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Urbanization is persistent globally and has increasingly significant spatial and environmental consequences. It is especially challenging in developing countries due to the increasing pressure on the limited resources, and damage to the bio-physical environment. Traditional analytical methods of studying the urban land use dynamics associated with urbanization are static and tend to rely on top-down approaches, such as linear and mathematical modeling. These traditional approaches do not capture the nonlinear properties of land use change. New technologies, such as artificial intelligence (AI) and machine learning (ML) have made it possible to model and predict the nonlinear aspects of urban land dynamics. AI and ML are programmed to recognize patterns and carry out predictions, decision making and perform operations with speed and accuracy. Classification, analysis and modeling using earth observation-based data forms the basis for the geospatial support for land use planning. In the process of achieving higher accuracies in the classification of spatial data, ML algorithms are being developed and being improved to enhance the decision-making process. The purpose of the research is to bring out the various ML algorithms and statistical models that have been applied to study aspects of land use planning using earth observation-based data (EO). It intends to review their performance, functional requirements, interoperability requirements and for which research problems can they be applied best. The literature review revealed that random forest (RF), deep learning like convolutional neural network (CNN) and support vector machine (SVM) algorithms are best suited for classification and pattern analysis of earth observation-based data. GANs (generative adversarial networks) have been used to simulate urban patterns. Algorithms like cellular automata, spatial logistic regression and agent-based modeling have been used for studying urban growth, land use change and settlement pattern analysis. Most of the papers reviewed applied ML algorithms for classification of EO data and to study urban growth and land use change. It is observed that hybrid approaches have better performance in terms of accuracies, efficiency and computational cost.

Purpose The optimal strategy of fluid resuscitation in the early hours of severe sepsis and septic shock is controversial, with both an aggressive and conservative approach being recommended. Methods We used the 2013 Premier Hospital Discharge database to analyse the administration of fluids on the first ICU day, in 23,513 patients with severe sepsis and septic shock, who were admitted to an ICU from the emergency department. Day 1 fluid was grouped into categories 1 L wide, starting with 1–1.99 L up to ≥9 L, to examine the effect of day 1 fluids on patient mortality. We built binary response models for hospital mortality and the propensity for receiving more than 5 L of fluids on day 1, using patient age and acute conditions present on admission. Patients were grouped by the requirement for mechanical ventilation and the presence or absence of shock. We assessed trends in the difference between actual and expected mortality, in the low fluid range (1–5 L day 1 fluids) and the high fluid range (5 to ≥9 L day 1 fluids) categories, using weighted linear regression controlling for the effects of sample size and variation within the day 1 fluid category. Results Day 1 fluid administration averaged 4.4 L being lowest in the group with no mechanical ventilation and no shock (3.6 L) and highest (5.4 L) in the group receiving mechanical ventilation and in shock. The administration of day 1 fluids was remarkably consistent on the basis of hospital size, teaching status, rural/urban location, and region of the country. The hospital mortality in the entire cohort was 25.8%, with a mean ICU and hospital length of stay of 5.1 and 9.1 days, respectively. In the entire cohort, low volume resuscitation (1–4.99 L) was associated with a small but significant reduction in mortality, of −0.7% per litre (95% CI −1.0%, −0.4%; p  = 0.02). However, in patients receiving high volume resuscitation (5 to ≥9 L), the mortality increased by 2.3% (95% CI 2.0, 2.5%; p  = 0.0003) for each additional litre above 5 L. Total hospital cost increased by $999 for each litre of fluid above 5 L (adjusted R 2  = 92.7%, p  = 0.005). Conclusion The mean amount of fluid administered to patients with severe sepsis and septic shock in the USA during the first ICU day is less than that recommended by the Surviving Sepsis Campaign guidelines. The administration of more than 5 L of fluid during the first ICU day is associated with a significantly increased risk of death and significantly higher hospital costs.

This research expands efforts to understand differences in NIH funding associated with the self-identified race and ethnicity of applicants. We collected data from 2,397 NIH Biographical Sketches submitted between FY 2003 and 2006 as part of new NIH R01 Type 1 applications to obtain detailed information on the applicants' training and scholarly activities, including publications. Using these data, we examined the association between an NIH R01 applicant's race or ethnicity and the probability of receiving an R01 award. The applicant's publication history as reported in the NIH biographical sketch and the associated bibliometrics narrowed the black/white funding gap for new and experienced investigators in explanatory models. We found that black applicants reported fewer papers on their Biosketches, had fewer citations, and those that were reported appeared in journals with lower impact factors. Incorporating these measures in our models explained a substantial portion of the black/white funding gap. Although these predictors influence the funding gap, they do not fully address race/ethnicity differences in receiving a priority score.

