Miracle-dz/UniFAR-FTUs huggingface dataset:
A Novel Ultrasound-Guided “Three in One” Approach Plus Interfascial Plane Blocks for the Treatment of Cervicogenic Headache

Objective Cervicogenic headache (CEH) is a condition resulting from upper cervical spine dysfunction and associated structural and soft tissue abnormalities, significantly impacting patients’ quality of life. To acquire better therapeutic results, we presented a novel ultrasound-guided “three in one” approach plus interfascial plane (IFP) blocks for the treatment of CEH. This approach allows for the modulation of C2 dorsal root ganglion (DRG), third occipital nerve (TON), and C3 medial branch with one-point puncture. Additionally, it allows for IFP blocks between the upper neck and occipital muscles within the same scanning plane. Patients and Methods We evaluated patients diagnosed with CEH from July 2021 to December 2022 in our pain clinic. We included those who did not respond to conservative treatment and single occipital nerve block, therefore received nerve block or pulsed radiofrequency (PRF) using the “Three in One” approach plus IFP blocks. The accuracy of the ultrasound-guided C2 DRG puncture procedures was confirmed through fluoroscopy with C-arm and the sensory testing of PRF. The therapeutic effect of these interventions was assessed using the numerical rating scale (NRS) scores during telephone follow-ups at 1, 3, and 6 months. Results Utilizing the “Three in One” approach, a total of 5 patients diagnosed with CEH underwent nerve block plus IFP blocks, while 2 patients underwent PRF plus IFP blocks. Employing ultrasound-guided C2 DRG puncture procedures, the needle tip’s correct placement was confirmed through both fluoroscopy and sensory testing of PRF. Notably, none of the cases experienced any complications associated with the approach. Subsequent follow-up assessments revealed an improvement in the NRS scores for CEH in all patients. Conclusion The ultrasound-guided “Three in One” approach plus IFP blocks may be a potential effective method for the treatment of CEH.
An Anti-Oxidative Bioink for Cartilage Tissue Engineering Applications

Since chondrocytes are highly vulnerable to oxidative stress, an anti-oxidative bioink combined with 3D bioprinting may facilitate its applications in cartilage tissue engineering. We developed an anti-oxidative bioink with methacrylate-modified rutin (RTMA) as an additional bioactive component and glycidyl methacrylate silk fibroin as a biomaterial component. Bioink containing 0% RTMA was used as the control sample. Compared with hydrogel samples produced with the control bioink, solidified anti-oxidative bioinks displayed a similar porous microstructure, which is suitable for cell adhesion and migration, and the transportation of nutrients and wastes. Among photo-cured samples prepared with anti-oxidative bioinks and the control bioink, the sample containing 1 mg/mL of RTMA (RTMA-1) showed good degradation, promising mechanical properties, and the best cytocompatibility, and it was selected for further investigation. Based on the results of 3D bioprinting tests, the RTMA-1 bioink exhibited good printability and high shape fidelity. The results demonstrated that RTMA-1 reduced intracellular oxidative stress in encapsulated chondrocytes under H2O2 stimulation, which results from upregulation of COLII and AGG and downregulation of MMP13 and MMP1. By using in vitro and in vivo tests, our data suggest that the RTMA-1 bioink significantly enhanced the regeneration and maturation of cartilage tissue compared to the control bioink, indicating that this anti-oxidative bioink can be used for 3D bioprinting and cartilage tissue engineering applications in the future.
Multi-region relaxed magnetohydrodynamic stability of a current sheet

It is shown that the resistive magnetohydrodynamic stability of a slab force-free current sheet can be calculated using the variational principle of multi-region relaxed magnetohydrodynamics and that the corresponding stability boundary is in exact agreement with linear tearing mode theory.It is shown that the resistive magnetohydrodynamic stability of a slab force-free current sheet can be calculated using the variational principle of multi-region relaxed magnetohydrodynamics and that the corresponding stability boundary is in exact agreement with linear tearing mode theory.
Secure computation protocols under asymmetric scenarios in enterprise information system

