bluuebunny/crossref_metadata_2025_split huggingface dataset:
Efficient elimination of MELAS-associated m.3243G mutant mitochondrial DNA by an engineered mitoARCUS nuclease
Authors: Shoop Wendy K. , Lape Janel , Trum Megan , Powell Alea , Sevigny Emma , Mischler Adam , Bacman Sandra R. , Fontanesi Flavia , Smith Jeff , Jantz Derek , Gorsuch Cassandra L. , Moraes Carlos T. 
Published: November 2023

AbstractNuclease-mediated editing of heteroplasmic mitochondrial DNA (mtDNA) seeks to preferentially cleave and eliminate mutant mtDNA, leaving wild-type genomes to repopulate the cell and shift mtDNA heteroplasmy. Various technologies are available, but many suffer from limitations based on size and/or specificity. The use of ARCUS nucleases, derived from naturally occurring I-CreI, avoids these pitfalls due to their small size, single-component protein structure and high specificity resulting from a robust protein-engineering process. Here we describe the development of a mitochondrial-targeted ARCUS (mitoARCUS) nuclease designed to target one of the most common pathogenic mtDNA mutations, m.3243A>G. mitoARCUS robustly eliminated mutant mtDNA without cutting wild-type mtDNA, allowing for shifts in heteroplasmy and concomitant improvements in mitochondrial protein steady-state levels and respiration. In vivo efficacy was demonstrated using a m.3243A>G xenograft mouse model with mitoARCUS delivered systemically by adeno-associated virus. Together, these data support the development of mitoARCUS as an in vivo gene-editing therapeutic for m.3243A>G-associated diseases.
The open ocean kinetic energy cascade is strongest in late winter and spring
Authors: Schubert René , Vergara Oscar , Gula Jonathan 
Published: November 2023

AbstractThe oceanic kinetic energy cascade, the flux of kinetic energy between currents of different horizontal scales, shapes the structure of the global ocean circulation and the associated heat, salt, nutrient, and oxygen fluxes. Here, we show with a numerical ocean simulation that the surface geostrophic cascade can be estimated from satellite altimetry observations and present its regional distribution and seasonal cycle at scales of 40 to 150 km for large parts of the global ocean based on observations. The time-mean cascade is inverse (towards larger scales), strongest in large-scale current systems, and decreases with distance from these systems. In the open ocean, the inverse cascade is associated with a maximum in late winter at the smallest scales studied, which transitions to scales larger than 100 km within two to three months, consistent with the widespread absorption of mixed-layer eddies by mesoscale eddies in spring.
Miniaturized 3‐bit frequency‐reconfigurable monopole antenna with a meander line
Authors: Hu Xueyang , Liu Yun , Yang Yueyou 
Published: November 2023

AbstractA novel 3‐bit frequency‐reconfigurable antenna (FRA) with miniaturized dimensions is realized with a meander line. The frequency reconfiguration of the antenna is achieved by introducing N Radio Frequency (RF) PIN diodes into the meander line. The related parts of the meander line with different lengths are bypassed or included into the antenna by switching on or off the diodes, resulting in 2N switchable size lengths of the antenna and equally spaced operating frequencies. A 3‐bit reconfigurable meander‐line antenna (N = 3) is designed, and the simulated and measured results agree well. The antenna provides 8 (23) independent and switchable states, with the operating frequencies covering a wide switchable frequency range from 1.04 to 1.51 GHz and the working bandwidths varying from 80 to 150 MHz. The number of working bandwidth states is maximized, considering the number of switches used. Moreover, the results reveal an acceptable peak gain of 1.59 dBi in terms of the miniaturized total dimension of 0.17 λg × 0.07 λg (λg is the guided wavelength at the lowest working frequency), which is more compact than several published FRAs.
Inkjet printed intelligent reflecting surface for indoor applications
Authors: Takimoto Kairi , Nakamura Kazutomo , Njogu Peter , Suzuki Kota , Sugimoto Masato , Fathnan Ashif , Kondo Takashi , Mori Masayuki , Anzai Daisuke , Wakatsuchi Hiroki 
Published: November 2023

