bluuebunny/crossref_metadata_2025 huggingface dataset:
Nachbehandlung nach Knorpeltherapie am Kniegelenk – eine Empfehlung der AG Klinische Geweberegeneration der DGOU
Authors: Niethammer Thomas R. , Aurich Matthias , Brucker Peter U. , Faber Svea , Diemer Frank , Pietschmann Matthias F. , Schoch Wolfgang , Zinser Wolfgang , Müller Peter E.
Published: January 2024

Die erste Nachbehandlungsempfehlung der AG Klinische Geweberegeneration der DGOU stammt aus dem Jahr 2012. Neue wissenschaftliche Evidenz und veränderte Rahmenbedingungen machten eine
Aktualisierung der Nachbehandlungsempfehlungen nach Knorpeltherapie erforderlich.

Im Rahmen einer mehrstufigen Mitgliederbefragung wurde ein Konsensus erzielt, der gemeinsam mit der wissenschaftlichen Evidenz die Basis für die vorliegende Nachbehandlungsempfehlung
gibt.

Das maßgebliche Kriterium für die Nachbehandlung ist weiterhin die Defektlokalisation. Dabei wird zwischen femorotibialen und patellofemoralen Defekten unterschieden. Zudem werden nun auch
weiterführende Kriterien bez. der Knorpeldefekte berücksichtigt (stabiler Knorpelrand, Lage außerhalb der Hauptbelastungszone) und auf die unterschiedlichen Verfahren der Knorpeltherapie (z. B.
osteochondrale Transplantation, Minced Cartilage) eingegangen.

Die vorliegende aktualisierte Nachbehandlungsempfehlung beinhaltet unterschiedliche Aspekte der Nachbehandlung, beginnend vom frühen perioperativen Management bis zur Sportfreigabe und
Wiederaufnahme von Kontaktsport nach erfolgter Knorpeltherapie.
COVID-19 in Children with Chronic Kidney Disease; Does it Differ
Much?
Authors: Baltu Demet , Kurt-Sukur Eda Didem , Tastemel Ozturk Tugba , Gulhan Bora , Ozaltin Fatih , Duzova Ali , Topaloglu Rezan
Published: January 2024

Background COVID-19 is known to have a mild course in children, however
more data on pediatric chronic kidney disease (CKD) is needed. We aimed to
assess the incidence and severity of COVID-19 in pediatric CKD patients.

Methods A questionnaire including demographics, COVID-19 history,
symptoms, and vaccination status was applied to patients with CKD. We also
retrospectively reviewed the presentation and outcomes of SARS-CoV-2 infection
in this patient group from March 2020 to December 2021.

Results 220 patients were included, 48 were found to have experienced
COVID-19. There was no significant difference regarding age, gender, underlying
kidney disease, CKD stage, dialysis status, type or number of immunosuppressive
medications, and glomerular filtration rate between patients with and without
COVID-19. Most were infected by a household member (43.8%) and during
outpatient or inpatient care (18.8%). Four (8.3%) were
asymptomatic, and 43 (89.6%) had mild infection. Severe COVID-19 was
observed in only one patient. Eleven (22.9%) patients with COVID-19 were
previously vaccinated. Acute kidney injury was detected in 4 (8.3%); as
stage 1 in all. Median follow-up after COVID-19 was 4.6 months. All patients
fully recovered, and no renal disease flare or death was observed.

Conclusions Although the vaccination rate was low in our cohort, the
majority of the children with COVID-19 showed a mild course. Along with the
vaccination, general precautions seemed to be successful for this
population.
Computational Fluid Dynamics and Its Potential Applications for the ENT Clinician
Authors: Root Zachary T. , Schneller Aspen R. , Lepley Thomas J. , Wu Zhenxing , Zhao Kai
Published: January 2024

This article is an examination of computational fluid dynamics in the field of otolaryngology, specifically rhinology. The historical development and subsequent application of computational fluid dynamics continues to enhance our understanding of various sinonasal conditions and surgical planning in the field today. This article aims to provide a description of computational fluid dynamics, the methods for its application, and the clinical relevance of its results. Consideration of recent research and data in computational fluid dynamics demonstrates its use in nonhistological disease pathology exploration, accompanied by a large potential for surgical guidance applications. Additionally, this article defines in lay terms the variables analyzed in the computational fluid dynamic process, including velocity, wall shear stress, area, resistance, and heat flux.
Lipoxygenases regulate digestive enzyme inhibitor activities in developing seeds of field-grown soybean against the southern green stink bug (Nezara viridula)
Authors: Barneto Jésica A. , Sardoy Pedro M. , Pagano Eduardo A. , Zavala Jorge A.
Published: January 2024

