bluuebunny/crossref_metadata_2025 huggingface dataset:
Artificial Neural Network for Fast and Versatile Model Parameter Adjustment Utilizing PAT Signals of Chromatography Processes for Process Control under Production Conditions
Authors: Mouellef Mourad , Szabo Glaenn , Vetter Florian Lukas , Siemers Christian , Strube Jochen
Published: April 2022

Preparative chromatography is a well-established operation in chemical and biotechnology manufacturing. Chromatography achieves high separation performances, but often has to deal with the yield versus purity trade-off as the optimization criterium regarding through-put. The initial trade-off is often disturbed by the well-known phenomenon of chromatogram shifts over process lifetime, and has to be corrected by operators via adjustment of peak fraction cutting. Nevertheless, with regard to autonomous operation and batch to continuous processing modes, an advanced process control strategy is needed to identify and correct shifts from the optimal operation point automatically. Previous studies have already presented solutions for batch-to-batch variance and process control options with the aid of rigorous physico-chemical process modeling. These models can be implemented as distinct digital twins as well as statistical process operation data analyzers. In order to utilize such models for advanced process control (APC), the model parameters have to be updated with the aid of inline Process Analytical Technology (PAT) data to describe the actual operational status. This updating process also includes any operational change phenomena that occur, and its relation to their physico-chemical root cause. Typical phenomena are fluid dynamic changes due to packing breakage, channelling or compression as well as mass transfer and phase equilibrium-related separation performance decrease due to adsorbent aging or feed and buffer composition changes. In order to track these changes, an Artificial Neural Network (ANN) is trained in this work. The ANN training is in this first step, based on the simulation results of a distinct and previously experimentally validated process model. The model is implemented in the open source tool CasADi for Python. This allows the implementation of interfaces to process control systems, among others, with relatively low effort. Therefore, PAT signals can easily be incorporated for sufficient adjustment of the process model for appropriate process control. Further steps would be the implementation of optimization routines based on PAT and ANN predictions to derive optimal operation points with the model.
Using Simulation to Evaluate a Tube Perception Algorithm for Bin Picking
Authors: Leão Gonçalo , Costa Carlos M. , Sousa Armando , Reis Luís Paulo , Veiga Germano
Published: April 2022

Bin picking is a challenging problem that involves using a robotic manipulator to remove, one-by-one, a set of objects randomly stacked in a container. In order to provide ground truth data for evaluating heuristic or machine learning perception systems, this paper proposes using simulation to create bin picking environments in which a procedural generation method builds entangled tubes that can have curvatures throughout their length. The output of the simulation is an annotated point cloud, generated by a virtual 3D depth camera, in which the tubes are assigned with unique colors. A general metric based on micro-recall is proposed to compare the accuracy of point cloud annotations with the ground truth. The synthetic data is representative of a high quality 3D scanner, given that the performance of a tube modeling system when given 640 simulated point clouds was similar to the results achieved with real sensor data. Therefore, simulation is a promising technique for the automated evaluation of solutions for bin picking tasks.
A SLAM System with Direct Velocity Estimation for Mechanical and Solid-State LiDARs
Authors: Jie Lu , Jin Zhi , Wang Jinping , Zhang Letian , Tan Xiaojun
Published: April 2022

Simultaneous localization and mapping (SLAM) is essential for intelligent robots operating in unknown environments. However, existing algorithms are typically developed for specific types of solid-state LiDARs, leading to weak feature representation abilities for new sensors. Moreover, LiDAR-based SLAM methods are limited by distortions caused by LiDAR ego motion. To address the above issues, this paper presents a versatile and velocity-aware LiDAR-based odometry and mapping (VLOM) system. A spherical projection-based feature extraction module is utilized to process the raw point cloud generated by various LiDARs, hence avoiding the time-consuming adaptation of various irregular scan patterns. The extracted features are grouped into higher-level clusters to filter out smaller objects and reduce false matching during feature association. Furthermore, bundle adjustment is adopted to jointly estimate the poses and velocities for multiple scans, effectively improving the velocity estimation accuracy and compensating for point cloud distortions. Experiments on publicly available datasets demonstrate the superiority of VLOM over other state-of-the-art LiDAR-based SLAM systems in terms of accuracy and robustness. Additionally, the satisfactory performance of VLOM on RS-LiDAR-M1, a newly released solid-state LiDAR, shows its applicability to a wide range of LiDARs.
Change Detection of Amazonian Alluvial Gold Mining Using Deep Learning and Sentinel-2 Imagery
Authors: Camalan Seda , Cui Kangning , Pauca Victor Paul , Alqahtani Sarra , Silman Miles , Chan Raymond , Plemmons Robert Jame , Dethier Evan Nylen , Fernandez Luis E. , Lutz David A.
Published: April 2022

