bluuebunny/crossref_metadata_2025 huggingface dataset:
An Automatic Privacy‐Aware Framework for Text Data in Online Social Network Based on a Multi‐Deep Learning Model
Authors: Liu Gan , Sun Xiongtao , Li Yiran , Li Hui , Zhao Shuchang , Guo Zhen
Published: November 2023

With the increasing severity of user privacy leaks in online social networks (OSNs), existing privacy protection technologies have difficulty meeting the diverse privacy protection needs of users. Therefore, privacy‐aware (PA) for the text data that users post on OSNs has become a current research focus. However, most existing PA algorithms for OSN users only provide the types of privacy disclosures rather than the specific locations of disclosures. Furthermore, although named entity recognition (NER) technology can extract specific locations of privacy text, it has poor recognition performance for nested and interest privacy. To address these issues, this paper proposes a PA framework based on the extraction of OSN privacy information content. The framework can automatically perceive the privacy information shared by users in OSNs and accurately locate which parts of the text are leaking sensitive information. Firstly, we combine the roformerBERT model, BI_LSTM model, and global_pointer algorithm to construct a direct privacy entity recognition (DPER) model for solving the specific privacy location recognition and entity nesting problems. Secondly, we use the roformerBERT model and UniLM framework to construct an interest privacy inference (IPI) model for interest recognition and to generate interpretable text that supports this interest. Finally, we constructed a dataset of 13,000 privacy‐containing texts for experimentation. Experimental results show that the overall accuracy of the DPER model can reach 91.80%, while that of the IPI model can reach 98.3%. Simultaneously, we compare the proposed model with recent methods. The analysis of the results indicates that the proposed model exhibits better performance than previous methods.
Be Aware of the Benefits of Drafting in Sports and Take Your Advantage: A Meta-Analysis
Authors: van den Brandt Floor A. P. , Khudair Mohammed , Hettinga Florentina J. , Elferink-Gemser Marije T.
Published: November 2023

Purpose. In competitive sports, optimizing performance is the key. An interesting venue to explore is to consider drafting as a pacing strategy. The purpose of this study is to identify the magnitude of drafting benefits for biomechanical, physiological, and psychobiological parameters in and between athletes in cycling, kayaking, running, skating, skiing, and swimming. Design. A systematic review and meta-analysis. Methods. Systematic searches were performed in PubMed, Web of Science, and Embase databases. Results. In total, 205 studies were found, from which 22 were relevant (including 232 participants and 548 observations). Methodological quality was high for all the included articles. The meta-analyses for all parameters indicated strong evidence for a benefit of drafting, with moderate effects between leading and drafting athletes found for the heart rate (3.9%), VO2 (8.9%), power output (11.3%), and rating of perceived exertion (10.4%). Large effect sizes were found for blood lactate (24.2%), VE (16.2%), and EMG (56.4%). A moderator analysis showed differences between sports on the effect of drafting with most benefits in cycling. Discussion. Based on the observed effects of drafting in the biomechanical, physiological, and psychobiological parameters, it can be considered as an element of pacing, a strategy to conserve energy and optimize performance. Conclusion. There is strong evidence that drafting benefits athletes, with varying levels of effect for athletes in different sports. Knowledge about the magnitude of benefits can be used to improve training sessions, race strategies, and performance in competition.
Topological Complexity and LS-Category of Certain Manifolds
Authors: Akhtarifar Fezzeh , Asadi-Golmankhaneh Mohammad A.
Published: November 2023

The Lusternik–Schnirelmann category and topological complexity are important invariants of topological spaces. In this paper, we calculate the Lusternik–Schnirelmann category and topological complexity of products of real projective spaces and their wedge products by using cup and zero-cup length. Also, we will find the topological complexity of

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Characterization of the Active Ingredient and Prediction of the Potential Mechanism of Dahuoluo Pill via Mass Spectrometry with the Network Pharmacology Method
Authors: Xu Haoran , Bi Yuelin , Feng Xin , Wang Jiaqi , Yu Gengyuan , Zhang Tonghua , Li Tianyi , Gao Xuhua , Liu Runhua , Sun Yu , Wu Hao , Fang Linlin , Zhang Chenning , Sun Yikun
Published: November 2023

The Dahuoluo pill (DHLP) is a classic Chinese patent medicine used to treat rheumatoid arthritis and other conditions. However, there has been no research on the chemical components of DHLP and the mechanisms by which it ameliorates rheumatoid arthritis. Hence, we analysed the chemical components of DHLP and the DHLP components absorbed in blood by using ultraperformance liquid chromatography-Q-exactive-orbitrap-mass spectrometry. We then used network pharmacology to predict the underlying mechanisms by which DHLP ameliorates rheumatoid arthritis. We identified 153 chemical compounds from DHLP, together with 27 prototype components absorbed in blood. We selected 48 of these compounds as potential active ingredients to explore the mechanism. These compounds are related to 88 significant pathways, which are linked to 18 core targets. This study preliminarily reveals the potential mechanisms by which DHLP ameliorates rheumatoid arthritis and provides a basis for further evaluation of the drug’s efficacy.
A Prediction Model for Neonatal Coarctation Repair Involving Fetal and Neonatal Echocardiographic Parameters
Authors: Shi Qi , Tang Jiazhong , Zhang Minjie , Chen Sun , Wu Yurong , Lu Yanan
Published: November 2023

