bluuebunny/crossref_metadata_2025 huggingface dataset:
Motivation and goal-pursuit for injury prevention training in amateur football coaches: a cross-sectional study using the Health Action Process Approach
Authors: Lindblom Hanna , Hägglund Martin
Published: September 2023

Background

Adoption of injury prevention exercise programmes (IPEPs) in team sports is contingent on behaviour change among coaches. The aim was to study motivation and goal-pursuit in IPEP use among coaches of amateur football players.

Methods

A cross-sectional study using web-based questionnaires was administered to coaches in one Swedish regional football district. The study was carried out one season after dissemination of the IPEPKnee Control+. The questionnaire was based on the Health Action Process Approach and covered perceptions and beliefs about usingKnee Control+. Questions were rated on 1–7 Likert scales.

Results

440 coaches participated (response rate 32%). Coaches were neutral about injury risks (median 4–5) and knowledge about preventing injuries (median 5) but had positive outcome expectancies of preventive training (median 6). Coaches who had used an IPEP perceived they had more knowledge about preventing injuries than non-users (median 5 vs 4, small effect sized=0.43). Coaches who usedKnee Control+were positive about their practical ability to use it (median 6) and had high intention to prioritise continuous use (median 7). Highly adherent coaches to higher extent believed that specific training may prevent injuries and had plans for how to instruct the players and how to work around barriers compared with low adherent coaches.

Conclusion

Coaches need more knowledge and support on IPEP usage and how to structure training. Coaches who had adoptedKnee Control+had high belief in their abilities but may need constructive plans on how to use the programme and to overcome barriers.
Mechanical disorders of the cervicocerebral circulation in children and young adults
Authors: Baranoski Jacob F , White Andrew C , Chung Charlotte Y , Catapano Joshua S , De Oliveira Sillero Rafael , Hui Ferdinand K , Huisman Thierry AGM , Lawton Michael T , Abruzzo Todd
Published: September 2023

Mechanical disorders of the cervicocerebral circulation (MDCC) are conditions in which neurological symptoms result from a disturbance of cerebral blood flow attributable to external mechanical forces exerted on extracranial blood vessels by adjacent musculoskeletal structures during head movement that is presumably within a physiological range. The disease spectrum includes bow hunter’s syndrome, carotid-type Eagle syndrome, and various dynamic venous compression syndromes. These conditions have distinct phenotypes in children which differ from those expressed in older adults. In contemporary practice, recognition and diagnostic evaluation is the domain of the neuroendovascular specialist. The diagnostic evaluation of MDCC involves significant technical nuance that can be critical to directing appropriate management, particularly in children. This report aims to provide a comprehensive overview of the pathophysiology, anatomical patterns, diagnosis, and treatment for the full spectrum of MDCC that is commonly encountered in clinical practice.
Turning good intentions into good outcomes: ethical dilemmas at a student-run clinic and a rubric for reflective action
Authors: Peoples Nicholas , Gebert J Thomas , Clark Dana
Published: September 2023

Student-run clinics represent a unique medical education and healthcare delivery model powered largely by good intentions. These good intentions may produce questionable results, however, when juxtaposed with intense academic pressure to fill one’s curriculum vitae with personal achievements, leadership roles and peer-reviewed publications. It becomes a legitimate ethical question whether student-run clinics consistently and materially enrich the care of underserved communities, or merely inspire a litany of rushed, short-term and low-quality projects that sidestep patient welfare or even cause brazen harm. As co-directors of HOMES Clinic, a student-managed clinic which offers free health and social services to people experiencing housing insecurity, we routinely encounter such well-intentioned but ethically questionable proposals. Here, we present four short case studies that dissect apart some of these common yet suspect assumptions underpinning student-run clinics. We then conclude with a rubric for reflective, calibrated action.
Atopic and non-atopic effects of fish oil supplementation during pregnancy
Authors: Bisgaard Hans , Mikkelsen Marianne , Rasmussen Morten Arendt , Sevelsted Astrid , Schoos Ann-Marie Malby , Brustad Nicklas , Eliasen Anders U , Thorsen Jonathan , Chawes Bo , Gürdeniz Gözde , Morin Andreanne , Stark Ken , Stokholm Jakob , Ober Carole , Pedersen Casper Emil Tingskov , Bønnelykke Klaus
Published: September 2023

Background

We recently conducted a double-blinded randomised controlled trial showing that fish-oil supplementation during pregnancy reduced the risk of persistent wheeze or asthma in the child by 30%. Here, we explore the mechanisms of the intervention.

Methods

736 pregnant women were given either placebo or n-3 long-chain polyunsaturated fatty acids (LCPUFAs) in the third trimester in a randomised controlled trial. Deep clinical follow-up of the 695 children in the trial was done at 12 visits until age 6 years, including assessment of genotype at the fatty acid desaturase (FADS) locus, plasma fatty acids, airway DNA methylation, gene expression, microbiome and metabolomics.

Results

Supplementation with n-3 LCPUFA reduced the overall risk of non-atopic asthma by 73% at age 6 (relative risk (RR) 0.27 (95% CI 0.06 to 0.85), p=0.042). In contrast, there was no overall effect on asthma with atopic traits (RR 1.42 (95% CI 0.63 to 3.38), p=0.40), but this was significantly modified by maternal FADS genotype and LCPUFA blood levels (interaction p<0.05), and supplementation did reduce the risk of atopic asthma in the subgroup of mothers with FADS risk variants and/or low blood levels of n-3 LCPUFA before the intervention (RR 0.31 (95% CI 0.11 to 0.75), p=0.016). Furthermore, n-3 LCPUFA significantly reduced the number of infections (croup, gastroenteritis, tonsillitis, otitis media and pneumonia) by 16% (incidence rate ratio 0.84 (95% CI 0.74 to 0.96), p=0.009).

