bluuebunny/crossref_metadata_2025_split huggingface dataset:
A pedestrian trajectory prediction method based on improved LSTM network
Authors: Liu Fugang , Duan Songnan , Juan Wang 
Published: October 2023

AbstractPedestrian trajectory prediction based on vision is a popular task in autopilot system. As pedestrian trajectories always cross each other, pedestrian targets will frequently obscure each other, which makes the collected pedestrian trajectories produce errors. Moreover, the interaction between pedestrians will have an impact on their trajectories in crowded areas, which leads to great challenge in trajectory prediction. In order to solve the above two problems, a pedestrian trajectory prediction method is proposed. Based on the YOLOv7 algorithm, it is connected with the StrongSORT algorithm. Then adding a feature recognition (ReID) module to the model, the problem of target switching and jumping in the process of pedestrian tracking can be solved. The dot product attention mechanism is also integrated into the long short term memory (LSTM) algorithm, the improved LSTM correlate target position and distance information for the pedestrian trajectory prediction. Extensive experiments on three most challenging datasets showed that this method improves the performance and largely reduces the model size.
A parking occupancy prediction method incorporating time series decomposition and temporal pattern attention mechanism
Authors: Ye Wei , Kuang Haoxuan , Li Jun , Lai Xinjun , Qu Haohao 
Published: October 2023

AbstractParking occupancy prediction is an important reference for travel decisions and parking management. However, due to various related factors, such as commuting or traffic accidents, parking occupancy has complex change features that are difficult to model accurately, thus making it difficult for parking occupancy to be accurately predicted. Moreover, how to give appropriate weights to these changing features in prediction becomes a new challenge in the era of machine learning. To tackle these challenges, a parking occupancy prediction method called time series decomposition–long and short‐term memory neural network (LSTM)–temporal pattern attention mechanism, which consists of three modules, namely 1) time series decomposition: modelling parking occupancy changes by extracting features such as trend, period, and effect; 2) encoder: extracting temporal correlations of feature sequences with LSTM; 3) temporal pattern attention mechanism: assigning attention to different features, are proposed. The evaluation results of 30 parking lots in Guangzhou city show that the proposed model 1) improves accuracy over the baseline model LSTM by 9.14% on average; 2) performs outstanding in four prediction time intervals and six types of parking lots, proving its validity and generality; 3) demonstrates its rationality and interpretability through ablation experiments and Shapley additive explanation.
Millimetre‐wave radar‐based spirometry for the preliminary diagnosis of chronic obstructive pulmonary disease
Authors: Wang Wei , Wan Yinghua , Li Chengxi , Chen Zhaoxi , Zhang Wenyu , Zhao Lina , Zhao Jingquan , Mu Xiangdong , Li Gang 
Published: October 2023

AbstractChronic respiratory diseases, especially chronic obstructive pulmonary disease (COPD), have high morbidity and mortality worldwide. Spirometry is regarded as the gold standard for the diagnosis of COPD. However, conventional spirometry requires expensive devices and trained personnel. Therefore, it is not feasible for conventional spirometry to popularise outside the hospital. Millimetre‐wave radar has the characteristics of low cost and high integration. It can accurately capture the motion of the chest, which makes it possible to evaluate the pulmonary function of humans. A method to measure important respiratory indices in spirometry based on a 60‐GHz frequency‐modulated continuous‐wave radar system is proposed. The impact of body motion is reduced via a dedicated body twitch correction algorithm. A new fitting formula was utilised to estimate forced expiratory volume in one second and forced vital capacity. Experimental results demonstrated that millimetre‐wave radar‐based spirometry can achieve a high agreement with conventional spirometry. It is potential for radar‐based spirometry to be an alternative to conventional spirometry in the preliminary diagnosis of COPD outside the hospital.
A novel fault diagnosis method for PV arrays using convolutional extension neural network with symmetrized dot pattern analysis
Authors: Lu Shiue‐Der , Wu Chia‐Chun , Sian Hong‐Wei 
Published: October 2023