Monitoring changes within the land surface and open water bodies is critical for natural resource management, conservation, and environmental policy. While the use of satellite imagery for these purposes is common, fine-scale change detection can be a technical challenge. Difficulties arise from variable atmospheric conditions and the problem of assigning pixels to individual objects. We examined the degree to which two machine learning approaches can better characterize change detection in the context of a current conservation challenge, artisanal small-scale gold mining (ASGM). We obtained Sentinel-2 imagery and consulted with domain experts to construct an open-source labeled land-cover change dataset. The focus of this dataset is the Madre de Dios (MDD) region in Peru, a hotspot of ASGM activity. We also generated datasets of active ASGM areas in other countries (Venezuela, Indonesia, and Myanmar) for out-of-sample testing. With these labeled data, we utilized a supervised (E-ReCNN) and semi-supervised (SVM-STV) approach to study binary and multi-class change within mining ponds in the MDD region. Additionally, we tested how the inclusion of multiple channels, histogram matching, and La*b* color metrics improved the performance of the models and reduced the influence of atmospheric effects. Empirical results show that the supervised E-ReCNN method on 6-Channel histogram-matched images generated the most accurate detection of change not only in the focal region (Kappa: 0.92 (± 0.04), Jaccard: 0.88 (± 0.07), F1: 0.88 (± 0.05)) but also in the out-of-sample prediction regions (Kappa: 0.90 (± 0.03), Jaccard: 0.84 (± 0.04), and F1: 0.77 (± 0.04)). While semi-supervised methods did not perform as accurately on 6- or 10-channel imagery, histogram matching and the inclusion of La*b* metrics generated accurate results with low memory and resource costs. These results show that E-ReCNN is capable of accurately detecting specific and object-oriented environmental changes related to ASGM. E-ReCNN is scalable to areas outside the focal area and is a method of change detection that can be extended to other forms of land-use modification.
Satellite Observations of Fire Activity in Relation to Biophysical Forcing Effect of Land Surface Temperature in Mediterranean Climate
Authors: Stoyanova Julia S. , Georgiev Christo G. , Neytchev Plamen N.
Published: April 2022

The present work is aimed at gaining more knowledge on the nature of the relation between land surface temperature (LST) as a biophysical parameter, which is related to the coupled effect of the energy and water cycles, and fire activity over Bulgaria, in the Eastern Mediterranean. In the ecosystems of this area, prolonged droughts and heat waves create preconditions in the land surface state that increase the frequency and intensity of landscape fires. The relationships between the spatial–temporal variability of LST and fire activity modulated by land cover types and Soil Moisture Availability (SMA) are quantified. Long-term (2007–2018) datasets derived from geostationary MSG satellite observations are used: LST retrieved by the LSASAF LST product; fire activity assessed by the LSASAF FRP-Pixel product. All fires in the period of July–September occur in days associated with positive LST anomalies. Exponential regression models fit the link between LST monthly means, LST positive anomalies, LST-T2 (as a first proxy of sensible heat exchange with atmosphere), and FRP fire characteristics (number of detections; released energy FRP, MW) at high correlations. The values of biophysical drivers, at which the maximum FRP (MW) might be expected at the corresponding probability level, are identified. Results suggest that the biophysical index LST is sensitive to the changes in the dynamics of vegetation fire occurrence and severity. Dependences are found for forest, shrubs, and cultivated LCs, which indicate that satellite IR retrievals of radiative temperature is a reliable source of information for vegetation dryness and fire activity.
Machine Learning for Defining the Probability of Sentinel-1 Based Deformation Trend Changes Occurrence
Authors: Confuorto Pierluigi , Medici Camilla , Bianchini Silvia , Del Soldato Matteo , Rosi Ascanio , Segoni Samuele , Casagli Nicola
Published: April 2022

The continuous monitoring of displacements occurring on the Earth surface by exploiting MTInSAR (Multi Temporal Interferometry SAR) Sentinel-1 data is a solid reality, as testified by the ongoing operational ground motion service in the Tuscany region (Central Italy). In this framework, anomalies of movement, i.e., accelerations or deceleration as seen by the time series of displacement of radar targets, are identified. In this work, a Machine Learning algorithm such as the Random Forest has been used to assess the probability of occurrence of the anomalies induced by slope instability and subsidence. About 20,000 anomalies (about 7000 and 13,000 for the slope instability and the subsidence, respectively) were collected between 2018 and 2020 and were used as input, while ten different variables were selected, five related to the morphological and geological setting of the study area and five to the radar characteristics of the data. The resulting maps may provide useful indications of where a sudden change of displacement trend may occur, analyzing the contribution of each factor. The cross-validation with the anomalies collected in a following timespan (2020–2021) and with official landslide and subsidence inventories provided by the regional authority has confirmed the reliability of the final maps. The adoption of a map for assessing the probability of the occurrence of MTInSAR anomalies may serve as an enhanced geohazard prevention measurement, to be periodically updated and refined in order to have the most precise knowledge possible of the territory.
Assessing Representation Learning and Clustering Algorithms for Computer-Assisted Image Annotation—Simulating and Benchmarking MorphoCluster
Authors: Schröder Simon-Martin , Kiko Rainer
Published: April 2022