Conclusions

n-3 LCPUFA supplementation in pregnancy showed protective effects on non-atopic asthma and infections. Protective effects on atopic asthma depended on maternal FADS genotype and n-3 LCPUFA levels. This indicates that the fatty acid pathway is involved in multiple mechanisms affecting the risk of asthma subtypes and infections.

Trial registration number

NCT00798226.
Comparison of known spawner abundance from fence counts to visual counts for simplified spawner estimation methods
Authors: Askey Paul J. , Ward Hillary G.M. , Weir Tyler , King Kristen
Published: September 2023

Many salmon species are monitored by visual counts of spawners in streams; however, there are few data sets where abundance is known and compared to estimates derived from visual counts. We used spawner fences to obtain known kokanee ( Oncorhynchus nerka) spawner abundance (14 stream-years) on streams that are monitored with annual visual surveys (7 to 9 counts per year) and incorporated similar published data from pink salmon ( Oncorhynchus gorbuscha) (11 stream-years). We investigated the performance of several simplified expansion factor estimation methods with survey life and observer efficiency as unknown nuisance parameters. All visual indices of kokanee and pink salmon spawners from live ground counts were highly correlated to abundance from fence counts ( r2 ≥ 0.96 and 0.89, respectively). Application of cross-validation on out-of-sample data for both species showed that mean% error could range from 13% to 53% on a previously unsampled stream depending on the species, counting method, and visual index used. Predictive performance metrics were less sensitive to counting frequency than observer efficiency and associated variability, which was influenced by the counting method (aerial versus ground surveys).
Keep in Balance: Runtime-reconfigurable Intermittent Deep Inference
Authors: Yen Chih-Hsuan , Mendis Hashan Roshantha , Kuo Tei-Wei , Hsiu Pi-Cheng
Published: September 2023

Intermittent deep neural network (DNN) inference is a promising technique to enable intelligent applications on tiny devices powered by ambient energy sources. Nonetheless, intermittent execution presents inherent challenges, primarily involving accumulating progress across power cycles and having to refetch volatile data lost due to power loss in each power cycle. Existing approaches typically optimize the inference configuration to maximize data reuse. However, we observe that such a fixed configuration may be significantly inefficient due to the fluctuating balance point between data reuse and data refetch caused by the dynamic nature of ambient energy.

This work proposes
DynBal
, an approach to dynamically reconfigure the inference engine at runtime. DynBal is realized as a middleware plugin that improves inference performance by exploring the interplay between data reuse and data refetch to maintain their balance with respect to the changing level of intermittency. An indirect metric is developed to easily evaluate an inference configuration considering the variability in intermittency, and a lightweight reconfiguration algorithm is employed to efficiently optimize the configuration at runtime. We evaluate the improvement brought by integrating DynBal into a recent intermittent inference approach that uses a fixed configuration. Evaluations were conducted on a Texas Instruments device with various network models and under varied intermittent power strengths. Our experimental results demonstrate that DynBal can speed up intermittent inference by 3.26 times, achieving a greater improvement for a large network under high intermittency and a large gap between memory and computation performance.
FedHIL: Heterogeneity Resilient Federated Learning for Robust Indoor Localization with Mobile Devices
Authors: Gufran Danish , Pasricha Sudeep
Published: September 2023

Indoor localization plays a vital role in applications such as emergency response, warehouse management, and augmented reality experiences. By deploying machine learning (ML) based indoor localization frameworks on their mobile devices, users can localize themselves in a variety of indoor and subterranean environments. However, achieving accurate indoor localization can be challenging due to heterogeneity in the hardware and software stacks of mobile devices, which can result in inconsistent and inaccurate location estimates. Traditional ML models also heavily rely on initial training data, making them vulnerable to degradation in performance with dynamic changes across indoor environments. To address the challenges due to device heterogeneity and lack of adaptivity, we propose a novel embedded ML framework called
FedHIL
. Our framework combines indoor localization and federated learning (FL) to improve indoor localization accuracy in device-heterogeneous environments while also preserving user data privacy.
FedHIL
integrates a domain-specific selective weight adjustment approach to preserve the ML model's performance for indoor localization during FL, even in the presence of extremely noisy data. Experimental evaluations in diverse real-world indoor environments and with heterogeneous mobile devices show that
FedHIL
outperforms state-of-the-art FL and non-FL indoor localization frameworks.
FedHIL
is able to achieve 1.62 × better localization accuracy on average than the best performing FL-based indoor localization framework from prior work.
LaDy: Enabling

L

ocality-

a

ware

D

eduplication Technolog

y

on Shingled Magnetic Recording Drives
Authors: Chang Jung-Hsiu , Chang Tzu-Yu , Shih Yi-Chao , Chen Tseng-Yi
Published: September 2023

