Search

Speleoseismology aims to reconstruct palaeoseismic records by dating pre- and post-damage speleothem calcite. A common approach is to infer palaeo-earthquakes from evidence of coinciding damage features (e.g., rockfall and broken speleothems) at multiple locations, which can be challenging in regions of high tectonic strain where short recurrence intervals of large earthquakes require dating of an impractically large number of damage features. Alternative approaches concerned with dating successive growth changes in individual speleothems (e.g., axis changes and growth hiatuses) are better suited to high-seismicity settings, as closely spaced events are more readily resolved. However, the origins of these growth changes can be ambiguous.This study tested a novel geochemical proxy for quantifying ground shaking that is amenable to high-resolution speleothem studies, and potentially more diagnostic of earthquake damage. We evaluated the hypothesis that past large earthquakes temporarily elevate Mg/Ca in cave drip waters via incongruent carbonate dissolution following host rock fracturing (ICDC), leading to corresponding Mg enrichments in speleothem calcite. To do this, we examined a well-dated Holocene stalagmite (GT1) from a cave near the Alpine Fault, which is Aotearoa/New Zealand’s longest (>500 km) active onshore fault and a major source of seismic hazard. The locality is 4 km from the Alpine Fault’s northern section, which typically ruptures every 414–470 yr in a major (MW >7) to great (MW >8) earthquake, resulting in shaking intensities of MMI >VIII at the study site (MMI: Modified Mercalli Intensity).We present a record of Mg/Ca variability in GT1 since ~5 ka, obtained by laser ablation inductively coupled plasma mass spectrometry along the stalagmite growth axis, and constrained temporally by >40 U–Th ages. Preliminary data show high baseline Mg concentrations in GT1 that cannot be explained solely by other mechanisms of drip water Mg/Ca enrichment (i.e., prior calcite precipitation), suggesting an ongoing contribution of Mg to drip waters by ICDC. Anomalous Mg peaks are therefore interpreted as high-intensity shaking events that temporarily elevated drip water Mg/Ca above baseline values. Post-2.5 ka Mg peaks are generally more subtle (30–50% enrichment) than pre-2.5 ka peaks (40–100%). Magnesium peaks are also strongly associated with brown-stained laminae inferred to reflect soil-derived organics. We propose that the high-Mg/high-organics horizons represent large earthquakes that both fractured the host rock and enhanced the mobilisation of organics from overlying soil.We compared the GT1 record with a proximal and independent 1.4-kyr record of well-dated seismically triggered lacustrine turbidites. Given the subtle nature of Mg peaks in this interval, we consider those associated with physical growth changes (i.e., growth onset/cessation and/or axis change) as more likely to represent earthquakes. Of nine Mg peaks identified, five are associated with major physical growth changes. Of the four largest (MMI >VIII) shaking events in the lake turbidite record, which correspond to northern Alpine Fault surface-rupturing earthquakes, three overlap in age with a GT1 Mg peak and physical growth change. Further, two of the three historic earthquakes that generated MMI ≥VII shaking at the study site also overlap in age with a Mg peak.

Signaling pathways regulate the patterns of Hox gene expression that underlie their functions in specification of axial identity. Little is known about the properties of cis-regulatory elements and underlying transcriptional mechanisms that integrate graded signaling inputs to coordinately control Hox expression. Here we optimized single molecule fluorescent in situ hybridization (smFISH) technique with probes spanning introns to evaluate how three shared retinoic acid response element (RARE)-dependent enhancers in the Hoxb cluster regulate patterns of nascent transcription in vivo at the level of single cells in wild type and mutant embryos. We predominately detect nascent transcription of only a single Hoxb gene in each cell, with no evidence for simultaneous co-transcriptional coupling of all or specific subsets of genes. Single and/or compound RARE mutations indicate each enhancer differentially impacts global and local patterns of nascent transcription, suggesting that selectivity and competitive interactions between these enhancers is important to robustly maintain the proper levels and patterns of nascent Hoxb transcription. This implies rapid and dynamic regulatory interactions potentiate transcription of genes through combined inputs from these enhancers in coordinating the RA response.