Image annotation is a time-consuming and costly task. Previously, we published MorphoCluster as a novel image annotation tool to address problems of conventional, classifier-based image annotation approaches: their limited efficiency, training set bias and lack of novelty detection. MorphoCluster uses clustering and similarity search to enable efficient, computer-assisted image annotation. In this work, we provide a deeper analysis of this approach. We simulate the actions of a MorphoCluster user to avoid extensive manual annotation runs. This simulation is used to test supervised, unsupervised and transfer representation learning approaches. Furthermore, shrunken k-means and partially labeled k-means, two new clustering algorithms that are tailored specifically for the MorphoCluster approach, are compared to the previously used HDBSCAN*. We find that labeled training data improve the image representations, that unsupervised learning beats transfer learning and that all three clustering algorithms are viable options, depending on whether completeness, efficiency or runtime is the priority. The simulation results support our earlier finding that MorphoCluster is very efficient and precise. Within the simulation, more than five objects per simulated click are being annotated with 95% precision.
Propulsion Calculated by Force and Displacement of Center of Mass in Treadmill Cross-Country Skiing
Authors: Zhao Shuang , Ohtonen Olli , Ruotsalainen Keijo , Kettunen Lauri , Lindinger Stefan , Göpfert Caroline , Linnamo Vesa
Published: April 2022

This study evaluated two approaches for estimating the total propulsive force on a skier’s center of mass (COM) with double-poling (DP) and V2-skating (V2) skiing techniques. We also assessed the accuracy and the stability of each approach by changing the speed and the incline of the treadmill. A total of 10 cross-country skiers participated in this study. Force measurement bindings, pole force sensors, and an eight-camera Vicon system were used for data collection. The coefficient of multiple correlation (CMC) was calculated to evaluate the similarity between the force curves. Mean absolute force differences between the estimated values and the reference value were computed to evaluate the accuracy of each approach. In both DP and V2 techniques, the force–time curves of the forward component of the translational force were similar to the reference value (CMC: 0.832–0.936). The similarity between the force and time curves of the forward component of the ground reaction force (GRF) and the reference value was, however, greater (CMC: 0.879–0.955). Both approaches can estimate the trend of the force–time curve of the propulsive force properly. An approach by calculating the forward component of GRF is a more appropriate method due to a better accuracy.
A Deep Learning Method for Foot Progression Angle Detection in Plantar Pressure Images
Authors: Ardhianto Peter , Subiakto Raden Bagus Reinaldy , Lin Chih-Yang , Jan Yih-Kuen , Liau Ben-Yi , Tsai Jen-Yung , Akbari Veit Babak Hamun , Lung Chi-Wen
Published: April 2022

Foot progression angle (FPA) analysis is one of the core methods to detect gait pathologies as basic information to prevent foot injury from excessive in-toeing and out-toeing. Deep learning-based object detection can assist in measuring the FPA through plantar pressure images. This study aims to establish a precision model for determining the FPA. The precision detection of FPA can provide information with in-toeing, out-toeing, and rearfoot kinematics to evaluate the effect of physical therapy programs on knee pain and knee osteoarthritis. We analyzed a total of 1424 plantar images with three different You Only Look Once (YOLO) networks: YOLO v3, v4, and v5x, to obtain a suitable model for FPA detection. YOLOv4 showed higher performance of the profile-box, with average precision in the left foot of 100.00% and the right foot of 99.78%, respectively. Besides, in detecting the foot angle-box, the ground-truth has similar results with YOLOv4 (5.58 ± 0.10° vs. 5.86 ± 0.09°, p = 0.013). In contrast, there was a significant difference in FPA between ground-truth vs. YOLOv3 (5.58 ± 0.10° vs. 6.07 ± 0.06°, p < 0.001), and ground-truth vs. YOLOv5x (5.58 ± 0.10° vs. 6.75 ± 0.06°, p < 0.001). This result implies that deep learning with YOLOv4 can enhance the detection of FPA.
Classifying Muscle States with One-Dimensional Radio-Frequency Signals from Single Element Ultrasound Transducers
Authors: Brausch Lukas , Hewener Holger , Lukowicz Paul
Published: April 2022

The reliable assessment of muscle states, such as contracted muscles vs. non-contracted muscles or relaxed muscles vs. fatigue muscles, is crucial in many sports and rehabilitation scenarios, such as the assessment of therapeutic measures. The goal of this work was to deploy machine learning (ML) models based on one-dimensional (1-D) sonomyography (SMG) signals to facilitate low-cost and wearable ultrasound devices. One-dimensional SMG is a non-invasive technique using 1-D ultrasound radio-frequency signals to measure muscle states and has the advantage of being able to acquire information from deep soft tissue layers. To mimic real-life scenarios, we did not emphasize the acquisition of particularly distinct signals. The ML models exploited muscle contraction signals of eight volunteers and muscle fatigue signals of 21 volunteers. We evaluated them with different schemes on a variety of data types, such as unprocessed or processed raw signals and found that comparatively simple ML models, such as Support Vector Machines or Logistic Regression, yielded the best performance w.r.t. accuracy and evaluation time. We conclude that our framework for muscle contraction and muscle fatigue classifications is very well-suited to facilitate low-cost and wearable devices based on ML models using 1-D SMG.
Resilient Safety Culture and Safety Performance: Examining the Effect in Malaysian Paramedic Training Institute through Importance-Performance Map Analysis (IPMA)
Authors: Noor Arzahan Intan Suraya , Ismail Zaliha , Yasin Siti Munira
Published: April 2022

