Miracle-dz/UniFAR-FTUs huggingface dataset:
Patient-oriented Emergency Care – a Telemedical Rescue Assistance System

Marie-Thérèse Schneiders, Institute of Information Management in Mechanical Engineering (IMA) Aachen University, Germany, Marie.Schneiders@ima.rwth-aachen.de Frederik Hirsch, Department of Anaesthesiology, University Hospital Aachen, Germany, fhirsch@ukaachen.de Christian Büscher, Institute of Information Management in Mechanical Engineering (IMA) Aachen University, Germany, Christian.Buescher@ima.rwth-aachen.de Daniel Schilberg, Institute of Information Management in Mechanical Engineering (IMA) Aachen University, Germany, Daniel.Schilberg@ima.rwth-aachen.de Sabina Jeschke, Institute of Information Management in Mechanical Engineering (IMA) Aachen University, Germany, Sabina.Jeschke@ima.rwth-aachen.de
Radiation-induced charge transfer inefficiency in charge-coupled devices: Sentinel-4 CCD pre-development as a case study

Energetic particles in space damage electronic components, and in particular affect the capability of Charge-Coupled Devices (CCD) to transfer photo-generated charge packets to the output node. If not properly accounted for either during the instrument design process or in the mission data processing pipeline, radiation-induced Charge Transfer Inefficiency (CTI) causes image distortion, decreases the signal-to-noise ratio, and ultimately leads to bias in the measurement carried out. CTI is a well-identified error budget contributor for mission operating in the photon-starving regime like space telescopes dedicated to Astronomy, but is less studied in the context of Earth Observation missions. We present a study conducted during the Sentinel-4/UVN CCD pre-development to provide a first assessment of the CTI effects on the Sentinel-4 measurements.
Ice Accretions and Icing Effects for Modern Airfoils

Icing tests were conducted to document ice shapes formed on three different two-dimensional airfoils and to study the effects of the accreted ice on aerodynamic performance. The models tested were representative of airfoil designs in current use for each of the commercial transport, business jet, and general aviation categories of aircraft. The models were subjected to a range of icing conditions in an icing wind tunnel. The conditions were selected primarily from the Federal Aviation Administration's Federal Aviation Regulations 25 Appendix C atmospheric icing conditions. A few large droplet icing conditions were included. To verify the aerodynamic performance measurements, molds were made of selected ice shapes formed in the icing tunnel. Castings of the ice were made from the molds and placed on a model in a dry, low-turbulence wind tunnel where precision aerodynamic performance measurements were made. Documentation of all the ice shapes and the aerodynamic performance measurements made during the icing tunnel tests is included in this report. Results from the dry, low-turbulence wind tunnel tests are also presented.
Determination of Knee Joint Centre by Ct-Scanning

In gait analysis the center of the knee joint is used for the calculations that define anatomically based reference systems. Usually, anatomical landmarks are defined on the knee surface, and these coordinates are then used to calculate the knee joint center. However, most calculations are based on equations based on X-rays of one single person. Here we present knee joint center calculations based on CT-scans of 40 corpses. Coordinates for anatomical landmarks, over which skin markers are placed, were registered and used to calculate the location of the joint center following the conventional equation. Using a three-dimensional representation of the CT-scan, the joint center was also estimated visually. The locations of the visually estimated and calculated joint center were compared to each other. The results show that with the calculated joint center as a reference, the location of the visually estimated joint center is on average 16.41 mm (SD 5.75) dorsal, 4.59 mm (SD 2.21) lateral and 16.59 mm (SD 5.07) distal to the calculated center. These results show a systematic deviation between the location of the calculated and visually estimated joint center. The systematic deviation may form the basis for a new equation for calculation of the knee joint center.
Molecular Characterisation and Plasmid Profiling of Hydrocarbon Utilizing Bacteria Isolates from Wetlands in Rivers State, Southern Nigeria

