bluuebunny/crossref_metadata_2025 huggingface dataset:
La supervivencia de una vieja estructura románica en la Baja Edad Media: La Iglesia conventual de La Cabrera (Madrid)
Authors: Cuadrado Marta , Abad Castro Concepción
Published: October 2024

Anuario del Departamento de Historia y Teoría del Arte
Notas sobre la identidad (sobre Max Ernst)
Authors: Castro Flórez Fernando
Published: October 2024

Anuario del Departamento de Historia y Teoría del Arte
Polština v jazykové krajině ostravské ZOO
Authors: Muryc Jiří
Published: October 2024

The purpose of this text is to present several aspects of language landscape research using the example of Zoological Garden and Botanical Park Ostrava. The Polish language in the linguistic landscape of ZOO Ostrava was analysed from a synchronic perspective using the author’s own field research, conducted in 2023–2024. The subject of the research were inscriptions (but also various types of voice messages and audio announcements of an informative or persuasive nature) in Polish found in the ZOO Ostrava area and recorded by the author of this text in the form of photographs and recordings. In order to collect material for description and analysis, all signs in Polish on the outside of buildings, exceptionally also in their interiors were photographed, virtually all over ZOO area. Linguistic signs were analysed in accordance with the methodology adopted in linguistic landscape studies, and were divided into monolingual, polyphonic and mixed, as well as signs of public or private character.
Inversion method and evolutionary behaviour of matric suction for diesel-contaminated soil
Authors: Liu Liyang , Chen Zhixiang , Wan Yong , Sun Xiang
Published: October 2024

Determining matric suction in diesel-contaminated soil within unsaturated regions is essential for simulating the diesel remediation process. Existing literature methods are limited to measuring changes in total liquid content in soil under constant suctions and cannot differentiate between changes in diesel or water content. In this study, a method was proposed to invert the matric suction of unsaturated soil with varying water and diesel contents, based on the theoretical relationship between matric suction and direct shear strength parameters. On this basis, the evolutionary behaviours of matric suction for diesel-contaminated soil are studied. The results show that the water in diesel-contaminated soil primarily resides on the surface of soil particles, while diesel is present within the interstitial pores. The modified van Genuchten model can better predict the change in matric suction of diesel-contaminated soil but cannot describe well the matric suction of each liquid in the soil. The change in soil matric suction caused by reducing the water content is greater than that of reducing the same diesel content. There is little correlation between the residual liquid content of soil and whether it is filled with water or diesel.
Unraveling the proteomic signatures of coronary artery disease and hypercholesterolemia
Authors: Anlar Gulsen Guliz , Pedersen Shona , Al Ashmar Sarah , Krzyslak Hubert , Kamareddine Layla , Zeidan Asad
Published: October 2024

Atherosclerosis, a leading cause of coronary artery disease (CAD), is heavily influenced by hypercholesterolemia (HC). Proteomics research has shown promise in identifying biological markers for CAD diagnosis and prognosis. This cross-sectional study aimed to identify novel biomarkers for detecting HC and CAD. Through the analysis of proteome data from healthy controls (n = 45) and patients diagnosed with HC (n = 51) or CAD (n = 32), distinct protein patterns associated with each condition were identified. Significant alterations in protein levels were identified with a false discovery rate (FDR)-corrected q-value of <0.05. Subsequent receiver operating characteristic (ROC) analysis, with an area under the curve (AUC) greater than 0.75, was conducted. CAD patients exhibited significantly increased levels of the cholesterol-metabolizing protein proprotein convertase subtilisin/kexin type 9 (PCSK9) and varied levels of the angiogenesis-related protein stromal-cell-derived factor-1 (SDF-1) compared to controls. In pairwise comparisons among the study groups, 65 proteins showed significant differential expression. Notably, 14 of these proteins had significant correlations with blood cholesterol levels. Additionally, 22 of the identified proteins were associated with CAD or HC pathways, with nine proteins being common to both conditions (APO E, APO E3, MMP-3, PCSK9, SDF-1, APO B, PAFAH, 60 kDa heat shock protein, and TGF-beta-activated kinase 1 and MAP3K7-binding protein 1 fusion). Nevertheless, this is an exploratory study, and validation studies are needed to confirm these potential protein biomarkers for CAD in the context of HC.
The Analysis of Criminogenic Factors in a Sample of Drug Addicts: The Relevance of the Social -Environmental Element in Antisocial Behavior. Pilot Study
Authors: Domenico Piccininno , Giulio Perrotta
Published: October 2024

