Miracle-dz/UniFAR-FTUs huggingface dataset:
Air Pollution Exposure and the Development of Chronic Rhinosinusitis in the Active Duty Population.

INTRODUCTION It has been shown that combat environment exposure, including burn pits that produce particulate matter 2.5 (PM2.5), is associated with lower respiratory tract disease in the military population with increased hypothetical risk of upper respiratory disease, but no study has been done that examines the effects of non-combat environmental exposures on the development of chronic rhinosinusitis (CRS) in the active duty population. The primary goal of this study is to evaluate how air pollution exposure correlates to the development of CRS in active duty service members in the United States. METHODS The military electronic medical record was queried for active duty service members diagnosed with CRS by an otolaryngologist between January 2016 and January 2018, who have never deployed, stationed in the United States from 2015 to 2018 (n = 399). For each subject, the 1-year mean exposure of PM2.5, particulate matter 10 (PM10), nitrogen dioxide (NO2), and ozone was calculated. The control group was comprised of the same criteria except these patients were diagnosed with cerumen impaction and matched to the case group by age and gender (n = 399). Pollution exposure was calculated based on the Environmental Protection Agency's data tables for each subject. Values were calculated using chi-square test for categorical variables and the Mann-Whitney U-test for continuous variables. RESULTS Matched cases and controls (n = 399) with 33.1% male showed a statistically significant odds ratio (OR) of 5.99 (95% CI, 2.55-14.03) for exposure of every 5 µg/m3 of PM2.5 increase and the development of CRS when controlling for age, gender, and diagnosis year. When further adjusting for smoking status, the OR was still statistically significant at 3.15 (95% CI, 1.03-9.68). Particulate matter 10, ozone, and NO2 did not show any statistical significance. Odds ratios remained statistically significant when further adjusting for PM10 and ozone, but not NO2. Dose-dependent curves largely did not show a statistical significance; however, they did trend towards increased exposure of PM2.5 leading to an elevated OR. CONCLUSION This study showed that PM2.5 exposure is a major independent contributor to the development of CRS. Exposure to elevated levels produced statistically significant odds even among smokers and remained significant when controlling for other measured pollutants. There is still much to be understood about the genesis of CRS. From a pollution exposure perspective, a prospective cohort study would better elucidate the risk of the development of CRS among those exposed to other pollutants.
Lower Limb Joint Functions during Single-Leg Hopping in-Place in Children and Adults

Abstract Children often display different whole-body dynamics compared to adults during locomotion such as walking and hopping. However, it is unknown whether these differences result in diverging functional usage of the lower limb joints. This study aimed to compare the mechanical functions of the ankle, knee, and hip joints between children and adults during single-leg hopping in-place at different frequencies. Children aged 5–11 years and adults aged 18–35 years performed hopping at their preferred frequency and slower and faster frequencies. Function of the joint was modeled as a combination of a strut, spring, motor, and damper. At the preferred frequency, children hopped equally with strut and spring functions at the ankle and knee joints while adults primarily used the spring function. When increasing frequency, both children and adults decreased the spring index and increased the strut index at the ankle and knee joints. Across all conditions, both children and adults used the strut function primarily at the hip joint. Results suggest that preadolescent children are still developing the adult-like spring function of their ankle and knee joints during hopping in-place. Quantification of spring function during hopping in-place may present an innovative approach to understand the maturation of the stretch-shortening cycle in children.
Influence of developmental nicotine exposure on serotonergic control of breathing‐related motor output

Serotonin plays an important role in the development of brainstem circuits that control breathing. Here, we test the hypothesis that developmental nicotine exposure (DNE) alters the breathing‐related motor response to serotonin (5HT). Pregnant rats were exposed to nicotine or saline, and brainstem–spinal cord preparations from 1‐ to 5‐day‐old pups were studied in a split‐bath configuration, allowing drugs to be applied selectively to the medulla or spinal cord. The activity of the fourth cervical ventral nerve roots (C4VR), which contain axons of phrenic motoneurons, was recorded. We applied 5HT alone or together with antagonists of 5HT1A, 5HT2A, or 5HT7 receptor subtypes. In control preparations, 5HT applied to the medulla consistently reduced C4VR frequency and this reduction could not be blocked by any of the three antagonists. In DNE preparations, medullary 5HT caused a large and sustained frequency increase (10 min), followed by a sustained decrease. Notably, the transient increase in frequency could be blocked by the independent addition of any of the antagonists. Experiments with subtype‐specific agonists suggest that the 5HT7 subtype may contribute to the increased frequency response in the DNE preparations. Changes in C4VR burst amplitude in response to brainstem 5HT were uninfluenced by DNE. Addition of 5HT to the caudal chamber modestly increased phasic and greatly increased tonic C4VR activity, but there were no effects of DNE. The data show that DNE alters serotonergic signaling within brainstem circuits that control respiratory frequency but does not functionally alter serotonin signaling in the phrenic motoneuron pool.
Research Progress on Preparation, Mechanism, and Clinical Application of Nanofat

