Miracle-dz/UniFAR-FTUs huggingface dataset:
The Redox State of Earth's Mantle

Oxygen thermobarometry measurements on spinel peridotite rocks indicate that the oxygen fugacity at the top of the upper mantle falls within ±2 log units of the fayalite-magnetite-quartz (FMQ) oxygen buffer. Measurements on garnet peridotites from cratonic lithosphere reveal a general decrease in fo2 with depth, which appears to result principally from the effect of pressure on the controlling Fe3+/Fe2+ equilibria. Modeling of experimental data indicates that at approximately 8 GPa, mantle fo2 will be 5 log units below FMQ and at a level where Ni-Fe metal becomes stable. Fe-Ni alloy and an Fe2O3-garnet component will be formed as a result of the disproportionation of FeO, which is experimentally demonstrated through observations of high Fe3+/ΣFe ratios in minerals in equilibrium with metallic Fe. In the lower mantle, the favorable coupled substitution of Al and Fe3+ into (Fe,Mg)SiO3 perovskite results in very high perovskite Fe3+/ΣFe ratios in equilibrium with metallic Fe. As a result, the lower mantle sh.
R-AODV: Reverse Ad-Hoc On-Demand Distance Vector Routing Algorithm With LoRa Mesh Based for Emergency Alert System

This research introduces a LoRa mesh network for emergency notification systems, which addresses the challenges of the conventional point-to-point LoRa system, such as limited transmission range and lack of backup paths. The mesh network comprises nodes that serve as relays, facilitating multi-hop data transmission to the gateway. The network also adapts to node failures and route changes by employing the Reverse Ad-hoc On-demand Distance Vector (R-AODV) routing algorithm. The performance of the proposed system was assessed through three types of tests: point-to-point, multi-hop, and node failure. The results indicate that the LoRa mesh network improves network coverage and reliability for emergency communication. The average delay for sending alert messages from the gateway neighbor node to the gateway is 0.82s, from the alarm node to the gateway is 1.54s in normal conditions, and 11.65s in case of a gateway neighbor node failure. The user satisfaction score is 4.31 out of 5.
Managing the Ecosystem by Leverage Points: A Model for a Multispecies Fishery

Ecosystem management has been popularly adopted as a goal of fisheries management, but what does it really mean? In stressed ecosystems, ecosystem functions may remain unchanged while changes in species composition—particularly dominance—and the health of individuals can change dramatically (Schindler et al. 1985). The species are more sensitive indicators of stress than the system. We suggest, therefore, that there is little value in trying to manage a marine ecosystem as a whole. Instead one should manage people’s interaction with the particular ecosystem components that influence the quantity and quality of valued products. We call these particular interactions “leverage points” and use a 5-year study of the southeastern Australian continental shelf fishery ecosystem to show how leverage points can be found. Neither nearshore production nor predation on commercial fish species has a major influence on fisheries production; they therefore have little leverage potential. However, the interaction of benthic habitat with fish and fishers is a potential leverage point. Benthic habitat directly influences the fish community, and specific benthic habitats are vulnerable to fishing. Their vulnerability is increasing because of technological advances in accurate positioning (Global Positioning System) and position recording (trackplotters), fishing vessel power, and fishing gear. Accurate positioning can also be used to manage the location of fishing effort. For this leverage point to be successful, the spatial management of fishing effort would need to be developed in collaboration with the fishing industry and to be targeted specifically at the vulnerable habitats. We suggest that new management instruments such as the transferable ecological stock rights are needed to link fisheries management directly to the ecosystem.
Bone mineral density after exercise training in patients with chronic kidney disease stages 3 to 5: a sub-study of RENEXC—a randomized controlled trial

