Miracle-dz/UniFAR-FTUs huggingface dataset:
Probabilistic Constellation Shaping for Molecular Communications

Molecular communication (MC) is an emerging field aiming at realizing information exchange via chemical signals between nanomachines in nanonetworks. Information transmission that is energy-efficient and relies on relatively low-complexity transceiver techniques is of practical importance for MC systems. Based on the fact that constellation shaping can improve energy efficiency, in this paper, we propose a molecular shell mapping (MSM) scheme to implement the probabilistic constellation shaping for MC. The MSM method is designed to exploit the concentration sequences with the lowest sum sequence weight, which results in an energy-efficient signal constellation. Furthermore, we propose an algorithm for selecting and sorting the concentration sequences to mitigate inter-symbol interference. For information detection, we design a genie-aided maximum-likelihood (ML) detector and a realistic ML detector to leverage the constructive effect of intra-sequence interference, as well as derive their bit error rates and achievable rates. Additionally, for the applications using large blocklength sequences, a low-complexity ML detection method is proposed. Numerical simulation results confirm that the shaped signaling using the MSM method is more energy-efficient than the conventional equiprobable signaling, achieving shaping gains of up to 1.5 dB at an ultra-short blocklength of 4.
Distributed optimisation design with triggers for disturbed continuous-time multi-agent systems

A distributed optimisation problem is investigated for disturbed continuous-time multi-agent systems with discrete-time communication and gradient measurement. First, a distributed optimisation algorithm with time-triggered communication and gradient measurement is proposed. Then an event-triggered communication strategy and an event-triggered gradient measurement strategy are developed, and a distributed optimisation algorithm combining these two event-triggered strategies is designed, in which the two event-triggered strategies are free of Zeno behaviour. Moreover, the exponential convergence of system can be guaranteed by using the internal model design to reject the external disturbance. Finally, an example illustrates the effectiveness of the proposed algorithms.
“Look before you leap”: comparing the turnover intention of nurses as public servants and private employees

PurposeIn recent decades, human resource management (HRM) in health organizations has faced several problems associated with employees' efficiency and happiness, which has been particularly exacerbated after the pandemic crisis. In this scenario, this study seeks to analyze nurses' turnover intention by comparing Portuguese public and private healthcare organizations. As determining factors, transformational leadership, perceived organizational support and organizational commitment were considered.Design/methodology/approachA survey was digitally applied to 277 nurses from Portuguese public and private healthcare organizations.FindingsResults suggested that there are differences in nurses' turnover intentions: there is a greater likelihood of nurses in the private sector planning to leave the healthcare organizations the nurses work for when compared to public hospital nurses. Furthermore, nurses in public hospitals perceive lower levels of transformational leadership, organizational support and organizational commitment than those in the private sector. The underlying cause as to the intention of leaving the public sector resides in normative commitment. On the other hand, lower affective commitment explains the intention to abandon the private sector.Practical implicationsThis study is relevant for human resource managers and administrators in public and private hospitals since it enables a diagnosis of the situation, as well as a definition of the most appropriate policies for each of the sectors as a strategy to attract and retain health professionals.Originality/valueThis study is significant as the study provides a better understanding of the reasons which lead nurses to consider leaving the organization where the nurses work and the difference between nursing professionals in public and private hospitals.
Risk factors for the rupture of intracranial aneurysms: a systematic review and meta-analysis

