bluuebunny/crossref_metadata_2025 huggingface dataset:
Enhancing Sustainable Competitive Advantage: The Role of Emotional Intelligence in Organizational Adaptation within Dynamic Business Environments
Authors: Juniarti Atty Tri , Setia Bayu Indra , Alghifari Erik Syawal , Pangestu Erry S.R. , Onasis Dini , Nuramaliah Arla
Published: November 2024

This research aims to analyze how emotional intelligence facilitates the process of organizational adaptation in response to rapidly changing and complex business environments, thereby contributing to the achievement of sustainable competitive advantage. This research uses a quantitative method, gathering data through 400 survey responses from 60 companies in the textile industry sector in Indonesia. SEM techniques are employed to analyze data in order to investigate the connections between sustainable competitive advantage, organizational adaptation, and emotional intelligence. The findings indicate that emotional intelligence has a positive and significant impact on organizational adaptation, which in turn positively influences sustainable competitive advantage. These results highlight the importance of developing emotional intelligence among leaders and employees as a strategy to enhance organizational adaptability and maintain long-term competitive advantage. The implications of this study include recommendations for managers and organizational leaders to focus on improving emotional intelligence as part of human resource development initiatives. Additionally, this research provides insights for academics on the importance of the interaction between individual psychological factors and organizational dynamics in the context of sustainable competitive advantage. Ultimately, this study underscores the strategic value of emotional intelligence in fostering resilient and adaptable organizations capable of sustaining a competitive edge in dynamic markets.
Does robotic arm-assisted total knee arthroplasty have a role to play in large deformities?
Authors: Vermorel Pierre-Henri , Ciccullo Carlo , De Berardinis Luca , Gigante Antonio Pompilo , Neri Thomas , Philippot Rémi
Published: November 2024

Background: Total knee arthroplasty (TKA) for patients with a large preoperative deformity (more than 10° varus or valgus) remains a challenge leading to a high rate of outliers, unsatisfactory functional results, or early prosthetic loosening. Robotic arm-assisted TKA (RATKA) has shown improvements in implant positioning accuracy. This study aimed to assess RATKA implant positioning accuracy and functional results at one year postoperative for patients with a large preoperative deformity. Methods: From November 2019 to July 2022, 500 RATKA were performed. About 74 patients with more than 10° of varus or valgus global deformity were included. Each patient received a semi-constrained implant. The difference between the valgus or varus value planned intra-operatively and the varus or valgus measured on one-year postoperative X-rays has been assessed. Functional outcomes (VAS, range of motion, KOOS) have also been evaluated. Results: For varus, the mean difference was 0.54 ± 1.21°, all patients (100%) had a difference of less than 3° at one-year post-operative. For valgus, the mean difference was 0.63 ± 1.29°, most patients (92%) had a difference of less than 3° at one year postoperative. Overall, 98.6% (n = 73) of cases had a difference of less than 3° at one-year postoperative. The mean VAS was 1.6 ± 1.4 [1;4]. Mean flexion was 132 ± 7.6° [100;145]. A total of 69 patients (93%) had a good or excellent KOOS score (KOOS total > 70) at one year post-operative. Conclusion: For large preoperative deformities, RATKA provides a high degree of accuracy in implant positioning, permitting it to fit the desired alignment without compromising knee stability, and giving the possibility of using semi-constrained implants. At one year postoperative, functional results are encouraging and most patients have recovered an optimal range of motions.
Stacking model framework reveals clinical biochemical data and dietary behavior features associated with type 2 diabetes: A retrospective cohort study
Authors: Fu Yong , Liang Xinghuan , Yang Xi , Li Li , Meng Liheng , Wei Yuekun , Huang Daizheng , Qin Yingfen
Published: November 2024

Background: Type 2 diabetes mellitus (T2DM) is the most common type of diabetes, accounting for around 90% of all diabetes. Studies have found that dietary habits and biochemical metabolic changes are closely related to T2DM disease surveillance, but early surveillance tools are not specific and have lower accuracy. This paper aimed to provide a reliable artificial intelligence model with high accuracy for the clinical diagnosis of T2DM. Methods: A cross-sectional dataset comprising 8981 individuals from the First Affiliated Hospital of Guangxi Medical University was analyzed by a model fusion framework. The model includes four machine learning (ML) models, which used the stacking method. The ability to leverage the strengths of different algorithms to capture complex patterns in the data can effectively combine questionnaire data and blood test data to predict diabetes. Results: The experimental results show that the stacking model achieves significant prediction results in diabetes detection. Compared with the single machine learning algorithm, the stacking model has improved in the metrics of accuracy, recall, and F1-score. The test set accuracy is 0.90, and the precision, recall, F1-score, area under the curve, and average precision (AP) are 0.91, 0.90, 0.90, 0.90, and 0.85, respectively. Additionally, this study showed that HbA1c (P < 0.001,OR = 2.203), fasting blood glucose (FBG) (P < 0.001,OR = 1.586), Ph2BG (P < 0.001,OR = 1.190), age (P < 0.001,OR = 1.018), Han nationality (P < 0.001,OR = 1.484), and carbonate beverages (P = 0.001,OR = 1.347) were important predictors of T2DM. Conclusion: This study demonstrates that stacking models show great potential in diabetes detection, and by integrating multiple machine learning algorithms, stacking models can significantly improve the accuracy and stability of diabetes prediction and provide strong support for disease prevention, early diagnosis, and individualized treatment.
Estimating the offshore wind power potential of Portugal by utilizing gray-zone atmospheric modeling
Authors: Baki H. , Basu S. , Lavidas G.
Published: November 2024

