Ishikane Masahiro , Arashiro Takeshi , Saito Shinji , Ainai Akira , Hirata Yuichiro , Iida Shun , Katano Harutaka , Tobiume Minoru , Tokunaga Kenzo , Fujimoto Tsuguto , Suzuki Michiyo , Nagashima Maki , Nakagawa Hidenori , Narita Masashi , Kato Yasuyuki , Igari Hidetoshi , Fujita Kaori , Kato Tatsuo , Hiyama Kazutoshi , Shindou Keisuke , Adachi Takuya , Fukushima Kazuaki , Nakamura-Uchiyama Fukumi , Hase Ryota , Yoshimura Yukihiro , Yamato Masaya , Nozaki Yasuhiro , Ohmagari Norio , Suzuki Motoi , Saito Tomoya , Iwami Shingo , Suzuki Tadaki
Published: December 2023

Infectious virus shedding from individuals infected with severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) is used to estimate human-to-human transmission risk. Control of SARS-CoV-2 transmission requires identifying the immune correlates that protect infectious virus shedding. Mucosal immunity prevents infection by SARS-CoV-2, which replicates in the respiratory epithelium and spreads rapidly to other hosts. However, whether mucosal immunity prevents the shedding of the infectious virus in SARS-CoV-2-infected individuals is unknown. We examined the relationship between viral RNA shedding dynamics, duration of infectious virus shedding, and mucosal antibody responses during SARS-CoV-2 infection. Anti-spike secretory IgA antibodies (S-IgA) reduced viral RNA load and infectivity more than anti-spike IgG/IgA antibodies in infected nasopharyngeal samples. Compared with the IgG/IgA response, the anti-spike S-IgA post-infection responses affected the viral RNA shedding dynamics and predicted the duration of infectious virus shedding regardless of the immune history. These findings highlight the importance of anti-spike S-IgA responses in individuals infected with SARS-CoV-2 for preventing infectious virus shedding and SARS-CoV-2 transmission. Developing medical countermeasures to shorten S-IgA response time may help control human-to-human transmission of SARS-CoV-2 infection and prevent future respiratory virus pandemics.
A meta-analytic review of morphological priming in Semitic languages
Authors: Xu Lily , Solá-Llonch Elizabeth , Wang Huilei , Sundara Megha
Published: December 2023

Two types of discontinuous morphemes are thought to be the basic building blocks of words in Semitic languages:
roots and templates. However, the role of these morphemes in lexical access and representation is debated. Priming experiments,
where reaction times to target words are predicted to be faster when preceded by morphologically-related primes compared to
unrelated control primes, provide conflicting evidence bearing on this debate. We used meta-analysis to synthesise the findings
from 229 priming experiments on 4710 unique Semitic speakers. With Bayesian modelling of the aggregate effect sizes, we found
credible root and template priming in both nouns and verbs in Arabic and Hebrew. Our results show that root priming effects can be
distinguished from the effects of overlap in form and meaning. However, more experiments are needed to determine if template
priming effects can be distinguished from overlap in form and morphosyntactic function.
Data-driven approach for prediction of band diagram of locally resonant sonic crystal
Authors: Karthik R , Barathula Sreeram , Srinivasan K
Published: December 2023

The present study focuses on the prediction of the band diagram of locally resonance sonic crystal (LRSC) using machine learning models from structural, lattice material parameters. The data set for the study is generated from the numerical simulations of LRSC for wide ranges of structural, lattice material parameters using COMSOL multiphysics solver. Three machine learning algorithms namely, support vector machine (SVM), artificial neural network (ANN), and random forest regression (RFR), are employed for the study. A total of 23040 samples are simulated and included in the training of the models. Hyperparameter tuning and data set size optimization are carried out to find the optimum machine learning model given the minimum required data set. The R2 score, root mean square error (RMSE), computational time, and inference time are used to evaluate the performance of machine learning algorithms. The feature importance scores and partial dependence plots (PDPs) are used to understand each input feature’s critical role in predicting the band diagram. Among all the machine learning models studied, RFR outperformed the ANN and SVM models. RFR with 50 decision trees performed well. However, RFR with 10 decision trees also performed well with slight higher RMSE offering lower inference time compared to RFR with 50 decision trees. Due to the importance of the first two band gaps in noise attenuation, the width and center frequency of the first two bandgaps are predicted through the band diagram. The feature importance scores and PDPs of RFR models show that the structural and lattice parameters play a crucial role in predicting the first and second bandgap, aligning with physical significance.
A MCKF-based cascade vector tracking method designed for ship navigation
Authors: Liu Wei , Ma Panting , Hu Yuan , Wang Xingdi , Hsieh Tsung-Hsuan , Han Bing , Wang Shengzheng
Published: December 2023