Soybean (Glycine max) is the world’s most widely grown seed legume. One of the most important pests that decrease seed quality and reduce yield of soybean crops is the southern green stink bug (Nezara viridula). Insect damage triggers accumulation of defensive compounds such as protease inhibitors (PIs), isoflavonoids and reactive oxygen species, which are regulated by the lipoxygenase (LOX)-regulated jasmonic acid (JA) to stop insect feeding. This study identified and characterised the role of LOX isoforms in the modulation of chemical defences in seeds of field-grown soybean that decreased digestive enzyme activities of N. viridula after insect attack. Stink bugs attack increased LOX 1 and LOX 2 expression, and activities of LOX 1 and LOX 3 isoenzymes in developing soybean seeds. In addition, stink bug damage and methyl jasmonate application induced expression and activity of both cysteine PIs and trypsin PIs in developing soybean seeds, suggesting that herbivory induced JA in soybean seeds. High PI activity levels in attacked seeds decreased cysteine proteases and α-amylases activities in the gut of stink bugs that fed on field-grown soybean. We demonstrated that LOX isoforms of seeds are concomitantly induced with JA-regulated PIs by stink bugs attack, and these PIs inhibit the activity of insect digestive enzymes. To our knowledge, this is the first study to investigate the participation of LOX in modulating JA-regulated defences against stink bugs in seeds of field-grown soybean, and our results suggest that soybean PIs may inhibit α-amylase activity in the gut of N. viridula.
Choice of language in the construction of cultural identity by Tamil speakers in India
Authors: Eldho Elizabeth , Kumar Rajesh
Published: January 2024

Individuals in multilingual societies are associated with several culturally diverse groups, and so their cultural
identity is multifarious and subject to constant change across time and space as a result of increasing intercultural engagements.
While cultural norms are essentially embedded in one’s language, the choice of language is understood as a significant tool in
projecting the cultural identity of a linguistic community. This paper examines how language choice becomes an agency for Tamil
speakers in India to construct their cultural identity. Contextualized among native Tamil speakers in Chennai, the capital city of
the southernmost Indian state of Tamil Nadu, this study unravels the narratives by which the speakers’ specific language
preference in family, friendship, and institutional domains is used to perform identities and maintain a community consciousness.
It also examines the role of language ideologies in contributing to their choices. The study finds that despite the penetration of
English into all three domains in varying degrees, Tamil remains the ‘pride’ and the preferred language for all. This affinity is
driven by ideological discourses surrounding the cultural history of Tamizhakam, from which arise the need to
form a distinct Tamil identity.
Spectroscopic analysis of hidden-charm pentaquarks
Authors: Sharma Ankush , Upadhyay Alka
Published: January 2024

In this work, the multiquark approach is used to analyze the spectroscopy of hidden-charm pentaquark states, motivated by recent discoveries at the LHCb collaboration. Using the SU(3) flavor representation, pentaquarks having J

P
= 5/2− are arranged into 10 (decuplet) of the SU(3) flavor multiplets. The masses of pentaquarks are calculated using the extension of the Gursey–Radicati mass formula and the effective mass scheme. Also, we calculated the magnetic moments of the hidden-charm pentaquarks using the effective mass and shielded charge technique. Further, we suggested the possible production modes for J

P
= 5/2− pentaquarks from the decay of bottom baryons, which consist of pentaquark states as intermediate states. Our results for masses demonstrate reasonable agreement with the available data and our analysis for both masses and magnetic moments may be useful for future experimental studies.
GMM-based GNSS spoofing detector using double differential phase measurement
Authors: Vinh La The , Nguyen Van Hien , Van Hiep Hoang , Dinh Thuan Nguyen , Hung Pham Ngoc , Ta Tung Hai
Published: January 2024

GNSS spoofing is an intentional interference wherein a GNSS receiver tracks counterfeit signals, resulting in incorrect outcome positions. This is the most dangerous type of intervention in the GNSS technology. In this study, we introduce a novel method for detecting spoofing signals using a Gaussian mixture model (GMM) on the double-carrier phase difference (DD) created by two independent receivers. The DD can completely eliminate errors caused by the satellite clock, receiver clock, and atmospheric layers; hence, the signal angle of arrival (AoA) is clearly expressed in the DD measurement. We utilized the GMM to model the probability density function of the DD measurement computed from the phase measurement of the receivers. Theoretically, AoA values of an authentic signal change over time owing to the nature of the signal broadcast from an orbiting satellite. However, fake signals are often transmitted from the generator, resulting in a central distribution of the corresponding AoA values. Existing studies deal with the spoofing detection problem using the above theoretical assumptions. However, it is practical to broadcast spoofing signals from several sources, and random noise can be mixed into the generated phase to render the DD measurement noisy. In such complicated scenarios, existing approaches are not sufficiently robust to detect non-authentic signals. Another observation is that because real satellites are moving in fixed orbits, there should be a correlation among the AoA values of the signals coming from these satellites. In contrast, counterfeit signals (with the main purpose of causing the wrong position or noisy phase) do not follow the pattern of the real signals. Therefore, instead of using the above hard assumption about the signal AoA, we propose a statistical model GMM to learn the hidden relationship of the AoA values among real signals from different real satellites, which are then used to detect spoofing signals.
Fault diagnosis of rotating machinery using novel self-attention mechanism TCN with soft thresholding method
Authors: Ding Li , Li Qing
Published: January 2024

