Adaptive Component Research Articles

An enhanced temporal algorithm- coupled optimized adaptive sparse principal component analysis methodology for fault diagnosis of chemical processes

Principal component analysis (PCA) is a classic fault diagnosis method widely used in chemical process data modeling. However, the limitation of PCA to handle dynamic and time-variant data has been progressively exposed with the ever-increasing development of artificial intelligence technologies and applications of automation systems in the chemical industry. In this paper, an enhanced temporal algorithm-coupled optimized adaptive sparse PCA (ETA-OASPCA) methodology is proposed with the aim to improve the conventional PCA method by introducing temporal state computation and dynamic adaptive sparsity. The ETA is constructed to extract the state transitions of the time-variant process data by introducing the “Transition” and “Hold”, acquire the region of interest by employing a Maximum Fuzzy c-means (MFCM) method, and then use the region time prediction automaton to label the possible abnormal states. The introduction of dynamic adaptive sparsity in PCA, achieved by presenting an iterative interior point optimization method to update the dynamic sparse penalty term, can impose sparsity constraints on dynamic data calculations, thus enhancing the interpretability of the PCA model. The effectiveness of the proposed method was validated through its application in the Eastman Tennessee process, showing that an average fault detection rate, false alarm rate, and latency of 99.4%, 0.37%, and 4.11 mins can be achieved, respectively.

Components of local adaptation and divergence in pollination efficacy in a coevolving species interaction.

Selection leading to adaptation to interactions may generate rapid evolutionary feedbacks and drive diversification of species interactions. The challenge is to understand how the many traits of interacting species combine to shape local adaptation in ways directly or indirectly resulting in diversification. We used the well-studied interactions between Lithophragma plants (Saxifragaceae) and Greya moths (Prodoxidae) to evaluate how plants and moths together contribute to local divergence in pollination efficacy. Specifically, we studied L. bolanderi and its two specialized Greya moth pollinators in two contrasting environments in the Sierra Nevada, California. Both moths pollinate L. bolanderi during nectaring, and one of them - G. politella - also while ovipositing through the floral corolla into the ovary. Firstly, field surveys of floral visitors and the presence of G. politella eggs and larvae in developing capsules showed that one population is visited only by G. politella and few other pollinators, whereas the other is visited by both Greya species and other pollinators. Secondly, L. bolanderi in these two natural populations differed in several floral traits putatively important for pollination efficacy. Thirdly, laboratory experiments with greenhouse-grown plants and field-collected moths showed that L. bolanderi is more efficiently pollinated by local compared to non-local nectaring moths of both species. Pollination efficacy of ovipositing G. politella was also higher for local moths for the L. bolanderi population that relies more heavily on this species in nature. Finally, time-lapse photography in the laboratory showed that G. politella from different populations differ in oviposition behavior, suggesting the potential for local adaptation also among Greya populations. Collectively, our results are a rare example of components of local adaptation contributing to divergence in pollination efficiency in a coevolving interaction and, thus, provide insights into how geographic mosaics of coevolution may lead to coevolutionary diversification in species interactions. This article is protected by copyright. All rights reserved.

A Holistic Evaluation of Multivariate Statistical Process Monitoring in a Biological and Membrane Treatment System.

Unsupervised process monitoring for fault detection and data cleaning is underdeveloped for municipal wastewater treatment plants (WWTPs) due to the complexity and volume of data produced by sensors, equipment, and control systems. The goal of this work is to extensively test and tune an unsupervised process monitoring method that can promptly identify faults in a full-scale decentralized WWTP prior to significant system changes. Adaptive dynamic principal component analysis (AD-PCA) is a dimension reduction method modified to address autocorrelation and nonstationarity in multivariate processes and is evaluated in this work for its ability to continuously detect drift, shift, and spike faults. For spike faults, univariate drift faults, and multivariate shift faults, implementing AD-PCA on data that are subset by treatment processes and operating states with significant differences in covariates and whose model parameters use week-long training windows, moderate cumulative variance, and a high threshold for detection was found to detect faults prior to existing operational thresholds. To improve the consistency with which the AD-PCA method detects out-of-control conditions in real time, additional work is needed to remove outliers prior to model fitting and to detect multivariate drift faults in which the covariates change slowly.

