bluuebunny/crossref_metadata_2025_split huggingface dataset:
Personalized Respiratory Motion Modeling Incorporating Longitudinal Data through Two-stage Transfer Learning
Authors: Chen Peizhi , Zou Xupeng , Guo Yifan 
Published: January 2025

Purpose:
This study aims to develop an accurate image registration framework for personalized respiratory motion modeling.

Methods:
The proposed framework incorporates longitudinal data through a two-stage transfer learning approach. In the first stage, transfer learning is
employed on longitudinal data collected from the same device. In the second stage, a personalized model is constructed using the transfer learning
approach, reusing the model from the first stage. A novel cross-error function is introduced to guide the customized adaptation stage.

Results:
The experiments demonstrate the effectiveness of the proposed framework in respiratory motion modeling. Integrating longitudinal data allows for
improved accuracy for personalized respiratory motion modeling.

Conclusion:
The study presents a novel approach that incorporates longitudinal data into a two-stage transfer learning process for personalized respiratory
motion modeling. The framework demonstrates improved accuracy. The results highlight the potential of leveraging longitudinal data to provide
personalized image registration solutions.
Enhancing Medical Image Classification through Transfer Learning and CLAHE Optimization
Authors: Halloum Kamal , Ez-Zahraouy Hamid 
Published: January 2025

Introduction:
This paper examines the impact of transfer learning and CLAHE (Contrast Limited Adaptive Histogram Equalization) optimization on the
classification of medical images, specifically brain images.

Methods:
Four different setups were tested: normal images without data augmentation, normal images with data augmentation, CLAHE-processed images
without data augmentation, and CLAHE-processed images with data augmentation.

Results:
The results show that using CLAHE combined with data augmentation significantly improves classification accuracy. Specifically, the
combination of CLAHE and data augmentation achieved a precision of 0.90, a recall of 0.87, an F1-score of 0.89, and an accuracy of 0.86,
outperforming the other setups.

Conclusion:
These findings highlight the effectiveness of CLAHE optimization in the context of transfer learning, particularly when data augmentation
techniques are also applied, leading to an overall improvement in the performance of brain image classification models.
Eriochrome Cyanine R Immobilized Amberlite XAD-2 for Efficient
Separation and Preconcentration of Fe(III)
Authors: Gupta Ashu , Gupta Radhika , Sharma R. K. 
Published: January 2025

Background:
Metal contamination in water is a significant environmental and public
health issue. They can find their way into water sources through industrial waste, mining activities,
agricultural runoff and improper disposal of chemicals. Once present in water, these metals can accumulate in the bodies of aquatic organisms and move up the food chain, ultimately affecting human
health. Hence, the development of effective water treatment technologies is required to reduce risks
associated with contaminated water sources.

Method:
In the present study, we report the fabrication of Eriochrome cyanine R immobilized Amberlite XAD-2 for the separation and preconcentration of Fe(III). Various parameters that can affect
adsorption, were optimized, such as pH, contact time, temperature, analyte concentration and resin
loading. The reliability of the proposed method has also been examined in the presence of possible
matrix ions. To prove the large-scale applicability of the fabricated sorbent, real waste stream aliquots were obtained from nearby leather and electroplating industries.

Result:
The synthesized chelating resin proves its supremacy as an environmentally benign sorbent
for the adsorption of Fe(III) ions from various aqueous samples under mild conditions. A wide pH
range of 4-9, with a contact time of just 7.5 min, under ambient temperature and using just 40 mg of
the resin, offers a sustainable approach for efficient removal of Fe(III) ions with a high preconcentration factor of 150. Additionally, these adsorbed ions can be effortlessly desorbed using mild eluent.
Satisfactory results were obtained with real industrial samples. The sorbent also imparts recyclability
for up to five consecutive cycles

Conclusion:
Eriochrome cyanine R immobilized Amberlite XAD-2 was proven to be highly effective in the removal of Fe(III) ions from various water samples, including real wastewater, which
offer the potential for scale-up in various practical applications. Additionally, it offers a costeffective, reusable, and environmentally friendly solution compared to other traditional methods. Its
wide application in industrial wastewater treatment makes it an essential component in reducing
metal contamination and protecting water quality
Unveiling the Potential of S4 on Non-small Cell Lung Cancer Cells: Impact on Proliferation, Apoptosis, Senescence, and Metabolome Profile
Authors: Demircan Turan , Yavuz Mervenur , Bölük Aydın 
Published: January 2025

Background:
Lung cancer is a highly aggressive tumor with limited therapeutic options. The misregulation
of Androgen Receptor (AR) signaling has been observed in lung cancer. Therefore, inhibiting AR signaling
is a promising strategy for treating lung cancer.

