Combining Fleetwide AviTeam Aviation Emission Modeling with LCA Perspectives for an Alternative Fuel Impact Assessment.

Reducing aviation emissions is important as they contribute to air pollution and climate change. Several alternative aviation fuels that may reduce life cycle emissions have been proposed. Comparative life cycle assessments (LCAs) of fuels are useful for inspecting individual fuels, but systemwide analysis remains difficult. Thus, systematic properties like fleet composition, performance, or emissions and changes to them under alternative fuels can only be partially addressed in LCAs. By integrating the geospatial fuel and emission model, AviTeam, with LCA, we can assess the mitigation potential of a fleetwide use of alternative aviation fuels on 210 000 shorter haul flights. In an optimistic case, liquid hydrogen (LH2) and power-to-liquid fuels, when produced with renewable electricity, may reduce emissions by about 950 GgCO2eq when assessed with the GWP100 metric and including non-CO2 impacts for all flights considered. Mitigation potentials range from 44% on shorter flights to 56% on longer flights. Alternative aviation fuels' mitigation potential is limited because of short-lived climate forcings and additional fuel demand to accommodate LH2 fuel. Our results highlight the importance of integrating system models into LCAs and are of value to researchers and decision-makers engaged in climate change mitigation in the aviation and transport sectors.

H*ads dynamics engineering via bimetallic Pd-Cu@MXene catalyst for enhanced electrocatalytic hydrodechlorination.

Electrocatalytic hydrodechlorination (EHDC) is a promising approach to safely remove halogenated emerging contaminants (HECs) pollutants. However, sluggish production dynamics of adsorbed atomic H (H*ads) limit the applicability of this green process. In this study, bimetallic Pd-Cu@MXene catalysts were synthesized to achieve highly efficient removal of HECs. The alloy electrode (Pd-Cu@MX/CC) exhibited better EHDC performance in comparison to Pd@MX/CC electrode, resulting in diclofenac degradation efficiency of 93.3 ± 0.1%. The characterization analysis revealed that the Pd0/PdII ratio decreased by forming bimetallic Pd-Cu alloy. Density functional theory calculations further demonstrated the electronic configuration modulation of the Pd-Cu@MXene catalysts, optimizing binging energies for H* and thereby facilitating H*ads production and tuning the reduction capability of H*ads. Noteably, the amounts and reduction potential of H*ads for Pd-Cu@MXene catalysts were 1.5 times higher and 0.37 eV lower than those observed for the mono Pd electrode. Hence, the introduction of Cu into the Pd catalyst optimized the dynamics of H*ads production, thereby conferring significant advantages to EHDC reactions. This augmentation was underscored by the successful application of the alloy catalysts supported by MXene in EHDC experiments involving other HECs, which represented a new paradigm for EHDC for efficient recalcitrant pollutant removal by H*ads.

Assisted Robots in Therapies for Children with Autism in Early Childhood.

Children with autism spectrum disorder (ASD) have deficits that affect their social relationships, communication, and flexibility in reasoning. There are different types of treatment (pharmacological, educational, psychological, and rehabilitative). Currently, one way to address this problem is by using robotic systems to address the abilities that are altered in these children. The aim of this review will be to analyse the effectiveness of the incorporation of the different robotic systems currently existing in the treatment of children up to 10 years of age diagnosed with autism. A systematic review has been carried out in the PubMed, Scopus, Web of Science, and Dialnet databases, with the following descriptors: child, autism, and robot. The search yielded 578 papers, and nine were selected after the application of the PRISMA guideline. The quality of the studies was analysed with the PEDRo scale, and only those with a score between four and six were selected. From this study, the conclusion is that the use of robots, in general, improves children's behaviour in the short term, but longer-term experiences are necessary to achieve more conclusive results.

The Effects of Speed and Delays on Test-Time Performance of End-to-End Self-Driving.

This study investigates the effects of speed variations and computational delays on the performance of end-to-end autonomous driving systems (ADS). Utilizing 1:10 scale mini-cars with limited computational resources, we demonstrate that different driving speeds significantly alter the task of the driving model, challenging the generalization capabilities of systems trained at a singular speed profile. Our findings reveal that models trained to drive at high speeds struggle with slower speeds and vice versa. Consequently, testing an ADS at an inappropriate speed can lead to misjudgments about its competence. Additionally, we explore the impact of computational delays, common in real-world deployments, on driving performance. We present a novel approach to counteract the effects of delays by adjusting the target labels in the training data, demonstrating improved resilience in models to handle computational delays effectively. This method, crucially, addresses the effects of delays rather than their causes and complements traditional delay minimization strategies. These insights are valuable for developing robust autonomous driving systems capable of adapting to varying speeds and delays in real-world scenarios.

