bluuebunny/crossref_metadata_2025 huggingface dataset:
SIRT7 expression predicts poor prognosis in upper tract urothelial carcinoma undergoing postoperative platinum-based adjuvant chemotherapy
Authors: Cao Yudong , Ma Jinchao , Wang Shuo , Yang Xiao , Long Mengping , Ji Yongpeng , Yu Ziyi , You Ruijian , Lin Chen , Yang Yong , Du Peng
Published: February 2025

Introduction
To evaluates the expression of SIRT7 in UTUC as well as the predictive value for prognosis in patients undergoing radical nephroureterectomy followed platinum-based adjuvant chemotherapy.
Methods
Pathological samples of 146 UTUC with clinical stage T2 and above undergoing radical nephrectomy (RNU) were collected. All patients received adjuvant cisplatin-based chemotherapy and 40 UTUC patients received second-line immunotherapy after disease progression. The relationship between the expression level of SIRT7 by immunohistochemistry (IHC) and clinicopathological characteristics, disease-free survival (DFS), overall survival (OS) and overall survival after progression (POS) was analyzed.
Results
Over a mean follow‑up 47 months, 61 (41.8%) patients experienced recurrence and 42 (28.8%) patients died due to UTUC. The results revealed that 70.2% of UTUC tissue samples exhibited high expression levels of SIRT7. High expression of SIRT7 is associated with lymph node metastasis(P＜0.001), lymphovascular invasion (P=0.001) and histological differentiation (P =0.025). In addition, UTUC patients with elevated SIRT7 expression experienced significantly shorter DFS （hazard ratio[HR] 3.760, 95% CI 1.884-7.504, P＜0.001 and OS (HR 2.706, 95% CI 1.235-5.929, P=0.013). Multivariate analyses demonstrated that SIRT7 served as a significant predictor for DFS (HR 2.337, 95% CI 1.117-4.890, P = 0.024) in UTUC patients. Furthermore, we found SIRT7 high expression is associated with prolonged POS in patients progressed after adjuvant cisplatin-based chemotherapy and received second-line immunotherapy.
Conclusion
SIRT7 is an independent prognostic marker of poor DFS in locally advanced UTUC patients after RNU. Moreover, these data suggest that SIRT7 could potentially serve as a target for assessing the efficacy of chemotherapy and immunotherapy in UTUC.
Electromagnetic Iontophoresis: A Novel Nonsurgical Method for the Treatment of Dense Vitreous and Retinal Hemorrhages
Authors: Arslan Umut , Arslan Deniz , Özmert Emin
Published: February 2025

Introduction: Vitreous, retinal and suprochoroidal hemorrhages might develop secondary to trauma, retinal tear or detachment, neovascularization due to ischemic retina. If the clearance of retinal and vitreous hemorrhages can be accelerated, more effective treatments can be planned for the underlying pathology.
Case Presentations: We present 6 different cases with dense vitreous, preretinal, and subretinal hemorrhages due to Valsalva retinopathy, polypoid choroidal vasculopathy (PCV), diabetic retinopathy (DR), neovascular age-related macular degeneration (nAMD), retinitis pigmentosa with vasculitis, and myopic choroidal neovascularization. To accelerate the clearance of these dense intraocular hemorrhages, a novel nonsurgical method of electromagnetic iontophoresis (MagnoVisionTM) was used together with some appropriate medications in an outpatient setting without any complications or side effects. In all cases, liquefaction of the intraocular hemorrhage began by 5 days and mostly resolved by 10 days. This nonsurgical rapid clearance allowed us to diagnose and evaluate the underlying retinal and choroidal pathologies earlier and to treat them appropriately as early as possible.
Conclusion: Combined use of electromagnetic iontophoresis, subtenon platelet rich plasma (PRP) and bevacizumab injection, and oral bromelain can be considered as an effective and safe new treatment method for vitreous and retinal hemorrhages without any need for surgical intervention.
Unveiling the Link: Obesity, Diet, Hypothalamic Inflammation and Central Precocious Puberty - Recent Insights and Implications
Authors: Stathori Galateia , Tzounakou Anastasia-Maria , Vlahos Nikolaos F. , Charmandari Evangelia , Valsamakis Georgios
Published: February 2025

Background: Childhood obesity is on the rise globally, raising concerns among the medical community. The phenomenon is closely linked to high-fat diets. Concurrently, the prevalence of Central Precocious Puberty (CPP) is increasing. Recent evidence demonstrates that obesity and high-fat diets induce inflammation in the mediobasal hypothalamus in humans, a region housing both the primary appetite-regulating centers and the GnRH neurons. Early activation of GnRH neurons is implicated in CPP. The proximity of these hypothalamic sites, exposed to obesity/diet-induced neuroinflammation, coupled with the positive association between CPP, obesity, and high-fat diets, prompts exploration into the potential involvement of hypothalamic inflammation (HI) in CPP occurrence. Summary: This article delves into the molecular mechanisms through which HI may contribute to CPP in obese and lean girls, based on existing literature. We present evidence suggesting that HI could activate the gonadotropic axis by influencing cytokines and prostaglandins production, BDNF, and potentially phoenixin. Key Messages: HI emerges as a potential pathophysiological mechanism linking obesity, high-fat diets, and CPP. Further research is imperative to elucidate the relationship between HI and CPP, providing insights into the origins of CPP, often termed as idiopathic
Eye Movement Desensitisation and Reprocessing with and without Dialectical Behaviour Therapy for Posttraumatic Stress Disorder and Comorbid Borderline Personality Disorder Symptoms: A Randomised Controlled Trial
Authors: Snoek Aishah Cecile , van den End Arne , Beekman Aartjan T. F. , Dekker Jack , Aarts Inga , Blankers Matthijs , Vriend Chris , van den Heuvel Odile A. , Lommerse Nick , Thomaes Kathleen
Published: February 2025