An increasing number of studies have shown that safety culture factors have a substantial influence on safety performance in a variety of industrial sectors. These factors’ impact on safety performance are unclear, especially at public service and statutory authorities. On the other hand, the understanding of indicators for safety performance in every working sector in Malaysia is continuing to progress. Hence, this study’s contribution is to explore the influence of safety culture factors (i.e., management commitment and supervision in safety, safety system) and safety competence on safety performance in government paramedic training institutes. Importance-performance map analysis (IPMA) is a technique used in Smart PLS to determine the significance and performance of each of these factors. The study was conducted via an online survey and involved 258 safety and health committee members in the Ministry of Health paramedic training institute. As a matter of relevance, the IPMA’s empirical data study revealed that management commitment and supervision in safety were the predominant factors in determining safety performance. Meanwhile, for performance, the findings showed that worker involvement, safety system, and safety competence perform well in determining safety performance.
The Causality Analysis of Airports and Regional Economy: Empirical Evidence from Jiangsu Province in China
Authors: Bai Yang , Wu Cheng-Lung
Published: April 2022

China is the second largest aviation country in the world. The Chinese aviation industry and economy both developed quickly in the last two decades. However, the interaction mechanisms of aviation and the regional economy were different in each province. Jiangsu was the most important province in the Yangtze River delta region. The GDP of Jiangsu ranked second in China, but air transportation didn’t have the same leading position in the last decade. Taking Jiangsu province as for analysis, this paper provided empirical evidence of the causality between airport development and regional economic growth. The results showed that: (1) From 2008 to 2018, the overall volume of airport passenger throughput and GDP in Jiangsu had a strong upward trend with strong seasonal fluctuations; (2) There was a bi-directional Granger causality relationship between the airport passenger throughput and GDP in Jiangsu based on the vector autoregression (VAR) model and the Granger causality test; (3) From the impulse response and variance decomposition, the inter-contribution of GDP and airport development was sustainable and increasing over time. However, the impact of economic growth on airports was more significant than the impact of airports on economic growth.
Assessing Farmers’ Attitudes towards Rural Land Circulation Policy Changes in the Pearl River Delta, China
Authors: Li Zhansheng , Yang Qiying , Yang Xuchao , Ouyang Zutao , Cai Xiumin , Qi Jiaguo
Published: April 2022

An emerging and pressing issue in China’s economic reform is the intensified conflict between arable land protection and the encroachment of urban development into fertile farmlands that threaten food security and urban sustainability. New policies were issued to encourage rural land circulation as an attempt to ensure urban development and a sustainable food system, but farmers’ willingness to adopt the policies is largely unknown. A total of 4500 farmers within 9 cities’ boundaries in the Pearl River Delta were surveyed, and the theory of planned behavior and statistical tools were used to determine key factors affecting farmers’ attitudes towards the new sustainability policy. The results indicate that farmers’ cognition of the policies positively influenced farmers’ willingness to participate in land circulation. Attitude toward the Behavior (AB), Subjective Norm (SN), and Perceived Behavioral Control (PBC) were the dominant factors affecting the policies’ implementation. PBC had the most significant influence on sustainable policy participation, followed by SN and AB. AB alone could not determine the actual participation behavior because of external factors such as family, community, and other policy-related considerations. In conclusion, the successful implementation of the rural land-use policy will be primarily determined by the farmers’ cognition and behavior.
Test Studies on Geogrid–Soil Interface Behavior under Static and Dynamic Loads
Authors: Jin Jing , Liang Xiaoyong , Yang Guangqing , Zhou Yitao
Published: April 2022

Pullout tests on geogrids have been regarded as the most direct way to investigate geogrid–soil interaction. In the pullout tests on geogrids, either static or dynamic load is commonly used for applying the vertical loads. In order to investigate the influence of static and dynamic load on pullout test results, pullout tests are carried out to analyze the mechanical response of geogrids and soils under static and dynamic load from the large-scale pullout tester. The results show that frequency and amplitude have significant effects on the pullout test results under the dynamic load. The interface cohesion and friction coefficients under dynamic loads are smaller than those under static loads. The reinforcement effect of geogrids is reduced by dynamic load. Therefore, the strength of geogrids should be reduced when quasi-static analysis is used for reinforced structures. Knockdown factor is recommended for the corresponding reduction. The investigation results of this study may provide scientific references for regulating the design method of reinforced structures.
Linking the Use of Ergonomics Methods to Workplace Social Sustainability: The Ovako Working Posture Assessment System and Rapid Entire Body Assessment Method
Authors: Gajšek Brigita , Draghici Anca , Boatca Maria Elena , Gaureanu Alin , Robescu Diana
Published: April 2022