The continuous increase in data volume has led to the adoption of shingled-magnetic recording (SMR) as the primary technology for modern storage drives. This technology offers high storage density and low unit cost but introduces significant performance overheads due to the read-update-write operation and garbage collection (GC) process. To reduce these overheads, data deduplication has been identified as an effective solution as it reduces the amount of written data to an SMR-based storage device. However, deduplication can result in poor data locality, leading to decreased read performance. To tackle this problem, this study proposes a data locality-aware deduplication technology, LaDy, that considers both the overheads of writing duplicate data and the impact on data locality to determine whether the duplicate data should be written. LaDy integrates with DiskSim, an open-source project, and modifies it to simulate an SMR-based drive. The experimental results demonstrate that LaDy can significantly reduce the response time in the best-case scenario by 87.3% compared with CAFTL on the SMR drive. LaDy achieves this by selectively writing duplicate data, which preserves data locality, resulting in improved read performance. The proposed solution provides an effective and efficient method for mitigating the performance overheads associated with data deduplication in SMR-based storage devices.
FSIMR: File-system-aware Data Management for Interlaced Magnetic Recording
Authors: Lien Yi-Han , Chen Yen-Ting , Chang Yuan-Hao , Liang Yu-Pei , Shih Wei-Kuan
Published: September 2023

Interlaced Magnetic Recording (IMR) is an emerging recording technology for hard-disk drives (HDDs) that provides larger storage capacity at a lower cost. By partially overlapping (interlacing) each bottom track with two adjacent top tracks, IMR-based HDDs successfully increase the data density while incurring some hardware write constraints. To update each bottom track, the data on two adjacent top tracks must be read and rewritten to avoid losing their valid data, resulting in additional overhead for performing read-modify-write (RMW) operations. Therefore, researchers have proposed various data management schemes to mitigate such overhead in recent years, aiming at improving the write performance. However, these designs have not taken into account the data characteristics of the file system, which is a crucial layer of operating systems for storing/retrieving data into/from HDDs. Consequently, the write performance improvement is limited due to the unawareness of spatial locality and hotness of data. This paper proposes a file-system-aware data management scheme called FSIMR to improve system write performance. Noticing that data of the same directory may have higher spatial locality and are mostly updated at the same time, FSIMR logically partitions the IMR-based HDD into fixed-sized zones; data belonging to the same directory will be arranged to one zone to reduce the time of seeking to-be-updated data (seek time). Furthermore, cold data within a zone are arranged to bottom tracks and updated in an out-of-place manner to eliminate RMW operations. Our experimental results show that the proposed FSIMR could reduce the seek time by up to 14% without introducing additional RMW operations, compared to existing designs.
Thermal Management for 3D-Stacked Systems via Unified Core-Memory Power Regulation
Authors: Shen Yixian , Schreuders Leo , Pathania Anuj , Pimentel Andy D.
Published: September 2023

3D-stacked processor-memory systems stack memory (DRAM banks) directly on top of logic (CPU cores) using chiplet-on-chiplet packaging technology to provide the next-level computing performance in embedded platforms. Stacking, however, severely increases the system’s power density without any accompanying increase in the heat dissipation capacity. Consequently, 3D-stacked processor-memory systems suffer more severe thermal issues than their non-stacked counterparts. Nevertheless, 3D-stacked processor-memory systems do inherit power (thermal) management knobs from their non-stacked predecessors - namely Dynamic Voltage and Frequency Scaling (DVFS) for cores and Low Power Mode (LPM) for memory banks. In the context of 3D-stacked processor-memory systems, DVFS and LPM are performance- and power-wise deeply intertwined. Their non-unified independent use on 3D-stacked processor-memory systems results in sub-optimal thermal management. The unified use of DVFS and LPM for thermal management for 3D-stacked processor-memory systems remains unexplored. The lack of implementation of LPM in thermal simulators for 3D-stacked processor-memory systems hinders real-world representative evaluation for a unified approach.

We extend the state-of-the-art interval thermal simulator for 3D-stacked processor-memory systems
CoMeT
with an LPM power management knob for memory banks. We also propose a learning-based thermal management technique for 3D-stacked processor-memory systems that employ DVFS and LPM in a unified manner. Detailed interval thermal simulations with the extended
CoMeT
framework show a 10.15% average response time improvement with the
PARSEC
and
SPLASH-2
benchmark suites, along with widely-used Deep Neural Network (DNN) workloads against a state-of-the-art thermal management technique for 2.5D processor-memory systems (ported directly to 3D-stacked processor-memory systems) that also proposes unified use of DVFS and LPM.
Verified Compilation of Synchronous Dataflow with State Machines
Authors: Bourke Timothy , Pesin Basile , Pouzet Marc
Published: September 2023

Safety-critical embedded software is routinely programmed in block-diagram languages. Recent work in the Vélus project specifies such a language and its compiler in the Coq proof assistant. It builds on the CompCert verified C compiler to give an end-to-end proof linking the dataflow semantics of source programs to traces of the generated assembly code. We extend this work with switched blocks, shared variables, reset blocks, and state machines; define a relational semantics to integrate these block- and mode-based constructions into the existing stream-based model; adapt the standard source-to-source rewriting scheme to compile the new constructions; and reestablish the correctness theorem.
Proactive Stripe Reconstruction to Improve Cache Use Efficiency of SSD-Based RAID Systems
Authors: Sha Zhibing , Wu Jiaojiao , Li Jun , Gerofi Balazs , Cai Zhigang , Liao Jianwei
Published: September 2023

Solid-State Drives (SSDs) exhibit different failure characteristics compared to conventional hard disk drives. In particular, the Bit Error Rate (BER) of an SSD increases as it bears more writes. Then, Parity-based Redundant Array of Inexpensive Disks (RAID) arrays composed from SSDs are introduced to address correlated failures. In the RAID-5 implementation, specifically, the process of parity generation (or update) associating with a data stripe, consists of read and write operations to the SSDs. Whenever a new update request comes to the RAID system, the related parity must be also updated and flushed onto the RAID component of SSD. Such frequent parity updates result in poor RAID performance and shorten the life-time of the SSDs. Consequently, a DRAM cache is commonly equipped accompanying with the RAID controller, called the parity cache, and used to buffer the parity chunks that are most frequently updated data, for boosting I/O performance.

