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In this reflective piece, the author, a Latino librarian with 25 years of experience in academic libraries, explores the challenges and opportunities surrounding diversity and inclusion within the profession. Through personal anecdotes and historical context, the author highlights the persistent underrepresentation of Latinx librarians in academic settings and the growing importance of addressing this disparity, particularly in response to the demographic shifts in the United States. The establishment of the REFORMA Academic Librarians Advancing Service (ALAS) committee emerges as a pivotal initiative aimed at empowering Latinx librarians and better serving Latinx student populations. Drawing inspiration from mentors and predecessors, the author emphasizes the need for proactive measures from library deans and directors to support initiatives like ALAS, promote cultural competency, and foster diversity within their institutions. By fostering inclusivity, representation, cultural competency, and equitable access to knowledge, the profession can evolve to reflect the diversity of the communities it serves. [ABSTRACT FROM AUTHOR]

Inspired by the tip feathers of soaring birds, the device of tip sails was designed and installed on the wing to achieve drag reduction. The influences of design parameters including cant angles, toe angles and twist angles on aerodynamic characteristics of tip sails were investigated through 77 cases of 11 configurations at 7 different angles of attack. According to the results grouped, the optimal cant angles (30, 15, 0) were determined. By adjusting the toe angles, drag reduction can be improved under different flight conditions. The decreasing twist angles can inhibit flow separation on sail surface. The optimal toe angles (18, 15, 12) and twist angles (12, 9, 6) resulted in the weakest flow separation. Ensuring that the twist angle of each sail is 6° less than that of the corresponding toe angle can effectively inhibit flow separation on the sail surface. The tip sails can also split and weaken the wingtip vortex. In addition, in the validation of the numerical method, we also investigate the influence of numerical schemes and turbulence models on the results of wingtip vortex flow. In the cases with unstructured meshes, the third-order finite volume scheme had higher computational efficiency than the traditional second-order finite volume scheme in obtaining grid independent solutions, and the turbulence model with rotation correction can improve the calculation accuracy of the wingtip vortex flow. The results of this paper provide a valuable reference for the design of tip sails. [ABSTRACT FROM AUTHOR]

Nickel‐rich cobalt‐free LiNi0.9Mn0.05Al0.05O2 (NMA955) is considered a promising cathode material to address the scarcity and soaring cost of cobalt. Particle size and elemental composition significantly impact the electrochemical performance of NMA955 cathodes. However, differences in precipitation rates among metal ions coveys a challenge in obtaining cathode materials with the desired particle size and composition via hydroxide co‐precipitation synthesis. Utilizing complexing agents like ammonia offers an effective strategy to tackle these issues. Here, we investigate the optimal ammonia concentration to achieve moderate particle size and precise material composition. Although ammonia only forms complex coordination with transition metals, its concentration also affects the final product's precipitation and composition, including aluminum. This study shows that ammonia serves a dual function in NMA synthesis via hydroxide co‐precipitation, i. e., regulating particle size and adjusting elemental composition. It was found that an ammonia concentration of 1.2 M achieved optimal particle size and composition, resulting in superior electrochemical performance. NMA955 synthesized in 1.2 M ammonia demonstrated a high specific capacity of 188.12 mAh g−1 at 0.1 C, retained 71.16 % of its capacity after 200 cycles at 0.2 C, and delivered 110.30 mAh g−1 at 5 C. These results suggest that tuning ammonia concentration is crucial for producing high‐performance cathode materials. [ABSTRACT FROM AUTHOR]

Suicide is a global health concern whose rates are soaring in many low-and-middle-income countries. Public awareness campaigns have been implemented in Brazil; however, their impact is uncertain. This was an ecological study using population data from DATA-SUS, a Brazilian official notification system, selecting only deaths that were voluntarily self-inflicted (CID-10 × 60-X84). We analyzed all available data from 2000 to 2019 to assess trends before and after the national Yellow September (YS) campaign started in 2015. Differences in trends were assessed by Joinpoint Analysis (JA) and Regression Discontinuity Analysis (RDD), unadjusted and adjusted for economic factors. Overall, there was a progressive increase in the rate of relative (per 100,000 inhabitants) number of suicides over time between 2000 and 2019 (57 % increase). The JA detected a change in the slope of the curve representing an acceleration in suicides starting in the year 2015. Adjusted RDD revealed the year that Yellow September started significantly change the slope of the association between time and rates of suicide (p interaction < 0.01), and marginal analysis detected the coefficient increased from 0.07 (95%CI 0.04–0.10) to 0.27 (95%CI -0.07-0.60) suicides/year per 100,000 inhabitants. The ecological nature of the manuscript compromises causational implications. We found an increase in suicidal trends in Brazil, against the global trend that coincides with the beginning of a large national awareness campaign. Although we cannot attribute causality, our results reinforce the need of further studies to better understand the role of awareness campaigns in suicide reduction interventions, including potential unintended effects. • Despite the implementation of the Yellow September campaign, the study reveals a worrying nationwide increase in suicide rates in Brazil. • After the implementation of Yellow September Campaign, suicides tended to cluster more closely to months following September. • The study recommends a multifaceted approach integrating awareness campaigns with concrete healthcare modifications, emphasizing the need for campaigns to focus on positive coping strategies and destigmatization. [ABSTRACT FROM AUTHOR]