Objective:
Selective Androgen Receptor Modulators (SARMs) are small molecule drugs with a high affinity for
the AR. S4, a member of SARMs was potentially positioned as a promising therapeutic agent in A549 lung cancer
cells owing to its high bioavailability, lesser side effects, and novelty in cancer.

Methods:
We employed several techniques to investigate the potential anti-carcinogenic effect of S4 on A549
cells at cellular level. The cytotoxicity of S4 was investigated thorough MTT, and the IC50 value was identified
as 0.22 mM. Then, the anchorage-dependent and -independent colonization of cells were assessed by colony
formation and soft agar assays, respectively. Additionally, migration capacity, apoptosis, proliferation, senescene,
cell-cycle progression of cells was examined thoroughly. In addition, gene expression profile and metabolome
signature were explored via qRT-PCR and metabolomics, respectively to provide molecular links for S4 mode of
action.

Results:
Our findings demonstrate that S4 inhibited growth, migration, and proliferation while inducing apoptosis.
S4 significantly upregulated the BAX, CDKN1A, PUMA, and GADD45A genes while downregulating MKI67,
BIRC5, and PCNA expression. S4 treatment drastically altered the metabolome signature, and enrichment of
cancer related pathways by altered metabolites was noteworthy.

Conclusion:
We report the first study evaluating the potential anti-carcinogenic effects of S4 on lung cancer invitro
which would bridge the gap on the utility of SARMs as inhibitors of lung cancer. Our results suggest that S4
could be considered as a promising drug candidate to test further for lung cancer treatment.

conclusion:
We report the first study evaluating the potential anti-carcinogenic effects of S4 on lung cancer in-vitro which would bridge the gap on the utility of SARMs as inhibitors of lung cancer.
Enhancing Solubility of a BCS Class II Drug- Itraconazole by Developing
and Optimizing Solid Lipid Nanoparticles using a Central Composite
Design
Authors: Mohammed Irfan A. , Jonnalagadda Sriramakamal 
Published: January 2025

Background:
Itraconazole (ICZ) has been approved by the FDA to treat many fungal infections including, blastomycosis, histoplasmosis, and aspergillosis. ICZ can be also used as
prophylaxis in the population who are at high risk for developing systemic fungal infections, such
as HIV patients, and chemotherapy patients.

Aim:
However, since ICZ is a BCS Class II drug that has low solubility and high permeability,
leads to low oral bioavailability. In addition, the absorption of ICZ from commercial oral dosage
forms is highly affected by food intake and pH.

Objective:
The current study aimed to develop, optimize, and characterize ICZ-loaded solid lipid
nanoparticles (ICZ-SLNs) using a Central Composite Design for improved solubility and extendedrelease profile.

Methods:
ICZ-SLNs were optimized based on physicochemical characteristics. ICZ-SLNs were also evaluated for differential scanning calorimetry (DSC), in-vitro release, lyophilization, transmission electron microscopy (TEM), and physicochemical stability at refrigerated and room temperatures for three months.

Results:
The optimized ICZ-SLNs formulation showed particle size, polydispersity index, zeta potential, drug content, and entrapment efficiency of 335.6±8.0 nm, 0.25±0.02, -23.8±0.5 mV,
98.3±2.5%, and 99.5±1.5%, respectively. ICZ-SLN dispersions showed extended-release profiles
for ICZ compared to the control solution over 24 h. The absence of the endothermic melting drug
peak of the lyophilized formulation indicated that the drug was converted to its amorphous form inside the solid matrix. In addition, TEM studies showed spherical shape nanoparticles. Moreover, the
optimized ICZ-SLN formulation was stable at both tested storage conditions

Conclusion:
The current ICZ formulation could exhibit improved oral bioavailability with better
therapeutic outcomes during the treatment of systemic fungal infections.
Analytical Modeling of Inductance for Variable Flux Reluctance Machine with Fully Understanding of Influence of Geometrical Parameters
Authors: Zhao Qiang , Liu Xu 
Published: January 2025

Background:
The winding function method, commonly utilized for calculating machine
inductance, requires solving the integral involving the product of the winding function and
air-gap flux density. However, obtaining an analytical result for inductance via the winding function
method in a variable flux reluctance machine (VFRM) is challenging due to the complex airgap
flux density in its doubly salient structure.

Objective:
An analytical model of VFRM inductance is established with a comprehensive understanding
of the influence of geometrical parameters.

Methods:
This paper presents a novel approach to transform the product of the winding function
and air-gap flux density into a cosine series. Then, the integral can be calculated with the aid of
the periodicity of trigonometric functions.

