bluuebunny/crossref_metadata_2025_split huggingface dataset:
Liver and Focal Lesion Segmentation in Multi-Sequence MRI Enhanced by Cascaded Deep Learning
Authors: Gut Daniel , Schneider Zofia , Obuchowicz Rafał , Lasek Julia 
Published: November 2024

Abstract

Automatic segmentation of medical images is considered to be one of the most promising applications of deep learning models. However accurate segmentation of liver lesions in MRI remains open problem. This study presents a cascaded deep learning approach for liver and focal lesion segmentation in multi-sequence MRI, specifically using Diffusion-Weighted Imaging (DWI) and T2-weighted sequences. The baseline method, utilizing a U-Net architecture, achieved robust liver segmentation but faced challenges in accurately segmenting lesions, with mean Dice Similarity Coefficients (DSC) of 0.700 and 0.656 on DWI and T2, respectively. To address this, a novel cascaded prediction technique was introduced, wherein segmentation predictions from one modality were iteratively refined by incorporating information from the other modality. This approach significantly improved lesion segmentation performance, with mean DSC increasing to 0.754 on DWI and 0.714 on T2 after three cascade steps. The model also showed substantial gains in lesion-wise sensitivity, crucial for accurate detection, increasing from 0.727 to 0.778 for DWI and from 0.683 to 0.738 for T2. Validation on the LLD-MMRI dataset further demonstrated the method’s generalization potential, achieving a lesion-wise sensitivity of 0.723 for DWI and 0.761 for T2. These findings highlight the effectiveness of the cascaded model in improving segmentation accuracy and suggest its utility in clinical applications for liver and lesion analysis in MRI.
DMC-BH derivative DMC-GF inhibits the growth of glioma stem cells by targeting the TRIM33/SLC25A1/mitochondrial oxidative phosphorylation pathway
Authors: Shi Lei , Huang Jian , Fei Xifeng , He Bao , Sun Zhixiang , sun guan 
Published: November 2024

Abstract

Glioma stem cells (GSCs) present formidable resistance to conventional radiotherapy and chemotherapy, thereby largely contributing to the high recurrence rates associated with gliomas. There is an urgent unmet clinical need for efficacious targeted therapeutics. Previously, we identified DMC-BH, a derivative of curcumin, exhibiting potent anti-glioma activity both in vitro and in vivo. However, it was encumbered by poor metabolic stability and a lack of specificity for the brain. To overcome these obstacles, we developed DMC-GF, a novel GLUT1 (glucose transporter protein 1)-based brain-targeted therapeutic. Our in vitro experiments revealed that DMC-GF potently inhibited the proliferation of tumor cells, surpassing the performance of DMC-BH. Mechanistically, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses indicated that the action of DMC-GF against GSCs might be intricately linked to mitochondrial oxidative phosphorylation. Further exploration revealed that DMC-GF, even at lower concentrations, could cause a decrease in mitochondrial membrane potential and a subsequent reduction in maximal mitochondrial oxygen consumption. Interestingly, DMC-GF administration led to a significant reduction in SLC25A1 protein levels. The overexpression of SLC25A1 significantly attenuated the DMC-GF-induced inhibition of proliferation and increase in apoptosis in GSCs. Importantly, the proteasome inhibitor MG132 was able to inhibit the DMC-GF-mediated decrease in SLC25A1 protein levels; likewise, lowering TRIM33 expression via shRNA was able to achieve a similar outcome. Collectively, these findings provide valuable insights into the potential utility of DMC-GF as a targeted therapeutic against GSCs.
Green Sustainable synthesis of fused pyrimido[4,5-d]pyrimidine systems via Hantzsch reaction
Authors: Eid Elshimaa Mohmed 
Published: November 2024

Abstract

Sustainable green heterocycles compounds of fused bi, tri, and tetracyclic systems containing pyrimidine-barbituric acid rings were synthesized via Hantzch reaction in a simple and efficient method using one-pot three-component of bis aldehydes, barbituric acid, and substituted amines the reactions occurred under microwave irradiation and in catalyst-free conditions. The products were produced with high yields and simple workups. This article emphasizes the significance of sustainable green philosophy that applies to synthesis methods for fused pyrimido[4,5-d]pyrimidine systems, highlighting their environmental friendliness advantages, efficiency, and safety.
Predicting Fire Incidents with ML : an XAI approach
Authors: Lee Donghyeok , Tellez Fernando Perez , Jaiswal Rajesh 
Published: November 2024