Adversarial Attacks against Deep-Learning-Based Automatic Dependent Surveillance-Broadcast Unsupervised Anomaly Detection Models in the Context of Air Traffic Management.

Deep learning has shown significant advantages in Automatic Dependent Surveillance-Broadcast (ADS-B) anomaly detection, but it is known for its susceptibility to adversarial examples which make anomaly detection models non-robust. In this study, we propose Time Neighborhood Accumulation Iteration Fast Gradient Sign Method (TNAI-FGSM) adversarial attacks which fully take into account the temporal correlation of an ADS-B time series, stabilize the update directions of adversarial samples, and escape from poor local optimum during the process of iterating. The experimental results show that TNAI-FGSM adversarial attacks can successfully attack ADS-B anomaly detection models and improve the transferability of ADS-B adversarial examples. Moreover, the TNAI-FGSM is superior to two well-known adversarial attacks called the Fast Gradient Sign Method (FGSM) and Basic Iterative Method (BIM). To the best of our understanding, we demonstrate, for the first time, the vulnerability of deep-learning-based ADS-B time series unsupervised anomaly detection models to adversarial examples, which is a crucial step in safety-critical and cost-critical Air Traffic Management (ATM).

Prolonged Heat Stress during Winter Diapause Alters the Expression of Stress-Response Genes in Ostrinia nubilalis (Hbn.).

During diapause, a state of temporarily arrested development, insects require low winter temperatures to suppress their metabolism, conserve energy stores and acquire cold hardiness. A warmer winter could, thus, reduce diapause incidence and duration in many species, prematurely deplete their energy reserves and compromise post-diapause fitness. In this study, we investigated the combined effects of thermal stress and the diapause program on the expression of selected genes involved in antioxidant defense and heat shock response in the European corn borer Ostrinia nubilalis. By using qRT-PCR, it has been shown that response to chronic heat stress is characterized by raised mRNA levels of grx and trx, two important genes of the antioxidant defense system, as well as of hsp70 and, somewhat, of hsp90, two major heat shock response proteins. On the other hand, the expression of hsc70, hsp20.4 and hsp20.1 was discontinuous in the latter part of diapause, or was strongly controlled by the diapause program and refractory to heat stress, as was the case for mtn and fer, genes encoding two metal storage proteins crucial for metal ion homeostasis. This is the first time that the effects of high winter temperatures have been assessed on cold-hardy diapausing larvae and pupae of this important corn pest.

Towards the establishment of national diagnostic reference levels for abdomen, KUB, and lumbar spine x-ray examinations in Sri Lanka: a multi-centric study.

Diagnostic reference levels (DRLs) and achievable doses (ADs) provide guidance to optimise radiation doses for patients undergoing medical imaging procedures. This multi-centre study aimed to compare institutional DRLs (IDRLs) across hospitals, propose ADs and multi-centric DRLs (MCDRLs) for four common x-ray examinations in Sri Lanka, and assess the potential for dose reduction. A prospective cross-sectional study of 894 adult patients referred for abdomen anteroposterior (AP), kidney-ureter-bladder (KUB) AP, lumbar spine AP, and lumbar spine lateral (LAT) x-ray examinations was conducted. Patient demographic information (age, sex, weight, BMI) and exposure parameters (tube voltage, tube current-exposure time product) were collected. Patient dose indicators were measured in terms of kerma-area product (PKA) using a PKAmeter. IDRLs, ADs, and MCDRLs were calculated following the International Commission on Radiological Protection guidelines, with ADs and MCDRLs defined as the 50th and 75th percentiles of the median PKAdistributions, respectively. IDRL ranges varied considerably across hospitals: 1.42-2.42 Gy cm2for abdomen AP, 1.51-2.86 Gy cm2for KUB AP, 0.83-1.65 Gy cm2for lumbar spine AP, and 1.76-4.10 Gy cm2for lumbar spine LAT. The proposed ADs were 1.82 Gy cm2(abdomen AP), 2.03 Gy cm2(KUB AP), 1.27 Gy cm2(lumbar spine AP), and 2.21 Gy cm2(lumbar spine LAT). MCDRLs were 2.24 Gy cm2(abdomen AP), 2.40 Gy cm2(KUB AP), 1.43 Gy cm2(lumbar spine AP), and 2.38 Gy cm2(lumbar spine LAT). Substantial intra- and inter-hospital variations in PKAwere observed for all four examinations. Although ADs and MCDRLs in Sri Lanka were comparable to those in the existing literature, the identified intra- and inter-hospital variations underscore the need for dose reduction without compromising diagnostic information. Hospitals with high IDRLs are recommended to review and optimise their practices. These MCDRLs serve as preliminary national DRLs, guiding dose optimisation efforts by medical professionals and policymakers.

