University of California, Merced

Inter‐annual precipitation in California is highly variable, and future projections indicate an increase in the intensity and frequency of hydroclimatic “whiplash.” Understanding the implications of these shocks on California's water system and its degree of resiliency is critical from a planning perspective. Therefore, we quantify the resilience of reservoir services provided by water and hydropower systems in four basins in the western Sierra Nevada. Using downscaled runoff from 10 climate model outputs, we generated 200 synthetic hydrologic whiplash sequences of alternating dry and wet years to represent a wide range of extremes and transitional conditions used as inputs to a water system simulation model. Sequences were derived from upper (wet) and lower (dry) quintiles of future streamflow projections (2030–2060). Results show that carryover storage was negatively affected in all basins, particularly in those with lower storage capacity. All basins experienced negative impacts on hydropower generation, with losses ranging from 5% to nearly 90%. Reservoir sizes and inflexible operating rules are a particular challenge for flood control, as in extremely wet years spillage averaged nearly the annual basins' total discharge. The reliability of environmental flows and agricultural deliveries varied depending on the basin, intensity, and duration of whiplash sequences. Overall, wet years temporarily rebound negative drought effects, and greater storage capacity results in higher reliability and resiliency, and lesser volatility in services. We highlight potential policy changes to improve flexibility, increase resilience, and better equip managers to face challenges posed by whiplash while meeting human and environmental needs.

Biotribology, the fascinating intersection of biology, materials science, and engineering, delves into these interactions, unraveling the secrets of how biological systems minimize friction, resist wear, and adapt to their environments. This chapter serves as an accessible introduction to the captivating world of biotribology. It embarks on a journey through diverse biological interfaces, exploring the ingenious mechanisms employed by nature to achieve remarkable tribological feats. From the self-lubricating joints of lobsters to the adhesive prowess of gecko feet, we discover how these marvels inspire the development of novel biomimetic materials and technologies. Delving deeper, we investigate the tribological challenges faced by biological systems, such as biocompatibility, wear resistance, and lubrication under extreme conditions. We explore how these challenges are overcome through tailored surface structures, material properties, and ingenious biological fluids. The chapter then highlights the burgeoning field of bioinspired tribology, where insights from nature are harnessed to design innovative solutions for human applications. We delve into exciting areas like biomimetic implants, self-cleaning surfaces, and drag-reducing coatings, showcasing the immense potential of biotribology to revolutionize various fields. Finally, we ponder the future of biotribology, outlining current research frontiers and emerging trends. This chapter paves the way for further exploration, inviting readers to join the captivating quest to understand and harness the power of surface interactions in the biological world.

The utilization of drug-eluting devices has surged in the biomedical sector owing to their precise delivery of therapeutic agents to targeted areas within the body. Composites, a combination of two or more components with distinct properties, offer an innovative avenue for developing highly effective drug-eluting devices. This review aims to explore the potential of composites in drug delivery, focusing on selection criteria, integration of therapeutic agents, release mechanisms, toxicity evaluation, and advanced fabrication techniques. Composite materials, often pairing a biocompatible matrix with therapeutic agents, provide structural support and controlled release properties, while the therapeutic agents deliver targeted treatment. Selecting the right composite material is critical, considering factors like biocompatibility, degradability, mechanical properties, and drug compatibility. This will also emphasize advanced fabrication techniques, particularly additive manufacturing, which is pivotal in biomedical applications. The exploration of composite materials for drug delivery encompasses a comprehensive understanding of their characteristics, selection criteria, and potential across various biomedical domains. Surface engineering and characterization methods, including structural, chemical, and mechanical analysis, will be discussed in detail. Moreover, the study will explore advanced fabrication techniques like additive manufacturing, which is essential for drug delivery, tissue engineering, and regenerative medicine applications. Challenges in composite-based drug delivery, such as biocompatibility, controlled release, and scalability, will be outlined alongside emerging trends. Ultimately, the paper aims to provide readers with a foundational understanding of composite material usage in drug delivery mechanisms and its potential in transformative biomedical applications, steering them toward a comprehensive comprehension of this dynamic realm.

This book chapter explores the dynamic terrain of contemporary biomedical manufacturing techniques, shedding light on cutting-edge advancements that redefine the landscape of medical technology. This chapter also explores the innovative methodologies for precision biomedical engineering, 3D printing, and advanced materials shaping the forefront of biomedical manufacturing. Through a comprehensive examination, it navigates the intricacies of these techniques and highlights their impact on healthcare delivery, device customization, and therapeutic innovations. The chapter aims to provide a comprehensive overview of the current state of biomedical manufacturing, offering insights into its transformative potential and implications for the future of healthcare.

