Search Results (62)

The goal of newborn screening (NBS) has remained the same despite its significant expansion from its inception as a public health initiative. This goal is to identify infants that are at risk for a set list of conditions and to implement a care plan to prevent, delay, or mitigate adverse health outcomes for those affected. The role of genetic counselors (GCs) in the NBS space is currently evolving, and there is limited research on parental experiences with genetic counseling for more recently added conditions on a list approved by the U.S. Secretary of Health and Human Services called the Recommended Uniform Screening Panel (RUSP). This qualitative study interviewed parents who have spoken to a genetic counselor after their child was diagnosed with one of three following conditions in the past five years: Pompe disease, X-linked Adrenoleukodystrophy, and Spinal Muscular Atrophy. A total of 13 interviews were conducted and results were organized into five thematic areas: (1) NBS/Results Disclosure, (2) Diagnostic Process after NBS, (3) Treatment/Follow-Up, (4) Communication, and (5) Holistic Support. The findings of this study highlighted parental preferences for early involvement of genetic counselors, provider, and parent education on NBS, and the provision of family support beyond genetic resources. Full article

U-Space, the European Union’s legal framework for enabling drone traffic in low altitude, has implications extending beyond airspace management, particularly on the sustainable development of urban areas. This article presents a case study involving regional and local level representatives, examining anticipated concerns and strategic interests, as well as managing requirements in urban U-Space planning. Following a three-stage capacity building process conducted in the German federal state of Hamburg, the results specify ambitions for enhancing economic attractiveness coupled with locally embedded visions for improved public service provision. Instruments that have shown apposite in the given setting to address concerns surrounding public order and security, as well as the impairment of area functions, are presented. The challenges of implementing U-Space in alignment with societal expectations are outlined. Based on the discussion of these findings, recommendations for local-level capacity-building policy and the multi-level governance of U-Space are derived. Full article

This study investigates the determinants of Romanian workers’ migration intentions towards Italy, integrating economic, social, and psychological perspectives. Based on a sample of 358 respondents, four hypotheses were tested concerning perceived living standards, working conditions, quality of public services, and anticipated integration difficulties. Data were analysed using descriptive statistics, Spearman’s rho correlation, Mann–Whitney U, Chi-square, ANOVA, and ordinal logistic regression. The results confirm that higher perceived living standards and better working conditions in Italy significantly increase the likelihood of expressing migration intentions, while favourable evaluations of healthcare and education act as additional pull factors. Conversely, anticipated integration difficulties, particularly language barriers and cultural adaptation, reduce migration intentions, indicating that socio-psychological obstacles can counterbalance economic incentives. By combining non-parametric and multivariate analyses, the study demonstrates that migration is a multidimensional process shaped not only by structural opportunities but also by behavioural and psychological appraisals. These findings are consistent with recent research on European labour mobility and contribute to the literature by highlighting the role of subjective perceptions in shaping migration decisions. Implications for policy include the need to address both economic disparities and integration barriers to support more balanced mobility within the European space. Full article

College websites are a primary source of information for prospective students. As increasing numbers of autistic students head to college, we wanted to capture whether and how college websites were presenting themselves as autism-friendly or autism-aware environments. This is a descriptive study of how college websites from liberal arts institutions in the U.S. talk about autism. The top 50 liberal arts schools, as ranked by the US World and News Report from 2023, were searched for the following terms: “autism”, “autistic”, “ASD”, “neurodiversity”, “neurodivergent”, and “neurodivergence.” Five website areas where these terms may appear, or where prospective students may look for them, were identified: admissions, accessibility, counseling/mental health, faculty resources, and student life. Overall, the occurrence of any searched terms was extremely low across all areas. This lack of terminology representation likely reflects the reality of autism-related services on these campuses. On some websites, mentions of autism did not reflect a deeper cultural understanding of the term. The lack of representation of and information about autism and neurodiversity on college websites should be a call to these types of institutions that there are a number of students whose identities are not being recognized by these academic spaces. Full article