Introduction: Comorbidity between posttraumatic stress disorder (PTSD) and borderline personality disorder (BPD) is prevalent. Despite evidence-based therapies, high rates of non-response and dropout persist. This study therefore aimed to examine whether the concurrent application of eye movement desensitization and reprocessing (EMDR) for PTSD and dialectical behavior therapy (DBT) for BPD yields better results than EMDR alone.
Methods: Patients with a PTSD diagnosis and at least four BPD symptoms were randomly assigned to EMDR (n = 63) or concurrent EMDR-DBT (n = 61). Over one year, changes in PTSD symptoms were measured using the Clinician-Administered PTSD Scale for DSM-5. Secondary outcomes included BPD symptoms, global functioning and quality of life.
Results: Both treatments led to large reductions in PTSD symptoms, without significant differences after one year (p = .312, d = -0.23, 95% CI = -0.6, 0.1). Both treatments also yielded large and comparable reductions in BPD symptoms and improved quality of life. Global functioning improved only in the EMDR condition according to one measure (WHODAS 2.0), while the other measure (OQ-45) showed improvements in both groups. Additionally, patients in the EMDR-DBT condition were twice as likely to drop out from EMDR treatment compared to those in the EMDR-only condition.
Conclusion: Stand-alone EMDR demonstrated safety and efficacy in alleviating PTSD and BPD symptoms, as well as enhancing quality of life. These findings support the use of EMDR as a strong therapeutic option for patients with PTSD and comorbid BPD symptoms. Further research is needed to assess longer-term outcomes beyond one year.
Empowering Malaysian micro agri-entrepreneurs: the role of key success factors in e-agribusiness adoption
Authors: Tariq Sehrish , Vaiappuri Selvakkumar K N , Mahmood Haider , Houaneb Amira
Published: February 2025

Progress in the agricultural sector is one of the most imperative tools to enhance the productivity of agribusiness. This study identified the key success factors required for the adoption of e-agribusiness platforms in the Malaysian agriculture sector. The study analyzed potential key factors from the prior studies and contextually adjusted using a pilot study. These factors are categorized in various categories such as financial imperative, technological imperative, knowledge imperative, risk and trust factors, governance and public policy, and challenging business environment. The study has collected data from 302 micro agri-entrepreneurs within Malaysia through a questionnaire for quantitative analysis. The exploratory factor analysis (EFA) is used to see the impact of critical success factors (CSFs) that help to increase technological adoption thereby enhancing communication, advertisement, and overall sales of agri-products on the e-business platform. The study has a significant impact on key success factors (financial imperative, technological imperative, knowledge imperative, risk and trust factors, governance and public policy, and challenging business environment) on the adoption of e-agribusiness platforms. The findings provide guidelines to micro agri-entrepreneurs and policymakers that how to use key success factors to improve business performance by utilizing e-agribusiness platforms.
A GRU-based approach for botnet detection using deep learning technique
Authors: G. Suchetha , K. Pushpalatha
Published: February 2025

The increasing volume of network traffic data exchanged among interconnected devices on the internet of things (IoT) poses a significant challenge for conventional intrusion detection systems (IDS), especially in the face of evolving and unpredictable security threats. It is crucial to develop adaptive and effective IDS for IoT to mitigate false alarms and ensure high detection accuracy, particularly with the surge in botnet attacks. These attacks have the potential to turn seemingly harmless devices into zombies, generating malicious traffic that disrupts network operations. This paper introduces a novel approach to IoT intrusion detection, leveraging machine learning techniques and the extensive UNSW-NB15 dataset. Our primary focus lies in designing, implementing, and evaluating machine learning (ML) models, including K-nearest neighbors (KNN), random forest (RF), long short-term memory (LSTM), and gated recurrent unit (GRU), against prevalent botnet attacks. The successful testing against prominent Bot- net attacks using a dedicated dataset further validates its potential for enhancing intrusion detection accuracy in dynamic and evolving IoT landscapes.
Word embedding for contextual similarity using cosine similarity
Authors: Asri Yessy , Kuswardani Dwina , Sari Amanda Atika , Ansyari Atikah Rifdah
Published: February 2025

Perspectives on technology often have similarities in certain contexts, such as information systems and informatics engineering. The source of opinion data comes from the Quora application, with a retrieval limit of the last 5 years. This research aims to implement Indo-bidirectional encoder representations from transformers (BERT), a variant of the BERT model optimized for Indonesian language, in the context of information system (IS) and information technology (IT) topic classification with 414 original data, which, after being augmented using the synonym replacement method, The generated data becomes 828. Data augmentation aims to evaluate the performance of models by using synonyms and rearranging text while maintaining meaning and structure. The approach used is to label the opinion text based on the cosine similarity calculation of the embedding token from the IndoBERT model. Then, the IndoBERT model is applied to classify the reviews. The experimental results show that the approach of using IndoBERT to classify SI and IT topics based on contextual similarity achieves 90% accuracy based on the confusion matrix. These positive results show the great potential of using transformer-based language models, such as IndoBERT, to support the analysis of comments and related topics in Indonesian.
Enhance big data security based on HDFS using the hybrid approach
Authors: Zine-Dine Fayçal , Alcabnani Sara , Azouaoui Ahmed , El Kafi Jamal
Published: February 2025