Wear and friction mechanisms in knee and hip rehabilitation have been a focus of intense research due to their critical importance in the longevity and performance of prosthetic implants. This comprehensive review explores the key factors influencing the selection of hip and knee prosthetics, ranging from implant longevity and wear mechanisms to biological responses to wear debris, material selection, design strategies, and patient-specific considerations. The clinical impact and regulatory standards governing these prosthetics are also examined. Various musculoskeletal conditions related to bones, including osteoporosis, bone cancer, congenital anomalies, war-related injuries, and unexpected incidents, collectively result in a yearly economic burden of $136.8 billion on the United States economy. The review further classifies types of hip and knee replacements, including total hip replacement (THR) and resurfacing hip replacement (RHR). It underscores the clinical significance of wear and friction in these contexts. Types of wear in knee and hip joints, such as adhesive, abrasive, fatigue, and corrosion/oxidative wear, are discussed, along with materials selection for implants, encompassing metallic, ceramic, polymer, and composite options. Various surface modifications for enhancing wear resistance are also explored, including ion implantation, surface coatings, and biomimetic modifications. Lubrication strategies in hip and knee replacement, the role of synovial fluid, and lubrication techniques in artificial joints are reviewed alongside emerging surface coatings for wear resistance, such as hydroxyapatite, diamond-like carbon, and metal nitride coatings. Experimental approaches to wear and friction studies, including pin-on-disk testing, joint simulators, tribo-corrosion testing, and wear debris analysis techniques, are analyzed, with a focus on future directions and emerging technologies like additive manufacturing, smart implants, biomaterial innovations, and artificial intelligence in wear prediction. This review concludes by summarizing the current state of knowledge in wear and friction mechanisms in knee and hip rehabilitation and outlines future research directions in this critical area.

There are practical answers to tribology-related problems all around us. Often, one of the interacting surfaces in relative motion is the human skin. Tribological measurement of the skin is an asset to study the properties of the skin and how they are altered in different conditions and with the popular dermal treatments. Test procedures for skin tribology must be in vivo, subject- and anatomical location-specific. In this system, measurement includes the contact with a flexible body and the presence of friction-induced vibration. Tribological studies depend on the frictional and electrical properties of the skin surface, which are determined by the frictional coefficients. These studies are used to quantify skin hydration and health. The friction coefficient of the skin measured depends on key factors like age, anatomical site, and skin hydration. Other factors which affect the coefficient are the design of the measuring instrument and the probe geometry and material. It was found that the skin with decreased hydration had a reduced friction coefficient and an increased resistance to current flow. The treatments on the skin which can affect the skin hydration level also influence the friction coefficient. The application of emollients and moisturisers influences the quantity of greasiness and stickiness quantitatively. Surface texturing and polymer brush coatings are intriguing new developments because they offer a way to customise friction in sliding contacts without having to make significant product adjustments.

Manufacturing of biomedical device involves in-depth understanding of tribology and biology, biotribology. The word “tribology,” comes from ancient Greek. In this chapter, the focus is on challenges and future scopes of biotribology in the field of biomedical devices. Some of the problems while designing a biomedical device involve making the device nano, large-scale production of the device, inconsistency of quality of the device, use of chips in human organs(brain), high-cost manufacturing, mechanical biocompatibility, poor bioprinting mechanism, cell damage rate(high), the device user’s ability, etc. Here the discussion is about how to target each one of them with highly advanced techniques like using combination of 3D and 4D printing techniques, biomedical gadgets which incorporate gecko’s skin, bionic ears/eyes, biosensors, and microgels, biorobots, shark skin properties, biomimetic watery oil applications, lotus leaf surface, creepy crawly silk, and catfish skin bodily fluid, they are highly advance application and still lacking in understanding of their organic working and strategy of manufacture. Human factors engineering (HFE), role of voltametric sensors, internet of things (IoT) in healthcare, and binder jetting-based 3D printing also have contribution to biomedical device’s future. Using software like Autodock, Discovery studio, and Pyrx will help in recognizing the material (protein or ligand) in silico. It also helps in estimating the interaction that is taking place, such as bond types (protein-ligand interaction profiler) and their negative delta G prediction in nature (mimicking). Hence, minimizing the uncertainty of desired results. To target these future scopes various advanced techniques has been discussed in this chapter. The most commonly used techniques are biocompatible film technology, cost-effective techniques for CKD biodevice, non-invasive glucose monitoring devices technique, biosensing device techniques involving volumetric glucose sensors, optical or spectroscopy techniques for other detection purposes, cost-effective electrochemical voltametric sensors techniques, non-invasive glucose monitoring devices technique, three-dimensional (3D) printing techniques, ultraviolet light-emitting diode (UV-LED) stereolithography printer technique, four-dimensional (4D) printing techniques, fabrication(techniques) of hollow self-folding 4D vascular tubes having shape memory by direct-ink-writing (DIW) printing techniques, technique for direct-write printing (DWP) of a vascular 4D scaffold by shape memory nanocomposites (SMNCs: Iron oxide (Fe3O4)), shape memory polymers (SMPs: PLA ink), and advanced biomedical techniques involving biorobots.