DNA has emerged as a promising storage medium to meet the soaring need for archival data storage because of its exceptional storage density and stability. However, current DNA‐based data storage systems are incompetent of achieving high‐quality random multiplexed access and frequently accessed data storage, which impedes its practical applications. Here, a dual‐mode storage system is proposed that combines DNA‐based archival data and nanodot‐based active data. This novel data‐storage system is constructed by writing the active and archival data on the same substrate through a facile two‐step process involving scanning probe lithography (SPL), DNA synthesis, and chemical immobilization. The data files are categorized and stored orderly in different microregions of the substrate to achieve efficient random access. On each microregion, the nanodot array stores not only the concise information for the archival DNA data but also contains the corresponding primer sequence. Such interrelation between active and archival data allows for facilely data reading by efficient microscopic modalities and in situ polymerase chain reaction (PCR). Facilitated by the integration of nanodot and DNA, this novel dual‐mode storage system demonstrates efficient data access and the potential of excellent storing capacity, paving the way for the advancement of DNA‐based data storage. [ABSTRACT FROM AUTHOR]

Utilizing thermal updrafts shows potential for enabling long-endurance cruising of fixed-wing unmanned aerial vehicles without energy consumption. This article presents a novel online method based on sparse identification of nonlinear dynamics (SINDy) approach to achievement identification of thermal sources in the atmosphere. Initially, the algorithm is incorporated into the upper-level planning system, interacting with the lower-level controller. Then, experiments are conducted through software-in-the-loop simulations (SITL) to validate the implementation of the proposed algorithm. It is found that direct observation of thermal sources through measurements using SINDy is unfeasible during straight and circular flight modes. Nevertheless, simulation analysis of the proposed approach indicates that under unobservable conditions, a portion of the parameters can still be identified. By comparing results obtained using the particle filter algorithm, this method is shown to accurately estimate the parameters with negligible errors under observability conditions. The novelty of this approach lies in its significant improvement of the localization accuracy of the thermal source, without the need for parameter adjustments in the algorithm. Finally, the proposed methods are integrated into commonly used hardware platforms, and their online feasibility is verified through hardware-in-the-loop simulations. [ABSTRACT FROM AUTHOR]

The field of natural language processing has experienced significant advances in recent years, but these advances have not yet resulted in improved analytics for instructors on MOOC platforms. Valuable information, such as suggestions, is generated in the comment forums of these courses, but due to their volume, manual processing is often impractical. This study examines the feasibility of fine-tuning and effectively utilizing state-of-the-art deep learning models to identify comments that contain suggestions in MOOC forums. The main challenges encountered are the lack of labeled datasets from the MOOC context for fine-tuning classification models and the soaring computational cost of this training. For this study, we manually collected and labeled 2228 comments in Spanish and English from 5 MOOCs and scraped 1.4 million MOOC reviews from 3 platforms. We fine-tuned and evaluated 4 pretrained models based on the transformer architecture and 3 traditional machine learning models to compare their effectiveness in the suggestion mining task in this domain. Transformer-based models proved to be highly effective in this task/domain combination, achieving performance levels that matched or exceeded those deemed appropriate in other contexts and were significantly greater than those achieved by traditional models. Domain adaptation led to improved linguistic understanding of the target domain; however, in this project, this approach did not translate into an observable improvement in suggestion mining. The automated identification of comments that can be labeled as suggestions can result in considerable time savings for instructors, especially considering that less than a quarter of the analyzed comments contain suggestions. [ABSTRACT FROM AUTHOR]

In the era of low-power very large-scale integration design, approximate computing is a soaring design paradigm that assures energy-efficient circuit design at the cost of some accuracy. Multiplication is a very important operation of an arithmetic unit and compressor is the inherent part of the multiplier. In this paper, an energy-efficient design of a 4:2 approximate compressor is proposed. The inclusion of the extra leakage control transistors in the logic has led to leakage power reduction, which ultimately reduces the power dissipation in the circuits. The proposed 4:2 compressor is simulated at 10 nm fin-field effect transistor (FinFET) technology. The proposed compressor has been verified for its functionality and robustness. The proposed design shows a power dissipation of 154.48 nW and a delay of 9.16 ps. In comparison to other 4:2 approximate compressors, the proposed compressor shows the least power dissipation, the lowest power delay product (PDP) and the highest robustness. The power dissipation of the proposed compressor is 92.84% less than that of the base compressor. The PDP of the designed compressor is 80.58% less than the minimum PDP among other compressors. The aging analysis for the negative bias temperature instability (NBTI) effect is also checked for the proposed compressor and compared with the existing designs. [ABSTRACT FROM AUTHOR]