ABSTRACT It has become acentral question to guarantee the security of sensitive data in enterprise information systems. Actually, different enterprises may grasp asymmetric information due to their scales. How to guarantee the computation security under such scenario is acrucial problem for enterprise information system. In this paper, we propose asecure computation protocol under asymmetric information scenario in the presence of rational parties. We also work towards the achievement of security properties in enterprise information systems. Our new definition of utilities is proved to be coincident (and compatible) with the former definitions under asymmetric information scenario.
A Comprehensive Review on Cyber-Attacks in Power Systems: Impact Analysis, Detection, and Cyber Security

Continuous communication and information technology advancements facilitate the modernization of the conventional energy grid into an integrated platform. Internet-of-Things (IoT) incorporates power systems, particularly smart grid features and the delivery of new services from the utility side to the end user over a two-way communication channel. However, severe security vulnerabilities have been created due to over-dependency on IoT based communication systems. In addition, critical information exchange between any two entities or devices is always an appealing target for cyber-attackers, especially with financial interest motive by damaging integrity, confidentiality and authenticity in a communication channel. Maintaining data security and preserving privacy in between two entities during the transmission or any data distribution are essential. The potential attacks and impacts of those attacks need to be investigated to develop an effective cyber security infrastructure. Thus, considerable researchers focused on detection and mitigation of these vulnerable cyber-attacks using advanced computation tools. This review article thoroughly investigated possible ways to address cyber security challenges such as smart meter security, end-users privacy, electricity theft cyber-attacks using blockchain and cryptography against communication attacks in smart grid. The operational impacts of cyber-attacks on power system security, as well as the economic impact on deregulated energy markets, have been extensively explored. In addition, the robustness of security features and cryptographic methods against various cyber-attacks is investigated to suggest unexplored cyber-attacks for future scope. Specially, the study of real-world cyber security events, case studies, new findings and new scopes in diverse power industries are carried out. More than 135 research articles has been examined for this review article. This paper mainly concentrates on distribution-side cyber-attacks with impact analysis, detection and protection techniques.
Understanding Users’ Multi-Homing Intention on Peer-to-Peer Accommodation Platforms

An intriguing phenomenon in short-term accommodation market is that most users would adopt more than one accommodation platforms simultaneously, instead of being committed to utilizing only one platform. However, little attention has been paid to the underlying mechanisms about why users employ multiple accommodation platforms concurrently. To bridge the research gap, this study proposes a research model to investigate users’ multi-homing intention on accommodation platforms by combining benefit-cost framework, social influence and need for cognition theory. This model is tested using data collected from 437 users who have ever used multiple accommodation platforms. Analytical results indicate that perceived information complementarity and decision complementarity contribute to users’ multi-homing intention. Social influence and need for cognition have significant positive effects on the intention. Moreover, seeking cost decreases users’ intention to adopt several competing platforms at the same time, while integration cost promotes the intention. At the end, implications for research and practice as well as limitations of this study are discussed.
Validation industrielle de la mesure du différentiel d'eau dans une colonne de flottation