Biotribology is an important term which deals with all major facets of tribology anxious with biological system. It is one of the major appealing and briskly developing fields of tribology. It is admitted as one of the more predominant deliberations in various types of biological system to know about the performance of our natural biological system as well as how disorders are caused and the processor of medical treatments should be followed for the treatment of these diseases. Tribological researches related to biological systems are criticized in this book chapter. A brief history, classification as well as present target on biotribology studies are examined on the basis of the previous research in this field. Like development in the field of Joint Tribology, Skin Tribology and Oral Tribology besides this other biological system of living organism is presented. Few important anticipations are discussed.

Nature-driven artifacts have the most precise form of tribological properties. Because of hydration lubrication, biological tissues like articular cartilage have the lowest friction and wear. However, these natural tissues are hard to repair in case of injury, accident, or fracture. Recent advances in bio-tribology include replacement material development like hydrogel through surface property analysis and using hydrogel as an ECM microenvironment for cell proliferation. Hydrogels are used as potential biological tissue development because of the biphasic low friction nature of the material as it contains almost 90% water content like biological tissue. Hydration lubrication enables improved surface characterization and improves tribological properties. The chapter will primarily concentrate on characterizing the surface and structure of hydrogels and exploring the potential they offer as substitutes for biological tissue.

Nanofluidic channels impose extreme confinement on water and ions, giving rise to unusual transport phenomena strongly dependent on the interactions at the channel–wall interface. Yet how the electronic properties of the nanofluidic channels influence transport efficiency remains largely unexplored. Here we measure transport through the inner pores of sub-1 nm metallic and semiconducting carbon nanotube porins. We find that water and proton transport are enhanced in metallic nanotubes over semiconducting nanotubes, whereas ion transport is largely insensitive to the nanotube bandgap value. Molecular simulations using polarizable force fields highlight the contributions of the anisotropic polarizability tensor of the carbon nanotubes to the ion–nanotube interactions and the water friction coefficient. We also describe the origin of the proton transport enhancement in metallic nanotubes using deep neural network molecular dynamics simulations. These results emphasize the complex role of the electronic properties of nanofluidic channels in modulating transport under extreme nanoscale confinement.

Phylogenetic diversity offers critical insights into the ecological dynamics shaping species composition and ecosystem function, thereby informing conservation strategies. Despite its recognized importance in ecosystem management, the assessment of phylogenetic diversity in endangered habitats, such as vernal pools, remains limited. Vernal pools, characterized by cyclical inundation and unique plant communities, present an ideal system for investigating the interplay between ecological factors and phylogenetic structure. This study aims to characterize the phylogenetic patterns of vernal pools and their associated vegetation zones, addressing questions about taxonomic and phylogenetic community discreteness, the role of flooding as a habitat filter, the influence of invasive species on phylogenetic structure, and the impact of seasonal variation on phylogenetic diversity. I find that zones‐of‐vegetation exhibit high between zone taxonomic and phylogenetic beta diversity whereas each zone forms a unique cluster, suggesting that zones are taxonomically and phylogenetically discrete units. Regions of high‐inundation pressure exhibit phylogenetic clustering, indicating that flooding is a habitat filter in vernal pool habitats. Competition between native species conform to the ‘competitive relatedness hypothesis’ and, conversely, communities dominated by invasive Eurasian grass species are phylogenetically clustered. In addition, I find that phylogenetic diversity within zones fluctuates across the spring season in response to changing water levels, precipitation, and temperature. By analyzing three pools within the Merced Vernal Pool and Grassland Reserve, this research elucidates the phylogenetic dynamics of vernal pools. The findings underscore the need for tailored conservation strategies that account for the unique ecological characteristics of each vegetation zone within vernal pool habitats.