Abstract

With increasing urbanization and industrial activities in Dublin city, there is a growing interest in natural disasters and accidents. In this research, we compared the regression performances for the number of fire incidents in Dublin with seven different machine learning models. We evaluated how each model performs with metrics like Mean Squared Error (MSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and R-Squared scores. Among the used models which are Prophet, Auto-Regressive Integrated Moving Average (ARIMA), Simple Linear Regression, Polynomial Regression, Support Vector Regression, Decision Tree Regression, and Random Forest Regression, the most precise model was the Prophet with the highest R-Squared score of 0.91 because it effectively captures the underlying trend, seasonality and holiday effects. This research also aims not only to establish the superior model but also to give clear and understandable reasons for these predictions using explainable AI (XAI). In particular, the trust in Prophet is enhanced by global explanation and local explanation for users to believe in the decision-making processes in the model. It enabled us to enhance the interpretability and transparency of the Prophet, which is aligning with ethical AI (Artificial Intelligence).
Unsupervised Band Selection Based on Covariance Matrix for Hyperspectral Image Classification
Authors: Abdelhafez Eman N. , Hagag Ahmed , Abassy Tamer A. 
Published: November 2024

Abstract

Spectral-spatial classification in hyperspectral imagery has garnered significant interest due to the potential to leverage detailed spectral and spatial information for improved accuracy. However, noisy, or closely spaced spectral bands in original hyperspectral images can detrimentally affect classification, often leading to their exclusion based on expert knowledge. In this paper, we propose an unsupervised band selection method utilizing a covariance matrix for hyperspectral image classification. First, spectral band analysis is performed as a preprocessing step for the proposed method. Second, the absolute difference between the spectral wavelets for the different classes is calculated to select the minimal number of bands based on the maximum absolute difference. After that, the covariance matrix is extracted from the selected band to select the most important bands. Third, the global feature was extracted from the original hyperspectral image (HSI) using selected bands determined by a deep convolutional neural network (CNN) model. Finally, SoftMax and support vector machine (SVM) algorithms were employed for classifying the different classes within the HSI images. To evaluate the effectiveness of our approach, it was compared against contemporary methods using two widely used public HSI datasets: Indian Pines and Salinas-A. The experimental results demonstrate convincingly that our band selection technique outperforms alternative methods in terms of classification accuracy.
Numerical investigation of the structural performance of timber concrete composite structure
Authors: Akram Mostafa Humayun , Alam Md. Rabiul , Islam Monirul 
Published: November 2024

Abstract

Purpose– Coastal people of the USA, Japan, Bangladesh, etc., face sustainable housing solutions against coastal hazards like hurricanes, typhoons, cyclones, tsunamis, etc., for their safe human life and wealth. Most of them build their houses using locally available timber materials, which cannot resist these wind-producing forces. Timber concrete composite (TCC) structures could be the sustainable solution for this issue.
Methods– This research investigates the structural performance of the TCC push-out test made with locally available timbers (Garjan/Gamari) and low-strength brick aggregate concrete. The push-out test represents the practical performance of timber-concrete composite beam slab elements in composite structures. A numerical model was developed using ANSYS finite element (FE) software to simulate the timber-concrete push-out test accurately. This model considered nonlinear material behavior, interface conditions, and complex geometries to capture the structural responses realistically.
Results– The failure load obtained from the analysis closely satisfies the experimental failure load carried out by another researcher and the CUET laboratory. Moreover, a calibrated version of the numerical model based on experimental data achieved a high degree of agreement with load-slip relationships. The failure load and slip increased with the increased strength of concrete. The failure load for Garjan timber was higher than that of Gamari timber. Specimens with 6 rebar shear connectors exhibited a greater failure load than those with only 2.
Conclusion– This research intentions to improve the understanding of the behavior of timber-concrete composite structures and provide valuable insights for optimizing their design and performance. The TCC housing system is sustainable, environmentally friendly, and a novel solution for housing for moderate to low-income coastal people. TCC structures are able to provide necessary rehabilitation for the coastal people of the world.
Efficient and Accurate Stereo Matching via Guided Deformable Aggregation
Authors: Li Jie , Li Xinjia , Chang Mingyuan , Wang Lin , Du Shuangli , Zhou Jie , Liu Yiguang 
Published: November 2024