Hadoop has emerged as a prominent open-source framework for the storage, management, and processing of extensive big data through its distributed file system, known as Hadoop distributed file system (HDFS). This widespread adoption can be attributed to its capacity to provide reliable, scalable, and cost-effective solutions for managing large datasets across diverse sectors, including finance, healthcare, and social media. Nevertheless, as the significance and scale of big data applications continue to expand, the challenge of ensuring the security and safeguarding of sensitive data within Hadoop has become increasingly critical. In this study, the authors introduce a novel strategy aimed at bolstering data security within the Hadoop storage framework. This approach specifically employs a hybrid encryption technique that leverages the advantages of both advanced encryption standard (AES) and data encryption standard (DES) algorithms, whereby files are encrypted in HDFS and subsequently decrypted during the map task. To assess the efficacy of this method, the authors performed experiments with various file sizes, benchmarking the outcomes against other established security measures.
Trends in machine learning for predicting personality disorder: a bibliometric analysis
Authors: Sulistiani Heni , Syarif Admi , Warsito Warsito , Berawi Khairun Nisa
Published: February 2025

Over the last decade, research on artificial intelligence (AI) in the medical field has increased. However, unlike other disciplines, AI in personality disorders is still in the minority. For this reason, we conduct a map research using bibliometric and build a visualization map using VOSviewer in AI to predict personality disorders. We conducted a literature review using the systematic literature review (SLR) method, consisting of three stages: planning, implementation, and reporting. The evaluation involved 22 scientific articles on AI in predicting personality disorders indexed by Scopus Quartile Q1–Q4 from the Google Scholar database during the last five years, from 2018–2023. In the meantime, the results of bibliometric analysis have led to the discovery of information about the most productive publishers, the evolution of scientific articles, and the quantity of citations. In addition, VOSviewer’s visualization of the most frequently occurring terms in abstracts and titles has made it easier for researchers to find novel and infrequently studied subjects in AI on personality disorders.
Spatial-temporal data imputation for predictive modeling in intelligent transportation systems
Authors: Widi Prasetyo Yohanes Pracoyo , Linawati Linawati , Wiharta Dewa Made , Sastra Nyoman Putra
Published: February 2025

Data imputation is necessary to overcome data loss in intelligent transportation systems (ITS) due to the many sensors used to monitor traffic conditions. Sensor malfunction, hardware limitations, and technical glitches can lead to incomplete data, potentially leading to errors in traffic data analysis. This analysis investigated spatial-temporal data imputation approaches applied for predictive modeling in ITS. Each approach's strengths, weaknesses, and applicability in the context of ITS are evaluated. We analyzed various imputation approaches involving statistical, machine learning, and combined methods. Statistical methods are more straightforward but could effectively handle modern traffic's complexity. On the other hand, machine learning and combined approaches, such as hybrid convolutional neural network (CNN)- long short-term memory (LSTM), offer more robust capabilities in capturing non-linear patterns present in spatio-temporal data. This research aims to investigate the effectiveness of each approach in overcoming data incompleteness and the accuracy of predicting future traffic conditions with the widespread adoption of IoT, electric vehicles, and autonomous vehicles. The results of this investigation provide an understanding of the most suitable approaches to address the challenges of spatio-temporal data imputation and provide practical guidance for predictive modeling in ITS.
A novel mobile application for personality assessment based on the five-factor model and graphology
Authors: Remaida Ahmed , Sabri Zineb , Abdellaoui Benyoussef , Fri Chakir , Lakhchaf Yassine , El Idrissi Younès El Bouzekri , Lafraxo Mohammed Amine , Moumen Aniss
Published: February 2025

With the rising interest over the last decade, automated graphology has emerged as a promising filed of research, providing new insights on personality traits prediction on the basis of handwriting analysis. Although, few practical solutions to automate the extraction of handwriting features and personality prediction exist in the literature. This work aims to contribute to closing the gap in automated handwriting personality prediction by proposing a novel mobile application that uses robust feature extraction and machine learning models to predict big five personality traits. Our findings, based on high correlations between handwriting characteristics and personality traits, revealed convincing links. Notably, extraversion and extraversion have strong correlations with top margin feature, whereas agreeableness is expressed through line spacing. These findings emphasize the ability of automated graphology to properly interpret individual personalities. The proposed system achieved exceptional accuracy by using well known machine learning classifiers. The testing accuracy exceeded 92% in binary classification and 87% in multi-class case scenario, proving the adaptability and dependability of the system’s architecture. Our Android app promises to provide users with unprecedented insights into their personalities, establishing a robust tool for psychological assessment and self-discovery.
Acute lymphoblastic leukemia diagnosis and aubtype segmentation in blood smears using CNN and U-Net
Authors: Reza Hamim , Tareq Nazrul Islam , Rabbi M M Fazle , Tanim Sharia Arfin , Rudro Rifat Al Mamun , Nur Kamruddin
Published: February 2025