Purpose The study aimed to identify potential risk factors for aneurysm rupture by performing a systematic review and meta-analysis. Materials and methods We systematically searched the PubMed, Embase, and Cochrane Library electronic databases for eligible studies from their inception until June 2023. Results Eighteen studies involving 17,069 patients with unruptured intracranial aneurysm (UIA) and 2,699 aneurysm ruptures were selected for the meta-analysis. Hyperlipidemia [odds ratio (OR): 0.47; 95% confidence interval (CI): 0.39–0.56; p < 0.001] and a family history of subarachnoid hemorrhage (SAH) (OR: 0.81; 95% CI: 0.71–0.91; p = 0.001) were associated with a reduced risk of aneurysm rupture. In contrast, a large-size aneurysm (OR: 4.49; 95% CI: 2.46–8.17; p < 0.001), ACA (OR: 3.34; 95% CI: 1.94–5.76; p < 0.001), MCA (OR: 2.16; 95% CI: 1.73–2.69; p < 0.001), and VABA (OR: 2.20; 95% CI: 1.24–3.91; p = 0.007) were associated with an increased risk of aneurysm rupture. Furthermore, the risk of aneurysm rupture was not affected by age, sex, current smoking, hypertension, diabetes mellitus, a history of SAH, and multiple aneurysms. Conclusion This study identified the predictors of aneurysm rupture in patients with UIAs, including hyperlipidemia, a family history of SAH, a large-size aneurysm, ACA, MCA, and VABA; patients at high risk for aneurysm rupture should be carefully monitored. Systematic Review Registration Our study was registered in the INPLASY platform (INPLASY202360062).
Tiny impacts for far-field focusing by plasmonic lens with a free slit-width design

Abstract. We proposed a plasmonic lens (PL) to achieve far-field focusing performance under a 532 nm wavelength. This lens is produced by perforating multiple concentric rings on the gold layer, and the radius and width of the ring can be designed flexibly. Its machining process has adopted the electron beam lithography and lift-off technology. The lenses are designed within a small range of phase delay and the small-sized slits of the PL are replaced with a larger-sized one, which has almost no impact on either the full width at half maximum (FWHM) or the focal length of the PL. With an increase of the slits width, a further enhancement of the spot intensity has been observed. Meanwhile, both the numerical relationships of simulation and experiment are consistent. This method can reduce the difficulty of PL processing, by which the PL with large-sized slits has almost the same performance as that of small-sized ones. The method is of great significance to the low-cost production of modern optoelectronic devices, and it would promote potential applications in optical interconnection devices, controllable focusing, and superresolution imaging.
Leadership during Crisis; Using Change Role Reversal Theory: A Study from Service Sector of Pakistan

In the volatile economic situation, there is a growing interest in Change Role Reversal, due to COVID-19 pandemic that would lead to successful leader-follower relationship. Change role reversal theory become so popular during the COVID-19 pandemic, many businesses have opposed the systemic shock triggered by the COVID-19 pandemic. The key variables of change role reversal are digitalization, employee empowerment, a shift in responsibility, perceived organizational support taken as independent variables that would have a positive impact on the leader-follower relationship and firm performance mediate the relationship between change role reversal and leader-follower relationship. This study follows the quantitative research approach and the philosophy of research is positivism and the research approach is deductive in which hypothesis is generated from the existing theories. This method was used because data about the variables could be collected once at a given time and this research is explanatory. The study unit of analysis had been individual. The research was performed using a descriptive cross-sectional survey method. The data for this study are obtained from the Services industry of Pakistan and the sample is the managerial employees that have interaction with their leaders. Total 450 close-ended questionnaires were distributed to the organizations online and out of which only 290 questionnaires were adopted for analysis. Statistical Package for Social Science (SPSS) and SMART PLS3 are used to check the hypothesis. This study revealed that change role reversal having positive relationship with leader follower relationship and firm performance strongly mediate with the relationship between change role reversal and leader follower relationship. This study offers also limitation and future direction in order to contribute in literature in future.
Anchoring your bridge: the importance of paraphrasing to inference making in self-explanations

