Miracle-dz/UniFAR-FTUs huggingface dataset:
Exploring the Documentation of Delirium in Patients After Cardiac Surgery

Delirium is a common disorder for patients after cardiac surgery. Its manifestation and care can be examined through EHRs. The aim of this retrospective, comparative, and descriptive patient record study was to describe the documentation of delirium symptoms in the EHRs of patients who have undergone cardiac surgery and to explore how the documentation evolved between two periods (2005-2009 and 2015-2020). Randomly selected care episodes were annotated with a template, including delirium symptoms, treatment methods, and adverse events. The patients were then manually classified into two groups: nondelirious (n = 257) and possibly delirious (n = 172). The data were analyzed quantitatively and descriptively. According to the data, the documentation of symptoms such as disorientation, memory problems, motoric behavior, and disorganized thinking improved between periods. Yet, the key symptoms of delirium, inattention, and awareness were seldom documented. The professionals did not systematically document the possibility of delirium. Particularly, the way nurses recorded structural information did not facilitate an overall understanding of a patient's condition with respect to delirium. Information about delirium or proposed care was seldom documented in the discharge summaries. Advanced machine learning techniques can augment instruments that facilitate early detection, care planning, and transferring information to follow-up care.
Three-Dimensional Printing Applications in Pediatric Spinal Surgery: A Systematic Review

Study Design Systematic Review Objective 3DP technology use has become increasingly more common in the field of medicine and is notable for its growing utility in spine surgery applications. Many studies have evaluated the use of pedicle screw placement guides and spine models in adult spine patients, but there is little evidence assessing its efficacy in pediatric spine patient populations. This systematic review identifies and evaluates the current applications and surgical outcomes of 3-Dimensional Printing (3DP) technology in pediatric spinal surgery. Methods A search of publications was conducted using literature databases and relevant keywords in concordance with PRISMA guidelines. Inclusion criteria consisted of original studies, and studies focusing on the use of 3DP technology in pediatric spinal surgery. Studies with a focus on adult populations, non-deformity surgery, animal subjects, systematic or literature reviews, editorials, or non-English studies were excluded from further analysis. Results After application of inclusion/exclusion criteria, we identified 25 studies with 3DP applications in pediatric spinal surgery. Overall, the studies found significantly improved screw placement accuracy using 3DP pedicle screw placement guides but did not identify significant differences in operative time or blood loss. All studies that utilized 3D spine models in preoperative planning found it helpful and noted an increased screw placement accuracy rate of 89.9%. Conclusions 3DP applications and techniques are currently used in pre-operative planning using pedicle screw drill guides and spine models to improve patient outcomes in pediatric spinal deformity patients.
Mechanical Thrombectomy for Large Ischemic Stroke

Background and Objectives There is growing evidence for endovascular thrombectomy (EVT) in patients with large ischemic core infarct and large vessel occlusion (LVO). The objective of this study was to compare the efficacy and safety of EVT vs medical management (MM) using a systematic review and meta-analysis of observational studies and randomized controlled trials (RCTs). Methods We searched the PubMed, Embase, Cochrane Library, and Web of Science databases to obtain articles related to mechanical thrombectomy for large ischemic core from inception until February 10, 2023. The primary outcome was independent ambulation (modified Rankin Scale [mRS] 0–3). Effect sizes were computed as risk ratio (RR) with random-effect or fixed-effect models. The quality of articles was evaluated through the Cochrane risk assessment tool and the Newcastle-Ottawa Scale. This study was registered in PROSPERO (CRD42023396232). Results A total of 5,395 articles were obtained through the search and articles that did not meet the inclusion criteria were excluded by review of the title, abstract, and full text. Finally, 3 RCTs and 10 cohort studies met the inclusion criteria. The RCT analysis showed that EVT improved the 90-day functional outcomes of patients with large ischemic core with high-quality evidence, including independent ambulation (mRS 0–3: RR 1.78, 95% CI 1.28–2.48, p < 0.001) and functional independence (mRS 0–2: RR 2.59, 95% CI 1.89–3.57, p < 0.001), but without significantly increasing the risk of symptomatic intracranial hemorrhage (sICH: RR 1.83, 95% CI 0.95–3.55, p = 0.07) or early mortality (RR 0.95, 95% CI 0.78–1.16, p = 0.61). Analysis of the cohort studies showed that EVT improved functional outcomes of patients without an increase in the incidence in sICH. Discussion This systematic review and meta-analysis indicates that in patients with LVO stroke with a large ischemic core, EVT was associated with improved functional outcomes over MM without increasing sICH risk. The results of ongoing RCTs may provide further insight in this patient population.
NgR1 binding to reovirus reveals an unusual bivalent interaction and a new viral attachment protein

