Challenging Mission Research Articles

Adaptive communication power control for enhancing attack resilience in UAV networks

A swarm of Unmanned Aerial Vehicles (UAVs) comprises multiple UAVs that are capable of completing tasks beyond the capabilities of a single UAV. Due to the unique challenges of UAV missions, these vehicles often operate far from base stations, making network connectivity crucial for the successful completion of UAV swarm missions. However, existing methods do not account for strategies to maintain the overall connectivity of the UAV network when nodes are under attack. To address this issue, we propose a method named Adaptive Communication Power Control (ACPC) that dynamically adjusts UAV communication power to mitigate potential connectivity losses caused by node failures or malicious attacks. This adjustment ensures that the network can maintain information exchange among the remaining UAVs even in the event of disruptions. Additionally, we introduce a novel evaluation method to assess the overall connectivity of the network and validate ACPC through simulations of UAV swarm missions where some UAVs experience failures. Using this evaluation method, we measured the network’s state before and after attacks and recovery and calculated the additional energy consumption required by the UAVs. The results indicate that our method can increase the resilience of the UAV network by up to 5.36 times, while only raising the total communication energy consumption to 1.53 times.

Comprehensive Insights into the Development of Antitoxoplasmosis Drugs: Current Advances, Obstacles, and Future Perspectives.

Current therapies for toxoplasmosis rely on a few drugs, most of which have severe side effects, and seeking ideal therapies for different types of toxoplasmosis is a long-term and challenging mission. Research and development (R&D) of novel drugs against Toxoplasma gondii (T. gondii) has focused on two main directions, the structural modification of lead compounds and natural products. Here we summarize the recent advances in the development of anti-T. gondii drugs from these two perspectives and provide comprehensive insights, reflecting on the advantages and selected molecules in each field. This review also focuses on the current obstacles to the development of novel anti-T. gondii agents, proposes comprehensive solutions, and facilitates future development.

Analysis of fly-around mission with spinning tether system for space station observation

This paper presents the mission scenarios of using spinning tether system to conduct space stations fly-around mission and validates its feasibility. The main challenge of fly-around mission lies in the difficulty of balancing low fuel consumption and long-term fly-around observation. To deal with this problem, a novel spinning tether system is proposed. Firstly, the fly-around process with spinning tether system is introduced, and the tether system is modeled based on Newton-Euler method with a novel description of spinning motion. Secondly, Given the unique structural limitations of space stations, two fly-around schemes and referenced fly-around trajectories are detailed. Thirdly, a backstepping controller is proposed for tracking the reference motion of fly-around satellites, and the fuel consumption among different fly-around schemes is compared and analyzed. In the end, numerical results validate that under the proposed control strategy, the spinning tether system can maintain a stable fly-around configuration in both the planar and vertical plane, the symmetrical formation configuration prevents the central space station from being affected by the motion of fly-around satellites. Moreover, energy consumption analysis indicates that tethered system can save 62.8 % of impulse compared to traditional schemes when flying in the planar plane, making it the most energy-efficient option.

The challenges of children's safety in pre-hospital emergencies: a qualitative study

Objective: Exploring the challenges experienced by the pre-hospital emergency personnel to prevent the secondary injuries and provide more effective services to children can be helpful. This study aims to explain the safety challenges of children in the pre-hospital emergencies. Method: This qualitative study, which was conducted with the content analysis approach, was a semi-structured, and in-depth data collection process with the field notes for pre-hospital emergency personnel in Dezful city in 2022. Sampling was done in a targeted and available manner. The sampling process continued until the data saturation was reached. The trustworthiness of data was improved by reviewing and revising the data, experience and expertise of the interviewer, review of research participants and researchers. The research data, including interview texts and field notes, were divided into the semantic units, and then summarized by compression, and then abstracted in the order of subclasses, main classes, and finally themes. Results: Qualitative data analysis of interviews and notes led to the extraction of eight themes, which expressed the nature of children's safety challenges in the pre-hospital emergency: the lack of pre-hospital equipment for children, physical and mental characteristics of children, the lack of safety of vehicles for children, the lack of clinical skills of personnel for children, anxiety and non-cooperation of parents, operational and legal problems, the lack of attention to professional responsibility and high work pressure in children's missions . Conclusion: This study’s results showed that identifying children's safety challenges for pre-hospital emergency personnel can help better understand the care needs of this age group and help managers plan in order to reduce children's safety challenges in the pre-hospital missions.

