bluuebunny/crossref_metadata_2025 huggingface dataset:
Diagnostik peripherer Lungenrundherde: Kombination von konfokaler Laser-Endomikroskopie und robotergestützter Bronchoskopie
Authors: Kempa Axel Tobias
Published: January 2023

Die robotergestützte Bronchoskopie hat bei kleinen peripheren Lungenrundherden einen hohen Navigationserfolg gezeigt, die diagnostische Ausbeute ist jedoch deutlich geringer. Die nadelbasierte konfokale Laser-Endomikroskopie (needle-based confocal laser endomicroscopy, nCLE) ermöglicht eine mikroskopische Echtzeit-Bildgebung an der Nadelspitze. Ziel dieser Studie war es, die Durchführbarkeit, Sicherheit und Repositionierung der Nadel auf der Grundlage der nCLE-Echtzeitführung während der robotergestützten Bronchoskopie bei kleinen peripheren Lungenknoten zu untersuchen. Patienten mit Verdacht auf ein peripheres Lungenkarzinom unterzogen sich einer Fluoroskopie und einer radialen EBUS (endobronchialer Ultraschall)-gestützten Roboterbronchoskopie. Nach der Identifizierung des radialen EBUS-Knotens wurde eine nCLE-Bildgebung des betreffenden Bereichs durchgeführt. Zur Bestimmung des optimalen Entnahmeortes wurden die Kriterien nCLE-Malignität und Atemwege/Lungenparenchym herangezogen. Die Biopsienadel wurde neu positioniert, sobald die Atemwege sichtbar wurden. Nach der Bestätigung des nCLE-Tools im Rundherd wurde die Nadelbiopsie an derselben Stelle durchgeführt. Zwanzig Patienten wurden in die Studie eingeschlossen. Es traten keine Komplikationen auf. Bei 19 von 20 Patienten wurden nCLE-Videos von guter Qualität gewonnen. Bei 9 Patienten (45%) ergab die nCLE-Bildgebung in Echtzeit eine unzureichende Positionierung der Nadel, so dass eine Neupositionierung vorgenommen wurde. Nach der Neupositionierung lieferte die nCLE-Bildgebung bei 19 von 20 Patienten die Bestätigung, dass sich die Nadel im Herd befand. Die anschließende ROSE-Untersuchung ergab bei 9 von 20 Patienten (45%) repräsentatives Material, und die diagnos­tische Gesamtausbeute betrug 80% (16/20). Von den 3 Patienten mit malignem nCLE-Bildmaterial, aber unzureichender Pathologie, wurde bei 2 im Rahmen der Nachsorge ein Malignom diagnostiziert. Die robotergestützte bronchoskopische nCLE-Bildgebung ist gut durchführbar und sicher. Die nCLE-Bildgebung bei kleinen, schwer zugänglichen Lungenknoten lieferte zusätzliches Echtzeit-Feedback über die korrekte Sondenpositionierung mit dem Potenzial zur Optimierung der Entnahmestelle und der diagnos­tischen Ausbeute.
Safety and Feasibility of a Novel Externally Cooled Bronchoscopic Radiofrequency Ablation Catheter for Ablation of Peripheral Lung Tumours: A First-In-Human Dose Escalation Study
Authors: Steinfort Daniel P. , Antippa Phillip , Rangamuwa Kanishka , Irving Louis B. , Christie Michael , Chan Ewan , Marinelli Brett , Wang Jie , Yoneda Ken Y. , Raina Shashank , Herth Felix J.
Published: January 2023

Background: Radiofrequency ablation (RFA) is an established modality for percutaneous ablation of non-small cell lung cancer (NSCLC) in medically inoperable patients but is underutilized clinically due to side effects. We have developed a novel, completely endobronchial RFA catheter with an externally cooled electrode. Objectives: The objective of this study was to establish the safety and feasibility of bronchoscopic RFA using a novel, externally cooled catheter for ablation of peripheral NSCLC. Methods: Patients with stage I biopsy-confirmed NSCLC underwent bronchoscopic RFA of tumour 7 days prior to lobectomy. The RFA catheter was delivered bronchoscopically to peripheral NSCLC lesions, guided by radial endobronchial ultrasound, with positioning confirmed using intra-procedural cone beam CT. Pre-operative CT chest and histologic examination of resected specimens were used to establish distribution/uniformity of ablation and efficacy of tumour ablation. Results: RFA in the first patient was complicated by dispersal of heated saline due to cough, resulting in ICU admission. The patient recovered fully and underwent uncomplicated lobectomy. Subsequently, the protocol was altered to mandate neuromuscular blockade with a pre-determined dose escalation, with algorithm-restricted energy (kJ) and irrigated saline volume (mL) constraints. A further 10 patients consented and seven underwent successful bronchoscopic RFA of peripheral NSCLC. No significant adverse events were noted. Ablation zone included tumour in all cases (proportion of tumour ablated ranged 8–72%), with uniform necrosis of tissue within ablation zones observed at higher energy levels. Ablation zone diameter correlated with RFA energy delivered (R2 = 0.553), with maximum long axis diameter of ablation zone 3.1 cm (22.9 kJ). Conclusion: Bronchoscopic RFA using an externally cooled catheter is feasible, appears safe, and achieves uniform ablation within the treatment zone. Uncontrolled escape of heated saline poses a major safety risk but can be prevented procedurally through neuromuscular blockade and by limiting irrigation.
Phospholipase A2 Receptor Antibodies and Clinical Prognosis in Patients with Idiopathic Membranous Nephropathy: An Updated Systematic Review and Meta-Analysis
Authors: Zhang Jialing , Fan Zhengjia , Wang Peixin , Zhang Ai-Hua
Published: January 2023