Advancements in floating offshore wind energy are unlocking the potential of the coastal waters of Portugal for the installation of wind farms. A thorough evaluation of coastal effects and variability across different time scales is crucial to ensure successful offshore wind farm investments. State-of-the-art atmospheric reanalysis datasets fall short in explaining the coastal effects due to their modest grid resolution. This study aims to fill this gap by simulating a 31-year wind dataset at a gray-zone resolution of 500 m using the Weather Research and Forecasting model, covering a significant portion of the Portugal coast. The gray-zone refers to grid scales of a few hundred meters, where turbulence is only partially resolved, traditional turbulence modeling breaks down, and large-eddy simulations are computationally prohibitive. The newly generated dataset has been validated with buoy observations and compared against reanalysis datasets, demonstrating improved performance and highlighting its higher fidelity in assessing wind resources. Two wind turbine power curves, the Leanwind 8 megawatt (MW) reference wind turbine (RWT), which has been commercialized, and the International Energy Agency (IEA) 15 MW RWT, which represents future commercialization, are considered in energy production calculations. In the simulated data, the Iberian Peninsula Coastal Jet (IPCJ) emerges as a crucial factor influencing wind maxima, especially during the summer months. The diurnal and annual variability of wind energy resources aligns with the occurrence of IPCJ, highlighting its impact on wind energy generation. The energy production capability of the 15 MW turbine model is demonstrated to be significantly higher, attributed not only to its increased capacity but also to the stronger jet winds near the turbine hub height. Interestingly, wind resources are not monotonically increasing with distance from the coastline, but a tongue-like resource maxima is observed, which is attributed to the IPCJ.
Cascaded injection locking of optomechanical crystal oscillators
Authors: Alonso-Tomás David , Arregui Guillermo , Mercadé Laura , Martínez Alejandro , Griol Amadeu , Capuj Néstor E. , Navarro-Urrios Daniel
Published: November 2024

Optomechanical oscillators stand out as high-performance and versatile candidates for serving as reference clocks in sequential photonic integrated circuits. Indeed, they have the unique capability of simultaneously generating mechanical tones and optical signal modulations at frequencies determined by their geometrical design. In this context, the concept of synchronization introduces a powerful means to precisely coordinate the dynamics of multiple oscillators in a controlled manner, therefore increasing efficiency and preventing errors in signal processing photonic systems or communication interfaces. In this work, we demonstrate the cascaded injection locking of a pair of silicon-based optomechanical crystal cavities acting as optomechanical oscillators to an external reference signal that subtly modulates the laser driving only one of them. In contrast to most previous implementations, both cavities support isolated optical resonances and interact by a weak mechanical interconnection. This configuration allows one cavity to be used for probing the mechanical perturbation generated by the oscillator that receives the external forcing. The combination of the obtained results, supported by a numerical model, with remote optical injection locking schemes discussed in the literature lays the groundwork for the distribution of reference signals within large networks of processing elements in future phonon–photon hybrid circuits.
Rain-free imaging using second-order correlations in the time domain
Authors: Li Yuge , Duan Deyang
Published: November 2024

The traditional rain scattering model regards rain streaks as time-varying noise and rain fog as time invariant noise, which creates difficulties in analyzing the properties of rain scattering light fields in the time domain. Here, the rain streak noise and rain fog noise are unified as time-dependent noise. We theoretically and experimentally demonstrate that the rain streaks and rain fog photons (noise photons) result in the absence of stable temporal second-order correlations, while the photons that do not interact with raindrops (signal photons) are opposite. Therefore, the noise photons and signal photons can be distinguished by measuring the temporal second-order correlations of time-varying scattering light when the coherence time is shorter than the time interval between two consecutive measurement events, which provides the first optical protocol to simultaneously eliminate the rain streaks and rain fog, thereby obtaining clean images. Therefore, the image degradation caused by falling raindrops can be eliminated by the raindrops themselves. For common scenes, the rain removal performance of the proposed method is even better than deep learning when the integration time is short. The approach can be integrated into traditional cameras and offers optical promise for anti-interference imaging in harsh weather.
Supramolecular synthons, tectons, and crystal structures of noncovalent organic frameworks
Authors: Hisaki Ichiro , Fujii Takuto , Oketani Ryusei
Published: November 2024