To better improve the use efficiency of the parity cache, this paper proposes a stripe reconstruction approach to minimize the number of parity updates on SSDs, thus boosting I/O performance of the SSD RAID system. When the currently updated stripe has both cold and hot updated data chunks, it will proactively carry out stripe reconstruction if we can find another matched stripe that also includes cold and hot update data chunks on the complementary RAID components. In the reconstruction process, we first group the cold data chunks of two matched stripes, to build a new stripe and flush the parity chunk on the RAID component. After that, the hot data chunks are organized as a new stripe as well, and its parity chunk is buffered in the parity cache. This results in better cache use efficiency, as it can reduce the number of parity updates on RAID components of SSDs, as well as proactively free up cache space for quickly absorbing subsequent write requests. In addition, the proposed method adjusts the target SSD of write requests based on stripe reconstructions through considering the I/O workload balance of all SSDs. Experimental results show that our proposal can reduce the number of parity chunk updates in SSDs by
2.3%
and overall I/O latency by
12.2%
on average, compared to state-of-the-art parity cache management techniques.
Predictable GPU Wavefront Splitting for Safety-Critical Systems
Authors: Klashtorny Artem , Wu Zhuanhao , Kaushik Anirudh Mohan , Patel Hiren
Published: September 2023

We present a predictable wavefront splitting (PWS) technique for graphics processing units (GPUs). PWS improves the performance of GPU applications by reducing the impact of branch divergence while ensuring that worst-case execution time (WCET) estimates can be computed. This makes PWS an appropriate technique to use in safety-critical applications, such as autonomous driving systems, avionics, and space, that require strict temporal guarantees. In developing PWS on an AMD-based GPU, we propose microarchitectural enhancements to the GPU, and a compiler pass that eliminates branch serializations to reduce the WCET of a wavefront. Our analysis of PWS exhibits a performance improvement of 11% over existing architectures with a lower WCET than prior works in wavefront splitting.
Kryptonite: Worst-Case Program Interference Estimation on Multi-Core Embedded Systems
Authors: Singh Nikhilesh , Renganathan Karthikeyan , Rebeiro Chester , Jose Jithin , Mader Ralph
Published: September 2023

Due to the low costs and energy needed, cyber-physical systems are adopting multi-core processors for their embedded computing requirements. In order to guarantee safety when the application has real-time constraints, a critical requirement is to estimate the worst-case interference from other executing programs. However, the complexity of multi-core hardware inhibits precisely determining the Worst-Case Program Interference. Existing solutions are either prone to overestimate the interference or are not scalable to different hardware sizes and designs.

In this paper we present 
Kryptonite
, an automated framework to synthesize Worst-Case Program Interference (WCPI) environments for multi-core systems. Fundamental to 
Kryptonite
is a set of tiny hardware-specific code gadgets that are crafted to maximize interference locally. The gadgets are arranged using a greedy approach and then molded using a Reinforcement Learning algorithm to create the WCPI environment. We demonstrate 
Kryptonite
on the automotive grade Infineon AURIX TC399 processor with a wide range of programs that includes a commercial real-time automotive application. We show that, while being easily scalable and tunable, 
Kryptonite
creates WCPI environments
increasing the runtime by up to 58% for benchmark applications and 26% for the automotive application.
Towards Building Verifiable CPS using Lingua Franca
Authors: Lin Shaokai , Manerkar Yatin A. , Lohstroh Marten , Polgreen Elizabeth , Yu Sheng-Jung , Jerad Chadlia , Lee Edward A. , Seshia Sanjit A.
Published: September 2023

Formal verification of cyber-physical systems (CPS) is challenging because it has to consider real-time and concurrency aspects that are often absent in ordinary software. Moreover, the software in CPS is often complex and low-level, making it hard to assure that a formal model of the system used for verification is a faithful representation of the actual implementation, which can undermine the value of a verification result. To address this problem, we propose a methodology for building verifiable CPS based on the principle that a formal model of the software can be derived
automatically
from its implementation. Our approach requires that the system implementation is specified in
Lingua Franca
(LF), a polyglot coordination language tailored for real-time, concurrent CPS, which we made amenable to the specification of safety properties via annotations in the code. The program structure and the deterministic semantics of LF enable automatic construction of formal axiomatic models directly from LF programs. The generated models are automatically checked using Bounded Model Checking (BMC) by the verification engine
Uclid5
using the
Z3
SMT solver. The proposed technique enables checking a well-defined fragment of Safety Metric Temporal Logic (Safety MTL) formulas. To ensure the completeness of BMC, we present a method to derive an upper bound on the completeness threshold of an axiomatic model based on the semantics of LF. We implement our approach in the LF V
erifier
and evaluate it using a benchmark suite with 22 programs sampled from real-life applications and benchmarks for Erlang, Lustre, actor-oriented languages, and RTOSes. The LF V
erifier
correctly checks 21 out of 22 programs automatically.
DASS: Differentiable Architecture Search for Sparse Neural Networks
Authors: Mousavi Hamid , Loni Mohammad , Alibeigi Mina , Daneshtalab Masoud
Published: September 2023