Acute lymphoblastic leukaemia (ALL) is a severe disease requiring invasive, expensive, and time-consuming diagnostic tests for definitive diagnosis. Initial diagnosis using blood smear pictures (BSP) is crucial but challenging due to the similar indications and symptoms of ALL, often leading to misdiagnoses. This study presents a custom approach using Convolutional Neural Networks (CNNs) to detect all cases and categorize subtypes. Utilizing publicly available databases, the study includes 3562 blood smear images from 89 patients. The innovative combination of U-Net for segmentation and various CNN architectures (U-Net, MobileNetV2, InceptionV3, ResNet50, NASNet) for feature extraction, with DenseNet201 being the most effective, forms the core of this method. The U-Net model achieved a segmentation accuracy of 98% by recognizing patterns within blood smear images. Following segmentation, CNN architectures extracted high-level features, with DenseNet201 proving the most effective in diagnostic and classification tasks. Our proposed custom CNN model achieved a test accuracy of 98%, with a training accuracy of 99.31% and validation accuracy of 97.09%. This approach enables an accurate distinction between ALL and non-pathologic cases.
The integration of metaverse technology in healthcare: a comprehensive review and future research directions
Authors: Roy Rita , Das Tarinmoy , Karras Dimitrios Alexios
Published: February 2025

The impact of using the metaverse in healthcare is investigated in this research work. Emerging technologies are essential to enhancing medical consultants’ care, especially in developing countries like India. The study filters and reviews the pertinent literature using the scientific procedures and rationales for systematic literature reviews (SPAR-4-SLR) methodology. The initial search yielded 180 articles. Forty-four articles were considered for the study after screening the papers in light of the research questions and relevant literature. The theory-context-characteristics-methodology (TCCM) framework is used in this study to assess future metaverse research trends. This study also used the context, intervention, mechanism, and outcome (CIMO) logic for planning and decision-making. This study examines the development of metaverse research over the past ten years and supports research findings published in peer-reviewed journals. Based on the TCCM framework, recommendations have been made for additional research.
Clinical Severity and Outcomes in Large Infarcts With Endovascular Therapy: A Post Hoc Analysis of the ANGEL-ASPECT Trial
Authors: Lu Qixuan , Zheng Lina , Nie Ximing , Wang Mengxing , Duan Wanying , Liu Xin , Zhang Zhe , Wen Miao , Yang Zhonghua , Leng Xinyi , Pan Yuesong , Nguyen Thanh N. , Liu Liping
Published: February 2025

BACKGROUND:

Endovascular therapy (EVT) has been proven effective for patients with acute ischemic stroke with large infarcts. This study aimed to explore the impact of clinical severity on the efficacy of EVT in such patients.

METHODS:

This was a post hoc analysis of the ANGEL-ASPECT trial (Endovascular Therapy in Acute Anterior Circulation Large Vessel Occlusive Patients With a Large Infarct Core), a randomized controlled trial that enrolled patients from 46 centers across China between October 2, 2020, and May 18, 2022. These patients had large infarcts (defined as Alberta Stroke Program Early CT Score of 3–5 or infarct-core volume 70–100 mL) due to anterior-circulation large vessel occlusion within 24 hours after stroke onset with a National Institutes of Health Stroke Scale score of 6 to 30. Patients were randomized into either the EVT group or the medical management alone (MM) group. For this analysis, we categorized the patients into 2 subgroups: moderate stroke and severe stroke, based on a baseline National Institutes of Health Stroke Scale score of either <20 or ≥20. The primary outcome was the ordinal 90-day modified Rankin Scale score (0, no symptoms, to 6, death).

RESULTS:

Among 455 eligible patients, 347 (76.3%) presented with moderate stroke (170 received EVT, 177 underwent MM), and 108 (23.7%) had severe stroke (60 received EVT, 48 underwent MM). A significant shift toward better outcomes in the 90-day modified Rankin Scale distribution was observed in the EVT group compared with the MM group (generalized odds ratio, 1.66 [95% CI, 1.29–2.13];
P
<0.001) among patients with moderate stroke. However, this was not the case for those with severe stroke (generalized odds ratio, 1.06 [95% CI, 0.54–2.10];
P
=0.87), indicating a significant interaction (
P
=0.03).

CONCLUSIONS:

In patients with acute large infarcts, EVT was associated with improved functional outcomes compared with MM in patients with moderate stroke. However, no significant difference was observed in patients with severe stroke. Therefore, stroke severity should be considered when selecting patients with large infarcts for EVT.