Abstract Background We evaluated the effects of 12 months of exercise training on bone mineral density (BMD) in patients with chronic kidney disease (CKD) stages 3–5 not on kidney replacement therapy (KRT). Methods A total of 151 patients were randomized to 12 months of either balance or strength training, both together with endurance training. Some 112 patients completed and 107 (69 men, 38 women) were analysed, with a mean age 66 ± 13.5 years and 31% having diabetes. The exercise training was self-administered, prescribed and monitored by a physiotherapist. Total body, hip and lumbar BMD, T score and Z score were measured at baseline and after 12 months using dual energy X-ray absorptiometry. Results Both groups showed increased physical performance. The prevalence of osteoporosis and osteopenia was unchanged. The strength group (SG) decreased total body BMD (P < .001), the balance group (BG) increased total body T score (P < .05) and total body Z score (P < .005). Total body ΔT score was negative in the SG and unchanged in the BG (P < .005). Total body ΔZ score was negative in the SG and positive in the BG (P < .001). The proportion of progressors measured by ΔT (P < .05) and ΔZ scores (P < .05) was significantly lower in the BG compared with the SG. In multivariate logistic regression analysis, belonging to the BG was the only factor with a lower risk of deterioration of total body BMD, T and Z scores. Conclusions Twelve months of balance training together with endurance training seemed to be superior to strength training in maintaining and improving BMD in patients with CKD not on KRT.
Comparative Performance of CNN and Transformer Architectures in Infrared Small Target Detection

Infrared (IR) small target detection is a challenging task due to the low resolution of IR cameras, the presence of noise and variability, and the similarity of thermal characteristics between small targets and surrounding objects. Deep learning has shown significant improvements in IR small target detection by capturing complex patterns and features. In deep learning-based algorithms, there are convolutional neural networks (CNN) and Transformer-based architectures that utilize attention concepts. This paper focuses on the benefits when Transformer-based architecture, like the Swin UNet, is applied to IR small target detection. So, a comparative simulation is conducted to evaluate the performance of a CNN model and a Transformer model in the context of object detection. The CNN models utilized in the experiment are UNet, UNet++, and UNet 3+, while the Transformer model employed is the Swin UNet. As a result, the experiments demonstrate that the performance of UNet 3+ and Swin UNet are similar. The results indicate that the Transformer-based architecture does not always outperform the existing CNN-based model.
Hybrid IoT Device Selection With Knowledge Transfer for Federated Learning

Federated learning (FL) enables collaborative model training across massively distributed edge devices, such as Internet of Things (IoT) nodes. However, resource constraints impose a major challenge, as there exists a tradeoff between maximizing learning accuracy and minimizing communication overhead between the resource-limited devices. In this article, we present a device selection approach for heterogeneous FL systems based on multiobjective optimization (MOO) and knowledge transfer (KT). We formulate the resource constraint in federated optimization as a multiobjective problem, and obtain Pareto-optimal solutions balancing resource efficiency and test accuracy. Additionally, we introduce an innovative KT mechanism that propagates the globally optimal models obtained during MOO to subsequent FL tasks, further expediting convergence. The multiobjective formulation and KT provide new insights into efficient and robust FL for resource-constrained IoT applications. We conduct extensive experiments on real-world data sets. Results demonstrate that our method achieves up to 11% higher accuracy than state-of-the-art methods, while effectively mitigating resource constraints. Impact Statement—FL is an efficient algorithm that enables everything to be interconnected without sharing data. However, resource constraint is the main challenge for federated optimization problems. Although many works have proposed various solutions from different perspectives, these methods cannot simultaneously minimize the communication resource cost while ensuring algorithm performance. We propose an automatic device selection algorithm for federated systems based on MOO and KT. This work not only reduces the global resource usage rate of FL but also enables it to converge quickly.
A QoS Throughput Performance Measurement Comparison between UGS and BE Services of a Real-time FPGA Based OFDM Multi-user System Design Implementation