AbstractA passive, low‐cost, paper‐based intelligent reflecting surface (IRS) is designed to reflect a signal in a desired direction to overcome non‐line‐of‐sight scenarios in indoor environments. The IRS is fabricated using conductive silver ink printed on paper with a specific nanoparticle arrangement, yielding a cost‐effective paper‐based IRS that can easily be mass‐produced. Full‐wave numerical simulation results were consistent with measurement results, demonstrating the IRS's ability to reflect incident waves into a desired nonspecular direction based on the inkjet‐printed design and materials.
Dynamic impedance model based two‐stage customized charging–navigation strategy for electric vehicles
Authors: Ji Chenlin , Yang Qiming , Wu Jiayu , Zhou Xinyang , Cong Leyao , Gu Dengke , Liu Youbo 
Published: November 2023

AbstractWith the continuously increasing penetration of electric vehicles (EVs), the mutual match between the distribution of charging resources and the spatial–temporal distribution of EV charging demands is becoming increasingly important. To address this, this paper proposes a novel two‐stage customized EV charging–navigation strategy. Building on previous research on the real‐time information from dynamic traffic networks, a personalized dynamic road impedance (PDRI) model is built to transform three main criteria (distance, time, and finance) affecting charging–navigation into comprehensive road impedance. In the first navigation stage, fast‐charging stations (FCSs) with the lowest overall objective are selected. In the second navigation stage, an improved Floyd–Warshall algorithm is utilized to identify the routes with the lowest personalized weight to the selected FCS in the PDRI model. Notably, the personalized preferences of EV drivers for the three primary criteria are considered in both stages of the navigation process. Finally, simulation results demonstrate a significant improvement in the degree of matching between charging navigation plans and drivers' personalized requirements, and a more balanced spatial–temporal distribution of EV charging demands among FCSs, which verifies the effectiveness of the proposed strategy.
A self‐constraint model predictive control method via air conditioner clusters for min‐level generation following service
Authors: Ma Yunfeng , Zhang Chao , Ding Bangkun , Mi Zengqiang 
Published: November 2023

AbstractAs renewable power generation increases in distribution networks, the real‐time power balance is becoming a tough challenge. Unlike simple peak‐load shedding or demand turn‐down scenarios, generation following (GF) requires persistent and precise control due to the temporal response performance of controlled resources. This motivates a comprehensive control design considering the temporal response limits and execution performance of air conditioner clusters (ACCs) when providing GF. Accordingly, this paper proposes a self‐constraint model predictive control (SMPC) that properly allocates the generation following task among different ACCs, consisting of three main parts: response rehearsal, distributed consistency‐based power allocation, and real‐time task execution. Specifically, the rehearsal knowledge of ACCs is evaluated by introducing model predictive control (MPC) to track power signals with different values and thus obtain prior factors, including the upward/downward limits and control cost function. On this basis, the coherence of the incremental response costs of different clusters is achieved to allocate the GF signals. Once the optimised following signals (OFS) are obtained, a real‐time MPC for generation following task execution is employed, where the OFS are used as reference and the upward/downward limits are used as constraints. Simulations are conducted to verify the feasibility and effectiveness of the proposed method.
Cardiac disease risk prediction using machine learning algorithms
Authors: Stonier Albert Alexander , Gorantla Rakesh Krishna , Manoj K 
Published: November 2023

AbstractHeart attack is a life‐threatening condition which is mostly caused due to coronary disease resulting in death in human beings. Detecting the risk of heart diseases is one of the most important problems in medical science that can be prevented and treated with early detection and appropriate medical management; it can also help to predict a large number of medical needs and reduce expenses for treatment. Predicting the occurrence of heart diseases by machine learning (ML) algorithms has become significant work in healthcare industry. This study aims to create a such system that is used for predicting whether a patient is likely to develop heart attacks, by analysing various data sources including electronic health records and clinical diagnosis reports from hospital clinics. ML is used as a process in which computers learn from data in order to make predictions about new datasets. The algorithms created for predictive data analysis are often used for commercial purposes. This paper presents an overview to forecast the likelihood of a heart attack for which many ML methodologies and techniques are applied. In order to improve medical diagnosis, the paper compares various algorithms such as Random Forest, Regression models, K‐nearest neighbour imputation (KNN), Naïve Bayes algorithm etc. It is found that the Random Forest algorithm provides a better accuracy of 88.52% in forecasting heart attack risk, which could herald a revolution in the diagnosis and treatment of cardiovascular illnesses.
Virtual network embedding method based on node delay perception
Authors: Wang Yaning , Zhi Hui 
Published: November 2023