This article concretizes the continuous development of social sustainability in organizations based on ergonomics methods and tools, among others. Numerous scientific studies have already revealed many reasons for justifying balanced efforts towards organizational sustainability, including its economic, social, and environmental dimensions. Because the social dimension is recognized as the weakest and is often neglected, it is placed at the forefront of the present research. The link between social sustainability in the workplace and the ergonomics concept is provided through 17 underlying indicators of the workplace sustainability framework proposed in a previous study. The OWAS and REBA ergonomic risk assessment methods were used in a toolmaking company to study how results can be used directly or indirectly to determine the size or value of indicators used in the sustainability framework. The research finds that direct use of the OWAS and REBA results is not possible, but it is certain that the implementation of proposals in response to identified levels of risk affects up to four out of five factors that constitute the sustainability framework. The use of OWAS and REBA is not suitable to address environmental concerns. This study encourages companies to use ergonomic methods and tools to develop social sustainability in the workplace. It is often necessary to decide between the pen-and-paper approach and an advanced one using artificial intelligence (e.g., supported by the ErgoIA software tool). Not only the method but also the technique chosen affects the degree of sustainability achieved. Finally, relevant aspects of knowledge exploitation in the field of ergonomic education for social sustainability were summarized.
What Teachers Should Know for Effective Marine Litter Education: A Scoping Review
Authors: Ahmad-Kamil E. I. , Syed Zakaria Sharifah Zarina , Othman Murnira
Published: April 2022

Marine litter has had a huge impact on the marine environment and the socio-economic activities that depend on healthy oceans. All members of the community must play their part to address marine litter. Teachers are agents of change that are capable of encouraging pro-environmental practices among the community that will reduce environmental issues, including marine litter. However, teachers were found to have limited knowledge regarding ocean literacy and marine pollution. A scoping review was conducted to identify various aspects of content knowledge related to marine litter education that has been recently conducted for school teachers and students. Web of Science, Scopus and ERIC databases were searched for articles published in English between 2015 and 8 July 2021. Fourteen peer-reviewed articles were selected for this study and were subjected to content analysis. Topics related to marine litter were frequently addressed. Meanwhile, topics related to teaching Environmental Education/Education for Sustainable Development (EE/ESD) were the least addressed. Benthic marine litter, solutions to marine litter and the introduction of new types of marine litter were identified as topics that need to be addressed in future marine litter education. This study lists content knowledge based on previous literature and identified the gaps, which will be useful for teachers to improve their knowledge and implement effective marine litter education in school.
The Role of Blockchain in Revolutionizing the Agricultural Sector
Authors: Alobid Mohannad , Abujudeh Said , Szűcs István
Published: April 2022

Since blockchain technology has proven to be effective in the development of a wide range of industries, its use in other fields is also being expanded. Agriculture is one such sector, where blockchain technology is being used to improve farm business operations. Today, several agribusiness firms are utilizing technology to improve food supply chain tracking. For example, Farmers Edge, the world’s leading company that revolutionized the field of digital agriculture through its work in providing advanced artificial intelligence solutions, as well as new opportunities that give agriculture a globally advanced future for all stakeholders, has taken a significant step forward. The issue of blockchain network technology and its applications in agriculture will be discussed in this study, as well as the key advantages that this technology can provide, when employed to make the lives of both producers and consumers easier. In addition, a total of 79 research papers were evaluated, with a focus on the state of blockchain technology in agriculture, related issues, and its future importance, as well as relevant contributions to this new technology and the distributions of this study by different countries.
Extensions of Orthogonal p-Contraction on Orthogonal Metric Spaces
Authors: Bilgili Gungor Nurcan
Published: April 2022

Fixed-point theory and symmetry are major and vigorous tools to working nonlinear analysis and applications, specially nonlinear operator theory and applications. The subject of examining the presence and inimitableness of fixed points of self-mappings defined on orthogonal metric spaces has become very popular in the latest decade. As a result, many researchers reached more relevant conclusions. In this study, the notion of ϕ-Kannan orthogonal p-contractive conditions in orthogonal complete metric spaces is presented. W-distance mappings do not need to satisfy the symmetry condition, that is, such mappings can be symmetrical or asymmetrical. Self-distance does not need to be zero in w-distance mappings. The intent of this study is to enhance the recent development of fixed-point theory in orthogonal metric spaces and related nonlinear problems by using w-distance. On this basis, some fixed-point results are debated. Some explanatory examples are shown that indicate the currency of the hypotheses and grade of benefit of the suggested conclusions. Lastly, sufficient cases for the presence of a solution to nonlinear Fredholm integral equations are investigated through the main results in this study.
Machine Reading at Scale: A Search Engine for Scientific and Academic Research
Authors: Sousa Norberto , Oliveira Nuno , Praça Isabel
Published: April 2022