Figure legends for Figures S1-S10

Supplemental Methods 1. Exome sequencing pipeline Supplemental Methods 2. RNA seq pipeline Supplemental Methods 3. DNA methylation profiling pipeline Supplemental Methods 4. Fluorescence in situ hybridization Supplemental Methods 5. TCGA samples with possible copy neutral loss of heterozygosity in 3p21 and 3p25 regions

Purpose: Sarcomatoid renal cell carcinoma (SRCC) ranks among the most aggressive clinicopathologic phenotypes of RCC. However, the paucity of high-quality, genome-wide molecular examinations of SRCC has hindered our understanding of this entity.Experimental Design: We interrogated the mutational, copy number, and transcriptional characteristics of SRCC and compared these data with those of nonsarcomatoid RCC (RCC). We evaluated whole-exome sequencing, single-nucleotide polymorphism, and RNA sequencing data from patients with SRCC (n = 65) and RCC (n = 598) across different parent RCC subtypes, including clear-cell RCC, papillary RCC, and chromophobe RCC subtypes.Results: SRCC was molecularly discrete from RCC and clustered according to its parent RCC subtype, though with upregulation of TGFβ signaling across all subtypes. The epithelioid (E-) and spindled (S-) histologic components of SRCC did not show differences in mutational load among cancer-related genes despite a higher mutational burden in S-. Notably, sarcomatoid clear-cell RCC (SccRCC) showed significantly fewer deletions at 3p21-25, a lower rate of two-hit loss for VHL and PBRM1, and more mutations in PTEN, TP53, and RELN compared with ccRCC. A two-hit loss involving VHL predicted for ccRCC and a better prognosis, whereas mutations in PTEN, TP53, or RELN predicted for SccRCC and worse prognosis.Conclusions: SRCC segregates by parent subtype, and SccRCC has a fundamentally different early molecular pathogenesis, usually lacking the classic 3p21-25 deletion and showing distinctive mutational and transcriptional profiles. These features prompt a more precise molecular classification of RCC, with diagnostic, prognostic, and therapeutic implications. Clin Cancer Res; 23(21); 6686–96. ©2017 AACR.See related commentary by Bergerot et al., p. 6381

Figure S1. Biphasic histologic components of sarcomatoid renal cell carcinoma. The macrodissected paired epithelioid or carcinomatous (E) and spindled or sarcomatoid (S) components of clear cell RCC (upper panel), Papillary RCC (middle panel), and chromophobe RCC (lower panel). H&E stain, scale bar 200 �m. Figure S2. Sarcomatoid ccRCC shows fewer VHL deletions. (A) Clear cell RCC (H&E stain, scale bar 100 µm) with (B) Fluorescence in situ hybridization (FISH) image showing paired CEN3q signals (green) and a single VHL signal (red). (C) Sarcomatoid ccRCC (H&E stain, scale bar 100 µm) with (D) FISH image showing balanced CEN3q (green) and VHL (red) signals. (E) Box plot showing significantly higher VHL/3q ratios associated with sarcomatoid histology, P

Table S7a. Ingenuity Pathway Analysis of SRCC vs RCC Table S7b. Ingenuity Pathway Analysis of SccRCC vs advanced stage ccRCC Table S7c. Ingenuity Pathway Analysis of E vs S components of ccRCC

Building ventilation accounts for up to 30% of the heat loss in commercial buildings and 25% in industrial buildings. To effectively aid the reduction of energy consumption in the building sector, the development of demand-driven control systems for heating ventilation and air-conditioning (HVAC) is necessary. In countries with temperate climates such as the UK, many buildings depend on natural ventilation strategies such as openable windows, which are useful for reducing overheating prevalence during the summer. The manual opening and adjustment of windows by occupants, particularly during the heating season, can lead to substantial heat loss and consequent energy consumption. This could also result in the unnecessary or over ventilation of the space, or the fresh air is more than what is required to ensure adequate air quality. Furthermore, energy losses build up when windows are left open for extended periods. Hence, it is important to develop control strategies that can detect and recognise the period and amount of window opening in real-time and at the same time adjust the HVAC systems to minimise energy wastage and maintain indoor environment quality and thermal comfort. This paper presents a vision-based deep learning framework for the detection and recognition of manual window operation in buildings. A trained deep learning model is deployed into an artificial intelligence-powered camera. To assess the proposed strategy's capabilities, building energy simulation was used with various operation profiles of the opening of the windows based on various scenarios. Initial experimental tests were conducted within a university lecture room with a south-facing window. Deep learning influenced profile (DLIP) was generated via the framework, which uses real-time window detection and recognition data. The generated DLIP were compared with the actual observations, and the initial detection results showed that the method was capable of identifying windows that were opened and had an average accuracy of 97.29%. The results for the three scenarios showed that the proposed strategy could potentially be used to help adjust the HVAC setpoint or alert the occupants or building managers to prevent unnecessary heating demand. Further developments include enhancing the framework ability to detect multiple window opening types and sizes and the detection accuracy by optimising the model.