Background: Idiopathic membranous nephropathy (IMN) is the most common form of primary nephrotic syndrome in adults. Antibodies against the M-type phospholipase A2 receptor (PLA2R-ab) are considered as diagnostic biomarkers of IMN. Objective: Here, we performed an updated meta-analysis to assess the diagnostic value of PLA2R-ab for clinical remission in IMN patients. Method: PubMed, Embase, and Cochrane databases were searched for relevant studies published before September 2022. Odds ratios and corresponding 95% confidence intervals were determined using a fixed or random effects model. The heterogeneity among studies was explored by subgroup analysis. Results: Sixteen studies involving 1,761 IMN participants were included. There were significant differences between PLA2R-ab (+) and PLA2R-ab (−) patients in terms of complete remission (CR) and spontaneous remission. The rates of partial remission (PR) and relapse were similar between the two groups. Patients with PLA2R-ab (−) were at a higher CR rate when treated with a calcineurin inhibitor or a treatment course for 3 months and 6 months, while the spontaneous remission rate was higher in PLA2R-ab seronegative patients from Asia. However, the CR and spontaneous remission rate only significantly declined in IMN patients with the highest titer, but not a middle titer, when compared to those with the lowest titer. Conclusion: In contrast with previous meta-analyses, our results verified that PLA2R-ab can likely predict CR and spontaneous remission in IMN patients, instead of PR and relapse. Race, immunosuppressive agents, and duration of treatment may affect the prognostic value of PLA2R-ab. Considering that the remission rate of IMN patients with a middle level of PLA2R-ab was not different from that of patients with the lowest level, a proper cut-off value of PLA2R-ab for prognosis should be clarified.
Body Composition Predictors of Complicated Crohn’s Disease
Authors: Barajas Ordonez Felix , Melekh Bohdan , Rodríguez-Feria Pablo , Melekh Oksana , Thormann Maximilian , Damm Robert , Omari Jazan , Pech Maciej , Surov Alexey
Published: January 2023

Background: High visceral adipose tissue (VAT) and creeping fat (CrF) in Crohn’s disease (CD) have been widely recognized. The VAT to subcutaneous adipose tissue (SAT) ratio and sarcopenia have been associated with CD complications. Studies regarding the influence of body composition predictors on CD complications assessed with magnetic resonance enterography (MRE) are scarce. Aim: The aim of this study was to assess body composition parameters and CrF in opportunistic MRE as predictors of complicated CD. Methods: This was a retrospective study of 114 patients with inflammatory (n = 54) and complicated (n = 60) CD. The semiautomated assessment of body composition and the qualitative evaluation of CrF were performed. Results: Body composition parameters did not differ between both groups regarding the body mass index (p = 0.50), total adipose tissue index (TATI) (p = 0.14), subcutaneous adipose tissue index (SATI) (p = 0.17), visceral adipose tissue index (VATI) (p = 0.33), VAT/SAT ratio (p = 0.77), intramuscular adipose tissue (p = 0.64), skeletal muscle index (p = 0.22), and sarcopenia (p = 0.50). 47 strictures, 18 fistulae, and seven abscesses were identified. Fistulae were more likely to occur in patients with CrF (odds ratio [OR] 5.07, 95% confidence interval [CI] 1.76–14.56; p=<0.001) and high VAT/SAT ratio (OR: 3.82, 95% CI 1.34–10.85; p = 0.01). Conclusion: Body composition measurements in CD patients displayed no statistically significant difference between the groups of inflammatory and complicated disease. Nonetheless, CD patients stratified in the group of high VAT/SAT ratio and the presence of CrF should be recognized as risk groups for the occurrence of fistulae.
Clinical Outcome and Treatment Sequences of Patients with Advanced Pancreatic Cancer Treated with Contemporary Chemotherapy Protocols
Authors: Roehrle Julius , Kasper Stefan , Treckmann Jürgen-Walter , Markus Peter , Schumacher Brigitte , Albers David , Wendling Johanna , Ting Saskia , Mende Bastian , Maßmann Marlene , Markus Maximilian , Virchow Isabel , Rosery Vivian , Laue Katharina , Zaun Gregor , Kostbade Karina , Pogorzelski Michael , Reissig Timm M. , Liffers Sven-Thorsten , Schmid Kurt , Schildhaus Hans-Ulrich , Schuler Martin , Siveke Jens T. , Wiesweg Marcel
Published: January 2023