In reticular chemistry, framework structures formed from organic molecules by noncovalent intermolecular interactions [i.e., noncovalent organic frameworks (nCOFs)] have been intensively investigated over the last two decades as another type of candidate for porous materials. Noncovalent interactions, such as hydrogen bonds (H-bonds), are weaker than covalent bonds or coordination bonds; therefore, various structural factors should be considered when a certain nCOF is designed. In this review, we examine nCOFs possessing three types of classic molecular scaffolds: 1,3,5-trisubstituted benzene, 1,2,3,4,5,6-hexasubstituted benzene, and tetraphenylethene, from viewpoints of the strength and directionality of intermolecular interactions (supramolecular synthons) and the geometry and rigidity of building block molecules (tectons). Combination of rigid tectons and robust supramolecular synthons is useful for preorganization of the framework structures, while flexible tectons and synthons can provide various photochemical functionality such as stimuli-responsiveness and chemosensing. Relationship between the structure of tectons, type of supramolecular synthons, and property of nCOFs is overviewed.
Increasing fire danger in the Netherlands due to climate change
Authors: Lambrechts Hugo A. , Sooijs Raoul D. H. , Paparrizos Spyridon , Ludwig Fulco , Stoof Cathelijne R.
Published: November 2024

Background Temperatures and extreme weather events in Northwestern Europe are expected to increase due to climate change. As a result, longer and more intense water deficits are expected, resulting in weather conditions conducive to wildfires. Aims We assessed the impact of recent and future climate change on fire danger in the Netherlands. Methods Historical weather data and climate scenarios in combination with the Canadian Fire Weather Index (FWI) and Fine Fuel Moisture Code (FFMC) were used to assess historical and future trends in fire danger. Key results Our analyses showed that, especially during the last decade (2011–2020), the number of days at elevated fire danger has increased. The number of days with elevated fire danger is projected to double by mid-century compared to the reference period 1981–2010 for high emission scenarios. The days at elevated fire danger during the last decade were already comparable to predictions for 2085, indicating that the climate change scenarios may underestimate future fire danger. Conclusions Days at elevated fire danger increased over the last four decades and will continue to do so under future climate scenarios. Implications The Netherlands needs to prepare for more days with weather conducive to wildfires.
Fire for the future: governance of market-based savanna fire management projects in Arnhem Land, northern Australia
Authors: Calnan Taegan , Yibarbuk Dean , Russell-Smith Jeremy
Published: November 2024

Background Developing effective participatory community-based governance is a key challenge for delivering equitable outcomes in market-based carbon and ecosystem services projects. Aim To explore Indigenous participants’ perspectives concerning implementation of representative community-based governance model for the longest running and largest market-based savanna fire management (SFM) project in northern Australia, the Arnhem Land Fire Abatement (ALFA) projects. Methods The study employed semi-structured interviews conducted between 2020–2022 exploring governance priorities and outcomes with 20 Indigenous participants occupying ALFA project leadership positions. Key results The ALFA governance model, involving participation of Indigenous Ranger Groups (IRGs) and representation of traditional Landowners as Directors on an entirely Indigenous-led Board, was considered to provide effective SFM project oversight and broader community acceptance. Identified benefits included supporting local cultural fire and land management responsibilities, regional networking, collective decision-making for benefit-sharing arrangements. Expressed concerns included potential for external IRG hosting institutions to diminish decision-making responsibilities of traditional Landowners, and preference for local IRG’s to strengthen links to traditional Landowners to promote broad community benefits. Conclusions The principles of the Indigenous representative and participatory ALFA governance model serve as an instructive example for local communities in other regional settings seeking to leverage emergent development opportunities through ecosystem service economies.
Subtraction
Authors: Levis John M.
Published: November 2024

This editorial argues for the value of considering subtraction (Klotz, 2021) as a curricular decision in pronunciation teaching and learning. Subtraction is a decision to focus on prioritizing particular aspects of pronunciation that will result in spoken intelligibility and to avoid focusing on aspects of pronunciation that are likely only to mark accentedness.
Recontextualizing knowledge in academic video publications
Authors: Velilla Sánchez María Ángeles
Published: November 2024

Online videos have gained popularity as a means for academics to communicate complex scientific ideas both to specialist and non-specialist audiences (Erviti & Stengler 2016; León & Bourk 2018; Luzón & Pérez-Llantada 2019). Nonetheless, concerns are raised about the potential journalistic or oversimplified nature of such science communication efforts. Consequently, this paper aims to shed light on how researchers can enhance transparency without reducing the significance of the content. The study is accomplished through an analysis of a corpus consisting of 10 videos compiled from the ‘Chemistry’ section of the website Latest Thinking (lt.org). This study adopts a discourse analysis approach, focusing on the discursive strategies employed in these videos to recontextualize knowledge for a wide audience. The findings reveal three types of recontextualization strategies performed through the orchestration of various semiotic modes: simplification strategies, strategies to construct an authorial persona and bonding strategies.
Credibility-driven rumor spreader and debunker co-evolutionary mechanisms for rumor propagation
Authors: Nian Fuzhong , Jia Yi , Wang Zhen
Published: November 2024

