bluuebunny/crossref_metadata_2025_split huggingface dataset:
Process Optimization for Biosurfactant Production by Bacillus aryabhattai SPS1001 using Taguchi Method
Authors: Fatima Farkhunda , Tiwari Nishi Prakash , Singh Varsha 
Published: May 2024

Abstract

This study employs Taguchi design of experiments (DOE) to optimize biosurfactant yield by analyzing the impact of various input parameters. Signal-to-noise ratio analysis is utilized for optimization, corroborated by ANOVA findings. Regression equations depicts response behaviour and are validated through a confirmation test. Taguchi methodology identifies optimal conditions for maximum biosurfactant yield: agitation (180 rpm), inoculum size (2%), beef extract (5 g/L), diesel (20 ml/L), peptone (5 g/L), NaCl (7 g/L), incubation time (4 days), pH (7.9), and yeast extract (6 g/L). This yields an 8.33% increase to 1.53 g/L, with initial optimum parameters projecting 1.41 g/L. ANOVA ranks and quantifies control factor contributions, revealing agitation's significant (34.12%) impact on yield. The study underscores the viability of Taguchi's optimal conditions for substantial yield improvement within specific ranges. The strong alignment between expected and experimental yields affirms the reliability of developed models for optimal yield selection. This study underscores the power of statistical techniques like Taguchi DOE and ANOVA in systematically enhancing biosurfactant production by Bacillus aryabhattai SPS1001 and paves the way for future advancements in bioprocess optimization.
Graph-based Semi-supervised Learning for 3D Pose Estimation
Authors: Sharma Ravi Kant , Jha Raghav Kumar , Meena Shweta 
Published: May 2024

Abstract

The challenge of estimating 3D pose has been thoroughly explored and researched in computer vision due to its broad range of applications. However, due to complex structures, occlusion, frame rates, varying sizes and resolutions, this problem is highly challenging. This paper demonstrates the ability of graph neural networks (GNNs) and long short-term memory (LSTM) for 2D to 3D pose estimation in a sequence of frames. LSTM is used as a feature extractor. The bone length and joint angle play a crucial role in pose estimation. Our model uses a GNN to analyze the relationships between nearby joints and their angles and then predicts the final 3D joint positions using a multi-layer perceptron (MLP) model. A Semi-supervised learning and frame-dropping strategy approach is employed to enhance the accuracy of our model. Our model outperforms various latest advancements models, achieving an accuracy of 6.5 mm in joint localization on the HumanEva-1 and Human3.6m datasets.
Support Issues for People with Mental Disorders in Group Homes in Japan
Authors: Yamada Noriko , Tanabe Yuriko , Tanaka Rie 
Published: May 2024

Abstract

In Japan, group homes for people with mental disorders are accommodations affiliated with hospitals where residents can live relatively independent lives. However, the scope of their activities is limited to interactions with caretakers, hospital visits, and nearby shopping. Caretakers in such homes often provide insufficient care and commonly lack medical knowledge and skills to manage aging-related situations. Previous surveys conducted by us in 2008, 2013, and 2018 among the staff of a sample of such establishments in a major city revealed the challenges posed by residents’ aging and the increasing severity of their mental and physical diseases. Another survey will be conducted in December 2023 to clarify changes over time and support difficulties by comparing the results to those of the previous surveys. In the 10 years between 2008 and 2018, the percentage of residents aged 60 and older increased from 25.6–28.6%, those who could manage their medication independently decreased from 90.8–78.4%, while those needing to be accompanied to medical examinations increased from 7.4–15.6%. These results can be used as a basis for implementing improved support systems that include qualified mental health nurses capable of advocating the rights of people with mental disorders in communities.
Sociocultural factors influencing ‘assessments for learning’ at the clinical workplace – A scoping review
Authors: Riaz Qamar , Waterval D. G. J. , Sehlbach Carolin , Paulus A. T. G (Aggie) 
Published: May 2024