Effects of supplementation of different selenium sources on lipid profile, selenium, and vitamin E concentration of yolk.

Egg preference as a source of protein also provides beneficial fatty acids, vital for human consumption. However, rich in lipid products are prone to oxidative damage. The study aims to determine the effect of supplementing biogenic selenium (Se) from Stenotrophomonas maltophilia, ADS18 (ADS18) in laying hens' diet on yolk lipid oxidation status (MDA), beta-carotene (ß-carotene) content, cholesterol, fatty acids, Se, and vitamin E (VE) level. A total of one hundred and twenty (120) laying hens of Lohmann Brown strains aged 50 weeks, weighing 1500 to 2000 g were reared individually in A-shape two-tier stainless-steel cages sized 30 cm x 50 cm x 40 cm (width, depth height). The hens were randomly allotted into four treatments with six replications in a complete randomised design for the period of 12 weeks. The basal diet contains 100 mg/kg VE. Treatment diets consist of basal diet as control, SS containing 0.3 mg/kg sodium selenite, Se-yeast containing 0.3 mg/kg selenised yeast, and VADS18 containing 0.3 mg/kg of ADS18. Forty-eight eggs were collected and freeze-dried biweekly for analysis. The results of the present study showed that hens supplemented ADS18 had significantly (P < 0.05) lower MDA and cholesterol levels while their egg yolks had higher levels of Se and mono-unsaturated fatty acids (MUFA). The control group had significantly (P < 0.05) higher saturated fatty acid (SFA) contents than the VE and dietary Se-supplemented groups, while the ADS18 group had the lowest SFA contents. Conversely, in comparison to the inorganic and control groups, the VE content of the egg yolk was significantly (P < 0.05) higher in organic Se-supplemented (Se-yeast and VADS18) groups. Hens with SS supplementation had significantly (P < 0.05) higher egg yolk ß-carotene content. When compared to other treatment groups, the control group had higher (P < 0.05) polyunsaturated fatty acids (PUFA) content. The ADS18 is therefore deemed comparable to other Se sources. To prevent Se toxicity, however, a better understanding of the levels of ADS18 incorporation in poultry diets is required.

Intra-Beam Interference Mitigation for the Downlink Transmission of the RIS-Assisted Hybrid Millimeter Wave System.

Millimeter-wave (mmWave) communication systems leverage the directional beamforming capabilities of antenna arrays equipped at the base stations (BS) to counteract the inherent high propagation path loss characteristic of mmWave channels. In downlink mmWave transmissions, i.e., from the BS to users, distinguishing users within the same beam direction poses a significant challenge. Additionally, digital baseband precoding techniques are limited in their ability to mitigate inter-user interference within identical beam directions, representing a fundamental constraint in mmWave downlink transmissions. This study introduces an innovative analog beamforming-based interference mitigation strategy for downlink transmissions in reconfigurable intelligent surface (RIS)-assisted hybrid analog-digital (HAD) mmWave systems. This is achieved through the joint design of analog beamformers and the corresponding coefficients at both the RIS and the BS. We first present derived closed-form approximation expressions for the achievable rate performance in the proposed scenario and establish a stringent upper bound on this performance in a large number of RIS elements regimes. The exclusive use of analog beamforming in the downlink phase allows our proposed transmission algorithm to function efficiently when equipped with low-resolution analog-to-digital/digital-to-analog converters (A/Ds) at the BS. The energy efficiency of the downlink transmission is evaluated through the deployment of six-bit A/Ds and six-bit pulse-amplitude modulation (PAM) signals across varying numbers of activated RIS elements. Numerical simulation results validate the effectiveness of our proposed algorithms in comparison to various benchmark schemes.