Rotating machinery (e.g. rolling bearings and gearboxes) is usually operated in high-risk and vulnerable environments such as time-varying loads and poor lubrication. Timely assessment of the operational status of rotating machinery is crucial to prevent damage caused by potential failure and shutdown, which significantly enhances the reliability of mechanical systems, prolongs the service life of critical components in rotating machinery, and minimizes unnecessary maintenance costs. In this regard, in this paper, a novel approach named self-attention mechanism combining time convolutional network with soft thresholding algorithm (SAM-TCN-ST) is proposed for fault intelligent recognition of rotating machinery. Specifically, the vibration signals are transformed into time-frequency graphs with distinct features utilizing the continuous wavelet transform, and then the proposed SAM-TCN-ST algorithm is employed for capturing essential data characteristics and classification performance. Eventually, datasets from rolling bearings and gearboxes are used to verify the accuracy and effectiveness of the proposed method compared with state-of-the-art benchmark networks such as pure TCN, convolutional neural networks and long short-term memory models. Experimental results demonstrate that the recognition accuracy rate of the proposed SAM-TCN-ST is higher than that obtained from the benchmark methods. This research presents an intelligent and viable solution for achieving real-time monitoring of the status and detecting faults in rotating machinery, thereby expectedly enhancing the reliability of mechanical systems. Consequently, the proposed SAM-TCN-ST algorithm holds significant potential for applications in prognostic and health management practices related to rotating machinery.
Error analysis and modeling of the racetrack magnetohydrodynamic linear motion sensor
Authors: Xu Mengjie , Mo Jiahui , Xia Chenyan , Yang Lei , Ji Feng , Chen Jingjing , Li Xingfei
Published: January 2024

Micro-vibration measurement methods for spacecraft structures mainly include the use of an accelerometer, laser, and magnetohydrodynamic (MHD) measurement methods. The micro-vibration measurement sensor developed based on the MHD measurement method has no mechanical wear between internal components, a fast high-frequency vibration response, and strong anti-interference properties. To reduce the measurement error of the racetrack MHD linear motion sensor developed in the laboratory, this paper investigated the sensor error, analysed the error source, combined the BP neural network optimized by particle swarm optimization (PSO) with variational mode decomposition (VMD), used the VMD-PSO-BP neural network to establish the error compensation model of the racetrack MHD linear motion sensor, and combined the PSO-BP neural network with wavelet threshold de-noising (WTD). The WTD-PSO-BP and RBF neural networks were used to develop the error compensation model of the racetrack MHD linear motion sensor. Comparing the three models, the experimental results show that the VMD-PSO-BP model has the best compensation effect. The mean absolute error of the output signal of the racetrack MHD linear motion sensor compensated by the VMD-PSO-BP neural network model was 1–2 times lower than that before compensation, the signal-to-noise ratio was 10 times higher on average, and the correlation coefficient was more than 0.95.
Power loss model of electromagnetic waves propagation in cell solutions by GHz electrical impedance spectroscopy
Authors: Zhang An , Liu Xiayi , Wang Zhilong , Sun Bo , Zhao Tong
Published: January 2024

The propagation of GHz electromagnetic (EM) waves across cells in cell solutions has been analytically modeled and numerically calculated in order to elucidate the power loss in the boundary between dispersed medium and cell by establishing a theoretical model. Living and dead yeast cells are chosen as objects because of the simple cell structure and ease of observation under optical microscope. Through the model, the average power density of the incident wave
S
avi
, reflected wave
S
avr
, transmitted wave
S
avt
, and ratio of the power loss ψ are calculated and compared to analyze the power loss of EM waves inside living and dead yeast cells by considering the impacts of frequency of EM wave, cell viability, concentration, and component structures of the cell. Results demonstrate decreased
S
avi, S
avr
, and
S
avt
with rising frequency, especially noticeable below 100 MHz due to enhanced absorption from cell components. EM waves in living yeast cell solutions exhibit faster attenuation and stronger reflection compared to dead yeast cells, attributed to intact organelles and membranes intensifying absorption and scattering. The increasing cells concentration further attenuates EM waves. This work elucidates propagation and power loss of EM waves in cell solutions and provides an effective computational approach to optimize EM wave based biomedical applications.
Effect of annealing temperature on structural and electrochemical behaviour on MgFe2O4 as electrode material in neutral aqueous electrolyte for supercapacitors
Authors: Palani Hema , Rastogi Ankur
Published: January 2024

Binary metal oxides possess unique structures and multiple oxidation states, making them highly valuable in electrochemical analysis. This study aims to determine the effect of annealing temperature on the electrochemical properties of magnesium ferrite when used as an electrode material in a neutral aqueous electrolyte. We utilized the sol–gel technique to synthesize the material and annealed it at various temperatures. Our analysis of the material using different characterization techniques reveals significant changes in its structural and electrochemical properties. We found that the material exhibited a range of phases, and higher annealing temperatures led to improved electrochemical properties. The electrochemical measurements showed reversible and redox pseudo-capacitance behavior, with the material annealed at 500 °C exhibiting the highest specific capacitance of 117 F g−1 at a current density of 0.5 A g−1. Capacitive and diffusion-controlled processes govern the total charge storage mechanism, and their contribution changes significantly as the annealing temperature varies. The capacitance retention of 500 °C annealed sample was 58% and it remained stable. This work establishes a correlation between annealing temperature on structural, morphological, and electrochemical behavior, thereby opening up avenues for tailoring them effectively. These findings can be useful in the development of future electrode materials for electrochemical applications.
Soft H-L back transitions by applying resonant magnetic perturbations in the low q
95 EAST plasmas
Authors: Shao L M , Chen R , Sun Y W , Wu M F , Gao W , Li K D , Li X , Jia M N , Ma Q , Meng L Y , Wang H H , Wang M R , Xu G S , Zang Q , Zhang L , Zhou C ,   the EAST Team
Published: January 2024