Objective. The aim of this study is to investigate the predictive value of fetal and neonatal echocardiographic parameters for neonatal coarctation repair in fetuses suspected of coarctation of the aorta (CoA), establish a prediction model for neonatal coarctation repair, and verify its predictive effectiveness and clinical applicability. Methods. From September 2017 to September 2022, fetuses suspected with CoA were enrolled. They were divided into two groups based on the need for neonatal coarctation repair. Fetal and neonatal echocardiographic parameters and clinical characteristics were collected retrospectively. Univariate and multivariate logistic regressions were applied to select significant predictors, which were further used to establish the nomogram prediction model. The area under the curve (AUC) of the receiver operating characteristic (ROC) was employed to quantify its discrimination ability. The calibration curve was drawn for internal verification, and the decision curve analysis (DCA) and clinical impact curve (CIC) were used to evaluate the clinical applicability of the prediction model. Results. This study included 50 infants suspected of CoA prenatally, of which 16 (32%) received aortic coarctation repair in the neonatal period and 34 (68%) did not. Multivariable logistic regression analysis revealed that the fetal echocardiographic parameter aortic isthmus/ductus arteriosus (AoI/DA) diameter ratio and the neonatal echocardiographic parameters such as the distance from left common carotid to left subclavian artery (LCSA) and the diameter of distal transverse aortic arch (DTAA) were independent predictors for neonatal coarctation repair. The ROC curve of the model showed excellent predictive value (AUC = 0.943). The calibration curve of the prediction model exhibited good fitness. The DCA and CIC demonstrated that the model had good clinical utility. Conclusion. The prediction model, which combines the fetal echocardiographic parameter AoI/DA diameter ratio and the neonatal echocardiographic parameters distance of LCSA and DTAA diameter, has an exceptional level of clinical value and prediction accuracy.
Local Entropy-Based Coupled Anisotropic Diffusion for Detail-And Edge-Preserving Smoothing
Authors: Zhao De , Chen Lan
Published: November 2023

It is important in image restoration to remove noise while preserving sharp edges and fine details such as blurred thin edges and low-contrast fine feature. The Perona–Malik (P-M) model is a well-known anisotropic diffusion denoising model, which can effectively remove noise while preserving edges. However, its diffusion coefficient only associates with the gradient of each pixel but not with the local region information; thus, the P-M model is not able to effectively preserve the important details of image. To address this problem, this paper proposes an anisotropic diffusion denoising model based on local entropy. The diffusion coefficient of the new model not only depends on the gradient of image but also on the local region information described by local entropy. On this basis, a coupled anisotropic diffusion scheme is proposed for detail-and edge-preserving smoothing. Experimental results show that the proposed model not only can effectively remove noise while preserving the boundaries better but also can maintain important details in an image very well.
High-Intensity Transient Signals Detected in a Renal Allograft
Authors: Kaadi Lea , Lahoud Christele , Hachem Samir , Smayra Tarek , Hachem Kamal
Published: November 2023

High-intensity transient signals (HITS) are signals recorded by the Doppler ultrasounds, reflecting either the passage of microemboli, both solid or gaseous in the vessels, or artifacts. Their identification during Duplex US highlights the need for further evaluation to rule out a potential embolic source. A 49-year-old female was referred to our hospital for renal transplantation. The Doppler ultrasound done on day 4 after the surgery revealed the presence of high-intensity transient signals (HITS) suggesting the passage of an emboli. Renal magnetic resonance angiography (MRA) confirmed the presence of peripheral parenchymal defects suggestive of a distal embolus. A better understanding and recognition of this radiological sign are essential in order to initiate appropriate patient management when needed. In this report, we review the importance of HITS and present a case in which HITS were detected in an unusual location: an allograft kidney artery.
Figure S2 from Cancer Relevance of Circulating Antibodies Against LINE-1 Antigens in Humans
Authors: Vylegzhanina Alexandra V. , Bespalov Ivan A. , Novototskaya-Vlasova Ksenia A. , Hall Brandon M. , Gleiberman Anatoli S. , Yu Han , Leontieva Olga V. , Leonova Katerina I. , Kurnasov Oleg V. , Osterman Andrei L. , Dy Grace K. , Komissarov Alexey A. , Vasilieva Elena , Gehlhausen Jeff , Iwasaki Akiko , Ambrosone Christine B. , Tsuji Takemasa , Matsuzaki Junko , Odunsi Kunle , Andrianova Ekaterina L. , Gudkov Andrei V.
Published: November 2023