The deployment of Deep Neural Networks (DNNs) on edge devices is hindered by the substantial gap between performance requirements and available computational power. While recent research has made significant strides in developing pruning methods to build a sparse network for reducing the computing overhead of DNNs, there remains considerable accuracy loss, especially at high pruning ratios. We find that the architectures designed for dense networks by differentiable architecture search methods are ineffective when pruning mechanisms are applied to them. The main reason is that the current methods do not support sparse architectures in their search space and use a search objective that is made for dense networks and does not focus on sparsity.

This paper proposes a new method to search for sparsity-friendly neural architectures. It is done by adding two new sparse operations to the search space and modifying the search objective. We propose two novel parametric
SparseConv
and
SparseLinear
operations in order to expand the search space to include sparse operations. In particular, these operations make a flexible search space due to using sparse parametric versions of linear and convolution operations. The proposed search objective lets us train the architecture based on the sparsity of the search space operations. Quantitative analyses demonstrate that architectures found through DASS outperform those used in the state-of-the-art sparse networks on the CIFAR-10 and ImageNet datasets. In terms of performance and hardware effectiveness, DASS increases the accuracy of the sparse version of MobileNet-v2 from 73.44% to 81.35% (+7.91% improvement) with a 3.87× faster inference time.
Mining Hyperproperties using Temporal Logics
Authors: Bartocci Ezio , Mateis Cristinel , Nesterini Eleonora , Ničković Dejan
Published: September 2023

Formal specifications are essential to express precisely systems, but they are often difficult to define or unavailable. Specification mining aims to automatically infer specifications from system executions. The existing literature mainly focuses on learning properties defined on single system executions. However, many system characteristics, such as security policies and robustness, require relating two or more executions, and hence cannot be captured by properties. Hyperproperties address this limitation by allowing simultaneous reasoning about multiple executions with quantification over system traces.

In this paper, we propose an effective approach for mining Hyper Signal Temporal Logic (HyperSTL) specifications. Our approach is based on the syntax-guided synthesis framework and allows users to control the amount of prior knowledge embedded in the mining procedure. To the best of our knowledge, this is the first mining method for hyperproperties that does not require a pre-defined template as input and allows for quantifier alternation. We implemented our approach and demonstrated its applicability and versatility in several case studies where we showed that we can use the same method to mine specifications both with and without templates, but also to infer subsets of HyperSTL, including STL, HyperLTL, LTL and non-temporal specifications.
CrossTalk
: Making Low-Latency Fault Tolerance Cheap by Exploiting Redundant Networks
Authors: Loveless Andrew , Phan Linh Thi Xuan , Erickson Lisa , Dreslinski Ronald , Kasikci Baris
Published: September 2023

Real-time embedded systems perform many important functions in the modern world. A standard way to tolerate faults in these systems is with Byzantine fault-tolerant (BFT) state machine replication (SMR), in which multiple replicas execute the same software and their outputs are compared by the actuators. Unfortunately, traditional BFT SMR protocols are
slow
, requiring replicas to exchange sensor data back and forth over multiple rounds in order to reach agreement before each execution. The state of the art in reducing the latency of BFT SMR is
eager execution
, in which replicas execute on data from different sensors simultaneously on different processor cores. However, this technique results in 3–5× higher computation overheads compared to traditional BFT SMR systems, significantly limiting schedulability.

We present
CrossTalk
, a new BFT SMR protocol that leverages the prevalence of redundant switched networks in embedded systems to reduce latency without added computation. The key idea is to use specific algorithms to move messages between redundant network planes (which many systems already possess) as the messages travel from the sensors to the replicas. As a result,
CrossTalk
can ensure agreement
automatically
in the network, avoiding the need for any communication between replicas. Our evaluation shows that
CrossTalk
improves schedulability by 2.13–4.24× over the state of the art. Moreover, in a NASA simulation of a real spaceflight mission,
CrossTalk
tolerates more faults than the state of the art while using nearly 3× less processor time.
Attacking Shortest Paths by Cutting Edges
Authors: Miller Benjamin A. , Shafi Zohair , Ruml Wheeler , Vorobeychik Yevgeniy , Eliassi-Rad Tina , Alfeld Scott
Published: September 2023

Identifying shortest paths between nodes in a network is a common graph analysis problem that is important for many applications involving routing of resources. An adversary that can manipulate the graph structure could alter traffic patterns to gain some benefit (e.g., make more money by directing traffic to a toll road). This article presents theForce Path Cutproblem, in which an adversary removes edges from a graph to make a particular path the shortest between its terminal nodes. We prove that the optimization version of this problem is APX-hard but introducePATHATTACK, a polynomial-time approximation algorithm that guarantees a solution within a logarithmic factor of the optimal value. In addition, we introduce theForce Edge CutandForce Node Cutproblems, in which the adversary targets a particular edge or node, respectively, rather than an entire path. We derive a nonconvex optimization formulation for these problems and derive a heuristic algorithm that usesPATHATTACKas a subroutine. We demonstrate all of these algorithms on a diverse set of real and synthetic networks, illustrating where the proposed algorithms provide the greatest improvement over baseline methods.
Skeletal muscle-derived FSTL1 starting up angiogenesis by regulating endothelial junction via activating Src pathway can be upregulated by hydrogen sulfide
Authors: Li Meng-Yao , Gao Ru-Pan , Zhu Qi , Chen Ying , Tao Bei-Bei , Zhu Yi-Chun
Published: September 2023

