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When a market continues to hold against a resistance level and refuses to turn down after several instances of threatening price action, one has to consider absorption is taking place. Absorption is the process through which the long liquidation, profit‐taking, and new short selling are overcome. It can show up on any chart, regardless of the time frame.

Microplastics are observed ubiquitously and in different environmental compartments ranging from marine waters and sediments to freshwater and terrestrial ecosystems including biota. Over the last decade, several methods have been applied and advanced to monitor and quantify microplastics, to identify the polymer material and to describe the particle properties, such as size, shape or colour. In most cases, the overarching aim is to elucidate patterns of occurrence that might result from (micro)plastic emissions and environmental fate. But the applied methods are subject to uncertainties and boundary conditions, be it spatial resolution that excludes the smallest microplastics or limitations in distinguishing microplastic particles from natural particles. This critical review provides an overview of the state-of-the-art procedures in microplastic analysis, gives examples of potential ways ahead and remaining challenges and classifies available methods according to the underlying research question. The resulting decision tree for the selection of analytical methods starts with a common research question and takes specificities of the environmental matrix into account. The procedural range consequently ranges from fast screening methods based on visual identification to a highly sophisticated combination of analytical methods that provide information on polymer type, particle number or mass and eventually particle size but are very time-consuming and expensive. Standardization of microplastic analytical methods on the basis of the research aim will help to make study results comparable and obtain a more comprehensive picture of microplastic abundance and fate in the environment.

Diabetes is a worldwide epidemic, and associated neuropathy is its most costly and disabling complication. Given the rising prevalence of painful diabetic neuropathy, it is increasingly important that we understand the best ways to diagnose and treat this condition. Diagnostic tests in this field are evolving rapidly. These include the use of skin biopsies to measure small unmyelinated fibers, as well as even newer techniques that can measure both small unmyelinated fibers and large myelinated fibers in the same biopsy. The main treatments for painful diabetic neuropathy remain management of the underlying diabetes and drugs for the relief of pain. However, emerging evidence points to major differences between type 1 and type 2 diabetes, including the ability of glycemic control to prevent neuropathy. Enhanced glucose control is much more effective at preventing neuropathy in patients with type 1 diabetes than in those with type 2 disease. This dichotomy emphasizes the need to study the pathophysiologic differences between the two types of diabetes, because different treatments may be needed for each condition. The impact of the metabolic syndrome on neuropathy in patients with type 2 diabetes may account for the difference between the two types of diabetes and requires further study. Finally, neuropathic pain is under-recognized and undertreated despite an ever evolving list of effective drugs. Evidence exists to support several drugs, but the optimal sequence and combination of these drugs are still to be determined.

Funded at $100 billion each, the BRICS Contingent Reserve Arrangement (CRA) and New Development Bank (NDB) represent 'sub-imperial' finance, insofar as, by all indications, they fit into - instead of providing alternatives to - the prevailing world systems of sovereign debt and project credits. Balance of payments constraints for BRICS members will not be relieved by the CRA, which requires an IMF intervention after just 30% of the quota is borrowed. In this context the NDB would appear close to the Bretton Woods Institution model, promoting frenetic extractivist calculations based on US dollar financing and hence more pressure to export.

Pasture management is highly dependent on accurate biomass estimation. Usually, such activity is neglected as current methods are time-consuming and frequently perceived as inaccurate. Conversely, spectral data is a promising technique to automate and improve the accuracy and precision of estimates. Historically, spectral vegetation indices have been widely adopted and large numbers have been proposed. The selection of the optimal index or satisfactory subset of indices to accurately estimate biomass is not trivial and can influence the design of new sensors. This study aimed to compare a canopy-based technique (rising plate meter) with spectral vegetation indices. It examined 97 vegetation indices and 11,026 combinations of normalized ratio indices paired with different regression techniques on 900 pasture biomass data points of perennial ryegrass (Lolium perenne) collected throughout a 1-year period. The analyses demonstrated that the canopy-based technique is superior to the standard normalized difference vegetation index (∆, 115.1 kg DM ha−1 RMSE), equivalent to the best performing normalized ratio index and less accurate than four selected vegetation indices deployed with different regression techniques (maximum ∆, 231.1 kg DM ha−1). When employing the four selected vegetation indices, random forests was the best performing regression technique, followed by support vector machines, multivariate adaptive regression splines and linear regression. Estimate precision was improved through model stacking. In summary, this study demonstrated a series of achievable improvements in both accuracy and precision of pasture biomass estimation, while comparing different numbers of inputs and regression techniques and providing a benchmark against standard techniques of precision agriculture and pasture management.