Supplementary Figure S2 shows anti‐ORF1p, anti‐ORF2p IgG titers and anti‐p53 IgG signals in serum samples of patients with 14 cancer types and healthy individuals.
Clear Cell Carcinoma Arising in Low-Grade Mullerian Adenosarcoma: First Reported Case with Insight into Molecular Profile
Authors: Gašljević Gorana , Vivod Gregor , Škerl Petra , Novaković Srdjan
Published: November 2023

Uterine adenosarcoma (AS) is a rare biphasic neoplasm composed of a malignant, usually low-grade stromal component and benign epithelial component, usually endometrioid. Pathogenesis is unknown; some cases are undoubtably associated with tamoxifen use. Endometrial clear cell carcinoma (CCC) is an aggressive subtype of endometrial cancer, accounting for less than 10% of all uterine carcinomas. The etiology is unknown but can rarely be associated with Lynch syndrome and tamoxifen administration. The development of a composite neoplasm consisting of adenocarcinoma in AS is extremely rare. Endometrioid carcinoma typically represents the epithelial component of the composite tumor. Here we present the very first case of composite tumor, namely, AS with CCC in which next-generation sequencing was performed. Patient was an 85-year-old woman treated with tamoxifen for 5 years. To better understand the pathobiology of two tumors, a targeted genomic analysis of both components was performed. We found seven identical somatic variants in the samples of both tumors, indicating that the tumors have a high probability of having the same origin. Dual amplification of CDK4 and MDM2 was the most likely primary cause of tumor formation, but also one driver variant in the DHX15 gene that was present in both tumor components, suggesting that DHX15 may play an important role in the initiation and development of sarcoma and carcinoma. The patient is followed by regular clinical controls and is alive without signs of disease recurrence 18 months after surgery.
Designing a framework for blockchain-based e-voting system for Libya
Authors: Khalifa Salem S. M. , Ejmaa Ali Mohamed E. , Najih Abdulmawla Mohammad Ali , Zneen Mohamed Abd Arahman Masoud
Published: November 2023

A transition to democratic rule is considered the first step down a long road towards Libya’s recovery and prosperity. Thus, it strives to improve the country’s elections by introducing new technologies. A blockchain is a distributed ledger that is characterised by independence and security. Therefore, it has been widely applied in various fields ranging from credit encryption and digital currency. With the development of internet technology, electronic voting (E-voting) systems have been greatly popularised. However, they suffer from various security threats, which create a sense of distrust among existing systems. Integrating blockchain with online elections is a promising trend, which could lead to make an election transparent, immutable, reliable, and more secure. In this paper, we present a literature review and a case analysis of blockchain technology. Moreover, a framework for an E-voting system based on blockchain is proposed. The methodology is adopted on the basis of three activities, they are identification of the relevant literature about E-voting, system modelling, and the determination of suitable technological tools. The framework is secure and reliable. Thus, it could help increase the number of voters and ensure a high level of participation, as well as facilitate free and fair electoral processes
Hybrid transformation with first order statistics for medical image analysis and classification
Authors: George Loay E. , Abdullah Maryam Yaseen , Abdulhassan Raghad K. , Al_Qaisi Asmaa Abdulrazzaq
Published: November 2023

Skin cancer, one of the most critical forms of cancer, required early detection and documentation for efficient treatment, especially as certain types are fatal. In this study, an artificial neural network (ANN) was utilized to discover and index diverse melanomas using the ISIC 2018 dataset. The pre-processing phase is stringent as it insulates the cancerous fraction of a skin image, involving removing, trimming, thinning, and normalizing. In this phase, unwanted hair pieces on the image are eliminated in this phase. Feature extraction from the clipped image is achieved using a discrete cosine transform (DCT) and a gradient transform to transform it into frequency-domain coefficients. Statistical feature extraction is used to reduce the amount of data required for ANN training. A dataset from ISIC 2018 that consists of seven different images from dermoscopic procedures for classification purposes is used in the empirical investigation. An accuracy of 85.44% for DCT in the sub-bands and 76.07% for the sub-band gradient transform was achieved by the applied ANN. The hybrid system's mean squared error (MSE) was discovered to be 3.52×10-4. The work highlights the potential of ANN in the early detection of skin cancer, supporting more efficient treatment and preventing advanced cases.
Agile adoption challenges in insurance: a systematic literature and expert review
Authors: Putra Munandar Krishna Yudhakusuma , Raharjo Teguh
Published: November 2023

The drawback of agile is struggled to function in large businesses like banks, insurance companies, and government agencies, which are frequently associated with cumbersome processes. Traditional software development techniques were cumbersome and pay more attention to standardization and industry, this leads to high costs and prolonged costs. The insurance company does not embrace change and agility may find themselves distracted and lose customers to agile competitors who are more relevant and customer-centric. Thus, to investigate the challenges and to recognize the prospect of agile adoption in insurance industry, a systematic literature review (SLR) in this study was organized and validated by expert review from professional with expertise in agile. The project performance domain from project management body of knowledge (PMBOK) was applied to align the challenges and the solution. Academicians and practitioners can acquire the perception and knowledge in having exceeded understanding about the challenge and solution of agile adoption from the results.
A new approach to solve the problem of partial shading in a photovoltaic system
Authors: Abdessamad Benlafkih , El Idrissi Mohamed Chafik , Hadjoudja Abdelkader , El Moujahid Yassine , El Maliki Anas , Othmane Echarradi , Mounir Fahoume
Published: November 2023

