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Vulvovaginal atrophy (VVA) is a common and underreported condition associated with decreased estrogenization of the vaginal tissue. Symptoms include dryness, irritation, soreness, and dyspareunia with urinary frequency, urgency, and urge incontinence. It can occur at any time in a woman's life cycle, although more commonly in the postmenopausal phase, during which the prevalence is close to 50%. Clinical findings include the presence of pale and dry vulvovaginal mucosa with petechiae. Vaginal rugae disappear, and the cervix may become flush with the vaginal wall. A vaginal pH of 4.6 or more supports the diagnosis of VVA. Even while taking systemic estrogen, 10% to 20% of women may still have residual VVA symptoms. Breast cancer treatment increases the prevalence of VVA because the surgical, endocrine, and chemotherapeutic agents used in its treatment can cause or exacerbate VVA. Local estrogen treatment for this group of women remains controversial.

Unlike classical heat diffusion at macroscale, nanoscale heat conduction can occur without energy dissipation because phonons can ballistically travel in straight lines for hundreds of nanometres. Nevertheless, despite recent experimental evidence of such ballistic phonon transport, control over its directionality, and thus its practical use, remains a challenge, as the directions of individual phonons are chaotic. Here, we show a method to control the directionality of ballistic phonon transport using silicon membranes with arrays of holes. First, we demonstrate that the arrays of holes form fluxes of phonons oriented in the same direction. Next, we use these nanostructures as directional sources of ballistic phonons and couple the emitted phonons into nanowires. Finally, we introduce thermal lens nanostructures, in which the emitted phonons converge at the focal point, thus focusing heat into a spot of a few hundred nanometres. These results motivate the concept of ray-like heat manipulations at the nanoscale. Heat conduction at the nanoscale is unlike macroscopic diffusion and phonons can travel in straight lines without dissipation. Here Anufriev et al . show that heat conduction can be spatially directed in nanostructured silicon and exploit this effect to concentrate heat into a focal point.

Nuclear receptors （NRs） are members of a large superfamily of evolutionarily related transcription factors that control a plethora of biological processes. NRs orchestrate complex events such as development, organ homeostasis, metabolism, immune function, and reproduction. Approximately one-half of the 48 human NRs have been shown to act as ligand-regulated transcription factors and respond directly to a large variety of endogenous hormones and metabolites that are generally hydrophobic and small in size （eg, retinoic acid or estradiol）. The second half of the NR family comprises the so-called orphan receptors, for which regulatory ligands are still unknown or may not exist despite the presence of a C-terminal ligand-binding domain, which is the hallmark of all NRs. Several chemicals released into the environment （eg, bisphenols, phthalates, parabens, etc） share some physicochemical properties with natural ligands, allowing them to bind to NRs and activate or inhibit their action. Collectively referred to as endocrine disruptors or endocrine-disrupting chemicals （EDCs）, these environmental pollutants are highly suspected to cause a wide range of developmental, reproductive, neurological, or metabolic defects in humans and wildlife. Crystallographic studies are revealing unanticipated mechanisms by which chemically diverse EDCs interact with the ligand-binding domain of NRs. These studies thereby provide a rational basis for designing novel chemicals with lower impacts on human and animal health. In this review, we provide a structural and mechanistic view of endocrine disrupting action using estrogen receptors α and β, （ERα/β）, peroxisome proliferator activated receptor y （PPARy）, and their respective environmental ligands as representative examples.

RNA interference (RNAi)-based therapeutics are approaching clinical approval for genetically defined diseases. Current clinical success is a result of significant innovations in the development of chemical architectures that support sustained, multi-month efficacy in vivo following a single administration. Conjugate-mediated delivery has established itself as the most promising platform for safe and targeted small interfering RNA (siRNA) delivery. Lipophilic conjugates represent a major class of modifications that improve siRNA pharmacokinetics and enable efficacy in a broad range of tissues. Here, we review current literature and define key features and limitations of this approach for in vivo modulation of gene expression.

Response efforts in emergency applications such as border protection, humanitarian relief and disaster monitoring have improved with the use of Unmanned Aerial Vehicles (UAVs), which provide a flexibly deployed eye in the sky. These efforts have been further improved with advances in autonomous behaviours such as obstacle avoidance, take-off, landing, hovering and waypoint flight modes. However, most UAVs lack autonomous decision making for navigating in complex environments. This limitation creates a reliance on ground control stations to UAVs and, therefore, on their communication systems. The challenge is even more complex in indoor flight operations, where the strength of the Global Navigation Satellite System (GNSS) signals is absent or weak and compromises aircraft behaviour. This paper proposes a UAV framework for autonomous navigation to address uncertainty and partial observability from imperfect sensor readings in cluttered indoor scenarios. The framework design allocates the computing processes onboard the flight controller and companion computer of the UAV, allowing it to explore dangerous indoor areas without the supervision and physical presence of the human operator. The system is illustrated under a Search and Rescue (SAR) scenario to detect and locate victims inside a simulated office building. The navigation problem is modelled as a Partially Observable Markov Decision Process (POMDP) and solved in real time through the Augmented Belief Trees (ABT) algorithm. Data is collected using Hardware in the Loop (HIL) simulations and real flight tests. Experimental results show the robustness of the proposed framework to detect victims at various levels of location uncertainty. The proposed system ensures personal safety by letting the UAV to explore dangerous environments without the intervention of the human operator.

