Miracle-dz/UniFAR-FTUs huggingface dataset:
The SYMPTOM‐upper gastrointestinal study: A mixed methods study exploring symptom appraisal and help‐seeking in Australian upper gastrointestinal cancer patients

Abstract Objective There is limited evidence on the development of pancreatic and oesophagogastric cancer, how patients decide to seek help and the factors impacting help‐seeking. Our study, the first in Australia, aimed to explore symptom appraisal and diagnostic pathways in these patients. A secondary aim was to examine the potential to recruit cancer patients through a cancer quality registry. Methods Patients diagnosed with pancreatic or oesophagogastric cancer were recruited through Monash University's Upper‐Gastrointestinal Cancer Registry. Data collected through general practitioners (GP) and patient questionnaires included symptoms and their onset, whereas patient interviews focused on the patient's decision‐making in seeking help from healthcare pracitioners. Data collection and analysis was informed by the Aarhus statement. Coding was inductive, and themes were mapped onto the Model of Pathways to Treatment. Results Between November 2018 and March 2020, 27 patient questionnaires and 13 phone interviews were completed. Prior to diagnosis, patients lacked awareness of pancreatic and oesophagogastric cancer symptoms, leading to the normalisation, dismissal and misattribution of the symptoms. Patients initially self‐managed symptoms, but worsening of symptoms and jaundice triggered help‐seeking. Competing priorities, beliefs about illnesses and difficulties accessing healthcare delayed help‐seeking. Conclusion Increased awareness of insidious pancreatic and oesophagogastric cancer symptoms in patients and general practitioners may prompt more urgent investigations and lead to earlier diagnosis.
Cyclooxygenase-Derived Prostaglandin E2 Drives IL-1–Independent Mycobacterium bovis Bacille Calmette-Guérin–Triggered Skin Dendritic Cell Migration to Draining Lymph Node

Inoculation of Mycobacterium bovis Bacille Calmette-Guérin (BCG) in the skin mobilizes local dendritic cells (DC) to the draining lymph node (dLN) in a process that remains incompletely understood. In this study, a mouse model of BCG skin infection was used to investigate mechanisms of skin DC migration to dLNs. We found enhanced transcription of cyclooxygenase (COX)-2 and production of COX-derived PGE2 early after BCG infection in skin. Animals treated with antagonists for COX or the PGE2 receptors EP2 and EP4 displayed a marked reduction in the entry of skin DCs and BCG to dLNs, uncovering an important contribution of COX-derived PGE2 in this migration process. In addition, live BCG bacilli were needed to invoke DC migration through this COX-PGE2 pathway. Having previously shown that IL-1R partially regulates BCG-induced relocation of skin DCs to dLNs, we investigated whether PGE2 release was under control of IL-1. Interestingly, IL-1R ligands IL-1α/β were not required for early transcription of COX-2 or production of PGE2 in BCG-infected skin, suggesting that the DC migration-promoting role of PGE2 is independent of IL-1α/β in our model. In DC adoptive transfer experiments, EP2/EP4, but not IL-1R, was needed on the moving DCs for full-fledged migration, supporting different modes of action for PGE2 and IL-1α/β. In summary, our data highlight an important role for PGE2 in guiding DCs to dLNs in an IL-1–independent manner. Key Points BCG-triggered PGE2 release mobilizes skin DCs to the draining lymph node. Migrating DCs use EP2 and EP4 to relocate to the draining lymph node. Live BCG bacilli are needed for PGE2-mediated DC migration.
Differential impacts of COVID‐19 and associated responses on the health, social well‐being and food security of users of supportive social and health programs during the COVID‐19 pandemic: A qualitative study