Rumor-propagation models have been an active research topic, while few methods consider the dynamic mutual transformation of the rumor spreaders and debunkers during the rumor propagation. To address the problem, we consider the possibility of co-evolution between spreaders and debunkers due to their suspicion of the message’s authenticity. Specifically, we define three dyadic rules that specify the transformation of ignorants to spreaders, ignorants to debunkers, and the mutual transformation between spreaders and debunkers in the competition of spreading-debunking during rumor propagation. Utilizing the proposed dyadic rule, we establish a new SI

r

I

d
rumor propagation model (susceptible ignorants (S), rumor spreaders (I

r
), rumor debunkers (I

d
)). Additionally, we introduce credibility as an indicating factor for the mutual transformation between spreaders and debunkers, and the credibility itself is updated according to the individual influence of each node, the local changes of neighboring spreader and debunker nodes, and the global changes of spreader and debunker nodes in the entire network. We first evaluate the proposed SI

r

I

d
model with simulation experiments in three typical networks, namely, Watts-Strogatz (WS), Erdős-Rényi (ER), and Barabasi-Albert (BA) networks. The results show that the proposed SI

r

I

d
model is strongly adaptable to these networks. We then conduct a series of parameter and ablation studies to analyze the proposed model theoretically and experimentally. Finally, we evaluate the proposed SI

r

I

d
model with multiple real retweet datasets collected from Weibo and Twitter to verify the generality and adaptability of the proposed model. The results show that our SI

r

I

d
can mimic rumor propagation in real-world scenarios.
An innovative method for solving the nonlinear fractional diffusion reaction equation with quadratic nonlinearity analysis
Authors: Khan Alamgir , Ullah Ikram , Iqbal Javed , Shah Kamal , Bilal Muhammad
Published: November 2024

This study generates and investigates spreading solitons in the fractional DR quadratic equation (FDE) with fractional derivatives using the Extended Direct Algebraic Method (EDAM). In population growth, mathematical biology, and reaction-diffusion mechanisms, the FDE is crucial. Applying the series form solution to the NODE from the FDE conversion into a recommended EDAM yields many traveling soliton solutions. To characterize and explore soliton structure propagation, we draw shock and kink soliton solutions. Through reaction-diffusion mechanics and mathematical biology, we may explain complex processes in many academic subjects.
Investigation of total ionizing dose effects on SOI FinFETs at elevated temperatures
Authors: Zhang Z J , Wu Y C , Liu F Y , Zhao S P , Liu H Y , Luo H Z , Zhang X , Li Y L
Published: November 2024

The synergistic effects of total ionization dose (TID) and high temperature (HT) are investigated for n-type Silicon-on-Insulator (n-SOI) FinFETs. Experimental results reveal that both HT and TID will lead to a negative shift in threshold voltage (ΔV
TH) in n-SOI FinFETs. While the ΔV
TH induced by the synergistic effects is smaller than the sum of the ΔV
TH shifts caused by TID and HT effects individually. Theoretical analysis suggests that the weaken degradation phenomenon can be attributed to the decrease of shallow-level electron traps in the HfO2 layer of stacked gate oxide. Based on this analysis, an analytical model is developed to simulate the synergistic effects of TID and HT, which has been validated by both experimental results and TCAD simulations. The proposed model enables accurate prediction of the potential distribution within the fin, allowing for precise calculation of V
TH variations under HT and TID irradiation.
Synthesis of Cu doped Ba(OH)2 thin film by SILAR method for supercapacitor electrode application
Authors: Sahu Abhishek Kumar , Pandey S N
Published: November 2024

An economically suitable successive ionic layer adsorption and reaction (SILAR) method has been used to deposit 0.25, 0.50 and 0.75 wt% copper doped barium hydroxide on stainless steel (SS) substrate. X-ray diffraction analysis shows the orthorhombic crystal structure of Cu doped Ba(OH)2 electrode. FTIR analysis reveals the chemical bonds present in the sample. The energy-dispersive x-ray spectroscopy (EDAX) and x-ray photo electron spectroscopy (XPS) measurements have been performed to confirm Cu doping into Ba(OH)2. The electrochemical properties of Cu doped Ba(OH)2 electrode have been analysed by cyclic voltammetry (CV) and galvanostatic charge–discharge (GCD) techniques. The 0.50 wt% Cu doped barium hydroxide electrode exhibits the highest specific capacitance (Csp) of 356.12 F g−1 (59.55 mF cm−2) at 1 mV s−1 scan rate in 1 M Na2SO4 electrolyte solution. This electrode also shows

~

85% capacitance retention up to 8000 cycles. A symmetric device has also been fabricated by using two electrodes. This device shows energy and power densities of 1.13 Wh Kg-1 and 279.7 W Kg-1 respectively. This cyclic retention and capacitive behaviour of Cu-doped Ba(OH)2 shows its utility as an energy storage material in the near future.
Self-powered methane (CH4) gas sensor based on vanadium oxide (VOx) nanostructures
Authors: Alipour Baladeh Saed , Haratizadeh Hamid
Published: November 2024

Gas detection technology has undergone significant changes over time. In coal mines, where methane gas (CH4) is typically found, swift detection of this gas is crucial for safety. This study developed the VOx pile rock nanostructures as a sensing material using DC magnetron sputtering and a quartz tube furnace to prepare vanadium nanostructures from a thin sputtered vanadium film. The sensor detected 1000, 2000, and 4000 ppm CH4 at room temperature without UV excitation, with ultrafast response/recovery times and 7%, 12%, and 27% responses, respectively. In addition, sensing analysis of this sample was performed for 125 days for 2000 ppm of CH4. The results exhibit that despite the decrease in the response value, the response and recovery times are almost the same as initial values. Using self-powered and rapid response/recovery time methane gas sensors is important for various applications, such as underground mining environments, where it can identify and alert methane gas levels that exceed the limit immediately, thus saving many lives in case of an explosion.
Tunneling dynamics of the relativistic Schrödinger/Salpeter equation
Authors: Daem F , Matzkin A
Published: November 2024