A desirable objective in self-supervised learning (SSL) is to avoid feature collapse. Whitening loss guarantees collapse avoidance by minimizing the distance between embeddings of positive pairs under the conditioning that the embeddings from different views are whitened. In this paper, we propose a framework with an informative indicator to analyze whitening loss, which provides a clue to demystify several interesting phenomena and a pivoting point connecting to other SSL methods. We show that batch whitening (BW) based methods do not impose whitening constraints on the embedding but only require the embedding to be full-rank. This full-rank constraint is also sufficient to avoid dimensional collapse. We further demonstrate that the stable rank of the embedding is invariant during training by gradient descent, given the assumption that embedding is updated with an infinitely small learning rate. Based on our analysis, we propose channel whitening with random group partition (CW-RGP), which exploits the advantages of BW-based methods in preventing collapse and avoids their disadvantages requiring large batch size. Experimental results on ImageNet classification and COCO object detection reveal that the proposed CW-RGP possesses a promising potential for learning good representations.

Many problems in fluid mechanics require single-shot 3D measurements of fluid flows, but are limited by available techniques. Here, we design and build a novel flexible high-speed two-color scanning volumetric laser-induced fluorescence (H2C-SVLIF) technique. The technique is readily adaptable to a range of temporal and spatial resolutions, rendering it easily applicable to a wide spectrum of experiments. The core equipment consists of a single monochrome high-speed camera and a pair of ND: YAG lasers pulsing at different wavelengths. The use of a single camera for direct 3D imaging eliminates the need for complex volume reconstruction algorithms and easily allows for the correction of distortion defects. Motivated by the large data loads that result from high-speed imaging techniques, we develop a custom, open-source, software package, which allows for real time playback with correction of perspective defects while simultaneously overlaying arbitrary 3D data. The technique is capable of simultaneous measurement of 3D velocity fields and a secondary tracer in the flow. To showcase the flexibility and adaptability of our technique, we present a set of experiments: (1) the flow past a sphere, and (2) vortices embedded in laminar pipe flow. In the first experiment, two channel measurements are taken at a resolution of 512 × 512 × 512 with volume rates of 65.1 Hz. In the second experiment, a single-color SVLIF system is integrated on a moving stage, providing imaging at 1280 × 304 × 256 with volume rates of 34.8 Hz. Although this second experiment is only single channel, it uses identical software and much of the same hardware to demonstrate the extraction of multiple information channels from single channel volumetric images.

Understanding the spatial patterns of plant diversity across vernal pool complexes remains challenging, as plant communities change rapidly in time and concurrent collection of relevant data for modeling remain logistically elusive. In the absence of coupled ecohydrological data, we demonstrate that the application of drone-mounted light detection and ranging (LiDAR) systems to vernal pools enables estimation of species richness using hydrological proxies and spatial modeling. Parameters related to hydrologic connectivity, soil moisture, and hydroperiod describe substantial variation in species richness patterns (r2 = 0.28 ± 0.03) across vernal pool complexes. Converging factors, such as proximity to areas of hydrologic connectivity with low surface roughness, tend to promote forb richness but describe less of the variation in grasses. Estimates of species richness are accurate to within 2-3 species using models derived from UAV-LiDAR, providing an approximation of potential biodiversity hotspots in lieu of in-situ surveys.

The relationship between catchment storage and discharge is nonlinear. The dynamicity of this relationship is dependent on the distance of the storage measurement from the stream, the depth of the soil moisture (SM) measurement, antecedent SM storage, and precipitation characteristics. Understanding the relative influence of these factors is critical for interpreting runoff generation processes and predicting discharge. In this study, we used a hysteresis index approach and analysed the nonlinear dynamics of catchment storage–discharge relationship across points, hillslope and catchment scales, and their controlling factors. A small headwater forested catchment located in the southern part of the Sierra Nevada region, California, was selected as a case study. In this Mediterranean catchment, the anticlockwise class IV hysteresis loop, indicating an earlier discharge peak than SM, was observed as a prevalent hysteresis class across all the scales, irrespective of seasons (i.e., dry vs. wet) and years (i.e., normal vs. drought). A few clockwise hysteresis loops were observed at the shallow depths (10 and 30 cm) of upslope and lower slope topographic positions. Further, we found a shorter lag time between SM peak to discharge peak at 60 and 90 cm soil depths during the wet season, and during the drought period. The shorter lag at the deeper depth was due to the presence of subsurface flow during high antecedent SM storage conditions and preferential flow through the soil pores during the drought periods. The variability in hysteresis at catchment and hillslope scales was controlled by peak rainfall intensity and antecedent SM storage. However, rainfall characteristics (intensity and depth) were major governing factors for most of the point scale locations. Overall, the current study highlighted the role of SM sensor's location in characterizing storage–discharge behaviour.