Unmanned Aerial Vehicle (UAV) development has garnered significant attention, yet one of the major challenges in the field is how to rapidly iterate the overall design scheme of UAVs to meet actual needs, thereby shortening development cycles and reducing costs. This study integrates a “Decision Support System” and “Live Virtual Construct (LVC) environment” into the existing Model-Based Systems Engineering framework, proposing a Modified Model-Based Systems Engineering methodology for the full-process development of UAVs. By constructing a decision support system and a hybrid reality space—which includes pure digital modeling and simulation analysis software, semi-physical simulation platforms, real flight environments, and virtual UAVs—we demonstrate this method through the development of the electric vertical take-off and landing fixed-wing UAV DB1. This method allows for rapid, on-demand iteration in a fully digital environment, with feasibility validated by comparing actual flight test results with mission indicators. The study results show that this approach significantly accelerates UAV development while reducing costs, achieving rapid development from “demand side to design side” under the “0 loss” background. The DB1 platform can carry a 2.5 kg payload, achieve over 40 min of flight time, and cover a range of more than 70 km. This work provides valuable references for UAV enterprises aiming to reduce costs and increase efficiency in the rapid commercialization of UAV applications.

Unmanned tilt-rotor electric Vertical Take-Off and Landing (eVTOL) aircraft face significant control challenges during the transition from hover to forward flight, particularly when using open-source autopilot systems that rely on open-loop tilt control and static control gains. After the transition, the Total Energy Control System (TECS) becomes active in fixed-wing mode, but its default static gains often fail to correct energy imbalances, resulting in substantial altitude loss. This paper presents the Steepest Descent-based Total Energy Control System (SD-TECS), a real-time adaptive TECS framework that dynamically tunes gains using the steepest descent method to enhance post-transition altitude and airspeed regulation in unmanned tilt-rotor eVTOLs. The proposed method integrates gain adaptation directly into the TECS loop, optimizing control actions based on instantaneous flight states such as altitude and energy-rate errors. This enables improved responsiveness to nonlinear dynamics during the critical post-transition phase. Simulation results demonstrate that the SD-TECS approach significantly improves control performance compared to the default PX4 TECS, achieving a 35.5% reduction in the altitude settling time, a 57.3% improvement in the airspeed settling time, and a 66.1% decrease in the integrated altitude error. These improvements highlight the effectiveness of SD-TECS in enhancing the stability and reliability of unmanned tilt-rotor eVTOLs operating under autonomous control.

Noncommunicable diseases (NCDs) are by far the major cause of death in lower-middle, upper-middle, and high-income countries; by 2015, they will also be the leading cause of death in low-income countries.

This article analyses a case involving the dismissal of a tenured faculty member at Hiroshima City University of Japan. The university dismissed a Korean woman associate professor after filing a criminal complaint against her, leading to a house raid, her arrest and media coverage. After 11 days of detention, the Hiroshima Prosecutor’s Office decided not to indict her because they could not find criminal intent on her part. With the suspicion of the university’s fabrication of her criminality looming large, she was dismissed within a few hours of her release. The university’s attempt to purge a critical foreign faculty member from the university campus, faculty housing and the country of Japan was an almost complete success until the case became an international controversy with counter-media exposure and the formation of a transnational support network. This case reveals a volatile mixture of race- and gender-based discrimination, administrative incompetence and politicised financial subsidy as a backdrop to violations of human rights and academic freedom. The present article shows that the rights’ violations in this case are closely connected to rising nationalism, the politicisation of educational subsidy and ideological human agencies with a set of professional agendas.

This paper proposes a specific method of balance control learning at a half-rising posture using an assistive system for improving the pulling chair movement, and reports a case study of a quadriplegic wheelchair user. The system provides informatics-based biofeedback and user weight support. It does not require attaching any equipment or sensor to the user's body. Although our participant was able to transfer from a wheelchair to a chair, she was not able to pull a chair until the desired position. We analyzed the physical kinematics and kinetics during pulling chair movement and developed a balance control learning method that enables the user to move the center of gravity (COG) backward when assuming a deep half-rising posture. We conducted an experiment on a quadriplegic participant once a week for four weeks. Before learning, the participant was not able to realize the pulling chair movement even though a lot of time was provided. However, after learning, the participant could move the COG backward when attempting to realize the half-rising posture, and pull a chair completely. This case proved our hypothesis that a half-rising posture with backward shifting of the center of pressure is effective in improving the pulling chair movement. Through the experiment, we achieved proof of concept of the proposed learning method and the first case study of successful application of the method.