ABSTRACT Analyzing constructed responses, such as think-alouds or self-explanations, can reveal valuable information about readers’ comprehension strategies. The current study expands on the extant work by (1) investigating combinations and patterns of comprehension strategies that readers use and (2) examining the extent to which these patterns relate to individual differences and comprehension outcomes. We leveraged archival data from three datasets (n = 472) to examine how comprehension strategy use varied across datasets, texts, and populations (high school, undergraduate). Students’ self-explanations were coded for strategy use and then further analyzed in terms of combinations and patterns of strategies. Our analyses revealed that almost all readers primarily engaged in paraphrasing and/or the combination of paraphrasing and bridging, with few instances of elaboration. Further, the combination of paraphrasing and bridging was the best predictor of performance on a comprehension test. In terms of patterns, switching between strategies was not correlated to reading comprehension and was negatively correlated with the combination of paraphrasing and bridging. Understanding which strategy combinations and patterns are optimal can be used to inform adaptive instruction and feedback that can aid in more individualized support for readers.
Free-wake analysis of twin-rotor systems

A free-wake analysis of twin-rotor systems is described. The analysis uses a recently developed pseudo-implicit predictor-corrector (PIPC) relaxation algorithm for the solution of the governing differential equations of the tip vortex geometries. Typical results are shown for tandem, side-by-side and co-axial rotor configurations.
IPAPS: An improved public auditing protocol for secure data storage in cloud‐based medical storage system

Cloud‐based medical storage system is becoming popular. Cloud server is curious about the private information of stored cases, and the integrity of outsourced data has become increasingly concerned. Numerous public auditing protocols for the outsourced data into the cloud server were proposed. Unfortunately, in the existing protocols, some of them may neglect security to improve efficiency. Recently, Li et al. proposed an efficient privacy‐preserving public auditing protocol for cloud‐based medical storage system (EPPAP), which improved the communication efficiency by storing some of data owner's data in third part auditors, however we find that the protocol is vulnerable to collusion attack and replace attack. In this paper, we analyze the security attacks of the existing protocol, and further propose an improved public auditing protocol for secure data storage in cloud‐based medical storage system (IPAPS). In addition, we give the formal security proof and analyze the performance of our proposed protocol. The security proof shows our protocol takes into account integrity, collusion attack and replace attack at the same time. The simulation experiments in our performance analysis show that the proposed protocol is practical.
Uniaxial-stress tuned large magnetic-shape-memory effect in Ni-Co-Mn-Sb Heusler alloys

Combined strain and magnetization measurements on the Heusler shape-memory alloys Ni45Co5Mn38Sb12 and Ni44Co6Mn38Sb12 give evidence for strong magneto-structural coupling. The sample length changes up to 1% at the martensitic transformation, between a ferromagnetic, austenitic phase at high temperatures and a weakly magnetic, low-symmetry martensitic phase at lower temperatures. Under moderate uniaxial stress, the change in the sample length increases to and saturates at about 3%, pointing to stabilization of a single martensitic variant. A reverse martensitic transformation can also be induced by applying magnetic field: we find that within the temperature range of thermal hysteresis of the martensitic transformation, applying a field can induce a metastable expansion of the sample, while at slightly lower temperatures, the field response is reversible. These findings provide key information for future use of Ni(Co)-Mn-Sb-based Heusler compounds in, e.g., actuators and mechanical switches.
Analysis of Motorcycle Accident Injury Severity and Performance Comparison of Machine Learning Algorithms

Motorcycle road traffic accidents represent a big concern, as vulnerable road users account for more than half of all road deaths worldwide. The estimation of the influential factors associated with the increase of injury severity of motorcyclists involved in a road accident is of extreme importance as it provides a necessary basis for the development of an appropriate and targeted sustainable prevention plan for improving road safety. This study adopted the decision tree, ordered logistic regression (LR), random forest (RF), gradient boosting, extreme gradient boosting, k-nearest neighbor, and support vector machine methods to predict the injury severity outcome of motorcycle accidents. All the developed models were compared with six different performance metrics. A 10-year (2010–2019) dataset with motorcycle accidents that occurred in Portugal was used for analysis. As usual in traffic accidents datasets, this dataset is class unbalanced which was dealt with by under-sampling. The developed models made it possible to determine the factors associated with the increase of injury severity of motorcyclists involved in road accidents. The interpretation of each factor is based on the Shapley additive explanations values. The RF and LR models (developed with the balanced dataset) outperformed the other models. Risk factors associated with alcohol consumption, road type, road conditions, location, motorcycle age, rider’s gender, and when the accident occurs were estimated. This study provides a suitable framework analysis to build a proper predictive model, allowing researchers and practitioners to evaluate more accurately the risk factors of motorcycle injury severity.
The effects of initial vortex size on tropical cyclogenesis and intensification