Introduction: Behavior is the consequence of cognitive processes that originate from multifactorial products, such as genetic predisposition, education received, and experience gained from the family and social context of reference. The deficiency or defect of one or more of these factors could cause psychopathological shaping in the individual that can foster or nurture deviant or antisocial behavior. It is necessary to investigate what are the main factors underlying the criminal phenomenon. Materials and methods: The literature up to August 2024 was reviewed and 40 articles were included in the research. The survey was conducted through the administration of an experimental Questionnaire-type sociological survey (QA2CPICB). Results: In this pilot study, a population of 49 individuals (42 males and 7 females) most with criminal records and currently addicted to narcotic substances / drugs / alcohol, aged between 24 and 57 years (M: 39.7; SD: 9.1), residents or permanent residents of the “Emmanuel” Communities of the Apulia Region (Italy), were selected. The variable of age is negatively correlated with the areas investigated by the QA2CPICB (as age increases, the impact of the factors investigated decreases). Conclusion: Variables that can describe lived life influences (such as traumatic childhood events, critical family and work issues, economic poverty in adulthood, and lack of stable and lasting affective-emotional support), psychiatric disorders, and social-environmental influences (such as degraded, poor, and/or criminal family and social environment) are negatively correlated with the age variable and serve as positive reinforcers for maintaining the pathological state of drug addiction and engaging in deviant or criminal conduct to procure the necessary economic liquidity. Early intervention, reeducation and economic-work support can act as a deterrent and negative reinforcer on drug addiction, promoting patient recovery and limiting further legally relevant behavior in the justice system. Key points 1. The social-environmental factor plays a central role in maintaining criminal conduct. 2. Criminal conduct is the prerequisite for nurturing the substance-dependence state of drug addicts. 3. Early intervention, reeducation and economic-work support can act as a deterrent and negative reinforcer on drug addiction, promoting patient recovery and limiting further legally relevant behavior in the justice system.
easyIRF preparation of cell monolayers for in resin fluorescence using progressive lowering of temperature v1
Authors: Lumkwana Dumisile
Published: October 2024

This easyIRF protocol details the preparation of cell monolayers for in resin fluorescence using progressive lowering of temperature.
nCoV-2019 sequencing protocol for illumina v5
Authors: Itokawa Kentaro , Sekizuka Tsuyoshi
Published: October 2024

This protocol was originally folked from "ARTIC amplicon sequencing protocol for MinION for nCoV-2019" by Josh Quick to adapt for any illumina sequencers (iSeq, MiSeq, NextSeq, etc.). Because the PCR products are fragmented and ligated with adapters, this protocol is compatible to many sequencing kits with various read lengths (75PE, 150PE, etc.) for Illumina machines. While the library preparation uses QIAseq FX by Qiagen and is basically straight forward (as par kit instruction but modified to 1/4 scale), some tweaks for much of simplicity and speed were added. Change histories (V2): The amount of cDNA input to multiplex PCR is increased (now almost same amount to the ARTIC Network's original protocol) (Step 10). This change gives better results for samples with extremely low RNA copy. Amount of adapter solution input was corrected (Step 19). Change histories (V3): RT step has been changed to use of LunaScript (Tyson et al., 2020). Corrected typos and wrong descriptions about amount of reagents. Added a link to library quantification protocol. Other minor changes. Change histries (V4): Added description about the primer set ver. N1/N2. Added suggestion to double the concentration of nCoV-2019_74_LEFT and nCoV-2019_74_RIGHT. Default annealing & extension temperature of multiplex PCR was changed to 64 °C. Optional normalization step after PCR clean-up was omitted. Change histries (V5): Added description about a new primer set ver. N4 addressing drop-out in B.1.1.529 (Omicron). Clean-up of each PCR products became optional. Instead, you can just dilute them and go. PCR volume was reduced to 1/2.
On Some Feature of Deformation Behavior of a Bird Eggshell
Authors:   Ural Federal University named after the First President of Russia B.N. Yeltsin, Russia, Panfilov Peter , Mezhenov Maxim ,   Ural Federal University named after the First President of Russia B.N. Yeltsin, Russia,   Ural State Mining University, Russia, Guo Jinming ,   Hubei University, China, Zaitsev Dmitry ,   Ural Federal University named after the First President of Russia B.N. Yeltsin, Russia,   Ural State Mining University, Russia
Published: October 2024

Behavior of bird eggshells—biominerals consisting of about 90% of calcium carbonate—under bending is examined. Eggs of several birds were used with two sets of samples cut from every bird eggshell. Mechanical testing was carried out on dry and wet samples in air. Cracks in eggshell samples under bending were studied in situ using a light microscope. Eggshell exhibits brittle behavior on the macroscopic scale in both dry and wet states. However, the crack width could be increased by increasing bending deflection similar to ductile metals under tension. Wet samples show lower bending strength. The morphology of cracks in an eggshell under bending is close to the crack in neck region of a flat aluminum sample. It may be concluded that a bird eggshell under bending exhibits some features of ductile fracture on the microscopic scale.
Rise of Populism in Northeast India: A Case of Assam
Authors: Mochahary Rakesh , K. K. Loung Nathan
Published: October 2024

A blend of historical and contemporary forces has shaped populism in India. The Congress government’s shortcomings (2004–2014), marked by dynastic politics and corruption, paved the way for the rise of populism, particularly under the Bharatiya Janata Party (BJP), which capitalized on anti‐elite sentiment. Narendra Modi’s leadership, characterized by Hindu nationalism and a development agenda, has significantly altered India’s political landscape. This study focuses on the rise of populism in Northeast India, specifically in Assam, where populist movements and leaders have increasingly influenced the socio‐political environment. It explores the socio‐economic conditions and identity politics that have driven the growth of populist ideologies, often leading to the marginalization of ethnic minorities. By analyzing key political events, movements, and policies, the research seeks to uncover the root causes of populism in Assam and its impact on democracy, social cohesion, and regional stability. Employing a qualitative methodology that includes political speeches, media analysis, and empirical evidence, the study examines how political leaders in Assam have mobilized regional and ethnic sentiments for electoral gains, further exacerbating ethnic marginalization. The article aims to understand the catalysts and consequences of populist governance in Assam, offering insights into the broader trend of populism in Northeast India and its future trajectory.
A família Cactaceae em um morro relictual do Pampa brasileiro (Cerro do Loreto, São Vicente do Sul)
Authors: Silva Cassiano Vila Nova da , Ferreira Henrique da Rosa , Secretti Elisangela , Tadielo Érica Acorsi , Lima Luis Fernando Paiva
Published: October 2024