Introduction: Systemic therapy is firmly established in patients with advanced or metastatic pancreatic ductal adenocarcinoma (PDAC). Clinical efficacy is still modest and options are limited. Combination therapy protocols such as FOLFIRINOX and gemcitabine/nab-paclitaxel (Gem/NP) define standard-of-care. Patients may receive a sequence of both regimens as first- and second-line palliative treatment. However, there is no guidance regarding a preferred order. Methods: This is a retrospective analysis of clinical characteristics, treatment trajectories, and outcomes of patients with advanced PDAC treated at the West German Cancer Center Essen from 2014 to 2020 to inform treatment decisions with respect to predictive factors, impact of chemotherapy regimen sequence, and maintenance treatment. Results: We identified 170 patients with available follow-up. Of those, 160 (94.1%) patients received palliative CTX for primary metastatic, locally advanced, or recurrent PDAC. Median progression-free survival (PFS) upon first palliative chemotherapy was 4.1 (3.1–5.9) months. First-line FOLFIRINOX was associated with superior PFS (median 6.3 months) and OS (9.7 months, HR 0.7, p = 0.03) as compared to Gem/NP or other regimens (PFS 3.0, OS 6.9 months). However, OS benefit of first-line FOLFIRINOX was lost in patients who received at least two treatment lines (median OS 12.1 vs. 13.1 months, p = 0.43). A landmark analysis of patients with clinical benefit (defined as CR/PR/SD for at least 20 weeks) upon first-line therapy revealed improved OS (HR 0.53, p = 0.02) for patients receiving continued deescalated maintenance therapy. Second-line regimens resulted in similar PFS (overall log-rank p = 0.92, median PFS upon second-line therapy 2.3 [1.8–2.9], per-regimen median between 1.8 and 3.9 months). A previously established systemic inflammation score proved to be strongly prognostic and allowed identification of a patient subgroup with dismal prognosis (OS 2.9 vs. 11.4 months, HR 5.23, p < 0.001), independent of other prognostic factors and with no relevant interaction with the choice of first-line regimen. Conclusion: In this real-world population of PDAC patients treated with contemporary combination chemotherapies, a positive impact of first-line FOLFIRINOX was only observed when no second or further line treatment was administered. Intensity-reduced maintenance therapy may lead to superior survival.
Optimization and fault diagnosis of 132 kV substation low-voltage system using electrical transient analyzer program
Authors: Mohammed Mohammed Kareem , Taha Mohammed Qasim , Salih Firas Fadhil , Saeed Falah Noori
Published: January 2023

In this paper, a simulation and analysis of 132 kV Substation in feeds western Iraq have been presented including a short circuit (S.C) analysis. This work helps to properly control and coordinate the protection equipment used in this grid interconnection spot. This work includes power flow analysis carried out using electrical transient analyzer program (ETAP) simulator. Also, the most common types of faults are investigated for the substation buses using International Electrotechnical Commission (IEC) and the American National Standards Institute (ANSI) standards to discover the behavioral characteristics under different scenarios for the substation transformers connection to assess the range of S.C current this substitution can ride through. Finally, the results of ANSI and IEC are theoretically investigated for validity to ensure reliability and quality assurance in the case study substation.
IEC 61850-9-2 based module for state estimation in co-simulated power grids
Authors: Celeita David , Rios Mario A. , Laverty David M. , Forero Jaime , Moreno-Jaramillo Andres F. , McLoone Sean
Published: January 2023

This paper presents a research context on the virtualization of phasor measurement units (PMUs) and real-time power grids simulation with state estimation. In this research, real-time simulation is introduced to use powerful features for validating state estimation solutions with PMUs. Virtual and online measurement equipment are reviewed in this manuscript to develop an innovative integration of the OpenPMU incorporated with a real-time simulation power grid and additional virtualized PMUs. The implementation of the platform has useful features within the infrastructure that allows the user to reproduce a detailed modeled power grid with simulation software. The use of real-time simulation tools brings several possibilities for improving testing and prototype assessment with higher precision in different applications. In this case, 2 tests power systems are evaluated by realistic integration of IEC61850-9-2 data utilization to observe the performance of a customized state estimation approach. The study implements a versatile methodology for commissioning OpenPMU devices, interacting simultaneously with additional virtual PMUs within the same simulation through sampled values (SV) to validate the measurement frames and assess the estimation with the generated data. Finally, the proposed work identifies the potential of virtualizing PMUs and the features of the OpenPMU applied to state estimation in conjunction with real-time simulation data.
Optimal interdigitated electrode sensor design for biosensors using multi-objective particle-swarm optimization
Authors: Sabiri Issa , Bouyghf Hamid , Raihani Abdelhadi
Published: January 2023

Interdigitated electrodes (IDEs) are commonly employed in biological cellular characterization techniques such as electrical cell-substrate impedance sensing (ECIS). Because of its simple production technique and low cost, interdigitated electrode sensor design is critical for practical impedance spectroscopy in the medical and pharmaceutical domains. The equivalent circuit of an IDE was modeled in this paper, it consisted of three primary components: double layer capacitance, Cdl, solution capacitance, CSol, and solution resistance, RSol. One of the challenging optimization challenges is the geometric optimization of the interdigital electrode structure of a sensor. We employ metaheuristic techniques to identify the best answer to problems of this kind. multi-objective optimization of the IDE using multi-objective particle swarm optimization (MOPSO) was achieved to maximize the sensitivity of the electrode and minimize the Cut-off frequency. The optimal geometrical parameters determined during optimization are used to build the electrical equivalent circuit. The amplitude and phase of the impedance versus frequency analysis were calculated using EC-LAB® software, and the corresponding conductivity was determined.
Evaluation of optical and synthetic aperture radar image fusion methods: a case study applied to Sentinel imagery
Authors: Monsalve-Tellez Jose Manuel , Garcés-Gómez Yeison Alberto , Torres-León Jorge Luís
Published: January 2023