Abstract The effects of the coronavirus disease‐2019 (COVID‐19) pandemic on the lives of underserved populations are underexplored. This study aimed to identify the impacts of the COVID‐19 pandemic and associated public health responses on the health and social well‐being, and food security of users of Housing First (HF) services in Toronto (Canada) during the first wave of the COVID‐19 pandemic. This qualitative descriptive study was conducted from July to October 2020 in a subsample of 20 adults with a history of homelessness and serious mental disorders who were receiving HF services in Toronto. A semi‐structured interview guide was used to collect narrative data regarding health and social well‐being, food security and access to health, social and preventive services. A thematic analysis framework guided analyses and interpretation of the data. The COVID‐19 pandemic and response measures had a variable impact on the health, social well‐being and food security of participants. Around 40% of participants were minimally impacted by the COVID‐19 pandemic. Conversely, among the remaining participants (impacted group), some experienced onset of new mental health problems (anxiety, stress, paranoia) or exacerbation of pre‐existing mental disorders (depression, post‐traumatic stress disorder and obsessive‐compulsive disorder). They also struggled with isolation and loneliness and had limited leisure activities and access to food goods. The pandemic also contributed to disparities in accessing and receiving healthcare services and treatment continuity for non‐COVID‐19 health issues for the negatively impacted participants. Overall, most participants were able to adhere to COVID‐19 public health measures and get reliable information on COVID‐19 preventive measures facilitated by having access to the phone, internet and media devices and services. In conclusion, the COVID‐19 pandemic and associated response measures impacted the health, social well‐being, leisure and food security of people with experiences of homelessness and mental disorders who use supportive social and housing services in diverse ways.
Seizure Forecasting by High-Frequency Activity (80–170 Hz) in Long-term Continuous Intracranial EEG Recordings

Background and Objectives Reliable seizure forecasting has important implications in epilepsy treatment and improving the quality of lives for people with epilepsy. High-frequency activity (HFA) is a biomarker that has received significant attention over the past 2 decades, but its predictive value in seizure forecasting remains uncertain. This work aimed to determine the utility of HFA in seizure forecasting. Methods We used seizure data and HFA (80–170 Hz) data obtained from long-term, continuous intracranial EEG recordings of patients with drug-resistant epilepsy. Instantaneous rates and phases of HFA cycles were used as features for seizure forecasting. Seizure forecasts based on each individual HFA feature, and with the use of a combined approach, were generated pseudo-prospectively (causally). To compute the instantaneous phases for pseudo-prospective forecasting, real-time phase estimation based on an autoregressive model was used. Features were combined with a weighted average approach. The performance of seizure forecasting was primarily evaluated by the area under the curve (AUC). Results Of 15 studied patients (median recording duration 557 days, median seizures 151), 12 patients with >10 seizures after 100 recording days were included in the pseudo-prospective analysis. The presented real-time phase estimation is feasible and can causally estimate the instantaneous phases of HFA cycles with high accuracy. Pseudo-prospective seizure forecasting based on HFA rates and phases performed significantly better than chance in 11 of 12 patients, although there were patient-specific differences. Combining rate and phase information improved forecasting performance compared to using either feature alone. The combined forecast using the best-performing channel yielded a median AUC of 0.70, a median sensitivity of 0.57, and a median specificity of 0.77. Discussion These findings show that HFA could be useful for seizure forecasting and represent proof of concept for using prior information of patient-specific relationships between HFA and seizures in pseudo-prospective forecasting. Future seizure forecasting algorithms might benefit from the inclusion of HFA, and the real-time phase estimation approach can be extended to other biomarkers. Classification of Evidence This study provides Class IV evidence that HFA (80–170 Hz) in long-term continuous intracranial EEG can be useful to forecast seizures in patients with refractory epilepsy.
Peripheral sTREM2-Related Inflammatory Activity Alterations in Early-Stage Alzheimer’s Disease