Este estudo tem como objetivo listar as espécies de cactáceas associadas a um morro relictual localizado no domínio do pampa gaúcho, trazendo consigo aspectos ecológicos, taxonômicos e de distribuição. Realizaram-se excursões mensais, entre os anos de 2022 e 2023, e foram coletadas e herborizadas as amostras férteis para identificação taxonômica. O inventário aponta que todos os táxons encontrados pertencem a subfamília Cactoideae, resultando em nove espécies distribuídas em cinco gêneros (Cereus, Echinopsis, Lepismium, Parodia e Rhipsalis). Duas espécies de Lepismium e uma de Rhipsalis são novidades para a flora local. A preservação de florestas em morros relictuais, como o Cerro do Loreto, torna-se importante para a manutenção de uma flora epifítica dentro de um contexto predominantemente campestre.
PERSPECTIVES OF USE ARTIFICIAL INTELLIGENCE TECHNOLOGIES IN ACCOUNTING: EUROPEAN INTEGRATION VECTOR OF REGULATION
Authors:   State University of Trade and Economics, Kyiv, Ukraine, Umantsiv Halyna , Dakhno Kostiantyn ,   State University of Trade and Economics, Kyiv, Ukraine
Published: October 2024

The article discusses the role of artificial intelligence in accounting processes, its problems and risks of application in the accounting industry. Special attention is paid to the issue of artificial intelligence regulation at the international level. The problem of interaction between specialists and artificial intelligence is also raised. The purpose of the article is to systematize information on the impact of artificial intelligence on the accounting profession and accounting processes. The article is based on the hypothesis that artificial intelligence systems will replace accountants in some routine duties. At the same time, these systems will not be able to completely displace accountants from the industry. The results of the study indicate that the efficiency of accounting will be significantly improved with the assistance of artificial intelligence by automating complex tasks, increasing accuracy, systematizing information in real time, speeding up reconciliation procedures, and helping to detect fraud. The findings indicate that accounting processes are being transformed under the influence of artificial intelligence technologies.
Verbal Portraits of Strong and Weak Emotional Facial Expressions
Authors: Nosulenko V.N. , Zhegallo A.V. , Basiul I.A.
Published: October 2024

The article presents the results of an analysis of verbal data obtained when people compared images of emotional expressions of different intensities. The assumption is confirmed that the perceived quality of the same expression (in accordance with the categorization given in Ekman’s papers), but with different degrees of its severity, can reflect the perception of different objects. This assumption turned out to be true for both facial and affective verbal portraits - empirical referents of the perceived quality of expressions. The results obtained confirm the conclusion made in previous works that the comparison of data on the perceived quality of expressions and their list presented in Ekman’s papers is not completely legitimate, since we are not talking about the perception of the corresponding image, but about performing the task of identifying a specific expression. Accordingly, in the first case, the result is characteristics of perceived quality, in the aggregate of which the sign of a given expression will not necessarily come to the fore. In the second case, the image is assessed by the researcher himself based on data on the degree to which the subject recognizes the expression, the content of which is specified by the instructions.
Designing Question-Answer Based Search System in Libraries: Application of Open Source Retrieval Augmented Generation (RAG) Pipeline
Authors: Mazumder Jhantu , Mukhopadhyay Parthasarathi
Published: October 2024

This study primarily aims to prepare a prototype and demonstrate that libraries can develop a low-cost conversational search system using open-source software tools and Large Language Models (LLMs) through a Retrieval-Augmented Generation (RAG) framework. LLMs often hallucinate and provide outdated and non-contextualized responses. However, this experiment shows that LLMs can deliver contextualized, relevant responses when augmented with a set of relevant documents. Augmenting LLMs with relevant documents before generating answers is known as retrieval-augmented generation. The methodology involved creating a RAG pipeline using tools like LangChain, vector databases like ChromaDB, and open-source LLMs like Llama3 (a 70-billion parameter-based model). The prototype developed includes a dataset of 250+ relevant documents on the Chandrayaan-3 mission that was collected, processed, and ingested into the pipeline. Finally, the study compared responses from standard LLMs and LLMs with RAG augmentation. Key findings revealed that standard LLMs (without RAG) produced confidently incorrect, hallucinated responses against queries related to Chandrayaan-3, while LLMs with RAG consistently provided accurate, informative, and contextualized answers when supplied with a set of relevant documents before generating the response. The study concluded that open-source RAG-based systems offer a cost-effective solution for libraries to enhance information retrieval and transform libraries into dynamic information services.
Impact of discounts on sales in Delhi NCR: a survey report
Authors: Meena Rohit , Kumar Ashwini
Published: October 2024