AbstractPV fault diagnosis remains difficult due to the non‐linear characteristic of PV output, which makes PV output to be likely disturbed by the ambient environment. This study proposes a novel convolutional extension neural network (CENN) algorithm, which is a jointed architecture based on convolutional neural network (CNN) and extension neural network (ENN), takes advantage of CNN and ENN. The CENN is combined with the symmetrized dot pattern (SDP) analysis method to diagnose the common eight PV array faults. The SDP is used to transform the measured PV signals into the point coordinate feature image; then, the CENN is trained to identify the different PV faults. Experimental results show an obvious improvement in short detection times and high accuracy compared with traditional CNN and the histogram of oriented gradient (HOG) extraction method with support vector machine (SVM), K‐nearest neighbours (KNN), and back propagation neural network (BPNN) classifiers, with 95.3%, 94%, 93.5%, and 93.3% accuracy, respectively. Using the proposed CENN, the accuracy can be raised to 97.3%. Additionally, the signals measured by various sensors are collected using programmable logic controller (PLC). The human–machine interface (HMI) and the proposed algorithm are developed using LabVIEW for graphical design. Finally, the information is transmitted to a tablet PC for performing real‐time remote monitoring.
Transient Hypoxemia Upon Initiation of Cardiopulmonary Bypass
Authors: Rohrer Charlene H. , Auvil Jackson , Vertrees Roger A. , Rousou John H. , Engelman Richard M. 
Published: October 2023

A review of 38 consecutive coronary artery bypass perfusions was undertaken with the goal to determine the efficiency of oxygenation with the BOS-10 oxygenator. In reviewing these 38 cases, six (16%) showed surprisingly low initial arterial oxygen tension (PaO2 56–70 torr). These six patients required active remedial measures to correct this deficit which was corrected within 10 minutes of continued perfusion. In addition, there were five more patients (13%) with initial PaO2 70–100 torr, or a total of eleven (29%) of the 38 cases with less than optimal PaO2. All of the initial blood gases were drawn after stabilization of perfusion flows and pressures, discontinuation of patient ventilation, and the initiation of moderate hypothermia (30°C). No explanation could be found for this transient hypoxemia which appeared to correlate only with a higher hematocrit in patients with the lowest oxygen tensions.
It has been observed that, on occasion, an unacceptably low arterial oxygen tension (PaO2) develops during the initial phase of routine perfusion. This observation prompted a review of the last 38 consecutive coronary artery bypass perfusions done in this institution. The review has shown that eleven (28.9%) of the cases done with the BOS-1 0* oxygenator had PaO2’s less than 100 torr. An attempt was therefore made to delineate the factors involved and to try to isolate the problem. Realizing fully that at a PaO2 of 70 torr, the hemoglobin is still well saturated, and probably is not detrimental to the anesthetized patient, six patients (16%) had truly depressed oxygenation with PaO2 56–0 torr and in these six patients, arterial desaturation could become a factor in successful perfusion.
Endpunkte zu mikrovaskulären Folgekomplikationen: klinische Endpunkte, patientenberichtete Endpunkte und Surrogatendpunkte, Methodik von Surrogatvalidierungsstudien
Authors: Gallwitz Baptist , Kellerer Monika , Müller-Wieland Dirk , Wanner Christoph , Ziemssen Focke 
Published: October 2023

ZusammenfassungFür die Bewertung und die Vergleichbarkeit klinischer Langzeitstudien zur Sicherheit und/oder Effektivität verschiedener Therapieformen bei chronischen Erkrankungen sind möglichst vergleichbare und homogene vorab festgelegte Endpunkte und Surrogatparameter wichtig. Am Beispiel des Diabetes mellitus Typ 2 als chronische Erkrankung wird die Erhebung mikrovaskulärer Endpunkte und von Surrogatparametern bei der diabetesbedingten Retinopathie und Nephropathie dargelegt und diskutiert.
Bewegung beim Menschen über 60 Jahre: aktuelle Studie auf der
Basis einer Forsa-Befragung
Authors: Albrecht Franziska , Dresel Uwe 
Published: October 2023

