bluuebunny/crossref_metadata_2025 huggingface dataset:
An Augmented Reality Platform for Real-Time Ergonomic Assessment and Biomechanical Simulation
Authors: Vitali Andrea , Lanzoni Daniel , Ferrari Davide , Regazzoni Daniele , Catalano Manuel Giuseppe , Rizzi Caterina
Published: November 2024

Despite the existence of numerous innovative solutions aimed at enhancing the objectivity and efficiency of physical ergonomics analysis, traditional methods are still widely used among ergonomists, relying on direct observation of workers and their task performances. This research addresses this gap by introducing AR4Ergo, an Augmented Reality platform specifically designed to assist ergonomists by computing real-time standard indexes and simulating musculoskeletal loads using biomechanical virtual models.

Xsens inertial motion capture system is employed to monitor human movements, while the OpenSim Application Programming Interface has been integrated into AR4Ergo for the simulation of musculoskeletal loads. Microsoft Hololens v2 is used to visualize human and workplace digital twins with information relative to ergonomic indexes and biomechanical simulations during the observation of the tasks performed by workers.

A test was conducted to evaluate the functionalities of the platform, with three testers taking turns performing the roles of both the ergonomists and the operators. The results demonstrate how real-time analysis with a visual interface can be performed to augment ergonomists’ experience without modifying the basic observational procedure. Even if the feedback is positive, some improvements have been identified in order to allow the ergonomist to use AR4Ergo in daily practice for different industrial applications.
Dynamic State Tracking of Overhead Powerlines With Real Time State Estimation: a Data-Driven Approach
Authors: Nambiar Nipun , Barry Oumar
Published: November 2024

This study focuses on laying the groundwork for the effective vibration suppression of power lines using mobile damping robots (MDR). Earlier research shows that effective vibration suppression is achieved by positioning the MDR at the anti-nodes of the power line. This study focuses on accurately estimating the dynamic state of the power line using a data-driven approach, hence identifying the position of the antinode. The entire dynamics of the vibration of the system is estimated from the displacement data of the power line using Dynamic Mode Decomposition (DMD) and the resulting system is stabilized with Tikhonov Regularization. The stabilized system is then used in conjunction with a Kalman Filter to accurately estimate the dynamic state of the power line using minimal displacement. All displacement data used in this study is acquired from a Galerkin model of the power line. This study shows that this method is a viable alternative to existing numerical methods which are often computationally expensive and time-consuming.
Exploring Deep Learning Models for Pathological Tremors Prediction Using EMG and Kinematic Measurements
Authors: Samal Subham , Barry Oumar
Published: November 2024

Pathological tremor is a common neuromuscular disorder that significantly affects the quality of life for patients worldwide. With recent developments in robotics, rehabilitation exoskeletons serve as one of the solutions to alleviate these tremors. Accurate predictive modeling of tremor signals can be used to provide alleviation from these tremors via various currently available solutions like adaptive deep brain stimulation, electrical stimulation and rehabilitation orthoses, motivating us to explore better modeling of tremors for long-term predictions and analysis. This study is a preliminary step towards the prediction of tremors using artificial neural networks using EMG signals, leveraging the 20–100 ms of Electromechanical Delay. The kinematics and EMG data of a publicly available Parkinsonian tremor dataset is first analyzed, which confirms that the underlying EMGs have similar frequency composition as the actual tremor. 2 hybrid CNN-LSTM based deep learning architectures are then proposed to predict the tremor kinematics ahead of time using EMG signals and tremor kinematics history, and the results are compared with baseline models. The motivation behind hybrid CNN-LSTM models is to exploit both the temporal and spatial dependencies using CNN and LSTM respectively. This is then further extended by adding constraints-based losses in an attempt to further improve the predictions.
Leveraging Latent Textual Topology for Standard Identification in Engineering Design
Authors: Bowen Matthew , Smith Logan , Carroll Cody , Morkos Beshoy
Published: November 2024

In engineering design, standards are instrumental in providing technical definitions and guidelines to designers, manufacturers, and users, reflecting best practices that are widely recognized. These standards, numbering in the hundreds of thousands, encapsulate the current state of technological expertise and aim to promote safety, reliability, productivity, and efficiency in both component and system design. Despite the clear value of standards, the vast quantity and diversity of these documents present significant challenges for designers in retrieving and implementing the appropriate standards for their projects. Moreover, the significant amount of time design engineers exhaust navigating through technical documentation highlights the necessity for more effective methods of engaging with the textual knowledge base represented by engineering standards, as the current manual process is inefficient and time-intensive. This presents an even greater challenge for small and medium-sized enterprises (SMEs) lacking the requisite personnel to adeptly navigate evolving standards. To bridge this gap, this research develops a fundamental understanding of language embeddings and large language models to assist in navigating engineering standards. This work examines the efficacy of three semantic-based approaches for engineering standard retrieval and further validates these approaches through an industry case study. Additionally, the Standards Augmented Requirements Generator (SARG) tool is presented, which provides a domain-specific approach to leveraging Retrieval Augmented Generation (RAG) in design contexts.
A Star Based Path Planning Strategy for Off-Road Vehicle Applications With Considering Wheel Mobility Performance
Authors: Fan Huashuai , Zhang Siyuan , Patel Parth , Moradi Lee , Vantsevich Vladimir
Published: November 2024