BackgroundThe COVID-19 pandemic has had a significant impact on delivery of NHS care. We have developed the OpenSAFELY Service Restoration Observatory (SRO) to describe this impact on primary care activity and monitor its recovery.ObjectivesTo develop key measures of primary care activity and describe the trends in these measures throughout the COVID-19 pandemic.MethodsWith the approval of NHS England we developed an open source software framework for data management and analysis to describe trends and variation in clinical activity across primary care electronic health record (EHR) data on 48 million adults.We developed SNOMED-CT codelists for key measures of primary care clinical activity selected by a expert clinical advisory group and conducted a population cohort-based study to describe trends and variation in these measures January 2019-December 2021, and pragmatically classified their level of recovery one year into the pandemic using the percentage change in the median practice level rate.ResultsWe produced 11 measures reflective of clinical activity in general practice. A substantial drop in activity was observed in all measures at the outset of the COVID-19 pandemic. By April 2021, the median rate had recovered to within 15% of the median rate in April 2019 in six measures. The remaining measures showed a sustained drop, ranging from a 18.5% reduction in medication reviews to a 42.0% reduction in blood pressure monitoring. Three measures continued to show a sustained drop by December 2021.ConclusionsThe COVID-19 pandemic was associated with a substantial change in primary care activity across the measures we developed, with recovery in most measures. We delivered an open source software framework to describe trends and variation in clinical activity across an unprecedented scale of primary care data. We will continue to expand the set of key measures to be routinely monitored using our publicly available NHS OpenSAFELY SRO dashboards with near real-time data.

Due to the wave nature of light, optical microscopy has a lower-bound lateral resolution limit of approximately half of the wavelength of visible light, that is, within the range of 200 to 350 nm. Fluorescence fluctuation-based super-resolution microscopy (FF-SRM) is a term used to encompass a collection of image analysis techniques that rely on the statistical processing of temporal variations of the fluorescence signal. FF-SRM aims to reduce the uncertainty of the location of fluorophores within an image, often improving spatial resolution by several tens of nanometers. FF-SRM is suitable for live-cell imaging due to its compatibility with most fluorescent probes and relatively simple instrumental and experimental requirements, which are mostly camera-based epifluorescence instruments. Each FF-SRM approach has strengths and weaknesses, which depend directly on the underlying statistical principles through which enhanced spatial resolution is achieved. In this review, the basic concepts and principles behind a range of FF-SRM methods published to date are described. Their operational parameters are explained and guidance for their selection is provided.Due to light's wave nature, an optical microscope's resolution range is 200 to 350 nanometers. Several techniques enhance resolution; this work encompasses several fluorescence fluctuation super-resolution (FF-SMR) methods capable of achieving nanoscopic scales. FF-SRM is known to be suitable for fixed or live-cell imaging and compatible with most conventional microscope setups found in a laboratory. However, each FF-SRM approach has its strengths and weaknesses, which depend directly on the underlying principles through which enhanced spatial resolution is achieved. Therefore, the basic concepts and principles behind diverse FF-SRM methods are revisited in this review. In addition, their operational parameters are explained, and guidance for their selection is provided for microscopists interested in FF-SRM.