Controlled ‘soft’ H-L transitions with a simultaneous ramp-down of plasma density and stored energy, generated by applying resonant magnetic perturbations (n = 2 RMPs), relevant to the control of ITER terminations, are achieved in the EAST tokamak. These H-mode plasmas are run at median electron densities and a low safety factor q
95 (

q

95

=
3.5

–4.0) under neutral beam injection (NBI) dominant heating. During a slow ramp in the RMP current the internal transport barrier for the electron density collapses at the beginning and the edge transport barrier for the electron density collapses later. Before the controlled H-L back transitions, the plasma stored energy W
MHD is linearly correlated with the core line-averaged density

⟨

n

e

⟩

. These controlled H-L back transitions ensue from the collapse of the edge transport barrier and at a similar energy confinement time

τ

e

H-L

∼
48

ms. These H-L transitions are not sensitive to the NBI power but are very sensitive to the fueling rate and ramp-up rate of the RMP current.
Controlled multiple spectral hole burning via a tripod-type atomic medium
Authors: Tiaz Gul , Sadia Qureshi Haleema , Ullah Shakir , Ghafoor Fazal
Published: January 2024

In limit of saturation spectroscopy, we theoretically study the spectral hole burning (SHB) in the absorption spectrum of a probe field through a tripod atomic system. The response function for the probe field is calculated in a Doppler-broadened medium. Burning of spectral holes is observed only for the counter propagation of either one or both the coupling fields in the medium. The SHB is not observed below some critical temperature which is a condition for the electromagnetically induced transparency (EIT) in the medium. The most interesting and significant feature is that the Doppler broadening acts as a decoherence effect in case of EIT, however, the Doppler broadening acts inversely in case of SHB and consequently the burning effect enhances. The SHB is further enhanced and controlled by classes of the average velocity of atoms. The classes of high average atomic velocity in the medium increase the number of spectral hole burns (HBs). The widths of HBs can be controlled by the intensity of the driving fields. A single HB can be switched to multiple HBs in a well-controlled manner using different classes of high average atomic velocity. The various switchable holes can be burned in a desired position of the absorption spectrum which in turn simultaneously slow down multiple probe fields. The phenomenon of SHB may be useful in the construction of multichannel optical switching and storage devices.
Optimal remote restoring of quantum states in communication lines via local magnetic field
Authors: Fel’dman E B , Pechen A N , Zenchuk A I
Published: January 2024

Optimal state transport across spin chains, which are proposed as quantum wires for information transfer in solid state quantum architectures, is an important topic for quantum technologies. In this work, we study the remote restoring of a quantum state transferred along a spin chain. The structural state-restoring technique provides proportionality between the appropriate elements of the density matrices of the initial sender state and receiver state at some time instant. We develop a remote state-restoring protocol which uses an inhomogeneous magnetic field with step-wise time-dependent Larmor frequencies as the state-control tool. For simulating the multiparametric Hamiltonian we use two approximating models. First model is based on the Trotter-Suzuki method, while the second model is based on using short pulses of high intensity. In both cases we estimate the accuracy of the approximation and find the optimal restoring parameters (Larmor frequencies) of the protocol which maximize the coefficients in the proportionality for spin chains of various lengths.
Experimental study on AC loss of 1G and 2G HTS coils with an identical structure, geometry and number of turns
Authors: Zhang Yan , Yang Tianhui , Li Wenxin , Xing Yuying , Li Ning , Li Chao , Xin Ying
Published: January 2024

Devices made of High Temperature Superconductor (HTS) will suffer AC loss during AC operations, which has unnegligible influence on energy consumption, overall efficiency, cooling cost, and operational stability of the devices. In this study, comparative measurements on 1G and 2G HTS coil samples with an identical structure, geometry, and number of turns were systematically conducted with a calorimetric method at different current values (I
rmss) and frequencies (fs). The AC loss characteristics of the HTS samples were analyzed and compared based on the experimental results. The results show that eddy current and coupling play a more dominant role than magnetic hysteresis in the total AC loss of coils made of HTS tapes. The AC loss of both samples increases with I
rms and f, but the AC loss is more sensitive to I
rms than to f. Under the same conditions, the 1G coil sample has a slightly larger AC loss than the 2G one.
Damped Kadomtsev Petviashvilli equation for magnetosonic waves in a dissipative OH plasma in the ionospheric F-Layer
Authors: Tariq Z , Shah H A , Kahlon L Z , Asam M T
Published: January 2024