Three high‐resolution numerical simulations are carried out to investigate the effects of initial vortex size on tropical cyclogenesis and intensification, starting with a relatively weak initial vortex with a maximum tangential wind speed of 5 m s−1, but located at different radii. In all simulations, there is a progressive organization of convectively induced, cyclonic relative vorticity into a monopole structure. As the initial vortex size is increased, the organization occurs later. In addition, the size of the vorticity monopole, the sizes of the inner and outer core tangential wind circulations and the lifetime intensity of the vortex all become larger. An explanation for this behaviour is offered in terms of a boundary‐layer control of the overturning circulation. The findings are consistent with those of previous studies that bypass the genesis stage and start with appreciably stronger initial vortices.
U-PEN++: redesigning U-PEN architecture with multi-head attention for retinal image segmentation

In the era of the ever-increasing need for computing power, deep learning (DL) algorithms are becoming critical for accomplishing success in various domains, such as accessibility and processing of information from the quantum of data present in the physical, digital, and biological realms. Medical image segmentation is one such application of DL in the healthcare sector. The segmentation of medical images, such as retinal images, enables an efficient analytical process for diagnostics and medical procedures. To segment regions of interest in medical images, U-Net has been primarily used as the baseline DL architecture that consists of contracting and expanding paths for capturing semantic features and precision localization. Although several forms of U-Net have shown promise, its limitations such as hardware memory requirements and inaccurate localization of nonstandard shapes still need to be addressed effectively. In this work, we propose U-PEN++, which reconfigures previously developed U-PEN (U-Net with Progressively Expanded Neuron) architecture by introducing a new module named Progressively Expanded Neuron with Attention (PEN-A) that consists of Maclaurin Series of a nonlinear function and multi-head attention mechanism. The proposed PEN-A module enriches the feature representation by capturing more relevant contextual information when compared to the U-PEN model. Moreover, the proposed model removes excessive hidden layers, resulting in less trainable parameters when compared to U-PEN. Experimental analysis performed on DRIVE and CHASE datasets demonstrated more effective segmentation and parameter efficiency of the proposed U-PEN++ architecture for retinal image segmentation tasks when compared to U-Net, U-PEN, and Residual U-Net architectures.
Oscillation of a bubble in a liquid confined in an elastic solid