Background Simulation training can improve the learning curve of surgical trainees. This research aimed to systematically review randomized clinical trials (RCT) evaluating the performance of junior surgical trainees following virtual reality training (VRT) and other training methods in laparoscopic cholecystectomy. Methods MEDLINE (PubMed), Embase (Ovid SP), Web of Science, Scopus and LILACS were searched for trials randomizing participants to VRT or no additional training (NAT) or simulation training (ST). Outcomes of interest were the reported performance using global rating scores (GRS), the Objective Structured Assessment of Technical Skill (OSATS) and Global Operative Assessment of Laparoscopic Skills (GOALS), error counts and time to completion of task during laparoscopic cholecystectomy on either porcine models or humans. Study quality was assessed using the Cochrane Risk of Bias Tool. PROSPERO ID: CRD42020208499. Results A total of 351 titles/abstracts were screened and 96 full texts were reviewed. Eighteen RCT were included and 15 manuscripts had data available for meta-analysis. Thirteen studies compared VRT and NAT, and 4 studies compared VRT and ST. One study compared VRT with NAT and ST and reported GRS only. Meta-analysis showed OSATS score (mean difference (MD) 6.22, 95%CI 3.81 to 8.36, P Conclusion Meta-analysis suggests that performance measured by OSATS and time to completion of task is improved with VRT compared with NAT for junior trainee in laparoscopic cholecystectomy. However, conclusions are limited by methodological heterogeneity and more research is needed to quantify the potential benefit to surgical training.

Occupancy behaviour in buildings can impact the energy performance and the operation of heating, ventilation and air-conditioning systems. To ensure building operations become optimised, it is vital to develop solutions that can monitor the utilisation of indoor spaces and provide occupants’ actual thermal comfort requirements. This study presents the analysis of the application of a vision-based deep learning approach for human activity detection and recognition in buildings. A convolutional neural network was employed to enable the detection and classification of occupancy activities. The model was deployed to a camera that enabled real-time detections, giving an average detection accuracy of 98.65%. Data on the number of occupants performing each of the selected activities were collected, and deep learning–influenced profile was generated. Building energy simulation and various scenario-based cases were used to assess the impact of such an approach on the building energy demand and provide insights into how the proposed detection method can enable heating, ventilation and air-conditioning systems to respond to occupancy’s dynamic changes. Results indicated that the deep learning approach could reduce the over- or under-estimation of occupancy heat gains. It is envisioned that the approach can be coupled with heating, ventilation and air-conditioning controls to adjust the setpoint based on the building space’s actual requirements, which could provide more comfortable environments and minimise unnecessary building energy loads. Practical application Occupancy behaviour has been identified as an important issue impacting the energy demand of building and heating, ventilation and air-conditioning systems. This study proposes a vision-based deep learning approach to capture, detect and recognise in real-time the occupancy patterns and activities within an office space environment. Initial building energy simulation analysis of the application of such an approach within buildings was performed. The proposed approach is envisioned to enable heating, ventilation and air-conditioning systems to adapt and make a timely response based on occupancy’s dynamic changes. The results presented here show the practicality of such an approach that could be integrated with heating, ventilation and air-conditioning systems for various building spaces and environments.

Due to the wave nature of light, optical microscopy has a lower-bound lateral resolution limit of about half of the wavelength of the detected light, i.e., within the range of 200 to 300 nm. The Fluorescence Fluctuation based Super Resolution Microscopy (FF-SRM) encompases a collection of image analysis techniques which rely on the statistical processing of temporal variations of fluorescence to reduce the uncertainty about the fluorophore positions within a sample, hence, bringing spatial resolution down to several tens of nm. The FF-SRM is known to be suitable for live-cell imaging due to its compatibility with most fluorescent probes and lower instrumental and experimental requirements, which are mostly camera-based epifluorescence instruments. Each FF-SRM approach has strengths and weaknesses, which depend directly on the underlying statistical principles through which enhanced spatial resolution is achieved. In this review, the basic concepts and principles behind a range of FF-SRM methods published to date are revisited. Their operational parameters are explained and guidance for its selection is provided.

Airtightness refers to the amount of air leakage through a building’s envelope. This uncontrolled exchange of air between inside and outside, either infiltration or exfiltration, may lead to therma...

The acute respiratory distress syndrome (ARDS) is a major cause of acute respiratory failure. Its development leads to high rates of mortality, as well as short- and long-term complications, such as physical and cognitive impairment. Therefore, early recognition of this syndrome and application of demonstrated therapeutic interventions are essential to change the natural course of this devastating entity. In this review article, we describe updated concepts in ARDS. Specifically, we discuss the new definition of ARDS, its risk factors and pathophysiology, and current evidence regarding ventilation management, adjunctive therapies, and intervention required in refractory hypoxemia.