Significance Neuronal plasticity is an essential process in central nervous system (CNS) development and is coordinated in part by a key scaffold protein called NgR1. NgR1 also functions as a receptor for reovirus, a CNS-tropic virus capable of causing encephalitis in young mammals. Despite the important role of NgR1 in brain homeostasis, structural information guiding an understanding of NgR1 interactions with its ligands is lacking. Here, we describe in molecular detail how NgR1 uses its predicted key scaffolding surface to bind reovirus, which revealed a noncanonical viral ligand for this pathogen. These studies highlight how viruses employ multiple capsid components to engage host receptors and often target receptor surfaces required for interaction with host proteins with essential, conserved functions.
A Mildly Acidic Environment Alters Pseudomonas aeruginosa Virulence and Causes Remodeling of the Bacterial Surface

P. aeruginosa encounters environments with acidic pH when establishing infections in hosts. The bacterium develops an altered phenotype to tolerate a moderate decrease in the environmental pH. ABSTRACT Pseudomonas aeruginosa is a versatile pathogen that resists environmental stress, such as suboptimal pH. As a result of exposure to environmental stress, P. aeruginosa shows an altered virulence-related phenotype. This study investigated the modifications that P. aeruginosa undertakes at a mildly low pH (pH 5.0) compared with the bacteria grown in a neutral medium (pH 7.2). Results indicated that in a mildly acidic environment, expression of two-component system genes (phoP/phoQ and pmrA/pmrB), lipid A remodeling genes such as arnT and pagP and virulence genes, i.e., pqsE and rhlA, were induced. Moreover, lipid A of the bacteria grown at a mildly low pH is modified by adding 4-amino-arabinose (l-Ara4N). Additionally, the production of virulence factors such as rhamnolipid, alginate, and membrane vesicles is significantly higher in a mildly low-pH environment than in a neutral medium. Interestingly, at a mildly low pH, P. aeruginosa produces a thicker biofilm with higher biofilm biomass. Furthermore, studies on inner membrane viscosity and permeability showed that a mildly low pH causes a decrease in the inner membrane permeability and increases its viscosity. Besides, despite the importance of PhoP, PhoQ, PmrA, and PmrB in Gram-negative bacteria for responding to low pH stress, we observed that the absence of each of these two-component systems does not meaningfully impact the remodeling of the P. aeruginosa envelope. Given that P. aeruginosa is likely to encounter mildly acidic environments during infection in its host, the alterations that the bacterium undertakes under such conditions must be considered in designing antibacterial strategies against P. aeruginosa. IMPORTANCE P. aeruginosa encounters environments with acidic pH when establishing infections in hosts. The bacterium develops an altered phenotype to tolerate a moderate decrease in the environmental pH. At the level of the bacterial envelope, modified lipid A composition and a reduction of the bacterial inner membrane permeability and fluidity are among the changes P. aeruginosa undergoes at a mildly low pH. Also, the bacterium is more likely to form biofilm in a mildly acidic environment. Overall, these alterations in the P. aeruginosa phenotype put obstacles in the way of antibacterial activities. Thus, considering physiological changes in the bacterium at low pH helps design and implement antimicrobial approaches against this hostile microorganism.
Approaching the Intrinsic Properties of Moiré Structures Using Atomic Force Microscopy Ironing