Alzheimer’s disease (AD) has been linked to multiple immune system–related genetic variants. Triggering receptor expressed on myeloid cells 2 (TREM2) genetic variants are risk factors for AD and other neurodegenerative diseases. In addition, soluble TREM2 (sTREM2) isoform is elevated in cerebrospinal fluid in the early stages of AD and is associated with slower cognitive decline in a disease stage–dependent manner. Multiple studies have reported an altered peripheral immune response in AD. However, less is known about the relationship between peripheral sTREM2 and an altered peripheral immune response in AD. The objective of this study was to explore the relationship between human plasma sTREM2 and inflammatory activity in AD. The hypothesis of this exploratory study was that sTREM2-related inflammatory activity differs by AD stage. We observed different patterns of inflammatory activity across AD stages that implicate early-stage alterations in peripheral sTREM2-related inflammatory activity in AD. Notably, fractalkine showed a significant relationship with sTREM2 across different analyses in the control groups that was lost in later AD-related stages with high levels in mild cognitive impairment. Although multiple other inflammatory factors either differed significantly between groups or were significantly correlated with sTREM2 within specific groups, three inflammatory factors (fibroblast growth factor-2, GM-CSF, and IL-1β) are notable because they exhibited both lower levels in AD, compared with mild cognitive impairment, and a change in the relationship with sTREM2. This evidence provides important support to the hypothesis that sTREM2-related inflammatory activity alterations are AD stage specific and provides critical information for therapeutic strategies focused on the immune response. Key Points Early-stage alterations were evident in peripheral sTREM2-related inflammatory activity. These alterations implicate early inflammatory cell development and recruitment signaling in AD. Patterns of inflammatory activity are altered across all AD stages.
BROADBAND LOW PROFILE AND COMPACT RDRA LOADED WITH METALLIC STRIPS FOR WIDEBAND APPLICATIONS

in this paper, a compact broadband, low-profile rectangular dielectric resonator antenna (RDRA) is proposed using relatively low dielectric constant substrate material (Rogers RT/Duroid 3010 εr = 10.2) and developed for wireless communication applications. The rectangular DRA is fed with a modified stepped Microstrip feed to ensure efficient coupling between the RDRA and the feeder. Broadband operation is achieved by loading the rectangular dielectric resonator antenna with conducting metallic strip which results in a new resonance beside the antenna operating frequency. The performance of the proposed antenna has been significantly improved by loading the RDRA with two narrow conducting metallic strips of suitable lengths, which results in dual-resonance excitation and leads to a wider operating bandwidth (up to 23.75 %). The frequency characteristics and radiation performance of the proposed antenna are successfully optimized using numerical experimentation techniques. The antenna size reduction is demonstrated while maintaining a reasonable bandwidth. Simulations results based on a 3D full-wave electromagnetic simulator are presented in the paper.
Peran Kelembagaan Dalam Pengelolaan Persampahan Di Kabupaten Trenggalek

One of the social problems that often arise in urban areas is a waste problem. Waste problem is basically caused by many things, such as the lack of good waste management, the behavior of a society that is still low in maintaining hygiene and environmental health, as well as the growing population, thus adding of waste produced by households. Waste management in the region, will involve communities, government, NGOs and the private sector. But in Trenggalek, the absence of private parties who participated in addressing rural waste. Waste management in Trenggalek handled by the government and the people who lead the waste pelayananaan less than optimal or not in accordance with existing regulations. The aim of this study was to assess the extent to which institutional role in waste management in Trenggalek, in creating a healthy environment, berhindar of soil and water pollution caused by garbage. The analysis in this study was performed using Pearson correlation analysis, crosstab analysis and scale analysis. Results from this study were 1) Waste in Trenggalek differentiate into 2 (two), namely organic and inorganic waste, the most dominant is the leaf litter and food waste amounted to 81.30%. 2) Institute for waste management there are only two (2) institutions, namely the government and society. 3) Waste management in Trenggalek done by way of being transported by a janitor, burned and dumped into the river. 4) The role of each institution shows that government plays an important role in waste management in Trenggalek. 5) Based on the analysis of the correlation between institutional waste management indicates that the government has a weak relationship with the community, so that waste management is less than optimal.
Children’s interaction with the Internet: time dedicated to communications and games