Results:
The analytical results of the winding inductance are validated by the finite element method
(FEM) simulations and experimental measurements. The relative error for the three-phase peak
self-inductances is 4.8% between analytical and FEM results and does not exceed 4.9% between
analytical and experimental results.

Conclusion:
With this approach, the Fourier series of inductance can be calculated analytically
rather than numerically. The relationship between the harmonic amplitude/order of inductance and
machine parameters is revealed. This analytical model can provide the preliminary basis for the
inductance design of VFRMs.
Impact of Furfural Raffinate Oil as a Filling Agent on the Vulcanization and Mechanical Properties of Rubber
Authors: Wali Suleiman A. , Mohammed Abubakar , Abubakar Abdulhalim Musa , Usman Abdulmuhsin , Khan Kamran 
Published: January 2025

Background:
This study investigates the utilization of furfural raffinate oil (FRO) as a
filling agent in rubber vulcanization processes, focusing on its impact on the mechanical properties
of various rubber types. The research aims to understand how different amounts of 2# and 4#
Raffinate oils affect the vulcanization characteristics of chlorinated polyethylene (CPE), natural
rubber (NR), styrene-butadiene rubber (SBR), and cis-butadiene rubber (BR).

Method:
Through experimental analysis, the density-temperature relationship of raffinate oils was
examined, revealing distinct differences between 2# and 4#, which have implications for their
composition and properties. The study involved filling CPE rubber with slurry FRO and evaluating
the mechanical properties across different samples. Standardized tests were used to assess the
physical and mechanical properties of the vulcanized rubber, ensuring quality and performance
consistency in rubber products.

Result:
The findings show that the CPE rubber filled with slurry FRO exhibits varying mechanical
properties across different samples. Changes in tensile strength were observed to enhance mechanical
strength, while variations in elongation at break with different oil fillings indicated the impact
of oil content on flexibility and stretchability. Additionally, changes in tear strength with varying
oil fillings improved the tear resistance and durability of the rubber materials.

Conclusion:
These results suggest that the choice of filler oil significantly influences the mechanical
properties of vulcanized rubber. The study highlights the potential of furfural raffinate oil as
an alternative or complementary option to traditional filling oils in the rubber industry. Exploring
novel additives like FRO could optimize rubber properties and applications, offering valuable insights
for enhancing the performance and durability of rubber products.
An Overview of FDA-approved Anticancer and Biologics in 2023: An
Observational Study
Authors: Shukla Ajay Kumar , Sarajhna Ashish Kumar , misra Saurav 
Published: January 2025

Background:
The United States Food and Drug Administration (US FDA) is responsible for ensuring public health by conducting a comprehensive assessment and approval of
pharmaceuticals, medical devices, and food products. The federal agency conducts a thorough
evaluation of drug safety and efficacy before granting market approval.

Material and Methods:
This retrospective study aimed to analyse all new drug approvals that
took place during the 2023 study period using an observational, record-based approach. To
gather data on drug approvals by the US FDA, we relied on the FDA database website. We also
conducted a literature search on electronic databases like PubMed, clinicaltrials.gov, and the
Cochrane database to gather comprehensive drug-related information

Results:
In the CY 2023, a total of 55 drugs were approved by US-FDA. Out of which 23 drugs
(42%) were given orphan drug designation and 12 drugs (22%) were approved in first in class
category during this period. US-FDA has gave 7 breakthrough approvals, 22 priority, 18 fast
track, 2 Qualified Infectious Disease Product Designation, 4 accelerated approvals in CY2023.
There were 16 drugs (29%) which were approved for cancer in 2023 by US-FDA. Out of 16
drugs, 06 belongs to tyrosine kinase class, 07 were monoclonal antibody and 01 each of gamma
secretase inhibitor, estrogen receptor antagonist and radioactive drug. During the CY 2023, 16
(29%) biological drugs were approved which included monoclonal antibodies, (N=12), enzymes derivatives (N= 3) and hormones derivatives (N=1)

Conclusion:
Notable advancements in the drug development market were witnessed between
2015 and 2022, and 2023 was no different. The total number novel drugs approved was significantly higher than previous year. Expedited approval of anticancer and biologics is seen as
recent trend in drug development.
Implementación del sistema de gestión ambiental SIGA en una Universidad Publica en Colombia
Authors: Samper Maestría Orlando Miranda , Oyaga Martínez Rafael Fernando , Campo Calderón Iván 
Published: January 2025