Abstract Autologous adipose tissue is an ideal soft tissue filling material in theory, which has the advantages of easy access, comprehensive source, and high biocompatibility and is now widely used in clinical practice. Based on the above benefits of autologous fat, autologous fat grafting is an essential technique in plastic surgery. Conventional macrofat is used to improve structural changes after soft tissue damage or loss caused by various causes such as disease, trauma, or aging. Due to the large diameter of particles and to avoid serious complications such as fat embolism, blunt needles with larger diameters (2 mm) are required, making the macrofat grafting difficult to the deep dermis and subdermis. Nanofat grafting is a relatively new technology that has gained popularity in cosmetic surgery in recent years. Nanofat is produced by mechanical shuffling and filtration of microfat, which is harvested by liposuction. The harvesting and processing of nanofat are cost-effective as it does not require additional equipment or culture time. Unlike microfat, nanofat particles are too small to provide a notable volumizing effect. Studies have shown that nanofat contains abundant stromal vascular fraction cells and adipose-derived stem cells, which help reconstruct dermal support structures, such as collagen, and regenerate healthier, younger-looking skin. Moreover, the fluid consistency of nanofat allows application in tissue regeneration, such as scars, chronic wounds, and facial rejuvenation. This article reviews the current research progress on the preparation, mechanism, and clinical application of nanofat.
Trade-off of major bleeding versus myocardial infarction on mortality after percutaneous coronary intervention

Background The choice of antithrombotic therapy after percutaneous coronary intervention (PCI) is heavily dependent on the relative trade-off between major bleeding (MB) and myocardial infarction (MI). However, the mortality trade-off was mostly described in Western populations and remained unknown in East Asians. Method This was a retrospective cohort study from 14 hospitals under the Hospital Authority of Hong Kong between 2004 and 2017. Participants were patients undergoing first-time PCI and survived for the first year. Patients were stratified by the presence of MB and MI during the first year. The primary endpoint was all-cause mortality between 1 and 5 years after PCI. The secondary endpoint was cardiovascular mortality. Results A total of 32 180 patients were analysed. After adjustment for baseline characteristics and using patients with neither events as reference, the risks of all-cause mortality were increased in patients with MI only (HR, 1.63; 95% CI 1.45 to 1.84; p<0.001), further increased in those with MB only (HR, 2.11, 95% CI 1.86 to 2.39; p<0.001) and highest in those with both (HR, 2.92; 95% CI 2.39 to 3.56; p<0.001). In both Cox regression and propensity score analyses, MB had a stronger impact on all-cause mortality than MI, but similar impact on cardiovascular mortality. Conclusions Both MB and MI within the first year after PCI were associated with increase in all-cause and cardiovascular mortality in Chinese patients, but the impact was stronger with MB.
The mouth‐opening muscular performance in adults with and without temporomandibular disorders: A systematic review

Abstract Background The mouth‐opening muscular performance in patients with temporomandibular disorders (TMDs) is unclear. Understanding the impairments of this muscle group within specific TMDs is important to develop proper management strategies. Objective To characterise the mouth‐opening muscular performance in adults with and without TMDs. Methods PubMed, EMBASE, CINAHL, Scopus, Web of Science and Cochrane databases were searched from inception to 12 November 2020. Bibliographies were searched for additional articles, including grey literature. Case‐control, cross‐sectional and interventional studies reporting mouth‐opening muscular strength and/or endurance were included. Risk of bias was assessed by the SIGN checklist for case‐control studies and by the NIH quality assessment tool for cross‐sectional studies. Results were pooled with a random‐effects model. Confidence in cumulative evidence was determined by means of the GRADE guidelines. Results Fourteen studies were included; most were rated as having a moderate risk of bias. Only three studies assessed patients with TMDs and the other 11 assessed healthy adults. Significant sex differences in muscular performance were found for healthy adults in the review (strength deficit for females versus males). There was a significant reduction in maximal mouth opening performance (strength and endurance) in the three studies that assessed patients with temporomandibular disorders. Conclusion Sex plays a significant role in maximal mouth opening strength. There is a lack of reliable data on the normal mouth‐opening strength and endurance of healthy adults as well as for patients with TMDs. Implications Lack of reliable TMDs patient data and comparable healthy adult data highlight future direction for research.
Propagators in the correlated worldline theory of quantum gravity