161 Single-Cell RNA-seq Highlights Immune-Driven Gender Differences in Glioblastoma

INTRODUCTION: Glioblastoma (GBM) is the most common primary malignant brain tumor and has a 1.6-fold higher incidence and shorter survival in men versus women. Gene expression differences may contribute to gender-specific differences. METHODS: Single cell RNA-sequencing (scRNA-seq) was conducted on 19,642 cells from primary IDH-wild type GBM patients of both sexes (n = 11 total, 5 men and 6 women). A two-sample t-test was conducted on average age between sexes. Kaplan-Meier curves were used to evaluate survival between sexes. Bulk RNA-sequencing data was accessed via The Cancer Genome Atlas GBM dataset. Functional enrichment analyses were conducted on both scRNA and bulk RNA-seq data to determine relevant pathways from upregulated genes and visualized as gene concept networks via R. RESULTS: There was no difference in age (63.8 versus 53.8 years in men and women respectively) and survival (24 versus 26 months in men and women respectively). scRNA-seq functional enrichment analysis revealed myeloid cell upregulation in men and increased expression of angiogenesis genes such as ADM in women. There was no difference in T cell gene expression between sexes. Bulk RNA-seq analysis of 90 men and 50 women revealed marked elevation of immunoglobulin genes in men and innate genes such as M1 marker NOS2 in women. CONCLUSIONS: Innate myeloid and adaptive humoral components are highly upregulated in men with GBM compared to women, with no differences seen in T cell expression between sexes. This may contribute to higher incidences and shorter survival in men versus women, which should be accounted for in clinical trial evaluation.

Boosting Adversarial Attacks with Nadam Optimizer

Deep neural networks are extremely vulnerable to attacks and threats from adversarial examples. These adversarial examples deliberately crafted by attackers can easily fool classification models by adding imperceptibly tiny perturbations on clean images. This brings a great challenge to image security for deep learning. Therefore, studying and designing attack algorithms for generating adversarial examples is essential for building robust models. Moreover, adversarial examples are transferable in that they can mislead multiple different classifiers across models. This makes black-box attacks feasible for practical applications. However, most attack methods have low success rates and weak transferability against black-box models. This is because they often overfit the model during the production of adversarial examples. To address this issue, we propose a Nadam iterative fast gradient method (NAI-FGM), which combines an improved Nadam optimizer with gradient-based iterative attacks. Specifically, we introduce the look-ahead momentum vector and the adaptive learning rate component based on the Momentum Iterative Fast Gradient Sign Method (MI-FGSM). The look-ahead momentum vector is dedicated to making the loss function converge faster and get rid of the poor local maximum. Additionally, the adaptive learning rate component is used to help the adversarial example to converge to a better extreme point by obtaining adaptive update directions according to the current parameters. Furthermore, we also carry out different input transformations to further enhance the attack performance before using NAI-FGM for attack. Finally, we consider attacking the ensemble model. Extensive experiments show that the NAI-FGM has stronger transferability and black-box attack capability than advanced momentum-based iterative attacks. In particular, when using the adversarial examples produced by way of ensemble attack to test the adversarially trained models, the NAI-FGM improves the success rate by 8% to 11% over the other attack methods. Last but not least, the NAI-DI-TI-SI-FGM combined with the input transformation achieves a success rate of 91.3% on average.