Wetlands can intercept runoff from surfaces prior to reaching open water and remove pollutants through physical, chemical, and biological processes thereby protecting and preserving the environment. Because of unsustainable oil exploration activities, most wetlands in Rivers State, Southern Nigeria have suffered severe petroleum-damaged ecosystems. This research was carried out to characterize and identify the hydrocarbon utilizing bacteria associated with crude oil polluted wetlands and to screen for the presence of plasmids that could confer resistance to antibiotics using both cultural and molecular methods. Soil samples were collected from three different wetlands across the state with hand auger at two depths of 0-15cm and 15-30cm twice monthly for three months. The presence of microbial activity was determined by the enumeration and isolation of total heterotrophic and hydrocarbon utilizing bacteria. Eight (8) most occuring hydrocarbon utilizing bacterial isolates were isolated and identified culturally and phenotypically from the 54 wetland soil samples. These bacteria isolates were confirmed to be Bacillus flexus, Bacillus subtilis, Lysinibacillus macroides, Staphylococcus aureus, Chryseobacterium aquifrigidense, Pseudomonas aeruginosa and Salmonella enterica molecularly via sequencing of the 16S rRNA gene. The most common bacteria isolated were Bacillus species, followed by Pseudomonas at a dilution of 106. Seven (7) out of the eight (8) isolates (except Salmoella enterica) showed the presence of the 25kb plasmids at various intensities.
Rational sampling rate conversion structures with minimum delay requirements

Recent developments on multirate system design show that a rational (L/M) sampling rate conversion system can be reconfigured into a three-dimensional polyphase structure. However, the delay requirements associated with each subfilter path in such a structure have not sufficiently been considered. The paper presents a detailed analysis of the delay requirements, and shows that a reduction by a factor of L on the number of data stores can be achieved. A design approach is introduced for efficient structures based on the minimisation of the total number of delay units. Two transformation rules are derived which directly lead to a homogeneous system configuration. This approach is general and simple so that any rational sampling rate conversion system can be specified by a set of parameters calculated by a small computer program. A hardware implementation is also presented, which demonstrates the usefulness of the present approach. >
Managing water amongst competing uses: the Usangu wetland in Tanzania

Demand for water in the Usangu Basin is driven by a number of competing uses. These include domestic supplies, irrigated agriculture, livestock, fishing, maintenance of the Usangu wetland, a National Park and major hydroelectric system downstream. As a result of a number of driving forces including the growing population, the water resources of the basin are becoming increasingly stressed, and downstream flows have now reduced to zero during the dry season. The paper is based on recent work to study to situation and work with local stakeholders to develop a sustainable management plan for the basin.
Multi-Agent Reinforcement Learning Aided Intelligent UAV Swarm for Target Tracking

Past few years have witnessed the widespread adoption of unmanned aerial vehicles (UAVs) in target tracking for regional monitor and strike. Most existing target tracking approaches rely on the target motion frames obtained by the camera equipped, or on ideally assuming a pre-set target trajectory. However, in practice, the real trajectory of the target cannot be perfectly known to the UAVs in advance, and also the target may intelligently adjust its flying strategy according to the environment. Besides, the limited flight performance, as well as information capture and processing capability, of a single UAV can hardly fulfill high tracking success rate requirements. To address aforementioned issues, this paper proposes an end-to-end cooperative multi-agent reinforcement learning (MARL) scheme, where UAVs are enabled to make intelligent flight decisions for cooperative target tracking, on the basis of the past and current states of the target. In order to reduce power consumption and prolong the lifetime of the UAV tracking system, the propulsion power consumption model and energy saving strategy are introduced. Moreover, to further increase the detection coverage, spatial information entropy is introduced in the tracking algorithm. Simulation results show that our proposed algorithm outperfoms the deep reinforcement learning baselines in terms of the mean episode rewards, while also yields high performances with respect to tracking success rates, power saving efficiency and detection coverage.
A probabilistic method for the evaluation of the reliability of stand alone wind energy systems