This paper introduces a novel global maximum power point (GMPP) tracking method that addresses the challenges of efficiency and power quality degradation in photovoltaic (PV) systems caused by inadequate tracking of the GMPP. The proposed approach employs a cuckoo search algorithm with proportional, integral, and derivative (CSPID). A bio-inspired optimization technique, to effectively track the GMPP under varying weather conditions. To demonstrate its effectiveness, the CSPID algorithm is comprehensively evaluated against two well-established methods, particle swarm optimization (PSO), and cuckoo search algorithm traditional (CSA). The evaluation includes three different scenarios with gradual changes in irradiance and temperature, these tests show the ability of the algorithm to handle the condition of partial shading. The results reveal that the CSPID method achieves an average tracking time of 0.098s and an average tracking efficiency of 99.62%, thereby significantly improving the efficiency and quality of photovoltaic energy production.
Novel broadband circularly polarized pentagonal printed antenna design for wireless power transmission applications
Authors: En-Naghma Walid , Halaq Hanan , El Ougli Abdelghani
Published: November 2023

This paper provides a new conception for a microstrip patch antenna array that operates in a circularly polarized manner for wireless power transmission (WPT) at 2.45 GHz. The proposed conception combines four pentagonal patches and the defected ground structure (DGS) method. The antenna array with a dielectric constant of 4.4 and a tangential loss of 0.025 is printed on a FR4 where its thickness is about 1.58 mm. The developed design aims to optimize the antenna array performance. Th e main contribution, to the telecommunications and WPT fields, is to achieve a maximum energy transfer with low losses, while also ensuring adequate adaptation to the excitation port. To prove the effectiveness of this design, simulation results were obtai ned using computer simulation technology microwave studio (CST MWS) software and validated by another solver high - frequency structure simulator (HFSS). Simulation results are presented and compared with those obtained using existing conceptions in the lite rature. The proposed design has proven to be very effective in achieving the intended objectives, which makes this design very good for radiofrequency (RF) energy collection and its various applications to power a variety of devices without harming our pla net.
A novel hybrid radio over fiber visible light communication system combining 5G mmWave and coarse wavelength division multiplex grid
Authors: Towfiqur Rahman Muhammad , Parthiban Rajendran , Bakau Masud
Published: November 2023

Visible light communication(VLC)has gained attention for enabling gigabitdata transmission over a short-range. Inradio over fiber (RoF), modulatedradio frequency (RF) is carried over optical fiber. Millimeter-wave (mmW)range also offers a vast amount of spectrum and enables integration with RoF.We propose a novel hybrid network using mmWave based RoF backhaulandcoarse wavelength division multiplexed(CWDM)-VLC for indoorcommunication. Three different optical tones were introduced to produce thedesired mmW signal using optical heterodyning with one of them carryingmodulated data and the other two carrying unmodulated data. Opticalsideband signal with the carrier(OSSB+C) is used for uplink communication.Modulated mmWave signal is used for VLC downlink to drive a multi-colorCWDM system. The performance of the VLC downlink is measured usingdifferent optical filters such as Bessel, Trapezoidal, Gaussian, and FabryPerot. A maximum data rate of 2.64 Gb/s and 6.58 Gb/s were achieved with10 and 20channelsoff the shelf LEDs with 16quadrature amplitudemodulation (QAM) with reasonable BER for downlink VLC communication.The uplink communication was carried out using mmW with 2.5 Gb/s datarate usingon-off keying(OOK)modulation and the data from thiscommunication down converted atcentral office(CO) through RoF backhaul.
A study of stereo matching algorithm on low texture and depth discontinuity regions
Authors: Gan Yeou Wei Melvin , Affendi Hamzah Rostam , Syahrim Nik Anwar Nik , Irwan Herman Adi
Published: November 2023

This article studies the performance of the proposed stereo matchingalgorithm on complex regions. These regions are areas with very limitedinformation for the matching process which are low texture, and depthdiscontinuity regions. In this study, each algorithm uses different matchingcost computation (MCC) techniques, but for cost aggregation (CA), disparityoptimization (DO) and disparity refinement (DR), the technique remains thesame. The MCC areabsolute difference(AD), the combination ofabsolutedifference and gradient matching(AD+GM) andcensus transform(CT).Then, for CA, DO and DR, they areminimum spanning tree(MST),winnertake all(WTA) andbilateral filter(BF), respectively. The results are presentedand discussed in this article. Hence, thru this study the robust method can beestimated at the MCC stage.
Exploring the potential of skeleton and machine learning in classroom cheating detection
Authors: Tran Nha , Nguyen Minh , Le Tri , Nguyen Tuong , Nguyen Tinh , Nguyen Tuan
Published: November 2023