Stacking monolayers of transition metal dichalcogenides (TMDs) has led to the discovery of a plethora of new exotic phenomena, resulting from moiré pattern formation. Due to the atomic thickness and high surface-to-volume ratio of heterostructures, the interfaces play a crucial role. Fluctuations in the interlayer distance affect interlayer coupling and moiré effects. Therefore, to access the intrinsic properties of the TMD stack, it is essential to obtain a clean and uniform interface between the layers. Here, we show that this is achieved by ironing with the tip of an atomic force microscope. This post-stacking procedure dramatically improves the homogeneity of the interfaces, which is reflected in the optical response of the interlayer exciton. We demonstrate that ironing improves the layer coupling, enhancing moiré effects and reducing disorder. This is crucial for the investigation of TMD heterostructure physics, which currently suffers from low reproducibility.
Analysis of Nuclei Detection with Stain Normalization in Histopathology Images

This paper proposes a unique detection technique to identify nuclei from microscopy images of breast histopathology slides. The method involves stain normalization, color decomposition and hysteresis thresholding. A comparative analysis of different pre-processed images on nuclei detection reveals an accuracy of 97% for Blue Ratio (BR) images. The technique uses three color channels for accurate detection of nuclei. An analysis of two stain normalization procedure is also presented.
William George Hill. 7 August 1940—17 December 2021

William (Bill) Hill was an internationally acclaimed statistical, population and quantitative geneticist. His work was inspired by practical problems in animal breeding, but is widely applicable to evolutionary biology and human genetics. Bill's work focused on the joint effects of linkage, mutation and genetic architecture in finite populations. He showed that linked loci under selection can interfere with each other, reducing the rate of response to selection. He derived a widely used metric for linkage disequilibrium and showed that there is likely to be substantial linkage disequilibrium between closely linked variants in finite populations. He also showed that the sampling variance of linkage disequilibrium is very large, hampering its use in estimating effective population size or recombination rates. Bill derived sampling variances for inbreeding and realized relatedness between individuals with the same expected degree of relatedness. He raised awareness about the importance of new mutations for quantitative genetic variation and the response to artificial selection, and developed models for the maintenance of quantitative genetic variation by a balance between mutation and stabilizing selection. His experimental designs for estimating heritability and conducting artificial selection experiments have been widely adopted, and were utilized in his own long-term mouse selection experiments. Bill influenced animal breeding directly through consultancies with breeding companies, and his influence on quantitative genetics continues today via his numerous mentees.
Upper beak depression instead of elevation dominates cranial kinesis in woodpeckers

The value of birds’ ability to move the upper beak relative to the braincase has been shown in vital tasks like feeding and singing. In woodpeckers, such cranial kinesis has been thought to hinder pecking as delivering forceful blows calls for a head functioning as a rigid unit. Here, we tested whether cranial kinesis is constrained in woodpeckers by comparing upper beak rotation during their daily activities such as food handling, calling and gaping with those from closely related species that also have a largely insectivorous diet but do not peck at wood. Both woodpeckers and non-woodpecker insectivores displayed upper beak rotations of up to 8 degrees. However, the direction of upper beak rotation differed significantly between the two groups, with woodpeckers displaying primarily depressions and non-woodpeckers displaying elevations. The divergent upper beak rotation of woodpeckers may be caused either by anatomical modifications to the craniofacial hinge that reduce elevation, by the caudal orientation of the mandible depressor muscle forcing beak depressions, or by both. Our results suggest that pecking does not result in plain rigidification at the upper beak's basis of woodpeckers, but it nevertheless significantly influences the way cranial kinesis is manifested.
Validity of Weekly and Monthly Perceived Exertion in Runners