Most current path planning algorithms, used in various applications such as robotics and unmanned ground vehicles, aim to find the shortest path. However, they have not yet incorporated terrain-dependent speed limits into these calculations, which could affect the practicality and safety of the resulting paths. This study investigates the integration of mobility considerations into vehicle path planning algorithms within off-road terrain environments. In this context, the Wheel Mobility Performance (WMP) index is introduced as a novel metric designed to assess the mobility performance of off-road vehicles across varied terrain conditions. An optimized version of the A* algorithm, which integrates the WMP index, has been developed and implemented to navigate challenging terrains. Simulation results demonstrate that the optimized algorithm effectively reduces traversal time by selecting paths with enhanced mobility performance. These findings highlight the potential of integrating domain-specific metrics like WMP to improve path planning efficiency for off-road vehicles, with implications for autonomous navigation and robotics applications.
Generative Design of Planar Four-Bar Motions Using Conditional Variational Autoencoder
Authors: Halwah Amro , Nurizada Anar , Purwar Anurag
Published: November 2024

This paper introduces a novel deep generative approach to the approximate motion synthesis of planar four-bar mechanisms. Existing motion synthesis approaches for synthesizing four-bar mechanisms have generally focused on representing the motion as five or less discrete poses while not providing any guarantees on the practicality of the solutions, such as ones without circuit-, branch-, and order-defects. This paper presents a Conditional Variational Autoencoder (C-VAE) based approach for synthesizing practical mechanisms that can capture the overall motion requirement while generating a continuous motion approximately. The mathematical machinery in our work uses quaternion and kinematic mapping to represent the geometric constraints of dyads of four-bar mechanism as algebraic constraint manifolds in a three-dimensional projective space. The parameters describing the manifolds encode information about the type and dimensions. These parameters are used as input to a C-VAE that uses an arbitrarily large number of input poses approximating a motion as the condition. A procedure is presented for normalizing input motions such that they are invariant with respect to rotation, scaling, translation and reflection. The trained model can generate several pairs of constraint manifolds from which four-bar mechanisms with different parameters can be retrieved. These mechanisms’ coupler poses approximate the input’s coupler poses to varying degrees of error. A method for filtering mechanisms by the quality of match of their output motion to the input motion is also proposed. Different metrics for quantifying the similarity of an output mechanism’s motion with the input motion are presented for path and orientation separately.
Real-Time Multibody Co-Simulation of Thermal and Electromechanical Systems in an Electric Wheel Loader Model
Authors: Ikäheimo Eero , Khadim Qasim , Choudhury Tuhin , Kurvinen Emil
Published: November 2024

The electrification of on-road and off-road vehicles is increasing due to the depletion of fossil fuels and emissions from internal combustion engines (ICE). Real-time simulation analysis of electric vehicles can aid in both the design and analysis processes, enabling users to actively participate in the design phase. However, the computational costs associated with various subsystems, such as electro-thermal dynamics, hydraulics, tires, friction, and contacts etc. make real-time computational efficiency of electric vehicles cumbersome. To this end, this study introduces the real-time multibody co-simulation of multibody, hydraulics and electro-thermal dynamic systems. In the co-simulation approach, the multibody and hydraulics are solved within one solver, while the electro-thermal system is solved within a different solver. The communication between different solvers is performed using the TCP/IP (Transmission Control Protocol/Internet Protocol) connection. The proposed approach is implemented on a four degrees of freedom electric wheel loader. This system was modelled using the standard multibody system dynamics, lumped fluid theory, tyre model, Li-ion Thevenin battery equivalent circuit model and power transmission systems. The dynamic and electro-thermal performance of this system was tested in a simulation experiment under different temperatures of +0 °C, 15 °C and +30 °C. The results confirm the real-time computational performance of the electric wheel loader, even considering the computation of various subsystems. Further, the state of charge and temperature of the battery can be estimated during the vehicle working cycle. This study can contribute to efforts aimed at optimizing the design of high-efficiency electric machinery and developing intelligent electric vehicles through real-time simulations, thereby increasing the lifespan of the vehicles.
Exploring the Use of Immersive VR for Human-Robot Collaboration in Construction: An Interview Study With Industry Experts and University Faculty
Authors: Kim Ruby Yeeun , Cai Jiacheng , Chandran Swati , Liu Jieru , Peng Aoran , Miller Scarlett R.
Published: November 2024