The uniform Kruskal theorem: between finite combinatorics and strong set existence.

The uniform Kruskal theorem extends the original result for trees to general recursive data types. As shown by Freund, Rathjen and Weiermann (Freund, Rathjen, Weiermann 2022 Adv. Math. 400, 108265 (doi:10.1016/j.aim.2022.108265)), it is equivalent to [Formula: see text]-comprehension, over [Formula: see text] with the ascending descending sequence principle ([Formula: see text]). This result provides a connection between finite combinatorics and abstract set existence. The present article sheds further light on this connection. Firstly, we show that the original Kruskal theorem is equivalent to the uniform version for data types that are finitely generated. Secondly, we prove a dichotomy result for a natural variant of the uniform Kruskal theorem. On the one hand, this variant still implies [Formula: see text]-comprehension over [Formula: see text] extended by the chain antichain principle ([Formula: see text]). On the other hand, it becomes weak when [Formula: see text] is removed from the base theory. This article is part of the theme issue 'Modern perspectives in Proof Theory'.

Understanding Recruitment Yield From Social Media Advertisements and Associated Costs of a Telehealth Randomized Controlled Trial: Descriptive Study.

BACKGROUND: Recruiting study participants for clinical research is a challenging yet essential task. Social media platforms, such as Facebook, offer the opportunity to recruit participants through paid advertisements. These ad campaigns may be a cost-effective approach to reaching and recruiting participants who meet specific study criteria. However, little is known about the extent to which clicks on social media advertisements translate to the actual consent and enrollment of participants who meet the study criteria. Understanding this is especially important for clinical trials conducted remotely, such as telehealth-based studies, which open the possibility to recruit over large geographical areas and are becoming more common for the treatment of chronic health conditions, such as osteoarthritis (OA). OBJECTIVE: The aim of this study was to report on the conversion of clicks on a Facebook advertisement campaign to consent to enrollment in an ongoing telehealth physical therapy study for adults with knee OA, and the costs associated with recruitment. METHODS: This was a secondary analysis using data collected over the first 5 months of an ongoing study of adults with knee OA. The Delaware Physical Exercise and Activity for Knee Osteoarthritis program compares a virtually delivered exercise program to a control group receiving web-based resources among adults with knee OA. Advertisement campaigns were configured on Facebook to reach an audience who could be potentially eligible. Clicking on the advertisement directed potential participants to a web-based screening form to answer 6 brief questions related to the study criteria. Next, a research team member called individuals who met the criteria from the screening form and verbally asked additional questions related to the study criteria. Once considered eligible, an electronic informed consent form (ICF) was sent. We described the number of potential study participants who made it through each of these steps and then calculated the cost per participant who signed the ICF. RESULTS: In sum, between July and November 2021, a total of 33,319 unique users saw at least one advertisement, 9879 clicks were made, 423 web-based screening forms were completed, 132 participants were successfully contacted, 70 were considered eligible, and 32 signed the ICF. Recruitment costed an average of US $51.94 per participant. CONCLUSIONS: While there was a low conversion from clicks to actual consent, 32% (32/100) of the total sample required for the study were expeditiously consented over 5 months with a per-subject cost well below traditional means of recruitment, which ranges from US $90 to US $1000 per participant. TRIAL REGISTRATION: Clinicaltrails.gov NCT04980300; https://clinicaltrials.gov/ct2/show/NCT04980300.

Testing Multiple Methods to Effectively Promote Use of a Knowledge Portal to Health Policy Makers: Quasi-Experimental Evaluation.