ABSTRACT In the context of growing interest of individuals in the Internet, the literature has not paid attention to the uses of time for children, given the scarcity of appropriate data bases that provide accurate information. To partially cover this gap, we now provide here evidence of the time that children aged between 10 and 12 years dedicate to two online activities: computer communication and computer gaming. To that end, we estimate a simultaneous seemingly unrelated regressions (SUR) model with data from the Spanish Time Use Survey for 2009–2010. Results indicate that being female generates a positive influence on the time devoted to computer communication, and being male generates a positive influence on the time devoted to computer gaming. We also find that a greater number of family members with secondary studies generates a positive influence on the time spent on computer gaming. Children with better health spend more time on both of these activities and, finally, living in a larger city produces a positive effect on the time dedicated to computer gaming.
Human errors play a remarkable role in sheet metal industry

In many manufacturing companies an appreciable portion of profit within reach is wasted due to poor quality of design and workmanship. This paper concentrates to the origins of production errors in the production flow of sheet metal based constructions. This study is based on a field study carried out in three Finnish case factories and the conclusion is, that workforce and work organization re-lated human activity based errors cause most of the studied production errors.
LINEARISED FREQUENCY DOMAIN GUST ANALYSIS OF LARGE CIVIL AIRCRAFT

Predicting loads due to atmospheric turbulence is crucial in the aircraft design and certification process. Efficient methods are important regarding the large number of simulations needed to cover the parameter space of e.g. Mach number, flight altitude and gust shape. Since commercial aircraft operate at transonic flight speeds, applied methods should consider aerodynamic nonlinearities such as shocks and boundary layer separation. Based on a recently presented method using frequency domain computational fluid dynamics for gust interaction, an extension towards industry-relevant three-dimensional cases is proposed. Results are shown for a large civil aircraft solving the Reynolds-averaged Navier-Stokes equations. Complex-valued surface pressures from time-linearised simulations are compared to nonlinear unsteady timemarching investigations. Responses to 1-cos gusts are obtained to discuss time histories of load factors and worst case surface pressure distributions.
Digging out intersexual and meteorological effects on cicada emergence using 10‐year citizen monitoring

Understanding the mechanisms determining the emergence timing of herbivorous insects is ecologically important. However, little is known about the effect of climatic factors and the presence of conspecific individuals on their emergence in the field. In particular, it is challenging to investigate the seasonal emergence of cicadas because these insects have a long life‐cycle and subterranean larval stages. We assembled a time‐series dataset that consists of daily counts of emerging cicadas together with meteorological factors, using long‐term collection of cicada exuviae by elementary and junior‐high‐school students. We then performed a non‐linear time‐series analysis, empirical dynamic modelling, to identify factors behind the timing of cicada emergence. Our findings are three‐fold: (1) emergence of individuals of the opposite sex constitute a major driver of the number of individuals emerging per day, and this effect is stronger in males than in females, (2) as in other insect species, air temperature consistently affects cicada emergence, but its effects are relatively weak and (3) precipitation and humidity were causally related to emergence. These results are consistent with the theory of sexual selection as well as the fact that it is hard for the subterranean cicada larvae to use information about air temperature. Significantly, the findings are based on long‐term field data collected by non‐expert citizens.
Deep Learning for Information Extraction

The explosion of data has made it crucial to analyze the data and distill important information effectively and efficiently. A significant part of such data is presented in unstructured and free-text documents. This has prompted the development of the techniques for information extraction that allow computers to automatically extract structured information from the natural free-text data. Information extraction is a branch of natural language processing in artificial intelligence that has a wide range of applications, including question answering, knowledge base population, information retrieval etc. The traditional approach for information extraction has mainly involved hand-designing large feature sets (feature engineering) for different information extraction problems, i.e, entity mention detection, relation extraction, coreference resolution, event extraction, and entity linking. This approach is limited by the laborious and expensive effort required for feature engineering for different domains, and suffers from the unseen word/feature problem of natural languages. This dissertation explores a different approach for information extraction that uses deep learning to automate the representation learning process and generate more effective features. Deep learning is a subfield of machine learning that uses
Results and conclusions: perception sensor study for high speed autonomous operations