Electro‐Reconfigurable Adaptive Microlens with Simultaneous Multidirectional Focal Adjustment and Zooming

AbstractElectrically reconfigurable lenses capable of focal adjustment and zooming require deformable adaptive optical components. However, existing electroactive optical devices that perform these functions are limited by fluid leakage or require complex mechanical parts. Although polyvinyl chloride (PVC) gel‐based lenses with variable focal lengths and zooming have recently been developed, focal adjustment can only be made in the horizontal axis. Herein, a PVC gel‐based adaptive microlens capable of controlling the focal length and focal point simultaneously in the vertical, horizontal, and diagonal directions without mechanical gears or liquid leakage is presented. By optimizing the characteristics of PVC gels plasticized with three different structured plasticizers, a PVC gel‐based adaptive microlens is fabricated. The produced microlens demonstrates the properties of multidirectional focal adjustment, variable focal length (+33.7 to −15.1 mm) at low input voltages (<300 V), excellent transparency (>90%), fast response (0.10 s at 100 V), silent operation, low power consumption (0.39 mW), and excellent potential for further miniaturization.

A Novel Approach for Adaptive Partial Sliding Mode Controller Design and Tuning in Non-Minimum Phase Switch-Mode Power Supplies

In this article, a novel systematic approach is proposed for a partial sliding mode controller (SMC) design and tuning in non-minimum phase switch-mode power supplies (SMPS). To achieve a more simplified controller in comparison with the conventional SMCs, the partial SMC (PSMC) is introduced in this article, which just requires a part of the sliding surface for controller formulation. The accuracy of the developed PSMC is proved mathematically within the entire range of operation. Since the control parameters of the PSMC are not selected by trial and error, it can maintain the stability and robustness of the closed-loop system in a broad operational range. In this regard, and to develop a systematic approach for robust control of SMPS, a constant frequency equivalent SMC is designed using the converter nominal parameters. Then, the extracted controller is combined with an adaptive component to ensure asymptotical stability against load and line changes. Considering the Lyapunov stability criteria for nonlinear systems, it is proved that the presented SPMC can be used for output voltage regulation in both discontinuous and continuous operating modes with zero steady state error. To avoid the trial and error method during the controller tuning and parameters selection, the system characteristic equation is extracted using the Jacobian approach. Considering the roots of the characteristic equation and the stable range of the closed-loop system, the controller parameters are tuned. Furthermore, in addition to simulation, the developed approach is evaluated practically using the TMS3220F2810 digital signal processor. It is shown that the dynamic response of the proposed approach is faster than the standard double-loop SMC during load and line changes. Additionally, it is seen that the developed controller is robust against model changes in both continuous and discontinuous operations.

Contribution of the immune response to stroke provides promising directions for future stroke immunotherapies

In the entire world, stroke is a significant source of morbidity and mortality. Tissue plasminogen activator is the sole FDA-approved drug for the treatment of acute ischemic stroke at the moment. Despite the intensive search for new treatments, hundreds of drugs targeting various pathophysiological processes have failed clinical trials. The pathogenesis of risk factors, neurotoxicity, tissue remodelling, and healing are all stages of stroke that are impacted by the immune system. The brain and immune system communicate in both directions, and infection following a stroke is the main cause of patient mortality due to the immunosuppression it causes. While clinical sequelae like dementia may now potentially be described in terms of immunity, more recent research also suggests that the gut microbiota plays a role in the immunological response to stroke. Despite research indicating both harmful and positive actions, the precise roles of innate and adaptive components are still not well understood. If immunity and inflammation are neuroprotective or neurotoxic, time is a critical factor in determining this. In addition, it is evident that many suggested treatments are influenced by the local inflammatory environment. The most promising potential stroke immunotherapies are highlighted here as this review dissects the various elements of the immune response to stroke.

A roadmap for implementation of kV-CBCT online adaptive radiation therapy and initial first year experiences.