What is known and objective Stenotrophomonas maltophilia is an intrinsically multidrug-resistant (MDR) organism which commonly presents as a respiratory tract infection. S. maltophilia is typically treated with high-dose sulfamethoxazole/trimethoprim (SMX/TMP). However, SMX/TMP and other treatment options for S. maltophilia can be limited because of resistance, allergy, adverse events or unavailability of the drug; use of novel agents may be necessary to adequately treat this MDR infection and overcome these limitations. Case description This small case series describes two patients who underwent treatment with tigecycline for ventilator-associated pneumonia (VAP) caused by S. maltophilia after admission to a trauma intensive care unit. At the time of admission for the two reported patients, a national drug shortage of intravenous (IV) SMX/TMP prevented its use. Tigecycline was chosen as a novel agent to treat S. maltophilia VAP based on culture and susceptibility data, and it was used successfully. Both patients showed clinical signs of improvement with eventual cure and discharge from the hospital after treatment with tigecycline, and one patient demonstrated confirmed microbiological cure with a negative repeat bronchoscopic bronchoalveolar lavage (BAL). What is new and conclusion To our knowledge, this small case series is the first documentation of utilizing tigecycline to treat S. maltophilia VAP in the United States. Although it likely should not be considered as a first-line agent, tigecycline proved to be an effective treatment option in the two cases described in the setting of a national drug shortage of the drug of choice.

Summary Background Treatment of ventilated pneumonia is often unsuccessful, even when patients are treated according to established guidelines. Therefore, we aimed to investigate the efficacy of the combination drug device Amikacin Inhale as an adjunctive therapy to intravenous standard-of-care antibiotics for pneumonia caused by Gram-negative pathogens in intubated and mechanically ventilated patients. Methods INHALE was a prospective, double-blind, randomised, placebo-controlled, phase 3 study comprising two trials (INHALE 1 and INHALE 2) done in 153 hospital intensive-care units in 25 countries. Eligible patients were aged 18 years or older; had pneumonia that had been diagnosed by chest radiography and that was documented as being caused by or showing two risk factors for a Gram-negative, multidrug-resistant pathogen; were intubated and mechanically ventilated; had impaired oxygenation within 48 h before screening; and had a modified Clinical Pulmonary Infection Score of at least 6. Patients were stratified by region and disease severity (according to their Acute Physiology and Chronic Health Evaluation [APACHE] II score) and randomly assigned (1:1) via an interactive voice-recognition system to receive 400 mg amikacin (Amikacin Inhale) or saline placebo, both of which were aerosolised, administered every 12 h for 10 days via the same synchronised inhalation system, and given alongside standard-of-care intravenous antibiotics. All patients and all staff involved in administering devices and monitoring outcomes were masked to treatment assignment. The primary endpoint, survival at days 28–32, was analysed in all patients who received at least one dose of study drug, were infected with a Gram-negative pathogen, and had an APACHE II score of at least 10 at diagnosis. Safety analyses were done in all patients who received at least one dose of study drug. This study is registered with ClinicalTrials.gov , numbers NCT01799993 and NCT00805168 . Findings Between April 13, 2013, and April 7, 2017, 807 patients were assessed for eligibility and 725 were randomly assigned to Amikacin Inhale (362 patients) or aerosolised placebo (363 patients). 712 patients received at least one dose of study drug (354 in the Amikacin Inhale group and 358 in the placebo group), although one patient assigned to Amikacin Inhale received placebo in error and was included in the placebo group for safety analyses. 508 patients (255 in the Amikacin Inhale group and 253 in the placebo group) were assessed for the primary endpoint. We found no between-group difference in survival: 191 (75%) patients in the Amikacin Inhale group versus 196 (77%) patients in the placebo group survived until days 28–32 (odds ratio 0·841, 95% CI 0·554–1·277; p=0·43). Similar proportions of patients in the two treatment groups had a treatment-emergent adverse event (295 [84%] of 353 patients in the Amikacin Inhale group vs 303 [84%] of 359 patients in the placebo group) or a serious treatment-emergent adverse event (101 [29%] patients vs 97 [27%] patients). Interpretation Our findings do not support use of inhaled amikacin adjunctive to standard-of-care intravenous therapy in mechanically ventilated patients with Gram-negative pneumonia. Funding Bayer AG.