Background: Delhi NCR, which includes Delhi and its neighbouring areas, has experienced considerable growth in the shopping sector over the past decade. A major factor that draws customers to these shopping destinations is the opportunity for bargaining and discounts. This paper examines the impact of discounts on the sales of various item categories.
Methods: A survey has been conducted to collect data. Along with focus on responses to a structured questionnaire, the study also analyses sales across various groups of items, with each group divided into two categories: one offering discounts and the other not.
Results: findings of this study have the potential to shed light on the fact that offering discounts is beneficial and finally leads to increase in sales as it attracts more customers. For most the groups an increase in sales has been witnessed.
Conclusions: From the findings of the study, it can be concluded that if discounts are offered, more customers are attracted which eventually leads to increase in sales day by day.
Sanayi Devrimi Sonrası Görsel İletişimde Yenilik ve Değişim: Peter Behrens’in Modern Tasarım Mirası
Authors: Şahin Muhammet Enes
Published: October 2024

Görsel iletişim tarihi; sosyolojik, psikolojik, ekonomik ve kültürel değişimlerden sıklıkla etkilenmiştir. 18. yüzyılın sonlarında Sanayi Devrimi, sanayi ve tasarımın yakınlaşmasına neden olmuş, bu da iş birliğine dayalı üretim ve tüketim süreçlerine yol açmıştır. Bu bağlamda sanayi ve tasarımın estetik ve işlev kaygılarıyla birbirine yakınlaşması yeni bir tasarımcı profilinin oluşmasına neden olmuştur. Peter Behrens, bu yeni profilin en önemli temsilcilerinden biri olarak kabul edilmektedir. Bu araştırmada Peter Behrens odağında Sanayi Devrimi’nin Avrupa’da görsel iletişim tasarımına etkileri ve modern tasarım anlayışının sanayileşme süreciyle ilişkisi incelenmiştir. Bu çerçevede Behrens’in AEG için yaptığı tasarımlar, modern tasarım anlayışı odağında analiz edilmiş, Behrens’in eğitim süreci, fikirsel arka planı, Avrupa'nın siyasi, iktisadi ve içtimai değişimi ve tasarım dili bütüncül bir yaklaşımla ele alınarak, daha nitelikli ve derin bir şekilde anlaşılması amaçlanmıştır.
Prior Authorization Requirements and Medicaid Enrollees’ Use of Tobacco Cessation Medications, Colorado, 2023
Authors: Dillender Marcus , Mermelstein Robin
Published: October 2024

Despite tobacco cessation medications being a first-line treatment for quitting smoking, a majority of Medicaid programs require health care providers to obtain prior authorization before prescribing them. We examined the impact of Colorado’s Medicaid program removing its prior authorization requirement for these drugs on their use and estimated the additional number of Coloradoans who used these therapies in 2023 because of the policy change. The findings indicate that these requirements decrease low-income people’s use of these medications. ( Am J Public Health. 2025;115(1):42–46. https://doi.org/10.2105/AJPH.2024.307868 )
Delayed En Bloc Excision of L3 for Metastatic Sacrococcygeal Teratoma on a 1-Year-Old Boy
Authors: Tötterman Sandra , Syvänen Johanna , Grönroos Marika , Gardberg Maria , Raitio Arimatias , Helenius Ilkka
Published: October 2024

Case:

A 1-year old boy was presented with cauda equina syndrome and progressive loss of motor function in lower limbs. MRI and CT scans revealed a sacrococcygeal teratoma with metastases para-aortically and in L3 producing compression into the epidural space. Despite metastases and a progressive cauda equina, neoadjuvant treatment was given to achieve cytoreduction for neurological recovery and facilitate curative treatment.

Conclusion:

Malignant sacrococcygeal teratoma with intraspinal infiltration or metastasis requires surgical and adjuvant treatment. If primary neurologic function-sparing surgery makes curative treatment impossible, adequate and quick decompression of neural structures with similar results can be achieved by preoperative chemotherapy, avoiding the local spill of malignant cells.
Gait parameters associated with falls in female patients with end-stage hip osteoarthritis
Authors: Kiko Yu , Uchitomi Hirotaka , Matsubara Masaaki , Miyake Yoshihiro
Published: October 2024

Osteoarthritis of the hip (hip OA) may increase the risk of falls. To decrease fall risk, it is important to assess the gait characteristics of patients with hip OA in detail. This study aimed to investigate the gait characteristics of patients with hip OA caused by falls by simultaneously assessing foot and waist trajectories via an inertial measurement unit (IMU). The subjects were 77 patients with hip OA, 17 of whom had fallen in the past year. Compared with the nonfall group, the fall group was older and had higher fall scores and lower JOA hip scores. With respect to gait characteristics, the stride length on the nonaffected side was significantly shorter in the fall group than in the nonfall group. Stride velocity gait asymmetry was also significantly lower in the fall group than in the nonfall group. The amount of lifting of the waist on the affected and nonaffected sides was significantly lower in the falling group than in the nonfalling group. It was suggested that the fall group might be adapting to stabilization and adjusting to a stable and safe gait pattern because of the effects of falls, new gait characteristics regarding falls in patients with hip OA were found.
Covariance Matrices and Case-Based Reasoning Synergy for Interpretable EEG Classification in Neurological Disorders
Authors: Fernandez Jonah , Innocenti Bianca , López Beatriz
Published: October 2024