Starting from a formulation of Correlated Worldline (CWL) theory in terms of functional integrals over paths, we define propagators for particles and matter fields in this theory. We show that the most natural formulation of CWL theory involves a rescaling of the generating functional for the theory; correlation functions then simplify, and all loops containing gravitons disappear from perturbative expansions. The spacetime metric obeys the Einstein equation, sourced by all of the interacting CWL paths. The matter paths are correlated by gravitation, thereby violating quantum mechanics for large masses. We derive exact results for the generating functional and the matter propagator, and for linearized weak field theory. For the example of a two-path experiment, we derive the CWL matter propagator, and show how the results compare with conventional quantum theory and with semiclassical gravity. We also exhibit the structure of low-order perturbation theory for the CWL matter propagator.
Efficient algorithms for dynamic bidirected Dyck-reachability

Dyck-reachability is a fundamental formulation for program analysis, which has been widely used to capture properly-matched-parenthesis program properties such as function calls/returns and field writes/reads. Bidirected Dyck-reachability is a relaxation of Dyck-reachability on bidirected graphs where each edge u→(iv labeled by an open parenthesis “(i” is accompanied with an inverse edge v→)iu labeled by the corresponding close parenthesis “)i”, and vice versa. In practice, many client analyses such as alias analysis adopt the bidirected Dyck-reachability formulation. Bidirected Dyck-reachability admits an optimal reachability algorithm. Specifically, given a graph with n nodes and m edges, the optimal bidirected Dyck-reachability algorithm computes all-pairs reachability information in O(m) time. This paper focuses on the dynamic version of bidirected Dyck-reachability. In particular, we consider the problem of maintaining all-pairs Dyck-reachability information in bidirected graphs under a sequence of edge insertions and deletions. Dynamic bidirected Dyck-reachability can formulate many program analysis problems in the presence of code changes. Unfortunately, solving dynamic graph reachability problems is challenging. For example, even for maintaining transitive closure, the fastest deterministic dynamic algorithm requires O(n2) update time to achieve O(1) query time. All-pairs Dyck-reachability is a generalization of transitive closure. Despite extensive research on incremental computation, there is no algorithmic development on dynamic graph algorithms for program analysis with worst-case guarantees. Our work fills the gap and proposes the first dynamic algorithm for Dyck reachability on bidirected graphs. Our dynamic algorithms can handle each graph update (i.e., edge insertion and deletion) in O(n·α(n)) time and support any all-pairs reachability query in O(1) time, where α(n) is the inverse Ackermann function. We have implemented and evaluated our dynamic algorithm on an alias analysis and a context-sensitive data-dependence analysis for Java. We compare our dynamic algorithms against a straightforward approach based on the O(m)-time optimal bidirected Dyck-reachability algorithm and a recent incremental Datalog solver. Experimental results show that our algorithm achieves orders of magnitude speedup over both approaches.
Technology-mediated Citizens’ Co-Production on Disaster Management: The case of highly urbanized city

Disaster Management (DM) has been a forefront for research in the 21st century as countries around the world have faced tremendous challenges relating to an overwhelming and imminent scale of disaster occurrences. To bolster disaster preparedness and recovery, DM has been crafted and emerged as a mechanism as well as a strategy in reducing the impact of disaster on humans and structures. In parallel, extant literature and experts in the field have in constant debate on the relevance and the role of information and communications technology (ICT) to play in disaster management in surmounting the posited challenges. Accordingly, it is vital that ICT is developed in promoting innovation and collaboration among government and the people. However, the evolving and dynamic nature of citizens to participate and co-produce in technology-enabled disaster management still needs to be explored. The Philippines is one of the most recurrently visited by disasters due to its geographical location making it susceptible to many threats. The country has numerous initiatives for disaster risk reduction and management, including the Nationwide Operational Assessment of Hazards (NOAH), a flagship ICT-based program in combating disasters. However, the implementation of DM programs remains many challenges especially that Local Government Units (LGUs) have different disaster risks management and implementation styles. This research would fill in the present gap by exploring the dynamics on how the citizens could be a co-producer of relevant information with the government in a technology-based platform. This research also employs an interpretive methodology, that is usually aimed in creating an interpretation of the context on an information system or technology. The qualitative case study design is also ideal in an interpretive approach by enabling people to express their understanding of howNOAH could promote the process of co-production, qualitatively analyzed using thematic analysis.
Dynamic Testing Techniques of Non-functional Requirements in Mobile Apps: A Systematic Mapping Study

Context: The mobile app market is continually growing offering solutions to almost all aspects of people’s lives, e.g., healthcare, business, entertainment, as well as the stakeholders’ demand for apps that are more secure, portable, easy to use, among other non-functional requirements (NFRs). Therefore, manufacturers should guarantee that their mobile apps achieve high-quality levels. A good strategy is to include software testing and quality assurance activities during the whole life cycle of such solutions. Problem: Systematically warranting NFRs is not an easy task for any software product. Software engineers must take important decisions before adopting testing techniques and automation tools to support such endeavors. Proposal: To provide to the software engineers with a broad overview of existing dynamic techniques and automation tools for testing mobile apps regarding NFRs. Methods: We planned and conducted a Systematic Mapping Study (SMS) following well-established guidelines for executing secondary studies in software engineering. Results: We found 56 primary studies and characterized their contributions based on testing strategies, testing approaches, explored mobile platforms, and the proposed tools. Conclusions: The characterization allowed us to identify and discuss important trends and opportunities that can benefit both academics and practitioners.
Detecting denial-of-service hardware Trojans in DRAM-based memory systems