HCI education reflects the continual evolution of HCI, embracing the changing landscapes of technology, infrastructure, and technology use. This forum aims to provide a platform for HCI educators, practitioners, researchers, and students to share their perspectives, reflections, and experiences related to HCI education. --- Sukeshini Grandhi, Editor

Here we present a machine-learning-based method for utilizing traditional ocean-viewing satellites to perform automated atmospheric correction of nanosatellite data. These sensor convolution techniques are required because nanosatellites do not usually possess the wavelength combinations required to atmospherically correct upwelling radiance data for oceanographic applications; however, nanosatellites do provide superior ground-viewing spatial resolution (~3 m). Coincident multispectral data from the Suomi National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite (Suomi NPP VIIRS; referred to herein as “VIIRS”) were used to remove atmospheric contamination at each of the nanosatellite’s visible wavelengths to yield an estimate of spectral water-leaving radiance [Lw(l)], which is the basis for surface ocean optical products. Machine learning (ML) algorithms (KNN, decision tree regressors) were applied to determine relationships between Lw and top-of-atmosphere (Lt)/Rayleigh (Lr) radiances within VIIRS training data, and then applied to test cases for (1) the Marine Optical Buoy (MOBY) in Hawaii and (2) the AErosol RObotic Network Ocean Color (AERONET-OC), Venice, Italy. For the test cases examined, ML-based methods appeared to improve statistical results when compared to alternative dark spectrum fitting (DSF) methods. The results suggest that ML-based sensor convolution techniques offer a viable path forward for the oceanographic application of nanosatellite data streams.

Intestinal epithelial replenishment is fueled by continuously dividing intestinal stem cells (ISCs) resident at the crypt niche. However, the cell type(s) enabling replenishment upon damage and subsequent loss of whole crypts remain largely unclear. Using Set domain-containing protein 4 (Setd4), we identify a small population with reserve stem cell characteristics in the mouse intestine. Upon irradiation-induced injury, Setd4-expressing (Setd4

Aim Ventral hernias are increasing in prevalence and many recur despite attempted repair. To date, much of the literature is underpowered and divergent. As a result there is limited high quality evidence to inform surgeons succinctly which perioperative variables influence postoperative recurrence. This systematic review aimed to identify predictors of ventral hernia recurrence. Material and Methods PubMed was searched for studies reporting prognostic data of ventral hernia recurrence between 1 January 1995 and 1 January 2018. Extracted data described hernia type (primary/incisional), definitions of recurrence, methods used to detect recurrence, duration of follow-up, and co-morbidity. Data were extracted for all potential predictors, estimates and thresholds described. Random-effects meta-analysis was used. Bias was assessed with a modified PROBAST (Prediction model Risk Of Bias ASsessment Tool). Results Screening of 18 214 abstracts yielded 274 individual studies for inclusion. Hernia recurrence was defined in 66 studies (24.1 per cent), using 41 different unstandardized definitions. Three patient variables (female sex, age 65 years or less, and BMI greater than 25, 30, 35 or 40 kg/m2), five patient co-morbidities (smoking, diabetes, chronic obstructive pulmonary disease, ASA grade III–IV, steroid use), two hernia-related variables (incisional/primary, recurrent/primary), six intraoperative variables (biological mesh, bridged repair, open versus laparoscopic surgery, suture versus mesh repair, onlay/retrorectus, intraperitoneal/retrorectus), and six postoperative variables (any complication, surgical-site occurrence, wound infection, seroma, haematoma, wound dehiscence) were identified as significant prognostic factors for hernia recurrence. Conclusions This study summarized the current evidence base for predicting ventral hernia recurrence. Results should inform best practice and future research.