The Internet, much like our universe, is ever-expanding. Information, in the most varied formats, is continuously added to the point of information overload. Consequently, the ability to navigate this ocean of data is crucial in our day-to-day lives, with familiar tools such as search engines carving a path through this unknown. In the research world, articles on a myriad of topics with distinct complexity levels are published daily, requiring specialized tools to facilitate the access and assessment of the information within. Recent endeavors in artificial intelligence, and in natural language processing in particular, can be seen as potential solutions for breaking information overload and provide enhanced search mechanisms by means of advanced algorithms. As the advent of transformer-based language models contributed to a more comprehensive analysis of both text-encoded intents and true document semantic meaning, there is simultaneously a need for additional computational resources. Information retrieval methods can act as low-complexity, yet reliable, filters to feed heavier algorithms, thus reducing computational requirements substantially. In this work, a new search engine is proposed, addressing machine reading at scale in the context of scientific and academic research. It combines state-of-the-art algorithms for information retrieval and reading comprehension tasks to extract meaningful answers from a corpus of scientific documents. The solution is then tested on two current and relevant topics, cybersecurity and energy, proving that the system is able to perform under distinct knowledge domains while achieving competent performance.
Systems Organize Information in Mind and Nature: Empirical Findings of Part-Whole Systems (S) in Cognitive and Material Complexity
Authors: Cabrera Derek , Cabrera Laura , Cabrera Elena
Published: April 2022

Part-whole Systems (S) structure is foundational to a diverse array of phenomena such as belonging and containment, networks, statistics, reductionism, holism, etc. and is extremely similar if not synonymous with sets, sorts, groups, combinations and combinatorics, clusters, etc. In Cabrera (1998), part-whole Systems (S) or “S-rule” is established as one of four universals for the organization of information and thus is foundational to systems and systems thinking as well as the consilience of knowledge. In this paper, seven empirical studies are presented in which (unless otherwise noted) subjects completed a task. Ranging from n = 407 to n = 34,398, the sample sizes vary for each study but are generalizeable to a normal distribution of the US population. With high statistical significance, the results of these studies support the predictions made by DSRP Theory regarding part-whole Systems (a.k.a., “S-rule”) including: the universality of S-rule as an observable phenomenon in both mind (cognitive complexity) and nature (ontological complexity) (i.e., parallelism); the internal structures and dynamics of S-rule; S-rule’s mutual dependencies on other universals of DSRP (Distinctions, Systems, Relationships, and Perspectives (i.e., Distinctions, Relationships, and Perspectives); the role S-rule plays in making structural predictions; and, S-rule’s efficacy as a metacognitive skill. In conclusion, these data suggest the observable and empirical existence, universality, efficacy, and parallelism (between cognitive and ontological complexity) of part-whole Systems (S).
A Video-Based Behavioral Intervention Associated with Improved HPV Knowledge and Intention to Vaccinate
Authors: Marshall Sarah , Moore Anne C. , Fleming Aoife , Sahm Laura J.
Published: April 2022

The aim of this study was to design, develop, and evaluate the feasibility of a theory- and evidence-based intervention to improve human papillomavirus (HPV) and HPV vaccine knowledge and intention to vaccinate, among parent–daughter dyads. A theory- and evidence-based online behavioral intervention, “Is the HPV vaccine for me?”, was developed to improve HPV and HPV vaccine knowledge and intention to vaccinate. Knowledge, intention to vaccinate, and feasibility of the intervention were evaluated in a prospective, randomized, controlled feasibility trial. A total of 49 parent–daughter dyads completed the baseline knowledge assessment (n = 24 control, n = 25 intervention), and 35 dyads completed the knowledge assessment at week 2 (n = 17 control, n = 18 intervention). The intervention resulted in a statistically significant increase in HPV and HPV vaccine knowledge and intention to vaccinate. All intervention participants found the video interesting, while 96% found it useful. This intervention was found to be useful, effective, safe, and acceptable in this feasibility study.
Transport Automation in Urban Mobility: A Case Study of an Autonomous Parking System
Authors: Plihal Jiri , Nedoma Pavel , Sestak Vladimir , Herda Zdenek , Aksjonov Andrei
Published: April 2022

Parking road vehicles is one of the most tedious and challenging tasks a human driver performs. Despite the low speeds involved, parking manoeuvres are among the main causes of minor and sometimes major traffic accidents, especially in urban areas where limited parking spaces are available. Furthermore, searching for a parking space wastes time and contributes to unnecessary road occupancy and pollution. This paper is dedicated to the development of an autonomous parking system for on-street parking in urban areas. The system is capable of fully automated parking manoeuvres from drop-off to pick-up zones, thus removing human drivers from the vehicle control loop. The system autonomously navigates to the parking space and parks the vehicle without human intervention. The proposed system incorporates a communication protocol that connects automated vehicles, parking infrastructure, and drivers. Several convenient human–machine interface concepts for efficient system communication and state monitoring have been developed. A methodology for validating the system in real time is proposed, which includes functionality requirements and a description of parallel and perpendicular parking manoeuvres. The proposed pipeline is tested on an electric vehicle platform with automated functions, where successful technological functionality is demonstrated.
Thermodynamic Study of Phosphate Adsorption and Removal from Water Using Iron Oxyhydroxides
Authors: Kalaitzidou Kyriaki , Zouboulis Anastasios , Mitrakas Manassis
Published: April 2022