With the expected increase in drone operations, inter-operator fairness issues and congestion problems are expected to arise due to the strategic authorization approach mandated in European regulation. As an alternative, the proposed authorization method is based on a deferred authorization decision with multiple-priority classes that are gate-kept by a series of scarce flight tokens. In it, operators can guide the aerial traffic deconfliction process by indicating the criticality of each operation (i.e., selected priority class) based on their business logic and the available flight tokens. Scarce token distribution is performed by a centralized service following a fairness- or congestion-management policy defined by authorities. Also, geographical and temporal incentives can be considered using a 4D-dependent temporal airspace cost to compute the required number of tokens per flight. Results based on several simulation scenarios demonstrate the validity of the approach and its capability in prioritizing different operators’ behaviors (fairness management) or avoiding flight hotspots (congestion management). Overall, it is concluded that the proposed method is an efficient, fair, simple and scalable novel authorization process that can be integrated into the U-space ecosystem. Full article

Driven by the rapid development of e-commerce and intelligent logistics, the volume of express delivery services has surged, making the efficient and accurate identification of shipping information a core requirement for automatic sorting systems. However, traditional Optical Character Recognition (OCR) technology struggles to meet the accuracy and real-time demands of complex logistics scenarios due to challenges such as image distortion, uneven illumination, and field overlap. This paper proposes a three-level collaborative recognition method based on deep learning that facilitates structured information extraction through regional normalization, dual-path parallel extraction, and a dynamic matching mechanism. First, the geometric distortion associated with contour detection and the lightweight direction classification model has been improved. Second, by integrating the enhanced YOLOv5s for key area localization with the upgraded PaddleOCR for full-text character extraction, a dual-path parallel architecture for positioning and recognition has been constructed. Finally, a dynamic space–semantic joint matching module has been designed that incorporates anti-offset IoU metrics and hierarchical semantic regularization constraints, thereby enhancing matching robustness through density-adaptive weight adjustment. Experimental results indicate that the accuracy of this method on a self-constructed dataset is 89.5%, with an F1 score of 90.1%, representing a 24.2% improvement over traditional OCR methods. The dynamic matching mechanism elevates the average accuracy of YOLOv5s from 78.5% to 89.7%, surpassing the Faster R-CNN benchmark model while maintaining a real-time processing efficiency of 76 FPS. This study offers a lightweight and highly robust solution for the efficient extraction of order information in complex logistics scenarios, significantly advancing the intelligent upgrading of sorting systems. Full article

In the U-Space environment, seamless communication between key stakeholders—such as U-Space Service Providers (USSP), Common Information Service Providers (CISP), and drone operators—is very important for the safe and efficient management of Unmanned Aerial Vehicle (UAV) operations. A major challenge in this context is minimizing communication latency, which directly affects the performance of time-sensitive services. This study investigates latency issues by evaluating two communication protocols: push–pull (using REST-API and ZeroMQ) and publish–subscribe (using AMQP and MQTT). Through a case study focused on drone detection, the research examines latency across critical operational activities, including conformance monitoring, flight plan confirmation, and the transmission of alerts via the USSP system under varying message intervals and payload sizes. The results indicate that while message interval has a significant influence on latency, message size has a minimal effect. Furthermore, the push–pull protocols consistently deliver lower and more stable latency compared to publish–subscribe protocols under the tested conditions. Both approaches, however, achieve latency levels that align with EASA’s operational requirements for U-Space systems. Full article

The CORUS-XUAM project defined three two-way U-space corridors linking Frankfurt Airport’s Terminal 2 on the city outskirts with the city-center Trade Fair. These corridors avoid the approach cones of the northern and central runways and bypass hospital no-fly zones and large buildings. In our previous studies, we first used fast-time simulations to evaluate the U-space routing and its operating concept, based on historical air traffic data. Included were arriving and departing airplanes as well as police, and medical helicopters throughout the city. The focus was on the limitations of the airspace, avoiding conflicts with other airspace users and between the airtaxis using a different corridor or delaying the departure, as well as determining the throughput potential of such a corridor system. Building on our previous studies, this study incorporates higher-fidelity traffic simulation data and an updated demand analysis for the airtaxi shuttle service. Our new sizing analysis reveals that ground operations typically, not airspace capacity, constitute the primary bottleneck. Full article