Abstract

In stereo vision, depth information relies on the dense registration accuracy of binocular stereo images, and its realtime performance is also significant in many automation applications. Recently, it is still a challenge to balance the efficiency and accuracy. Motivated by this problem, we propose a lightweight 2D guided deformable aggregation(GDA) module. It uses color prior information to learn the aggregation sampling points for fitting the irregular window. And it enables to fast recover the lost high-frequency detail information from a coarse cost volume. Furthermore, we propose a guided deformable aggregation based stereo matching network (GDANet) for balancing the efficiency and accuracy. It builds a fast 3D network to obtain the cost volume of low-frequency non-detail regions, and then uses the lightweight 2D GDA module to recover high-frequency detail regions. Experiments show that GDANet achieves better results than current high efficiency methods in SceneFlow and KITTI datasets. Especially, in edge regions and thin structures, our method shows better qualitative and quantitative results.
Successive Approximation Register Maximum Power Point Tracking Control with modified PWM-VSI STATCOM for active and reactive power management in a utility grid tied solar photovoltaic system
Authors: Nibedita Nibedita Ghosh , Asha Asha Rani M. A. , Rahul Rahul Kumar 
Published: November 2024

Abstract

A photovoltaic micro grid linked to a utility grid requires active and reactive power control. Active power balances generation and load demand, preventing oversupply or overloading. The Static Synchronous Compensator (STATCOM) based on a Pulse Width Modulation (PWM) Voltage Source Inverter (VSI) is used to control these power flows, enhancing grid stability, power quality, and energy efficiency. Reactive power is crucial for maintaining voltage levels within the grid, especially in distribution networks with high PV penetration. STATCOM, a PWM-VSI-based system, manages reactive power flow by dynamically adjusting the inverter's output voltage to compensate for voltage fluctuations and maintain a stable voltage profile. Reactive power management enhances reliability and quality in micro grid connected utility grid by minimizing issues like voltage sags, flickers, and power losses. In this proposed system, the modified PWM-VSI STATCOM regulates PV system voltage and current waveforms using P&O MPPT controller and SAR MPPT controller, ensuring grid stability during variable solar generation. Active power and reactive power controlling by implementing SAR MPPT connected SPV system tied 400 V,50 Hz utility grid integrated modified PWM-VSI STATCOM controller is superior as compared to the P&O MPPT connected SPV system tied 400 V, 50 Hz utility grid integrated modified PWM-VSI STATCOM controller in terms of active power management and reactive power control. In this proposed system, it has been observed that the SAR MPPT control based SPV plant is capable to extract 13.56 KW power & 883.9 V whereas P&O control based SPV plant is capable to extract 13.47 KW power, 882.7 V.
Chitosan-clay beads: Preparation, characterization and use as water adsorbent
Authors: Mourak Abdellah , hajjaji mohamed , alagui abdelhakim 
Published: November 2024