Flotation is a separation process whose objective is to separate the valuable minerals from the ore gangue for their recovery in the form of a concentrate. During this process, two steps are can be identified: the first one is the selection and collection of valuable particles and then, the objective of the second step is the recuperation of those particles from the device. The product obtained is the concentrate, which is then commercialized by mining companies for profit. These concentrates are evaluated with economic terms found in a document named the Smelter contract. The objective of this contract is to standardize the quality and the quantity of the concentrate sold by the concentrators to the foundries. For this reason, a key objective, in order to maximize profits while respecting the specifications of the client, is to be able to control the recovery and the content of the valuable particles in the concentrate produced. The research project developed by Université Laval seeks to attain this objective using as an example a standard separation device known as a flotation column. The project is being executed in various steps. The first step is to measure and control the variables involved in the optimization of recovery and grade. The project develops around a pilot column 7.2 m high and 14 cm in diameter. This column is fed with the same pulp as an industrial cleaning column in the copper circuit of the Laronde concentrator (Agnico-Eagle Mines). This experimental column has sensors to measure the level, gas hold-up and bias rate, all based on the use of electrical conductivity as an on-line measurable property. The last of these variables corresponds to the net downward water flow, which passes through the interface between the froth and the pulp in a flotation column. As such it is to a great extent considered responsible for the grade in the cleaning flotation step of the flotation circuits [7], [8], [9]. The first stage of the research was done by a multidisciplinary group from the department of electrical engineering and the department of mines, metallurgy and materials engineering of Université Laval, and the objective was to build, install and operate a pilot column and its accessories (pumps, tanks, etc.) in an industrial environment. Then, Riquelme [25] developed a new electronic measuring system designed to measure electrical conductivity in the column's control system and, particularly, in the on-line froth-depth and gas hold-up sensors. This research presents the validation of the measuring system developed by Riquelme in the Université Laval's flotation laboratory. The same system was then tested in a three phases system in the pilot column installed at the Laronde concentrator. The acquired results permitted the development of a methodology to obtain an empirical relation, which allows estimating the bias rate on-line. The application of this method to industrial columns of this concentrator should be considered in the near future.
Learn Stable MRI Under-Sampling Pattern With Decoupled Sampling Preference

Accelerating the scanning time of magnetic resonance imaging (MRI) and improving the imaging quality is critical to the patient experience in clinical applications. In accelerated MRI, MR data can be under-sampled in the raw k-space, and the available measurements are used for image reconstruction. Many recent studies have shown that the quality of image reconstruction depends largely on the MRI under-sampling pattern. Our study shows that the way to binarize sampling masks in previous deep-learning-based under-sampling patterns leads to unstable reconstruction results when cooperating with data-driven reconstruction methods. Therefore, we design a stable under-sampling pattern learning strategy, which straightly optimizes the sampling mask at fixed k-space locations. In addition, our method designs the sampling pattern from both reconstruction contribution and reconstruction capacity perspectives, which are not considered in previous approaches. We decouple the under-sampling preferences and form a new paradigm for pattern optimization. To accelerate the joint learning process, we utilize prior knowledge of the MRI k-space energy distribution to guide the optimization of under-sampling patterns in our proposed paradigm. Experimental results demonstrate that our proposed under-sampling pattern learning strategy can yield better reconstruction quality than previous methods and facilitate the training process, irrespective of the task being single-coil MRI reconstruction or parallel MRI reconstruction.
FORECASTING TYPHOON CHABA'S (2004) INTENSITY CHANGE USING A COUPLED ATMOSPHERE-OCEAN-WAVE MODEL

Recorded 10 typhoons have destroyed many lives of coastal residents on the Japan islands in the 2004 Northwest Pacific typhoon season. Typhoonand flood-related claims for the fiscal 2004 were 18 times higher than that of the previous year (5 billion dollars). To reduce such disaster risks, an early warning system, which can provide highly accurate information of the track (latitude and longitude of the storm center) and intensity (central pressure, maximum sustained wind speed, and radius of 50kt winds) of an approaching storm, must be implemented and refined. Several meteorological organizations, JTWC Guam, NHC Miami, CPHC Honolulu and RSMC Tokyo routinely provide first-level basic information of future position and intensity of tropical cyclones in each basin. In recent years, dynamic models of tropical cyclones are generally used for predictions. Although rapid developments of meteorological, remote sensing and computing technologies make it possible to simulate a track of a tropical cyclone with high accuracy, it would be difficult to evaluate the storm intensity even in short-term forecasts because of the following reasons: (1) still lack of spatial resolution in current models, (2) the inadequate parameterizations of key air-sea interaction processes, (3) the inconsistency of the typhoon initialization method using a tropical cyclone bogussing scheme. The objectives of this study are to develop a high-resolution atmosphere-ocean-wave coupled model for tropical cyclone forecasts over the Northwest Pacific Ocean, and to quantify the impact of complex sea surface processes on Typhoon Chaba’s (2004) intensity change, as a case study of a hazardous event which affected the coastal areas of the Japan islands in August 2004.
Optimized Genetic Algorithm (OGA) for Homogeneous WSNs