ZusammenfassungDurch den demografischen Wandel und die Zunahme sitzender Tätigkeit in
Alltag und Beruf wird das Gegensteuern durch körperliche
Aktivität und Bewegung gegen einen Abbau der physischen und kognitiven
Leistungsfähigkeit sowie gegen die Verschlechterung der Gesundheit durch
die Zunahme chronisch-degenerativer Erkrankungen mit zunehmendem Alter immer
entscheidender. Sowohl die WHO als auch nationale Bewegungsempfehlungen
unterstreichen die Wichtigkeit dieses Themas mit konkreten Mindestempfehlungen
für körperliche Aktivität auch und vor allem im Alter.
Aktuelle Ergebnisse einer Forsa-Umfrage der Krankenkasse DAK-Gesundheit zeigen
jedoch, dass die Mehrheit der Personen ab 60 Jahren in Deutschland diese
Empfehlungen nicht erreicht. Ab 80 Jahren erreicht nicht einmal jeder Dritte
diese Empfehlungen. Diese aktuellen Ergebnisse verdeutlichen die weitere Arbeit,
die notwendig ist, um körperliche Aktivität und Bewegung als
elementare Lebensbestandteile auch im Alter zu integrieren und im Rahmen der
Prävention über deren Wichtigkeit zu sensibilisieren. Auch die
Personengruppe ab 80 Jahren muss hier verstärkt adressiert werden.
Grußwort
Authors: Storm Andreas 
Published: October 2023

Sehr geehrte Leserinnen und Leser,der demografische Wandel führt dazu, dass immer mehr alte immer weniger
jungen Menschen gegenüberstehen. Damit ist die Pflege eine der
großen Herausforderungen für unsere Gesellschaft. Wir haben eine
Verantwortung für die Pflegebedürftigen und müssen
sicherstellen, dass ein Leben in Würde auch im Alter möglich ist und
die pflegerische Versorgung nicht zur Fürsorgefalle wird. Auf der anderen
Seite müssen Ausbildung und Arbeitsbedingungen von Pflegerinnen und Pflegern
attraktiv gestaltet sein. Entscheidend hierbei ist, auch die Gesundheit von
Pflegekräften in den Fokus zu nehmen – ein
verhältnismäßig hoher Krankenstand in der Branche erfordert
rasches Handeln.
POLKA und Digitalisierung: Über das Spielen zu mehr
Bewegung
Authors: Huber Gerhard 
Published: October 2023

ZusammenfassungDie Digitalisierung im Gesundheitswesen ist eine vordringliche Aufgabe der
Gesundheitspolitik. Gleichzeitig besteht ein dringender Bedarf an einer
regelmäßigen und nachhaltigen Bewegungsförderung in der
stationären Altenpflege. Die Erfüllung dieser Anforderung ist
angesichts der knappen Personalressourcen nur selten im notwendigen Umfang
möglich.Vor diesem Hintergrund wurde im Rahmen des Projektes POLKA eine digitale
Anwendung entwickelt, die über eine spielerische Aufgabe
(„Apfelpflücken“) die Bewegungsaktivitäten von
Bewohner*innen in stationären Altenpflegeeinrichtungen steigern
soll. Der Gesetzgeber fordert für solche „Gesundheitsanwendung
niedriger Risikoklasse“ die Evaluation von Machbarkeit und Nutzen der
Anwendung.In dem Beitrag wird zunächst der Forschungsstand zu
„Gamification“ in der Geriatrie vorgestellt. Das geplante
Vorgehen soll die technische und motivationale Akzeptanz des
„Apfelpflückspiels“ in der stationären
geriatrischen Versorgung sowie die Effekte auf der funktionellen Ebene
überprüfen.
A Facile, Mechanochemical, Solvent-, and Catalyst-Free Synthesis of Functionalized 4-Thiazolidinones
Authors: Bhargava Gaurav , Wahan Simranpreet K. , Chawla Pooja A. , Singh Parvesh , Kumar Rupesh 
Published: October 2023

AbstractA highly eco-friendly greener approach based on the mechanochemical method using mortar and pestle is explored for the preparation of a variety of functionalized 4-thiazolidinones. The developed methodology does not require the use of harmful or expensive reagents and organic solvents and requires very less reaction time with easy isolation. The explored greener approach for the synthesis of 4-thiazolidinones is an important in terms of their usefulness for their valuable pharmacological properties.
Hepatic Visceral Larva Migrans: A Case Series
Authors: Jain Suchita , Jain Ajay K. , Agrawal Praveen , Bhagat Priyanka , Chatterji Debi 
Published: October 2023