The author describes a probabilistic method for the computation of the loss of load probability and the expected unserved energy of a stand-alone wind energy system. The system consists of a wind generator and a storage battery supplying the consumer load. The statistics of the surplus generation (excess wind generation over load demand) time series are computed and used for the calculation of the desired reliability indices. It is shown, that in the probability computations, the serial correlation of the surplus generation cannot be ignored. The performance of the developed method is demonstrated with computational results. Some results useful for the design of stand-alone wind energy systems are also presented. >
Survey on Research of RNN-Based Spatio-Temporal Sequence Prediction Algorithms

: In the past few years, deep learning has developed rapidly, and many researchers try to combine their subjects with deep learning. The algorithm based on Recurrent Neural Network (RNN) has been successfully applied in the fields of weather forecasting, stock forecasting, action recognition, etc. because of its excellent performance in processing Spatio-temporal sequence data. Among them, algorithms based on LSTM and GRU have developed most rapidly because of their good design. This paper reviews the RNN-based Spatio-temporal sequence prediction algorithm, introduces the development history of RNN and the common application directions of the Spatio-temporal sequence prediction, and includes precipitation nowcasting algorithms and traffic flow forecasting algorithms. At the same time, it also compares the advantages and disadvantages, and innovations of each algorithm. The purpose of this article is to give readers a clear understanding of solutions to such problems. Finally, it prospects the future development of RNN in the Spatio-temporal sequence prediction algorithm.
Performance of Three Measures of Comorbidity in Predicting Critical COVID-19: A Retrospective Analysis of 4607 Hospitalized Patients

Background Comorbidity burden has been identified as a relevant predictor of critical illness in patients hospitalized with coronavirus disease 2019 (COVID-19). However, comorbidity burden is often represented by a simple count of few conditions that may not fully capture patients’ complexity. Purpose To evaluate the performance of a comprehensive index of the comorbidity burden (Queralt DxS), which includes all chronic conditions present on admission, as an adjustment variable in models for predicting critical illness in hospitalized COVID-19 patients and compare it with two broadly used measures of comorbidity. Materials and Methods We analyzed data from all COVID-19 hospitalizations reported in eight public hospitals in Catalonia (North-East Spain) between June 15 and December 8 2020. The primary outcome was a composite of critical illness that included the need for invasive mechanical ventilation, transfer to ICU, or in-hospital death. Predictors including age, sex, and comorbidities present on admission measured using three indices: the Charlson index, the Elixhauser index, and the Queralt DxS index for comorbidities on admission. The performance of different fitted models was compared using various indicators, including the area under the receiver operating characteristics curve (AUROCC). Results Our analysis included 4607 hospitalized COVID-19 patients. Of them, 1315 experienced critical illness. Comorbidities significantly contributed to predicting the outcome in all summary indices used. AUC (95% CI) for prediction of critical illness was 0.641 (0.624–0.660) for the Charlson index, 0.665 (0.645–0.681) for the Elixhauser index, and 0.787 (0.773–0.801) for the Queralt DxS index. Other metrics of model performance also showed Queralt DxS being consistently superior to the other indices. Conclusion In our analysis, the ability of comorbidity indices to predict critical illness in hospitalized COVID-19 patients increased with their exhaustivity. The comprehensive Queralt DxS index may improve the accuracy of predictive models for resource allocation and clinical decision-making in the hospital setting.
FINITE ELEMENT ANALYSIS OF CONSOLIDATION PROBLEM IN SEVERAL TYPES OF COHESIVE SOILS USING THE BOUNDING SURFACE MODEL

Finite element analyses of consolidation problem in several types of saturated cohesive soils were performed using the elastoplastic bounding surface model. In this paper, the model and the finite element formulation were described and examples of model prediction and accuracy of the finite element formulation were given. The transient response of the saturated porous media is based on Biot’s theory of consolidation. Transient analysis of a two-dimensional consolidation problem involving a flexible strip footing on a clay layer of finite thickness is then carried out which demonstrate the effects of consolidation process and model parameters on the pore pressure response and ground movements under the strip footing.
Conceptual Model of the Cyber-physical System in the Space of the M9J Road Section