REGISTRATION:

URL:
https://www.clinicaltrials.gov
; Unique identifier: NCT04551664.
A new Saxonagrionidae (Insecta: Odonatoptera) from Southern France Middle Permian confirms the attribution of the family to Panodonata
Authors: BODERAU MATHIEU , GARROUSTE ROMAIN , KUNDURA JEAN-PAUL , NEL ANDRÉ
Published: February 2025

The superorder Odonatoptera Martynov, 1932 comprises a great number of clades (e.g., Meganisoptera, Protanisoptera, Triadophlebiomorpha, etc.) that could be considered as orders at the same rank of the extant Odonata (dragonflies, damsel-dragonflies and damselflies) (Nel & Piney, 2023). The Odonatoptera is very ancient, with representatives dating from the Serpukhovian (late Early Carboniferous) (Petrulevičius & Gutiérrez, 2016). But how old are the Panodonata Bechly, 1996, the clade containing the Odonatoptera with the synapomorphy ‘distal discoidal vein MAb (= distal side of discoidal cell) and subdiscoidal vein (origin of CuA on MP) aligned’ (Bechly, 2016)? Kohli et al. (2016) proposed the triassolestid Triassolestodes asiaticus (age ca. 237 Ma) as the oldest known representative of the crown Odonata because this family belongs to the Epiproctophora (the stem group of the extant Anisoptera). Kohli et al. (2021: fig. 4) dated the divergence between the Zygoptera and Epiproctophora as between 298 and 253 Ma, on the basis of the work of Kohli et al. (2016). Nel et al. (1999) and Prokop et al. (2015) described the two families assigned to Panodonata: Saxonagrionidae Nel, Gand, Fleck, Béthoux & Lapeyrie, 1999 and Huangiopteridae Prokop, Szwedo, Lapeyrie, Garrouste & Nel, 2015 on the basis of two wings from the Guadalupian of Lodève (Southern France).
First observation of the flowers of Sloanea dussii (Eleocarpaceae), a tree endemic to Martinique (Lesser Antilles): ecological, morphological, and taxonomical insights
Authors: FERLAY BENJAMIN , THÉSÉE ALEXANDRE
Published: February 2025

Sloanea dussii is a species endemic to Martinique, Lesser Antilles. It was known only from very sporadic collections but inflorescences and flowers remained unknown. This paper includes a description, photographs, geographic distribution, and conservation assessment for the species. Taxonomic and nomenclatural considerations are also provided.
Carl Linnaeus the herpetologist: a review of his complete herpetological activity and legacy
Authors: KRECSÁK LÁSZLÓ , BAUER AARON M.
Published: February 2025

We provide a complete overview of Linnaeus’s herpetological writings with specific focus on a review of his 89 herpetology related publications. A short biographical summary focused on key episodes of the life of Linnaeus is presented to facilitate the herpetologist reader to place the Linnaean publications in chronological order and to understand in which period of Linnaeus’s life as a scientist the particular work was issued, and thus comprehend the maturity of the different ideas in the particular publication(s). The development of his publications is presented from the initial idea Linnaeus had on a subject, through the elaboration of these subjects by his students and their publication as academic dissertations, to their revision and inclusion in the multi-volume publication ‘Amoenitates Academicae’. The Linnaean publications containing his 222 available Amphibia names are discussed. We present a short history of binominals linked to Amphibia, the key characters in his classification of the class, and further provide an overview of the sources of the existing Linnaean type material.
A New Species of Triaenodes (Trichoptera: Leptoceridae), based on morphological and molecular data, from Kaeng Khoi Waterfall, Chumphon Province, southern Thailand
Authors: LAUDEE PONGSAK , MALICKY HANS , TAKENAKA MASAKI , SAWANGARROM PHUWADON , SUWANNARAT NANNAPHAT
Published: February 2025

A new species of Triaenodes tipmaneei sp. nov. is described and illustrated based on the male and female genitalia. The mitochondrial DNA (mtDNA) cytochrome c oxidase subunit I (COI) of the new species and of the most similar species T. themis Malicky and Prommi 2006 were analyzed. The male genitalia of Triaenodes tipmaneei sp. nov. is distinguished from other species in the genus by the shape of inferior appendages. Inferior appendages of the new species are without recurved processes; the dorsal branch is divided into a dorsal lobe and two processes, with the upper process curved upward and bifid, and the lower process slender and with pointed apex; the main body of the appendage has a short slender apicolateral process, the mesal process is short and pointed, the ventral process is stout, and the apex is pointed. The genetic distance between T. tipmaneei sp. nov. and T. themis, based on the mtDNA COI region, was 8.5 precent, indicating a large genetic differentiation between the two species.
A new species of genus Psilocladia Warren from India, bridging the boundaries of Africa and Asia (Lepidoptera: Geometridae: Ennominae)
Authors: SINGH MANPREET , LENKA RAJESH , CHATTERJEE PALLAB , SINGH NAVNEET
Published: February 2025

In the present manuscript, we describe a new species i.e., Psilocladia indica M. Singh, Lenka & N. Singh, sp. nov., from India and diagnose with its close congeners based on wing pattern and genitalia. Psilocladia indica sp. nov. is the fifth species of the genus. This study also reports Psilocladia Warren, 1898, a genus hitherto known only from Africa, for the first time from Asia. Psilocladia is closely similar to an African genus, Xenimpia Warren, 1895 and an Oriental genus Krananda Moore, 1868. The diagnostic attributes are explained and illustrated herein. Additionally, global checklist and identification key to all the species of the Psilocladia are provided.
Checklist and bilingual key to the genera of Scutelleridae (Hemiptera: Heteroptera) from Mexico, with new distribution records for the state of Oaxaca
Authors: GUZMÁN-VÁSQUEZ HÉCTOR M. , MARTÍNEZ-MARTÍNEZ LAURA
Published: February 2025