This work introduces a novel methodology for Electroencephalography (EEG) data analysis in the context of neurological diseases, emphasizing feature extraction through covariance matrices and their integration with Case-Based Reasoning (CBR). Departing from traditional techniques such as Fast Fourier Transform (FFT) and statistical analysis, we investigate the synergy between covariance matrices and CBR, highlighting their potential to improve the interpretability and efficacy of EEG data analysis over conventional methods like Random Forest (RF). Covariance matrices analyze the relationships between channels, indirectly capturing interactions between brain regions, while CBR uses similarities in these relationship patterns across cases to make decisions, both techniques focusing on understanding the data through its interrelationships. Furthermore, we explore the impact of using data windows in the analysis pipeline to assess their influence on covariance matrix feature extraction and subsequent classification performance in the context of neurological disease diagnosis. Empirical results on public EEG datasets show that CBR, using covariance matrices without temporal windows, achieved the best accuracy, with 0.64 for Alzheimer’s Disease (AD) and up to 0.83 for Parkinson’s Disease (PD), outperforming RF.
Whistles characterisation using artificial intelligence: responses of short-beaked common dolphins (Delphinus delphis) to a bio-inspired acoustic mitigation device
Authors: Lehnhoff Loïc , Glotin Hervé , Gall Yves Le , Peltier Hélène , Pochat Alain , Pochat Krystel , Canneyt Olivier Van , Mérigot Bastien
Published: October 2024

Understanding cetacean whistles is crucial for assessing their social interactions, behaviors, and responses to anthropicactivities. However, to detect and dissociate different kinds of whistles within acoustic records remains challenging. Wedeveloped an innovative semi-automatic deep learning approach (DYOC) to rapidly extract whistle contours from audiorecordings, using YOLOv8m for detection and ResNet18 for identification. Applied to 808 minutes of audio recordings of wildfree-ranging short-beaked common dolphin from the Bay of Biscay, France, DYOC enabled the annotation of 8,730 contours6 times faster than manual annotation. Their features (such as duration, frequency range, and number of inflections) werethen compared based on dolphin behavior, presence of fishing nets, and the DOLPHINFREE acoustic beacon’s influence.Beacon activation led to significant frequency shifts and lower Signal-to-Noise Ratios, while during activation and deactivationphases, whistles were longer with more inflections. A dimension reduction technique (UMAP) revealed gradients betweenarchetypal whistle shapes. This study provides the first characterisation of whistle features for a population of short-beakedcommon dolphins in the Bay of Biscay. The proposed methodological approach has the potential to be applied to the study ofwhistles across a wide range of research areas, species and applications related to animal behaviour.
"My Sports Data”: A Privacy Calculus Model Analysis with Mediation Effects of Personal Competence and Perceived Value
Authors: Kim Young-Jae , Kim E-Sack
Published: October 2024

This study analyzed individuals’ intention to provide their personal information, specifically the “My Sports Data (MSD),” and explored how personal competence and perceived value influence this intention. A privacy calculus model was applied and descriptive statistics, confirmatory factor analysis, correlation analysis, and structural equation modeling were conducted on a sample of 1,000 South Korean adults aged 20–65 years. The results showed that perceived private and public benefits affected perceived value and perceived privacy and security risks. In addition, perceived value significantly affected the intention to provide behavioral and physical information. These findings indicate that by ensuring the protection of personal information and clearly explaining the positive benefits of sharing sports data, people will be more likely to share their sports data so they could access potential benefits. This, in turn, allows for more personalized sports solutions and improvements in sports.
High-throughput, Multiplexed Assay Platform for Integrated Analysis of Sepsis
Authors: Min Jouha , Lim Yongjun , Tokmedash Mohammad Asadi , Allen Matthew , Gruich Cameron , Choi Jun Hee , Kim Changheon , Goldsmith Bryan , Dickson Robert , Bong Ki Wan
Published: October 2024

Complex diseases, such as sepsis and cancer, often involve intricate interactions between different biological systems, necessitating diagnostic tools that can analyze multiple biomarkers simultaneously. This is particularly urgent in sepsis, a dynamic syndrome driven by host–pathogen interactions, where current tools often fail to quickly and accurately assess both the host's immune response and the presence of viable pathogens. Most existing technologies are limited to either pathogen detection or host-response monitoring, missing the two-way signaling between host and pathogens that defines septic pathophysiology. Here, we present MIDAS (Multiplexed Intelligent Diffraction Analysis System), a new assay platform that enables the integrated analysis of the host–pathogen interface by quantifying both bacterial RNA markers for pathogen detection and phenotyping, as well as host inflammatory proteins, within a single system in under 4 h, significantly reducing the turnaround time for pathogen identification by over 20-40 h compared to standard culture workflows. MIDAS synergistically integrates (i) digital holography for high-throughput imaging, (ii) shape-encoded hydrogel sensor arrays for high multiplexing, and (iii) deep learning for fast, automated image analysis—all optimized for point-of-care use in low resource settings. In this proof-of-concept study with two sets of markers—5 bacterial species and 5 plasma proteins—MIDAS demonstrated superior performance in detection sensitivity/specificity, multiplexing power, and speed, compared to standard methods (ELISA, culture, qPCR), making it a powerful diagnostic tool for sepsis. Its modular design allows for expansion beyond the initial sensor elements and marker panels selected in this study. This generic platform, in conjunction with its single-cell analysis capabilities, could serve as a highly multiplexable solution for a variety of applications.
Feasibility of Volume Doubling Time for Predicting Regrowth of Uterine Fibroids Classified by T2-Weighted MR Images after HIFU Treatment
Authors: Liu Yang , Lv Fajin , Luo Yuanli , Qiu Xueke , Xiao Zhibo
Published: October 2024