A simple theoretical model is described for the oscillation of a gas bubble in a liquid in a cavity confined by an elastic solid. The phenomenon occurs in nature and technology but has only recently received attention. The compressibility effects in the continuity equation are shown to be negligible, using dimensional analysis. However, the volume change of the confined liquid has to be considered since the associated pressure variation is large. The variation of the cavity volume is assumed to be proportional to the change of the liquid pressure at the confinement wall. The Rayleigh-Plesset-like equation describing the dynamics of a confined bubble is derived, considering the viscous and surface tension effects. Using the linear stability analysis, we show that the bubble undergoes stable damping oscillation when it is subject to small disturbances. The natural frequency of oscillation is obtained analytically. The theory agrees well with recent experiments. The analyses show that the natural frequency of oscillation for a bubble in an elastic confinement is larger, in order of magnitude, than that in an unbounded liquid. The amplitude and period of oscillation of a transient bubble decrease significantly owing to the presence of a confinement, reaching a steady state in a much longer period and at a larger equilibrium radius. When subject to an acoustic wave, a bubble in a confinement oscillates at smaller amplitude. The effects of the confinement increase with the bulk modulus of the confinement and decrease rapidly with the cavity size but are still significant for a large cavity whose size is an order of magnitude larger than the bubble.A simple theoretical model is described for the oscillation of a gas bubble in a liquid in a cavity confined by an elastic solid. The phenomenon occurs in nature and technology but has only recently received attention. The compressibility effects in the continuity equation are shown to be negligible, using dimensional analysis. However, the volume change of the confined liquid has to be considered since the associated pressure variation is large. The variation of the cavity volume is assumed to be proportional to the change of the liquid pressure at the confinement wall. The Rayleigh-Plesset-like equation describing the dynamics of a confined bubble is derived, considering the viscous and surface tension effects. Using the linear stability analysis, we show that the bubble undergoes stable damping oscillation when it is subject to small disturbances. The natural frequency of oscillation is obtained analytically. The theory agrees well with recent experiments. The analyses show that the natural frequency o.
Hybrid Classification Ann, Dwt and Fractal Analysis for Directional Textures

In this paper, we present a hybrid directional classification of anisotropic textures. Our proposed method based to yield a robust attributes vector to classify the different anisotropic textures. A robust fractal analysis is put forward by hybridization of the statistical fractal with Discrete Wavelets Transform (DWT). Beside, to enhance the quality of texture, a preprocessing stage using histogram equalization is carried out. Then for a given direction from 0° to 360° by a step of 10°, we applied the DWT using Daubechies wavelets (db5) to the corresponding direction where the approximate image is inputted to Differential Box-Counting Method (DBCM) in order to yield a robust Fractal Dimension (FD) estimated in wavelets domain. We formed the vector attributes to each texture that correspond to the inputs of our Artificial Neurons Network (ANN) classifier. The originality of our work, reside in the use of the Daubechies Wavelets (db5), in particular the use of approximate image with the fractal analysis, by, estimating the directional FD and using the directional classification based on ANN classifier. To validate our algorithm, we used two classes of the Brodatz textures database. Performance classification was assessed by ROC analysis and confusion matrix. We report a successful separation of the two classes, after different training. Area under-curve (AUC) values for training, validation and testing are 1, 0.96 and 1 and classification rates are 94.1%, 85.7%, 85.7% respectively, with the classification rate for all data is 91.7% and a fail classification is 8.3%.
High-Temperature Superconductivity and Lattice Relaxation in Lithium-Deposited FeSe on SrTiO3

We studied the effect of strain, interface, and electron doping on the superconductivity in thin FeSe film on SrTiO3 by angle-resolved photoemission spectroscopy (ARPES). We observed the superconductivity with Tc as high as 43 K in a lithium (Li) deposited heavily electron-doped multilayer FeSe film. We found a significant relaxation of tensile strain at the surface in contrast to the case of potassium (K) deposition, although the high-Tc superconductivity is commonly observed in both cases. We discuss the interplay among carrier doping, tensile strain, and high-Tc superconductivity by comparing ARPES results on Li- and K-deposited FeSe films.
Inflation and cosmological evolution with F(R,G) gravity theory

In the last decade Planck PR4 data together with ground-based experimental data such as, BK18, BAO and CMB lensing, tightened constraint of the tensor to scalar ratio, starting form $r<0.14$ to $r<0.032$, while the spectral index lies within the range $0.9631<n_s<0.9705$. Viability of modified gravity theories, proposed as alternatives to the dark-energy issue, should therefore be tested in the light of such new result. Here, we explore $F(R,G)$ gravity theory in regard of the early universe and have shown that, it is not compatible with newly released constraints on $r$ and $n_s$ simultaneously. Further, it also fails to produce a feasible radiation dominated era. It therefore questions the justification of using the model for resolving the cosmic puzzle.