The construction industry is increasing its adaptation of automation technologies such as robots to improve productivity and efficiency. However, human-robot collaboration requires new skills and knowledge from both workers and engineers. However, training for these new skills might be difficult due to the high-risk nature of construction environments, the complexity of the tasks involved, and the need for precise and safe coordination between humans and robots. This research proposes an immersive virtual reality-based learning environment that provides a safe and engaging space for learning and practicing human-robot collaboration skills. The learning environment aims to simulate realistic construction site scenarios where human-robot teams collaborate. The research explores the effectiveness of the virtual learning environment in terms of learning outcomes, usability, and user satisfaction. To do so, eight interviews were conducted with industry experts and university faculty. The results of the interviews showed that there is a significant potential for the immersive virtual reality-based learning environment to improve workers’ skills, increase their confidence, and promote collaboration in the construction industry. Experts emphasized the importance of realistic simulations that closely mimic actual construction scenarios to enhance the learning experience. The interview results were then used to develop a medium-fidelity prototype. Usability testing of the prototype with undergraduate Construction Engineering and Management (CEM) students revealed that the students found the virtual environment engaging and beneficial for understanding the dynamics of human-robot collaboration. They reported an increased awareness of safety protocols and improved their ability to anticipate and coordinate with robot actions. However, some students noted challenges with the interface, suggesting areas for improvement in the system’s intuitiveness and user guidance. The findings of this research have implications for the development of immersive virtual reality-based learning environments and can contribute to the improvement of human-robot collaboration in the construction industry. Further, the technology’s immediate advantages, such as enhancing the safety and effectiveness of human-robot collaboration in construction, make it an important tool for companies in this sector trying to streamline their procedures and develop their staff. This research suggests that immersive VR training can be a valuable component of a broader strategy to integrate automation technologies into the construction industry, ensuring that workers are equipped with the necessary skills and confidence to work effectively alongside robots.
Exploring the Impact of CRAH Unit Partial Failure in Hybrid-Cooled Data Centers
Authors: Heydari Ali , Gharaibeh Ahmad R. , Tradat Mohammad , Soud Qusai , Manaserh Yaman , Radmard Vahideh , Eslami Bahareh , Rodriguez Jeremy , Sammakia Bahgat
Published: November 2024

The escalating information technology (IT) loads in modern data centers (DCs) present formidable challenges for traditional room-conditioning systems. The heat dissipated from IT equipment has witnessed a significant surge due to the rapid development of data processing, retrieval, and storage, driven by changing technology trends and the growing demand for online services. This evolving landscape poses a substantial burden on air-cooling systems, pushing them to their limits, especially with the prevailing trend of rising power densities in microprocessors and the emergence of hot spots. Amidst these challenges, single-phase cold plate cooling is gaining traction as IT power densities experience a dramatic climb. However, the widespread adoption of this cooling method faces impediments such as the limited availability of chilled water supplies, constrained air distribution pathways, and the absence of elevated floors in many older DCs. In response to these limitations, liquid-to-air (L2A) cooling distribution units (CDUs) have emerged as an alternative method. By incorporating hybrid air and liquid cooling technologies, the industry aims to achieve precise, on-demand cooling through the utilization of various techniques. In the realm of hybrid cooling systems that integrate both air and liquid cooling technologies, a partial failure of the Computer Room Air Handlers (CRAH) introduces unique challenges. Such a failure has the potential to disrupt the delicate balance between air and liquid cooling components, leading to uneven heat dissipation. Moreover, the interdependence of liquid and air cooling in hybrid systems means that even a partial failure can trigger a domino effect, reducing the overall cooling efficiency of the system. This comprehensive study delves into the implications of partial failure in the CRAH unit within the high-power density racks of a hybrid-cooled DC. The investigation explores how this partial failure impacts various critical parameters, including cooling capacity (CC), supply air temperature (SAT), air flow rate, supply fluid temperature (SFT), and thermal testing vehicle (TTV) heater case temperatures. For the purposes of this study, two L2A in-row CDUs were utilized, with a combined total heat load of 129 kW supplied to three racks. The experimental setup is meticulously equipped with the necessary instruments for monitoring and assessing tests on both the liquid coolant and air sides. By addressing these issues, the research contributes valuable insights to the ongoing efforts to optimize data center cooling solutions in the face of evolving IT demands and technological advancements.
Thermophysical Property Measurement of GaN-on-AlN Wafers for Next-Generation RF Device Technologies
Authors: Walwil Husam , Shoemaker Daniel C. , Song Yiwen , Kang Kyuhwe , McIlwaine Nathaniel S. , Schuette Michael L. , Tweedie James S. , Sheppard Scott T. , Maria Jon-Paul , Choi Sukwon
Published: November 2024