Objective: To investigate whether volume doubling time (VDT) after high-intensity focused ultrasound (HIFU) treatment can be used to assess the regrowth of uterine fibroids and validate the performance of VDT in T2-weighted imaging (T2WI) signal intensity (SI) classifications of fibroids.
Materials and Methods: A retrospective analysis was conducted on patients who underwent HIFU treatment and at least three follow-up magnetic resonance imaging (MRI) scans between 2016 and 2021. The VDT, VDT2, and VDT3 of the fibroids were calculated from the two MRI scans, and the predicted volumes V2 and V3 were calculated using VDT. Uterine fibroids were classified as hyperintense, isointense, or hypointense based on T2WI, and the correlation between each SI type and VDT was analyzed.
Results:Sixty patients were included in this study. There were no statistically significant differences between the predicted volumes V2 and V3 and the actual fibroid volumes (p=0.713, p=0.838). The VDTs for hyperintense, isointense, and hypointense fibroids showed significant statistical differences in VDT, VDT2, and VDT3 on T2WI(p<0.001). The VDTs for hyperintense, isointense, and hypointense fibroids were 235.6, 469.92, and 465.56 days, respectively. VDT correlated with the fibroid SI classification (r=-0.466, p<0.001), and multivariate Cox regression showed that VDT and non-perfusion volume ratio (NPVR) were independent factors for fibroid regrowth.
Conclusion: VDT can assess the regrowth of uterine fibroids after HIFU treatment. The three types classified by T2WI showed relatively constant VDTs after HIFU treatment, making VDT a relatively accurate predictive factor.
Green Synthesis and Anti-Cancer Properties of Cerium Oxide Nanoparticles Using Pistachio Vera Pericarp Essential Oil
Authors: Askari Nahid , Hojabrpour Hamide , Mirzaei Mohammad Reza , Mirzaei Vahid , Falahati-pour Soudeh Khanamani
Published: October 2024

In recent years, researchers have shown great interest in metal oxide nanoparticles for their possible use in medicine. The purpose of this investigation was to develop a simple and environmentally friendly method for producing cerium oxide nanoparticles (CeO2 NPs) using pistachio Vera Pericarp essential oil (PVEO) as a coating. It was measured the anti-cancer properties of these nanoparticles and their combined effects with zoledronic acid on human prostate (LNCap) and breast cancer cells (MCf7). Scanning electron microscopy (SEM) and X-ray diffractometry (XRD) were employed to examine the characteristics of the CeO2 NPs. SEM and XRD analyses confirmed the nanoparticles' size, shape, phase, and chemical composition. Biological tests demonstrated that the CeO2 NPs showed significant cytotoxic activity against LNCap and MCf7 cells, CeO2 NPs alone or with ZA reduced LNCaP and Mcf-7 cell viability. The CeO2 NPs effectively influenced cell proliferation, apoptosis, and migration by modulating the expression of apoptosis-related genes (BCL-2 and BAX), as indicated by real-time PCR results. The study also discovered that when combined with ZA, PVEO had a synergistic effect on LNCap and MCf7 cell lines. Overall, the study suggests that CeO2 NPs derived from PVEO have the potential to be a new therapeutic agent for prostate and breast cancers.
An accurate and robust RGB-D visual SLAM method in dynamic environments
Authors: Li Zhen , Zhang Xinguang , Fan Lihao , Li Jiahao
Published: October 2024

Traditional SLAM systems have achieved good robustness in static environments. However, the presence of dynamic objects in real-world environments can significantly reduce their localization accuracy. This paper introduces a dynamic SLAM system that combines semantic segmentation with epipolar constraints. The system can detect and remove dynamic points in dynamic environments, achieving good localization performance and generating dense point cloud maps. Initially, the system employs the YOLOv5 deep learning network to extract semantic information from images, thereby generating prior semantic masks for dynamic objects. Subsequently, a novel method for eliminating dynamic feature points is introduced. This method utilizes an adaptive threshold correlated with depth, integrating semantic prior information and epipolar constraint geometric information to further assess the motion state of feature points, thereby removing dynamic points. Finally, a dense point cloud map is produced in dynamic environments by integrating depth information with semantic information. Experiments conducted on the TUM dataset indicate that, compared to ORBSLAM2, the proposed system achieves an average localization accuracy improvement of 95\% in highly dynamic sequences, demonstrating the algorithm's effectiveness in enhancing localization accuracy in dynamic environments.
Spatial Distribution and Trend Analysis of Groundwater Contaminants Using the ArcGIS Geostatistical Analysis (Kriging) Algorithm; The case of Gurage Zone, Ethiopia
Authors: Ayalew Abel Amsalu , Tegenu Moges Tariku
Published: October 2024