In recent years, there have been certain drawbacks in the behavior of students in school cultural activities, especially the frequent occurrence of cheating in exams. Although many manual cheating detection methods have been applied, cheating behaviors have become increasingly sophisticated and difficult to detect. This makes manual cheating detection methods unable to completely prevent cheating in exams. Therefore, applying advanced technologies to automatically detect cheating cases becomes necessary to help supervisors better control the exam process. In this study, we propose a model architecture to monitor students’ cheating activities during exams. Firstly, we apply YOLO - Pose to detect skeleton keypoints, which are then passed through machine learning models such as support vector machine (SVM), decision tree (DT) classifier, random forest (RF), extreme gradient bo osting (XGBoost), and propose the Ac Long short - term memory (LSTM) to detect cheating behavior. The experimental results show the feasibility of the model on various metrics. The model is tested on a dataset of cheating behaviors in the classroom, which is designed to simulate paper - based exams. Moreover, the results showed that the proposed method can detect cheating behavior in a short amount of time and can be deployed for real - world applications.
Yoga pose annotation and classification by using time-distributed convolutional neural network
Authors: S. Dhanyal Somashekhar , S. Nandya Suvarna
Published: November 2023

In India, people have been practicing yoga for thousands of years to improve their health and well-being on all levels. As the pace of technological development increases, this presents a great opening for computational probing across all areas of social domains. Nevertheless, it remains difficult to integrate artificial intelligence (AI) and machine learning (ML) methods to an interdisciplinary field like yoga. The proposed study aims to develop a yoga pose annotation and classification for yogasana recognition in real time. The study considers TensorFlow for better implementation of data automation, performance monitoring. TensorFlow yields better numerical computation and hat helps ML and efficiently develops the neural network. The proposed composed of time-distributed convolutional neural network (CNN) through the Softmax function. Also, a poseNet algorithm is considered to estimate the user’s real-time yoga pose. The use of a database i.e., poseTrack in the proposed method offers annotation to the evaluation of yoga pose and tracking of it. The performance analysis of the proposed yoga pose annotation and classification model suggests that it offers higher accuracy than traditional, support vector machines (SVM) and K-nearest neighbor (KNN).
Enhancing lung cancer disease diagnosis by employing ensemble deep learning approaches
Authors: Nath Das Manmath , Panda Niranjan , Rautray Rasmita
Published: November 2023

Cancer is a disease that results from the unnatural proliferation of aberrant cells that infest the body’s healthy cells and spread throughout the body. Lung cancer is characterized by an imbalance in the cells of the affected organs, namely the lungs. The prediction of lung cancer at an early stage is very important, particularly in countries that are densely populated and have lower incomes. Clinically conventional approaches, such as blood tests and other types of treatments, are used by specialists. The age of artificial intelligence (AI) has begun, and today, it is feasible to construct a computer-aided diagnostic mechanism with the assistance of machine learning and deep learning algorithms. In this particular piece of research, one deep learning algorithm, an artificial neural network (ANN), has been investigated to determine whether or not lung cancer could be detected at an earlier stage. In addition to conventional ANN, ensemble ANN with weighted averaging and soft and hard voting ensemble techniques are also considered. In order to achieve this effectiveness, the state-of-the-art parameters for the proposed method using ANN are assessed and evaluated using the lung cancer dataset. The empirical analysis shows that hard voting-enabled ANN shows the highest accuracy at 97.47%.
Multiple object tracking using space-time adaptive correlation tracking
Authors: Sriram Kusuma , Purushotham Kiran
Published: November 2023

In application of tracking and detecting the suspicious activities, multiple object tracking (MOT) has been given fine attention due to its application as it provides the parallel task of identification and tracking of human. MOT ensures the identification and trajectory for each object frame as they interact, despite the changes in its appearance, occlusion and various other tasks involved. Recent adoption of deep learning has given a new perspective but still achieving high metrics remains a major issue to overcome such issues, this research work presents the integrated architecture of deep convolutional covariance networks (DCCNs) and space-time adaptive correlation tracking (STACT) algorithm with similarity map function (SMF). Moreover, in proposed work, DCCNs is utilized for feature extractions through each frame capturing the distinctive information, STACT is tracking approaches that utilizes the SMF for locating and tracking objects. SMFs are updated for any changes in human appearances and motion, also it deals with occlusion. Here the proposed model is evaluated on MOT17 and MOT20 dataset. Performance analysis is carried out through comparing the existing model and Integrated-DCCN achieves higher metrics.
Modelling and design of grid voltage oriented vector control scheme for DC railway recuperating system
Authors: Ling Toh Chuen , Wei Tan Chee
Published: November 2023

The braking energy harvested by a railway vehicle can be restored to the utility grid with a power recuperating system. A grid connected voltage source inverter (VSI) is commonly used as a grid-feeding converter in the recuperating system. This paper proposes to integrate grid voltage oriented vector control (GVOVC) and third harmonic voltage injection pulse width modulation (THVI-PWM) technique for the VSI to ensure grid voltage and frequency synchronization. A simulation study is carried out to evaluate the feasibility of the proposed control and modulation schemes using MATLAB/Simulink. The results show that the proposed controller may reach steady-state operating mode within 7 ms by producing good quality AC voltages and currents waveforms. With the independent control of voltage quantities in dq reference frame, the regulation of active and reactive power could be realized.
New species of Sycorax (Diptera: Psychodidae) from the Brazilian Amazon
Authors: Cordeiro Danilo Pacheco , Bravo Freddy , Ramires Adriane Costa
Published: November 2023