This paper evaluates different optical and synthetic aperture radar (SAR) image fusion methods applied to open-access Sentinel images with global coverage. The objective of this research was to evaluate the potential of image fusion methods to get a greater visual difference in land cover, especially in oil palm crops with natural forest areas that are difficult to differentiate visually. The application of the image fusion methods: Brovey (BR), high-frequency modulation (HFM), Gram-Schmidt (GS), and principal components (PC) was evaluated on Sentinel-2 optical and Sentinel-1 SAR images using a cloud computing environment. The results show that the application of the implemented optical/SAR image fusion methods allows the creation of a synthetic image with the characteristics of both data sources. The multispectral information provided by the optical image and information associated with the geometry and texture/roughness of the land covers, provided by the SAR image, allows a greater differentiation in the visualization of the various land covers, achieving a better understanding of the study area. The fusion methods that visually presented greater characteristics associated with the SAR image were the BR and GS methods. The HFM method reached the best statistical indicators; however, this method did not present significant visual changes in the SAR contribution.
Hybrid NarrowBand-internet of things protocol for real time data optimization
Authors: Kurniawan Denny , Ashar Muhammad , Ar Rosyid Harits
Published: January 2023

The level of dependence on data communication in the modern era is increasing exponentially. The internet of things (IoT) plays a very important role in the advancement of the industrial revolution 4.0 that utilizes data communication systems. IoT deployments require data communication protocols, such as hypertext transfer protocol (HTTP), and message queuing telemetry transport (MQTT) as well as network communication protocols (wireless) to meet the network needs of devices with limited resources. Optimization of data communication in IoT is needed to maintain the quality of sending and receiving data in real time. This research proposes a hybrid NarrowBand-IoT (NB-IoT) protocol designed using NarrowBand communication network technology with optimization of data communication using MQTT and HTTP protocols. In this research, the hybrid NB-IoT protocol has the best packet loss value of 0.010% against the HTTP NB-IoT protocol which has a value of 0.017%, and the MQTT NB-IoT protocol of 0.024%. The hybrid NB-IoT protocol has a latency value of 8.7 seconds compared to the HTTP NB-IoT protocol which has a latency of 10.9 seconds. Meanwhile, the throughput value of the hybrid NB-IoT protocol is 158906.1 byte/s and is better than the MQTT NB-IoT protocol which is only 158898.6 bytes/s.
A transportation scheduling management system using decision tree and iterated local search techniques
Authors: Ganokratanaa Thittaporn , Ketcham Mahasak
Published: January 2023

This paper aimed to develop a delivery truck scheduling management system using a decision tree to support decision-making in selecting a delivery truck. First-in-first-out (FIFO) and decision tree techniques were applied to prioritize loading doors for delivery trucks with the use of iterated local search (ILS) in recommending the route for the transport of goods. Besides, an arrangement of loading doors can be assigned to the door that meets the specified conditions. The experimental results showed that the system was able to assign the job to a delivery truck under the specified conditions that were close to the actual operation at a similarity of 0.80. In addition, the application of ILS suggested the route of the food delivery truck in planning the most effective transportation route with the best total distance.
Lifetime enhanced energy efficient wireless sensor networks using renewable energy
Authors: Tagare Trupti Shripad , Narendra Rajashree
Published: January 2023

In this paper, we consider a remote environment with randomly deployed sensor nodes, with an initial energy of E0 (J) and a solar panel. A hierarchical clustering technique is implemented. At each round, the normal nodes send the sensed data to the nearest cluster head (CH) which is chosen on the probability value. Data after aggregation at CHs is sent to the base station (BS). CH requires more energy than normal nodes. Here, we energize only CHs if their energy is less than 5% of its initial value with the use of solar energy. We evaluate parameters like energy consumption, the lifetime of the network, and data packets sent to CH and BS. The obtained results are compared with existing techniques. The proposed protocol provides better energy efficiency and network lifetime. The results show increased stability with delayed death of the first node. The network lifetime of the proposed protocol is compared to the multi-level hybrid energy efficient distributed (MLHEED) technique and low-energy adaptive clustering hierarchy (LEACH) variants. Network lifetime is enhanced by 13.35%. Energy consumption is reduced with respect to MLHEED-4, 5, and 6 by 7.15%, 12.10%, and 14.975% respectively. The no. of packets transferred to the BS is greater than the MLHEED protocol by 39.03%.
Priority based energy efficient hybrid cluster routing protocol for underwater wireless sensor network
Authors: Murgod Tejaswini R , Sundaram S. Meenakshi , Manchaiah Sowmya , Kumar Santhosh
Published: January 2023