We investigate potential scattering and tunneling dynamics of a particle wavepacket evolving according to the relativistic Schrödinger equation (also known as the Salpeter equation). The tunneling properties of the Salpeter equation differ from those of the standard relativistic wave equations (such as the Klein–Gordon or Dirac equations). In particular, the tunneling solutions must be found by working in momentum space, given that the equation in configuration space contains a pseudo-differential operator. The resulting integral equations are derived and solved numerically for wavepackets scattering on model potential barriers. The solutions are characterized by the absence of Klein tunneling and an effect of the potential on the fraction of the transmitted wavepacket that propagates outside the light cone, a feature that has in the past been well-studied only for free propagation.
Electronic g-tensors of dangling bonds in hydroxylated and aminated nanodiamonds: a computational study
Authors: Masys Šarūnas , Jonauskas Valdas , Rinkevicius Zilvinas
Published: November 2024

The calculations of electronic g-tensors, one of the most important parameters in electron paramagnetic resonance spectroscopy, are carried out for dangling bonds (DBs) introduced into hydroxylated and aminated diamond nanoparticles, or nanodiamonds (NDs), of different shapes and sizes. Regarding the shapes of NDs, octahedral, cubic, and tetrahedral model systems are used, while the impact of the change in size is inspected by increasing octahedral ND from C35 to C84. The results for single DBs reveal that tetrahedral NDs exhibit the widest variation range of the isotropic g-shift values for both surface functionalization schemes, whereas the isotropic g-shifts of octahedral and cubic NDs tend to strongly overlap. On the other hand, if one treats NDs as an ensemble of nanoparticles constituting a sample, the isotropic g-shifts arithmetically averaged over all available DBs show that tetrahedral ND with hydroxylated surface possesses a significantly higher value than the rest of the considered systems. However, applying the Boltzmann distribution results in a substantially lower value for cubic ND. In contrast, aminated NDs do not demonstrate average values that stand out from the others, irrespective of the analysis method employed. Overall, in addition to the comprehensive magnetic properties, the obtained data also provide interesting details on the formation of DBs in hydroxylated and aminated NDs.
Sucrose phononic crystal-based sensor via acoustically induced transparency
Authors: Omrani Ehsan Mehdizadeh , Nazari Fakhroddin
Published: November 2024

Accurate detection of sucrose concentration is vital for assessing sugar content in fruits, vegetables, and nuts. This article introduces an innovative method for sensing various sucrose concentrations using an acoustically induced transparency system integrated by a solid mechanic phononic crystal framework. The detector architecture is based on a two-dimensional phononic crystal that employs poly methyl methacrylate as its foundational material, complemented by a regularly spaced array of circular tungsten pillars. The layout features a linear waveguide linked to two coupled ring resonators, with the upper resonator housing four columns filled with varying sucrose concentrations, thereby enabling resonance frequencies that are specifically tailored to each concentration. Simulation findings demonstrate a strong correlation between the shifts in transmission peak frequency and the associated sound velocities and material densities. The sensor’s functionality is further confirmed through coupled mode theory, representative an excellent alignment with the sensor’s presentation. Particularly, the sensor achieves an impressive average quality factor of 53515, an average sensitivity of 195 Hz, a figure of merit of 4.75, a signal-to-noise ratio of 1.25, a resolution of 40 Hz, and average insertion losses of 1.48 dB. These results underscore the acoustically induced transparency system’s potential for precise sucrose concentration sensing, offering remarkable sensitivity and accuracy for agricultural applications.
Preparation of lead borate-titanate-barium glasses: experimental investigation of their optical and radiation shielding properties
Authors: Sayyed M I , Dwaikat Nidal , M Rashad , Mhareb M H A
Published: November 2024

Novel glasses with the xPbO-5TiO2-10BaO-10ZnO-(75-x)B2O3 (where x = 30 to 45 mol% in 5 mol% increments) molar compositions were prepared. We experimentally investigated the prepared glasses’ structural, optical and radiation shielding characteristics. All the glass samples, based on x-ray diffraction, were noted to be amorphous. Four vibrational bands related to PbO and B2O3 were revealed by Fourier transform infrared. The optical band gap significantly increased with adding PbO instead of B2O3, ranging from 2.905 to 3.601 eV for Pb30B45 and Pb45B30. The optical electronegativity showed enhancement, indicating a rise in the glass structure’s bond power. The reduction in optical basicity supported this conclusion, which refers to forming a covalent bond in the glass structure instead of an ionic bond. To examine the prepared glasses’ radiation shielding characteristics, we measured the mass attenuation coefficients (MAC) at five energies in the 0.184–0.81 MeV range. The results demonstrated that the experimental and XCOM MAC values are closely aligned, thus supporting the experimental setup’s reliability. At 0.184 MeV, the rate of increase in the linear attenuation coefficient (LAC) with adding PbO is significant, with LAC increasing from 3.22 to 4.51 cm−1. While, at 0.71 MeV, the rate of increase in LAC is small, with LAC increasing from 0.39 to 0.48 cm−1. The results of half value layer indicated that to get more protection from the harmful radiation, the shielding material thickness should be increased to get a greater attenuation.
Constraints on dark matter mass in an F(R) gravity model with an additional R2 correction term
Authors: Budhi Romy Hanang Setya , Allaudza’i Danial Ahmad
Published: November 2024