The myocyte-derived paracrine protein FSTL1 acts on vascular endothelial cells and initiates the process of angiogenesis by opening the intercellular junction via activating Src kinase. H2S can significantly upregulate FSTL1 protein levels in skeletal muscles by increasing HuR expression.
Lactate signaling and fuel selection in rainbow trout: mobilization of energy reserves
Authors: Talarico Giancarlo G. M. , Thoral Elisa , Farhat Elie , Teulier Loïc , Mennigen Jan A. , Weber Jean-Michel
Published: September 2023

Lactate is now recognized as a regulator of fuel selection in mammals because it inhibits lipolysis by binding to the hydroxycarboxylic acid receptor 1 (HCAR1). The goals of this study were to quantify the effects of exogenous lactate on: 1) lipolytic rate or rate of appearance of glycerol in the circulation ( Ra glycerol) and hepatic glucose production ( Ra glucose), and 2) key tissue proteins involved in lactate signaling, glucose transport, glycolysis, gluconeogenesis, lipolysis, and β-oxidation in rainbow trout. Measurements of fuel mobilization kinetics show that lactate does not affect lipolysis as it does in mammals ( Ra glycerol remains at 7.3 ± 0.5 µmol·kg−1·min−1), but strongly reduces hepatic glucose production (16.4 ± 2.0 to 8.9 ± 1.2 µmol·kg−1·min−1). This reduction is likely induced by decreasing gluconeogenic flux through the inhibition of cytosolic phosphoenolpyruvate carboxykinase (Pck1, alternatively called Pepck1; 60% and 24% declines in gene expression and protein level, respectively). It is also caused by lactate substituting for glucose as a fuel in all tissues except white muscle that increases glut4a expression and has limited capacity for monocarboxylate transporter (Mct)-mediated lactate import. We conclude that lipolysis is not affected by hyperlactatemia because trout show no activation of autocrine Hcar1 signaling (gene expression of the receptor is unchanged or even repressed in red muscle). Lactate regulates fuel mobilization via Pck1-mediated suppression of gluconeogenesis and by replacing glucose as a fuel. This study highlights important functional differences in the Hcar1 signaling system between fish and mammals for the regulation of fuel selection.
Differential responses to artificial photoperiods of the rising and falling phases of human melatonin rhythm are consistent with a dual oscillator hypothesis
Authors: Hashimoto Satoko , Endo Takuro , Honma Sato , Yamanaka Yujiro , Honma Ken-Ichi
Published: September 2023

The present study demonstrated differential light responsiveness of the rising and falling phases of nocturnal melatonin secretion in human subjects exposed to artificial long (LD 16:8) and short days (LD 8:16) and suggested the involvement of different oscillators under these phases. The findings well mimicked the seasonality of the circadian rhythms in nature and consisted with the evening/morning dual oscillator hypothesis proposed originally for nocturnal rodents, providing a new concept for the human circadian system.
Rapid onset vasodilation during baroreceptor loading and unloading
Authors: Leach Olivia K. , Gifford Jayson R. , Mack Gary W.
Published: September 2023

Rapid onset vasodilation (ROV) was linearly related to the peak force of each single 1-s muscle contraction. In addition, ROV is reduced by baroreceptor unloading (LBNP: −10, −120, and −40 mmHg) and increased by baroreceptor loading (LBPP: +10 and +20 mmHg). Without accounting for peak force and the level of baroreceptor engagement makes comparison of ROV in subjects of differing muscle size or strength untenable.
The uterine secretory cycle: recurring physiology of endometrial outputs that setup the uterine luminal microenvironment
Authors: Schalich Kasey M. , Koganti Prasanthi P. , Castillo Juan M. , Reiff Olivia M. , Cheong Soon Hon , Selvaraj Vimal
Published: September 2023

This study unravels the recurring sequence of changes within the uterus that supports vital functions (sperm transit and development of preimplantation embryonic stages) during the reproductive cycle in female Ruminantia. These data present new systems knowledge in uterine reproductive physiology crucial for setting up in vitro biomimicry and artificial environments for assisted reproduction technologies for a range of mammalian species.
A Case of Visceral Leishmaniasis in a 4-Year-Old Child Living in Nonendemic Area Located in Suburbs of Dakar, Senegal
Authors: Ndiaye Magatte , Cissé Dienaba Fafa , Djigal Aicha , Sow Aminata , Lélo Souléye , Ly Fatoumata , Manga Isaac A. , Diouf Mame Ami , Sow Doudou , Gaye Oumar , Camara Boubacar , Faye Babacar
Published: September 2023