Background Recent studies have implicated microglia—the resident immune cells of the brain—in the pathophysiology of alcoholism. Indeed, post-mortem alcoholic brains show increased microglial markers and increased immune gene expression; however, the effects of ethanol on microglial functioning and how this impacts the brain remain unclear. In this present study, we investigate the effects of acute binge ethanol on microglia and how microglial depletion changes the brain neuroimmune response to acute binge ethanol withdrawal. Methods C57BL/6J mice were treated intragastrically with acute binge ethanol for time course and dose-response studies. Cultured mouse BV2 microglia-like cells were treated with ethanol in vitro for time course studies. Mice were also administered the colony stimulating factor 1 receptor (CSF1R) inhibitor PLX5622 to deplete microglia from the brain. These mice were subsequently treated with acute binge ethanol and sacrificed during withdrawal. Brain and BV2 mRNA were isolated and assessed using RT-PCR to examine expression of microglial and neuroimmune genes. Results Acute binge ethanol biphasically changed microglial (e.g., Iba1, CD68) gene expression, with initial decreases during intoxication and subsequent increases during withdrawal. Acute ethanol withdrawal dose dependently increased neuroimmune gene (e.g., TNFα, Ccl2, IL-1ra, IL-4) expression beginning at high doses. BV2 cells showed biphasic changes in pro-inflammatory (e.g., TNFα, Ccl2) gene expression following ethanol treatment in vitro. Administration of PLX5622 depleted microglia from the brains of mice. Although some neuroimmune genes were reduced by microglial depletion, many others were unchanged. Microglial depletion blunted pro-inflammatory (e.g., TNFα, Ccl2) gene expression and enhanced anti-inflammatory (e.g., IL-1ra, IL-4) gene expression during acute binge ethanol withdrawal. Conclusions These studies find acute binge ethanol withdrawal increases microglial and neuroimmune gene expression. Ethanol exposure also increases microglial pro-inflammatory gene expression in vitro. Furthermore, microglial depletion decreases expression of microglia-specific genes but has little effect on expression of many other neuroimmune signaling genes. Microglial depletion blunted the acute binge ethanol withdrawal induction of pro-inflammatory genes and enhanced induction of anti-inflammatory genes. These findings indicate microglia impact the brain response to acute binge ethanol withdrawal.

Chronic obstructive pulmonary disease (COPD) and obstructive sleep apnea syndrome represent two of the most prevalent chronic respiratory disorders in clinical practice, and cardiovascular diseases represent a major comorbidity in each disorder. The two disorders coexist (overlap syndrome) in approximately 1% of adults but asymptomatic lower airway obstruction together with sleep-disordered breathing is more prevalent. Although obstructive sleep apnea syndrome has similar prevalence in COPD as the general population, and vice versa, factors such as body mass index and smoking influence relationships. Nocturnal oxygen desaturation develops in COPD, independent of apnea/hypopnea, and is more severe in the overlap syndrome, thus predisposing to pulmonary hypertension. Furthermore, upper airway flow limitation contributes to nocturnal desaturation in COPD without apnea/hypopnea. Evidence of systemic inflammation in COPD and sleep apnea, involving C-reactive protein and IL-6, in addition to nuclear factor-kappaB-dependent pathways involving tumor necrosis factor-alpha and IL-8, provides insight into potential basic interactions between both disorders. Furthermore, oxidative stress develops in each disorder, in addition to activation and/or dysfunction of circulating leukocytes. These findings are clinically relevant because systemic inflammation may contribute to the pathogenesis of cardiovascular diseases and the cell/molecular pathways involved are similar to those identified in COPD and sleep apnea. However, the pathophysiological and clinical significance of systemic inflammation in COPD and sleep apnea is not proven, and thus, studies of patients with the overlap syndrome should provide insight into the mechanisms of systemic inflammation in COPD and sleep apnea, in addition to potential relationships with cardiovascular disease.

The theoretical description of quantum dynamics in an intriguing way does not necessarily imply the underlying dynamics is indeed intriguing. Here we show how a known very interesting master equation with an always negative decay rate [ eternal non - Markovianity (ENM)] arises from simple stochastic Schrödinger dynamics (random unitary dynamics). Equivalently, it may be seen as arising from a mixture of Markov (semi-group) open system dynamics. Both these approaches lead to a more general family of CPT maps, characterized by a point within a parameter triangle. Our results show how ENM quantum dynamics can be realised easily in the laboratory. Moreover, we find a quantum time-continuously measured (quantum trajectory) realisation of the dynamics of the ENM master equation based on unitary transformations and projective measurements in an extended Hilbert space, guided by a classical Markov process. Furthermore, a Gorini-Kossakowski-Sudarshan-Lindblad (GKSL) representation of the dynamics in an extended Hilbert space can be found, with a remarkable property: there is no dynamics in the ancilla state. Finally, analogous constructions for two qubits extend these results from non-CP-divisible to non-P-divisible dynamics.