Abstract The development of the rating of perceived exertion (RPE) enables the easy assessment of runners’ training strain as well as training load (TL). However, the long-term and retrospective validity of TL assessment using RPE scales still needs further investigation. Therefore, this study examined the validity of weekly and monthly ratings of perceived exertion (W-RPE, M-RPE) in assessing TL in runners. Healthy adult runners (n=53) rated perceived exertion using the modified category-ratio 10 (CR-10) scale for each week of a four-week period, as well as for the month, considering the four-week period. CR-10 for the week and the month were multiplied by the total training time of the week and month, respectively, to assess the W-RPE and M-RPE. Training impulse (TRIMP) was used as the criterion measure. The results indicated that the W-RPE and M-RPE may be used for monitoring TL during prolonged periods, presenting a very large correlations with the criterion measure.
Domain-invariant icing detection on wind turbine rotor blades with generative artificial intelligence for deep transfer learning

Abstract Wind energy’s ability to liberate the world from conventional sources of energy relies on lowering the significant costs associated with the maintenance of wind turbines. Since icing events on turbine rotor blades are a leading cause of operational failures, identifying icing in advance is critical. Some recent studies have utilized deep learning (DL) techniques to predict icing events with high accuracy by leveraging rotor blade images, but these studies only focus on specific wind parks and fail to generalize to unseen scenarios (e.g., new rotor blade designs). In this paper, we aim to facilitate ice prediction on the face of lack of ice images in new wind parks. We propose the utilization of synthetic data augmentation via a generative artificial intelligence technique—the neural style transfer algorithm to improve the generalization of existing ice prediction models. We also compare the proposed technique with the CycleGAN as a baseline. We show that training standalone DL models with augmented data that captures domain-invariant icing characteristics can help improve predictive performance across multiple wind parks. Through efficient identification of icing, this study can support preventive maintenance of wind energy sources by making them more reliable toward tackling climate change.
Loop Rerolling for Hardware Decompilation

We introduce the new problem of hardware decompilation. Analogous to software decompilation, hardware decompilation is about analyzing a low-level artifact—in this case a netlist, i.e., a graph of wires and logical gates representing a digital circuit—in order to recover higher-level programming abstractions, and using those abstractions to generate code written in a hardware description language (HDL). The overall problem of hardware decompilation requires a number of pieces. In this paper we focus on one specific piece of the puzzle: a technique we call hardware loop rerolling. Hardware loop rerolling leverages clone detection and program synthesis techniques to identify repeated logic in netlists (such as would be synthesized from loops in the original HDL code) and reroll them into syntactic loops in the recovered HDL code. We evaluate hardware loop rerolling for hardware decompilation over a set of hardware design benchmarks written in the PyRTL HDL and industry standard SystemVerilog. Our implementation identifies and rerolls loops in 52 out of 53 of the netlists in our benchmark suite, and we show three examples of how hardware decompilation can provide concrete benefits: transpilation between HDLs, faster simulation times over netlists (with mean speedup of 6x), and artifact compaction (39% smaller on average).
Don’t Look UB: Exposing Sanitizer-Eliding Compiler Optimizations

Sanitizers are widely used compiler features that detect undefined behavior and resulting vulnerabilities by injecting runtime checks into programs. For better performance, sanitizers are often used in conjunction with optimization passes. But doing so combines two compiler features with conflicting objectives. While sanitizers want to expose undefined behavior, optimizers often exploit these same properties for performance. In this paper, we show that this clash can have serious consequences: optimizations can remove sanitizer failures, thereby hiding the presence of bugs or even introducing new ones. We present LookUB, a differential-testing based framework for finding optimizer transformations that elide sanitizer failures. We used our method to find 17 such sanitizer-eliding optimizations in Clang. Next, we used static analysis and fuzzing to search for bugs in open-source projects that were previously hidden due to sanitizer-eliding optimizations. This led us to discover 20 new bugs in Linux Containers, libmpeg2, NTFS-3G, and WINE. Finally, we present an effective mitigation strategy based on a customization of the Clang optimizer with an overhead increase of 4%.
Performal: Formal Verification of Latency Properties for Distributed Systems