For the first time, we provide a checklist and a bilingual key to the genera of Scutelleridae (Hemiptera: Heteroptera) from Mexico, with new distribution records for the state of Oaxaca. The scutellerid fauna of Mexico is comprised of 35 species, two subspecies, 14 genera and two subfamilies, of which seven species are endemic. The best-represented genus in Mexico is Symphylus with eight species. The states of Veracruz and Oaxaca have the highest richness with 17 and 15 species, respectively. The new records for Oaxaca correspond to the species: Camirus moestus (Stål), Orsilochides scurrilis (Stål), Stethaulax marmorata (Say), Symphylus caribbeanus Kirkaldy (all Pachycorinae) and Augocoris gomesii Burmeister (Scutellerinae). We add new locality records for Pachycoris klugii Burmeister and Tetyra antillarum Kirkaldy in Oaxaca. We provide data on the possible coprophagy of Sphyrocoris obliquus (Germar) (Pachycorinae). Stethaulax marmorata is a new state and national record. Also, we document new associations of scutellerids with plants and, a new host record for T. antillarum.
Reply to “Comment on ‘Marathon versus Sprint: Two Modes of Tropical Cyclone Rapid Intensification in a Global Convection-Permitting Simulation’”
Authors: Judt Falko , Rios-Berrios Rosimar , Bryan George H.
Published: February 2025

This reply addresses the comments by Montgomery and Smith on “Marathon versus sprint: Two modes of tropical cyclone rapid intensification in a global convection-permitting simulation.”
Predicting Return-to-Manual Performance in Lower- and Higher-Degree Automation
Authors: Griffiths Natalie , Bowden Vanessa K. , Wee Serena , Loft Shayne
Published: February 2025

Objective

To examine operator state variables (workload, fatigue, trust in automation, task engagement) that potentially predict return-to-manual (RTM) performance after automation fails to complete a task action.

Background

Limited research has examined the extent to which within-person variability in operator states predicts RTM performance, a prerequisite to adapting work systems based on expected performance degradation/operator strain. We examine whether operator states differentially predict RTM performance as a function of degree of automation (DOA).

Method

Participants completed a simulated air traffic control task. Conflict detection was assisted by either a higher- or lower-DOA. When automation failed to resolve a conflict, participants needed to prevent that conflict (i.e., RTM). Participants’ self-reported workload, fatigue, trust in automation, and task engagement were periodically measured.

Results

Participants using lower DOA were faster to resolve conflicts (RTM RT) missed by automation than those using higher DOA. DOA did not moderate the relationship between operator states and RTM performance. Collapsed across DOA, increased workload (relative to participants’ own average) and increased fatigue (relative to sample average, or relative to own average) led to the resolution of fewer conflicts missed by automation (poorer RTM accuracy). Participants with higher trust (relative to own average) had higher RTM accuracy.

Conclusions

Variation in operator state measures of workload, fatigue, and trust can predict RTM performance. However, given some identified inconsistency in which states are predictive across studies, further research is needed.

Applications

Adaptive work systems could be designed to respond to vulnerable operator states to minimise RTM performance decrements.
Perceived Discomfort is Decreased After Repeated Bouts of Isometric Handgrip Exercise With and Without Blood Flow Restriction
Authors: Spitz Robert W. , Wong Vickie , Yamada Yujiro , Kataoka Ryo , Song Jun Seob , Hammert William B. , Kang Anna , Seffrin Aldo , Bell Zachary W. , Loenneke Jeremy P.
Published: February 2025

Blood flow restricted exercise appears to be more discomforting than the same exercise without blood flow restriction. Changes in discomfort have not been investigated following repeated bouts of isometric exercise. It is possible that the isometric contractions may further trap metabolites resulting in greater discomfort. The purpose was to investigate the effects of six weeks of isometric handgrip exercise on perceived discomfort and willingness to continue with that form of exercise. 135 participants trained three times a week for six-weeks. The training consisted of four sets of 2-min low-intensity contractions (at 30% of their maximal voluntary contraction) with blood flow restriction (LI + BFR) and without blood flow restriction (LI). The maximal contraction group performed four, five second maximal contractions (MAX). Discomfort was measured post-exercise on the first, ninth, and last training session using the CR10+ scale. Changes in discomfort from the 1st to the 18th session were greater in the LI [-1.7 (1.7) AU] (BF10 = 6952.769) and LI + BFR [-1.5 (1.9) AU] (BF10 = 404.996) when compared to MAX group [0.04 (1.5) AU]. There was no difference between LI and LI + BFR (BF10 = 0.241). Although there were differences in discomfort, there was no difference in the desire to continue the same exercise amongst groups (BF10 = 0.208). Discomfort decreased more in both low intensity groups compared to the MAX group. Despite greater decreases in discomfort there was no difference in willingness to continue with the same form of exercise. This suggests other factors besides discomfort may influence an individual’s willingness to continue with the same type of exercise.
How Do Components of Executive Function Relate to Taiwanese Sixth Graders’ Mathematical Skills?
Authors: Shen I-hsuan , Chen Chia-ling
Published: February 2025