Convex optimization of stochastic path-constrained trajectories near asteroids

The environment around asteroids is of significant uncertainties, which could cause great challenges of exploration missions to asteroids. This paper presents a novel approach to stochastic optimal problem in path-constrained trajectory optimization near asteroids based on convex approach. The path constraints that prevent the spacecraft from colliding with asteroid in different scenarios are composed of keep-out zone constraint and glide-slope constraint, which are formulated in chance-constraint forms due to the uncertain state. To convexify these constraints, the first-order Taylor expansion is applied for linearization and the nonconvexity is tackled with the introduction of additional intermediate variable and virtual buffer. Thereafter, a convex optimization based method is proposed to solve stochastic optimal problem. The effectiveness of the proposed method is validated through simulations of soft landing and hopping transfer scenarios near irregular-shaped asteroid 1996HW1. The results indicate that the proposed method can generate path-constrained trajectories under uncertainties using convex optimization.

Adaptive Fuzzy Integral Sliding Mode Cooperative Control Based on Time-Delay Estimation for Free-Floating Close-Chain Manipulators.

Space manipulators are expected to perform more challenging missions in on-orbit service (OOS) systems, but there are some unique characteristics that are not found on ground-based robots, such as dynamic coupling between space bases and manipulators, limited fuel supply, and working with unfixed bases. This paper focuses on trajectory-tracking control and internal force control for free-floating close-chain manipulators. First, the kinematics and dynamics of free-floating close-chain manipulators are given using the momentum conservation and spatial operator algebra (SOA) methodologies, respectively. Furthermore, an adaptive fuzzy integral sliding mode controller (AFISMC) based on time delay estimation (TDE) was designed for trajectory-tracking control, and a proportional-integral (PI) control strategy was adopted for internal force control. The global asymptotic stability of the proposed controller was proven by using the Lyapunov methodology. Three cases were conducted to verify the efficiency of the controller by using numerical simulations on two six-link manipulators with a free-floating base. The controller presents the desired tracking capability.

Patterns of the Predicted Mutation Burden in 19,778 Domesticated Barley Accessions Conserved Ex Situ.

Long-term conservation of more than 7 million plant germplasm accessions in 1750 genebanks worldwide is a challenging mission. The extent of deleterious mutations present in conserved germplasm and the genetic risk associated with accumulative mutations are largely unknown. This study took advantage of published barley genomic data to predict sample-wise mutation burdens for 19,778 domesticated barley (Hordeum vulgare L.) accessions conserved ex situ. It was found that the conserved germplasm harbored 407 deleterious mutations and 337 (or 82%) identified deleterious alleles were present in 20 (or 0.1%) or fewer barley accessions. Analysis of the predicted mutation burdens revealed significant differences in mutation burden for several groups of barley germplasm (landrace > cultivar (or higher burden estimate in landrace than in cultivar); winter barley > spring barley; six-rowed barley > two-rowed barley; and 1000-accession core collection > non-core germplasm). Significant differences in burden estimate were also found among seven major geographical regions. The sample-wise predicted mutation burdens were positively correlated with the estimates of sample average pairwise genetic difference. These findings are significant for barley germplasm management and utilization and for a better understanding of the genetic risk in conserved plant germplasm.