Remote sensing technology in recent years has been regarded the most important source to provide substantial information for delineating the flooding extent to the disaster management authority. There have been numerous studies proposing mathematical or statistical classification models for flood mapping. However, conventional pixel-wise classifications methods rely on the exact match of the spectral signature to label the target pixel. In this study, we propose a fully convolutional neural networks (F-CNNs) classification model to map the flooding extent from Landsat satellite images. We utilised the spatial information from the neighbouring area of target pixel in classification. A total of 64 different models were generated and trained with a variable neighbourhood size of training samples and number of learnable filters. The training results revealed that the model trained with 3 × 3 neighbourhood sized training samples and with 32 convolutional filters achieved the best performance out of the experiments. A new set of different Landsat images covering flooded areas across Australia were used to evaluate the classification performance of the model. A comparison of our proposed classification model to the conventional support vector machines (SVM) classification model shows that the F-CNNs model was able to detect flooded areas more efficiently than the SVM classification model. For example, the F-CNNs model achieved a maximum precision rate (true positives) of 76.7% compared to 45.27% for SVM classification.

The self is a crucial component of the psychic life and plays a central role for the adaptation to the environment. In daily life, this adaptative function is ensured, inter alia, by numerous biases filtering information and favoring those which are self-related. After succinctly reviewing the most documented among them which are affective and mnesic biases, the current paper provides a critical review of literature about a bias which is supposed to be perceptive, the self-prioritization effect (SPE). That has been revealed by Sui et al. (2012, Journal of Experimental Psychology: Human Perception and Performance, 38(5), 1105) with an astute matching task and consists in the fact that arbitrarily tagging shapes to a word referring to the participant (e.g., you-square) leads to faster and more accurate responses as compared to shapes tagged to a word referring to another identity (e.g., strange-circle). The methodological variations of this task and the SPE's both extension and putative origins will be presented, as well as the restrictions which border it, related to the individuals, to the experimental situation and to some more general properties of the self. Finally, some avenues for future research will be proposed, drawing some promising paths: beyond being a robust and intriguing phenomenon, SPE can indeed be considered as a convenient tool to assess some mechanisms underlying social cognition, in various fields using an experimental approach such as developmental psychology and social psychology. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

•Viable motile sperm can sometimes be found in pre-ejaculate fluid.•This has forensic relevance in sexual assault cases.•Other discriminatory forensic science tests may be needed. Much has been written about the presence or absence of spermatozoa in pre-ejaculate fluid (PEF). Published studies only have a small number of participants; their results are conflicting, may be inaccurate and findings have not reached statistical significance. There are potential methodical issues. However, upon review, the possibility exists that PEF may sometimes contain viable spermatozoa. Additional forensic science differentiation may be required to determine whether or not any spermatozoa found on a swab/stain originate from PEF or ejaculate. This may have implications for sexual assault cases.

Although it is commonly accepted that root exudation enhances plant-microbial interactions in the rhizosphere, experimental data on the spatial distribution of exudates are scarce. Our hypothesis was that root hairs exude organic substances to enlarge the rhizosphere farther from the root surface. Barley (Hordeum vulgare 'Pallas' - wild type) and its root-hairless mutant (brb) were grown in rhizoboxes and labelled with 14CO2. A filter paper was placed on the soil surface to capture, image and quantify root exudates. Plants with root hairs allocated more carbon (C) to roots (wild type: 13 %; brb: 8 % of assimilated 14C) and to rhizosheaths (wild type: 1.2 %; brb: 0.2 %), while hairless plants allocated more C to shoots (wild type: 65 %; brb: 75 %). Root hairs increased the radial rhizosphere extension three-fold, from 0.5 to 1.5 mm. Total exudation on filter paper was three times greater for wild type plants compared to the hairless mutant. Root hairs increase exudation and spatial rhizosphere extension, which probably enhance rhizosphere interactions and nutrient cycling in larger soil volumes. Root hairs may therefore be beneficial to plants under nutrient-limiting conditions. The greater C allocation below ground in the presence of root hairs may additionally foster C sequestration.

Indonesia is currently one of the regions with the highest transformation rate of land surface worldwide related to the expansion of oil palm plantations and other cash crops replacing forests on large scales. Land cover changes, which modify land surface properties, have a direct effect on the land surface temperature (LST), a key driver for many ecological functions. Despite the large historic land transformation in Indonesia toward oil palm and other cash crops and governmental plans for future expansion, this is the first study so far to quantify the impacts of land transformation on the LST in Indonesia. We analyze LST from the thermal band of a Landsat image and produce a high-resolution surface temperature map (30 m) for the lowlands of the Jambi province in Sumatra (Indonesia), a region which suffered large land transformation towards oil palm and other cash crops over the past decades. The comparison of LST, albedo, normalized differenced vegetation index (NDVI) and evapotranspiration (ET) between seven different land cover types (forest, urban areas, clear-cut land, young and mature oil palm plantations, acacia and rubber plantations) shows that forests have lower surface temperatures than the other land cover types, indicating a local warming effect after forest conversion. LST differences were up to 10.1 ± 2.6 °C (mean ± SD) between forest and clear-cut land. The differences in surface temperatures are explained by an evaporative cooling effect, which offsets the albedo warming effect. Our analysis of the LST trend of the past 16 years based on MODIS data shows that the average daytime surface temperature in the Jambi province increased by 1.05 °C, which followed the trend of observed land cover changes and exceeded the effects of climate warming. This study provides evidence that the expansion of oil palm plantations and other cash crops leads to changes in biophysical variables, warming the land surface and thus enhancing the increase of the air temperature because of climate change.