The dominance of dark matter and dark energy presents one of the most significant challenges in cosmology. The chameleon mechanism in F(R) gravity offers a potential solution to this issue. However, many F(R) models encounter a problem known as the singularity problem, where the scalaron mass becomes too heavy to function as dark matter. This study aims to address the singularity problem within the Gogoi-Goswami F(R) model by incorporating an additional R
2 correction term. Assuming the scalaron functions as chameleonic dark matter, its mass must satisfy constraints across various scales, including the electroweak transition phase and galactic structures. By adopting a hierarchical scale with

R

0

≪

R

c

<

m

¯

2

, where R
0 is the Ricci scalar at late-time de Sitter space and

m

¯

represents the inflaton mass scale in Starobinsky's model, and assuming R

c
 ≃ 1 GeV2, the mass constraints during the electroweak transition can be satisfied with α ≃ 1.05. Nevertheless, meeting the required mass constraints on a galactic scale remains a challenge. Alternatively, if R

c
is considered relevant only in the current universe, such that

R

0

≪

R

c

≪

m

¯

2

, these dark matter mass constraints can be more easily met. For example, setting

R

c

≃

m

φ

2

(
gal
)
≃

(
1

0

−
32

)

2

GeV

2

effectively satisfies these constraints.
Experimental study on egress capacity of key facilities in pressurized oxygen-supplement compartments
Authors: Wang 王 Kai-Qiang 开强 , Song 宋 Xue-Hua 雪华 , Liu 刘 Wei-Jun 卫军 , Wen 文 Kang 康 , Shi 石 Zhi-Gang 志钢 , Zhang 张 Jun 俊 , Yao 姚 Bin 斌 , Song 宋 Wei-Guo 卫国
Published: November 2024

Pressurized buildings have emerged as a novel architectural solution to alleviate altitude illness in high-altitude regions. Unlike conventional buildings, evacuation from this kind of building has to experience a depressurization time, which results in air expansion and heat absorption, creating a dense fog and impairing sight within the buildings. Evacuation experiments were performed in a pressurized oxygen-supplement compartment to investigate the pedestrian motion properties. Based on the questionnaires, participants reported varying degrees of symptoms such as ear blockage, reduced environmental noise, and dizziness, which had a measurable impact on their mobility. We focus on the evacuation parameters through three basic building components: staircases, pressure transition cabins, and escape windows. As the visibility in the compartment decreases from high to low, the movement patterns of pedestrian shift from triangular to single-file with a significant decline in evacuation efficiency. It is found that there is a linear relationship between evacuation time and the number of evacuees through escape windows. The pressure transition cabin is a crucial evacuation route in emergencies, and evacuation time is recommended as the key metric for assessing its effectiveness. These findings offer valuable insights for emergency evacuation strategies in pressurized buildings.
Multi-layer Perceptron for Predicting Galaxy Parameters (MLP-GaP): Stellar Masses and Star Formation Rates
Authors: Guo 郭 Xiaotong 晓通 , Fang Guanwen , Feng Haicheng , Zhang Rui
Published: November 2024

The large-scale imaging survey will produce massive photometric data in multi-bands for billions of galaxies. Defining strategies to quickly and efficiently extract useful physical information from this data is mandatory. Among the stellar population parameters for galaxies, their stellar masses and star formation rates (SFRs) are the most fundamental. We develop a novel tool, Multi-Layer Perceptron for Predicting Galaxy Parameters (MLP-GaP), that uses a machine learning (ML) algorithm to accurately and efficiently derive the stellar masses and SFRs from multi-band catalogs. We first adopt a mock data set generated by the Code Investigating GALaxy Emission (CIGALE) for training and testing data sets. Subsequently, we used a multi-layer perceptron model to build MLP-GaP and effectively trained it with the training data set. The results of the test performed on the mock data set show that MLP-GaP can accurately predict the reference values. Besides MLP-GaP has a significantly faster processing speed than CIGALE. To demonstrate the science-readiness of the MLP-GaP, we also apply it to a real data sample and compare the stellar masses and SFRs with CIGALE. Overall, the predicted values of MLP-GaP show a very good consistency with the estimated values derived from spectral energy distribution fitting. Therefore, the capability of MLP-GaP to rapidly and accurately predict stellar masses and SFRs makes it particularly well-suited for analyzing huge amounts of galaxies in the era of large sky surveys.
Brain–computer interfaces patient preferences: a systematic review
Authors: Brannigan Jamie F M , Liyanage Kishan , Horsfall Hugo Layard , Bashford Luke , Muirhead William , Fry Adam
Published: November 2024