AbstractVisceral larva migrans is an uncommon systemic parasitic infection of liver caused by second-stage larva of Toxocara canis or Toxocara catis. The liver is the most common visceral organ to be involved. The diagnosis is usually delayed because of a lack of awareness about visceral larva migrans in adults, with most patients confused with either an abscess or neoplastic nodules. Heterogenous solid cystic, multiple hypodense, and hypovascular lesions on imaging with peripheral eosinophilia make the diagnosis in most cases. We present four adult patients with 2 to 4 weeks of fever and very high peripheral eosinophilia. The liver biopsy in three cases revealed an eosinophilic abscess. All cases on treatment with albendazole showed a good response. Visceral larva migrans must be considered in patients with heterogenous, hypovascular space-occupying liver lesions presenting with fever and peripheral eosinophilia.
Aiding Ukraine in the Russian war: unity or new dividing line among Europeans?
Authors: Stolle Dietlind 
Published: October 2023

AbstractThe Russian invasion of Ukraine has caused a seemingly high level of unity amongst Europeans in support of Ukraine. However, this article uncovers some inter- and intra-country fault-lines in public opinion across and within 16 EU countries and the UK regarding pro-Ukraine aid initiatives by using a two-wave design with data from the EUI-YouGov survey conducted in April and September 2022. Findings show that support is relatively stable but varies a lot depending on the specific measure and between countries. We uncover lowest support for measures that go against the self-interest of Europeans such as deploying troops and accepting higher energy costs. Frontrunners of Ukraine support are geographically close to Russia and located in both Western and Eastern Europe (though not exclusively), whereas laggards are countries of Eastern and Southern Europe with a history of Russian ties during the Cold War. Yet within countries, Ukraine support does not follow a simple pre-determined ideological pattern of the left and right. Most countries with lower overall support for Ukraine display a higher level of polarization between supporters of the incumbent versus the opposition party. Understanding these fault-lines is important for insights on current and future levels of Ukraine aid across Europe.
Global citizenship skills among Qatar University students
Authors: Alshawi Ali A. Hadi 
Published: October 2023

AbstractThe concept of the borderless environment, in the 21st century, has intensified global citizenship education and attracted tremendous attention from researchers and educators. This article explores the level of global citizenship in Qatar University students. This cross-sectional quantitative study examines Qatar University students’ perceptions of global changes. Data was collected from 10 colleges at Qatar University using a survey method based on Morais and Ogden’s global citizenship framework, and its elements of social responsibility, global competence and global civic engagement. The results of the cluster and correlation analyses reveal that all three elements of global citizenship skills (i.e., social responsibility, global competence and global civic engagement) apply to Qatar University students, to varying degrees. The demographic variables and global citizenship components (social responsibility, global competence, and global civic engagement) reveal Qatari students’ global citizenship skills, perceptions of a broader world, sense of being part of the world community, responsibility for contributing to the well-being of that community, understanding of diversity, politics and culture, and social, economic, environmental and technological functioning. The implications of the findings suggest ways policymakers, faculty, teachers and curriculum developers can develop robust global citizenship education.
Blending of Landsat and Sentinel images using Multi-sensor fusion
Authors: Bharathi D , Karthi R , Geetha P 
Published: October 2023

Abstract
Global surveillance based on remote sensing always has a trade-off between spectral, temporal, and spatial resolutions of the sensor data. Since unique land cover information could be estimated at a good spatial scale than the temporal resolution, the Sentinel sensor, for example, has a revisit of 5 days and gathers images at a 10-20m spatial resolution. The Landsat sensor can only be revisited every 16 days with a spatial scale of 30 m. Fine temporal and spatial resolution data are essential for seasonable observation of dynamic agricultural, environmental, or ecological phenomena. This trade-off problem can be solved by using fusion methods based on the linear differences between images with fine (Sentinel) and coarse (Landsat) spatial resolution. As a result, an image with high spatial resolution can be predicted than acquired from a single Landsat-like sensor. The proposed work will combine Landsat and Sentinel data to bridge the gap between the Landsat image (spatial resolution,30m) and the Sentinel image (temporal resolution,10m or 20m). As a result, detailed investigations of the Earth’s surface and dynamics will be possible. Evaluation metrics – RMSE, SRE, and SSIM are used to compare the predicted image with the Sentinel image of the predicted date. The metrics analysis found that the predicted image is like the reference image with optimal values for all three-evaluation metrics.
SOLMAT: A Neoteric Contextual Model for Odia Language Understanding
Authors: Dey G , Maringanti H B 
Published: October 2023