Executive functions are crucially important for helping to explain children’s mathematical performances. We investigated the relationships between components of executive functions and different aspects of mathematical ability in young school-aged Taiwanese children. In a cross-sectional design, a typically developing group of 122 sixth-grade students completed tests battery of working memory (WM), inhibition, and set-shifting tests, and a measure of achievement competence in mathematical concepts, computation, and applied problems. We found significant associations between general intellectual ability, working memory, inhibition, and set-shifting, and between these abilities and different mathematical skills. Verbal and spatial WM was positively correlated with different mathematical skills, and inhibition and set-shifting were positively correlated with mathematical performance to a lesser extent. We conducted partial correlation analyses to control for participants’ age, socioeconomic status, and processing speed, and we then found that verbal and spatial WM was related to the math domains of concepts, computation, and applied problems. Meanwhile, inhibition was correlated with the domain of applied problems. Regression analyses revealed that varied domains of mathematical skills were best predicted by a general intelligence index (GAI) and verbal working memory (WM). Inhibition predicted better performance in applied problems. We discuss the limitations and implications of these findings, as they provide important information about the specific associations between aspects of executive function and components of mathematics performance in middle childhood.
Artificial UV and natural ageing of polycarbonate/poly(butylene terephthalate) binary blend and reprocessing of aged blends
Authors: Kuram Emel , Ozcelik Babur , Sarman Omer Faruk , Kocoglu Hurol , Ayas Hamza , Dogan Mehmet
Published: February 2025

In this research, the effect of reprocessing for aged polycarbonate (PC)/poly (butylene terephthalate) (PBT) blends was determined on the mechanical properties (tensile, impact, flexural), melt flow index and morphology. Virgin PC/PBT blends were injection molded as the tensile, flexural and impact samples to evaluate the mechanical, rheological, and morphological properties. After that, samples were exposed to artificial accelerated ageing in an QUV chamber (simulating outdoor weathering with alternating cycles of ultraviolet (UV) light and moisture at controlled elevated temperature) for up to 336 hours and natural ageing in Gebze (Turkey) for up to 1 year between May 2017 and May 2018. After these ageing processes, naturally and UV aged specimens were ground, and the ground specimens were mixed with virgin PC/PBT blends at different ratios (25%, 50% and 75% by weight). The mixed materials were re-molded to fabricate test specimens and then characterized. In summary, in current study, the mechanical, rheological, and morphological properties of virgin, aged in natural for 12 months, aged in UV chamber for 336 hours and mixture of virgin-aged PC/PBT were investigated.
Disclosure Readability in Unregulated Financial Markets: Evidence From Initial Coin Offerings
Authors: Burke Qing L. , Li Ben , Wan Chi , Wang Yakun
Published: February 2025

Initial coin offerings (ICOs) have emerged as a popular method to raise capital by startups. During the ICO process, issuers release white papers, which serve as the primary offering documents. Unlike traditional corporate disclosures, ICO disclosures are largely unregulated. We hypothesize that more-readable white papers reflect less information obfuscation by the issuers and are less cognitively costly for potential investors to process and understand, thus enabling the issuers to attract more funding. Utilizing a hand-collected global sample, we find that white paper readability is positively associated with the likelihood of being funded and the amount raised, and the positive association is more pronounced for ICOs that attract more attention from individual investors and for ICOs whose white papers contain fewer numbers or more jargon. Furthermore, we find ventures with more-readable white papers have better post-ICO performance. Overall, this paper enhances our understanding of disclosure readability in a burgeoning, unregulated market.
Singleness and the Pandemic Dating Recession
Authors: Rosenfeld Michael J.
Published: February 2025

The Coronavirus pandemic in the US represented a fundamental challenge to casual dating and to romantic relationship formation. The How Couples Meet and Stay Together (HCMST) data for 2017–2022 show that the rate of singleness among US adults rose from 18.9% in 2017 to 24.3% in 2022 (or higher after adjusting for age), implying that more than 10 million more US adults were single during the pandemic in 2022 compared to 2017. HCMST data show that the difficulty in forming new relationships during the pandemic seems to explain most of the rise in pandemic singleness. Young adults were especially affected by the pandemic dating recession. The arrival of COVID-19 vaccines did not ameliorate the pandemic dating recession; on the contrary, vaccinated adults were more likely to describe barriers to dating in 2022. The rise in singlehood during the pandemic has been under-appreciated because our official data sources focus primarily on marriage and cohabitation, leaving casual and informal romantic relationships understudied. The lack of data on casual romantic relationships in the US has led to a lack of appreciation for the potential vulnerability of casual relationships to external shocks such as a pandemic.
How epigenetics impacts stroke risk and outcomes through DNA methylation: A systematic review
Authors: Gallego-Fabrega Cristina , Cullell Natalia , Fernández-Cadenas Israel
Published: February 2025

The impact of DNA methylation (DNAm) on epigenetics has gained prominence in recent years due to its potential influence on ischemic stroke (IS) and treatment outcomes. DNAm is reversible and a better understanding of its role in IS could help identify novel therapeutic targets. The aim of this systematic review was to compile the available data on DNAm in the risk and prognosis of IS and to explore its therapeutic potential. The review process followed the PRISMA criteria. We searched the Pubmed and Cochrane databases to identify studies that used hypothesis free methodological approaches. Of the 459 studies identified, 34 met the inclusion criteria. The studies were categorized as follows: risk of IS; outcomes; and DNAm age. Most studies used genotyping array technology rather than whole-genome sequencing. DNAm testing was mainly based on blood samples. Most studies involved European cohorts. Most of the studies were performed at a single-center with recruitment at the time of stroke. In a few studies, health status was determined longitudinally. This systematic review shows that IS patients are biologically older than expected and present characteristic DNAm patterns related to stroke risk and outcomes. These patterns could be used to develop new treatments with epidrugs.
Decentralized trajectory planning for quadrotor swarm in cluttered environments with goal convergence guarantee
Authors: Park Jungwon , Lee Yunwoo , Jang Inkyu , Kim H. Jin
Published: February 2025