In ship navigation, the most widely used technology is global navigation satellite systems (GNSS), which provide the ship’s position and velocity continuously over a period of time. However, when ships are blocked by port buildings or bridges, the quality of signals received from shipborne GNSS receivers may be reduced, resulting in inaccurate ship positioning that poses a risk to navigational safety. In an occluded environment, the measurement process during the signal processing of shipborne GNSS receivers is nonstationary and prone to measurement anomalies, which can contaminate measurement noise with outliers. To address this problem, a cascaded non-coherent vector tracking loop is designed, with the maximum correntropy Kalman filter serving as a cascaded carrier/code pre-filter for shipborne GNSS receivers. The measurement noise covariance matrix of the pre-filter is adaptively calculated and corrected using the carrier-to-noise ratio and the maximum correntropy criterion, respectively. The algorithm proposed is more sensitive to outliers than the traditional tracking methods and can effectively solve the state estimation problem under the condition of measurement anomalies. Specifically, the algorithm offers ships with more precise position and velocity estimations and lower signal tracking errors than traditional tracking methods under both static and dynamic conditions, as demonstrated by shipboard experiments. The horizontal positioning is increased by 88.4% and the horizontal velocity error is reduced by 62.1% in the occluded environment under dynamic conditions.
Ab initio study of the processes of nitrogen functionalisation in graphene
Authors: Malenfant-Thuot Olivier , Morinière Maxime , Côté Michel
Published: December 2023

Nitrogen functionalisation of graphene is studied with the help of ab initio electronic structure methods. Both static formation energies and energy barriers obtained from nudged elastic band calculations are considered. If carbon defects are present in the graphene structure, low energy barriers on the order of 0.5 eV were obtained to incorporate nitrogen atoms inside the sheet. For defect-free graphene, much larger barriers in the range of 3.70–4.38 eV were found, suggesting an external energy source is required to complete this type of incorporation.
Variable RBE in proton radiotherapy: a comparative study with the predictive Mayo Clinic Florida microdosimetric kinetic model and phenomenological models of cell survival
Authors: Parisi Alessio , Beltran Chris J. , Furutani Keith M.
Published: December 2023

Objectives. (1) To examine to what extent the cell- and exposure- specific information neglected in the phenomenological proton relative biological effectiveness (RBE) models could influence the computed RBE in proton therapy. (2) To explore similarities and differences in the formalism and the results between the linear energy transfer (LET)-based phenomenological proton RBE models and the microdosimetry-based Mayo Clinic Florida microdosimetric kinetic model (MCF MKM). (3) To investigate how the relationship between the RBE and the dose-mean proton LET is affected by the proton energy spectrum and the secondary fragments. Approach. We systematically compared six selected phenomenological proton RBE models with the MCF MKM in track-segment simulations, monoenergetic proton beams in a water phantom, and two spread-out Bragg peaks. A representative comparison with in vitro data for human glioblastoma cells (U87 cell line) is also included. Main results. Marked differences were observed between the results of the phenomenological proton RBE models, as reported in previous studies. The dispersion of these models’ results was found to be comparable to the spread in the MCF MKM results obtained by varying the cell-specific parameters neglected in the phenomenological models. Furthermore, while single cell-specific correlation between RBE and the dose-mean proton LET seems reasonable above 2 keV μm−1, caution is necessary at lower LET values due to the relevant contribution of secondary fragments. The comparison with in vitro data demonstrates comparable agreement between the MCF MKM predictions and the results of the phenomenological models. Significance. The study highlights the importance of considering cell-specific characteristics and detailed radiation quality information for accurate RBE calculations in proton therapy. Furthermore, these results provide confidence in the use of the MCF MKM for clonogenic survival RBE calculations in proton therapy, offering a more mechanistic approach compared to phenomenological models.
Integro-differential equations implicated with Caputo-Hadamard derivatives under nonlocal boundary constraints
Authors: Hammad Hasanen A , Aydi Hassen , Kattan Doha A
Published: December 2023

The goal of this work is to derive a new type of fractional system that arises from the combination of the Caputo-Hadamard derivative with the integro-differential equation. Also, the existence and uniqueness of solutions to this problem have been studied under nonlocal boundary conditions. Moreover, Hyer-Ulam stability has been studied for the considered problem. Finally, to reinforce the theoretical results and provide applications for our paper, two supporting examples have been emphasized.
Single photon hybrid quantum key distribution
Authors: Ferro Laryssa F , Avelar Ardiley T , Cardoso Wesley B , Gomes Rafael M
Published: December 2023