The heterogeneity of the physical environment determines the cost of transport for animals, shaping their energy landscape. Animals respond to this energy landscape by adjusting their distribution and movement to maximize gains and reduce costs. Much of our knowledge about energy landscape dynamics focuses on factors external to the animal, particularly the spatio-temporal variations of the environment. However, an animal’s internal state can significantly impact its ability to perceive and utilize available energy, creating a distinction between the ‘fundamental’ and the ‘realized’ energy landscapes. Here, we show that the realized energy landscape varies along the ontogenetic axis. Locomotor and cognitive capabilities of individuals change over time, especially during the early life stages. We investigate the development of the realized energy landscape in the Central European Alpine population of the golden eagle Aquila chrysaetos, a large predator that requires negotiating the atmospheric environment to achieve energy-efficient soaring flight. We quantified weekly energy landscapes using environmental features for 55 juvenile golden eagles, demonstrating that energetic costs of traversing the landscape decreased with age. Consequently, the potentially flyable area within the Alpine region increased 2170-fold during their first three years of independence. Our work contributes to a predictive understanding of animal movement by presenting ontogeny as a mechanism shaping the realized energy landscape. [ABSTRACT FROM AUTHOR]

The Pelagornithidae are an extinct group of soaring birds that lived all over the world between the early Palaeocene and the Pliocene-Pleistocene and are characterised by the presence of hollow denticles along the tomial edges formed by the expansion of the premaxillary, maxillary, and dentary bones. The presence of distinctive sulci in the upper and lower jaws together with the absence of wearing signs on the denticles, attributable to the handling of the prey, indicates the development of a resistant and compound rhamphotheca. To reconstruct it, we turned to the evidence provided by extant representatives with similar configurations and the osteological correlates of the beak. As a result, we propose a model for the middle-latest Eocene Antarctic Pelagornithidae, in which the rhamphotheca would have been formed by thick horny plates. The culminicorn was separated from the laternicorn by an extense sulcus nasi that continuous caudally to the apertura nasi ossea, a sturdy and hooked unguis maxillaris covering the rostrum, with small nares opening at the cranial end of the apertura nasi ossea, dorsal and ventral ramicorns, and a thick unguis mandibularis with a pseudomental fold and a sulcus on the mandible. [ABSTRACT FROM AUTHOR]

The increase of wind turbine installations to limit climate change may affect bird populations because of collisions with rotor blades. Birds may respond to wind turbine presence along a gradient of behavioral changes: avoiding the wind farm (macro-scale) or the wind turbines either by anticipating wind turbine locations (meso-scale) or engaging in last-minute flee attempts (micro-scale). We investigated flight responses of 25 adult Gyps fulvus (Griffon Vulture) equipped with GPS tags over 3 years in an area that included 10 wind farms in Causses, France. At the macro-scale, foraging range and habitat use revealed that G. fulvus did not avoid wind farms. To investigate avoidance at meso- and micro-scales, we focused on the 4 most visited wind farms. We compared vulture flights to null movement models, which allowed us to keep the correlation between flights and topography while creating movement independent of wind turbine locations. At most sites, G. fulvus did not show avoidance behavior. Overall, our results suggest wind farm-specific responses by soaring birds as a function of landscape topography. Thus, to reduce collision risks, stakeholders should first avoid constructing wind farms close to vulture nesting colonies. When siting, developers should investigate G. fulvus use of local topography to avoid areas in which birds are likely to travel. Finally, managers must prioritize the detection of species not able to avoid turbines when designing preventive measures, such as switching off on-demand technologies. [ABSTRACT FROM AUTHOR]

In nature, gliding birds frequently execute intricate flight maneuvers such as aerial somersaults, perched landings, and swift descents, enabling them to navigate obstacles or hunt prey. It is evident that birds rely on different wing–tail configurations to accomplish a wide range of aerial maneuvers. For traditional fixed‐wing unmanned aerial vehicles (UAVs), pitch control primarily comes from the tail's elevators, while adjusting flight lift and drag involves deploying wing flaps. Although these designs ensure reliable flight, they compromise the drones' maneuverability to maintain longitudinal stability. Therefore, the study introduces a biomimetic morphing wing UAV, and presents a pitch control strategy that simultaneously engages morphing wings, ailerons, and tail elevators. The pull‐up maneuver tests indicate that the proposed control method results in a pitch rate that is approximately 2.5 times greater than when using only the elevator control. A closed‐loop control system for the drone is also established. The closed‐loop flight experiment, which tracks a 45° pitch angle, demonstrates the effectiveness of the proposed coupled control method in adjusting the flight attitude. In addition, during cruising, the UAV employs three configurations, straight wing, forward‐swept wing, and back‐swept wing, to cater to different mission objectives and augment its flight capabilities. [ABSTRACT FROM AUTHOR]