Abstract
In this era of digital revolution people are expressing their opinion in natural language text. So, people of Odisha staying inside or outside Odisha are also expressing their opinion in Odia language text through different online blogs, review sites, social networking sites etc. Natural Language researchers are now working on these opinions to extract the actual sentiment of people hidden inside these opinions. More than 67% of works are based on machine learning and deep learning. Rarely 29% are only lexicon and context based because the development of lexicon is little bit difficult and time consuming. However, the lexical based gives more accurate result as compared to machine learning approach. As the opinion is much deeper than surface meaning, there is need of contextual analysis of opinion statements. In this paper we have designed a context based model named SOLMAT-A Neoteric Contextual Model for Odia Language Understanding to understand contextual meaning of the object statement for which opinion is called by identifying objects on which the opinion is based on, the action performed by or on the object, type, time of action(Present, Past, Future) and the type of statement( positive, negative or neutral) before forecasting the opinion.
A novel application to develop illness severity scores for predicting mortality and morbidities in a Neonatal Intensive Care Unit (NICU)
Authors: Shirwaikar Rudresh Deepak , Dinesh Acharya U , Lamgaonkar Yogini Eknath , Lal Shivkumar Mahadev 
Published: October 2023

Abstract
The first hundred days of child life is considered the most critical phase of its physical development and its health. Neonates who are critically sick are kept under observation in a Neonatal Intensive Care Unit (NICU) for continuous monitoring of their health conditions. Classifying infants on the first day of admission based on illness severity score would help neonatologist in understanding the prognosis and better management of neonates at NICU. Illness severity scoring systems with a Score for Neonatal Acute Physiology (SNAP) and its variants was proposed to classify neonates based on its prognosis. A novel risk stratification module was developed which allowed neonatologist to design and develop an illness severity scoring system using the Richardson defined method. The SNAP I, modified SNAP I and SNAP II for the study population at study site was validated on 230 preterm neonates diagnosed with respiratory distress syndrome (RDS), apnea and sepsis as a retrospective study. All the scores predicted mortality with statistical significance, with improved accuracy performance (+ 15 to 25%) was seen with proposed modified SNAP I. The proposed modified SNAP I score was found to be most accurate compared to SNAP I and SNAP II for predicting the mortality and also other outcome measures such as severity of respiratory distress syndrome (RDS) (70%), presence of apnea (65%) and sepsis (80%) for the study population. Results obtained were strong indication of the need for scoring system where the variables as well as their range could be altered based on study population and NICU involved for the study.
Performance Analysis of SnO2/CsSnGeI3/CuSCN perovskite solar cells using SCAPS 1D Simulator
Authors: Deepak K , Sharath Chandra Reddy G. , Tiwari Chandni 
Published: October 2023

Abstract
In this paper, we have used Cesium tin-germanium triiodide (CsSnGeI3) perovskite-based solar cells (PSC). Here, SnO2 and CuSCN have been used as electron transport and hole transport layers, respectively. We have optimized the performance parameters of this device using an open-source software known as Solar cell capacitance simulator (SCAPS–1D). We have varied the thickness of absorber layer to understand its impact on the efficiency of the proposed solar cell. We have also varied the interface defects and defect density of absorber layer to optimize the performance of this device. Further, we have also varied the thickness of ETL and HTL with respect to absorber layer to determine the best suitable thickness of all the layers. Later, we have varied the electron affinity of ETL layer to determine the most suitable value. Finally, we have varied the work function of the back metal contact to understand its influence on the efficiency of the solar cell. The analysis indicates that the highest obtained efficiency of this device is 31.97% and the observed open circuit voltage and fill factor is 1.25 V and 89.97%, respectively.
Efficient Object Detection for Micro Aerial Vehicle Navigation Using Enhanced SSD-HOG Descriptors
Authors: Salokhe Gururaj , Bhamare Sushant , Kodanda Ramayya A , Anbarasu B 
Published: October 2023

Abstract
Autonomous robots, such as micro aerial vehicles (MAVs), require object detection for navigation and inspection tasks. However, the limited computational resources and real-time constraints of MAVs make object detection challenging. To address this, we propose an efficient object detection method for MAVs using enhanced SSD-HOG descriptors. Our method combines HOG and SSD techniques to create enhanced descriptors that provide better object detection accuracy and efficiency than traditional HOG or SSD descriptors. We evaluate our method on an aerial image dataset and compare it with state-of-the-art methods like SSD and YOLO. Our experimental results demonstrate that our method achieves high accuracy and real-time performance while using limited computational resources. Our proposed method is ideal for MAV navigation applications that require real-time object detection with limited computational resources.