Online Adaptive Radiation Therapy (oART) follows a different treatment paradigm than conventional radiotherapy, and because of this, the resources, implementation, and workflows needed are unique. The purpose of this report is to outline our institution's experience establishing, organizing, and implementing an oART program using the Ethos therapy system. We include resources used, operational models utilized, program creation timelines, and our institutional experiences with the implementation and operation of an oART program. Additionally, we provide a detailed summary of our first year's clinical experience where we delivered over 1000 daily adaptive fractions. For all treatments, the different stages of online adaption, primary patient set-up, initial kV-CBCT acquisition, contouring review and edit of influencer structures, target review and edits, plan evaluation and selection, Mobius3D 2nd check and adaptive QA, 2nd kV-CBCT for positional verification, treatment delivery, and patient leaving the room, were analyzed. We retrospectively analyzed data from 97 patients treated from August 2021-August 2022. One thousand six hundred seventy seven individual fractions were treated and analyzed, 632(38%) were non-adaptive and 1045(62%) were adaptive. Seventy four of the 97 patients (76%) were treated with standard fractionation and 23 (24%) received stereotactic treatments. For the adaptive treatments, the generated adaptive plan was selected in 92% of treatments. On average(±std), adaptive sessions took 34.52±11.42min from start to finish. The entire adaptive process (from start of contour generation to verification CBCT), performed by the physicist (and physician on select days), was 19.84±8.21min. We present our institution's experience commissioning an oART program using the Ethos therapy system. It took us 12 months from project inception to the treatment of our first patient and 12 months to treat 1000 adaptive fractions. Retrospective analysis of delivered fractions showed that the average overall treatment time was approximately 35min and the average time for the adaptive component of treatment was approximately 20min.

Cu-doped TiO2 nanoparticles improve local antitumor immune activation and optimize dendritic cell vaccine strategies

Nanoparticle-mediated cancer immunotherapy holds great promise, but more efforts are needed to obtain nanoformulations that result in a full scale activation of innate and adaptive immune components that specifically target the tumors. We generated a series of copper-doped TiO2 nanoparticles in order to tune the kinetics and full extent of Cu2+ ion release from the remnant TiO2 nanocrystals. Fine-tuning nanoparticle properties resulted in a formulation of 33% Cu-doped TiO2 which enabled short-lived hyperactivation of dendritic cells and hereby promoted immunotherapy. The nanoparticles result in highly efficient activation of dendritic cells ex vivo, which upon transplantation in tumor bearing mice, exceeded the therapeutic outcomes obtained with classically stimulated dendritic cells. Efficacious but simple nanomaterials that can promote dendritic cancer cell vaccination strategies open up new avenues for improved immunotherapy and human health.Graphical

Endoplasmic reticulum–bound ANAC013 factor is cleaved by RHOMBOID-LIKE 2 during the initial response to hypoxia in Arabidopsis thaliana

Aerobic reactions are essential to sustain plant growth and development. Impaired oxygen availability due to excessive water availability, e.g., during waterlogging or flooding, reduces plant productivity and survival. Consequently, plants monitor oxygen availability to adjust growth and metabolism accordingly. Despite the identification of central components in hypoxia adaptation in recent years, molecular pathways involved in the very early activation of low-oxygen responses are insufficiently understood. Here, we characterized three endoplasmic reticulum (ER)-anchored Arabidopsis ANAC transcription factors, namely ANAC013, ANAC016, and ANAC017, which bind to the promoters of a subset of hypoxia core genes (HCGs) and activate their expression. However, only ANAC013 translocates to the nucleus at the onset of hypoxia, i.e., after 1.5 h of stress. Upon hypoxia, nuclear ANAC013 associates with the promoters of multiple HCGs. Mechanistically, we identified residues in the transmembrane domain of ANAC013 to be essential for transcription factor release from the ER, and provide evidence that RHOMBOID-LIKE 2 (RBL2) protease mediates ANAC013 release under hypoxia. Release of ANAC013 by RBL2 also occurs upon mitochondrial dysfunction. Consistently, like ANAC013 knockdown lines, rbl knockout mutants exhibit impaired low-oxygen tolerance. Taken together, we uncovered an ER-localized ANAC013-RBL2 module, which is active during the initial phase of hypoxia to enable fast transcriptional reprogramming.