Abstract

Background
Workplace-based assessments (WPBAs) play a crucial role in competency-based medical education (CBME) by facilitating learning and informing progression. While many studies have emphasized the role of socio-cultural factors on their implementation as assessment for learning (AfL), a gap exists in understanding how these factors influence WPBAs across different cultural contexts. This review aims to bridge this gap by elucidating how various socio-cultural factors can either enable or hinder the utilization of WPBAs for AfL.
Methods
Arksey and O’Malley’s 5-stage framework was used for this scoping review. Nine databases (PubMed, CINAHL, Dentistry & Oral Sciences Source, Scopus, Science Direct, Cochrane, Google scholar and PakMedinet were searched for studies published between 1995 and 2023. Hofstede’s 4 cultural dimensions namely power distance index, Masculinity vs Femininity, Uncertainty Avoidance Index, and Individualism vs Collectivism were used as the lens to describe the identified socio-cultural factors.
Results
Of 2939 articles screened for eligibility using defined inclusion and exclusion criteria, 81 were included for full text review. The factors influencing use of WPBA for AfL were classified broadly into Cultural and Contextual factors. While most contextual factors behaved similarly in western and non-western contexts, differences were found in the way cultural factors affected perceptions and use of WPBAs in different cultural contexts.
Conclusions
This review provided insights into varying effects of socio-cultural factors on WPBAs as AfL across diverse cultural contexts. These insights can be valuable for institutional leaders, program directors, and faculty members engaged in the implementation of effective WPBA within their specific contexts. prompting further investigation.
Sequential interpenetrating polymer network confines shear-aligned graphene oxide liquid crystals enabling precise molecular sieving
Authors: Bose Suryasarathi , Gupta Ria Sen , Islam Sk Safikul , Pradeep Dhondi , Rajan Ananth Govind 
Published: May 2024

Abstract

Graphene oxide (GO)-based membranes hold great promise for revolutionizing nanofiltration, thanks to their seamless water transport and efficient ion and molecular sieving capabilities. However, challenges such as membrane disintegration under high pressure and nanochannel swelling due to water intercalation hinder their upscaling. In this study, we addressed these issues by aligning GO-based liquid crystals through shear forces and stabilizing their stacking using a sequential interpenetrating polymeric network (IPN) via electrostatic anchorage. This approach retained long-range order through nanoconfinement. By carefully selecting starting materials for the IPN, such as dopamine and GO liquid crystals, we achieved a nematic phase at extremely low concentrations, a feat not achievable with conventional methods. The resulting membranes were extensively characterized using microscopic and spectroscopic techniques, revealing pore sizes in the range of 7 nm facilitated by nanomaterial inclusion. These highly ordered and structurally robust membranes exhibited exceptional water flux (145 LMH) and long-term separation efficiency (> 97%) for monovalent and divalent salts, dyes, and antibiotics. Molecular dynamics simulations provided detailed insights into the ionic sieving mechanism of the GO-based IPN membranes. The MD simulations support that the water flux is reduced upon arresting the rGO-I sheets within IPN which scales with the concentration of rGO-I. In addition, this confinement at molecular length scales leads to a reduction in the number of ions residing within the membrane region, favouring retention within the feed region. These results well corroborate with the observed experimental evidence. Moreover, the membranes showed antifouling, chlorine tolerance, antibacterial properties, and cytocompatibility. They remained stable over repeated operational periods and endured a wide range of harsh environmental conditions without swelling. These resilient and robust membranes pave the way for large-scale membrane fabrication and sustainable water treatment.
Implicit Neural Representation Steganography by Neuron Pruning
Authors: Dong Weina , Liu Jia , Chen Lifeng , Sun Wenquan , Pan Xiaozhong , Ke Yan 
Published: May 2024

Abstract

Recently, implicit neural representation (INR) has started to be applied in image steganography. However, the quality of stego and secret images represented by INR is generally low. In this paper, we propose an implicit neural representation steganography method by neuron pruning. Initially, we randomly deactivate a portion of neurons to train an INR function for implicitly representing the secret image. Subsequently, we prune the neurons that are deemed unimportant for representing the secret image in a unstructured manner to obtain a secret function, while marking the positions of neurons as the key. Finally, based on a partial optimization strategy, we reactivate the pruned neurons to construct a stego function for representing the cover image. The recipient only needs the shared key to recover the secret function from the stego function in order to reconstruct the secret image. Experimental results demonstrate that this method not only allows for lossless recovery of the secret image, but also performs well in terms of capacity, fidelity, and undetectability. The experiments conducted on images of different resolutions validate that our proposed method exhibits significant advantages in image quality over existing implicit representation steganography methods.
A comprehensive bioinformatics analysis of THOC3 highlights its potential role in pan-cancer and clinical significance in lung adenocarcinoma
Authors: Zhang Jixin , Zhao Qi , Zhao Jidong , Cui Xing , Chen Xin 
Published: May 2024