Gallium nitride (GaN) high electron mobility transistors (HEMTs) play a crucial role in modern radio frequency (RF) power amplifiers. However, the performance and reliability of GaN HEMTs are negatively impacted by device self-heating. Hence, it’s imperative to thoroughly characterize the entire thermal resistance network within the material stack to pinpoint any bottleneck resistance components. In this study, a multi-frequency, multi-spot time-domain thermoreflectance measurement approach was used to measure the thermal resistance associated with the constituent layers and interfaces within a GaN-on-AlN wafer stack. The thermal conductivity of the GaN layer and the AlN substrate in both through-plane and in-plane directions were determined. The GaN/AlN interface exhibits a high thermal boundary conductance (TBC) of 500 MW/m2·K. This surpasses previously reported TBC values across GaN/SiC and GaN/diamond interfaces, highlighting the potential for improved thermal management of GaN HEMTs.
Effect of Die Parameters on the Thermomechanical Performance of PBGA Packages With Hybrid SAC-LTS Interconnects
Authors: Chakraborty Souvik , Mondal Debabrata , Suhling Jeffrey C. , Lall Pradeep
Published: November 2024

Low-temperature solder (LTS) pastes are increasingly used in surface mount technology, replacing the conventional SAC (Sn-Ag-Cu) solder pastes, due to their lower melting point, reducing reflow energy consumption as well as their ability to significantly reduce warpage during package reflow. However, second-level interconnects (solder joints) still remain prone to failure, influenced by factors like peak reflow temperature, time above liquidus and paste-to-ball volume ratio. Besides, understanding the effects of die parameters on Thermal Fatigue Life (TFL) in hybrid SAC-LTS solder joints is crucial for ball grid array (BGA) package reliability. In this study, finite element analyses of plastic ball grid array (PBGA) packages with hybrid SAC-SnBi solder joints were conducted, with varying LTS paste to SAC sphere volume ratio, under thermal cycling boundary conditions. The nonlinear plastic work accumulations in the critical joints were used to compare thermal fatigue life. Once an optimal LTS paste to SAC sphere volume ratio was selected, a series of finite element analyses were conducted with varying die-dimensions (size and thickness) to capture their effects on thermomechanical performance of hybrid joints. This study provides insights for designing reliable PBGA packages, emphasizing the significance of paste-to-ball volume ratio along with die configuration.
Package-level Evaluation System for 3D Thermal Modelling
Authors: Parameswaran Suresh , Refai-Ahmed Gamal , Ramalingam Suresh , Chang Jonathan
Published: November 2024

Thermal modelling is a very important aspect of the thermal management of semiconductor chips. Developing a reliable 3D thermal model is critical. The 3D model will provide a 3-dimensional representation of the thermal behavior within the chip. 3-dimensional heat generation, distribution and measurement are required for this purpose. In this paper, we present a versatile 3D thermal evaluation vehicle that can serve as an important tool in addressing the above requirement. We have developed two generations of semiconductor chips with thermal evaluation capabilities (2D and 3D) to address the above needs. The chip forms the heart of the thermal evaluation system. The architecture, implementation, operation details, programming aspects and usage model of the 3D thermal evaluation tool are covered in this paper. The usage of the evaluation system in developing a 3D thermal model is covered. This chip has a simple implementation and is easy to program and test — yet has substantial 3D thermal modelling and evaluation capabilities. The applications include the following:

• 3D modelling of thermal behavior of semiconductor chips in development, to evaluate architecture/floorplan

• Calibrating 3D thermal simulation results against chip-level measurement data

• Use 3D thermal modelling to address package and cooling solution development

The chip has ability to do automated on-chip measurements through a test-friendly interface and has been tested on a simple and inexpensive test-platform. A large number of heating profiles were programmed, thermal data was collected and analyzed from this thermal evaluation system. Simulations were also done to model the thermal behavior in each of the above-mentioned cases. Comparison of measured data to numerical model based simulation results were done in each case. It is concluded that this evaluation vehicle can play a significant role in the 3D thermal modelling of a semiconductor chip which can be used throughout its development cycle — architecture, floor planning, cooling solutions, package development, and more.
Effect of Bismuth Concentration on the High Strain Rate Characteristics of Sn-Ag-Cu Solders and Analysis of High-g Level Shock Damage During Extended Sustained Operation at 100°C
Authors: Lall Pradeep , Mehta Vishal , Suhling Jeff , Locker David
Published: November 2024