In this paper we study the linear and nonlinear dynamics of magnetosonic waves in a dissipative Oxygen-Hydrogen (OH) plasma. It is shown that such waves can propagate nonlinearly as solitary structures for both super and sub, acoustic and Alfvenic regimes. We use the hyperbolic tangent method to solve the collisional Kadomtsev-Petviashvili (KP) equation and obtain a damped solitary wave solution. Both compressive and rarefactive damped solitary structures are obtained and are significantly affected by the oxygen ion-neutral collision frequency, temperature, propagation angle, and ambient magnetic field present in the F-layer of Earth’s ionosphere.
Correlated noise enhances performance of joint remote state preparation in quantum multi-hop network
Authors: Zhang Zhihua , Zhang Hanchen , Shen Beining , Qiu Zhipeng
Published: January 2024

Joint remote state preparation (JRSP for short) can increase the security of quantum communication by distributing different parts of classical information to different senders. However, the communication efficiency in terms of fidelity decreases with the increase of intermediate nodes in multi-hop network. In this paper, we try to explore methods to improve fidelity of JRSP in multi-hop network presented by Zhang and Chen in 2023 Phys. Scr. 98 065107. Specifically, correlated Pauli noise with partial memory was introduced into the shared channel. We find that the fidelity increases with the increase of memory parameters, which compensates for the loss of fidelity caused by the increase of network nodes.
Application of the reproducing kernel method for solving linear Volterra integral equations with variable coefficients
Authors: Amoozad Taher , Allahviranloo Tofigh , Abbasbandy Saeid , Rostamy Malkhalifeh Mohsen
Published: January 2024

This article proposes a new approach for solving linear Volterra integral equations with variable coefficients using the Reproducing Kernel Method (RKM). This method eliminates the need for the Gram-Schmidt process. However, the accuracy of RKM is influenced by various factors, including the selection of points, bases, space, and implementation method. The main objective of this article is to introduce a generalized method based on the Reproducing Kernel, which is successful in solving a special type of singular weakly nonlinear boundary value problems (BVPs). The easy implementation, elimination of the Gram-Schmidt process, fewer calculations, and high accuracy of the present method are interesting. The conformity of numerical results, including tables and figures, with theorems related to error analysis and convergence order, confirms the practicality of the present method.
Temperature-dependent characterization of optical parameters in novel high birefringence nematic liquid crystal mixtures: an empirical investigation
Authors: Farezi Navid , Khoshsima Habib , Zakerhamidi Mohammad Sadegh , Ranjkesh Amid , Yoon Tae-Hoon
Published: January 2024

This study investigates the temperature-dependent behaviors of three novel high-birefringence (Δn) nematic liquid crystals (NLCs) with varying clearing temperatures (T

NI
). The high birefringence of the studied novel nematic liquid crystals is advantageous for LCD applications. It ensures fast response times, wide viewing angles, enhanced color reproduction, and reduced cross-talk, optimizing display performance and image quality. The goal is to characterize their order parameters (S(T)), effective geometry parameters (α
eg), normalized polarizabilities, and crossover temperatures (T

co
). Utilizing a modified four-parameter model for temperature-dependent refractive indices, we extract adjustable parameters and analyze their impact on T

co
and S(T). Three approaches, including the Vuks model, the Haller approximation model, and an effective geometry parameter-based model, are employed to assess S(T). The study focuses on four unknown parameters (A, B, (Δn)
0, and β) derived from the modified model, along with the nematic–isotropic transition temperature (T

NI
). Findings reveal that a higher absolute value for the B parameter, a smaller β parameter value, elevated T

NI
values, and increased (Δn)0 values enhance the T

co
value.
Nonlinear complex generalized zakharov dynamical system inconformal sense utilizing new kudryashov method
Authors: Secer Aydin , Bayram Mustafa , Ozdemir Neslihan , Onder Ismail , Esen Handenur , Cinar Melih , Aydin Huseyin
Published: January 2024

We take into account the nonlinear complex generalized Zakharov dynamical system which models the spread of the Langmuir waves in ionized plasma, in the conformal sense in this manuscript. Fractional wave transformation is enforced to convert the nonlinear fractional system to a nonlinear ordinary differential equation system. The new Kudryashov method which was recently introduced and is an efficient method, is implemented to the presented equation to acquire analytical solutions. The required constraint conditions are offered to ensure the validity of the obtained solutions. To analyze the physical interpretations for some of the produced solutions, we illustrate some graphical representations. We derive the bright and singular solitons. Furthermore, 2D views of the behavior of the solitons are represented to investigate the effect of the values of the parameters in the proposed model and fractional parameters. Also, the modulation instability of the model is investigated to ensure the obtained results are stable.
Not-so-efficient proton acceleration by an intense laser pulse obliquely incident on a structured target
Authors: Khan Imran , Saxena Vikrant
Published: January 2024

The interaction of an obliquely incident laser pulse with a flat TNSA target is known to enhance the cut-off energy of protons/ions as compared to a normally incident laser pulse, owing to Brunel or v × B heating. However, it is not well understood how the oblique incidence of the laser pulse would affect the protons/ion spectra in the case of a micro-structured target. Using two-dimensional particle-in-cell simulations, we show here that the protons/ions cut-off energies are rather reduced in the case of oblique incidence of the laser pulse if the target has a micron-sized groove on its front surface. This is also found to be true for a periodically grooved target.
Quasi-mode evolution in a stochastic magnetic field
Authors: Cao Mingyun , Diamond P.H.
Published: January 2024

