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Abstract In recent years, deep learning has significantly reshaped numerous fields and applications, fundamentally altering how we tackle a variety of challenges. Areas such as natural language processing (NLP), computer vision, healthcare, network security, wide-area surveillance, and precision agriculture have leveraged the merits of the deep learning era. Particularly, deep learning has significantly improved the analysis of remote sensing images, with a continuous increase in the number of researchers and contributions to the field. The high impact of deep learning development is complemented by rapid advancements and the availability of data from a variety of sensors, including high-resolution RGB, thermal, LiDAR, and multi-/hyperspectral cameras, as well as emerging sensing platforms such as satellites and aerial vehicles that can be captured by multi-temporal, multi-sensor, and sensing devices with a wider view. This study aims to present an extensive survey that encapsulates widely used deep learning strategies for tackling image classification challenges in remote sensing. It encompasses an exploration of remote sensing imaging platforms, sensor varieties, practical applications, and prospective developments in the field. 

Tardigrades, commonly known as ‘waterbears’, are eight-legged microscopic invertebrates renowned for their ability to withstand extreme stressors, including high osmotic pressure, freezing temperatures, and complete desiccation. Limb retraction and substantial decreases to their internal water stores results in the tun state, greatly increasing their ability to survive. Emergence from the tun state and/or activity regain follows stress removal, where resumption of life cycle occurs as if stasis never occurred. However, the mechanism(s) through which tardigrades initiate tun formation is yet to be uncovered. Herein, we use chemobiosis to demonstrate that tardigrade tun formation is mediated by reactive oxygen species (ROS). We further reveal that tuns are dependent on reversible cysteine oxidation, and that this reversible cysteine oxidation is facilitated by the release of intracellular reactive oxygen species (ROS). We provide the first empirical evidence of chemobiosis and map the initiation and survival of tardigrades via osmobiosis, chemobiosis, and cryobiosis.In vivoelectron paramagnetic spectrometry suggests an intracellular release of reactive oxygen species following stress induction; when this release is quenched through the application of exogenous antioxidants, the tardigrades can no longer survive osmotic stress. Together, this work suggests a conserved dependence of reversible cysteine oxidation across distinct tardigrade cryptobioses. 

Ensuring software security is a critical task for a deliverable software system in today’s world, and its proper implementation guarantees the quality and security of the information ingested, stored, and processed by the system. It is imperative to introduce computer science and computer engineering students (CS/CE) with the secure software design practices early in their curriculum. This approach will help them understand fundamentals of secure programming, vulnerabilities in software systems, and secure software development before joining the industry workforce. In this paper, we propose an educational framework that integrates software security concepts in a software engineering design course. We envision that the framework will engage CS/CE students applying security principles and practices in different phases of the software development life cycle (SDLC) process. Our work focuses on review of common security requirements, policies, and mechanisms related to specific use cases as well as how those requirements are defined during the software design. 

Increases in the abundance of woody species have been reported to affect the provisioning of ecosystem services in drylands worldwide. However, it is virtually unknown how multiple biotic and abiotic drivers, such as climate, grazing, and fire, interact to determine woody dominance across global drylands. We conducted a standardized field survey in 304 plots across 25 countries to assess how climatic features, soil properties, grazing, and fire affect woody dominance in dryland rangelands. Precipitation, temperature, and grazing were key determinants of tree and shrub dominance. The effects of grazing were determined not solely by grazing pressure but also by the dominant livestock species. Interactions between soil, climate, and grazing and differences in responses to these factors between trees and shrubs were key to understanding changes in woody dominance. Our findings suggest that projected changes in climate and grazing pressure may increase woody dominance in drylands, altering their structure and functioning. 

A measurement is presented of the cross section in proton-proton collisions for the production of two $W$bosons and one $Z$boson. It is based on data recorded by the CMS experiment at the CERN LHC at center-of-mass energies $\sqrt{s}=13$and 13.6 TeV, corresponding to an integrated luminosity of $200{\mathrm{fb}}^{-1}$. Events with four charged leptons (electrons or muons) in the final state are selected. Both nonresonant $WWZ$production and $ZH$production, with the Higgs boson decaying into two $W$bosons, are reported. For the first time, the two processes are measured separately in a simultaneous fit. Combining the two modes, signal strengths relative to the standard model (SM) predictions of ${0.75}_{-0.29}^{+0.34}$and ${1.74}_{-0.60}^{+0.71}$are measured for $\sqrt{s}=13$and 13.6 TeV, respectively. The observed (expected) significance for the triboson signal is 3.8 (2.5) standard deviations for $\sqrt{s}=13.6\mathrm{TeV}$, thus providing the first evidence for triboson production at this center-of-mass energy. Combining the two modes and the two center-of-mass energies, the inclusive signal strength relative to the SM prediction is measured to be ${1.03}_{-0.28}^{+0.31}$, with an observed (expected) significance of 4.5 (5.0) standard deviations. 

Abstract Salient aspects of the commissioning, calibration, and performance of the CMS silicon strip tracker are discussed, drawing on experience during operation with proton-proton collisions delivered by the CERN LHC. The data were obtained with a variety of luminosities. The operating temperature of the strip tracker was changed several times during this period and results are shown as a function of temperature in several cases. Details of the system performance are presented, including occupancy, signal-to-noise ratio, Lorentz angle, and single-hit spatial resolution. Saturation effects in the APV25 readout chip preamplifier observed during early Run 2 are presented, showing the effect on various observables and the subsequent remedy. Studies of radiation effects on the strip tracker are presented both for the optical readout links and the silicon sensors. The observed effects are compared to simulation, where available, and they generally agree well with expectations. 

Interactions among grazing pressure, climate, soil properties, and biodiversity affect ecosystem services provided by drylands.