Abstract

THOC3, a crucial component of the THO complex, is involved in mRNA biosynthesis and export. Studies have shown that dysregulation of THOC3 is linked to various aspects of tumorigenesis, including tumor initiation, progression, and metastasis. In this study, we utilized a comprehensive bioinformatics analysis to explore the role of THOC3 in different types of cancer. Our analysis of different types of data helped us understand how THOC3 contributes to cancer at the molecular level, and its clinical significance. Moreover, our immune analysis revealed notable correlations between THOC3 and multiple immune-related signaling pathways. Our findings highlight the potential oncogenic role of THOC3 across different types of cancer and propose dysregulation of THOC3 as a key driver in tumor development. Furthermore, the associations between THOC3 and immune-related signaling pathways indicate its potential as a target for further experimental validation and investigation in the realm of immunotherapy.
Mechanism of geothermal water level rise induced by pumping in an island
Authors: Lee Cholwoo , Hamm Se-Yeong , Cheong Jae-Yeol 
Published: May 2024

Abstract

Groundwater levels rarely rise during pumping, and the underlying mechanism for their rise has not yet been revealed. Water level rise was observed during pumping at a deep geothermal well located approximately 1 km from the western coastline on Seokmo-do Island, Korea. We revealed the mechanism of the water level rise based on the relationship between the water level and tidal efficiency and the relationship between the flowing water temperature and the amount of naturally flowing water to the surface, considering the density and static pressure (h) of water. When water was pumped out of the geothermal well over time, the temperature at 9 m depth increased, whereas the density of the water continuously decreased, and then h increased. From the start of the natural flow, the water temperature in the well increased consistently along with a progressive increase in the amount of natural flow. When the temperature of naturally flowing water reaches ~ 65.5℃, the rate of natural flow increases to ~ 1,441 m3/d with ∆h of ~ 22.3 m. Using a simple formula of transmissivity and maximum drawdown during steady-state long-term pumping at a confined aquifer, the water level was 7.03 m above the land surface at a natural flow rate of 1441 m3/d.
Comparative Molecular Docking and ADMET Studies of Alpha-1-antitrypsin with Nanoparticles
Authors: Sundeep Lakshmi M , Jayaprakash Sakthidasan , J Sandhya , Milky Mariamawit 
Published: May 2024

Abstract

Stroke causes a large number of deaths yearly since it is not detected early. Stroke is caused by the narrowing of the blood vessels and reducing the flow of blood and oxygen to the brain. When ischemic stroke is about to occur some proteins are expressed making them a potential biomarker. The biomarker we chose to work with is alpha-1-antitrypsin because there are studies showing the correlation of alpha-1-antitrypsin with the acute stage of stroke. Due to the inflammation caused during stroke, there will be a rise in alpha-1-antitrypsin. By docking alpha-1-antitrypsin with nanoparticles we can use them as a diagnostic tool for stroke. Nanoparticles have shown a promising result in detection of cancer, arthritis and other infectious disease making it a potential ligand. From this study titanium oxide showed the lowest binding energy and showed lower toxicity compared to the other nanoparticles used in the study. By performing further studies, binding of alpha-1-antitrypsin and titanium oxide can be used for the detection of stroke at the early stage.
Fabrication and Wetting Characteristics of Copper Thin Film: An Active Layer for SPR-based Sensor Applications
Authors: Hossain Mohammad Kamal , Aljishi Abdullah , Khan Firoz , Ul-Hamid Anwar , Rahman Md Mosaddequr 
Published: May 2024