We present a multi-scale model of quasi-mode evolution in a stochastic magnetic field. The similarity between a quasi-mode and a ballooning mode enables us to address the challenges arising from the disparate geometries in the theories of ballooning modes in the presence of resonant magnetic perturbations. We obtain useful insights into our understanding of ballooning mode dynamics in a stochastic background. To maintain quasi-neutrality at all scales, the beat between the quasi-mode and the stochastic magnetic field drives microturbulence, which drives the turbulent background that promotes mixing and damps the quasi-mode. As a result of the broad mode structure of the quasi-mode, the turbulent viscosity and the turbulent diffusivity produced by the microturbulence are larger than those in our related study on resistive interchange modes. The stochastic magnetic field can also enhance the effective plasma inertia and reduce the effective drive, thereby slowing the mode growth. A nontrivial correlation between the microturbulence and the magnetic perturbations is shown to develop. This could account for the reduction in the Jensen–Shannon complexity of pedestal turbulence in the Resonant Magnetic Perturbation Edge-Localized Mode suppression phase observed in recent experiments. Directions for future experimental and theoretical studies are suggested.
β-induced Alfvén eigenmodes and fishbone driven by energetic electrons in EAST electron heating dominant plasmas
Authors: Chao Y. , Xu L.Q. , Mai C.W. , Wu M.Q. , Duan Y.M. , Lin S.Y. , Geng K.N , Zhou C. , Hu L.Q.
Published: January 2024

β-induced Alfvén eigenmodes (e-BAE) and fishbone (e-fishbone) driven by the energetic electrons have been identified on the experimental advanced superconducting tokamak in electron cyclotron resonance heating (ECRH), low hybrid wave (LHW) together with neutral beam injection plasma and in pure radio frequency heating plasma, respectively. The e-BAE is predominantly located near the pedestal region, and its frequency typically displays a chirping characteristic. The frequency is notably associated with the count of energetic electrons with energy between 30 keV and 80 keV driven by LHW and undergoes three distinct phases. A direct correlation is established between the frequency of e-BAE and the global parameters, including electron temperature, Alfvén velocity and

β

p

. The e-fishbone emerges in the core and becomes noticeable shortly after ECRH initiation, in an electron heated dominant and core confinement enhanced discharge. Experimental analyses suggest that the e-fishbone ties closely with both the population and energy distribution of energetic electrons. These observations can provide valuable insights into the behavior of energetic electrons, which play a crucial role in the formation and sustainability of transport barriers within hybrid plasma, both in the internal and pedestal regions.
Study and development of diagnostic systems to characterise the extraction region in SPIDER
Authors: Segalini B. , Candeloro V. , Poggi C. , Berton G. , Fasolo D. , Franchin L. , Laterza B. , Magagna M. , Trevisan L. , Pasqualotto R. , Serianni G. , Tollin M. , Sartori E.
Published: January 2024

SPIDER, an RF-driven negative ion source in the Neutral Beam Test Facility (NBTF), serves as the prototype for ITER's neutral beam injector (NBI). It is composed of 8 drivers powered by 4 RF generators, aiming to accelerate 50 A of negative hydrogen ions to 100 KeV with a beam uniformity target of 10%. The experiment, launched in 2018, tested negative ion production using caesium. Results match those of similar facilities, but SPIDER faces challenges due to its size, multiple drivers, and non-uniform plasma expansion. These issues impact beam uniformity, preventing the machine from reaching expected performance. To address this, SPIDER initiated a significant shutdown at the end of 2021 for improvements.

One the most important aspects studied during the first experimental campaign is source uniformity, addressed both in terms of plasma and of caesium distribution. The latter is particularly relevant since its quality is directly related to the beam uniformity and divergence. To have more insight about these issues, monitoring the plasma properties in the extraction region is crucial, hence in the present contribution, the design and development of two new diagnostic systems are described: a movable Langmuir probe and a Retarding Field Energy Analyser (RFEA).

The first can provide a vertical scan of the main plasma parameters close to the plasma grid. The spatial resolution would improve with respect to the already installed set of fixed Langmuir probes embedded in the grid system, and the newly installed diagnostic could interact with other sensors to produce complementary measurements (namely, electron photo-detachment).
The latter, instead, allows the monitoring of the positive ion energy distribution: positive ions, in fact, can be precursors of the negative ones produced at the caesiated surface, but also influence the energy of negative ion and their extraction probability and thus collecting information about their energy distribution allows inferring details about the extracted negative ion beam.