Accurately and quickly identifying harmful driving behaviors is of great research significance. This article introduces a multi class Adaboost algorithm for accurately and quickly identifying harmful driving behaviors on urban roads. This method first carefully collects data related to bad driving behavior on road sections. Then, the optical flow method is used to capture images of driving behavior, and the TV-L1 optical flow method is used to refine the images to improve clarity. Finally, the CART decision tree serves as the cornerstone for constructing a rigorously trained weak classifier, strategically combining multiple individual weak classifiers to form a robust strong classifier. This powerful classifier is supported by the Adaboost algorithm and can provide detailed classification of bad driving behavior. To ensure a holistic assessment, fuzzy mathematics is deployed to discern behavioral risks, thereby facilitating the correlated identification of adverse driving patterns. Experiment results verifies the efficacy of our approach, with recognition time dwindling to a mere 1.9 seconds and the accuracy of correlated recognition soaring to an impressive 99.8%. [ABSTRACT FROM AUTHOR]

Thermal soaring, a technique used by birds and gliders to utilize updrafts of hot air, is an appealing model-problem for studying motion control and how it is learned by animals and engineered autonomous systems. Thermal soaring has rich dynamics and nontrivial constraints, yet it uses few control parameters and is becoming experimentally accessible. Following recent developments in applying reinforcement learning methods for training deep neural-network (deep-RL) models to soar autonomously both in simulation and real gliders, here we develop a simulation-based deep-RL system to study the learning process of thermal soaring. We find that this process has learning bottlenecks, we define a new efficiency metric and use it to characterize learning robustness, we compare the learned policy to data from soaring vultures, and find that the neurons of the trained network divide into function clusters that evolve during learning. These results pose thermal soaring as a rich yet tractable model-problem for the learning of motion control. Thermal soaring, inspired by gliding birds, is an appealing model behavior for understanding motion control and how it is learned by animals and engineered autonomous systems. The authors propose a deep reinforcement learning framework to study the learning process of thermal soaring under horizontal wind conditions. [ABSTRACT FROM AUTHOR]

The Turkish economy presented a complicated picture ahead of the 2023 election, with significant currency depreciation and soaring inflation yet robust growth and stable employment levels. How did voters' economic perceptions shape election results in such a context? Drawing on Turkish Election Study surveys, this study reaches two main conclusions. First, while the average evaluation of the economy in the electorate was quite poor, there is a sharp divergence across incumbent supporters and others: The incumbent Justice and Development Party (Adalet ve Kalkınma Partisi – AKP) supporters' evaluations have changed little since the previous election in 2018, yet those of other voters have deteriorated significantly. Second, the opposition seems to have failed in convincing large parts of the electorate that they would manage the economy better than Erdoğan. Overall, economic voting appears to have worked as expected, and the unwavering economic evaluations of likely AKP voters and the perceived incompetence of the opposition seem to have helped Erdoğan to win another term. [ABSTRACT FROM AUTHOR]

In order to study the variation in the lift performance as a function of the angle of attack of a hypersonic gliding vehicle under supersonic (hypersonic) conditions, the cuspidal waverider was taken as the object of this study, and the variation in the lift performance depending on the angle of attack was simulated for its design condition (M = 3.86 and H = 25 km) and hypersonic incoming flow condition (M = 8 and H = 25 km). It was also compared with the delta-wing Model 1 with the same leading-edge swept angle and Model 2 with the same spread length, respectively. The obtained results show that the zero-lift angle of attack and the critical angle of attack of the cuspidal waverider are both greater than those of the Model 1 and Model 2. The critical angle of attack increases with the free-stream Mach number for all three models. The maximum lift coefficient angle of attack on the upper surface of the cuspidal waverider decreases with increase in the Mach number, contrary to Models 1 and 2, and this relates to the degree of expansion of the free-stream flow conditions, the model layout, and the vortex structure formed on the leeward side. [ABSTRACT FROM AUTHOR]

To meet the time-coordinated requirement of hypersonic gliding vehicles to reach a single target simultaneously in the presence of no-fly-zone constraints, this paper proposes a time-coordinated A* path planning method considering multiple constraints. The path planning method is designed based on an analytical steady gliding path model and the framework of the A* algorithm. Firstly, an analytical steady gliding path model is designed based on a quadratic function-type altitude-velocity profile. It can derive the control commands explicitly according to the desired terminal altitude and velocity, thus establishing a mapping between the terminal states and the control commands. Secondly, the node extension method of the A* algorithm is improved based on the mapping. Taking the terminal states as new design variables, a feasible path-node set is produced by a one-step integration using the control commands derived according to different terminal states. This node extension method ensures the feasibility of the path nodes while satisfying terminal constraints. Next, the path evaluation function of the A* algorithm is modified by introducing a heuristic switching term to select the most proper node as a waypoint, aiming to minimize the arrival time deviation. Meanwhile, introducing the penalty items into the path evaluation function satisfies the no-fly-zone constraints, process constraints, and control variable constraints. Finally, an online time-coordinated method is proposed to determine a commonly desired arrival time for several hypersonic gliding vehicles. It eliminates the need to specify the arrival time in advance and improves the capability to deal with sudden threats, increasing the path planning method's online application capability. The proposed method can achieve online time-coordinated multi-constraint path planning for several hypersonic gliding vehicles, whose effectiveness and superiority are verified by simulations. [ABSTRACT FROM AUTHOR]