Studying subjective perception of time by Vietnamese and Russian students

Introduction. The perception of time at student age is an important component for successful adaptation to other conditions of education, for socialising in a new social circle and for acquiring knowledge necessary for further professional development. Learning conditions in the modern world are generally similar; however, students from different countries are bearers of differing cultures. The aim is to compare the characteristics of subjective perception of time in terms of its past, present and future by Vietnamese and Russian students. Materials and methods. The sample encompassed a number of university students from Vietnam and Russia. The total number of respondents was 199 (105 Vietnamese students and 94 Russian students). To achieve the set goal, the psychosemantic method and the “Semantic time differential” method were applied. The statistical data processing methods involved the arithmetic mean and Mann-Whitney U-test. Results. The research results revealed certain differences in subjective perception of time between the students from Vietnam and Russia at the level of statistical trend (p≥0.05) – as concerns future perception peculiarities and time structure perception. Conclusion. The subjective perception of time by Vietnamese and Russian students is influenced by the society and culture: the Vietnamese society is less exposed to Western ideas of time management, therefore their perception of time structure is less meaningful; at the same time, the future and the past are deemed to be equally important due to the ancestor cult and placing importance on connection with the departed. The power and vividness of manifestation of different time aspects is also culturally conditioned since it is not customary in Southeast Asia to express one’s emotional manifestations vehemently.

CGAMP-activated cGAS–STING signaling: its bacterial origins and evolutionary adaptation by metazoans

The metazoan cGAMP-activated cGAS-STING innate immunity pathway is triggered in response to genomic instability and DNA damage, thereby providing host defense against microbial pathogens. This pathway also impacts on autophagy, cellular senescence and antitumor immunity, while its overactivation triggers autoimmune and inflammatory diseases. Metazoan cGAS generates cGAMP containing distinct combinations of 3'-5' and 2'-5' linkages, which target the adaptor protein STING and activate the innate immune response through a signaling cascade leading to upregulation of cytokine and interferon production. This Review highlights a structure-based mechanistic perspective of recent advances in cGAMP-activated cGAS-STING innate immune signaling by focusing on the cGAS sensor, cGAMP second messenger and STING adaptor components, thereby elucidating the specificity, activation, regulation and signal transduction features of the pathway. In addition, the Review addresses progress towards identification of inhibitors and activators targeting cGAS and STING, as well as strategies developed by pathogens to evade cGAS-STING immunity. Most importantly, it highlights cyclic nucleotide second messengers as ancient signaling molecules that elicit a potent innate immune response that originated in bacteria and evolved through evolutionary adaptation to metazoans.

Psychological support of the process of adaptation of pupils during the transition to the level of basic general education

The article deals with the problem of psychological support of 5 form pupils to the secondary school. The necessity of developing such adaptation components as psychological, educational, motivational and social through the implementation of the developed programme is shown. The results of a ascertaining experiment conducted on a sample of 90 fifthformers using the following diagnostic tools are presented – Beeman N. Phillips' School Anxiety Scale, the questionnaire “Studying school motivation of pupilsˮ by Natal’ya Luskanova, methodology for studying the motivation of teaching schoolchildren during the transition from primary to secondary by Margarita Luk’yanova and Natal’ya Kalinina, questionnaire for assessing the attractiveness of the classroom staff, expert assessments of teachers. The analysis of the data showed that some of the children of younger adolescence have a high level of school anxiety, a negative attitude to school, positional and marking motives of teaching, the pedagogic staff is not interesting and attractive for them, they systematically violate the rules of school life, showing some unsociability, which indicated the expediency of developing and implementing a programme for psychological support of pupils during the transition to a new stage of school education. There were 25 group classes with pupils using role-playing games, psycho-gymnastic exercises, mini-lectures, discussions, situation analysis, art therapy, fairy-tale-therapy and relaxation techniques; a parent meeting and two pedagogic councils on creating conditions for successful adaptation of fifthformers. The control experiment, as well as the use of mathematical statistics methods, showed the effectiveness of the work done – the presence of changes in all components of adaptation, in particular, the number of children with higher indicators of educational motivation, communication skills, positive attitude to school, the normative level of school anxiety increased.