It is defined in IEEE 802.16e that there are five different Quality of Service (QoS) classes, which include: UGS, rtPS, nrtPS, ertPS, and BE. This paper compares the throughput performance measurement results between the UGS and BE scheduling services for every modulation and coding scheme (MCS), which have been implemented in our FPGA-based real-time OFDM multi-user system. There are two FPGA-based RF transceiver boards involved in the one-slot experiment and three FPGA-based RF transceiver boards involved in the two-slot experiment. The downlink transmission is done in FDD, using 241 MHz as the center frequency, and the uplink transmission is done in TDD, using 261 MHz as the center frequency. The transmission scenario used in this experiment is point-to-multipoint (P2MP). The throughput measurement is taken under LOS conditions using cables and quarter-wave antenna connections. We observed that the BE service has higher downlink and uplink throughput compared to the UGS service by utilizing one uplink slot. However, there are almost 50% drops in the throughput results for every MCS in the BE implementation when two uplink slots are utilized. There are some limitations to this experiment, involving the number of subscriber stations, a connection timeout issue, and the experimental condition. Therefore, it is advised to increase the number of subscriber stations and test the system under several wireless conditions for future development.
Relationship between Summer Cross-Equatorial Flows and ENSO

The interannual relationships and its interdecadal variabilities between the intensity of summer 850hPa cross-equatorial flows in the Eastern Hemisphere and ENSO are analyzed by using NCEP/NCAR reanalysis data and the sea surface temperatures data of Hadley Center.Results show that Mascarene High was weaker(stronger) and Australia High stronger(weaker) than normal in the El Nino(La Nina) years,which caused summer 850hPa Somali jet was weaker(stronger) and the cross-equatorial flows of about 90°E,105°E,125°E and 150°E were stronger(weaker) than normal.The interannual relationship between Somali jet and ENSO was weakened in the late 1970s while the interannual relationships between the cross-equatorial flows of about 105°E,125°E and 150°E and ENSO were enhanced in the late 1960s.
Federal Reserve Structure and the Production of Monetary Policy Ideas

We evaluate the decentralized structure of the Federal Reserve System as a mechanism for generating and processing new ideas on monetary policy over the 1960 - 2000 period. We document the introduction of monetarism, rational expectations, credibility, transparency, and other monetary policy ideas by Reserve Banks into the Federal Reserve System. We argue that the Reserve Banks were willing to support and develop new ideas due to internal reforms to the FOMC that Chairman William McChesney Martin implemented in the 1950s and the increased ties with academia that developed in this period. Furthermore, the Reserve Banks were able to succeed at this because of their private-public governance structure. We illustrate this with a time-consistency model in which a decentralized organization is better at producing new ideas than a centralized one. We argue that this role of the Reserve Banks is an important benefit of the Federal Reserve’s decentralized structure by allowing for more competition in formulating ideas and by reducing groupthink.
An Analysis on the Relationship between Exchange Rate and Stock Prices in the Short-Run and Long-Run: NARDL Model Results for the Kuwait Economy

An analysis on the relationship between exchange rate and stock prices in the short-run and long-run: NARDL model results for the economy. Abstract The aim of this paper is to search for a possible asymmetric effect of the exchange rate on the stock market by Nonlinear Autoregressive Distributed Lag Model using the data spanning June 2002 – March 2018 for an oil producer country, Kuwait, while controlling consumer prices, interest rate, money supply and oil prices. Results are statistically preferable compared to linear models and there is a weak form of efficiency in the stock market. Appreciation of the local currency has a negative effect on stock prices in the long-run but depreciation has not a statistically significant effect so there is a case of long-run asymmetry . However, in the short-run, the exchange rate has no statistically significant effect on stock prices and there is no asymmetric causality .
A Fuzzy Neural Controller for Model-Free Control of Redundant Manipulators With Unknown Kinematic Parameters

In real-world robotics applications, kinematic parameters of redundant manipulators may need to be changed, thus creating difficulties in achieving precise control. To address this issue, this article proposes a fuzzy neural controller to learn kinematic parameters online and synchronously achieve the model-free control of redundant manipulators. Specifically, this controller consists of a gradient-based fuzzy (GBF) subsystem and a neural dynamics (ND) subsystem. On the one hand, the GBF subsystem is designed to achieve online learning of kinematic parameters, considering additional noise and a fuzzy parameter. Notably, the fuzzy parameter can drive the GBF subsystem to automatically terminate the learning process and convert the acquired information into usable structural knowledge once the kinematic parameters are precisely learned. On the other hand, based on the learned kinematic parameters, the ND subsystem is employed to solve a quadratic programming scheme for the kinematic control of manipulators. Such a scheme implements functions of orientation maintenance, trajectory tracking, and joint constraints in a model-free manner. Theoretical analyses confirm the effectiveness of the proposed controller's learning and control abilities. Finally, simulations, experiments, and comparisons demonstrate the feasibility and superiority of the fuzzy neural controller in controlling manipulators with unknown kinematic parameters.
Learning-Based Predictive Control for Vehicle Following Problems