In this paper, we propose and prove an innovative radar antenna concept suitable for collision avoidance (CA) systems installed onboard small, unmanned aircraft (UA). The proposed architecture provides 360° monopulse coverage around the host platform, enabling the detection and accurate position estimation of airborne, non-cooperative intruders using lightweight, low-profile antennas. These antennas can be manufactured using low-cost 3D printing techniques and are easily integrated into the UA airframe without compromising airworthiness. We present a Detect and Avoid (DAA) concept of operations (ConOps) aligned with the SESAR U-space ConOps, Edition 4. In this ConOps, the Remain Well Clear (RWC) and CA functions are treated separately: RWC is the responsibility of ground-based U-space services, while CA is implemented as an airborne safety net using onboard equipment. Based on this framework, we derive operation-centric design requirements and propose an antenna architecture based on a fixed circular array of sector waveguides. This solution overcomes key limitations of existing radar antennas for UAS CA systems by providing a wider field of view, higher power handling, and reduced mechanical complexity and cost. We prove the proposed concept through a combination of simulations and measurements conducted in an anechoic chamber using a 24 GHz prototype. Full article

This study presents a system framework by which cloud resources are utilized to analyze crop germination status in a 2U CubeSat. This research aims to address the onboard computing constraints in nanosatellite missions to boost space agricultural practices. Through the Espressif Simple Protocol for Network-on-Wireless (ESP-NOW) technology, communication between ESP-32 modules were established. The corresponding sensor readings and image data were securely streamed through Amazon Web Service Internet of Things (AWS IoT) to an ESP-NOW receiver and Roboflow. Real-time plant growth predictor monitoring was implemented through the web application provisioned at the receiver end. On the other hand, sprouts on germination bed were determined through the custom-trained Roboflow computer vision model. The feasibility of remote data computational analysis and monitoring for a 2U CubeSat, given its minute form factor, was successfully demonstrated through the proposed cloud framework. The germination detection model resulted in a mean average precision (mAP), precision, and recall of 99.5%, 99.9%, and 100.0%, respectively. The temperature, humidity, heat index, LED and Fogger states, and bed sprouts data were shown in real time through a web dashboard. With this use case, immediate actions can be performed accordingly when abnormalities occur. The scalability nature of the framework allows adaptation to various crops to support sustainable agricultural activities in extreme environments such as space farming. Full article

Nearly 50% of single homeless adults are over the age of 50, and adults aged 50 years and older are the fastest growing subpopulation of the homeless in the U.S. This subpopulation has unique mobility needs and barriers to transportation. We used rapid ethnographic assessments to explore the practices, needs, perceptions, and values of unhoused older adults in relation to their efforts to access and navigate health and social services via public transit. We conducted 23 observations of 12 participants as they navigated public transit to meet their travel needs. Our data consist of 65 h of observations with field notes, walking interviews, and travel diaries. Two themes—waiting and friction—encompassed participants’ experiences of mobility and their ongoing negotiations that involved time, space, individual ability, and interpersonal interactions within their environmental context. For this population, attainment of housing and improved health and well-being is contingent on access to reliable transportation—a condition that is not met in many communities. For the participants in our study, the physical demands of accessing public transit combined with the cognitive load of interpreting multi-step directions in specific time schedules were often insurmountable. The public transit system was often hostile, such that participants were stigmatized and segregated. Professionals who work with older homeless individuals must consider the capacity of their clients to successfully navigate public transit, and policymakers should consider the transit needs of their entire population when designing transit systems. Full article