A little change in the environment that goes unnoticed in an underwater communication network might lead to calamity. A little alteration in the environment must also be adequately analyzed in order to deal with a potential crisis. A priority-based routing protocol is required to ensure that the vital data perceived by the sensor about the environment changes. The priority-based routing system guarantees that vital data packets are delivered at a quicker pace to the destination or base station for further processing. In this work, we present a priority-based routing protocol based on the energy efficient hybrid cluster routing protocol (EEHRCP) algorithm. The suggested approach keeps two distinct queues for lower and higher priority data packets. In order to ensure that these packets get at their destination without any information loss and at a quicker rate, all of the crucial sensed data is passed through a higher priority queue. Test findings show that the suggested technique increases throughput, delivery percentage, and reduces latency for the crucial data packets.
Residual balanced attention network for real-time traffic scene semantic segmentation
Authors: Kherraki Amine , Saqib Warraich Shahzaib , Maqbool Muaz , El Ouazzani Rajae
Published: January 2023

Intelligent transportation systems (ITS) are among the most focused research in this century. Actually, autonomous driving provides very advanced tasks in terms of road safety monitoring which include identifying dangers on the road and protecting pedestrians. In the last few years, deep learning (DL) approaches and especially convolutional neural networks (CNNs) have been extensively used to solve ITS problems such as traffic scene semantic segmentation and traffic signs classification. Semantic segmentation is an important task that has been addressed in computer vision (CV). Indeed, traffic scene semantic segmentation using CNNs requires high precision with few computational resources to perceive and segment the scene in real-time. However, we often find related work focusing only on one aspect, the precision, or the number of computational parameters. In this regard, we propose RBANet, a robust and lightweight CNN which uses a new proposed balanced attention module, and a new proposed residual module. Afterward, we have simulated our proposed RBANet using three loss functions to get the best combination using only 0.74M parameters. The RBANet has been evaluated on CamVid, the most used dataset in semantic segmentation, and it has performed well in terms of parameters’ requirements and precision compared to related work.
Slum image detection and localization using transfer learning: a case study in Northern Morocco
Authors: El Moudden Tarik , Dahmani Rachid , Amnai Mohamed , Aït Fora Abderrahmane
Published: January 2023

Developing countries are faced with social and economic challenges, including the emergence and proliferation of slums. Slum detection and localization methods typically rely on regular topographic surveys or on visual identification of high-resolution spatial satellite images, as well as socio-environmental surveys from land surveys and general population censuses. Yet, they consume so much time and effort. To overcome these problems, this paper exploits well-known seven pretrained models using transfer learning approaches such as MobileNets, InceptionV3, NASNetMobile, Xception, VGG16, EfficientNet, and ResNet50, consecutively, on a smaller dataset of medium-resolution satellite imagery. The accuracies obtained from these experiments, respectively, demonstrate that the top three pretrained models achieve 98.78%, 97.9%, and 97.56%. Besides, MobileNets have the smallest memory sizes of 9.1 Mo and the shortest latency of 17.01 s, which can be implemented as needed. The results show the good performance of the top three pretrained models to be used for detecting and localizing slum housing in northern Morocco.
Sentiment analysis in SemEval: a review of sentiment identification approaches
Authors: El Haddaoui Bousselham , Chiheb Raddouane , Faizi Rdouan , El Afia Abdellatif
Published: January 2023

ocial media platforms are becoming the foundations of social interactions including messaging and opinion expression. In this regard, sentiment analysis techniques focus on providing solutions to ensure the retrieval and analysis of generated data including sentiments, emotions, and discussed topics. International competitions such as the International Workshop on Semantic Evaluation (SemEval) have attracted many researchers and practitioners with a special research interest in building sentiment analysis systems. In our work, we study top-ranking systems for each SemEval edition during the 2013-2021 period, a total of 658 teams participated in these editions with increasing interest over years. We analyze the proposed systems marking the evolution of research trends with a focus on the main components of sentiment analysis systems including data acquisition, preprocessing, and classification. Our study shows an active use of preprocessing techniques, an evolution of features engineering and word representation from lexicon-based approaches to word embeddings, and the dominance of neural networks and transformers over the classification phasefostering the use of ready-to-use models. Moreover, we provide researchers with insights based on experimented systems which will allow rapid prototyping of new systems and help practitioners build for future SemEval editions.
Machine learning for internet of things classification using network traffic parameters
Authors: Elhaloui Loubna , El Filali Sanaa , Benlahmer El Habib , Tabaa Mohamed , Tace Youness , Rida Nouha
Published: January 2023

With the growth of the internet of things (IoT) smart objects, managing these objects becomes a very important challenge, to know the total number of interconnected objects on a heterogeneous network, and if they are functioning correctly; the use of IoT objects can have advantages in terms of comfort, efficiency, and cost. In this context, the identification of IoT objects is the first step to help owners manage them and ensure the security of their IoT environments such as smart homes, smart buildings, or smart cities. In this paper, to meet the need for IoT object identification, we have deployed an intelligent environment to collect all network traffic traces based on a diverse list of IoT in real-time conditions. In the exploratory phase of this traffic, we have developed learning models capable of identifying and classifying connected IoT objects in our environment. We have applied the six supervised machine learning algorithms: support vector machine, decision tree (DT), random forest (RF), k-nearest neighbors, naive Bayes, and stochastic gradient descent classifier. Finally, the experimental results indicate that the DT and RF models proved to be the most effective and demonstrate an accuracy of 97.72% on the analysis of network traffic data and more particularly information contained in network protocols. Most IoT objects are identified and classified with an accuracy of 99.21%.
Cloud service analysis using round-robin algorithm for quality-of-service aware task placement for internet of things services
Authors: Mohd Pakhrudin Nor Syazwani , Kassim Murizah , Idris Azlina
Published: January 2023