BACKGROUND: Health policy makers and advocates increasingly utilize online resources for policy-relevant knowledge. Knowledge brokering is one potential mechanism to encourage the use of research evidence in policy making, but the mechanisms of knowledge brokerage in online spaces are understudied. This work looks at knowledge brokerage through the launch of Project ASPEN, an online knowledge portal developed in response to a New Jersey legislative act that established a pilot program for adolescent depression screening for young adults in grades 7-12. OBJECTIVE: This study compares the ability to drive policy brief downloads by policy makers and advocates from the Project ASPEN knowledge portal using a variety of online methods to promote the knowledge portal. METHODS: The knowledge portal was launched on February 1, 2022, and a Google Ad campaign was run between February 27, 2022, and March 26, 2022. Subsequently, a targeted social media campaign, an email campaign, and tailored research presentations were used to promote the website. Promotional activities ended on May 31, 2022. Website analytics were used to track a variety of actions including new users coming to the website, page views, and policy brief downloads. Statistical analysis was used to assess the efficacy of different approaches. RESULTS: The campaign generated 2837 unique user visits to the knowledge portal and 4713 page views. In addition, the campaign generated 6.5 policy web page views/day and 0.7 policy brief downloads/day compared with 1.8 views/day and 0.5 downloads/day in the month following the campaign. The rate of policy brief page view conversions was significantly higher for Google Ads compared with other channels such as email (16.0 vs 5.4; P<.001) and tailored research presentations (16.0 vs 0.8; P<.001). The download conversion rate for Google Ads was significantly higher compared with social media (1.2 vs 0.1; P<.001) and knowledge brokering activities (1.2 vs 0.2; P<.001). By contrast, the download conversion rate for the email campaign was significantly higher than that for social media (1.0 vs 0.1; P<.001) and tailored research presentations (1.0 vs 0.2; P<.001). While Google Ads for this campaign cost an average of US $2.09 per click, the cost per conversion was US $11 per conversion to drive targeted policy web page views and US $147 per conversion to drive policy brief downloads. While other approaches drove less traffic, those approaches were more targeted and cost-effective. CONCLUSIONS: Four tactics were tested to drive user engagement with policy briefs on the Project ASPEN knowledge portal. Google Ads was shown to be effective in driving a high volume of policy web page views but was ineffective in terms of relative costs. More targeted approaches such as email campaigns and tailored research presentations given to policy makers and advocates to promote the use of research evidence on the knowledge portal website are likely to be more effective when balancing goals and cost-effectiveness.

Original and Low-Cost ADS-B System to Fulfill Air Traffic Safety Obligations during High Power LIDAR Operation.

LIDAR is an atmospheric sounding instrument based on the use of high-power lasers. The use of these lasers involves fulfilling obligations with respect to air safety. In this article, we present a low-cost air traffic surveillance solution integrated into an automated operating system for the Rayleigh-Mie-Raman LIDAR of Clermont Ferrand and the statistical elements of its application over more than two years of operation from September 2019 to March 2022. Air traffic surveillance that includes the possibility of shutting off lasers is required by international regulations because LIDAR is equipped with a class four laser that presents potential dangers to aircraft flying overhead. The original system presented in this article is based on software-defined radio. ADS-B transponder frames are analyzed in real-time, and laser emission is stopped during LIDAR operation when an aircraft is detected within a 2 km radius around the LIDAR. The system was accredited in 2019 by the French air traffic authorities. Laser shutdowns due to the detection of aircraft near the Clermont Ferrand LIDAR caused a data loss rate of less than 2% during the period of application.

Performance Analysis of Lambda Architecture-Based Big-Data Systems on Air/Ground Surveillance Application with ADS-B Data.

This study introduces a novel methodology designed to assess the accuracy of data processing in the Lambda Architecture (LA), an advanced big-data framework qualified for processing streaming (data in motion) and batch (data at rest) data. Distinct from prior studies that have focused on hardware performance and scalability evaluations, our research uniquely targets the intricate aspects of data-processing accuracy within the various layers of LA. The salient contribution of this study lies in its empirical approach. For the first time, we provide empirical evidence that validates previously theoretical assertions about LA, which have remained largely unexamined due to LA's intricate design. Our methodology encompasses the evaluation of prospective technologies across all levels of LA, the examination of layer-specific design limitations, and the implementation of a uniform software development framework across multiple layers. Specifically, our methodology employs a unique set of metrics, including data latency and processing accuracy under various conditions, which serve as critical indicators of LA's accurate data-processing performance. Our findings compellingly illustrate LA's "eventual consistency". Despite potential transient inconsistencies during real-time processing in the Speed Layer (SL), the system ultimately converges to deliver precise and reliable results, as informed by the comprehensive computations of the Batch Layer (BL). This empirical validation not only confirms but also quantifies the claims posited by previous theoretical discourse, with our results indicating a 100% accuracy rate under various severe data-ingestion scenarios. We applied this methodology in a practical case study involving air/ground surveillance, a domain where data accuracy is paramount. This application demonstrates the effectiveness of the methodology using real-world data-intake scenarios, therefore distinguishing this study from hardware-centric evaluations. This study not only contributes to the existing body of knowledge on LA but also addresses a significant literature gap. By offering a novel, empirically supported methodology for testing LA, a methodology with potential applicability to other big-data architectures, this study sets a precedent for future research in this area, advancing beyond previous work that lacked empirical validation.