In this work, we propose a quantum key distribution protocol using the polarization and transverse spatial degrees of freedom of single photons. We show that the protocol is secure and easy to implement experimentally, thus being able to be used in investigations on optical communication. In addition, we show that the information transmitted between two separate parties is always greater than the information retained by a eavesdropper. In this way, it is always possible to employ classical error correction and privacy amplification to minimize eavesdropper information.
MIM plasmonic sensors based on single-side ring cavity with one stub and their applications
Authors: Sun Yiping , Qu Desheng , Wu Qiaohua , Li Chunlei
Published: December 2023

A plasmonic sensor is proposed, comprising a metal–insulator–metal (MIM) straight waveguide and a ring cavity with one stub (RCS). Using the finite element method, its transport properties are simulated and systematically analyzed. By optimizing the structure parameters, the sensor obtains the maximum sensitivity (S) of 2010 nm/RIU and the maximum figure of merit (FOM) of 49219.04 RIU−1. It demonstrates a sensing resolution (SR) of 4.98 × 10−7 RIU in the detection of refractive index variation. Based on the optimized parameters, temperature sensing is investigated utilizing Polydimethylsiloxane (PDMS) as the temperature-sensitive medium, and the temperature sensitivity is found to be −0.90 nm/°C. In addition, multiple independently tunable resonances are achieved by adding a ring cavity (RC) above the straight waveguide. This derived structure enables the simultaneous detection of electrolyte samples (Na+ and K+) in blood with bio-sensing sensitivities reaching 0.1833 nm·dL/mg and 0.2 nm·dL/mg. These results have directive significance for the development of multifunctional and ultra-compact plasmonic sensor.
A novel adaptive synchronization algorithm for a general class of fractional-order complex-valued systems with unknown parameters, and applications to circuit realization and color image encryption
Authors: Shoreh A A-H , Mahmoud Gamal M
Published: December 2023

This article proposes an adaptive synchronization (AS) algorithm to synchronize a general class of fractional-order complex-valued systems with completely unknown parameters, which may appear in physical and engineering problems. The analytical and theoretical concepts of the algorithm rely on the mathematical framework of the Mittag-Leffler global stability of fractional-order systems. A specific control system is established analytically based on the fractional-order adaptive laws of parameters, and the corresponding numerical results are executed to verify the accuracy of the AS algorithm. The proposed synchronization method is evaluated using the fractional-order complex Rabinovich system as an attractive example. The electronic circuits of the new system with different fractional orders are designed. By utilizing the Multisim electronic workbench software, various chaotic/hyperchaotic behaviors have been observed, and a good agreement is found between the numerical results and experimental simulation. In addition, the approximation of the transfer function for different fractional-order are presented. And the corresponding resistor and capacitor values in the chain ship model (CSM) are estimated, which can be utilized in designing electronic circuits for other fractional-order systems. Furthermore, two strategies for encrypting color images are proposed using the AS algorithm and fractional-order adaptive laws of parameters. In the first strategy, the color image is treated as a single package and divided into two vectors. The first vector is embedded into transmitter parameters, while the second vector is injected into the transmitter state signals. In the second strategy, the primary RGB channel components of the original color image are extracted and separated into two vectors, and the same process is followed as in the first strategy. These strategies complicate the decryption task for intruders. Different scales of white Gaussian noise are added to color images to examine the robustness of the proposed color images encryption strategies.
Emergent Unparticles Dark Energy can restore cosmological concordance
Authors: Ben-Dayan Ido , Kumar Utkarsh
Published: December 2023

Addressing the discrepancy between the late and early time measurements of the Hubble parameter, H
0, and the so-called S
8 parameter has been a challenge in precision cosmology. Several models are present to address these tensions, but very few of them can do so simultaneously. In the past, we have suggested Banks-Zaks/Unparticles as an emergent Dark Energy model, and claimed that it can ameliorate the Hubble tension. In this work, we test this claim, and perform a likelihood analysis of the model and its parameters given current data, and compare it to ΛCDM. The model offers a possible resolution of Hubble tension and softens the Large Scale Structure (LSS) tension without employing a scalar field or modifying the gravitational sector. Our analysis shows a higher value of H
0 ∼ 70 – 73 km/sec/Mpc and a slightly lower value of S
8 for certain combinations of data sets. Consideration of Planck CMB data combined with the Pantheon sample and SH0ES priors lowers the H
0 and S
8 tension to 0.96σ and 0.94σ respectively with best-fit Δχ
2 ≈ -11 restoring cosmological concordance. Significant improvement in the likelihood persists for other combinations of data sets as well. Evidence for the model is given by inferring one of its parameters to be x
0 ≃ -4.46.
The improvement in the fit is driven by the inclusion of the SH0ES prior. In its absence most of the improvement is due to larger error bars in the Emergent Unparticles Dark Energy model.
Dynamic modeling of cavitation bubble clusters: Effects of evaporation, condensation, and bubble–bubble interaction
Authors: Xu 许 Long 龙 , Yao 姚 Xin-Rui 昕锐 , Shen 沈 Yang 阳
Published: December 2023