The study explores the spatial distribution and trends of groundwater pollutants focusing on calcium and four other key water quality parameters in the Gurage Zone, Ethiopia, in 2024. It uses the ArcGIS geostatistical analysis tool with the Kriging algorithm to map and analyze the spatial variability of contaminants. The primary aim is to identify areas with high levels of pollutants and understand spatial patterns. It identifies contamination hotspots associated with natural processes and human activities. Twenty-seven samples were collected from various sites, and parameters like calcium, total dissolved solids, hardness, conductivity, and alkalinity were measured. The findings show that the distribution of contaminants varies significantly across different areas, with some areas exceeding safe drinking water limits. It reveals that the southern region has the highest calcium concentration, with shallow local boreholes. The deeper wells have higher dissolved solids, hardness, and conductivity. The spatial trend shows increased pollutant levels along the X and Y axes. The Kriging model effectively predicted contaminants in unsampled areas, offering a reliable technique aimed at groundwater quality monitoring. The study provides important insights for the local authorities to implement interventions for groundwater protection in the Gurage Zone.
Smart investing: Unveiling key drivers of strategic investment for investors in the Indonesia Stock Exchange
Authors: Yanuarti Loebiantoro Ika , Hooi Cheng Eaw , Annuar Nursyamilah
Published: October 2024

To achieve the optimal investment decision, people should have better financial literacy. A better understanding of stock investment can be obtained through having experience investing in the stock market. Besides experience, influences from financial socialization agents such as family, friends, education, and media will improve financial knowledge. Hence, it will determine investments wisely. The aim of this study is to determine the degree to which financial experience, family, peers, formal education, media, and financial literacy have direct on impact investment decisions and furthermore to determine the role of financial literacy as mediating variable between financial experience, family, peers, formal education, media, and investment decisions. Investors who have already registered on the Indonesia Stock Exchange are the respondents to this study. Only those investors are allowed to invest in the Indonesian stock market. There are 716 respondents who were analyzed using self-administered questionnaires and structural equation modeling (SmartPLS). Findings show that peers and financial literacy have a direct positive impact (p<0.05) on investment decisions, while financial experience, family, education, and media do not (p>0.05). Additionally, financial experience, peers, education, and media have a significant positive effect on financial literacy (p<0.05), while family does not (p>0.05). Financial literacy is shown to mediate the relationship between financial experience, peers, education, media, and investment decisions (p<0.05) but not with family (p>0.05). This implies that having financial experience improves financial literacy, which leads to better investment decisions. Furthermore, peers, education, and media all play an important role in increasing financial literacy to make optimal investment decisions.
AcknowledgmentWe want to express our sincere gratitude to Universitas Multimedia Nusantara for providing the grant to support this project. Without the generous support, the successful completion of this project would not have been possible. Additionally, we extend our appreciation to the editors and reviewers for their valuable input, which significantly contributed to enhancing the quality of this paper.
Hydrodynamic model-driven evolutionary algorithm-based operation optimization of an experimental drainage pumping station
Authors: Li Xuan , Xue Shuhong , Hou Jingming , Guo Yuan , Liu Yuan , Ma Huan , Zhang Tao , Wang Shu
Published: October 2024

The effective operation of pumping stations plays a crucial role in urban flood management. However, challenges persist in optimizing pumping station operations, including inaccuracies in characterizing flood propagation and the high computational costs associated with optimization. This study introduces a novel optimization approach for pumping station operation that integrates a hydrodynamic model with evolutionary algorithms, leveraging data-driven technology. The method iteratively computes operation rules using the adaptive particle swarm optimization (APSO) algorithm to identify optimal solutions. The hydrodynamic model accurately simulates flood propagation and provides hydraulic parameters for the objective function and constraints of the APSO algorithm. With the predictive capability of the Kriging model, the optimization enhances efficiency by reducing the frequency of calls to the hydrodynamic model. A study case of a flood management digital twin experimental platform was then taken for the application. Compared to initial operation rules, the objective function value of the proposed method is reduced by 28.7, 32.5, and 25%, respectively, under varying magnitudes of unsteady flood inflows, demonstrating high performances in both flood mitigation and operation cost control. Moreover, the method only requires 70 calls to the hydrodynamic model to formulate the decision operation rule.
The Present State and Impact of AI-Driven Computational Tools for Predicting Plant Protein Structures
Authors: Ceasar Stanislaus Antony , Ebeed Heba Talat
Published: October 2024