Moth flies of the subfamily Sycoracinae have been associated with anurans. Females of some species have been found feeding on the blood of these vertebrates. Here we describe a new species of the genus Sycorax Curtis from a preserved site of Amazon Forest in the city of Manaus, Amazonas, Brazil, with one male specimen collected in the dorsum of the frog Anomaloglossus stepheni (Martins).
Novelties and nomenclatural notes in Pabstiella (Orchidaceae) from the Brazilian Atlantic Rainforest of Bahia and Espírito Santo
Authors: GUTIÉRREZ MORALES NICOLÁS , TOSCANO DE BRITO A.L.V. , DE CAMARGO SMIDT ERIC
Published: November 2023

Three new species of Pabstiella from Espírito Santo and Bahia in Brazil are described and illustrated, with digital plates, comparative figures, and annotations on their ecology provided. The species are compared with similar taxa, and their phylogenetic placement is hypothesized based on their morphology. In addition, five species are proposed as synonyms, P. teschiana and P. henrique-aragonii as synonyms of P. crenata, P. wanderbildtiana as synonym of P. aurantiaca, P. osculator as synonym of P. rhombilabia and P. menegattii as synonym of P. decurva. A respective taxonomic discussion is provided for each case, and a lectotype is selected for P. aurantiaca.
A new Leccinum species from the Altai Mountains
Authors: VLASENKO VYACHESLAV A.
Published: November 2023

A new Leccinum species has been described based on morphological and molecular data. Its characteristic features are medium-sized basidiomata, pores cream to cinnamon-brown, and a dark cream pileus with a light marble pattern. It grows under Salix bebbiana and occurs in southeast Altay Mts. We present detailed descriptions with color photos of fresh fruiting bodies, SEM photos of spores, molecular phylogeny, and an analysis of the characteristic nucleotide sequences compared to the related species.
Grias portillae (Lecythidaceae): A new tree species from northwestern Ecuador
Authors: CORNEJO XAVIER
Published: November 2023

Grias portillae, a new tree species of Lecythidaceae from the evergreen lower montane Andean slopes at environs of Lita, in northwestern Ecuador, is here described and illustrated. It is characterized by the leaf blades with short-caudate apex, flowers with dark-purple petals, androecium creamish-white, fused in a developed staminal tube, stamens 18–21, arranged in one level on top of rim, and anthers with expanded, cucullate connectives with lateral flaps that encloses most of the thecae. Grias portillae is assessed provisionally as Endangered, and an updated key to all species of this genus is provided. The presence of colleters on the margins of the leaves is reported here for the first time as a new generic character in Grias.
Anthropogenic Influence on 2022 Extreme January–February Precipitation in Southern China
Authors: Hu Yamin , Dong Buwen , Xie Jiehong , Tan Haobo , Zhou Baiquan , Lin Shuheng , He Jian , Zhao Liang
Published: November 2023

The precipitation in January–February 2022 in southern China was the second-largest amount since 1961. Anthropogenic influence reduced the likelihood of extreme events like 2022 by about 50% (55%) in HadGEM3 (CMIP6).
Balanced Convective Circulations in a Stratified Atmosphere. Part I: A Framework for Assessing Radiation, the Coriolis Force, and Drag
Authors: Marsico David H. , Biello Joseph A. , Igel Matthew R.
Published: November 2023

The so-called traditional approximation, wherein the component of the Coriolis force proportional to the cosine of latitude is ignored, is frequently made in order to simplify the equations of atmospheric circulation. For velocity fields whose vertical component is comparable to their horizontal component (such as convective circulations), and in the tropics where the sine of latitude vanishes, the traditional approximation is not justified. We introduce a framework for studying the effect of diabatic heating on circulations in the presence of both traditional and nontraditional terms in the Coriolis force. The framework is intended to describe steady convective circulations on an f plane in the presence of radiation and momentum damping. We derive a single elliptic equation for the horizontal velocity potential, which is a generalization of the weak temperature gradient (WTG) approximation. The elliptic operator depends on latitude, radiative damping, and momentum damping coefficients. We show how all other dynamical fields can be diagnosed from this velocity potential; the horizontal velocity induced by the Coriolis force has a particularly simple expression in terms of the velocity potential. Limiting examples occur at the equator, where only the nontraditional terms are present, at the poles, where only the traditional terms appear, and in the absence of radiative damping where the WTG approximation is recovered. We discuss how the framework will be used to construct dynamical, nonlinear convective models, in order to diagnose their consequent upscale momentum and temperature fluxes.
Situating Dashed Prospects of Independence into the Xenophobic Narrative in South Africa
Authors: Yingi Edwin , Ncube Tomy , Benyera Everisto
Published: November 2023