We present a dynamic model of cavitation bubbles in a cluster, in which the effects of evaporation, condensation, and bubble–bubble interactions are taken into consideration. Under different ultrasound conditions, we examine how the dynamics of cavitation bubbles are affected by several factors, such as the locations of the bubbles, the ambient radius, and the number of bubbles. Herein the variations of bubble radius, energy, temperature, pressure, and the quantity of vapor molecules are analyzed. Our findings reveal that bubble–bubble interactions can restrict the expansion of bubbles, reduce the exchange of energy among vapor molecules, and diminish the maximum internal temperature and pressure when bursting. The ambient radius of bubbles can influence the intensities of their oscillations, with clusters comprised of smaller bubbles creating optimal conditions for generating high-temperature and high-pressure regions. Moreover, an increase in the number of bubbles can further inhibit cavitation activities. The frequency, pressure and waveform of the driving wave can also exert a significant influence on cavitation activities, with rectangular waves enhancing and triangular waves weakening the cavitation of bubbles in the cluster. These results provide a theoretical basis for understanding the dynamics of cavitation bubbles in a bubble cluster, and the factors that affect their behaviors.
Effect of overheating-induced minor addition on Zr-based metallic glasses
Authors: Yang 杨 Fu 福 , Bo 薄 Zhenxing 振兴 , Huang 黄 Yao 瑶 , Wang 王 Yutian 雨田 , Sun 孙 Boyang 博阳 , Lu 鲁 Zhen 振 , Sun 孙 Baoan 保安 , Liu 柳 Yanhui 延辉 , Wang 汪 Weihua 卫华 , Pan 潘 Mingxiang 明祥
Published: December 2023

Melt treatment is well known to have an important influence on the properties of metallic glasses (MGs). However, for the MGs quenched from different melt temperatures with a quartz tube, the underlying physical origin responsible for the variation of properties remains poorly understood. In the present work, we systematically studied the influence of melt treatment on the thermal properties of a Zr50Cu36Al14 glass-forming alloy and unveiled the microscopic origins. Specifically, we quenched the melt at different temperatures ranging from 1.1T
l to 1.5T
l (T
l is the liquidus temperature) to obtain melt-spun MG ribbons and investigated the variation of thermal properties of the MGs upon heating. We found that glass transition temperature, T
g, increases by as much as 36 K, and the supercooled liquid region disappears in the curve of differential scanning calorimetry when the melt is quenched at a high temperature up to 1.5T
l. The careful chemical analyses indicate that the change in glass transition behavior originates from the incorporation of oxygen and silicon in the molten alloys. The incorporated oxygen and silicon can both enhance the interactions between atoms, which renders the cooperative rearrangements of atoms difficult, and thus enhances the kinetic stability of the MGs.
Power generation Technology of condensed water Temperature Differences in central air conditioning
Authors: Li Chenchen , Guo Changbao
Published: December 2023

With the rapid development of modern society, the improvement of people’s requirements for living comfort makes the utilization rate of central air conditioning in civil buildings and industrial plants greatly improved. The research and development of energy-saving technology under “double carbon” has also been paid attention to. As a hot new energy technology in recent years, thermoelectric power generation technology can improve the efficiency of old energy and be used in acquiring renewable energy, which is widely a concern by researchers. And central air conditioning in the summer operation of the condensate water still has much cold capacity not used. Therefore, the purpose of this study is to use the temperature difference between the low-temperature condensed water of central air conditioning and the external high temperature of the environment to achieve the purpose of energy saving and emission reduction.
Configuration and Robust Optimization Method of Energy Storage Capacity on the User Side of Power Grid Based on Improved Grey Wolf Algorithm
Authors: Hu Yuou , Zhang Jing , Cui Fubo , Wang Yimeng , Xu Yijing , Zhu Yanan
Published: December 2023