Sharing in the Indiscriminate Generosity of God

This article probes three of the findings of the author’s D.Min. project thesis, which explored God’s call of racial justice in a predominantly white, affluent Episcopal parish. The research revealed theological and missional challenges that inhibit the church from joining in God’s mission of justice, namely participants viewing the church as the host of mission, white privilege hindering the practice of listening, and the reluctance of members to articulate the presence and activity of God as it relates to justice. In consideration of these obstacles, this article calls upon the indiscriminate generosity of God for funding the imagination of the missional community for faithful innovation related to racial justice.

Nursing roles in disaster zones: Experiences and lessons from Turkey's 2023 earthquakes.

Disasters affect human health and well-being globally. Nursing plays a vital role in disaster preparedness and response, ensuring efficient early care coordination and delivering effective field treatment. This study investigates the challenges an Israeli humanitarian delegation encountered during their response to major earthquakes in Turkey in 2023. It explicitly focuses on difficulties in preparation, operations, and collaboration with local teams. The study further analyzes the findings and extracts valuable lessons from the mission. Using a qualitative descriptive design, 22 out of 32 nurses involved in delegation participated in three focus group discussions within two months of returning to Israel. The discussions were recorded, transcribed verbatim, and analyzed thematically. The study followed the COREQ guidelines, ensuring comprehensive reporting and methodological rigor in qualitative research. The study's main findings spanned predeparture preparation, mission challenges in the disaster zone, and postmission lessons, each highlighted by subthemes and participant quotations. A strong sense of mission was evident among the participants, along with frustration at inefficient time management prior to deployment. Many participants noted additional challenges, related to the difficulty of working in multiple languages and across cultures, and the opportunities for resolution. Finally, participants called for better psychological support following the mission. Nurses in disaster zones offer valuable insights to enhance preparation, cross-cultural communication, and postmission implementation. Nurse managers and healthcare policymakers can utilize this study's findings to develop future nursing training programs in disaster-related skills. Additionally, it can help foster collaboration among international healthcare teams.

Improving permeability prediction via Machine Learning in a heterogeneous carbonate reservoir: application to Middle Miocene Nullipore, Ras Fanar field, Gulf of Suez, Egypt

Predicting and interpolating the permeability between wells to obtain the 3D distribution is a challenging mission in reservoir simulation. The high degree of heterogeneity and diagenesis in the Nullipore carbonate reservoir provide a significant obstacle to accurate prediction. Moreover, intricate relationships between core and well logging data exist in the reservoir. This study presents a novel approach based on Machine Learning (ML) to overcome such difficulties and build a robust permeability predictive model. The main objective of this study is to develop an ML-based permeability prediction approach to predict permeability logs and populate the predicted logs to obtain the 3D permeability distribution of the reservoir. The methodology involves grouping the reservoir cored intervals into flow units (FUs), each of which has distinct petrophysical characteristics. The probability density function is used to investigate the relationships between the well logs and FUs to select high-weighted input features for reliable model prediction. Five ML algorithms, including Linear Regression (LR), Polynomial Regression (PR), Support Vector Regression (SVR), Decision Trees (DeT), and Random Forests (RF), have been implemented to integrate the core permeability with the influential well logs to predict permeability. The dataset is randomly split into training and testing sets to evaluate the performance of the developed models. The models’ hyperparameters were tuned to improve the model’s prediction performance. To predict permeability logs, two key wells containing the whole reservoir FUs are used to train the most accurate ML model, and other wells to test the performance. Results indicate that the RF model outperforms all other ML models and offers the most accurate results, where the adjusted coefficient of determination (R2adj) between the predicted permeability and core permeability is 0.87 for the training set and 0.82 for the testing set, mean absolute error and mean squared error (MSE) are 0.32 and 0.19, respectively, for both sets. It was observed that the RF model exhibits high prediction performance when it is trained on wells containing the whole reservoir FUs. This approach aids in detecting patterns between the well logs and permeability along the profile of wells and capturing the wide permeability distribution of the reservoir. Ultimately, the predicted permeability logs were populated via the Gaussian Random Function Simulation geostatistical method to build a 3D permeability distribution for the reservoir. The study outcomes will aid users of ML to make informed choices on the appropriate ML algorithms to use in carbonate reservoir characterization for more accurate permeability predictions and better decision-making with limited available data.