Challenges imposed by geographical barriers during migration are selective agents for animals. Juvenile soaring landbirds often cross large water bodies along their migratory path, where they lack updraft support and are vulnerable to harsh weather. However, the consequences of inexperience in accomplishing these water crossings remain largely unquantified. To address this knowledge gap, we tracked the movements of juvenile and adult black kites Milvus migrans over the Strait of Gibraltar using high-frequency tracking devices in variable crosswind conditions. We found that juveniles crossed under higher crosswind speeds and at wider sections of the strait compared with adults during easterly winds, which represent a high risk owing to their high speed and steady direction towards the Atlantic Ocean. Juveniles also drifted extensively with easterly winds, contrasting with adults who strongly compensated for lateral displacement through flapping. Age differences were inconspicuous during winds with a west crosswind speed component, as well as for airspeed modulation in all wind conditions. We suggest that the suboptimal sea-crossing behaviour of juvenile black kites may impact their survival rates, either by increasing chances of drowning owing to exhaustion or by depleting critical energy reserves needed to accomplish their first migration. [ABSTRACT FROM AUTHOR]

The unmanned combat system-of-systems (UCSoS) in modern warfare is comprised of various interconnected entities that work together to support mission accomplishment. The soaring number of entities makes the UCSoS fragile and susceptible to triggering cascading effects when exposed to uncertain disturbances such as attacks or failures. Reconfiguring the UCSoS to restore its effectiveness in a self-coordinated and adaptive manner based on the battlefield situation and operational requirements has attracted increasing attention. In this paper, we focus on the UCSoS reconstruction with heterogeneous costs, where the collaboration nodes may have different reconstruction costs. Specifically, we adopt the heterogeneous network to capture the interdependencies among combat entities and propose a more representative metric to evaluate the UCSoS reconstruction effectiveness. Next, we model the combat network reconstruction problem with heterogeneous costs as a nonlinear optimization problem and prove its NP-hardness. Then, we propose an approach called SoS-Restorer, which is based on deep reinforcement learning (DRL), to address the UCSoS reconstruction problem. The results show that SoS-Restorer can quickly generate reconstruction strategies and improve the operational capabilities of the UCSoS by about 20∼60% compared to the baseline algorithm. Furthermore, even when the size of the UCSoS exceeds that of the training data, SoS-Restorer exhibits robust generalization capability and can efficiently produce satisfactory results in real time. [ABSTRACT FROM AUTHOR]

This article uses concepts from Lacanian discourse analysis to examine the rise and fall of Liz Truss, and to draw conclusions about the nature and resilience of neoliberalism. I begin by outlining Lacan's theory of the four discourses in relation to neoliberalism, distinguishing a 'neoliberal master discourse' comprising soaring rhetoric about freedom and prosperity, from a 'neoliberal university discourse' grounded in economic science. I argue Liz Truss represented an unusually pure form of the neoliberal master discourse, prioritising notions of freedom and prosperity over the more pragmatic focus on austerity and market discipline. However, when Truss' discourse failed it led not to the repudiation of neoliberalism, but rather to the return of a neoliberal university discourse of austerity developed by Rishi Sunak and Jeremy Hunt. I conclude that the relationship between the neoliberal master and university discourses is crucial to understanding the ongoing discursive resilience of neoliberalism. [ABSTRACT FROM AUTHOR]

The small diapsid reptile Ozimek volans is one of the most enigmatic representatives of the Late Triassic fauna of Krasiejów, Poland. Phylogenetically, Ozimek was identified as a 'protorosaurian' related to tanystropheids, but the extremely elongated limbs and presumed gliding abilities are unusual for this group. This raises the question of whether the lifestyle inferred for this taxon is reflected in its bone histology. Two long bones from a single bone association of Ozimek (humerus UOPB 1148a and femur UOPB 1148b) were sectioned at the midshaft to obtain details of the histological framework. A large medullary cavity, thin walls of lamellar bone with numerous lamellae, and only very few simple vascular canals are shared by both bones. Application of a modified 3‐front model (introducing a fourth front) of cortical growth reveals that the femur is ontogenetically younger when compared to the humerus. Ozimek limb bones, with their small diameter, compact structure, low vascularization, no remodelling, and a lack of pneumaticity, are histologically similar to those of modern small bats. The characteristic cortex of both may have been well suited to withstand high loads while limiting weight. The well‐ordered collagen fibres in successive lamellae along the bone may be a key adaptation for the better distribution of the load generated during gliding. © 2024 The Palaeontological Association. [ABSTRACT FROM AUTHOR]