AbstractWireless virtual network uses software defined network and network function virtualisation technologies to create multiple logically isolated virtual networks on a physical wireless network. Wireless virtual network can improve the utilisation of wireless resources to meet the requirements of different services. Delay is an important performance indicator, which has strict requirements for delay‐sensitive services such as video conferencing and online games. In this study, a virtual network embedding method based on node delay perception (VNE‐NDP) is proposed, which considers both the node and link resources as well as the embedding delay requirements of virtual networks. The virtual network embedding method based on node delay perception consists of two phases: virtual node embedding and virtual link embedding. In the virtual node embedding phase, a physical node sorting method based on node delay perception (PNS‐NDP) is proposed. In PNS‐NDP, the node deployment delay is introduced into the node sorting algorithm for the first time. The authors select candidate physical nodes for each virtual node according to their resource availability and delay performance, which can greatly reduce the VN embedding delay without sacrificing too much other performance. In the virtual link embedding phase, a shortest path algorithm with bandwidth and link deployment delay constraints to find feasible physical paths for each virtual link is used. In addition, the VN embedding (VNE) deployment time is set as a new evaluation index. Simulation results show that compared with other VNE methods, VNE‐NDP can achieve higher success rate, revenue‐to‐expenditure ratio, and lower deployment delay.
Estimated diameter increase from a 4S to a 6S hamstring graft configuration – A cadaveric study
Authors: Bourgeault-Gagnon Yoan , Leang Alexandre Keith , Bédard Sonia , Lebel Karina , Balg Frédéric , Vézina François 
Published: November 2023

Purpose: Graft diameter in anterior cruciate ligament reconstructions has been shown to influence the risk of failure. It is therefore important to be able to adjust the graft configuration to modify the diameter. To measure the impact of a 6-strand (6S) hamstring autograft configuration on graft diameter compared to the standard 4-strand (4S) configuration. Methods: Cadaveric study on 33 knees, using the usual hamstring graft harvesting technique. Semitendinosus and gracilis tendons were harvested and their length, width, and diameter were measured in 4S and 6S configurations separately by three evaluators. Results: 6S configuration leads to a median increase of 1.5 (range: 0.0–2.0) mm in diameter compared to 4S (p < 0.001). A graft diameter of more than 8 mm is attained in less than a third of 4S grafts within this population in comparison to 84% when the 6S configuration is used. Discussion: The 6S hamstring graft configuration increases the graft diameter by a median of 1.5 millimeters compared to the traditional 4S configuration. It can reliably be used to obtain an 8.5 mm graft diameter or more in cases where the semitendinosus measures at least 270.5 mm and the 4S configuration has a diameter of 7.5 mm or 8 mm. This information helps to better delineate the impact of a 6S configuration in a pre-operative or intra-operative setting to optimize the decisional process and surgical flow and to easily adapt the graft diameter.
Level of evidence: V (cadaveric study)
The Relationship Between Nurses' Sleep Quality and Their Tendency to Commit Medical Errors
Authors: Demir Gamze , Karadag Gülendam 
Published: November 2023

Abstract
Objective To examine the relationship between nurses' sleep quality and their tendency to commit medical errors.
Materials and Methods The research was conducted in a state hospital, a private hospital, and a university hospital in a province located in the west region of Turkey (n = 378 nurses) between September 2020 and October 2021. Data was collected using a sociodemographic data form, the Medical Error Tendency Scale in Nursing (METSN), and the Pittsburgh Sleep Quality Index (PSQI). Verbal and written consent were obtained from the nurses who participated in the study. The data were collected through face-to-face interviews.
Results The mean score of the nurses was of 8.25 ± 4.81 on the PSQI and of 230.29 ± 14.15 on the METSN. A significant difference was found regarding age, marital status, level of schooling, weekly working hours, and the shift schedule of nurses and their sleep quality (p < 0.001). A significant difference was found regarding age, marital status, level of schooling, the hospital the nurses worked in, and the tendency to commit medical errors (p < 0.001). There was a statistically significant negative and moderate correlation between the PSQI and METSN scores (p < 0.001; r = −0.548).
Conclusion The tendency of nurses to commit medical errors was determined as low, and their sleep quality was poor. We have also determined that, as the sleep quality worsened, the tendency of nurses to commit medical errors increased.
ZnO incorporated hybrid catalytic proton exchange membrane for H2 generation
Authors: Mishra Jay N. , Jha Priyanka A. , Jha Pardeep K. , Singh Parvin K. , Choudhary Suman Roy , Singh Prabhakar 
Published: November 2023