Precision Joint RF Measurement of Inter-Satellite Range and Time Difference and Scalable Clock Synchronization for Multi-Microsatellite Formations.

The rapid development of multi-satellite formations requires inter-satellite radio frequency (RF) measurement to be both precise and scalable. The navigation estimation of multi-satellite formations using a unified time reference demands the simultaneous RF measurement of the inter-satellite range and time difference. However, high-precision inter-satellite RF ranging and time difference measurements are investigated separately in existing studies. Different from the conventional two-way ranging (TWR) method, which is limited by its reliance on a high-performance atomic clock and navigation ephemeris, asymmetric double-sided two-way ranging (ADS-TWR)-based inter-satellite measurement schemes can eliminate such reliance while ensuring measurement precision and scalability. However, ADS-TWR was originally proposed for ranging-only applications. In this study, by fully exploiting the time-division non-coherent measurement characteristic of ADS-TWR, a joint RF measurement method is proposed to obtain the inter-satellite range and time difference simultaneously. Moreover, a multi-satellite clock synchronization scheme is proposed based on the joint measurement method. The experimental results show that when inter-satellite ranges are hundreds of kilometers, the joint measurement system has a centimeter-level accuracy for ranging and a hundred-picosecond-level accuracy for time difference measurement, and the maximum clock synchronization error was only about 1 ns.

A Hybrid Approach for Alluring Ads Phishing Attack Detection Using Machine Learning.

Phishing attacks are evolving with more sophisticated techniques, posing significant threats. Considering the potential of machine-learning-based approaches, our research presents a similar modern approach for web phishing detection by applying powerful machine learning algorithms. An efficient layered classification model is proposed to detect websites based on their URL structure, text, and image features. Previously, similar studies have used machine learning techniques for URL features with a limited dataset. In our research, we have used a large dataset of 20,000 website URLs, and 22 salient features from each URL are extracted to prepare a comprehensive dataset. Along with this, another dataset containing website text is also prepared for NLP-based text evaluation. It is seen that many phishing websites contain text as images, and to handle this, the text from images is extracted to classify it as spam or legitimate. The experimental evaluation demonstrated efficient and accurate phishing detection. Our layered classification model uses support vector machine (SVM), XGBoost, random forest, multilayer perceptron, linear regression, decision tree, naïve Bayes, and SVC algorithms. The performance evaluation revealed that the XGBoost algorithm outperformed other applied models with maximum accuracy and precision of 94% in the training phase and 91% in the testing phase. Multilayer perceptron also worked well with an accuracy of 91% in the testing phase. The accuracy results for random forest and decision tree were 91% and 90%, respectively. Logistic regression and SVM algorithms were used in the text-based classification, and the accuracy was found to be 87% and 88%, respectively. With these precision values, the models classified phishing and legitimate websites very well, based on URL, text, and image features. This research contributes to early detection of sophisticated phishing attacks, enhancing internet user security.

Low-Power Long-Term Ambulatory Electrocardiography Monitor of Three Leads with Beat-to-Beat Heart Rate Measurement in Real Time.