Xenophobia in South Africa is often depicted as anti-immigrant sentiments and stereotypes that emanate from social, political, and economic misconceptions. This paper argues that though the causes of xenophobia are many and complex, they stem from the dashed hopes of independence and the legacy of apartheid. This narrative has over the years been overshadowed by the view that xenophobic attacks in South Africa are a product of hate and anti-migration. We argue that the failure of successive governments of the ANC to correct the wrongs of the apartheid past and make the economy inclusive has stoked the tensions between citizens and foreign nationals. To underscore this point, this paper undertakes a discussion on the pertinent implications of the political trajectory of xenophobia in South Africa and makes some recommendations on what can be done to reduce incidences of xenophobic attacks in the future.
Revisiting the Structural (In)Variances of Homicide: Examining the Differential Effects of Context Across Homicide Types
Authors: Fridel Emma E.
Published: November 2023

Objectives

Extend foundational work on the structural covariates of homicide (concentrated disadvantage in particular) by examining the differential effects of context across distinct types of incidents.

Methods

Using data on 31,513 incidents nested within 4,598 places from the National Violent Death Reporting System (NVDRS) from 2003 to 2018, multilevel latent class analysis (MLCA) classified homicides into types. Two-level negative binomial regression models subsequently examined the place-level correlates of homicide counts disaggregated by type.

Results

Four empirically distinct types of incidents were identified, including felony, argument, intimate partner violence, and child abuse homicides. While concentrated disadvantage has a positive relationship with all four types, its effect is significantly stronger for felony and argument homicides relative to incidents involving intimate partner violence and child abuse.

Conclusions

The results indicate that context exhibits differential effects across homicide types, in turn suggesting that their underlying social processes and mechanisms are distinct.
Bernard Dionysius Geoghegan, Code: From Information Theory to French Theory
Authors: Pedwell Carolyn
Published: November 2023

Assembling a distinctive genealogy of cybernetic thought situated in relation to Progressive Era technocracy, industrial capitalism, (de)colonial relations, and eugenic machinery, Code uncovers the vital interdependence of informatics, the humanities, and the human sciences in the 20th century. Rather than figuring cybernetics as emerging from Second World War military technologies and post-war digital computing, Code argues that liberal technocrats’ inter-war visions of social welfare delivered via ‘neutral’ communication techniques shaped the informatic interventions of both the Second World War and the Cold War. Tracing how an organizing concept of code linked the work of diverse structurally-minded thinkers, such as Norbert Wiener, Warren Weaver, Margaret Mead, Gregory Bateson, Claude Lévi-Strauss, Roman Jakobson, Jacques Lacan, Roland Barthes, and Luce Irigaray, Bernard Dionysius Geoghegan reconstructs the cybernetic apparatus that spawned new fields, including structural anthropology, family therapy, and literary semiology – and grapples with the unfolding implications of such socio-technical dynamics for 21st-century critical theory, digital media, and data analytics.
COVID-19 in pediatric palliative care patients: Multicenter, retrospective cohort study
Authors: Korzeniewska-Eksterowicz Aleksandra , Brzezinska Olga , Dryja Urszula , Matczak Dominka , Sopilnyak Andriy , Szuszkiewicz Eugenia , Przysło Łukasz , Szmyd Krzystof , Jabłońska Katarzyna , Krych Piotr , Wojtków-Zielińska Agnieszka , Wąsińska Edyta , Niedźwiecki Maciej
Published: November 2023

Background:

Studies have shown the risk factors for COVID-19 severity in children, including comorbidities, but information on the infection course in children with life-limiting conditions is sparse.

Aim:

To describe the effect of COVID-19 on pediatric patients receiving palliative care due to life-limiting conditions.

Design:

We conducted retrospective cohort study. The WHO Clinical Progression Scale was used to measure COVID-19 severity.

Setting/participants:

Seven of the 24 invited pediatric palliative care centers participated in this study. We analyzed the medical records of children under palliative care with confirmed COVID-19 (January 2020–April 2022)

Results:

Records of 60 patients with COVID-19 aged 0.24 to 21.6 years (mean (SD); 9.8 (6.6)) were collected. The largest group of patients with COVID-19 was children with congenital malformations and chromosomal abnormalities (42%); the most common manifestation was fever (85%). Bacterial coinfection was confirmed in 17 (28%) children. Fifteen (25%) children required hospitalization, including four admitted to the Intensive Care Unit. Mild COVID-19 was identified in 44 (73%) children, moderate in 11 (18%), severe in 3 (5%), and death in 2 (3%). Six of the 20 eligible children were vaccinated against SARS-CoV-2, followed by 16 mothers and fathers.