The configuration and optimization of energy storage capacity on the user side of the power grid are currently active research areas in the power system. This article presents a method that utilizes an enhanced Grey Wolf algorithm to address the issues of configuring and optimizing energy storage capacity on the user side. The Grey Wolf algorithm is improved by incorporating differential evolution and calculating the fitness value. Based on this, the objective function for the configuration model of user-side energy storage capacity is established, considering the uncertainty parameters as uncertainty set to achieve robust optimization. The design of the method for user-side energy storage capacity configuration and robust optimization, utilizing the improved Grey Wolf algorithm, is accomplished. The experimental results confirm the practicality of the proposed method.
Design and Optimization of Complex High-Frequency Electromagnetic Treatment Cavity
Authors: Qin Chunyu , Wang Dongqiang , Li Gangsheng , Dong Xuewu , Jiang Haiqin
Published: December 2023

High-frequency electromagnetic water treatment devices play a crucial role in the scale inhibition and fouling control process of industrial water treatment. They are widely used in various factories and can be classified into coaxial treatment cavities and coil-wound treatment cavities. To address the issues of low energy distribution at the edge of the coaxial treatment cavity and weak peak energy in the coil-wound treatment cavity, which result in unstable scale inhibition and fouling control effectiveness, this study derives a numerical calculation formula for electromagnetic energy in a complex treatment cavity based on the theories of active polarization and quasi-static field. A complex high-frequency electromagnetic water treatment device is designed using this formula, and the internal structure of the treatment cavity is visually analyzed using simulation software. Through the optimization of the complex treatment cavity’s structure, the optimal range of the anode-cathode radius ratio is determined. The research results show that the energy distribution in the complex treatment cavity is significantly higher than that in the coaxial and coil-wound cavities. This study provides theoretical and practical guidelines for the design of high-frequency electromagnetic water treatment device cavities.
Modeling and simulation of dynamic characteristics of marine PEM fuel cells
Authors: Wang Jie , Teng Xianbin , Zhu Faxin , Chen Tian , Chen Hao , Wang Yining
Published: December 2023

This paper aims to achieve stable and reliable operation of the marine PEM fuel cell systems. To accomplish this, a dynamic model that incorporates the thermodynamic electric potential and the three irreversible voltage losses of the fuel cell was established and simulated using Matlab/Simulink software based on the steady-state model of the PEM fuel cell. Under certain ideal conditions, the dynamic response of the PEM fuel cell was simulated and analyzed concerning various environmental factors and internal parameters of the fuel cell stack. An input signal source was used as an applied load for this purpose. The simulations and analysis focused on examining the impact of each factor on the performance of the PEM fuel cell. Specifically, the dynamic response is investigated when the load signal undergoes a step change. In addition to enhancing the drawbacks of the conventional steady-state system model, which tends to be complex with redundant parameters and a large amount of data, the dynamic model also establishes a theoretical foundation for optimizing the performance of PEM fuel cells and enabling automatic control of the system.
LiCoO2 Cathode Modified With Liquid-exfoliated Graphene for High-performance Full Batteries
Authors: Nan Wenzheng
Published: December 2023

Graphene has been successfully applied for modification of LiCoO2 cathode, but finding a large-scale preparation method of high-quality graphene for commercial application remains a great challenge. In this work, we have demonstrated a facile strategy to prepare few-layer defect-free graphene. The prepared graphene performs well in application for LiCoO2 cathode in the full battery system as conductive additives. The superior conductive graphene is attached to LiCoO2 particles, and fast pathways of electronic transport in the bulk electrode and protective layer on the interface between LiCoO2 and electrolyte are constructed. The cathode with 0.35% wt% graphene displays superior rate capacity (145 mAh/g at 2C) and excellent 4.5 V high-voltage cycle performance, which can be contributed to lower internal resistance and a more stabilized interface. The graphene shows great potential in commercial applications for high-performance LiCoO2-based full batteries.
ICEEMDAN-IWOA-BiLSTM Hybrid Algorithm-based Model for Short-term Load Forecasting
Authors: Dong Enchong , Luan Wenting
Published: December 2023

Given the uncertain, random, and volatile characteristics of power load, accurate forecasting of power load becomes challenging. To address this issue, this paper proposes an optimized prediction model by using a modified Adaptive White Noise Complete Integrated Empirical Modal Decomposition Algorithm (ICEEMDAN) and the improved Whale Optimization Algorithm (IWOA) for bidirectional short-term and long-term memory networks (BiLSTM). First of all, Australian power load data is preprocessed in this study. Then, the load data is decomposed into a series of sequences by using ICEEMDAN. After that, the improved whale algorithm is employed to analyze the BiLSTM super parameter optimization. Finally, each decomposed component is input into the IWOA-BiLSTM model for load forecasting. The results demonstrate that the proposed algorithm achieves higher accuracy in power load forecasting, compared to individual benchmark models and most portfolio models, indicating its applicability and practical value.