DRAM latencies are inherently variable, potentially allowing a denial-of-service hardware Trojan (DoS HT) to degrade memory performance without becoming immediately obvious. This paper addresses the challenge of detecting a DoS HT that may have been inserted into a DRAM-based memory system, without requiring detailed internal knowledge of the DRAM device. We present a real-time machine-learning based DoS HT detection technique based on a low-cost hardware monitor at the interface to the DRAM controller, coupled with periodic software based analysis of monitoring output.
Prediction of ROP Method Based on Online Machine Learning and Multi-source Data Preprocessing Technology

The drilling operation is a large scale, technically complex and systematic project, which has always taken the top position of investment in oil exploration and development. Speed and efficiency are the primary goals of drilling engineering. Using information technology to optimize drilling parameters can reduce the complexity of accidents, improve the time efficiency of drilling, and significantly shorten the drilling construction cycle and save exploration and development costs. Forecasting drilling rate of penetration (ROP) is an essential component of drilling optimization. This paper introduces a machine learning-based permeability prediction method and its application effects. In response to the drilling rate of penetration (ROP) problem, a drilling rate of penetration (ROP) model based on an integrated learning algorithm is designed and implemented by mining the historical data collected from a specific block. Meanwhile, this approach is compared with traditional machine learning algorithms such as SVM, LR and KNN. The experimental results indicate that the algorithm has better accuracy and applicability than other methods, which can provide a scientific and reliable reference for improving drilling rate of penetration (ROP) and technical support for realizing intelligent drilling.
Optimally Tuned Controller for Single-Phase Grid-Connected PV Micro-Inverters

Photovoltaic energy from renewable sources is becoming more prevalent nowadays, as part of the process of converting this energy to AC voltage and feeding it into the power grid network, the output voltage or injected current total harmonic distortion (THD) should be low, usually below 5 %. This unwanted distortion can lead to increased current in the PV inverter resulting in higher temperature and additional energy loss. To suppress injected grid current THD, an advanced controller, i.e. a proportional resonant (PR) control design is commonly used. In this work, we report an approach to optimally select parameters (Kp, Ki and Wc for this controller to suppress the THD, reduce leakage current, and ensure a unity power factor operation in the system. The control algorithm is implemented in an integrated digital signal processing evaluation board from TI - TMS320F28335 eZdsp board. In this paper, both simulation and experimental results are provided to demonstrate the effectiveness of the proposed technique in reducing the injected current THD through the development of 500 W micro-inverter prototype as a case study.
Toward Personalized Emotion Recognition: A Face Recognition Based Attention Method for Facial Emotion Recognition

This paper aims to address the subject-dependent challenge of the facial emotion recognition (FER) task. To accomplish this, we propose a novel face recognition based attention FER (FRA-FER) framework which propagates subtle face recognition (FR) features through the FER network. Particularly, first a spatial attention map from the feature maps of an FR convolutional neural network (CNN) is created and then it is fused into the FER-CNN. By doing this FR feature propagation, the FER network is personalized as it takes the advantage of the FR features learned from large-scale face recognition datasets. Experiments on the two challenging datasets AffectNet and AFEW demonstrate the superiority of our proposed FRA-FER network to the state-of-the-art work.
Predictive Current Control Design Methodology for DC-DC Basic Topologies: Buck, Boost and Buck-Boost Converters

The DC-DC basic topologies are widely used in medium and high-voltage power systems like photovoltaic applications, renewable energies, electric vehicles, etc. Different modern control strategies have been developed, like the predictive control method that is a simple and intuitive technique, easy to implement and can be applied to a great variety of systems. In this paper the principle of operation and a detailed procedure of a predictive current controller design applied to a Buck, Boost and Buck-Boost converter are presented, being the basis to apply it to more complex systems. Simulations results that validate the proposed strategy are presented.
In-flight moving base alignment technique for platform inertial navigation system on missile

By establishing the system model of moving-base alignment velocity match, the factors that influenced the transfer alignment were analyzed, such as lever arm effect, flexible vibrations, etc. The off-line simulation was made using the navigation data sampled from the trial in sigmoid flying. It is concluded that alignment precision satisfies the performance requirements, that is level 1′, azimuth 6′, platform-drift 0.02 (°)/h, and alignment time 15 min. The simulation result shows the scheme proposed satisfies the system performance and is practicable.