Depression, anxiety, insomnia, stress, and the way of coping emotions as risk factors for ischemic stroke and their influence on stroke severity: A case-control study in Lebanon.

Stroke is a leading cause of disability and death worldwide. There are numerous debates regarding the relationship between depression, anxiety, insomnia, perceived stress, and ischemic stroke. Moreover, no research on the efficacy of emotion regulation, which is critical for various components of healthy affective and social adaptability, is being conducted. To the best of our knowledge, this is the first study in the MENA region to shed light on the relationship between these conditions and stroke risk, aiming to determine whether depression, anxiety, insomnia, stress, and the way of coping with emotions may be risk factors for ischemic stroke occurrence and to further investigate the ability of two specific types of emotion regulation (cognitive reappraisal and expressive suppression) as possible moderators of the relationship between these psychological diseases and ischemic stroke risk. As a secondary objective, we sought to determine how these pre-existing conditions affect stroke severity levels. This is a case-control survey study involving 113 Lebanese inpatients with a clinical diagnosis of ischemic stroke admitted in hospitals and rehabilitation centers in Beirut and Mount Lebanon, and 451 gender-matched volunteers without clinical signs of stroke as controls recruited from the same hospitals as the cases or attending outpatient clinics for illnesses or treatments unconnected to stroke or transient ischemic attack, as well as visitors or relatives of inpatients (April 2020-April 2021). Data was collected by filling out an anonymous paper-based questionnaire. According to the outcomes of the regression model, depression (aOR: 1.232, 95%CI: 1.008-1.506), perceived stress (aOR: 1.690, 95%CI: 1.413-2.022), a lower educational level (aOR: 0.335, 95%CI: 0.011-10.579), and being married (aOR: 3.862, 95%CI: 1.509-9.888) were associated with an increased risk of ischemic stroke. The moderation analysis revealed that expressive suppression had a significant moderating effect on the relationship between depression, anxiety, perceived stress, insomnia, and ischemic stroke risk, resulting in an increased risk of stroke incidence. In contrast, cognitive reappraisal significantly reduced the risk of ischemic stroke by moderating the association between ischemic stroke risk and the following independent variables: perceived stress and insomnia. On the other hand, our multinomial regression model revealed that the odds of moderate to severe/severe stroke were significantly higher in people with pre-stroke depression (aOR: 1.088, 95% CI: 0.747-1.586) and perceived stress (aOR: 2.564, 95% CI: 1.604-4.100) compared to people who had never had a stroke. Despite several limitations, the findings of our study suggest that people who are depressed or stressed are more likely to have an ischemic stroke. Consequently, additional research into the causes and effects of depression and perceived stress may provide new directions for preventive strategies that can help reduce the risk of stroke. Since pre-stroke depression and perceived stress were also found to be strongly correlated with stroke severity, future studies should evaluate the association between pre-stroke depression, perceived stress, and stroke severity to gain a deeper understanding of the complex interaction between these variables. Lastly, the study shed new light on the role of emotion regulation in the relationship between depression, anxiety, perceived stress, insomnia, and ischemic stroke.