A low-power long-term ambulatory ECG monitor was developed for the acquisition, storage and processing of three simultaneous leads DI, aVF and V2 with a beat-to-beat heart rate measurement in real time. It provides long-term continuous ECG recordings until 84 h. The monitor uses a QRS complex detection algorithm based on the continuous wavelet transform with splines, which automatically selects the scale for the analysis of ECG records with different sampling frequencies. It includes a lead-off detection to continuously monitor the electrode connections and a real-time system of visual and acoustic alarms to alert users of abnormal conditions in its operation. The monitor presented is based in an ADS1294 analogue front end with four channels, 24-bit analog-to-digital converters and programmable gain amplifiers, a low-power dual-core ESP32 microcontroller, a microSD memory for data storage in a range of 4 GB to 32 GB and a 1.4 in thin-film transistor liquid crystal display (LCD) variant with a resolution of 128 × 128 pixels. It has programmable sampling rates of 250, 500 and 1000 Hz; a bandwidth of 0 Hz to 50% of the selected sampling rate; a CMRR of -105 dB; an input margin of ±2.4 V; a resolution of 286 nV; and a current consumption of 50 mA for an average battery life of 84 h. The ambulatory ECG monitor was evaluated with the commercial data-acquisition system BIOPAC MP36 and its module for ECG LABEL SS2LB, simultaneously comparing the morphologies of two ECG records and obtaining a correlation of 91.78%. For the QRS detection in real time, the implemented algorithm had an error less than 5%. The developed ambulatory ECG monitor can be used for the analysis of the dynamics of the heart rate variability in long-term ECG records and for the development of one's own databases of ECG recordings of normal subjects and patients with cardiovascular and noncardiovascular diseases.

Analyzing Factors Influencing Situation Awareness in Autonomous Vehicles-A Survey.

Autonomous driving of higher automation levels asks for optimal execution of critical maneuvers in all environments. A crucial prerequisite for such optimal decision-making instances is accurate situation awareness of automated and connected vehicles. For this, vehicles rely on the sensory data captured from onboard sensors and information collected through V2X communication. The classical onboard sensors exhibit different capabilities and hence a heterogeneous set of sensors is required to create better situation awareness. Fusion of the sensory data from such a set of heterogeneous sensors poses critical challenges when it comes to creating an accurate environment context for effective decision-making in AVs. Hence this exclusive survey analyses the influence of mandatory factors like data pre-processing preferably data fusion along with situation awareness toward effective decision-making in the AVs. A wide range of recent and related articles are analyzed from various perceptive, to pick the major hiccups, which can be further addressed to focus on the goals of higher automation levels. A section of the solution sketch is provided that directs the readers to the potential research directions for achieving accurate contextual awareness. To the best of our knowledge, this survey is uniquely positioned for its scope, taxonomy, and future directions.

Using aircraft tracking data to estimate the geographic scope of noise impacts from low-level overflights above parks and protected areas.

Sightseeing air tours have proven to be a challenging management issue for many tourist destinations around the world, especially at locations meant to protect natural and cultural resources and wilderness character. Two of the primary challenges with managing air tours are a lack of information about their travel patterns and how such patterns result in a measurable noise impact to listeners. Recent studies have highlighted the usefulness of newer technology for tracking aircraft travel patterns, particularly over national parks. In this synthesis, we pair aircraft tracks with acoustic data using a quantitative observer-based audibility modelling software toolkit. The findings delimit the long-term geographic scope of audibility for specific aircraft noise sources above landscapes of Hawai'i Volcanoes and Denali National Parks, U.S. and identify practical, 3-dimensional offset distances that can be used to reduce the functional effects of air tour noise in terms of sound level.

Two-part vowel modifications in Child Directed Speech in Warlpiri may enhance child attention to speech and scaffold noun acquisition.

Study 1 compared vowels in Child Directed Speech (CDS; child ages 25-46 months) to vowels in Adult Directed Speech (ADS) in natural conversation in the Australian Indigenous language Warlpiri, which has three vowels (/i/, /a/, /u). Study 2 compared the vowels of the child interlocutors from Study 1 to caregiver ADS and CDS. Study 1 indicates that Warlpiri CDS vowels are characterised by fronting, /a/-lowering, f o -raising, and increased duration, but not vowel space expansion. Vowels in CDS nouns, however, show increased between-contrast differentiation and reduced within-contrast variation, similar to what has been reported for other languages. We argue that this two-part CDS modification process serves a dual purpose: Vowel space shifting induces IDS/CDS that sounds more child-like, which may enhance child attention to speech, while increased between-contrast differentiation and reduced within-contrast variation in nouns may serve didactic purposes by providing high-quality information about lexical specifications. Study 2 indicates that Warlpiri CDS vowels are more like child vowels, providing indirect evidence that aspects of CDS may serve non-linguistic purposes simultaneously with other aspects serving linguistic-didactic purposes. The studies have novel implications for the way CDS vowel modifications are considered and highlight the necessity of naturalistic data collection, novel analyses, and typological diversity.