Electronic components commonly face elevated strain loads in industries such as automotive, oil & gas, and aerospace due to shocks, vibrations, and drop-impact scenarios. These components are routinely exposed to a wide range of surrounding temperatures, fluctuating between −65°C and 200°C. Moreover, they may encounter high strain rates, varying from 1 to 100 per second. The solder joint, being one of the weakest links in electronic components/assemblies, is a crucial consideration. The industry has experimented with dopant addition to SAC solders in an effort to mitigate the harmful effects of prolonged exposure to high temperatures. Recently, various doped solder alloys like SAC-Q, SAC-R, M758, etc., have been introduced into electronic components, incorporating elements such as Bismuth, Nickel, and Antimony as dopants. The current literature does not adequately establish the mechanical characteristics of solder alloys at both very low and high working temperatures, especially for long aging times with high-temperature storage. According to JEDEC standard JESD22-B111 (2003), which defines a test board dimension of 132 × 77 × 1.6 mm, published research frequently focuses on the assessment of PCB-Package assemblies under drop/shock circumstances. Numerous research articles on Drop/Shock events contain investigations using Finite Element analysis that simply take into account the elastic characteristics of solder materials. Tensile specimens from different SAC Solders and subjected to testing at operational temperatures spanning from −65°C to 200°C. The tests are conducted at strain rates of up to 75 per second, and the specimens undergo isothermal aging for up to 1 year at a storage temperature of 100°C. The obtained experimental data is then fitted to the Anand viscoplasticity model. Based on trends of properties vs Bi% and, thermal degradation rates vs Bi%, prediction of mechanical properties of doped SAC solder containing higher Bismuth% (e.g. SAC + 4% Bismuth) was carried out. Anand constants are derived for tested and predicted solders, varying aging durations and subsequently applied to explore the viscoplastic behavior of solder joints. Additionally, FE analyses for drop/shock events at 1500g are conducted for various conditions involving the assembly of CABGA208 packages with the PCB (77 × 77 × 1 mm) - dimensions according to latest JEDEC standard JESD22-B111A (2016).
Sequential High Temperature and Hygrothermal Exposure on the Evolution of Interfacial Fracture Toughness of TIM-Copper and EMC Interfaces
Authors: Lall Pradeep , Kasturi Madhu
Published: November 2024

In automotive electronics, where high-performance semiconductors are increasingly utilized for advanced driver assistance systems, effective thermal management is crucial to optimize performance and integration density. One significant aspect is managing thermal interface materials (TIM) to enhance heat dissipation from chips to packages and to heat sinks. Exposure to automotive conditions, characterized by wide temperature ranges and humidity conditions, can lead to early fractures at TIM-to-Copper interfaces, escalating thermal resistance and device thermal runaway. The ongoing downsizing and integration of semiconductor devices has resulted in an increase in heat generated per unit volume of the chip. Insufficient understanding of the development of TIM material fracture toughness during extensive environments in automotive applications hampers the creation of predictive models for estimating time to failure. This paper aims to investigate the impact of temperature storage, and hygrothermal exposure on TIM-Copper and EMC-Substrate interfaces, along with evolving fracture toughness, to develop reliable damage models for assessing performance degradation and predicting interface survivability. The bi-material samples are stored first at high temperatures of between 100°C and 150°C for 60 days then stored in a humidity chamber for moisture absorption at 85°C/85% RH, this is called the sequential exposure. The bi-material samples are subjected to monotonic and fatigue loading to measure mode-1 and mode-2 critical stress intensity factors and Paris’s Power Law Exponents. And, the thermal diffusivity, activation energy, and acceleration factors are being investigated for hygrothermal exposure. The % weight loss/gain of the TIMs for all exposed conditions are presented.
Comparative Performance Analysis of Screen-Printed Structures on PET and BPET Substrates Utilizing Low-Temperature ECA and MACA for SMD Component Attachment
Authors: Lall Pradeep , Kulkarni Shriram , Miller Scott
Published: November 2024

Non-sustainable substrates, such as PET and PI, are used for the additive fabrication of FHE due to their excellent thermal, dimensional stability, and mechanical strength. However, their environmental impact is high due to minimal degradation even after decades in landfills. There is a growing global push for sustainable solutions for printed electronics. Recent studies indicate that alternatives like bio-based PET, polylactic acid (PLA), and regenerated cellulose film, all derived from renewable resources, might not only match but, in some instances, surpass the performance of traditional PET. While these materials show promise in certain environments, comprehensive research on their adaptability across various conditions remains inadequate. This research addresses these concerns, focusing on assessing the performance of bio-based PET substrates in FHE applications and comparing the performance with traditional PET substrates. Research Objectives include — (a) To understand the significance of Flexible Hybrid Electronics in the context of sustainable and environmentally friendly electronics. (b) To determine the compatibility and performance of the biodegradable PET substrate during the screen-printing process, especially while printing with water-based inks. (c) To test the performance of printed circuits and calculate the error percentage between the actual and simulated performance.
Warpage Prediction Improvements for Thin Package-on-Package Architectures
Authors: Kothari Nakul , Dhandapani Karthikeyan , Lee Sangjae (Brandon) , Aldrete Manuel , Puliyath Nidheesh
Published: November 2024