Electrocatalytic proton exchange membranes (PEMs) represent a promising avenue for advancing the field of electrochemical energy conversion and storage by combining the proton-conducting function of PEMs with enhanced catalytic activity by incorporation of metal ions. Here, we systematically studied the ZnO-based metal-organic framework (MOF) and found the introduction of pegylated ZnO to the (diethyl methylamine)/(H2PO4) matrix to form the p-type conducting MOF membrane with a bandgap of 3.67 eV. This membrane not only has a high protonic conductivity of 0.027 S/cm at 300 K with a transference number &gt;0.99 but also possesses high activity (Tafel slope ∼36 mV/decade). The high reaction kinetics supported by finite element modeling simulations shows its ability to produce efficient and sustainable hydrogen. Our results suggest high current density of 1.52 mA/cm2, a turn over frequency [H2 (s−1)] ∼0.474×1018s−1, and a stability of 168 h in neutral medium (pH = 7). This work will enhance new strategies for fabricating membranes with ionic liquid in order to get membranes with protonic conductivity along with high activity for large-scale water electrolysis.
Log-periodic gravitational-wave background beyond Einstein gravity
Authors: Calcagni Gianluca , Kuroyanagi Sachiko 
Published: November 2023

Abstract
Periodic patterns of logarithmic oscillations can arise in primordial curvature perturbation spectra and in the associated gravitational-wave background via different mechanisms. We show that, in the presence of log oscillations, the spectral shape of the stochastic background has a unique parametrization independent of its physical origin. We also show that this log-periodic modulation can be generated in any scenario beyond Einstein gravity endowed with an approximate discrete scale invariance, a symmetry typical of deterministic fractal spacetimes that could emerge in quantum gravity under certain conditions. We discuss how a log-oscillatory spectral shape arises from concrete inflationary models beyond Einstein gravity and the prospects for detection in Einstein Telescope and other next-generation gravitational-wave observatories. We find that these instruments will be sensitive to log-periodic features if the detection is made with a high signal-to-noise ratio (SNR) and that the error scales as

1

/

SNR

.
Carrier density dependent Auger recombination in c-plane (In,Ga)N/GaN quantum wells: insights from atomistic calculations
Authors: McMahon Joshua M , Kioupakis Emmanouil , Schulz Stefan 
Published: November 2023

Abstract
Understanding Auger recombination in (In,Ga)N-based quantum wells is of central importance to unravelling the experimentally observed efficiency ‘droop’ in modern (In,Ga)N light emitting diodes (LEDs). While there have been conflicting results in the literature about the importance of non-radiative Auger recombination processes for the droop phenomenon, it has been discussed that alloy fluctuations strongly enhance the Auger rate. However, these studies were often focused on bulk systems, not quantum wells, which lie at the heart of (In,Ga)N-based LEDs. In this study, we present an atomistic analysis of the carrier density dependence of the Auger recombination coefficients in (In,Ga)N/GaN quantum wells. The model accounts for random alloy fluctuations, the connected carrier localisation effects, and carrier density dependent screening of the built-in polarisation fields. Our studies reveal that at low temperatures and low carrier densities the calculated Auger coefficients are strongly dependent on the alloy microstructure. However, at elevated temperatures and carrier densities, where the localised states are starting to be saturated, the different alloy configurations studied give (very) similar Auger coefficients. We find that over the range of carrier densities investigated, the contribution of the electron-electron–hole related Auger process is of secondary importance compared to the hole-hole-electron process. Overall, for higher temperatures and carrier densities, our calculated total Auger coefficients are in excess of 10−31 cm6 s−1 and may reach 10−30 cm6 s−1, which, based on current understanding in the literature, is sufficient to result in a significant efficiency droop. Thus, our results are indicative of Auger recombination being an important contributor to the efficiency droop in (In,Ga)N-based light emitters even without defect-assisted processes.
Mitigating dust particle contamination in an afterglow plasma by controlled lifting with a DC electric field
Authors: Chaubey Neeraj , Goree J 
Published: November 2023