A wireless sensor network (WSN) is a network consisting of wireless computing devices called sensors that sense environmental conditions like motion, sound, etc in an area. These networks collect the information from the environment and send it to the sink node. The main constraint in these networks is the energy of the nodes. As these sensors have limited battery life, routing protocol should be designed appropriately so that minimal energy is used. Long communication distances between the sensors and the sink in the WSN drain the energy of the sensors and reduce the lifetime of the network. Clustering reduces energy consumption. By clustering a sensor network we can help minimize the total communication distance, thus increasing the network lifetime. In this paper, we an algorithm based on LEACH (Low Energy Adaptive Clustering Hierarchy protocol) using genetic algorithm has been proposed in order to achieve increased lifetime of the network and energy efficiency in WSN. The genetic algorithm is used to select the cluster heads for the WSN and hence create the energy efficient clusters for transmission of data in the wireless sensor network. The fitness function proposed in this algorithm considers both the distance of the nodes from the sink and their energies. The simulation results show that the proposed protocol results in prolonged network lifetime and optimal energy consumption of the wireless sensor network.
Reduced Model Predictive Control Toward Highly Dynamic Quadruped Locomotion

Controlling quadruped robots during dynamic motions presents significant challenges due to constraints on ground reaction forces and the inherent complexity of their dynamics. Model predictive control (MPC) has shown promise in addressing these challenges. However, the performance of MPC strongly relies on the accuracy and complexity of the model, making the modeling process critical for dynamic locomotion control. This paper introduces a novel approach using the reduced single rigid body model (SRBM) and an associated MPC for achieving high-frequency control–crucial for highly dynamic locomotion. The reduced SRBM is derived by isolating the key components responsible for robot balance from the full SRBM, reducing model complexity without compromising control performance. Additionally, the planar kinematics is developed that considers the motions neglected in the reduced model. This enables the design of foot trajectories that facilitate omni-directional motion and yaw control. To validate the proposed method, computer simulations are conducted under various scenarios. The simulations demonstrate that the quadruped robot can achieve galloping speeds of up to 7 m/s while remaining stable even when subjected to a lateral disturbance of 200 N.
Crossdating of terminal and reverse-latewood eucalypt tree- rings

Introduction Crossdating is a fundamental dendrochronological principle. However, despite its importance, crossdating has been applied infrequently in the eucalypt dendrochronological literature. One factor limiting crossdating in previous eucalypt tree-ring studies has been the difficulty associated with objective tree-ring identification and measurement, particularly in samples from lower montane (500-800m) sites (Bi 1994). To overcome this problem Brookhouse (1997) proposed the ‘reverse-latewood’ identification technique. In contrast to the terminal form, reverse-latewood occurs at the start of the eucalypt tree-ring (Fig. 1). Whilst tree-ring counts indicate that both terminal and reverse-latewood may indicate truly annual tree-ring boundaries (Brookhouse 1997, Green 1967) crossdating has not been quantitatively demonstrated for either type in eucalypts. The present study was undertaken using samples of known age to investigate the potential of eucalypts to preserve common environmental signals by quantitatively demonstrating crossdating within and between two eucalypt species – one characterised by terminal latewood and the other reverse-latewood – and identifying the climatological source of common signals preserved within the derived tree-ring chronologies.
Progress Estimation for End-to-End Training of Deep Learning Models With Online Data Preprocessing