Abstract

The microstructure of beads composed of 50 mass% α-chitosan and either montmorillonite, a clay minerals mixture (illite, pyrophyllite, and kaolinite), or palygorskite was investigated using X-ray diffraction and scanning electron microscopy. Moreover, the kinetics of water adsorption and desorption by the beads were studied at temperatures ranging from 25°C to 45°C. Adsorption-desorption cycles were conducted to assess the beads performance. The findings revealed that chitosan and montmorillonite were linked by electrostatic forces, with no intercalation of chitosan observed. Additionally, attractive electrostatic forces were noted between the clay minerals assemblage and chitosan. Conversely, repulsive electrostatic forces occurred between chitosan and palygorskite, with the clay fibers acting as fillers. The study also showed that the maximal adsorption kinetic constants for montmorillonite-containing beads, palygorskite-containing beads, and chitosan beads were 13.6x10⁻³ s⁻¹, 16.7x10⁻³ s⁻¹, and 31x10⁻³ s⁻¹, respectively. As for the beads composed of the clay minerals assemblage, the maximum adsorption kinetic constant was 2.8x10⁻² mg.s⁻¹. Notably, high water adsorption capacities were measured for the beads consisting of palygorskite and the clay minerals assemblage (22% and 34% mass/mass, respectively). Regarding desorption kinetics, relatively high rate constants were determined for beads composed of montmorillonite and the clay minerals assemblage (38.6x10⁻² s⁻¹ and 39x10⁻² s⁻¹, respectively). In addition, more than 90% of adsorbed water was released by all studied beads at 45°C, and the adsorption/desorption performances of the beads were not significantly affected by the applied cycles.
Descriptive phenomenology of examples of dishonesty in psychotherapy from the client's point of view
Authors: Alipour Hossein , Akbari Mahdi 
Published: November 2024

Abstract

The present research was conducted with the aim of identifying examples of dishonesty in psychotherapy from the clients' point of view in 1402. The method used in this research is a qualitative, descriptive phenomenology type. The statistical population of this research included all the clients of counseling centers in Amol city in 1402 who participated in this research using non-probability sampling method. The researcher reached information saturation by interviewing 19 clients and 4 more interviews were conducted with the clients, in total 23 people were the sample clients of this study. A 3-question semi-structured interview protocol was used to collect information. The seven-stage descriptive phenomenological method of Collaizi was used for data analysis. The findings showed that dishonesty in the treatment room is inevitable and the reasons for clients' dishonesty include individual reasons such as; sexual experiences and cognitive errors and external reasons including; Family experiences are lived experiences in society and the therapist's reaction. The results showed that it is difficult for the clients to tell about some issues, and most of them hid at least one issue from their therapist. Clients stated the possibility of being judged by the therapist, not trusting the therapist's confidentiality and avoiding feeling shame as the reason for dishonesty.
An innovative framework for quantifying eco-meteorological droughts in Iran rangeland ecosystems using Copula functions
Authors: Parisaei Banafsheh , Soltani Saeid , Pourmanafi Saeid , Jafari Reza , Isfahani Poria Mohit 
Published: November 2024

Abstract

Drought alone is one of the most complex and costly extreme events for ecosystems, whose types and effects are not solely specific to the lack of a moisture source or a particular region. A less noticeable aspect in drought studies is that this phenomenon can occur together with several other types of droughts or several extreme events and cause more damage than this phenomenon alone. One type of compound drought that can seriously threaten the health of ecosystems is eco-meteorological compound drought. These compound droughts take place when meteorological drought occurs in a situation where the ecosystem is ecologically vulnerable, or in other words, ecological drought dominates the ecosystem. Based on these facts, the purpose of this research was to develop multifaceted approaches for identifying and quantifying compound eco-meteorological droughts, by introducing two copula-based multivariate indices called Standard Eco-Meteorological Drought Index (SEMDI) and Ecological Drought Condition Index (EDCI). The basis for the calculation of both introduced indices was the linking of meteorological drought and ecological drought information through copula functions. In this study, the Standard Precipitation Index (SPI) was used to determine meteorological drought conditions, and the Vegetation Health Index (VHI) was used to determine ecological drought conditions. The results of the research showed that both introduced indices have a suitable capability for modeling the dependence structure between SPI and VHI variables, especially in arid and semi-arid regions. It was also found that the important rangeland ecosystems of Iran in the central plateau and eastern regions, western, southwestern, and southern regions of Iran compared to the northern, northeastern, and northwestern regions suffer more from eco-meteorological droughts, both in terms of frequency and drought intensity. The results achieved in the present study can provide useful information for comprehensive crisis management and reducing the effects of compound droughts in the rangeland ecosystems of Iran.
Deep Ransomware Detection through Dynamic Vulnerability Profiling for Real-Time Threat Identification
Authors: Oppal Michael , Whitmore Sebastian , Holloway Vincent , Abernathy Winston 
Published: November 2024