"The Benefits and Challenges of Cardiac Mission in Sub- Saharan Africa"

"The Benefits and Challenges of Cardiac Mission in Sub- Saharan Africa"

Bridging the voice of healthcare to digital transformation in practice – a holistic approach

BackgroundDigital transformation is key for healthcare to meet future needs and expectations and compete equally with new actors on the market. Medical digital diagnosis tools and clinical decision support systems (CDSS) are improving and offer new opportunities. To introduce new technology in healthcare can however be a challenging mission, too often ending in failure, with excessive costs or the actual transformation work not being carried out at all. It is unclear how to drive the establishment to reach desired results in this environment, and how industrial experiences can be used to support healthcare.ObjectiveThe objective of this study was to develop a holistic approach for introducing new information technology (IT), such as a CDSS, into a primary healthcare organization supported by industry best practices for digital transformation.MethodsThis qualitative study used a combined inductive and deductive method where the perceptions and beliefs of selected primary healthcare stakeholders were used as directions for developing an approach that could utilize existing industry best practices for digital transformation.ResultsA holistic healthcare-ified approach including 20 requirements was developed, that meet the needs of healthcare. The voice of healthcare was used as prism to healthcare-ify the industry practices and adapt it to match specific healthcare conditions. An example was provided showing how the research could be put into practice.ConclusionsThis study proposed a holistic approach, based on industry best practices, but adapted to healthcare using the voice of healthcare as a bridge, that may be used to introduce CDSS and other IT into a primary healthcare organization and step up the needed digitalization.

A statistical analysis on the opinion of Indian citizens about opportunities and challenges of digital India mission

A statistical analysis on the opinion of Indian citizens about opportunities and challenges of digital India mission

Defining global thresholds for anaemia: a challenging mission

Defining global thresholds for anaemia: a challenging mission

Women of Faith: Overcoming Challenges in the Church's Mission and the Academy

AbstractTwo recent books navigate the challenges and possibilities women encounter in church and society. Each proceeds from starkly different vantage points and targets distinct audiences. Dzubinski and Stasson's historical approach homes in on the horizon of ecclesial mission as depicted throughout the centuries of Christianity. This work is tailored especially for historians. Yuen and Collier‐Goubil focus on contemporary issues confronting women at the intersection of faith, the home, and the academy. This volume is written by and will appeal to a broad range of religious scholars, although it holds particular significance for those balancing a career in academia with motherhood. A comparison of these works offers unique insights into the shared concerns women with an array of vocations confront, as well as the distinct issues emerging from the arenas of ecclesial leadership, on the one hand, and the academy, on the other.

General studies, information and communication technology and contemporary mission in Africa

This study examines the relationship between general studies, information and communication technology (ICT), and contemporary evangelism in Nigeria. Information and communication technology (is defined as a diverse set of technological tools and resources used to transmit, store, create, share or exchange information. These technological tools and resources include computers, the Internet (websites, blogs and emails), live broadcasting technologies (radio, television and webcasting), recorded broadcasting technologies (podcasting, audio and video players, and storage devices) and telephony (fixed or mobile, satellite, visio/video conferencing, etc.). Contemporary evangelism and mission in Africa is a radical approach embarked upon by agents of modern religious thoughts and practices to expand the horizons of the mission of religion to mankind in the present dispensation through general studies (GS) and ICT programmes. Through the medium of ICT, Christian evangelism has received a boost in television, radio broadcasts, computers, and the Internet across cities and nations. This work is an attempt to examine the methods adopted by early missionaries in evangelising Africa vis-à-vis the modern techniques of GS and ICT, the challenges of mission, the concept of ICT and its various forms such as phones, television, radio, computers, and the Internet, and their relevance to mission. This work therefore adopted historical, missiological, and phenomenological approaches in the analysis of data.Contribution: This work discovers that radical development in communication across the globe has influenced and affected Christian methods and practices of carrying out ‘the mission of religion’ and its evangelical perspective, among others.