Accurate indoor positioning is essential for many applications. However, current methods often fall short in complex environments due to signal fluctuations. We propose a new indoor positioning approach, that is, improved sequential deep learning (ISDL), to address this issue. First, we apply sequential classification algorithms to progressively narrow the search space, reducing potential location regions into smaller neighborhoods. Next, we combine a deep neural network (DNN) with Weighted K-Nearest Neighbors (WKNN) to refine the final location prediction. Then, we validate our method using the publicly available $UJIndoorLoc$ dataset, demonstrating superior accuracy compared to existing methods. Specifically, we achieved 95% floor prediction accuracy and reduced the average positioning error to just 7.82 m. By combining sequential classification and the DNN-WKNN hybrid model, we achieve better localization in complex indoor environments. This system offers practical improvements for real-time location-based services and other applications requiring precise indoor positioning. Full article

Loss of communication, low battery, or bad weather conditions (like high-speed wind) are currently managed by performing a return to launch (RTL) point maneuver. However, the execution of this procedure can pose a safety threat since it has not been considered within the mission planning process. This work proposes an advanced management of contingency events based on the integration of a new U-space service that enhances mission description. The proposed new service, deeply linked to demand capacity balance and strategic deconfliction services, assigns alternative safe landing spots by analyzing the planned mission. Two potential solutions are characterized (distinguished primarily by the number of contingency vertiports assigned): contingency management based on the assignment of a single alternative vertiport to each mission (static) or the allocation of a set of different contingency vertiports that are valid during certain time intervals. It is proven that this enhanced mission planning could ensure that U-space volumes operate in an ultra-safe system conditions while facing these unforeseen events, highlighting its importance in high-risk scenarios like urban air mobility deployments. Full article

The integration of Unmanned Aircraft Systems (UASs) into the current airspace poses significant challenges in terms of safety, security, and operability. As an example, in 2019, the European Union defined a set of rules to support the digitalization of UAS traffic management (UTM) systems and services, namely the U-Space regulations. Current propositions opted for a centralized and private model, concentrated around governmental authorities (e.g., AlphaTango provides the Registration service and depends on the French government). In this paper, we advocate in favor of a more decentralized and transparent model in order to improve safety, security, operability among UTM stakeholders, and legal compliance. As such, we propose DFly, a publicly auditable and privacy-preserving UAS traffic management system on Blockchain, with two initial services: Registration and Flight Authorization. We demonstrate that the use of a blockchain guarantees the public auditability of the two services and corresponding service providers’ actions. In addition, it facilitates the comprehensive and distributed monitoring of airspace occupation and the integration of additional functionalities (e.g., the creation of a live UAS tracker). The combination with zero-knowledge proofs enables the deployment of an automated, distributed, transparent, and privacy-preserving Flight Authorization service, performed on-chain thanks to the blockchain logic. In addition to its construction, this paper details the instantiation of the proposed UTM system with the Ethereum Sepolia’s testnet and the Groth16 ZK-SNARK protocol. On-chain (gas cost) and off-chain (execution time) performance analyses confirm that the proposed solution is a viable and efficient alternative in the spirit of digitalization and offers additional security guarantees. Full article

In 1979, NASA established the Great Observatory program, which included four telescopes (Hubble, Compton, Chandra, and Spitzer) to explore the Universe. The Spitzer Space Telescope was launched in 2003 into solar orbit, gradually drifting away from the Earth. Spitzer was operated very successfully until 2020 when NASA terminated observations and placed the telescope in safe mode. In 2028, the U.S. Space Force has the opportunity to demonstrate satellite servicing by telerobotically reactivating Spitzer for astronomical observations, and in a separate experiment, carry out novel Space Weather research and operations capabilities by observing solar Coronal Mass Ejections. This will be accomplished by launching a small satellite, the Spitzer-Resurrector Mission (SRM), to rendezvous with Spitzer in 2030, positioning itself around it, and serving as a relay for recommissioning and science operations. A sample of science goals for Spitzer is briefly described, but the focus of this paper is on the unique opportunity offered by SRM to demonstrate novel Space Weather research and operations capabilities. Full article