The Package-on-Package (PoP) architecture gained widescale popularity for its relatively lower power consumption and smaller form-factor compared to traditional flip-chip (FC) packages and wafer level FC packages. This was because it effectively shortened the interconnection distance between processor chip and low power double data rate (LPDDR) memory. While the extent of CTE mismatch increased in this architecture, posing significant warpage driven yield loss, researchers have successfully developed finite elements-based simulation methods to predict warpage accurately. Some of the regular Finite Element warpage modeling assumptions made for a traditional Flip Chip Package-on-Package (FC PoP) architectures fail when it comes to thinner PoP architectures. The significantly reduced overall package height for thinner PoP architecture has made its warpage behavior extremely sensitive to the extent of copper content in the package. This high sensitivity is what makes finite elements modeling based warpage prediction challenging. The limited body of published work in this area does point to use of process-based approach for warpage prediction. While promising results and methods have been reported, this methodology is found to be quite cumbersome. Also, the accuracy of the warpage prediction at Room Temperature (RT) and High Temperature (HT) is found to be extremely reliant on one having full access to the detailed process steps which often changes from OSAT vendor to OSAT vendor, and many times deemed confidential, making this approach even more challenging. This paper demonstrates a modified version of the traditional End-of-Line (EoL) Finite Elements based simulation approach to predict warpage shape and magnitude for an already highly sensitive thin PoP architectures. A detailed methodology has been described, alongside step-by-step comparison of warpage prediction improvements from the conventional method to the modified version.
Sequential auditory grouping reduces binaural pitch fusion in listeners with normal hearing, hearing aids, and cochlear implants
Authors: Oh Yonghee , Dean Nicole , Gallun Frederick J. , Reiss Lina A. J.
Published: November 2024

Binaural pitch fusion, the perceptual integration of dichotically presented stimuli that evoke different pitches, can be considered a type of simultaneous grouping. Hence, auditory streaming cues such as temporally flanking stimuli that promote sequential grouping might compete with simultaneous dichotic grouping to reduce binaural fusion. Here, we measured binaural pitch fusion using an auditory streaming task in normal-hearing listeners and hearing-impaired listeners with hearing aids and/or cochlear implants. Fusion ranges, the frequency or electrode ranges over which binaural pitch fusion occurs, were measured in a streaming paradigm using 10 alterations of a dichotic reference/comparison stimulus with a diotic capture stimulus, with fusion indicated by perception of a single stream. Stimuli were pure tones or electric pulse trains depending on the hearing device, with frequency or electrode varied across trials for comparison stimuli. Fusion ranges were also measured for the corresponding isolated stimulus conditions with the same stimulus durations. For all groups, fusion ranges decreased by up to three times in the streaming paradigm compared to the corresponding isolated stimulus paradigm. Hearing-impaired listeners showed greater reductions in fusion than normal-hearing listeners. The findings add further evidence that binaural pitch fusion is moderated by central processes involved in auditory grouping or segregation.
A baseline decomposition ultra-short baseline localization algorithm for arbitrary array structures
Authors: Da Lianglong , Liu Baoheng , Zou Sichen , Zhang Xiaochuan
Published: November 2024

With the rapid development of the marine economy, hydroacoustic positioning technology plays an increasingly important role in marine engineering. The ultra-short baseline (USBL) hydroacoustic positioning system has the advantages of small size, simple operation, and flexible use, and has been widely used. Aiming at the existing USBL acoustic positioning algorithm with low positioning accuracy and complex calculation, a baseline decomposition localization algorithm with arbitrary array structure is proposed. The algorithm is based on the theory of coordinate system transformation, establishes positioning observation equations for each baseline in the base array, and adopts the least squares method to obtain positioning results by selecting different combinations of baselines. The systematic errors of different positioning models themselves are simulated, and then the effects of the three parameter errors, namely, time delay, element coordinates, and sound speed, on the positioning results are analyzed, respectively. Finally, the simulation results and sea trial data show that, compared with the existing algorithms, this algorithm not only simplifies the complicated computation process, but also improves the positioning accuracy and robustness, and has a better application effect.
Adherence Support Strategies for Physical Activity Interventions in People With Chronic Musculoskeletal Pain—A Systematic Review and Meta-Analysis
Authors: Heisig Julia , Lindner Nicole , Kornder Nele , Reichert Wiebke , Becker Annette , Haasenritter Jörg , Viniol Annika , van der Wardt Veronika
Published: November 2024

Background: Chronic musculoskeletal (MSK) pain significantly impacts individuals’ quality of life. Regular physical activity is an important key to therapy. However, adherence to exercise is often below the intended levels. This systematic review aims to assess the effectiveness of adherence support strategies in physical activity randomized controlled trials (RCTs) for patients with chronic MSK pain, to address the challenge of motivation and adherence in this population. Methods: Ovid and CINAHL databases were searched for MSK “chronic pain,” “adherence” and “physical activity” (in various synonyms) for RCTs with a follow-up of at least 6 months. After a screening process that included several team members, a narrative synthesis and a meta-analysis on adherence and effect sizes of different outcomes were performed. Results: An initial database output of 5816 articles resulted in 76 RCTs that remained for analysis. These RCTs showed high heterogeneity of intervention design and outcome data. Adherence to exercise varied widely, with 21 RCTs achieving rates of 80% or higher using strategies like education, goal setting, self-monitoring, and personal feedback. The meta-analysis, based on 29 out of 76 RCTs, indicated a nonsignificant correlation between adherence levels and an improved outcome (eg, pain or quality of life). No individual strategy emerged as superior, emphasizing the complexity and diversity of intervention designs. Conclusions: This review offers strategies, such as information/education and individual goal setting/feedback that may be beneficial for enhancing physical activity in patients with chronic MSK pain. Future research should focus on including promising adherence support strategies and providing data for adherence calculations.
Extending Our Understanding of the Social Determinants of Physical Activity and Sedentary Behaviors in Families: A Systems Mapping Approach
Authors: Rhodes Ryan E. , Banik Anna , Szczuka Zofia , Aulbach Matthias Burkard , DeSmet Ann , Durand Hannah , Gatting Lauren , Green James , Hillison Emily Zelda , Masaryk Radomír , Radtke Theda , Rigby Benjamin P. , Schenkel Konstantin , Warner Lisa Marie , Jones Christopher M. , Luszczynska Aleksandra
Published: November 2024