Previous research has presented work on sensor requirements, specifications, and testing, to evaluate the feasibility of increasing autonomous vehicle system speeds. Discussions included the theoretical background for determining sensor requirements, and the basic test setup and evaluation criteria for comparing existing and prototype sensor designs. This paper will present and discuss the continuation of this work. In particular, this paper will focus on analyzing the problem via a real-world comparison of various sensor technology testing results, as opposed to previous work that utilized more of a theoretical approach. LADAR/LIDAR, radar, visual, and infrared sensors are considered in this research. Results are evaluated against the theoretical, desired perception specifications. Conclusions for utilizing a suite of perception sensors, to achieve the goal of doubling ground vehicle speeds, is also discussed.
Path Following Control of the Underactuated USV Based On the Improved Line-of-Sight Guidance Algorithm

Abstract The path following control problem of the underactuated unmanned surface vessel (USV) is studied in this paper. An improved line-of-sight (LOS) guidance algorithm is proposed which can adjust adaptively based on the path following error. The global asymptotically stable path following controller is designed based on the nonlinear backstepping method and the Lyapunov stability theory. Firstly, the USV path following error model is established in the Serret-Frenet (SF) coordinate frame. The path following error in the inertial coordinate frame is transformed into the SF coordinate frame, which is used to define the path following control problem. Secondly, inspired by the traditional LOS guidance algorithm, the longitudinal path following error in the SF coordinate frame is introduced into the improved LOS guidance algorithm. This allows the algorithm to adjust adaptively to the desired path. Thirdly, in order to solve the underactuated problem of the USV path following control system, the tangential velocity of the desired path is designed as a virtual input. The underactuated problem is converted to a virtual fully actuated problem by designing the virtual control law for the tangential velocity. Finally, by combining backstepping design principles and the Lyapunov stability theory, the longitudinal thrust control law and the yaw torque control law are designed for the underactuated USV. Meanwhile, the global asymptotic stability of the path following error is proved. Simulation experiments demonstrate the effectiveness and reliability of the improved LOS guidance algorithm and the path following controller.
Correlation Between Endotracheal Tube Cuff Pressure and Tracheal Wall Pressure Using Air and Saline Filled Cuffs

Abstract : Endotracheal tubes (ETTs) utilizing high-volume, low-pressure cuffs lower the risk of tracheal wall injury, requiring less pressure to provide a seal. Recently introduced tapered ETT cuffs, which show a lower propensity for fluid leakage, provide another ETT option. Aeromedical transport presents a challenging environment for ETT cuff management and requires diligent monitoring to maintain pressure within the recommended range. The pressure measured in the cuff is assumed to be equal to the pressure exerted on the tracheal wall (TW). We performed a bench study to evaluate this correlation at sea level and simulated altitude. Mean TW pressure and cuff pressure were compared using Students t-test. Statistical significance was defined as p 0.05. When using air in the ETT cuff, TW pressure differences were statistically significant between baseline and at altitude with all ETTs but not between baseline and at sea level after descending from altitude. When using saline in the ETT cuff, TW pressure differences with the 7.5 high-volume, low-pressure cuff and 8.0 TaperGuard cuff were statistically significant at altitude and back at sea level, as compared to baseline. Cuff pressure differences with saline in all ETTs were not statistically significant. Comparing TW pressure and cuff pressure, differences were statistically significant at all conditions with all ETTs. The use of saline provided the highest baseline pressure but had the lowest pressure variation, while using air provided the highest pressure at altitude and the largest pressure variation from baseline. Due to lack of ability to measure pressure, use of saline in the ETT cuff is discouraged. Maintaining cuff pressure 30 cmH2O is imperative to minimize TW pressure.