The paper presents a conceptual model of a cyber-physical system (CPS) in the area of the road section of the Motorway 9th January (M9J) in Republic Srpska BiH. The properties, requirements, problems, entities, networks and technologies of the proposed CPS conceptual model are defined. The paper places special emphasis on networks and platform on which the proposed model relies: M:tel Banja Luka provider networks, Wireless Sensor Networks, Software platform.
Factor analytic structure of the Impact of Events Scale – Revised when used with a firefighting sample

Purpose – The Impact of Events Scale (IES)/Impact of Events Scale – Revised (IES‐R) is arguably one of the most well known tools used to assess post‐traumatic symptomatology. The background literature reveals a significant gap with respect to the structural properties of the IES/IES‐R when used with emergency service populations. In response to these identified gaps, this paper aims to provide an evaluation of the structural properties of the three‐factor IES‐R when used specifically with a firefighting sample.Design/methodology/approach – Responses to IES‐R for a sample of paid‐professional firefighters (n=94) and a sample of similar comparison participants (n=91) were evaluated for support of the suggested IES‐R subscales – i.e. hyperarousal, avoidance and intrusions. Responses for both groups were entered into a three‐factor maximum likelihood factor analysis with direct oblimin rotation.Findings – The results provide further support for the use of these subscales when the IES‐R is employed with a comm.
Air2Land: A ground-based vision dataset for UAV landing guidance

—In this paper we present a new dataset, called Air2Land(A2L), for advancing the state-of-art in object detection and 6D pose estimation in the context of UAV auto landing research. It meets vision and robotics for ground-based vision guidance system having the multi-modal data obtained by different sensors, and pushes forward the development of computer vision and robotic algorithms targeted at visually assisted UAV landing. The dataset, contains sequential stereo images and other sensor data (UAV pose, PTU angles) simulated in various climate conditions and landing scenarios, can be employed for tasks including UAV tracking, keypoint localization, pose estimation and action recognition, etc. In addition to providing plentiful and scene-rich data, our dataset covers high risk scenarios that are hardly accessing in reality. The dataset is avaliable at
Finite Element Analysis of Wood Materials

Continuous quality and reliability improvement of computers as well as their widespread applica- tion in design of furniture industry encourage the elaboration of optimization algorithms of furniture construc- tions, in which rigidity characteristics of the applied joints would be taken under consideration. In the last four decades, the fi nite element method, FEM, has become the dominant technique used for analyzing physical phe- nomena in the fi eld of structural, solid and fl uid mechanics as well as for the solution of fi eld problems. This paper gives a bibliographical review of the FEM applied in the analysis of furniture products constructed with wood. The following topics are included: Wood as a furniture construction material and its mechanical properties. It is, therefore, reasonable to replace statistical methods of furniture optimization, which have been applied so far, by gradient methods which allow obtaining much more precise results.
Application of Itô processes and Schwartz distributions to local volatility for Margrabe options

The main aim of this paper is a generalization and extension of the Dupire formula to the case of the Margrabe option. The aforementioned financial derivative is not a special case of a plain vanilla option, and therefore, our generalization is significant from both a theoretical and practical point of view. We use advanced stochastic methods, the theory of probability, and the theory of Schwartz distributions to provide a mathematically rigorous proof of the generalized Dupire formula in the space of distributions. We apply the obtained result in the classical Dupire local volatility setting. Furthermore, we discuss its application to interest rate swaptions.
Association of Atrial Fibrillation With Patient Characteristics in Postoperative Coronary Artery Bypass Grafting Surgery