Iron oxyhydroxides (FeOOHs) appear to be the optimal group of materials among inorganic adsorbents for the removal of phosphates from water, providing significant adsorption capacities. This research work presents a thermodynamic study of phosphate adsorption by examining five different FeOOHs sorbent nanomaterials. The otablebtained results indicated that the adsorption process in these cases was spontaneous. When the experiments were performed using distilled water, akageneite (GEH), schwertmannite, and tetravalent manganese feroxyhyte (AquAsZero), displaying ΔH° values of 31.2, 34.7, and 7.3 kJ/mole, respectively, presented an endothermic adsorption process, whereas for goethite (Bayoxide) and lepidocrocite, with ΔH° values of −11.4 and −7.7 kJ/mole, respectively, the adsorption process proved to be exothermic. However, when an artificial (according to NSF) water matrix was used, GEH, schwertmannite, lepidocrocite, and AquAsZero presented ΔH° values of 13.2, 3.3, 7.7, and 3.3 kJ/mole, respectively, indicative of an endothermic process, while only for Bayoxide, with ΔH° of −17 kJ/mole, the adsorption remained exothermic. The adsorption enthalpy values generally decreased with the NSF water matrix, probably due to the competition for the same adsorption sites by other co-existing anions as well to the possible formation of soluble phosphate complexes with calcium; however, an overall positive effect on the uptake of phosphates was observed.
Subarachnoid haemorrhage. A critical neurosurgical emergency
Authors: Bibiriță Alexandra , Teleanu Daniel , Ciurea Alexandru Vlad
Published: April 2022

Subarachnoid haemorrhage (SAH) accounts for 3% of all strokes and is the cause of 5% of stroke mortality. SAH by rupture of cerebral aneurysm or arterial-venous malformation (AVM) remains the most devastating cerebrovascular disease. During admission for SAH, about 30-70% of patients suffer a rebleed, and from all rebleeds, about 90% lead to death no matter the treatment. Available current scales help predict the prognosis and guide the therapy. Considering that the lifestyle risk factors for SAH are of increasing prevalence, it is expected that it will affect even more people in the future. SAH should not be regarded as a disease but rather a set of events with devastating complications requiring adequate management from debut extending long after patient discharge.
The stent-assisted coil-jailing technique for very small intracranial aneurysm treatment
Authors: Chiriac A. , Dobrin N. , Ion Georgiana , Faiyad Z. , Poeata I.
Published: April 2022

The stent-assisted coil-jailing technique was initially introduced as an effective and secure method in the treatment of large wide-necked intracranial aneurysms. Later on, this technique has proved its efficiency in the safety and optimal treatment of very small aneurysms. In this article, we will present the successful treatment of a very small middle cerebral artery aneurysm using the stent-assisted coil-jailing technique and review the current trends in this type of treatment.
Deep cerebral vein thrombosis due to anaemia in a child
Authors: Misra Rajneesh , Kumar Sushil , Sharma Sandeep
Published: April 2022

An eighteen-month-old child presented with vomiting, fever and altered sensorium of two days duration. He had anaemia and computed tomography of head revealed hyper-dense internal cerebral veins, vein of Galen and inferior sagittal sinus and bilateral thalamic hypo-density. The child improved with anti-coagulants and packed cell transfusion.
Visual outcome analysis in patients with posterior fossa tumours undergoing surgical treatment
Authors: Singh Deepak Kumar , Agrahari Vrihaspati Kumar , Kaif Mohd. , Kumar Rakesh , Yadav Kuldeep
Published: April 2022

Background: In the past, there were studies done to assess visual outcomes like visual acuity, fundoscopic findings and visual field mainly in pediatric patients with posterior fossa tumours (PFT). We assessed the above parameters pre- and post-operatively in all age group patients including both extra and intra-axial PFT. We also assessed visual outcome in patients with or without hydrocephalus.
Objectives: To analyze “visual outcomes in patients with posterior fossa tumours undergoing surgical treatment”. The effect of hydrocephalus on the visual outcome was also analyzed.
Materials and Methods: This prospective study including 107 patients with PFT undergoing definitive surgery was conducted in the Department of Neurosurgery at Dr Rmlims, Lucknow. Pre-op and post-op (six weeks after tumour resection) visual examinations were done and compared.
Results: A shifting trend towards normalization of visual acuity (VA) was seen post-surgery in all age groups. Overall improvement was seen in the majority of cases having pupil normal size sluggish reactive (NSSR) after surgery. Papilledema improved in the majority of patients in all age groups and patients having hydrocephalus. Colour vision and night vision also improved in the majority. The field of vision cut was not improved postoperatively in the majority.
Conclusion: Visual parameters like visual acuity, pupil size and reactivity to light; colour vision and night vision were improved significantly after surgery whereas cut field of vision did not improve. All fundoscopic findings like papilledema, retinal venous dilation and retinal splinters haemorrhage disappeared in a significant number of patients post-operatively. In cases with obstructive hydrocephalus, these parameters also improved significantly after Ventriculo-peritoneal shunt/ ETV or definitive surgery.
The use of corticosteroids in autoimmune encephalitis
Authors: Lozada Marintez Ivan David , Nahar-González Bryan Lester , Arevalo-Martínez Yandris , Quintana-Pajaro Loraine , Prada-Soto Silvia , Pacheco-Hernandez Teresa , Florez-Perdomo William , Picón-Jaimes Yelson Alejandro , Moscote-Salazar Luis Rafael
Published: April 2022