Objective. Brain–computer interfaces (BCIs) have the potential to restore motor capabilities and functional independence in individuals with motor impairments. Despite accelerating advances in the performance of implanted devices, few studies have identified patient preferences underlying device design, and each study typically captures a single aetiology of motor impairment. We aimed to characterise BCI patient preferences in a large cohort across multiple aetiologies. Approach. We performed a systematic review of all published studies reporting patient preferences for BCI devices, including both qualitative and quantitative data. We searched MEDLINE, Embase, and CINAHL from inception to 18 April 2023. Two reviewers independently screened articles and extracted data on demographic information, device use, invasiveness preference, device design, and functional preferences. Main results. From 1316 articles identified, 28 studies met inclusion criteria, capturing preferences from 1701 patients (mean age 42.1–64.3 years). The most represented conditions were amyotrophic lateral sclerosis (n = 15 studies, 53.6%) and spinal cord injury (n = 13 studies 46.4%). Individuals with motor impairments prioritised device accuracy over other design characteristics. In four studies where patients ranked performance characteristics, accuracy was ranked first each time. We found that the speed and accuracy of BCI systems in recent publications exceeds reported patient preferences, however this performance has been achieved with a level of training and setup burden that would not be tolerated by most patients. Preferences varied by disease aetiology and severity; amyotrophic lateral sclerosis patients typically prioritised communication functions, whereas spinal cord injury patients emphasised limb control and sphincteric functions. Significance. Our findings highlight that despite advances in BCI performance exceeding patient expectations, there remains a need to reduce training and setup burdens to enhance usability. Moreover, patient preferences differ across conditions and impairment severities, underscoring the importance of personalised BCI configurations and tailored training regimens to meet individual needs.
Enhancing neuroprosthesis calibration: the advantage of integrating prior training over exclusive use of new data
Authors: Thomson Caleb J , Tully Troy N , Stone Eric S , Morrell Christian B , Scheme Erik J , Warren David J , Hutchinson Douglas T , Clark Gregory A , George Jacob A
Published: November 2024

Objective. Neuroprostheses typically operate under supervised learning, in which a machine-learning algorithm is trained to correlate neural or myoelectric activity with an individual’s motor intent. Due to the stochastic nature of neuromyoelectric signals, algorithm performance decays over time. This decay is accelerated when attempting to regress proportional control of multiple joints in parallel, compared with the more typical classification-based pattern recognition control. To overcome this degradation, neuroprostheses and commercial myoelectric prostheses are often recalibrated and retrained frequently so that only the most recent, up-to-date data influences the algorithm performance. Here, we introduce and validate an alternative training paradigm in which training data from past calibrations is aggregated and reused in future calibrations for regression control. Approach. Using a cohort of four transradial amputees implanted with intramuscular electromyographic recording leads, we demonstrate that aggregating prior datasets improves prosthetic regression-based control in offline analyses and an online human-in-the-loop task. In offline analyses, we compared the performance of a convolutional neural network (CNN) and a modified Kalman filter (MKF) to simultaneously regress the kinematics of an eight-degree-of-freedom prosthesis. Both algorithms were trained under the traditional paradigm using a single dataset, as well as under the new paradigm using aggregated datasets from the past five or ten trainings. Main results. Dataset aggregation reduced the root-mean-squared error (RMSE) of algorithm estimates for both the CNN and MKF, although the CNN saw a greater reduction in error. Further offline analyses revealed that dataset aggregation improved CNN robustness when reusing the same algorithm on subsequent test days, as indicated by a smaller increase in RMSE per day. Finally, data from an online virtual-target-touching task with one amputee showed significantly better real-time prosthetic control when using aggregated training data from just two prior datasets. Significance. Altogether, these results demonstrate that training data from past calibrations should not be discarded but, rather, should be reused in an aggregated training dataset such that the increased amount and diversity of data improve algorithm performance. More broadly, this work supports a paradigm shift for the field of neuroprostheses away from daily data recalibration for linear classification models and towards daily data aggregation for non-linear regression models.
Synergetic Repetition Frequency Locking of an Optical Frequency Comb
Authors: Jin Ziyi , Yu Dongrui , Chen Ziyang , Guo Hong
Published: November 2024

This paper proposes a method to achieve long-term locking of the repetition frequency of the optical frequency comb under severe temperature fluctuations by cooperatively adjusting the cavity length of the resonator using piezoelectric ceramic, temperature control module, and delay line module. This method enhances the practicability and usability of optical frequency comb at a low cost.
Fringes and Light Shift in CPT-Ramsey Spectroscopy
Authors: Morinaga Atsuo , Yanagimachi Shinya
Published: November 2024

The CPT-Ramsey fringes are solved based on the time evolution of the Bloch vector and are calculated in the steady-state condition and in the pre-steady state condition. A consistent formula of the light shifts in the CPT-Ramsey fringes is presented due to the detection-time, the free evolution time, and the excitation-time. For a further reduction of the light shift, we propose to use the CPT-Ramsey fringes in the pre-steady state condition.
Dual-atom-interferometric gyroscope with continuous cold atomic beams
Authors: Wang Shengzhe , Meng Zhixin , Yan Peiqiang , Feng Yanying
Published: November 2024