Sharing information coherently between nodes of a quantum network is fundamental to distributed quantum information processing. In this scheme, the computation is divided into subroutines and performed on several smaller quantum registers that are connected by classical and quantum channels 1 . A direct quantum channel, which connects nodes deterministically rather than probabilistically, achieves larger entanglement rates between nodes and is advantageous for distributed fault-tolerant quantum computation 2 . Here we implement deterministic state-transfer and entanglement protocols between two superconducting qubits fabricated on separate chips. Superconducting circuits 3 constitute a universal quantum node 4 that is capable of sending, receiving, storing and processing quantum information 5 – 8 . Our implementation is based on an all-microwave cavity-assisted Raman process 9 , which entangles or transfers the qubit state of a transmon-type artificial atom 10 with a time-symmetric itinerant single photon. We transfer qubit states by absorbing these itinerant photons at the receiving node, with a probability of 98.1 ± 0.1 per cent, achieving a transfer-process fidelity of 80.02 ± 0.07 per cent for a protocol duration of only 180 nanoseconds. We also prepare remote entanglement on demand with a fidelity as high as 78.9 ± 0.1 per cent at a rate of 50 kilohertz. Our results are in excellent agreement with numerical simulations based on a master-equation description of the system. This deterministic protocol has the potential to be used for quantum computing distributed across different nodes of a cryogenic network. Deterministic quantum state transfer and entanglement generation is demonstrated between superconducting qubits on distant chips using single photons.

We report on our findings modifying MCFM using OpenMP to implement multi-threading. By using OpenMP, the modified MCFM will execute on any processor, automatically adjusting to the number of available threads. We modified the integration routine VEGAS to distribute the event evaluation over the threads, while combining all events at the end of every iteration to optimize the numerical integration. Special care has been taken that the results of the Monte Carlo integration are independent of the number of threads used, to facilitate the validation of the OpenMP version of MCFM.

Esr1 + cells in the VMHvl are well known to influence female sexual behaviors. Here the authors find a surprising new role of this population in female aggression. They further reveal that the female VMHvl contains two molecularly and anatomically distinct subdivisions: one for aggression and one for sex. As an essential means of resolving conflicts, aggression is expressed by both sexes but often at a higher level in males than in females. Recent studies suggest that cells in the ventrolateral part of the ventromedial hypothalamus (VMHvl) that express estrogen receptor-α (Esr1) and progesterone receptor are essential for male but not female mouse aggression. In contrast, here we show that VMHvl Esr1+ cells are indispensable for female aggression. This population was active when females attacked naturally. Inactivation of these cells reduced female aggression whereas their activation elicited attack. Additionally, we found that female VMHvl contains two anatomically distinguishable subdivisions that showed differential gene expression, projection and activation patterns after mating and fighting. These results support an essential role of the VMHvl in both male and female aggression and reveal the existence of two previously unappreciated subdivisions in the female VMHvl that are involved in distinct social behaviors.

Background Athina Markou and her colleagues discovered persistent changes in adult behavior following adolescent exposure to ethanol or nicotine consistent with increased risk for developing addiction. Building on Dr. Markou’s important work and that of others in the field, researchers at the Bowles Center for Alcohol Studies have found that persistent changes in behavior following adolescent stress or alcohol exposure may be linked to induction of immune signaling in brain. Aim This study aims to illuminate the critical interrelationship of the innate immune system (e.g., toll-like receptors [TLRs], high-mobility group box 1 [HMGB1]) in the neurobiology of addiction. Method This study reviews the relevant research regarding the relationship between the innate immune system and addiction. Conclusion Emerging evidence indicates that TLRs in brain, particularly those on microglia, respond to endogenous innate immune agonists such as HMGB1 and microRNAs (miRNAs). Multiple TLRs, HMGB1, and miRNAs are induced in the brain by stress, alcohol, and other drugs of abuse and are increased in the postmortem human alcoholic brain. Enhanced TLR-innate immune signaling in brain leads to epigenetic modifications, alterations in synaptic plasticity, and loss of neuronal cell populations, which contribute to cognitive and emotive dysfunctions. Addiction involves progressive stages of drug binges and intoxication, withdrawal-negative affect, and ultimately compulsive drug use and abuse. Toll-like receptor signaling within cortical-limbic circuits is modified by alcohol and stress in a manner consistent with promoting progression through the stages of addiction.