Round-robin (RR) is a process approach to sharing resources that requires each user to get a turn using them in an agreed order in cloud computing. It is suited for time-sharing systems since it automatically reduces the problem of priority inversion, which are low-priority tasks delayed. The time quantum is limited, and only a one-time quantum process is allowed in round-robin scheduling. The objective of this research is to improve the functionality of the current RR method for scheduling actions in the cloud by lowering the average waiting, turnaround, and response time. CloudAnalyst tool was used to enhance the RR technique by changing the parameter value in optimizing the high accuracy and low cost. The result presents the achieved overall min and max response times are 36.69 and 650.30 ms for running 300 min RR. The cost for the virtual machines (VMs) is identified from $0.5 to $3. The longer the time used, the higher the cost of the data transfer. This research is significant in improving communication and the quality of relationships within groups.
New hybrid ensemble method for anomaly detection in data science
Authors: Mohamed Elmahalwy Amina , Mousa Hayam M. , Amin Khalid M.
Published: January 2023

Anomaly detection is a significant research area in data science. Anomaly detection is used to find unusual points or uncommon events in data streams. It is gaining popularity not only in the business world but also in different of other fields, such as cyber security, fraud detection for financial systems, and healthcare. Detecting anomalies could be useful to find new knowledge in the data. This study aims to build an effective model to protect the data from these anomalies. We propose a new hyper ensemble machine learning method that combines the predictions from two methodologies the outcomes of isolation forest-k-means and random forest using a voting majority. Several available datasets, including KDD Cup-99, Credit Card, Wisconsin Prognosis Breast Cancer (WPBC), Forest Cover, and Pima, were used to evaluate the proposed method. The experimental results exhibit that our proposed model gives the highest realization in terms of receiver operating characteristic performance, accuracy, precision, and recall. Our approach is more efficient in detecting anomalies than other approaches. The highest accuracy rate achieved is 99.9%, compared to accuracy without a voting method, which achieves 97%.
Digital learning using Maktabah Syumilah NU 1.0 software and computer application for Islamic moderation in pesantren
Authors: Ibda Hamidulloh , Sofanudin Aji , Syafi’ Moh. , Soedjiwo Novena Ade Fredyarini , Azizah Ana Sofiyatul , Arif Muhamad
Published: January 2023

Digital learning through computer software and applications is rarely applied by pesantren (Islamic boarding schools) in Indonesia. So far, the application commonly used by traditional (salaf) pesantren, modern (khalaf) pesantren, and integrated pesantren is the Maktabah Syamila application. However, in Maktabah Syamila, religious radicalism, false hadiths, and texts allow the killing of innovators. Responding to this, pesantren activists developed digital learning through the application and computer program Maktabah Syumilah NU 1.0 as a comparison to Maktabah Syamila and an alternative to learning in pesantren as a counterradicalism. The research explores digital learning through Maktabah Syumilah NU 1.0 software and computer application to cultivate religious moderation in Temanggung Regency, Central Java, Indonesia. The qualitative research method with case studies on ten traditional pesantren using Maktabah Syumilah NU 1.0. The results show that digital learning through Maktabah Syumilah NU 1.0 is carried out in various activities in and outside the pesantren. The application of Maktabah Syumilah NU 1.0 is used to cultivate Islamic moderation for santri (students of pesantren). The use of Maktabah Syumilah NU 1.0 has an impact on strengthening Islamic moderation in pesantren. This research recommends that the Ministry of Religious Affairs implement Maktabah Syumilah NU 1.0 in all pesantren. Future researchers must explore digital learning more deeply through the latest applications for strengthening Islamic moderation in pesantren.
Measuring Is Making: The Radical Indeterminacy of Music
Authors: Lovett Matthew
Published: January 2023

In Meeting the Universe Halfway, the feminist theorist Karen Barad explores the indeterminate nature of measurement. Drawing on empirical research into quantum entanglement, they develop an axiomatic approach to configuring the fundamental interconnections between processes of measurement and making. This article builds on this aspect of Barad’s work and uses it to consider how an indeterminate measuring-as-making process might manifest in music. By staging an encounter between the composer John Cage’s investigations of indeterminacy and two contemporary pieces of music—Space Golf by Hen Ogledd and Wildfires by SAULT—the author considers how a Baradian theory of measuring-as-making can be used to offer new perspectives on musical creativity.
An updated key to the genus Limnophora Robineau-Desvoidy (Diptera: Muscidae) from China, with descriptions of two new species
Authors: DU BINTAO , LIU XIAOYAN , YANG DING
Published: January 2023

A key to the 80 species and 2 subspecies of the genus Limnophora Robineau-Desvoidy, 1830 from China based on males is provided, including two new species Limnophora magnipulvilla sp. nov. and Limnophora apiciflata sp. nov. Photographs of habitus and male genitalia as well as illustrations of the male genitalia of the new species are given.
Characteristics and Formation of Two Leading Marine Heatwave Modes in the North Indian Ocean during Summer and Their Implications for Local Precipitation
Authors: Sandaruwan Jayarathna W. N. D. , Zhou Wen , Cheung Paxson K. Y. , Du Yan , Wang Xuan
Published: January 2023