Abstract

In this work, a simple and two-step process was demonstrated to develop multifunctional Cu-based thin films that would be suitable for thin film photoactive devices. Cu thin films on quartz glass substrates were prepared by sputtering technique followed by a thermal treatment. The samples were annealed at high temperatures such as 200, 400, and 600°C for 2 hrs in a tubular furnace. Surface topography was investigated by a high-resolution scanning electron microscope (FESEM) and SEM-aided energy dispersion spectroscopy (EDS). At high temperatures, the thin films were found to have clusters and voids. Detailed studies on optical properties such as UV-vis absorptions, energy band gaps and Urbach energies have been carried out. A red shift in absorption edges (from 464 to 616 nm), a decrease in energy band gaps (from 2.38 to 1.54 eV) and an increase in Urbach energies (from 193 to 272 meV) were observed for those samples annealed at higher temperatures. Sessile drop tests were carried out to find the wetting contact angle and demonstrate the hydrophobicity of the thin film of pristine Cu and of those treated at high temperatures. Sessile drop tests were carried out to find the wetting contact angle (WCA) and demonstrate the hydrophobicity of the thin film of pristine Cu and of those treated at high temperatures. An approximate WCA of 71.9° was determined for the Cu thin film. After the samples were treated at 200°C and 400°C, respectively, the surface became more hydrophobic by 92.4° and 85.2°. Nevertheless, the same thin film's WCA was decreased and its hydrophilicity increased during additional annealing. Cu-based thin films have been suggested as the active layer in an SPR sensor model, and the spectrum and angular resolved reflectance properties have been thoroughly investigated. At spectral wavelengths of 600, 700, and 800 nm, the optimum thickness of Cu thin film was determined to be 40 nm at SPR angles of 44.7°, 42.7°, and 42.15°.
Optimal Video Caching at The Edge of Network by Using Machine Learning
Authors: Ullah Misbah , Xiaopeng Wang , Khan Sohail 
Published: May 2024

Abstract

Efficiently managing network resources in the dynamic field of video-on-demand (VoD) services is a significant challenge. This requires creative methods to optimize video caching strategies. This study examines the use of machine learning (ML), particularly reinforcement learning (RL), into edge network designs to improve video caching procedures. The decentralized, adaptable, and learning characteristics of machine learning offer a powerful method for effectively managing caching in real-time. This technique leads to reduced latency, optimized bandwidth utilization, and improved cache hit rates. Conventional caching algorithms frequently fail to adjust to the changing needs and popularity of material that is inherent in Video on Demand (VoD) services. Our study presents an innovative reinforcement learning (RL) caching method that is specifically developed to automatically adapt caching choices using real-time data analysis, thus guaranteeing an effective content delivery network. We created and evaluated three separate machine learning models: Convolutional Neural Networks (CNN) for extracting features, Deep Q-Networks (DQN) for generating decisions, and a hybrid model that combines the advantages of both CNN and DQN to achieve improved performance. By conducting thorough simulations and implementing our models in real-world deployment scenarios, we have shown substantial improvements compared to traditional caching methods in terms of scalability, adaptability to evolving user patterns, and overall network efficiency. This innovative method not only simplifies the transfer of content in Video on Demand (VoD) systems, but also establishes a new standard for integrating Artificial Intelligence (AI) technologies in network optimization. It effectively tackles present and future obstacles in the digital streaming industry.
Non-resolving Pneumonia with Bronchorrhea
Authors: Inbamuthiah Palaniappan , Gupta Rajesh , Mustafa Mohamed Alhaj , Elbarkouky Ahmed Hanea , Hamed Imad Eldin Ahmed , Alian Osama 
Published: May 2024

Introduction:
Non-resolving pneumonia after antibiotic treatment is encountered onquite a few occasions in clinical practice and is estimated to account for
approximately 15 percent of inpatient pulmonary consultations and 8 percent of bronchoscopies [1]. This is more frequently seen in intensive care/
ventilated patient-associated pneumonia compared to community-acquired pneumonia [2]. Treatment failures are mostly due to infectious causes,
and only 20% of the cases are due to noninfectious causes [3].