The built environment sector is responsible for almost one-third of the world's final energy consumption. Hence, seeking plausible solutions to minimise building energy demands and mitigate adverse environmental impacts is necessary. Artificial intelligence (AI) techniques such as machine and deep learning have been increasingly and successfully applied to develop solutions for the built environment. This review provided a critical summary of the existing literature on the machine and deep learning methods for the built environment over the past decade, with special reference to holistic approaches. Different AI-based techniques employed to resolve interconnected problems related to heating, ventilation and air conditioning (HVAC) systems and enhance building performances were reviewed, including energy forecasting and management, indoor air quality and occupancy comfort/satisfaction prediction, occupancy detection and recognition, and fault detection and diagnosis. The present study explored existing AI-based techniques focusing on the framework, methodology, and performance. The literature highlighted that selecting the most suitable machine learning and deep learning model for solving a problem could be challenging. The recent explosive growth experienced by the research area has led to hundreds of machine learning algorithms being applied to building performance-related studies. The literature showed that existing research studies considered a wide range of scope/scales (from an HVAC component to urban areas) and time scales (minute to year). This makes it difficult to find an optimal algorithm for a specific task or case. The studies also employed a wide range of evaluation metrics, adding to the challenge. Further developments and more specific guidelines are required for the built environment field to encourage best practices in evaluating and selecting models. The literature also showed that while machine and deep learning had been successfully applied in building energy efficiency research, most of the studies are still at the experimental or testing stage, and there are limited studies which implemented machine and deep learning strategies in actual buildings and conducted the post-occupancy evaluation.

Numerous genes required for sexual reproduction remain to be identified even in simple model species like Schizosaccharomyces pombe. To address this, we developed an assay in S. pombe that couples transposon mutagenesis with high-throughput sequencing (TN-seq) to quantitatively measure the fitness contribution of nonessential genes across the genome to sexual reproduction. This approach identified 532 genes that contribute to sex, including more than 200 that were not previously annotated to be involved in the process, of which more than 150 have orthologs in vertebrates. Among our verified hits was an uncharacterized gene, ifs1 (important for sex), that is required for spore viability. In two other hits, plb1 and alg9, we observed a novel mutant phenotype of poor spore health wherein viable spores are produced, but the spores exhibit low fitness and are rapidly outcompeted by wild type. Finally, we fortuitously discovered that a gene previously thought to be essential, sdg1 (social distancing gene), is instead required for growth at low cell densities and can be rescued by conditioned medium. Our assay will be valuable in further studies of sexual reproduction in S. pombe and identifies multiple candidate genes that could contribute to sexual reproduction in other eukaryotes, including humans.

Many genes required for sexual reproduction remain to be identified. Moreover, many of the genes that are known have been characterized in distinct experiments using different conditions, which complicates understanding the relative contributions of genes to sex. To address these challenges, we developed an assay inSchizosaccharomyces pombe that couples transposon mutagenesis with high-throughput sequencing (TN-seq) to quantitatively measure the fitness contribution of nonessential genes across the genome to sexual reproduction. This approach identified 532 genes that contribute to sex, including more than 200 that were not previously annotated to be involved in the process, of which more than 150 have orthologs in vertebrates. Among our verified hits was an uncharacterized gene,ifs1(importantforsex), that is required for spore viability. In two other hits,plb1andalg9, we observed a novel mutant phenotype of poor spore health wherein viable spores are produced, but the spores exhibit low fitness and are rapidly outcompeted by wildtype. Finally, we fortuitously discovered that a gene previously thought to be essential,sdg1(socialdistancinggene), is instead required for growth at low cell densities. Our assay will be valuable in further studies of sexual reproduction inS. pombeand identifies multiple candidate genes that could contribute to sexual reproduction in other eukaryotes, including humans.

This paper presents the experimental advances on the implementation of structural polymeric materials in a micro-turbine-generator for an organic Rankine cycle (ORC) and through testing provides an insight of its performance. The aim is to create awareness of the huge techno-economical potential that polymers represent as metal replacement in ORC applications. A micro-turbine-generator is developed considering R245fa as the working fluid. The unit is built using polymeric components; these components include an impeller made from polyether-ether-ketone and a nozzle body made from polyethylene. A program for the simulation of the micro-turbine performance is developed, a series of tests are conducted with compressed air and the performance with R245fa is predicted. The impeller was experimentally demonstrated to be able to withstand a rotational speed of 32,040 rpm whereas the predicted results showed the aerodynamic efficiency and the aerodynamic power to be around 0.65 and 1200 W respectively. The future of polymeric materials in ORC looks promising though a long-term test using the refrigerant as the working fluid is still needed to verify material-fluid compatibility, lifespan and resistance to fatigue.