Marine heatwaves (MHWs) are extreme climatic events that can have a significant impact on marine ecosystems and their services across the world. We examine the spatiotemporal variation of summer MHWs in the north Indian Ocean (NIO) and find that the whole NIO Basin exhibits a pronounced spatial variability as well as a significant increasing trend in MHW frequency. We show that the NIO has two leading MHW modes linked to two distinct sea surface temperature (SST) patterns during summer. The first MHW mode is associated with basinwide warming, which is preconditioned by a decaying El Niño–Southern Oscillation (ENSO) and sustained throughout the summer by anomalous northeasterlies extending from the anticyclonic circulation of the western North Pacific subtropical high (WNPSH). The combined effect of thermocline warming due to downwelling oceanic planetary waves, decreased wind-induced evaporative cooling, and enhanced insolation cause basinwide summer MHWs. The second MHW mode exhibits a zonal dipole pattern, which has unfavorable cooling conditions in the previous seasons. The second MHW mode is associated with a phase change of ENSO and is greatly influenced by the formation of an interhemispheric pressure difference (IHPD) due to strengthening of the Australian high (AH) and weakening of the WNPSH. The IHPD induces cross-equatorial southerly winds across the eastern Indian Ocean. These winds favor the transformation of basinwide cooling conditions into zonal SST patterns via wind–evaporation–SST and thermocline–SST feedback, causing MHWs with a zonal dipole pattern. These MHW modes have a significant influence on the distribution and intensity of summer precipitation in the NIO.
Seasonal Features and Potential Mechanisms of Submesoscale Processes in the Southern Bay of Bengal during 2011/12
Authors: Cheng Xuhua , Li Lanman , Jing Zhiyou , Cao Haijin , Zhou Guidi , Duan Wei , Zhou Yifei
Published: January 2023

This study investigates the seasonal features and generation mechanisms of submesoscale processes (SMPs) in the southern Bay of Bengal (BoB) during 2011/12, based on the output of a high-resolution model, LLC4320 (latitude–longitude–polar cap). The results show that the southern BoB exhibits the most energetic SMPs, with significant seasonal variations. The SMPs are more active during the summer and winter monsoon periods. During the monsoon periods, the sharpening horizontal buoyancy gradients associated with strong straining effects favor the frontogenesis and mixed layer instability (MLI), which are responsible for the SMPs generation. The symmetric instability (SI) scale is about 3–10 km in the southern BoB, which can be partially resolved by LLC4320. The SI is more active during summer and winter, with a proportion of 40%–80% during the study period when the necessary conditions for SI are satisfied. Energetics analysis suggests that the energy source of SMPs is mainly from the local large-scale and mesoscale processes. Baroclinic instability at submesoscales plays a significant role, further confirming the importance of frontogenesis and MLI. Barotropic instability also has considerable contribution to the submesoscale kinetic energy, especially during summer.

Significance Statement

Submesoscale processes (SMPs) are ubiquitous in the Bay of Bengal (BoB). Affected by the seasonally reversing monsoon, abundant rainfall and runoff, and equatorial remote forcing, the upper circulation in the BoB is complex, featuring active mesoscale eddies and rich submesoscale phenomena, making the BoB a “natural test ground” for submesoscale studies. It is found in this work that characteristics of SMPs in the BoB are quite different from other regions. In the southern bay, SMPs are most active during the summer and winter monsoons due to the frontogenesis, enhanced mixed layer instability (MLI), and symmetric instability. These findings could deepen our understanding on multiscale dynamic processes and energy cascade in the BoB and have implications for the study of marine ecology and biogeochemical processes.
Ocean Tides near Hawaii from Satellite Altimeter Data. Part III
Authors: Zhang Yibo , Jiao Shengyi , Wang Yuzhe , Wang Yonggang , Lv Xianqing
Published: January 2023

The Chebyshev polynomial fitting (CPF) method has been proved to be effective to construct reliable cotidal charts for the eight major tidal constituents (M2, S2, K1, O1, N2, K2, P1, and Q1) and six minor tidal constituents (2N2, J1, L2, Mu2, Nu2, and T2) near Hawaii in Part I and Part II, respectively. In this paper, this method is extended to estimate the harmonic constants of four long-period tidal constituents (Mf, Mm, Sa, and Ssa). The harmonic constants obtained by this method were compared with those from the TPXO9, Finite Element Solutions 2014 (FES2014), and Empirical Ocean Tide 20 (EOT20) models, using benchmark data from satellite altimeters and eight tide gauges. The accuracies of the Mf and Mm constituents derived from the CPF method are comparable to those from the models, but the accuracies of the Sa and Ssa constituents are significantly higher than those from the FES2014 and EOT20 models. The results indicate that the CPF method is also effective for estimating harmonic constants of long-period tidal constituents. Furthermore, since the CPF method relies only on satellite altimeter data, it is an easier-to-use method than these ocean tide models.
Research on the Growth Experience of Presidents and Scientific Research Performance of Top Universities in China
Authors: Li Zhen , Zhong Lingna , Lu Yuling
Published: January 2023