Recent studies highlight coarse-grained discrete element method (CGDEM) as a helpful tool for mitigating the computational cost associated with original discrete element method (DEM) simulations in large-scale industrial applications such as fluidized beds. This approach achieves cost savings by reducing the number of particles in the domain, while increasing their size. In the current work, CGDEM-LES (large-eddy simulation) numerical simulations are conducted on a 3D (three-dimensional) cylindrical pilot-scale fluidized bed in the bubbling regime, containing 9.6 M Geldart B-type particles. Macroscopic and mesoscopic analyses are performed, revealing qualitative and quantitative effects of coarse-graining on bed behavior. Among these effects, a global homogenization of the fluidized region is observed, marked by soaring bed surfaces, lower solid velocity, and solid fraction gradients. Additionally, a decrease in the bubble population is reported. These effects intensify as the coarse-graining factor increases. Despite influencing some results, the impact of mesh size is deemed negligible compared to that of particle coarse-graining. Some of the observed issues can be alleviated by incorporating additional mechanisms from the literature, aiming to dissipate the extra energy inherently present in coarse-grained systems. However, these mechanisms prove to be barely sufficient to replicate DEM results with the smallest coarse-graining factor tested. A thorough analysis allows identifying a side effect of one of these approaches, which is to slow particles down all the more as they move fast, causing a macroscopic misprediction of particle vertical velocity in turn. This model is then deemed less useful in the context of this study. [ABSTRACT FROM AUTHOR]

The mystery of soaring birds, such as albatrosses and eagles, has intrigued biologists, physicists, aeronautical/control engineers, and applied mathematicians for centuries. These fascinating avian organisms are able to fly for long durations while expending little to no energy, utilizing wind to gain lift. This flight technique/maneuver is called dynamic soaring (DS). For biologists and physicists, the DS phenomenon is nothing but a wonder of the very elegant ability of these birds to interact with nature and use its physical ether in an optimal way for better survival and energy efficiency. For the engineering community, the DS phenomenon is a source of inspiration and an unequivocal opportunity for biomimicking. Mathematical characterization of the DS phenomenon in the literature has been limited to optimal control configurations that utilized developments in numerical optimization algorithms along with control methods to identify the optimal DS trajectory taken (or to be taken) by the bird/mimicking system. Unfortunately, all of these methods are highly complex and non-real-time. Hence, the mathematical characterization of the DS problem, we believe, appears to be at odds with the phenomenon/birds-behavior. In this paper, we provide a novel twolayered mathematical approach to characterize, model, mimic, and control DS in a simple real-time implementation, which we believe more effectively decodes the biological behavior of soaring birds. First, we present a differential geometric control formulation and analysis of the DS problem, which allow us to introduce a control system that is simple yet controllable. Second, we establish a link between the DS philosophy and a class of dynamical control systems known as extremum seeking systems. This linkage provides the control input that makes DS a real-time reality. We believe our framework accurately describes the biological behavior of soaring birds and opens the door for geometric control theory and extremum seeking systems to be utilized in biological systems and natural phenomena. Simulation results are provided along with comparisons to powerful optimal control solvers, illustrating the advantages of the introduced method. [ABSTRACT FROM AUTHOR]

Digital Contact Tracing (DCT) has been proved to be an effective tool to counteract the new SARS-CoV-2 or Covid-19. Despite this widespread effort to adopt the DCT, less attention has been paid to the organisation of the health logistics system that should support the tracing activities. Actually, the DCT poses a challenge to the logistics of the local health system in terms of number of daily tests to be collected and evaluated, especially when the spreading of the virus is soaring. In this paper we introduce a new optimisation problem called the Daily Swab Test Collection (DSTC) problem, that is the daily problem of collecting swab tests at home in such a way to guarantee a timely testing to people notified by the app to be in contact with a positive case. The problem is formulated as a variant of the team orienteering problem. The contributions of this paper are the following: (i) the new optimisation problem DSTC that complements and improves the DCT approach proposed by Ferretti et al. (Science https://doi.org/10.1126/science.abb6936, 2020), (ii) the DSCT formulation as a variant of the TOP and a literature review highlighting that this variant can have useful application in healthcare management, (iii) new realistic benchmark instances for the DSTC based on the city of Turin, (iv) two new efficient and effective hybrid algorithms capable to deal with realistic instances, (v) the managerial insights of our approach with a special regard on the fairness of the solutions. The main finding is that it possible to optimise the underlying logistics system in such a way to guarantee a timely testing to people recognised by the DCT. [ABSTRACT FROM AUTHOR]