Background: The social environment is important to consider for effective promotion of movement behaviors like increased physical activity (PA) and reduced sedentary behavior (SB); yet, it is less often considered than individual and built environments. One way to advance social environment research is to develop system maps, an innovative, participatory, action-oriented research process that actively engages stakeholders to visualize system structures and explore how systems “work.” The purpose of this research was to develop PA and SB system maps of the social environment embedded within the core/nuclear family system. Methods: The development process began with a 2-day multicountry, 16-researcher, in-person participatory workshop in August 2023, followed by multiple online follow-up consultations. Attendees contributed to the creation of the maps through shared development of critical determinants and their causal pathways. The structure of the final maps was analyzed using network analysis methods to identify indicators of centrality, and key feedback loops and areas for potential intervention were explored. Results: Key central determinants that were likely critical targets for systems intervention to produce changes in PA and SB and featured prominently in most of the reinforcing and balancing feedback loops included shared family interests, values and priorities, family logistical support, family cohesion/organization, and shared experiences. The maps also highlighted key determinants of the broader social environment external to the family. Conclusions: These system maps support current evidence on movement behaviors in family systems and socioecological theories and have the utility to galvanize future research and policy to promote PA and reduce SB.
A Feminist Critical Discourse Analysis of Reactions to the Inaugural Tour de France Femmes Route
Authors: Delia Elizabeth B. , Sveinson Katherine , Ryder Suzanne
Published: November 2024

Despite interest and investment in women’s cycling, disparities exist between women’s and men’s cycling. Imbalances were evident following announcement of the inaugural Tour de France Femmes, which differed significantly from the Tour de France. We used feminist collective action and critical discourse analysis as theoretical and methodological frameworks to analyze social media users’ (re)production, negotiation, and contestation of gender ideology and gendered power relations in response to the event. We found intertwined discourses of resistance via collective action and counterresistance to maintain the status quo of gender power relations. These discourses underline androcentrism in cycling, where legitimacy in women’s cycling is marked by features of men’s cycling, making gender always relevant among supporters and resulting in significant emotional work. We discuss men’s dominance in sport and its impact on consumers of women’s sport and implications for managers and researchers.
Ediacaran origin and Ediacaran-Cambrian diversification of Metazoa
Authors: Carlisle Emily , Yin Zongjun , Pisani Davide , Donoghue Philip C. J.
Published: November 2024

The timescale of animal diversification has been a focus of debate over how evolutionary history should be calibrated to geologic time. Molecular clock analyses have invariably estimated a Cryogenian or Tonian origin of animals while unequivocal animal fossils first occur in the Ediacaran. However, redating of key Ediacaran biotas and the discovery of several Ediacaran crown-Metazoa prompt recalibration of molecular clock analyses. We present revised fossil calibrations and use them in molecular clock analyses estimating the timescale of metazoan evolutionary history. Integrating across uncertainties including phylogenetic relationships, clock model, and calibration strategy, we estimate Metazoa to have originated in the early Ediacaran, Eumetazoa in the middle Ediacaran, and Bilateria in the upper Ediacaran, with many crown-phyla originating across the Ediacaran-Cambrian interval or elsewise fully within the Cambrian. These results are in much closer accord with the fossil record, coinciding with marine oxygenation, but they reject a literal reading of the fossil record.
Electrically switchable chiral nonlinear optics in an achiral ferroelectric 2D van der Waals halide perovskite
Authors: Yumoto Go , Harata Fuyuki , Nakamura Tomoya , Wakamiya Atsushi , Kanemitsu Yoshihiko
Published: November 2024

Two-dimensional (2D) van der Waals (vdW) semiconductors play a key role in developing nanoscale nonlinear optical devices. 2D Ruddlesden-Popper lead halide perovskites (RPPs) expand the potential of using 2D vdW semiconductors in nonlinear optical applications because they exhibit electrically switchable and chiral second-order optical nonlinearity originating from the emergence of ferroelectricity and chirality. However, electrically switchable chiral nonlinear optics has not yet been realized because of the difficulty in electrically manipulating chiral structures. Here, we demonstrate that chiral second-harmonic generation (SHG) can be electrically induced and switched in an achiral biaxial ferroelectric 2D RPP. We observe reversible and continuous electrical switching of SHG circular dichroism and large nonlinear chiroptical activity. Polarization-resolved SHG imaging reveals that electrical poling induces the ferroelectric multidomain structure arising from the biaxial nature of the material, and the planar chirality appears. Our findings show a simple electrical control of the nonlinear chiroptical responses and establish chiral nonlinear optics based on ferroelectric 2D RPPs.
Ekman revisited: Surface currents to the left of the winds in the Northern Hemisphere
Authors: McPhaden Michael J. , Athulya K. , Girishkumar M. S. , Orlić Mirko
Published: November 2024