In this study, we have examined ceramic matrix composites with silicon carbide fibers in a melt-infiltrated silicon carbide matrix (SiC/SiC). We subjected samples to tensile loads while collecting micro X-ray computed tomography images. The results showed the expected crack slowing mechanisms and lower resistance to crack propagation where the fibers ran parallel and perpendicular to the applied load respectively. Cracking was shown to initiate not only from the surface but also from silicon inclusions. Post heat-treated samples showed longer fiber pull-out than the pristine samples, which was incompatible with previously proposed mechanisms. Evidence for oxidation was identified and new mechanisms based on oxidation or an oxidation assisted boron nitride phase transformation was therefore proposed to explain the long pull-out. The role of oxidation emphasizes the necessity of applying oxidation resistant coatings on SiC/SiC.

De novo protein design is a rapidly growing field, and there are now many interesting and useful examples of designed proteins in the literature. However, most designs could be classed as failures when characterised in the lab, usually as a result of low expression, misfolding, aggregation or lack of function. This high attrition rate makes protein design unreliable and costly. It is possible that some of these failures could be caught earlier in the design process if it were quick and easy to generate information and a set of high-quality metrics regarding designs, which could be used to make reproducible and data-driven decisions about which designs to characterise experimentally. We present DE-STRESS (DEsigned STRucture Evaluation ServiceS), a web application for evaluating structural models of designed and engineered proteins. DE-STRESS has been designed to be simple, intuitive to use and responsive. It provides a wealth of information regarding designs, as well as tools to help contextualise the results and formally describe the properties that a design requires to be fit for purpose.

An interprofessional team approach is required to achieve optimum fluid balance for patients during the perioperative period. Incorrect management of fluid assessment and monitoring is associated with adverse outcomes. The scientific understanding of perioperative fluid balance has improved over recent years leading to changes in clinical practice with regard to volume and choice of intravenous fluid. It is important that perioperative practitioners have an understanding of intravenous fluid, fluid compartmentalisation, fluid mechanics and intravascular fluid control mechanisms. Optimum fluid status not only shortens hospital stay but also reduces the incidence of postoperative nausea and vomiting and complication profiles. This article aims to provide perioperative practitioners with a comprehensive overview of fluid management. It will cover important issues surrounding physiological control of fluid balance, choice of intravenous fluid therapy, methods to monitor intravascular volume and factors which influence delivery.

Flag use by far-right demonstrators at the 2017 Unite the Right rally is similar to historical flag use in public demonstration by antidemocratic groups seeking to deprive others of equal democratic rights, such as the Nazi Party between 1920 and 1945 and American segregationists during the Civil Rights Movement in the mid-twentieth century. This sort of flag use brings democratic values such as free speech and equal protections into conflict. Since World War II, international democratic norms have shifted to emphasize human dignity and equality, even if it requires limitations on free speech. Germany’s constitutional order is designed to protect democracy from antidemocratic groups in part by criminalizing display of flags representing them. Meanwhile, free speech absolutism in the United States makes it exceedingly difficult to impose legal sanctions for flag use, allowing flags that are in fact hate speech to masquerade as protected political speech.

Introduction Thrombocytopenia is common in critically ill trauma patients and can lead to potentially broad differentials, including major bleeding, hemodilution, extracorporeal circuit losses, heparin-induced thrombocytopenia, and more. Understanding the normal time course of platelet decline and recovery may delineate thrombocytopenia(HIT) secondary to traumatic injury versus other inciting factors. Methods This retrospective study included trauma patients admitted over a 1-year period. The primary aim was characterizing the effect of trauma on platelet concentration and thrombocytopenia incidence in the first 30 days following injury. Thrombocytopenia was defined as platelet concentration 9/L. A secondary aim was evaluating significant factors contributing to thrombocytopenia. Results A total of 225 patients were included. Thrombocytopenia occurred in 67.3% of patients, and a platelet decline of 50% or greater occurred in 44%. Decrease in platelet concentration was significant from day 1 to day 4 (mean ± SD, 232 ± 86 vs 142 ± 76 × 109/L; p = .001). Platelets recovered to baseline on day 8 and peaked on day 16. Packed red blood cell or platelet transfusion, continuous renal replacement therapy, and acute liver injury independently predicted a ≥50% platelet decrease. HIT was not diagnosed in any patients. Conclusion Platelet nadir likely occurs approximately 4 days after injury and recovers relatively quickly thereafter. More studies are needed to evaluate the magnitude of effect on thrombocytopenia by factors beyond trauma.