Purpose: This paper aims to present numerical simulations for a series of flight processes for the postlaunching stage of the "balloon-borne UAV system." It includes the balloon further ascent motion after airborne launching. In terms of unmanned aerial vehicles (UAVs), the tailspin state and the charge-out process with an anti-tailspin parachute-assisted suspending are analyzed. Then, the authors conduct trajectory optimization simulations for the long-distance gliding process. Design/methodology/approach: The balloon kinematics model and the parachute Kane multibody dynamic model are established. Using steady-state tailspin to reduced-order analysis and achieving change-out simulation by parachute suspension dynamic model. A reentry optimization control problem is developed and the Radau pseudo-spectral method is used to calculate the glide trajectory. Findings: The established dynamic model and trajectory optimization method can effectively simulate the motion process of balloons and UAVs. The system mass reduction for launching UAVs will not cause damage to the balloon structure. The anti-tailspin parachute can reduce the UAV attack angles effectively. The UAV can glide to the designated target position by adjusting the attack angle and sideslip angle. The farthest flight distance after launching from 20 km height is 94 km and the gliding time is 40 min, which demonstrates the potential application advantage of high-altitude launching. Practical implications: The research content and related conclusions of this article achieve a closed-loop analysis of the flight mission chain for the "balloon-borne UAV system," which provides simulation references for relevant balloon launching experiments. Originality/value: This paper establishes a complete set of numerical simulation models and can effectively analyze various postlaunching behaviors. [ABSTRACT FROM AUTHOR]

Purpose: This study aims to study the thermal identification issue by harvesting both solar energy and atmospheric thermal updraft for a solar-powered unmanned aerial vehicle (SUAV) and its electric energy performance under continuous soaring conditions. Design/methodology/approach: The authors develop a specific dynamic model for SUAVs in both soaring and cruise modes. The support vector machine regression (SVMR) is adopted to estimate the thermal position, and it is combined with feedback control to implement the SUAV soaring in the updraft. Then, the optimal path model is built based on the graph theory considering the existence of several thermals distributed in the environment. The procedure is proposed to estimate the electricity cost of SUAV during flight as well as soaring, and making use of dynamic programming to maximize electric energy. Findings: The simulation results present the integrated control method could allow SUAV to soar with the updraft. In addition, the proposed approach allows the SUAV to fly to the destination using distributed thermals while reducing the electric energy use. Originality/value: Two simplified dynamic models are constructed for simulation considering there are different flight mode. Besides, the data-driven-based SVMR method is proposed to support SUAV soaring. Furthermore, instead of using length, the energy cost coefficient in optimization problem is set as electric power, which is more suitable for SUAV because its advantage is to transfer the three-dimensional path planning problem into the two-dimensional. [ABSTRACT FROM AUTHOR]

Rising food prices may rapidly push vulnerable populations into food insecurity, especially in developing economies and in low-income countries, where a substantial share of the financial resources available to the poorest households is spent on food. To capture soaring food prices and help in designing mitigating measures, we developed two complementary products: a nowcasting model that estimates official food consumer price inflation up to the current month and a daily food price monitor that checks whether the growth rate of a few basic food commodities exceeds a statistical threshold. Both products were designed with the consideration that the rapid acquisition of data and the automated extraction of insights are indispensable tools for policymakers, particularly in times of crisis. Our framework is characterized by three key aspects. Firstly, we leverage two non-traditional data sources to emphasize the importance of real-time information: a crowdsourced repository of daily food prices and textual insights obtained from newspapers articles. Secondly, our framework offers a global perspective, encompassing 225 countries and territories, which enables the monitoring of food prices dynamics on a global scale. Thirdly, results are made accessible daily via an intuitive and user-friendly interactive dashboard. [ABSTRACT FROM AUTHOR]

Rising food prices may rapidly push vulnerable populations into food insecurity, especially in developing economies and in low-income countries, where a substantial share of the financial resources available to the poorest households is spent on food. To capture soaring food prices and help in designing mitigating measures, we developed two complementary products: a nowcasting model that estimates official food consumer price inflation up to the current month and a daily food price monitor that checks whether the growth rate of a few basic food commodities exceeds a statistical threshold. Both products were designed with the consideration that the rapid acquisition of data and the automated extraction of insights are indispensable tools for policymakers, particularly in times of crisis. Our framework is characterized by three key aspects. Firstly, we leverage two non-traditional data sources to emphasize the importance of real-time information: a crowdsourced repository of daily food prices and textual insights obtained from newspapers articles. Secondly, our framework offers a global perspective, encompassing 225 countries and territories, which enables the monitoring of food prices dynamics on a global scale. Thirdly, results are made accessible daily via an intuitive and user-friendly interactive dashboard. [ABSTRACT FROM AUTHOR]

The article discusses the projected increase in costs associated with cardiovascular disease (CVD) from 2020 to 2050. It highlights the impact of an aging population, as well as increasing rates of obesity, hypertension, and diabetes among young and middle-aged adults, particularly in low-income communities. The article emphasizes the need for effective interventions to address these disparities, especially among minority populations. It also suggests potential solutions such as value-based payment reforms, telemedicine, and wearable health monitoring devices. The article concludes by emphasizing the importance of a comprehensive approach to address the challenges posed by the growing elderly population and decreasing disparities in healthcare. [Extracted from the article]