Case Presentation:
We present here an interesting case of non-resolving pneumonia. Our patient was a 58-year-old Middle Eastern descendant male who presented
with a cough with excessive mucoid sputum for 6 months. Chest radiology showed patchy consolidation in the right lower lobe, which gradually
progressed to multilobar consolidation over several months despite treatment with antibiotic antifungal and steroids. Extensive evaluation was done
with laboratory microbiological studies and bronchoscopy, but it was negative for tuberculosis and malignancy. So, the patient underwent an open
lung biopsy. Histopathology and immunohistochemical staining were suggestive of adenocarcinoma of the lung, predominant lepidic pattern, with
papillary, acinar patterns, and foci of invasion.

Conclusion:
This case is interesting because of its unique clinical presentation with bronchorrhea and progressive pneumonia. Also, it reveals the role of
surgical lung biopsy in navigating cases of difficult non-resolving pneumonia.
Nonresolving pneumonia with bronchorrhea
Unlocking the Role of Virus-like Particles (VLPs) for Cancer Treatment
Authors: S Venishaa , Kumar Prashant , Sen Aniruddha , Anand Amit , Kaushik Monika , Bhowmick Mithun , Bhowmick Pratibha , Ashique Sumel 
Published: May 2024

Abstract:
Self-assembling structures that look similar to viruses in broad terms but do not contain
viral genetic material are known as virus-like particles. These particles, made up of viral structural
proteins, can have size, shape, and surface characteristics similar to natural viruses. The breakthrough
potential of virus-like particles, or VLPs, as a novel cancer therapy strategy is explored in this article.
Starting with describing the problems facing cancer therapy today, the emphasis moves to an in-depth
study of VLPs, including their different sizes, shapes, and structural characteristics. With insights into
drug encapsulation techniques and their implications for anticancer therapy, integrating VLPs into
drug delivery systems is important. The article highlights the multiple roles vector lambda polymorphs
(VLPs) play in improving diagnostic methods by exploring their dual functioning in medication
delivery and imaging. To address concerns about safety and biocompatibility, the paper critically
analyses the toxicity study of VLPs. It provides a comprehensive review, touching on ongoing clinical
trials and significant patents that impact the environment.
Ultrasonographic Evaluation of Juvenile Localized Scleroderma: Enhancing
Objectivity in Diagnosis and Management
Authors: Türkmen Şeyma , Pirim Gülşah , Sözeri Betül 
Published: May 2024

Background:
Although clinical assessment has historically been the primary method used for pediatric localized sclerosis (LS) diagnosis and staging, highfrequency
ultrasonography (HFUS) is being investigated as a more accurate evaluation method for lesion.

Objectives:
This study aimed to assess, compare dermal and subcutaneous tissue characteristics and enhance enhance lesion staging in pediatric LS patients
using HFUS.

Methods:
Twenty two LS patients were cross-sectionally evaluated with B-mode ultrasonography. Lesions were clinically staged, and dermal and
subcutaneous tissue characteristics were compared with healthy tissue using HFUS.

Results:
Among 55 lesions, 27 were active/new (49.1%), and 28 were atrophic/old (50.9%). Active lesions typically had increased dermal thickness in
66.6% of cases, while atrophic lesions often showed decreased dermal thickness (78.5%), with significant differences (p<0.05). Dermal
echogenicity decreased in 40.7% of active lesions but remained largely unchanged in atrophic lesions (82.1%) (p<0.05). Subcutaneous tissue
thickness significantly decreased in atrophic lesions (78.5%) and increased in 59.2% of active lesions, with a significant difference (p = 0.002).
Subcutaneous tissue echogenicity increased in 44.4% of active lesions and remained mostly unchanged in atrophic lesions (67.8%). Importantly, a
considerable proportion of lesions diagnosed as active through physical examination were actually inactive on HFUS evaluation (55.6%), while a
significant portion of lesions categorized as atrophic on physical examination displayed areas of inactivity upon ultrasonographic assessment
(35.7%). These findings highlight HFUS's potential as a valuable diagnostic tool and reveal discordances between clinical and HFUS staging.

Conclusion:
Ultrasonography offers an objective LS lesion evaluation, especially in pediatrics.