Recent research shows that the combination of reinforcement learning (RL) with traditional control method can be an effective tool for designing near optimal feedback controller for dynamic systems. In this paper, a vehicle-following control based on reinforcement learning is proposed, in which pairs of the input-output of model predictive control (MPC) are chosen as offline-learning data. Through continuous iterations of actor-network and critic-network, the longitudinal vehicle-following controller can be obtained. Simulation results illustrate that proposed learning-based predictive control (LPC) can improve the computational efficiency, and obtain a better performance of policy optimization.
Coseismic Deformation of the 2015 Mw 6.4 Pishan, China, Earthquake Estimated from Sentinel‐1A and ALOS2 Data

The 2015 M w 6.4 Pishan earthquake is the largest to have occurred in the Tarim basin since 1976. It caused great damage to infrastructures and private houses in the city of Pishan and the surrounding areas. We use ascending and descending interferometric Sentinel‐1A (S1A) and Advanced Land Observation Satellite 2 data to constrain the source parameters of this earthquake. The coseismic fault‐slip model obtained from a joint inversion indicates that the rupture is dominated by a thrust motion with a 7 km buried depth. The fault slip is centralized on a roughly 30 km (along‐strike) × 15 km (down‐dip) rectangular asperity, with ∼1 m maximum slip at a depth of 11 km. The total seismic moment 5.6×1018 N·m, corresponding to a moment magnitude M w 6.47, is slightly larger than the seismological estimate. The absence of fault slip in the upper 7 km of the crust suggests that this earthquake left an unruptured up‐dip fault under the city of Pishan. Both the coseismic fault‐slip distribution and the early postseismic deformation demonstrate that the S1A data have obvious superiority in monitoring earthquakes worldwide.
Influence of Intertidal Flats on Tidal Asymmetry

Abstract The generation of tidal asymmetries in estuaries is analyzed by examining the differences in celerity at high and low tide. An analytical expression for the difference between ebb and flood durations is introduced and applied to a cross section composed of a channel flanked by tidal flats. The expression depends on the cross-sectional average of the celerity, for which two approximations are proposed and verified with a numerical model. Results confirm that tidal flats enhance ebb dominance, whereas large tidal amplitudes promote flood dominance. Maximum ebb dominance occurs for tidal flats at or above mean water level, depending on tidal amplitude and the extent of the tidal flats. Finally, qualitative arguments indicate that friction also enhances flood dominance.
BIMBOFICATION TO EMPOWER: REPRESENTATION OF HYPERFEMININITY ON TIKTOK