Talenticity (Talent, Creativity) in the Era of Metaintelligence

Today the consensus is almost general and indisputable: talent is a determining factor in the success of individuals and organizations around the world. More or less everyone is looking for talent in others and wants to demonstrate their own. We all want to work with talented people. It's a great way to develop our talent too. Discovering and enhancing a latent talent and making it grow ultimately represents one of the most rewarding and significant challenges of the educational mission as well as the mission that any society should have. For years we have been trying to answer the question of whether “talent is innate or developed through experience and the environment". The question we ask ourselves today is: Can learning in "personalized” environments, through artificial intelligence algorithms, foster creative thinking and the development of talents?

Model Predictive Control based Coordinated Control for Free-Flying Space Manipulator Systems

Space Manipulator Systems (SMS) used in On-Orbit Servicing (OOS) missions are over-actuated, and safety critical systems that perform complex tasks in space. We propose a coordinated control for a free-flying SMS, which is based on a cascaded output tracking nonlinear model predictive control, to simultaneously control the spacecraft-base and manipulator of the SMS. The output tracks a given end-effector pose trajectory, and by using an artificial reference the controller stays feasible even for an unreachable trajectory. Moreover, the systems over-actuation is optimally resolved, such that the base of the SMS can be utilized to generate an unrestricted workspace for robotic operations. Throughout the entire mission, critical constraints related to system and safety, including collision avoidance, field of view of sensor devices, joint limitations, and actuator saturations, are integrated as hard constraints. Simulations of the most challenging mission phases, such as the approach and detumbling of a target spacecraft, as well as an escape maneuver verify the performance, reliability, and flexibility of our coordinated control concept.

A Dual-Functional System for the Classification and Diameter Measurement of Aortic Dissections Using CTA Volumes via Deep Learning

Acute aortic dissection is one of the most life-threatening cardiovascular diseases, with a high mortality rate. Its prevalence ranges from 0.2% to 0.8% in humans, resulting in a significant number of deaths due to being missed in manual examinations. More importantly, the aortic diameter—a critical indicator for surgical selection—significantly influences the outcomes of surgeries post-diagnosis. Therefore, it is an urgent yet challenging mission to develop an automatic aortic dissection diagnostic system that can recognize and classify the aortic dissection type and measure the aortic diameter. This paper offers a dual-functional deep learning system called aortic dissections diagnosis-aiding system (DDAsys) that enables both accurate classification of aortic dissection and precise diameter measurement of the aorta. To this end, we created a dataset containing 61 190 computed tomography angiography (CTA) images from 279 patients from the Division of Cardiovascular Surgery at Tongji Hospital, Wuhan, China. The dataset provides a slice-level summary of difficult-to-identify features, which helps to improve the accuracy of both recognition and classification. Our system achieves a recognition F1 score of 0.984, an average classification F1 score of 0.935, and the respective measurement precisions for ascending and descending aortic diameters are 0.994 mm and 0.767 mm root mean square error (RMSE). The high consistency (88.6%) between the recommended surgical treatments and the actual corresponding surgeries verifies the capability of our system to aid clinicians in developing a more prompt, precise, and consistent treatment strategy.

Dietary and Supplementation Strategies for Recovery: A Proposal for Elite Soccer Players

Recovering as quickly as possible, restoring pre-performance levels is considered a crucial element of success in almost every athletic discipline, including soccer. For this reason, coaches and athletes are always in a continuous search for the most effective strategies, that include supplementation or food, to speed up post-exercise recovery. However, precisely defining the concept of “recovery from exercise” is a challenging mission due to the number of variables affecting an optimal recovery [1]. That's why, the prescription of post-match or post-training recovery strategies in elite soccer players is a key point to optimize soccer performance.