SOCIAL ADAPTATION OF INTERNATIONAL STUDENTS IN THE CONDITIONS OF TRAINING DURING COVID-19 PANDEMIC

Introduction. Social adaptation is an important part of adjustment of international students to training at educational establishments. Better academic achievements among international students are associated with the University membership and a high level of cross-cultural relations. All the components of social adaptation in the conditions of training during COVID-19 pandemic naturally have undergone substantial changes. It is also reflected on psychological state of students, since every country of residence introduced certain quarantine regulations at different times. Some of these regulations were rather strict including curfew and prohibition to leave the house. Under such conditions worries of parents concerning incidence of COVID-19 at home and the country of residence cannot be excluded, as well as intensification of nostalgia due to impossibility to cross the border and return home etc.Objective of our research was to study the main components forming social adaptation of international students in the conditions of quarantine caused by COVID-19.Materials and methods. Our study involved 220 junior students of the 1st-3rd years of training at Bukovinian State Medical University (BSMU). In order to obtain maximum objective and reliable results, the survey was anonymous and randomized involving every third student of a corresponding year of studies. The whole list of questions was arranged into one questionnaire. A student had to give a positive or negative answer. Social adaptation of international students was assessed by means of the Student Adaptation to College Questionnaire (SACQ) developed by Robert W. Baker and Bohdan Siryk (1989, 1994) with the author’s changes and modifications. About 85% of students involved in the survey were from India, about 4% – from Ghana, the rest 11% of the students were from other countries of Asia, Europe, Africa and USA.Results. Under conditions of transfer to the distance learning under pandemic conditions due to COVID-19 the components of social adaptation of international students remain on rather high levels. Thus, the level of general social adaptation under the above conditions remained on the highest and high rates among 55% international learners of higher education, and the rate of social distancing and communication with other people was in 41,4% of foreigners. Nostalgia level was maximum among 55,5% of international students under quarantine conditions of studies, and the rates of social adaptation to the environment remained on the highest levels practically among 80% of respondents.At the same time, direct interrelations of a moderate and strong levels are found between general social adaptation and social distancing with other people, nostalgia, social adaptation to the environment, between social distancing with other people and nostalgia, social distancing and social adaptation to the environment, and between nostalgia and social adaptation to the environment.Conclusions. One of the important components for successful academic progress of international students is their social adaptation.At the same time, all the major components of social adaptation in the form of general social adaptation, social distancing and communication with other people, nostalgia and social adaptation to the environment remain on the highest or rather high levels among the prevailing majority of international applicants of higher medical education under conditions of new forms of training during pandemic caused by COVID-19.

Low-elevation conifers in California's Sierra Nevada are out of equilibrium with climate.

Since the 1930s, California's Sierra Nevada has warmed by an average of 1.2 C. Warming directly primes forests for easier wildfire ignition, but the change in climate also affects vegetation species composition. Different types of vegetation support unique fire regimes with distinct probabilities of catastrophic wildfire, and anticipating vegetation transitions is an important but undervalued component of long-term wildfire management and adaptation. Vegetation transitions are more likely where the climate has become unsuitable but the species composition remains static. This vegetation climate mismatch (VCM) can result in vegetation conversions, particularly after a disturbance like wildfire. Here we produce estimates of VCM within conifer-dominated forests in the Sierra Nevada. Observations from the 1930s Wieslander Survey provide a foundation for characterizing the historical relationship between Sierra Nevada vegetation and climate before the onset of recent, rapid climate change. Based on comparing the historical climatic niche to the modern distribution of conifers and climate, ∼19.5% of modern Sierra Nevada coniferous forests are experiencing VCM, 95% of which is below an elevation of 2356 m. We found that these VCM estimates carry empirical consequences: likelihood of type-conversion increased by 9.2% for every 10% decrease in habitat suitability. Maps of Sierra Nevada VCM can help guide long-term land management decisions by distinguishing areas likely to transition from those expected to remain stable in the near future. This can help direct limited resources to their most effective uses-whether it be protecting land or managing vegetation transitions-in the effort to maintain biodiversity, ecosystem services, and public health in the Sierra Nevada.

The reprogrammed mouse heart phosphoproteome in response to the chronic stress of markedly high cardiac-specific adenylyl cyclase type 8 overexpression.