Understanding and debugging the performance of distributed systems is a notoriously hard task, but a critical one. Traditional techniques like logging, tracing, and benchmarking represent a best-effort way to find performance bugs, but they either require a full deployment to be effective or can only find bugs after they manifest. Even with such techniques in place, real deployments often exhibit performance bugs that cause unwanted behavior. In this paper, we present Performal, a novel methodology that leverages the recent advances in formal verification to provide rigorous latency guarantees for real, complex distributed systems. The task is not an easy one: it requires carefully decoupling the formal proofs from the execution environment, formally defining latency properties, and proving them on real, distributed implementations. We used Performal to prove rigorous upper bounds for the latency of three applications: a distributed lock, ZooKeeper and a MultiPaxos-based State Machine Replication system. Our experimental evaluation shows that these bounds are a good proxy for the behavior of the deployed system and can be used to identify performance bugs in real-world systems.
Interactive Privacy Management: Toward Enhancing Privacy Awareness and Control in the Internet of Things

The balance between protecting user privacy while providing cost-effective devices that are functional and usable is a key challenge in the burgeoning Internet of Things (IoT). In traditional desktop and mobile contexts, the primary user interface is a screen; however, in IoT devices, screens are rare or very small, invalidating many existing approaches to protecting user privacy. Privacy visualizations are a common approach for assisting users in understanding the privacy implications of web and mobile services. To gain a thorough understanding of IoT privacy, we examine existing web, mobile, and IoT visualization approaches. Following that, we define five major privacy factors in the IoT context: type, usage, storage, retention period, and access. We then describe notification methods used in various contexts as reported in the literature. We aim to highlight key approaches that developers and researchers can use for creating effective IoT privacy notices that improve user privacy management (awareness and control). Using a toolkit, a use case scenario, and two examples from the literature, we demonstrate how privacy visualization approaches can be supported in practice.
Flexible and Effective Object Tiering for Heterogeneous Memory Systems

Computing platforms that package multiple types of memory, each with their own performance characteristics, are quickly becoming mainstream. To operate efficiently, heterogeneous memory architectures require new data management solutions that are able to match the needs of each application with an appropriate type of memory. As the primary generators of memory usage, applications create a great deal of information that can be useful for guiding memory tiering, but the community still lacks tools to collect, organize, and leverage this information effectively. To address this gap, this work introduces a novel software framework that collects and analyzes object-level information to guide memory tiering. Using this framework, this study evaluates and compares the impact of a variety of data tiering choices, including how the system prioritizes objects for faster memory as well as the frequency and timing of migration events. The results, collected on a modern Intel platform with conventional DRAM as well as non-volatile RAM, show that guiding data tiering with object-level information can enable significant performance and efficiency benefits compared to standard hardware- and software-directed data tiering strategies.
Collecting Cyclic Garbage across Foreign Function Interfaces: Who Takes the Last Piece of Cake?

A growing number of libraries written in managed languages, such as Python and JavaScript, are bringing about new demand for a foreign language interface (FFI) between two managed languages. Such an FFI allows a host-language program to seamlessly call a library function written in a foreign language and exchange objects. It is often implemented by a user-level library but such implementation cannot reclaim cyclic garbage, or a group of objects with circular references, across the language boundary. This paper proposes Refgraph GC, which enables FFI implementation that can reclaim cyclic garbage. Refgraph GC coordinates the garbage collectors of two languages and it needs to modify the managed runtime of one language only. It does not modify that of the other language. This paper discusses the soundness and completeness of the proposed algorithm and also shows the results of the experiments with our implementation of FFI with Refgraph GC. This FFI allows a Ruby program to access a JavaScript library.