Ekman’s theory of wind-driven ocean currents on a rotating planet is central to our understanding of why surface currents are deflected to the right of the winds in the Northern Hemisphere and to the left of the winds in the Southern Hemisphere. The theory admits solutions for currents deflected in the opposite direction at periods shorter than the local inertial period, but Ekman did not mention these currents, and they have only rarely been observed. Here, we describe a prominent example of surface flow in the Bay of Bengal directed to the left of clockwise-rotating land breeze wind forcing using multiple years of data from a long-term deepwater surface moored buoy. We further refine Ekman’s theory so as to better reconcile it with our own and previous measurements and then conclude by discussing the broad implications of this work for understanding wind-forced ocean circulation.
Translating insights into therapies for Long Covid
Authors: Antar Annukka A. R. , Cox Andrea L.
Published: November 2024

Long Covid is defined by a wide range of symptoms that persist after the acute phase of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Commonly reported symptoms include fatigue, weakness, postexertional malaise, and cognitive dysfunction, with many other symptoms reported. Symptom range, duration, and severity are highly variable and partially overlap with symptoms of myalgic encephalomyelitis/chronic fatigue syndrome and other post-acute infectious syndromes, highlighting opportunities to define shared mechanisms of pathogenesis. Potential mechanisms of Long Covid are diverse, including persistence of viral reservoirs, dysregulated immune responses, direct viral damage of tissues targeted by SARS-CoV-2, inflammation driven by reactivation of latent viral infections, vascular endothelium activation or dysfunction, and subsequent thromboinflammation, autoimmunity, metabolic derangements, microglial activation, and microbiota dysbiosis. The heterogeneity of symptoms and baseline characteristics of people with Long Covid, as well as the varying states of immunity and therapies given at the time of acute infection, have made etiologies of Long Covid difficult to determine. Here, we examine progress on preclinical models for Long Covid and review progress being made in clinical trials, highlighting the need for large human studies and further development of models to better understand Long Covid. Such studies will inform clinical trials that will define treatments to benefit those living with this condition.
Initiating Long Covid RECOVERy
Authors: Marrazzo Jeanne , Gibbons Gary H. , Koroshetz Walter
Published: November 2024

The NIH’s RECOVER Initiative aims to ease the suffering of those living with Long Covid.
Exploring the interplay between yeast cell membrane lipid adaptation and physiological response to acetic acid stress
Authors: Wu Fei , Bettiga Maurizio , Olsson Lisbeth
Published: November 2024

Acetic acid is a byproduct of lignocellulose pretreatment and a potent inhibitor of yeast-based fermentation processes. A thicker yeast plasma membrane (PM) is expected to retard the passive diffusion of undissociated acetic acid into the cell. Molecular dynamic simulations suggest that membrane thickness can be increased by elongating glycerophospholipids (GPL) fatty acyl chains. Previously, we successfully engineered
Saccharomyces cerevisiae
to increase GPL fatty acyl chain length but failed to lower acetic acid net uptake. Here, we tested whether altering the relative abundance of diacylglycerol (DAG) might affect PM permeability to acetic acid in cells with longer GPL acyl chains (DAG

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). To this end, we expressed diacylglycerol kinase α (
DGKα
) in DAG

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. The resulting DAG

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_Dgkα strain exhibited restored DAG levels, grew in medium containing 13 g/L acetic acid, and accumulated less acetic acid. Acetic acid stress and energy burden were accompanied by increased glucose uptake in DAG

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_Dgkα cells. Compared to DAG

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, the relative abundance of several membrane lipids changed in DAG

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_Dgkα in response to acetic acid stress. We propose that the ability to increase the energy supply and alter membrane lipid composition could compensate for the negative effect of high net acetic acid uptake in DAG

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_Dgkα under stressful conditions.

IMPORTANCE

In the present study, we successfully engineered a yeast strain that could grow under high acetic acid stress by regulating its diacylglycerol metabolism. We compared how the plasma membrane and total cell membranes responded to acetic acid by adjusting their lipid content. By combining physiological and lipidomics analyses in cells cultivated in the absence or presence of acetic acid, we found that the capacity of the membrane to adapt lipid composition together with sufficient energy supply influenced membrane properties in response to stress. We suggest that potentiating the intracellular energy system or enhancing lipid transport to destination membranes should be taken into account when designing membrane engineering strategies. The findings highlight new directions for future yeast cell factory engineering.