Visceral leishmaniasis (VL) is an infectious disease caused by protozoa of the genus Leishmania. Sporadic cases are observed in nonendemic areas and often associated with limited foci; therefore, the disease is easily overlooked. In addition, other diseases have similar clinical symptoms, which make it difficult for clinicians to make an accurate diagnosis and to provide effective treatment. We identified visceral leishmaniasis in a 4-year-old child in Pikine, Senegal. The patient was admitted to the Pikine National Teaching Hospital for haemorrhagic, tumoral, and infectious syndromes. At admission, the patient presented with epistaxis and gingivorrhagia, a severe anaemic syndrome poorly tolerated, a systemic inflammatory response syndrome with fever at 39.5°C, a tumoral syndrome with 11 cm of hepatomegaly and 12 cm of type IV splenomegaly, and noninflammatory macropoly adenopathies. A spinal cord puncture was performed, and direct microscopy examination of the sample after GIEMSA staining revealed amastigote forms of Leishmania. The PCR amplification of extracted DNA from the bone marrow aspiration using specific primers for VL (forward and reverse) confirmed that VL was responsible for the infection. A treatment with meglumine antimoniate (Glucantime) was given and it gave a successful outcome with remission of clinical symptoms and favourable evolution with 3 months hindsight. Conclusion. This visceral leishmaniasis case diagnosis in Senegal has shown that, apart from haematological malignancies, this disease must be considered in combination with a tumor syndrome, haemorrhagic syndrome, and infectious syndrome.
Manifestation of Guillain–Barre Syndrome in a Case of Monkeypox Virus Infection: A Rare Case Report
Authors: Abdul Hamid Tariq , Mustafa Nayab , Zulfiquar Parkar Almas , Marina Varghese Sherin , Sayedahmed Ossama , Ghanaim Mohammed
Published: September 2023

Monkeypox virus (MPXV) is one of the rare zoonotic infections caused by orthopoxvirus. MPXV has recently been an evolving threat to public health with its contagious human-to-human transmission. Various presentations of MPXV infection have been reported ranging from generalised symptoms such as fever, chills, body aches, and swollen lymph nodes to dermatological presentations. Neurological manifestations that have been reported include headaches, myalgia, seizures, and even mood disturbances. Postinfectious complications such as encephalitis, vision problems, and skin infections have also been noticed. Guillain–Barre Syndrome (GBS) is an acquired acute inflammatory polyradiculoneuropathy characterized by progressive, symmetrical, proximal, and distal tingling and weakness. Although various microorganisms are known to cause GBS and have been linked to the smallpox vaccine, they are rarely linked to MPXV disease. In this report, we describe a case of a confirmed monkeypox infection in a patient presenting with Guillain-Barre Syndrome.
Predictive Value of Post-Percutaneous Coronary Intervention Quantitative Flow Ratio for Vessel-Oriented Composite Endpoint
Authors: Liu Weibin , Cai Huaxiu , Zheng Yin , Wen Yongkang , Chen Sicheng , Xie Xiuying , Zeng Huan , Zhu Hengqing , Ni Zhonghan , Pei Fang , Cao Jun , Cao Gang
Published: September 2023

At present, there is a lack of indicators, which can accurately predict the post-percutaneous coronary intervention (post-PCI) vessel-oriented composite endpoint (VOCE). Recent studies showed that the post-PCI quantitative flow ratio (QFR) can predict post-PCI VOCE. PubMed, Embase, and Cochrane were searched from inception to March 27, 2022, and the cohort studies about that the post-PCI QFR predicts post-PCI VOCE were screened. Meta-analysis was performed, including 6 studies involving 4518 target vessels. The results of the studies included in this meta-analysis all showed that low post-PCI QFR was an independent risk factor for post-PCI VOCE after adjusting for other factors, HR (95% CI) ranging from 2.718 (1.347–5.486) to 6.53 (2.70–15.8). Our meta-analysis showed that the risk of post-PCI VOCE was significantly higher in the lower post-PCI QFR group than in the higher post-PCI QFR group (HR: 4.14, 95% CI: 3.00–5.70,

P

 < 0.001, I2 = 27.9%). Post-PCI QFR has a good predictive value for post-PCI VOCE. Trial Registration. This trial is registered with CRD42022322001.
A Multi-Polarized Reconfigurable Plasma Antenna Array
Authors: Sun Zhen , Zhou Zhenzhen , Tan Zhihao , Wu Huafeng , Zhao Jiansen
Published: September 2023

Research on antenna reconfiguration is important in antenna applications. We present design of a multi-polarized plasma antenna with 40.68 MHz radio frequency (RF) power supplies and several discharge tubes filled with argon (neon) and mercury. Furthermore, self-made regulating circuits among the vibrators are introduced for the antenna array system. It can not only make the length of the dipole controllable but also improve the antenna gain and circular polarization (CP) performance under different lengths. Antenna arrays can be classified into linear and circular polarization by quickly adjusting the phase difference between vibrators. Both the experimental and simulation results indicate that the plasma antenna can realize impedance, pattern, and polarization reconstruction expediently. In addition, the linear polarization (LP) and CP can be transformed into each other quickly by adjusting the discharge conditions and regulating circuits. Moreover, compared with a symmetrical cross vibrator plasma antenna and a metal antenna of the same size, the proposed antenna array shows a certain gain and good reconfigurable performance within the frequency band of 150–250 MHz.
Association between Probiotics and Modulation of Gut Microbial Community Composition in Colorectal Cancer Animal Models: A Systematic Review (2010–2021)
Authors: Zeighamy Alamdary Shabnam , Halimi Shahnaz , Rezaei Akram , Afifirad Roghayeh
Published: September 2023