Among the diversity of trends and subcultures on TikTok, bimbofication has become a notable phenomenon with its representation of hyperfemininity to dismantle misogyny and patriarchal standards in society. The movement acknowledges and challenges the stigma towards bimbos who are often portrayed as hyperfeminine women, while inviting the audience to engage in traits and attitudes that are associated with the stereotypes. The purpose of the movement is to empower and liberate women from the fear of misogyny. However, due to the layers and complexity in the discussion, bimbofication may provoke mixed interpretations and invite various responses. The complexity of bimbofication can be found in videos posted by Chrissy Chlapecka, a self-proclaimed bimbo figure on TikTok. This paper contributes to gender studies as it explores hyperfemininity representation in relation to the notion of women’s empowerment. Moreover, it also intersects with cultural studies as it examines a social phenomenon on social media, specifically TikTok movement, and how it challenges society's standards. By following Sandelowski purposive sampling method (1995) and Murnen and Byrne’s hyperfemininity scale (1991), it is found that regardless of the ambiguities and varying interpretations, bimbofication has provided a space for women to freely express and explore their unique version of femininity.AbstrakDi antara keragaman tren dan subkultur di TikTok, bimbofication telah menjadi fenomena penting karena representasi hiperfeminitasnya yang membongkar misogini dan standar patriarkis dalam masyarakat. Gerakan ini mengakui dan menantang stigma terhadap bimbo yang sering digambarkan sebagai wanita hiperfeminin sambil mengajak penonton untuk melibatkan diri mereka dengan sifat dan sikap yang terkait dengan stereotip tersebut. Tujuan dari gerakan ini adalah pemberdayaan dan pembebasan perempuan dari ketakutan akan misogini. Namun, karena lapisan-lapisan dan kompleksitas dalam diskusi ini, bimbofication dapat memicu interpretasi yang beragam dan mengundang berbagai macam tanggapan. Kompleksitas bimbofication dapat ditemukan dalam video yang diunggah oleh Chrissy Chlapecka, sosok yang memproklamirkan dirinya sebagai bimbo di TikTok. Artikel ini berkontribusi pada studi gender dengan mengeksplorasi representasi hiperfeminitas dalam kaitannya dengan gagasan pemberdayaan perempuan. Selain itu, penelitian ini juga bersinggungan dengan kajian budaya karena meneliti fenomena sosial di media sosial, khususnya gerakan TikTok, dan bagaimana gerakan ini menantang standar masyarakat. Dengan mengikuti metode purposive sampling dari Sandelowski (1995) dan menggunakan skala hiperfeminitas Murnen dan Byrne (1991), artikel ini menemukan bahwa, terlepas dari ambiguitas dan interpretasi yang berbeda-beda, bimbofication telah memberikan ruang bagi perempuan untuk berekspresi secara bebas dan mengeksplorasi feminitas mereka yang unik.
Strata Boundary-Constrained Multitask Multihorizon Tracking

Multihorizon tracking deep learning methods have higher efficiency than single-horizon tracking deep learning methods, but they still have a great challenge to adapt to complex seismic data, resulting in undesired horizon tracking results. To achieve high-precision horizon tracking results, we propose a boundary-constrained multitask multihorizon tracking (BMTM) based on semantic segmentation, instance segmentation, and multitask learning (ML). The core idea of BMTM is to transform multihorizon tracking into strata recognition, using where the strata boundaries serve as the tracking results. BMTM comprises three components: strata label automatic generation, strata boundary-constrained multihorizon tracking network (BMTN), and strata boundary-constrained loss function. Strata label automatic generation automatically generates strata labels based on the input horizon labels. BMTN consists of a shared layer, an auxiliary task, and a main task. The auxiliary task takes the input horizon labels as its labels and employs semantic segmentation to directly output multihorizon tracking results. Main task takes the generated strata labels as its labels and employs instance segmentation with the outputs of auxiliary task to achieve high-precision strata (or horizon) tracking results. The strata boundary-constrained loss function aims to pay more attention to the strata boundary and ultimately improve the horizon tracking precision. One public 3-D synthetic seismic dataset study demonstrated the performance of BMTM, and one field 3-D seismic dataset application demonstrated that BMTM can be used for high-precision multihorizon tracking.
Stiffness and Vibration Resistance Analysis of Isotropic Stewart Platform (ISP) and Common Stewart Platform (CSP)

Parallel manipulators found wide applications in the industry such as entertainment, heavy, and aerospace industries. However, the contemporary growth of the economy and industry demands additional and exceptional capabilities for robots. Parallel manipulator applications in the industry are pretty specific and complex rather than serial manipulators. Therefore in this research, we proposed an isotropic Stewart parallel manipulator to enhance robot stiffness and payload capacity capabilities. Moreover, proves the concept by experimental methods. The main contribution of this paper is to rely on robot design, joint positions, and comparison of experimental results to prove the concept idea. The research paper is organized in the following order: introduction, design concept, joint positions and simulation, experimental results, and conclusion.