Deep learning is the best machine learning algorithm for numerous analytical tasks. On a large data set, training a deep learning model frequently lasts several days to several months. Throughout this long period, it would be helpful to show a progress indicator, which continually projects the percentage of model training work accomplished as well as the outstanding model training time. We formerly invented the first method to support this function while allowing early stopping. This method assumes that the input data to the model have been preprocessed before model training starts. This is a limitation. In practice, online data preprocessing is often integrated into the model and done as part of the end-to-end model training. Ignoring online data preprocessing costs can cause our former method to produce inaccurate estimates. To overcome this limitation, this paper presents a new progress estimation method that explicitly considers online data preprocessing. We did a coding implementation of our new method in TensorFlow. Our tests unveil that for various deep learning models that integrate online data preprocessing and in comparison with our former method, our proposed new method produces more stable progress estimates for model training and on average lowers the error of the predicted outstanding model training time by 16.0%.
Low-Power Phototransistor with Enhanced Visible-Light Photoresponse and Electrical Performances Using an IGZO/IZO Heterostructure

In this study, we demonstrated the effective separation of charge carriers within the IGZO/IZO heterostructure by incorporating IZO. We have chosen IGZO for its high mobility and excellent on–off switching behavior in the front channel of our oxide–oxide heterostructure. Similarly, for an additional oxide layer, we have selected IZO due to its outstanding electrical properties. The optimized optoelectronic characteristics of the IGZO/IZO phototransistors were identified by adjusting the ratio of In:Zn in the IZO layer. As a result, the most remarkable traits were observed at the ratio of In:Zn = 8:2. Compared to the IGZO single-layer phototransistor, the IGZO/IZO(8:2) phototransistor showed improved photoresponse characteristics, with photosensitivity and photoresponsivity values of 1.00 × 107 and 89.1 AW−1, respectively, under visible light wavelength illumination. Moreover, the electrical characteristics of the IGZO/IZO(8:2) transistor, such as field effect mobility (μsat) and current on/off ratio (Ion/Ioff), were highly enhanced compared to the IGZO transistor. The μsat and Ion/Ioff were increased by about 2.1 times and 2.3 times, respectively, compared to the IGZO transistor. This work provides an approach for fabricating visible-light phototransistors with elevated optoelectronic properties and low power consumption based on an oxide–oxide heterostructure. The phototransistor with improved performance can be applied to applications such as color-selective visible-light image sensors and biometric sensors interacting with human–machine interfaces.
Atmosphere and ocean energy transport in extreme warming scenarios

Extreme scenarios of global warming out to 2300 from the SSP5-8.5 extension scenario are analyzed in three state-of-the-art climate models, including two models with climate sensitivity greater than 4.5°C. The result is some of the largest warming amounts ever seen in simulations run over the historical record and into the future. The simulations exhibit between 9.3 and 17.5°C global mean temperature change between pre-Industrial and the end of the 23rd century. The extremely large changes in global temperature allow exploration of fundamental questions in climate dynamics, such as the determination of moisture and energy transports, and their relation to global atmosphere-ocean circulation. Three models performed simulations of SSP5-8.5 to 2300: MRI-ESM2-0, IPSL-CM6A-LR, and CanESM5. We analyze these simulations to improve understanding of climate dynamics, rather than as plausible futures. In the model with the most warming, CanESM5, the moisture content of the planet more than doubles, and the hydrologic cycle increases in intensity. In CanESM5 and IPSL-CM6A-LR nearly all sea ice is eliminated in both summer and winter in both hemispheres. In all three models, the Hadley circulation weakens, the tropopause height rises, and storm tracks shift poleward, to varying degrees. We analyze the moist static energy transports in the simulations using a diffusive framework. The dry static energy flux decreases to compensate for the increased moisture transport; however the compensation is imperfect. The total atmospheric transport increases but not as quickly as expected with a constant diffusivity. The decrease in eddy intensity plays an important role in determining the energy transports, as do the pattern of cloud feedbacks and the strength of ocean circulations.