Decentralized multi-agent trajectory planning (MATP) can enhance the efficiency of multi-robot systems thanks to high scalability and short computation time. However, it may lead to deadlock or livelock in obstacle-rich environments. To tackle this challenge, this paper presents a decentralized MATP algorithm for a quadrotor swarm that ensures convergence to a goal in maze-like environments. The proposed method guides the agents to their goal using the waypoints generated by a grid-based multi-agent path planning (MAPF) algorithm. Additionally, we introduce subgoal optimization to prevent deadlock while the agents follow the waypoints. The proposed algorithm guarantees that the agents converge to their goal if there is no dynamic obstacle and the agents are connected through a fully connected network. Moreover, it ensures deadlock-free even when the agent has a limited communication range. For dynamic obstacle avoidance, we revise the grid-based MAPF to prioritize collision avoidance when the agents encounter dynamic obstacles in a narrow corridor. In simulation, the proposed algorithm achieves a 100% success rate in static environments and shows a higher success rate and shorter flight time compared to most state-of-the-art baseline algorithms in dynamic environments. We validate the safety and robustness of the proposed work through the experiment with 10 quadrotors and one pedestrian in a maze-like environment.
A rare case of acrokeratosis paraneoplastica (Bazex syndrome) and a literature review
Authors: Zhang Xiaoyan
Published: February 2025

Acrokeratosis paraneoplastica is a rare and obligate paraneoplastic dermatosis most commonly associated with squamous cell carcinoma of the upper aerodigestive tract and lung. It has also been linked to adenocarcinomas of the lung, colon, and stomach. However, reports of its association with esophageal adenocarcinoma are exceedingly rare, with only one documented case to date. This condition primarily affects middle-aged White men, with limited cases reported in women. Moreover, its occurrence in the Chinese population is uncommon. We herein present a case of acrokeratosis paraneoplastica in a Chinese woman with primary esophageal adenocarcinoma, along with a review of the relevant literature. To our knowledge, this is the first documented instance of paraneoplastic acrokeratosis associated with esophageal adenocarcinoma in a woman.
MetaClassroom: A New Paradigm and Experience for Programming Education
Authors: Wang Chengliang , Chen Xiaojiao , Li Yifei , Wang Pengju , Wang Haoming , Li Yuanyuan
Published: February 2025

This study explored the impact of MetaClassroom, a virtual immersive programming learning environment designed based on the three-dimensional learning progression (3DLP) concept, on students’ multidimensional development. Utilizing a quasi-experimental research design, this study compared students’ programming learning achievements (PLA), self-regulated learning (SRL) skills, learning beliefs, and learning motivation in MetaClassroom with those in traditional classroom settings. The findings revealed that MetaClassroom significantly enhanced students’ PLA and SRL skills, particularly in subdimensions including Metacognitive Skills, Persistence, and Seeking Help. Additionally, MetaClassroom positively impacted students’ learning beliefs and learning motivation, demonstrating its potential in optimizing knowledge acquisition, application processes, and fostering students’ higher-order thinking skills. By integrating the 3DLP concept into targeted programming learning environments, MetaClassroom created an innovative immersive learning ecosystem, that bridged theory and practice, offering students a comprehensive and engaging platform to develop both foundational knowledge and practical skills. This study not only validated the effectiveness of MetaClassroom in improving students’ programming learning performance and learning experience, but also introduced a new paradigm that integrated teaching, learning, and assessment. The paradigm offers new insights and directions for both programming education and broader educational practices, paving the way for future developments in educational technology.
Sustainable biocomposites based on polylactic acid and agro waste biofillers for lightweight applications: Fabrication and properties
Authors: Ramesh M , Rajeshkumar L , Sanjay MR , Siengchin Suchart
Published: February 2025

The utilization of agricultural biomass residues as biofillers in polymer composites enhances the evolution of green and sustainable biocomposites that assist in progressing towards sustainable development goals. Agricultural biomass residues such as peels, seeds, stalks, and bunches increase with the increase in crop production. The current research focuses on evaluating the influence of waste pomegranate peel biofiller as a novel particulate reinforcement on the mechanical, thermal, and thermomechanical properties of polylactic acid (PLA)-based biocomposites. The pomegranate peel particulate biofillers were characterized using various characterization techniques. Different concentrations of biofillers ranging from 5–25 wt. % was used for the preparation of PLA-based composites. The fabricated composites were subjected to various mechanical and thermal tests. The experimental investigations showed that 15 wt. % of biofiller-reinforced biocomposites exhibited a 13.6 % increase in tensile strength, 42 % increase in tensile modulus, 9.34% increase in compressive strength, 41% in impact strength, and 26 % increase in hardness and better thermal and thermomechanical behaviour when compared with virgin PLA. The failure morphology of the biocomposites portrayed better interfacial bonding between composite constituents. It can be concluded from this study that the pomegranate peel powder can act as potential biofiller reinforcements for producing biocomposites for various lightweight structural applications. Hybridization with biofibers and other biofillers may enhance the application spectrum of these biocomposites further.