Conclusion:

In the study population initial presentation of COVID-19 was predominantly a mild; however, the small sample size precluded definitive conclusions. For children under palliative care, we should identify if they have an advance care plan for COVID-19, such as desires for intensive care support. Further studies are needed to define the short and long-term effects of COVID-19 in children with life-limiting conditions.
Trust and distrust in science: Embedding the interplay among scientists, mass media and public in Italy during the SARS-Cov-2 outbreak
Authors: Gobo Giampietro , Campo Enrico , Serafini Luca
Published: November 2023

COVID-19 pandemic has once again raised the long-standing problem of trust in science and scientists. However, many approaches tend, on one hand, to analyze science as if it were an entirely autonomous entity – and thus to attribute the causes of the decline in trust to factors external to it; on the other hand, these approaches address the question of trust in a dichotomous manner, in terms of presence or absence of it. Rather than assuming a causal and linear direction that proceeds from one domain (‘the outside’ of science) to the other (science), we will draw on those perspectives that investigate the ways in which science interacts with other subsystems. This article aims to propose a more nuanced approach that can contribute to overcoming binary categorizations such as the one that distinguishes between processes internal to the scientific community and factors external to it; such categorizations are somehow implicit in the widespread use of concepts like ‘infodemic’, ‘disinformation’ or ‘pseudoscience’. To this end, two research directions were followed: first, two conflicts between experts that animated the public debate in Italy during the Sars-Cov-2 outbreak and forced scientists to interact following different social subsystems logics were analyzed. Second, in order to go beyond a binary view of trust and to further reveal attitudes toward science and scientists, we conducted a pilot study on a sample of online readers of two Italian newspapers. Overall, a more nuanced view of the issue of trust toward scientists emerges, which is expressed in five different attitudes toward them, and which takes into consideration both the way in which scientists communicate and the philosophy of science they implicitly express in media interactions.
Social Activity Restriction and Psychological Health Among Caregivers of Older Adults With and Without Dementia
Authors: Irani Elliane , Wang Fei , Meyer Kylie , Moore Scott Emory , Ding Kedong
Published: November 2023

Objectives

We examined associations between social activity restriction and psychological distress and well-being for caregivers of older adults with and without dementia, and if the identified associations are different for the two groups.

Methods

Using data from the 2017 National Study of Caregiving, we identified caregivers of older adults with ( N = 541) and without ( N = 1701) dementia. Linear regression models were estimated, adjusting for caregivers’ age, gender, race, education, relationship to care recipient, and self-rated health.

Results

Restriction in visiting friends and family and attending religious services were associated with higher distress in dementia caregivers. Restriction in visiting friends and family was associated with higher distress and lower well-being in non-dementia caregivers. Any activity restriction had stronger association with distress for caregivers of older adults with versus without dementia.

Discussion

Findings highlight the need for tailored interventions based on caregivers’ perceptions of meaningful social activities and dementia-friendly communities to promote social participation.
Prioritizing exceptional social needs. Experimental evidence on the role of discrimination and client deservingness in public employees’ and citizens’ discretionary behavior
Authors: Dietrich Brian , Jankowski Michael , Schnapp Kai-Uwe , Tepe Markus
Published: November 2023

This study examines how public employees and citizens exercise administrative discretion in a dilemma. To identify and compare the moral reasoning underlying discretionary choices, we conducted a conjoint experiment among public employees, future civil servants, and lay citizens in Germany. In the conjoint, respondents were forced to prioritize between two equally eligible welfare claimants. Claimants’ profiles vary concerning attributes reflecting earned-deservingness (e.g., non-self-inflicted welfare dependency), need-deservingness (e.g., dependent children), and attributes that can be used for unlawful discrimination (e.g., nationality). While some signs of discrimination exist, need-deservingness is the most important factor shaping respondents’ prioritization choices. More importantly, we find no substantial differences in prioritization choices among public employees and citizens, indicating congruence in moral reasoning. From these findings, we conclude that efforts to reflect on national prejudices in the education of civil servants should be intensified, and a renewed emphasis on administrative ethics is required to equip public employees with the ability to make impartial yet balanced judgments in administrative dilemmas.
Enhancing journal bearing performance through surface texturing: A comprehensive review of latest developments and future prospects
Authors: Kumar Manish , Pandey K N
Published: November 2023

Incorporating surface textures on the contact points substantially improve bearing performances, which is evident from burgeoning interest in this field. This study thoroughly reviews existing literature on the topic from its inception to date. We have carried out an assiduous examination of various surface microcavities to assess how well they perform in terms of load-bearing capacity, friction coefficient, and friction force. The study briefly dwells upon numerical modeling techniques and their advantages and limitations. Further, this study develops a quantitative understanding of the impact of four textures including Pocket, Line, Cross, and Dot-like texture on the bearing parameters such as coefficient of friction, film thickness, and convergence ratio at the inlet and exit. The study elucidates how various surface textured designs would affect the way a hydrodynamic journal bearing functions . The present study also examines the texture roughness pattern transverse and longitudinal sinusoidal, full, and half-wave and its influence on the hydrodynamic journal bearing performance. The study gets concluded with the finding that in the case of pocket texture, the coefficient of friction is reduced by up to 20%. Transverse and longitudinal positive full wave texture pattern increase load-bearing capacity by up to 34% and reduces friction coefficient by up to 18%.