An appropriate intensity and duration of increased AC-cAMP-PKA-Ca2+ signaling is the quintessential component of acute adaptation to cardiac stress. Our another work demonstrated the existence of an exquisite heart performance and protection profile in response to chronically increased cardiac AC-cAMP-PKA-Ca2+ signaling in young adult mice with cardiac-specific overexpression of adenylyl cyclase type 8 (AC8) (TGAC8). Here, we conducted an unbiased phosphoproteomics analysis to determine the role of altered protein phosphorylation in the chronic adaptive heart performance and protection profile of left ventricle (LV) of TGAC8 at 3-4 months of age. We identified 12,963 phospho-peptides and 3646 phosphoproteins, including 4990 upregulated phosphopeptides and 781 differentially regulated (741 Up and 40 Down) phosphoproteins in TGAC8 vs. WT. Based on differentially regulated phosphoproteins by genotype, we discovered the enrichment of numerous stress response canonical pathways within reprogrammed TGAC8 LV, and predicted upstream regulators and downstream functions. In addition to PKA, numerous kinases (83) and phosphatases (30) were hyper-phosphorylated in TGAC8 vs. WT. By combining the phosphoproteome with its proteome and with the previously published TGAC8 transcriptome, we determined which cardiac performance and adaptive protection profiles were coordinately regulated at post-translational modification (PTM) (phosphorylation), translational and transcriptional levels. To assess the impact of phosphorylation on mRNA transcription, we determined the phosphorylation states of transcriptional factors (TFs) that differed by genotype. Hyper-phosphorylated TFs in TGAC8 were associated with increased mRNA transcription, and immune responses and metabolism pathways. To determine the coordination of proteome and phosphoproteome in reprogramming the TGAC8 LV, we normalized its phosphoproteome to its proteome. These analyses indicated that many stress response signaling pathways were consistently enriched at transcriptional, translational and PTM levels, and that PI3K/AKT signaling was also activated in TGAC8 LV.

Type II CRISPR-Cas System Nucleases: A Pipeline for Prediction and In Vitro Characterization

The use of CRISPR-Cas bacterial adaptive immunity system components for targeted DNA changes has opened broad prospects for programmable genome editing of higher organisms. The most widely used gene editors are based on the Cas9 effectors of the type II CRISPR-Cas systems. In complex with guide RNAs, Cas9 proteins are able to directionally introduce double-stranded breaks into DNA regions that are complementary to guide RNA sequences. Despite the wide range of characterized Cas9s, the search for new Cas9 variants remains an important task, since the available Cas9 editors have several limitations. This paper presents a workflow for the search for and subsequent characterization of new Cas9 nucleases developed in our laboratory. Detailed protocols describing the bioinformatical search, cloning, and isolation of recombinant Cas9 proteins, testing for the presence of nuclease activity in vitro, and determining the PAM sequence, which is required for recognition of DNA targets, are presented. Potential difficulties that may arise, as well as ways to overcome them, are considered.

Framework for Geometric Information Extraction and Digital Modeling from LiDAR Data of Road Scenarios

Road geometric information and a digital model based on light detection and ranging (LiDAR) can perform accurate geometric inventories and three-dimensional (3D) descriptions for as-built roads and infrastructures. However, unorganized point clouds and complex road scenarios would reduce the accuracy of geometric information extraction and digital modeling. There is a standardization need for information extraction and 3D model construction that integrates point cloud processing and digital modeling. This paper develops a framework from semantic segmentation to geometric information extraction and digital modeling based on LiDAR data. A semantic segmentation network is improved for the purpose of dividing the road surface and infrastructure. The road boundary and centerline are extracted by the alpha-shape and Voronoi diagram methods based on the semantic segmentation results. The road geometric information is obtained by a coordinate transformation matrix and the least square method. Subsequently, adaptive road components are constructed using Revit software. Thereafter, the road route, road entity model, and various infrastructure components are generated by the extracted geometric information through Dynamo and Revit software. Finally, a detailed digital model of the road scenario is developed. The Toronto-3D and Semantic3D datasets are utilized for analysis through training and testing. The overall accuracy (OA) of the proposed net for the two datasets is 95.3 and 95.0%, whereas the IoU of segmented road surfaces is 95.7 and 97.9%. This indicates that the proposed net could accomplish superior performance for semantic segmentation of point clouds. The mean absolute errors between the extracted and manually measured geometric information are marginal. This demonstrates the effectiveness and accuracy of the proposed extraction methods. Thus, the proposed framework could provide a reference for accurate extraction and modeling from LiDAR data.