Autoimmune encephalitis (AE) is a brain inflammation caused by autoantibodies that target proteins, intracellular and extracellular antigens, triggering damage in the CNS; AE is classified in various syndromes caused by various antibodies, It is a diagnosis of exclusion. Therefore, it has to be differentiated from multiple causes that could unleash encephalitis. However, its treatment is based primarily on immunotherapy, where corticosteroids as immunosuppressive agents, play a key role in the treatment along with other agents.
Paediatric brain abscesses in tribal region of India
Authors: Jain Sachin Kumar , Jaiswal Gaurav , Gupta Tarun Kumar , Lodha Krishna Govind , Lohar Vishnu Kumar , Yadav Kaushal
Published: April 2022

Introduction: Brain parenchymal abscesses are relatively infrequent but potentially serious infections in the paediatric population. Surgical intervention in addition to a prolonged administration of antibiotics is generally appropriate management.
Aims and objective: We performed this study to assess the clinical profile, aetiology and outcome of paediatric brain abscess which are treated surgically only by aspiration in the tribal region of Rajasthan.
Material and method: A single-centre retrospective study was conducted over a 5 year period (2014–2019) in the department of neurosurgery in RNT medical college, Udaipur, Rajasthan. We treated approx 60 patients of which 25 patients treated conservatively and 5 patient treated by craniotomy and abscess excision. So only 30 patient included in our study in which abscess treated by aspiration only. Patients<18 years of age with a confirmed intra-parenchymal abscess were included. Patient records were reviewed for abscess location, microbiology results, Clinical features, Surgical intervention, and outcome using the Glasgow Outcome Score at 3 months.
Result: 11 patients had an abscess in the temporal lobe and Streptococcus was the most common causative micro-organism (n¼15). 25 patients (80%) had an identifiable source which included: ENT infections, congenital cardiac malformations, recent dental surgery and meningitis. The most common symptom is fever f/b headache, seizure and vomiting. But despite previous studies seizure (10/30) presentation is comparatively more. All 30 patients underwent aspiration.
Conclusion: In tribal regions of India ENT infections are a more common source of brain abscess because of poor hygiene and illiteracy and their ignorance of ENT infections and also not taking seriously to fever, headache and other health issues. But at present, there are also decreasing trends of brain abscess by ENT infections and rising trends by congenital heart disease which is a good sign that the health and educational infrastructure is strengthening in the tribal region also.
Lateral orbitotomy in the management of an intra-orbital lipoma
Authors: Cherkaoui Mandour , Houssaine Ait Lhaj El , Adil Khouya Ali , Miloudi Gazzaz , Brahim E.L. Mostarchid
Published: April 2022

Introduction: Lipomas are benign subcutaneous mass, but the intra-orbital location is rarely reported in the literature and it can resemble a variety of other orbital lesions.
Case report: We describe a 15-year-old girl who presented with left exophthalmia. Orbital magnetic resonance imaging showed an encapsulated intra-conal mass displacing the optic nerve medially, the external right muscle laterally and the globe anteriorly. Excisional biopsy of the mass by lateral orbitotomy approach resolved the exophthalmia, and histology revealed a primary orbital lipoma.
Conclusion: The diagnosis of an intra-orbital lipoma is not easy and the surgical approach represents a challenge to achieve a total excision while avoiding complications.
Primary calvarial cavernous haemangioma in a child
Authors: Adel Khelifa , Bennabi Walid , Berchiche Lakhdar , Morsli Abdelhalim
Published: April 2022

A wide variety of bone lesions is encountered on the skull and usually with poor clinical presentations and non-specific radiological features. Primary cavernous hemangioma is one of these rare calvarial lesions that the symptoms are limited to a simple subcutaneous mass frequently neglected by the patient. Although seen in all ages from neonate to elderly; few cases were reported in the literature of patients in the first decade of life. We report a case of four years old boy with primary calvarial cavernous hemangioma in order to help to understand this pathology and to urge physicians to explore any chronic subcutaneous mass at any age.
Shunt in scrotum: unusual shunt complication in an operated case of post TBM hydrocephalus
Authors: Agarwal Manoj , Pandey Sharad , Kumar Pankaj , Gupta L.N.
Published: April 2022

The role of shunt placement is to divert cerebrospinal fluid (CSF) from within the ventricles to an alternative location most commonly peritoneal space. Ventriculo Peritoneal Shunt (VPS) is associated with many complications viz over drainage, valve failure, breaking of catheter, catheter obstruction, coiling of catheter, spontaneous knot formation, infection and migration of distal catheter and all of them finally leading to obstructive hydrocephalus. One such complication is distal catheter migration to a rare but possible site i.e. scrotum. We reported a case of scrotal migration of shunt as a late complication of VPS insertion.