Several key functions of plants, such as photosynthesis, nutrient transport, disease
resistance, and abiotic tolerance, are manifested by several classes of proteins. Prediction of 3-
dimensional (3-D) structures of proteins and their working mechanisms can have a profound impact
on plant proteomics research and could help improve key agricultural traits in crop plants. This
review aims to present the current status of plant protein structure determination and discuss the
way forward. Most experimentally proven protein structures are available only for the model plant
Arabidopsis thaliana. Most of the key crop plants have only a few hundred or fewer experimentally
proven 3-D structures. Fewer than 1% of the protein sequences in the majority of plants have had
their 3D structures experimentally determined, and A. thaliana is the sole plant with the highest
percentage of 1.4 % of protein sequences with experimentally determined structures. AI-based
protein structure prediction tool AlphaFold has predicted models of several thousand proteins for
many crop plants. In AlphaFold predicted protein models, soybean has the highest percentage
(65%) of its UniProt protein sequences with predicted models, and a few other crop plants have
also a considerable percentage of its UniProt sequences with AlphaFold predicted models.
AlphaFold might help predict models and bridge the gap in plant structure determination studies.
Protein structure information might lead to engineering key residues to improve the agronomical
performance of crop plants.
A Comprehensive and Concise Review on Significance of Potent Peptide; Amyloid Beta (Aβ) in Progression of Alzheimer’s Disease
Authors: Aziz Namra , Wal Pranay , Singh Yash Kumar , Kumar Pankaj , Singh Bhupendra
Published: October 2024

Background:

A condition associated with neurodegeneration is termed Alzheimer's,
characterized by mental as well as memory deterioration. Amyloid beta (Aβ) is a type of peptide
that accumulates within the central nervous system and causes plaque, cerebral amyloid angiopathy
(CAA), and neurodegeneration (loss of acetylcholine). These peptide forms have a major impact
on neuronal damage.

Objective:

Our goal is to provide an overview of Aβ's potential involvement in developing
Alzheimer's condition.

Methods:

An extensive literature review was done using the standard keywords “amyloid beta”,
“amyloid beta precursor protein”, “secretase”, and “Alzheimer’s disease” from the databases SCOPUS,
PubMed, Elsevier, and Web of Science.

Conclusion:

Amyloid-β precursor protein (AβPP) is converted to Aβ through a series of divisions
by β and γ secretases, which are found in lipid rafts. The control of these elements is believed to
have a significant role in Aβ production throughout the aetiology of Alzheimer's disease (AD). In
conclusion, research on Aβ aggregation and clearance has been active in preventing and curing
Alzheimer's disorders. Thus, the purpose of this article was to describe the pharmacological function
of Aβ peptide plus its process of aggregation.
Enhancing Photocatalytic Hydrogen Production Efficiency with Carbon Fibers: A Mini Review
Authors: Zhang Wenyan , Lin Xiaoxia , Guan Hangmin , Wang Yihan , Tao Weidong , Tian Wenjie , Hao Lingyun
Published: October 2024

Photocatalytic hydrogen evolution represents a promising route for sustainable and
clean energy production. Integrating carbon fiber with various photocatalysts has shown significant
enhancements in photocatalytic efficiency. This enhancement is primarily due to carbon fibers’
high conductivity, large surface area, and exceptional mechanical stability, which collectively
promote electron transfer, charge separation, light absorption, active site enrichment, and improve
catalysts’ robustness and resistance to environmental variation. Despite its potential, the use
of carbon fiber in this field has been less explored compared to other conductive supports. Aiming
to provide insights for future studies, this paper reviews the current advancements in integrating
carbon fibers within photocatalytic systems, exploring the underlying mechanisms and future perspectives
to boost hydrogen evolution efficiency and sustainability further.
Molecular Docking and In Silico ADME(T) Evaluation of Selective Phytochemical Inhibitors of VEGF2 Target for the Treatment of Diabetic Retinopathy
Authors: Alagarsamy Veerachamy , Sulthana Mohaideen Thasthagir , Solomon Viswas Raja , Satishchandra Aithamraju , Kulkarni Vishaka Sumant , Narendhar Bandi , Sangeetha Dhanwar , Murugesan Sankaranarayanan
Published: October 2024

Background:

Diabetic retinopathy (DR) is the leading cause of vision loss in diabetic patients.
Currently, the treatment involves the use of glucocorticoids or a VEGF antagonist, which are
"off-label" at present. However, the conventional method of drug discovery and development is a
time-consuming process that requires more than a decade of meticulous research and huge financial
support. While there are a few effective small organic molecules against DR that were identified
many years ago, nutraceuticals - naturally available functional foods containing vitamins, antioxidants,
minerals, fatty acids, and amino acids - can also help delay the progression of some diseases.

Methods:

In this study, 43 phytochemical constituents from four medicinal plants were tested for
their binding affinity to the influential VEGFR2 target of diabetic retinopathy. The study used a
computational approach, in silico molecular docking study, structure-based drug design approach,
MSD (Molecular Dynamic Simulation analysis), in silico ADME(T) studies.

Results:

The study reported that all phytochemical constituents displayed good to the highest binding
affinity than the standard ruboxistaurin. Six phytochemical constituents, namely terchebulin,
pedunculagin, punicalagin, punicalin, casuariniane, and chebulagic acid, exhibited equipotent to
higher activity than the standard. These constituents displayed conventional hydrogen bonds, pialkyl,
and pi-cation interactions to achieve their high binding affinity. The highest binding scores
were chosen for analysis using MSD, ensuring stability of the ligand-protein complex. Pharmacodynamic
and pharmacokinetic properties were evaluated, and their safety profile was validated.

Conclusion:

This in silico screening study suggests that active phytomolecules present in medicinal
plants may inhibit the VEGFR2 target. The best-docked compounds, possessing drug-like properties,
can be used to develop potential inhibitors against DR or to mitigate its severity.