Introduction Atrial fibrillation (AF) after coronary artery bypass grafting (CABG) is correlated with poor patient outcomes. The study evaluated the association of patients' clinical and sociodemographic characteristics with the incidence of atrial fibrillation, postoperatively. Methodology A longitudinal study was performed in the cardiology department of a tertiary care unit, Sindh, Pakistan between October 2019 and November 2020. All patients who underwent CABG surgery irrespective of gender aged 30 to 75 years were included in the study. Patients with a history of atrial fibrillation or severe left ventricular dysfunction were excluded from the study. The incidence of atrial fibrillation was determined by observing an irregular pattern on electrocardiography (ECG) with no definite P-wave and irregular R-R interval. The patients were monitored for seven postoperative days. The final outcome was measured on the seventh postoperative day. Results A total of 247 patients with a mean age of 63.43 ± 9.72 were enrolled in the study. Out of the 247 patients, 9.7% developed new-onset atrial fibrillation, postoperatively. Age above 65 years was associated with the occurrence of AF but it was not statistically significant (p>0.05). Similarly, patients who developed AF were more likely to have a left ventricle ejection fraction (LVEF) of less than 35% than those without AF (66.67% vs 43.95%; p=0.033). Conclusion A high rate of AF was observed in the study. Older age and impaired ventricular function were significantly associated with atrial fibrillation. It is recommended that hospitals should devise guidelines and protocols for the prevention and management of atrial fibrillation in patients undergoing cardiothoracic surgeries in order to minimize patient mortality and improve patient outcomes.
Piezoelectric Signals in Vascularized Bone Regeneration

The demand for bone substitutes is increasing in Western countries. Bone graft substitutes aim to provide reconstructive surgeons with off-the-shelf alternatives to the natural bone taken from humans or animal species. Under the tissue engineering paradigm, biomaterial scaffolds can be designed by incorporating bone stem cells to decrease the disadvantages of traditional tissue grafts. However, the effective clinical application of tissue-engineered bone is limited by insufficient neovascularization. As bone is a highly vascularized tissue, new strategies to promote both osteogenesis and vasculogenesis within the scaffolds need to be considered for a successful regeneration. It has been demonstrated that bone and blood vases are piezoelectric, namely, electric signals are locally produced upon mechanical stimulation of these tissues. The specific effects of electric charge generation on different cells are not fully understood, but a substantial amount of evidence has suggested their functional and physiological roles. This review summarizes the special contribution of piezoelectricity as a stimulatory signal for bone and vascular tissue regeneration, including osteogenesis, angiogenesis, vascular repair, and tissue engineering, by considering different stem cell sources entailed with osteogenic and angiogenic potential, aimed at collecting the key findings that may enable the development of successful vascularized bone replacements useful in orthopedic and otologic surgery.
Autonomous Vision-Based Navigation of a Quadrotor in Corridor-Like Environments

Vision-based bio-inspired control strategies offer great promise in demonstrating safe autonomous navigation of aerial microsystems in completely unstructured environments. This paper presents an innovative navigation technique that embeds bio-inspired wide-field processing of instantaneous optic flow patterns within the H∞ loop shaping synthesis framework, resulting in a dynamic controller that enables robust stabilization and command tracking behavior in obstacle-laden environments. The local environment is parameterized as a series of simpler corridor-like environments in the optic flow model, and the loop shaping controller is synthesized to provide robust stability across the range of modeled environments. Experimental validation is provided using a quadrotor aerial vehicle across environments with large variation in local structure, with the loop shaping controller demonstrating better tracking performance than other comparable controllers in straight-line corridors of different widths. The current approach is computationally efficient, as it does not involve explicit extraction of an environment depth map, and makes for an attractive paradigm for aerial microsystem navigation in urban environments.
Remedy Selection for Cleanup of Uncontrolled Waste Sites

Selection of remedy for uncontrolled hazardous waste sites involves comparisons of various technological approaches for minimization of threats and achievement of cleanup action levels. Approaches specified in the Comprehensive Environmental Response, Compensation and Liability Act (SUPERFUND Law) National Contingency Plan (40 CFR 300) are broadly labeled as actions, alternatives, and technologies. We have found considerable perplexity in denoting the rank-hierarchy of these approaches and have developed a classification system for dealing with the totality of available measures for consideration in selection of remedy.