Abstract
Particle contamination due to plasma processing motivates the design of a method of electrically lifting particles in a time interval after a plasma’s power is turned off. Small solid dust particles have electric charges that are not frozen until a late stage of the plasma afterglow. Beyond that time, before they fall to a surface below and cause defects, particles can be lifted in a controlled manner by applying an appropriate direct-current (DC) electric field, as we demonstrate experimentally. A few milliseconds after an argon plasma’s capacitively coupled radio-frequency power is switched off, a vertical DC electric field is applied. Thereafter, video imaging shows that the falling of the particles is slowed or stopped altogether, depending on the magnitude of the upward electric force.
Comparison of magnetoimpedance behaviors in meander CoFeNiSiB amorphous ribbon for deformation sensing applications
Authors: Yang Zhen , Liu Mengyu , Luo Liming , Wang Zhenbao , Li Haihua , Sun Xuecheng , Xu Jun , Sun Xun , Lei Chong 
Published: November 2023

Abstract
In this work, micro-ribbon strips and meanders based on CoFeNiSiB amorphous ribbons were fabricated by using the lithography technique and chemical etching. Flat and curved holders with different radius of curvature were obtained via 3D printing techniques for GMI testing. Longitudinal and transverse GMI (LGMI and TGMI) behaviors of micro-ribbon sensors in different bending directions and degrees were systematically investigated. The results show the LGMI and TGMI effects of micro-ribbon meanders with one turn is most sensitive to bending. It can be used in the development of deformation sensors. In addition, there is a linear range of field in the LGMI and TGMI curves of micro ribbons under different bending conditions, and the sensitivity of micro-ribbon sensors shows no significant change in the range. In particular, the micro-ribbon meanders with three turns are the least sensitive to bending deformation and can be used to develop stable and flexible GMI sensors for wearable electronics devices.
Anisotropic properties of two-dimensional (2D) tin dihalide (SnX2, X = Cl, Br, I) monolayer binary materials
Authors: Kumar Vipin , Jeon Hwajun , Kumar Pushpendra , Trung Le Gia , Ahuja Rajeev , Gwag Jin Seog 
Published: November 2023

Abstract
This paper investigated the electronic properties and photoresponse of two-dimensional SnX2 (X = Cl, Br, I) monolayer binary materials using computational techniques. The calculated band structure and density of states indicate that these are large band gap semiconducting materials with an indirect band gap. The studied chemical bonding mechanism shows the existence of the hybrid bonding of ionic and covalent bonds in these dihalide materials. The valence band (VB) and conduction band (CB) edge positions are also estimated, using the concept of electronegativity and band gap, to investigate the photocatalytic activity of SnX2. Next, we investigated the polarization and energy-dependent dielectric and optical functions along the crystallographic axes of these materials in the linear response approach of the perturbing incident oscillating light field. These materials exhibit an anisotropic behavior of these functions, especially in the high-energy visible and low-energy ultraviolet (UV) regions. The absorption of incident light photons is very fast in SnI2 than SnBr2 and SnCl2 in the low-energy UV region. It demonstrates the higher absorption coefficient and optical conductivity in Snl2. The obtained average static refractive index of SnCl2 is comparable to that of glass (1.5), showing its application as transparent material. The low reflection coefficient, less than 20%, makes them superior for antireflection coating materials in the infrared and visible regions. The prominent energy loss peaks show the existence of plasmon resonances in these materials. The most of losses occur in the UV region. The investigated electronic and photoresponse properties indicate that these Sn-based dihalide materials are excellent for electronic devices and optoelectronic applications. Also, the calculated VB and CB edge positions with respect to the normal hydrogen electrode show the favorable water-splitting capability of these materials.