In closed-loop dual-atom interferometers, the initial phase shift is a non-inertial phase induced by Raman pulses. This initial optical phase affects the measurements of both acceleration and rotation rate. In this study, we present a method to modulate the initial optical phase of light pulse atom interferometers (LPAIs). Employing this modulation method, we investigated the influence of the initial optical phase on a closed-loop dual-atom interferometer. The results reveal a better short-term sensitivity in the rotation rate measurement at an initial optical phase of 0. Our closed-loop dual-atom interferometer allows for decoupled measurements of rotation rate and acceleration. With a short interrogation time of 2T = 1.73 ms, the short-term sensitivities of the rotation rate and acceleration measurements are

2.73
×

10

−
5

(
rad
/
s
)
/

Hz

and

272
μ
g
/

Hz

, respectively.
Numerical Study on the Reinforcement Design of an Exhaust Pipe on a Locomotive Engine
Authors: Xing Yu , Xue Dongxin , Xiang Gong , Li Ruoxuan
Published: November 2024

The failure analysis of a bracket which supports an exhaust pipe on a locomotive engine is described in this paper. The structure is made of gray cast iron. Crack initiated at the foundation of the bracket after the locomotive engine serviced for more than three months. Static structural analysis was performed to provide the stress contribution of the structure, which was found still below the ultimate tensile strength of the material. On the other hand, the exhaust pipe impacted onto the end and caused vibration. From the model analysis of the structure and the Fast Fourier Transformation (FFT) of the exciting force, some natural frequencies are close to the peak value in the FFT spectrum and then resonance occurred. A new type of structure was designed not only to avoid resonance but also to stiffen the bracket strength. Moreover, spheroidal graphite cast iron (SG iron) can provide better structural performance than gray cast iron. From the modal analysis of the new structure, the natural frequencies were raised. Furthermore, vibration tests and dynamic strain analysis were performed. From the results, resonance was avoided successfully and the stress on the structure decreased.
Nano-biofertilizers: utilizing nanopolymers as coating matrix—a comprehensive review
Authors: Thirumurugan Navin Kumar , Velu Gomathi , Murugaiyan Senthilkumar , Maduraimuthu Djanaguiraman , Ponnuraj Sathyamoorthy , D J Sharmila , Subramanian K S
Published: November 2024

In modern agriculture, nanotechnology was recognized as a potentially transformative innovation. Nanopolymers as coating matrix in nano-biofertilizer has a massive impact on agricultural productivity. The integration of nanotechnology with biofertilizers has led to the creation of nano-biofertilizer formulations that enhance nutrient delivery, improve plant growth, and increase resistance to environmental stress. Nanopolymers, both synthetic and biogenic, including chitosan, cellulose, gelatin, sodium alginate, starch, and polyvinyl alcohol, are utilized as encapsulating materials. They are effective in ensuring controlled nutrient release and shielding beneficial microorganisms from external environmental conditions. Studies indicate that nano-biofertilizers improve soil quality, raise crop yields, and reduce the usage of chemical fertilizers to enhance sustainable agricultural practices. The review also addresses the microbial encapsulation methodology, release kinetics, phytotoxicity, challenges and future prospects of nano-biofertilizer technology, including nanoparticle-bacteria interaction, scalability, and regulatory considerations. This paper elaborates the potential and limitations of nano-biofertilizers, providing insights for future advancements in the agriculture field.
Inhibitory effect of expired glavox tablets on A36 carbon steel for optimized service life
Authors: Omomeji Loveth , Onifade M K , Onokwai A O , Atiba J , Salawu E Y , Joseph O O
Published: November 2024

This research delves into the potential of expired Glavox tablets, containing Amoxicillin and Clavulanic acid, as environmentally friendly substances to inhibit corrosion on A36 carbon steel in solutions of 1M HCl and 3.65 wt% NaCl. The findings from weight loss experiments in 1M HCl indicated a decrease in the corrosion rate, dropping from 1.24 mm y−1 for untreated specimens to 0.17 mm y−1 for specimens treated with 7.5 ml of Glavox solution. Similarly, in the 3.65 wt% NaCl solution, the corrosion rate reduced from 0.98 mm y−1 to 0.23 mm y−1 with the same concentration of inhibitor. Electrochemical assessments conducted in the HCl medium unveiled alterations in the corrosion potential (Ecorr) from −0.48 V to −0.35 V, and a decline in the corrosion current density (icorr) from 3.2 mA cm−2 to 0.42 mA cm−2, indicating a blend of inhibitory characteristics. Within the NaCl medium, Ecorr transitioned from −0.45 V to −0.30 V, while icorr decreased from 2.9 mA cm−2 to 0.57 mA cm−2. Studies on adsorption affirmed the robust adsorption capacity of Glavox on the steel surface, aligning well with Langmuir, Freundlich, and Temkin isotherm models. The formation of a barrier of protection on the inhibited samples was revealed by SEM/EDS examination of the surface morphology. The outcomes propose that expired Glavox tablets exhibit efficacy as corrosion inhibitors in acidic and saline settings, attaining an inhibition efficiency of up to 86%, predominantly through adsorption and the formation of a protective film.