Background. Colorectal cancer (CRC) is one of the most prevalent gastrointestinal malignancies and is considered the third major cause of mortality globally. Probiotics have been shown to protect against the CRC cascade in numerous studies. Aims. The goal of this systematic review was to gather the preclinical studies that examined the impact of probiotics on the alteration of gut microbiota profiles (bacterial communities) and their link to colorectal carcinogenesis as well as the potential processes involved. Methods. The search was performed using Scopus, Web of Science, and PubMed databases. Five parameters were used to develop search filters: “probiotics,” “prebiotics,” “synbiotics,” “colorectal cancer,” and “animal model.” Results. Of the 399 full texts that were screened, 33 original articles met the inclusion criteria. According to the current findings, probiotics/synbiotics could significantly attenuate aberrant crypt foci (ACF) formation, restore beneficial bacteria in the microbiota population, increase short-chain fatty acids (SCFAs), and change inflammatory marker expression. Conclusions. The present systematic review results indicate that probiotics could modulate the gut microbial composition and immune regulation to combat/inhibit CRC in preclinical models. However, where the evidence is more limited, it is critical to transfer preclinical research into clinical data.
Fungal Infections Are Not Associated with Increased Mortality in COVID‐19 Patients Admitted to Intensive Care Unit (ICU)
Authors: Ainsworth James , Sewell Peter , Eggert Sabine , Morris Keith , Pillai Suresh
Published: September 2023

Introduction. Fungal infection is a cause of increased morbidity and mortality in intensive care patients. Critically unwell patients are at increased risk of developing invasive fungal infections. COVID‐19 patients in the intensive care unit (ICU) may be at a particularly high risk. The primary aim of this study was to establish the incidence of secondary fungal infections in patients admitted to the ICU with COVID‐19. Secondary aims were to investigate factors that may contribute to an increased risk of fungal infections and to calculate the mortality between fungal and nonfungal groups. Methods. We undertook a retrospective observational study in a tertiary ICU in Wales, United Kingdom. 174 patients admitted with COVID‐19 infection from March 2020 until May 2021 were included. Data were collected through a retrospective review of patient’s clinical notes and microbiology investigation results obtained from the online clinical portal. Results. 81/174 (47%) COVID‐19 patients developed fungal infections, 93% of which were Candida species, including Candida albicans (88%), and 6% had an Aspergillus infection. Age and smoking history did not appear to be contributing factors. The nonfungal group had a significantly higher body mass index (33 ± 8 vs. 31 ± 7, p = 0.01). The ICU length of stay (23 (1–116) vs. 8 (1–60), p < 0.001), hospital length of stay (30 (3–183) vs. 15 (1–174) ± 7, p < 0.001), steroid days (10 (1–116) vs. 4 (0–28), p = 0.02), and ventilation days (18 (0–120) vs. 2 (0–55), p < 0.001) were significantly higher in the fungal group. The mortality rate in both groups was similar (51% vs. 52%). The Kaplan–Meier survival analysis showed that the fungal group survived more than the nonfungal group (log rank (Mantel–Cox), p < 0.001). Conclusion. Secondary fungal infections are common in COVID‐19 patients admitted to the ICU. Longer treatment with corticosteroids, increased length of hospital and ICU stay, and greater length of mechanical ventilation significantly increase the risk of fungal infections. Fungal infection, however, was not associated with an increase in mortality.
Source Rock Evaluation of Hydrocarbons in Deep-Water Offshore Areas Based on a BP Neural Network
Authors: Wu Jizhong , Shi Ying , Yang Qianqian , Wang Yanan
Published: September 2023

Due to the lack of drilling data and poor quality of seismic data in deep-water offshore areas, conventional methods cannot effectively predict the total organic carbon (TOC) content. In this paper, the BP neural network method is used to predict the TOC of the strata overlying the target layer, which adds to the TOC information in the study area. Then, the highest TOC value of the strata overlying the target layer is used to select the most sensitive seismic attributes. Finally, the sensitive seismic attributes are used to evaluate the source rocks with no or few wells. A set of TOC prediction technology flows is established for TOC combined with seismic attributes under the condition of no wells and few wells in deep-water areas. The application example shows the reliability of TOC prediction by this technical process, and the study has a certain reference significance for the evaluation of hydrocarbon source rocks in offshore deep water.
Client Violence towards Childcare Workers: A Systematic Literature Review
Authors: Díaz Bórquez Daniela , Calderón-Orellana Magdalena , Inostroza Correa Alejandra , Varas González Gonzalo
Published: September 2023

Client violence against childcare workers is a relevant problem due to its impact on their well-being and the service they provide due to their significant role in the child protection process. This study explored violence against childcare workers using a systematic literature review. PubMed, Science Direct, ResearchGate, and Google Scholar were searched for studies that included the words workers, childcare workers, child protection workers, social workers, user violence, client violence, child violence, parental violence, client aggression, client-perpetrated violence, residential childcare, childcare centres, and/or child protection centres. A total of twenty studies were included. Most studies described violent incidents, often directly involving children or their parents. The results indicate that the effects of violence significantly impact the life and well-being of workers and those workers and organizations naturalize it. It is necessary to advance in the denaturation of violence in the workplace and agree on a violence definition to implement preventive measures such as induction, training, and supervision.