A novel standard trajectory design and tracking guidance used in the multiple active leap maneuver mode for hypersonic glide vehicles (HGVs) is proposed in this paper. First, the dynamic equation and multiconstraint model are first established in the flight path coordinate system. Second, the reference drag acceleration-normalized energy (D-e) profile of the multiple active leap maneuver mode is quickly determined by the Newton iterative algorithm with a single design parameter. The range to go error is corrected by the drag acceleration profile update algorithm, and the drag acceleration error of the gliding terminal is corrected by the aerodynamic parameter estimation algorithm. Then, the reference drag acceleration tracking guidance law is designed based on the prescribed performance control method. Finally, the CAV-L vehicle model is used for numerical simulation. The results show that the proposed method can satisfy the design requirements of drag acceleration under multiple active leap maneuver modes, and the reference drag acceleration can be tracked precisely. The adaptability and robustness of the proposed method are verified by the Monte Carlo simulations under various combined deviation conditions. [ABSTRACT FROM AUTHOR]

Economic uncertainty, political instability, and security concerns marked 2023 as a year where the country desperately tried to survive. The year began with Pakistan on the brink of sovereign default, with depleting foreign reserves and soaring inflation. Although successful negotiations with the IMF averted economic catastrophe, political crisis seemed to replace the country's economic woes. In the second half of 2023, following Imran Khan's temporary arrest on May 9, political confrontation between the military and Pakistan Tehrik-e-Insaaf resulted in the worst democratic backsliding witnessed in recent years. Although Pakistan heads to the polls in the new year, it appears to be saddled by the weight of the political status quo. [ABSTRACT FROM AUTHOR]

The collateral channel literature predicts that soaring real estate prices increase the debt capacity of firms with more real estate asset holdings. This paper discusses the different relationships between collateral and investment. We find that firms with strong corporate governance were more likely to increase debt capacity via the collateral channel during the real estate boom from 1993 to 2006. Entrenched managers used less debt to finance their investments when their real estate collateral values increased. Our results hold even after controlling for noncollateralized debts and credit rating of the sample firms. [ABSTRACT FROM AUTHOR]

Clozapine is an antipsychotic medicine used to treat mental illnesses that is resistant to therapy. It can induce dose-dependent adverse effects such as increased susceptibility to infections and hematological irregularities. In this case report, we present a 37-year-old woman with schizoaffective disorder who experienced clozapine side effects following a moderate urinary tract infection (UTI). Her serum clozapine levels and side effects were increased throughout her UTI but resolved once the UTI was managed conservatively. We reviewed clozapine's pharmacokinetic properties to understand why serum levels rose during infection. While we could not definitely explain the mechanism of elevation, we emphasize the importance of monitoring serum clozapine levels and keeping watchful for adverse effects, as well as heightened scrutiny, evaluation for recent infections, and regular monitoring of patients. [ABSTRACT FROM AUTHOR]

To propose Mucormycosis staging and Outcome evaluation score. (i) To provide method of conveying clinical experience to others without ambiguity. (ii) To facilitate an estimation of prognosis. (iii) To provide useful information for treatment decision. Retrospective observational study. Tertiary care center, Rajkot. 556 confirmed operated case of mucormycosis. It was a single center observational study of 556 confirmed cases of mucormycosis. In suspected cases of fungal infection, clinical symptoms were noted along with covid history and comorbid condition. Clinical findings were noted after nasal endoscopy. Rest neurological examination was done to rule out CNS involvement. Representative sample from nasal mucosa sent for microbiological examination. MRI PNS with Brain and Orbit was advised. After surgery, specimen was sent for histopathological confirmation. We reported most common age group was 51–60 years. 52% cases presented early with only nasal involvement and 1.8% cases with late cerebral involvement presentation. From recorded all above findings we have described this diseases progression in 4 components limited to nasal, orbital, palate and/or skull base, cerebral involvement. It is bases on anatomical progression on clinical and radiological findings. Considering all four components, staging system is designed that includes stage I to stage Vb. Outcome evaluation score designed to consider factors like patient's age, comorbidity, stage of disease while presentation, IV antifungal coverage and patient's psychological condition. Our clinical and radiological diagnostic staging and outcome evaluation score may helpful for others for early and better management of mucormycosis. [ABSTRACT FROM AUTHOR]

Property talk has gained a new amplitude amid soaring land prices in India's agrarian-urban frontier. This article focuses on what is colloquially described as property ka kaam—property-work and ethnographically traces how property is continually made and remade on the ground. It heuristically identifies some of the key figures—the private developer, the religious leader, and the land broker—who, in their own specific ways, creatively improvise and draft the contours of an urbanizing frontier. It draws attention to everyday practices and discourses through which agropastoral land is turned into urban real estate and shows how the figures, working at different scales and capacities, navigate the complexly layered social-spatial dynamics of caste, class, community, and brotherhood to secure widespread consensus about urban transformation and coproduce an emergent agrarian-urban geography. This article opens a window into the opaque and dense world of property and highlights the contingent nature of property and place- and caste-based connections that undergird property-work. [ABSTRACT FROM AUTHOR]