The two diagnostics are designed focusing on the experimental constraint of integrating the diagnostics in a harsh and complex environment such as SPIDER plasma: a preliminary study of the placement inside the source is carried out, then the electrode of the movable probe and the RFEA sensor are sized according to the spatial and energy resolution requested by the system.
Effect of sampling bias on global estimates of ocean carbon export
Authors: Henson Stephanie , Bisson Kelsey , Hammond Matthew L , Martin Adrian , Mouw Colleen , Yool Andrew
Published: January 2024

Shipboard sampling of ocean biogeochemical properties is necessarily limited by logistical and practical constraints. As a result, the majority of observations are obtained for the spring/summer period and in regions relatively accessible from a major port. This limitation may bias the conceptual understanding we have of the spatial and seasonal variability in important components of the Earth system. Here we examine the influence of sampling bias on global estimates of carbon export flux by sub-sampling a biogeochemical model to simulate real, realistic and random sampling. We find that both the sparseness and the ‘clumpy’ character of shipboard flux observations generate errors in estimates of globally extrapolated export flux of up to ∼ ± 20%. The use of autonomous technologies, such as the Biogeochemical-Argo network, will reduce the uncertainty in global flux estimates to ∼ ± 3% by both increasing the sample size and reducing clumpiness in the spatial distribution of observations. Nevertheless, determining the climate change-driven trend in global export flux may be hampered due to the uncertainty introduced by interannual variability in sampling patterns.
Brain connectivity for subtypes of parkinson’s disease using structural MRI
Authors: Samantaray Tanmayee , Saini Jitender , Pal Pramod Kumar , Gupta Cota Navin
Published: January 2024

Objective. Delineating Parkinson’s disease (PD) into distinct subtypes is a major challenge. Most studies use clinical symptoms to label PD subtypes while our work uses an imaging-based data-mining approach to subtype PD. Our study comprises two major objectives - firstly, subtyping Parkinson’s patients based on grey matter information from structural magnetic resonance imaging scans of human brains; secondly, comparative structural brain connectivity analysis of PD subtypes derived from the former step. Approach. Source-based-morphometry decomposition was performed on 131 Parkinson’s patients and 78 healthy controls from PPMI dataset, to derive at components (regions) with significance in disease and high effect size. The loading coefficients of significant components were thresholded for arriving at subtypes. Further, regional grey matter maps of subtype-specific subjects were separately parcellated and employed for construction of subtype-specific association matrices using Pearson correlation. These association matrices were binarized using sparsity threshold and leveraged for structural brain connectivity analysis using network metrics. Main results. Two distinct Parkinson’s subtypes (namely A and B) were detected employing loadings of two components satisfying the selection criteria, and a third subtype (AB) was detected, common to these two components. Subtype A subjects were highly weighted in inferior, middle and superior frontal gyri while subtype B subjects in inferior, middle and superior temporal gyri. Network metrics analyses through permutation test revealed significant inter-subtype differences (p < 0.05) in clustering coefficient, local efficiency, participation coefficient and betweenness centrality. Moreover, hubs were obtained using betweenness centrality and mean network degree. Significance. MRI-based data-driven subtypes show frontal and temporal lobes playing a key role in PD. Graph theory-driven brain network analyses could untangle subtype-specific differences in structural brain connections showing differential network architecture. Replication of these initial results in other Parkinson’s datasets may be explored in future. Clinical Relevance- Investigating structural brain connections in Parkinson’s disease may provide subtype-specific treatment.
Optimizing for periodicity: a model-independent approach to flux crosstalk calibration for superconducting circuits
Authors: Dai X , Trappen R , Yang R , Disseler S M , Basham J I , Gibson J , Melville A J , Niedzielski B M , Das R , Kim D K , Yoder J L , Weber S J , Hirjibehedin C F , Lidar D A , Lupascu A
Published: January 2024

Flux tunability is an important engineering resource for superconducting circuits. Large-scale quantum computers based on flux-tunable superconducting circuits face the problem of flux crosstalk, which needs to be accurately calibrated to realize high-fidelity quantum operations. Typical calibration methods either assume that circuit elements can be effectively decoupled and simple models can be applied, or require a large amount of data. Such methods become ineffective as the system size increases and circuit interactions become stronger. Here we propose a new method for calibrating flux crosstalk, which is independent of the underlying circuit model. Using the fundamental property that superconducting circuits respond periodically to external fluxes, crosstalk calibration of N flux channels can be treated as N independent optimization problems, with the objective functions being the periodicity of a measured signal depending on the compensation parameters. We demonstrate this method on a small-scale quantum annealing circuit based on superconducting flux qubits, achieving comparable accuracy with previous methods. We also show that the objective function usually has a nearly convex landscape, allowing efficient optimization.
Diagnostic Prediction of portal vein thrombosis in chronic cirrhosis patients using data-driven precision medicine model
Authors: Li Ying , Gao Jing , Zheng Xubin , Nie Guole , Qin Jican , Wang Haiping , He Tao , Wheelock Åsa , Li Chuan-Xing , Cheng Lixin , Li Xun
Published: January 2024

Background

Portal vein thrombosis (PVT) is a significant issue in cirrhotic patients, necessitating early detection. This study aims to develop a data-driven predictive model for PVT diagnosis in chronic hepatitis liver cirrhosis patients.

Methods

We employed data from a total of 816 chronic cirrhosis patients with PVT, divided into the Lanzhou cohort (n = 468) for training and the Jilin cohort (n = 348) for validation. This dataset encompassed a wide range of variables, including general characteristics, blood parameters, ultrasonography findings and cirrhosis grading. To build our predictive model, we employed a sophisticated stacking approach, which included Support Vector Machine (SVM), Naïve Bayes and Quadratic Discriminant Analysis (QDA).