More than half of the presidents in top universities of China have been grown up in their original universities. According to the upper echelon theory, the “indigenization” characteristics of university presidents will have an impact on their cognitive level and thus affect the scientific research performance of universities. Based on data from the National Natural Science Fund Projects and the National Social Science Fund Projects of China from 2007 to 2016, as well as individual characteristics of presidents, this paper empirically investigates the influence of the growth experience of presidents in 115 “Project 211” universities on scientific research performance. The results show that the presidents who grow up from the original universities have a significant negative impact on national fund projects, especially on the national natural science foundation projects. This paper suggest that the reason maybe the insufficient motivation and less access to external resources for native presidents. Some corresponding policy recommendations are proposed for this purpose.
On Capitalism and Imperialism: A Note Based on Prabhat Patnaik’s Contributions to Economic Theory
Authors: Chandrasekhar C. P. , Ghosh Jayati
Published: January 2023

From his days as a doctoral student, Prabhat Patnaik was convinced that given the structure and spontaneous logic of capitalism, its expansion and relative ‘stability’ could not be understood without incorporating the role of primitive accumulation and imperialism in its development. That quest made clear that without transcending capitalism and the spontaneity that came from its essential structure, it was impossible to ensure a just, egalitarian and sustainable social order. This article draws on a small corpus of his enormous work to highlight a few insights that emerged from his wide-ranging engagement with that critique and search for an alternative.

JEL Codes: B14, B24, B51, E11, N10, N20
Female Chief Marketing Officers: When and Why Do Their Marketing Decisions Differ from Their Male Counterparts’?
Authors: Varma Rajita , Bommaraju Raghu , Singh Siddharth S.
Published: January 2023

Firms have appointed a significant number of female chief marketing officers (CMOs) over the past decade. However, the question of how female CMOs differ from their male counterparts is yet to be explored. This research uses a multimethod approach to examine when and why female CMOs’ marketing decisions differ from those of male CMOs. In Study 1, the authors use secondary data to examine the effect of CMO gender on multiple marketing decisions and find that female CMOs make less risky decisions. Further, the authors find evidence that female CMOs’ risk-taking behavior is contingent on structural, organizational, and environmental factors (CEO gender, relative firm performance, and demand uncertainty). In Study 2, the authors employ the MarkStrat simulation, in which participants assume the role of CMO, to test the main finding from Study 1 in a controlled setting and provide evidence for the differential effect of gender on radical versus incremental new product introductions. In Study 3, the authors examine survey data to find evidence for the underlying mechanisms (overconfidence, failure avoidance orientation, and scrutiny) behind female CMOs’ lesser risk-taking behavior.
A review on the production of 17-4PH parts using press and sinter technology
Authors: Kareem Mohammed Qasim , Mikó Tamás , Gergely Gréta , Gácsi Zoltán
Published: January 2023

The press and sinter method remains the standard among powder metallurgy processes for powdered stainless-steel materials. It delivers low cost, low oxidation rate, and adequate corrosion resistance. Furthermore, 17-4PH is a martensitic stainless-steel that is commonly used for high-strength and medium-ductility stainless steel parts. However, a few studies have investigated the press and sinter method for producing 17-4PH parts. This shortage is due to the high hardness (low compressibility) of 17-4PH powder. Thus, the main objective of this study is to evaluate the press and sinter method in terms of the manufacturing process, the influencing factors, and the theoretical basis of press and sinter methods in conjunction with metal injection molding technology for the production of 17-4PH parts. First, the literature and monographs are examined and summarized to cover the previous results, research progress, development trends, and applications of press and sinter method 17-4PH parts. Following the theoretical analysis, the practical investigation was conducted by producing parts with cold pressing from 800 to 1600 MPa, followed by sintering: the sintering temperature was 1200 °C for one hour under a protective vacuum atmosphere. ImageJ analysis was performed to measure the sinter density. The results showed an increase in relative sinter density from 84.43% to 96.43% for 800 and 1600 MPa, respectively, while the earlier results reached 93.47%. Overall, the press and sinter method enables the production of high-hardness 17-4PH parts with a high density, without using additives like lubricants, wax, or alloying elements.
Beyond urban ecomodernism: How can degrowth-aligned spatial practices enhance urban sustainability transformations
Authors: De Castro Mazarro Alejandro , George Kaliaden Ritu , Wende Wolfgang , Egermann Markus
Published: January 2023

For spatial practices such as architecture, urban design and planning, degrowth remains an abstract concept, as there is no clear alignment of its principles into spatial strategies. To bridge this gap, this paper examines how degrowth can be operationalised into sustainable spatial practices. Through a review of more than 200 sustainable spatial projects across the world operating at the building, neighbourhood and citywide scales, the paper shows that while the majority of sustainable interventions representative of dominant architecture and urban design culture do not align to degrowth principles, a significant number of examples using sustainability strategies such as convivial technologies, building retrofitting, urban renaturation and revitalisation, eco-urbanisation and spatial infrastructure upgrading are in fact aligned to degrowth principles. We suggest that these examples form a potential stepping-stone to enable an urban design and building culture rooted in a degrowth agenda, however further research and conceptualisation are needed to enable this to happen.