Internet of Things (IoT) have significantly heightened the level of our awareness about the world and extended the dimension of our interaction with it. While creating unprecedented growth opportunities for semiconductor industry in areas such as biomedical and wearable devices and health and environmental monitoring, IoT has revolutionized the design of integrated circuits and systems for such applications wireless and small for unobtrusive and massive deployment, ultra-low-power for long-term operation, and full integration of all functionalities.

By virtue of low-frequency signals in most of such applications, integrated circuits and systems for IoT nodes are usually heavily duty-cycles and as a result the overall power is usually dominated by the standby circuitry timers and bias blocks. A reference-free timer structure is proposed by using capacitive-discharging topology to avoid the necessity of the conventional power-hungry reference generators. Thereby, it is imperative to minimize the power consumption of the bias circuits. A voltage and current reference generator is implemented leveraging gate-leakage transistors to achieve temperature-stabilized voltage and current references with pW power consumption and being able to generate pA low current reference, which is then employed to implement a timer achieving improved temperature- and supply-stability.

Temperature is an important parameter to measure in a variety of IoT applications. A new temperature sensing technique that relies on complementary temperature dependencies of different types of MOSFETs biased in the subthreshold region, together with constant-with-temperature tunneling currents and a capacitive charging-time-to-digital feedback architecture that digitizes temperature is proposed that consumes 113 pW in a fully monolithically-integrated manner. Another important parameter ion concentration, for example ion homeostasis in sweat, blood, or saliva can potentially provide valuable additional insight into a user’s overall health status. An ion sensing platform that integrates ion-selective electrodes with ultra-low-power sensor instrumentation, a wireless transmitter, and power management circuits is proposed to implement complete sensing-to-transmission functionality, achieving a linear near-Nernstian response with a slope of 71 mV/log10[Na+] through in-vitro testing across a NaCl solution concentration range of 0.1-100 mM.

Wang Hui, editor of Dushu (Beijing), talked about the different historical narratives of China. He argued that the emergence of the modern nation state began in the Song Dynasty and thus the process was independent of European expansion into Asia. Sanjay Subrahmanyam, Director, Center for India and South Asia, Department of History, UCLA, discussed theories on the modernization of India. He talked about challenges to the dominant view that modernity was exported to India via British rule. The accompanying audio files provide the complete recording and audience discussion of the talks given by the authors. No formal paper is included. Those who download the audio files must have their own software for playing and listening.

Moving over X-ray crystallography, single particle cryogenic electron microscopy (cryoEM) has emerged as a method for determining atomic structures of purified proteins in recent years, kicking up a “cryoEM revolution”. However, obtaining high-resolution, in-situ cellular structures that faithfully represent the native environment remains a formidable challenge. To address this need, cryogenic electron tomography (cryoET) has emerged as an invaluable tool for biomedical research. CryoET has the unique capability to provide detailed insights into the molecular mechanisms and biological functions of macromolecular assemblies within their native cellular context. This dissertation embarks on a journey through the world of cryoET combined with subtomogram averaging (STA) to unravel the mysteries of cellular organelles. The first part of this work showcases the power of cryoET and STA in studying the entire flagellar structure of Trypanosoma brucei. This includes the elucidation of the conserved "9+2" axonemal 96 nm subunit, paraflagellar rod (PFR), PFR and Axoneme connectors (PACs), and center pair complex (CPC) structure. This comprehensive exploration sheds light on the motility unit of T. brucei, crucial for the parasite's transmission and pathogenesis. Leveraging the RNAi knockdown technique, we delve into the functions of critical proteins like DRC11, unraveling their structural role in parasite motility. The dissertation further addresses major challenges in the cryoET and STA pipeline through the introduction of two innovative software packages. Firstly, IsoNet tackles the persistent issue of "missing wedge" artifacts. In cryoET data collection, obtaining high-tilt angle images becomes impractical due to the increasing effective sample thickness. This missing information results in wedge-shaped artifacts in Fourier space, causing elongation artifacts along the Z-axis. IsoNet employs deep neural network techniques to fill meaningful signals into the Fourier space's missing wedge area, significantly mitigating or eliminating these artifacts. Secondly, TomoNet focuses on automating particle picking functions through a blend of optimized template matching and deep learning methods. This powerful combination aids in the identification and localization of particles, particularly within lattice-like structures. TomoNet not only simplifies the organization of complete tomography projects but also efficiently manages extensive tomogram datasets through its user-friendly graphical interface. To illustrate TomoNet's particle picking capability, we implemented it in the study of the sheath structure of Methanospirillum hungatei. Applying cryoET with STA, we attained a remarkable 7.9 Å resolution, unveiling the topological features and subunit organization responsible for the native cylindrical sheath tube. Furthermore, a near-atomic level structure prediction of the monomeric sheath protein provides intricate insights into the architecture of individual M. hungatei sheath hoops and their assembly into the sheath layer. We propose a novel route for the synthesis and assembly of sheath fibrils, specifically their insertion into growing sheath sites at the junctions between individual cells. This body of work exemplifies the immense potential of cryoET, STA, and innovative software solutions like IsoNet and TomoNet in elucidating complex biological structures and mechanisms.

The heatwave and drought stresses induced by rapid climate change can alter the emission of isoprene from terrestrial ecosystems. This, in turn, affects climate and air quality by modifying photochemistry and forming secondary organic aerosols. Understanding the complex interactions and feedback loops between climate and isoprene emissions is a challenging yet urgent task. This study integrates laboratory experiments and in-situ measurements to investigate and model these impacts within the Model of Emissions of Gases and Aerosols from Nature (MEGAN).In the first chapter, an empirical algorithm was developed to simulate drought effects on isoprene emissions, revealing an 11% global decrease in isoprene in 2012 due to drought. This algorithm improved the agreement between model simulations and satellite formaldehyde observations during droughts, as formaldehyde is widely used as a proxy for isoprene. However, its performance was limited by the model's ability to accurately capture drought severity. The second and third chapters focus on Arctic ecosystems, where rapid warming is accelerating isoprene emissions. The second chapter characterizes the temperature response of Arctic willows, finding that their hourly temperature response curve is similar to that of temperate plants. Isoprene emissions increase with rising temperature, reaching an optimal level before declining due to enzyme denaturation. Additionally, the isoprene capacity of willows could increase rapidly with rising ambient temperatures from the previous day. During heatwaves, Arctic willows exhibited a 66% higher isoprene emission when using a modified algorithm based on my measurements. The third chapter investigates sedges, another major Arctic isoprene emitter, and finds that their temperature response is notably stronger compared to other isoprene emitters. Integrating these findings into MEGAN improved the capacity of model to reproduce observations. The omission of these strong temperature responses from both willows and sedges led to a 20% underestimation of isoprene emissions in high-latitude regions between 2000 and 2009, and a 55% underestimation of long-term trends from 1960 to 2009. Therefore, rapid warming in the Arctic could significantly increase isoprene emissions, altering local chemistry and impacting the climate.