Abstract

The escalating sophistication and frequency of ransomware attacks have demonstrated the necessity for innovative detection methodologies capable of adapting to rapidly evolving threats. Dynamic Vulnerability Profiling (DVP) emerges as a novel approach, dynamically modeling system vulnerabilities in response to the adaptive behaviors exhibited by contemporary ransomware. Through the integration of advanced machine learning algorithms and real-time data processing, DVP achieves high detection accuracy and resilience against sophisticated evasion techniques, addressing critical challenges inherent in current cybersecurity frameworks. Empirical evaluations demonstrate DVP's adaptability across various ransomware types and its efficient resource utilization, highlighting its potential for deployment in diverse operational environments. The insights derived from this study not only demonstrate the effectiveness of DVP but also contribute to the broader discourse on enhancing proactive defense mechanisms against ransomware threats, emphasizing the imperative of continuous innovation and adaptation in cybersecurity strategies.
Possibilities of intraoperative hemostasis in endoscopic choanoplasty in children
Authors: Asmanov A. I. , Pivneva N. D. , Degtyareva D. V. , Lukin A. M. 
Published: November 2024

Introduction. Recently, a significant breakthrough has been noted in the surgery of congenital choanal atresia in children: new approaches, various modifications of surgical techniques of choanoplasty have reduced the percentage of complications along with achieving good clinical results in restoring nasal breathing. The outcome of surgery largely depends on adequate hemostasis. Thus, increasing its effectiveness remains relevant.Aim. Evaluation of the effectiveness of intraoperative hemostasis during choanoplasty in patients with congenital choanal atresia (CCA).Materials and methods. The study included 63 children diagnosed with CCA treated at the Veltischev Institute (Moscow). The patients were divided into 2 groups: the main group and the control group. In the main group, hemostasis was carried out by using a bipolar coagulator (power 18 W), periodic irrigation of the surgical field with 1-2 ml of 1% solution of incomplete silver salt of polyacrylic acid (total volume 10-20 ml), in combination with intravenous administration of tranexamic acid in a single dose of 15 mg/kg body weight at a rate of 1 ml/min. In the control group, only coagulation and tranexamic acid were used.Results and discussion. In the main group, the use of incomplete silver salt of polyacrylic acid reduced the average volume of blood loss by 1.3 times compared with the control group.Conclusion. The study showed that the use of incomplete silver salt of polyacrylic acid in hemostasis during choanoplasty in children with CCA is effective.
The effect of topical medications on olfactory function: Barrier therapy
Authors: Radtsig E. Yu. , Egina A. D. , Polunin M. M. 
Published: November 2024

Introduction. Sensory organs help humans exist in the surrounding world, but the evaluation of olfaction remained “in the shadows” practically until the COVID-19 pandemic, although many questions are still insufficiently studied, such as the effect of intranasal medications on olfactory function.Aim. To assess the olfactory function in healthy volunteers before and after a course of using an ectoine nasal solution.Materials and methods. Under our observation were healthy volunteers (medical university students and healthcare workers aged 16 to 35 years) who, in addition to routine ENT examinations, underwent an assessment of their olfactory status using a professional set of odorants for olfactometry and subjectively using a self-assessment scale for olfaction before and after a course of ectoine nasal solution, as well as a self-assessment of its preventive effect. The collected data were recorded in Excel spreadsheets (Microsoft Office 365) for further statistical analysis.Results and discussion. The results showed an average increase of 1 point in the self-assessment of olfaction in the observation group, as well as an increase in the number of “correct” responses when using the set of odorants. However, discrepancies were noted between self-assessment and the objective evaluation of olfaction. The extent of the preventive effect (based on the self-assessment by participants using a 10-point visual analog scale) was rated at 5 points.Conclusions. 1. A one-month course of barrier therapy (ectoine nasal solution) does not cause any impairment in olfactory function, as evidenced by olfactometric testing (an average increase of 10% in correct responses across the group, with 80% of participants showing improvement) and olfaction self-assessment (an average increase of 1 point across the group, with 55% of participants showing improvement). 2. Self-assessment of olfaction cannot be considered a reliable measure of the actual olfactory function. 3. The use of barrier therapy (ectoine nasal solution) has a moderate preventive effect (5 points).