Results

In the Lanzhou cohort, SVM and Naïve Bayes classifiers effectively classified PVT cases from non-PVT cases, among the top features of which seven were shared: Portal Velocity (PV), Prothrombin Time (PT), Portal Vein Diameter (PVD), Prothrombin Time Activity (PTA), Activated Partial Thromboplastin Time (APTT), age and Child–Pugh score (CPS). The QDA model, trained based on the seven shared features on the Lanzhou cohort and validated on the Jilin cohort, demonstrated significant differentiation between PVT and non-PVT cases (AUROC = 0.73 and AUROC = 0.86, respectively). Subsequently, comparative analysis showed that our QDA model outperformed several other machine learning methods.

Conclusion

Our study presents a comprehensive data-driven model for PVT diagnosis in cirrhotic patients, enhancing clinical decision-making. The SVM–Naïve Bayes–QDA model offers a precise approach to managing PVT in this population.
scFed: federated learning for cell type classification with scRNA-seq
Authors: Wang Shuang , Shen Bochen , Guo Lanting , Shang Mengqi , Liu Jinze , Sun Qi , Shen Bairong
Published: January 2024

The advent of single-cell RNA sequencing (scRNA-seq) has revolutionized our understanding of cellular heterogeneity and complexity in biological tissues. However, the nature of large, sparse scRNA-seq datasets and privacy regulations present challenges for efficient cell identification. Federated learning provides a solution, allowing efficient and private data use. Here, we introduce scFed, a unified federated learning framework that allows for benchmarking of four classification algorithms without violating data privacy, including single-cell-specific and general-purpose classifiers. We evaluated scFed using eight publicly available scRNA-seq datasets with diverse sizes, species and technologies, assessing its performance via intra-dataset and inter-dataset experimental setups. We find that scFed performs well on a variety of datasets with competitive accuracy to centralized models. Though Transformer-based model excels in centralized training, its performance slightly lags behind single-cell-specific model within the scFed framework, coupled with a notable time complexity concern. Our study not only helps select suitable cell identification methods but also highlights federated learning’s potential for privacy-preserving, collaborative biomedical research.
Genotype imputation accuracy and the quality metrics of the minor ancestry in multi-ancestry reference panels
Authors: Shi Mingyang , Tanikawa Chizu , Munter Hans Markus , Akiyama Masato , Koyama Satoshi , Tomizuka Kohei , Matsuda Koichi , Lathrop Gregory Mark , Terao Chikashi , Koido Masaru , Kamatani Yoichiro
Published: January 2024

Large-scale imputation reference panels are currently available and have contributed to efficient genome-wide association studies through genotype imputation. However, whether large-size multi-ancestry or small-size population-specific reference panels are the optimal choices for under-represented populations continues to be debated. We imputed genotypes of East Asian (180k Japanese) subjects using the Trans-Omics for Precision Medicine reference panel and found that the standard imputation quality metric (Rsq) overestimated dosage r2 (squared correlation between imputed dosage and true genotype) particularly in marginal-quality bins. Variance component analysis of Rsq revealed that the increased imputed-genotype certainty (dosages closer to 0, 1 or 2) caused upward bias, indicating some systemic bias in the imputation. Through systematic simulations using different template switching rates (θ value) in the hidden Markov model, we revealed that the lower θ value increased the imputed-genotype certainty and Rsq; however, dosage r2 was insensitive to the θ value, thereby causing a deviation. In simulated reference panels with different sizes and ancestral diversities, the θ value estimates from Minimac decreased with the size of a single ancestry and increased with the ancestral diversity. Thus, Rsq could be deviated from dosage r2 for a subpopulation in the multi-ancestry panel, and the deviation represents different imputed-dosage distributions. Finally, despite the impact of the θ value, distant ancestries in the reference panel contributed only a few additional variants passing a predefined Rsq threshold. We conclude that the θ value substantially impacts the imputed dosage and the imputation quality metric value.
Influenza: cause or excuse? An analysis of flu’s influence on worsening mortality trends in England and Wales, 2010–19
Authors: Hiam Lucinda , McKee Martin , Dorling Danny
Published: January 2024

Background

England and Wales experienced a stagnation of previously improving life expectancy during the 2010s. Public bodies cited influenza as an important cause.

Sources of data

We used data from the Office for National Statistics to examine mortality attributed directly to influenza and to all influenza-like diseases for the total population of England and Wales 2010–19. Several combinations of ICD-10 codes were used to address the possibility of under-counting influenza deaths.

Areas of agreement

Deaths from influenza and influenza-like diseases declined between 2010 and 2019, while earlier improvements in mortality from all causes of death were stalling and, with some causes, worsening. Our findings support existing research showing that influenza is not an important cause of the stalling of mortality rates 2010–19.

Areas of controversy

Influenza was accepted by many as an important cause of stalling life expectancy for much of the 2010s, while few in public office have accepted austerity as a key factor in the changes seen during that time.

Growing points

This adds to the mounting evidence that austerity damaged health prior to COVID-19 and left the population more vulnerable when it arrived.

Areas for developing timely research

Future research should explore why so many in public office were quick to attribute the change in trends in overall mortality in the UK in this period to influenza, and why many continue to do so through to 2023 and to deny the key role of austerity in harming population health.