La Universidad Popular del Cesar como institución de educación superior, y concibiendo dentro de su misión y política institucional el tema ambiental como eje fundamental para la conservación y prevalencia de la vida, enfoca todas sus estrategias y herramientas para vislumbrar, comprender y analizar el panorama general de la problemática ambiental y el deterioro de los ecosistemas, la cual se ha incrementado en las últimas décadas, fenómeno mundial que ataca a todas las culturas, sin distingo de raza o posición geográfica o social, ocasionado muchas veces por el mismo crecimiento económico y demográfico que es sin duda uno de los factores que acrecienta esta problemática.
El presente trabajo surge de la necesidad que posee la Universidad Popular del Cesar, seccional Aguachica, de enfocar los esfuerzos organizacionales hacia la identificación y tratamiento de aspectos e impactos ambientales generados por las actividades realizadas durante el proceso y la prestación de servicios, con la finalidad de promover el mejoramiento continuo de la universidad y la competitividad en el mercado generando servicios de buena calidad con el menor impacto ambiental posible.
Dentro de su política institucional y de acuerdo al direccionamiento estratégico de un sistema de gestión ambiental en la universidad es indispensable debido a que encamina el desarrollo del SGA a partir de un diagnóstico inicial integrado, donde todos los aspectos concernientes al proceso, dan como resultado la Planificación del Sistema de Gestión Ambiental dentro de la Universidad Popular del Cesar, seccional Aguachica que incluye, entre otros, los requisitos generales, la política ambiental, la identificación y documentación de aspectos e impactos ambientales, requisitos legales y otros requisitos y los objetivos, metas y programas ambientales.
La Universidad como centro generador de conocimiento es responsable de aumentar y afianzar desde el ámbito académico herramientas existentes para mejorar el desempeño y así llegar a la excelencia.
Predicting Age and Visual-Motor Integration Using Origami Photographs: Deep Learning Study
Authors: Huang Chien-Yu , Yu Yen-Ting , Chen Kuan-Lin , Lien Jenn-Jier , Lin Gong-Hong , Hsieh Ching-Lin 
Published: January 2025

Abstract

Background
Origami is a popular activity among preschool children and can be used by therapists as an evaluation tool to assess children’s development in clinical settings. It is easy to implement, appealing to children, and time-efficient, requiring only simple materials—pieces of paper. Furthermore, the products of origami may reflect children’s ages and their visual-motor integration (VMI) development. However, therapists typically evaluate children’s origami creations based primarily on their personal background knowledge and clinical experience, leading to subjective and descriptive feedback. Consequently, the effectiveness of using origami products to determine children’s age and VMI development lacks empirical support.

Objective
This study had two main aims. First, we sought to apply artificial intelligence (AI) techniques to origami products to predict children’s ages and VMI development, including VMI level (standardized scores) and VMI developmental status (typical, borderline, or delayed). Second, we explored the performance of the AI models using all combinations of photographs taken from different angles.

Methods
A total of 515 children aged 2-6 years were recruited and divided into training and testing groups at a 4:1 ratio. Children created origami dogs, which were photographed from 8 different angles. The Beery–Buktenica Developmental Test of Visual-Motor Integration, 6th Edition, was used to assess the children’s VMI levels and developmental status. Three AI models—ResNet-50, XGBoost, and a multilayer perceptron—were combined sequentially to predict age z scores and VMI z scores using the training group. The trained models were then tested using the testing group, and the accuracy of the predicted VMI developmental status was also calculated.

Results
The R2 of the age and the VMI trained models ranged from 0.50 to 0.73 and from 0.50 to 0.66, respectively. The AI models that obtained an R2>0.70 for the age model and an R2>0.60 for the VMI model were selected for model testing. Those models were further examined for the accuracy of the VMI developmental status, the correlations, and the mean absolute error (MAE) of both the age and the VMI models. The accuracy of the VMI developmental status was about 71%-76%. The correlations between the final predicted age z score and the real age z score ranged from 0.84 to 0.85, and the correlations of the final predicted VMI z scores to the real z scores ranged from 0.77 to 0.81. The MAE of the age models ranged from 0.42 to 0.46 and those of the VMI models ranged from 0.43 to 0.48.

Conclusion
Our findings indicate that AI techniques have a significant potential for predicting children’s development. The insights provided by AI may assist therapists in better interpreting children’s performance in activities.
Emprendimiento rural en Sinaloa Desafíos, oportunidades y su impacto en el desarrollo económico y social
Authors: Hernández Osuna Adolfo Arturo 
Published: January 2025

El emprendimiento rural en Sinaloa, México enfrenta múltiples desafíos, incluyendo el acceso limitado a financiamiento, la insuficiencia de infraestructura básica, las dificultades para acceder a mercados y la falta de capacitación adecuada, no obstante, existen numerosas oportunidades que, de ser aprovechadas, podrían transformar la economía rural y mejorar la calidad de vida de sus habitantes, este estudio analiza estos desafíos, oportunidades y evalúa su impacto en el desarrollo económico y social de la región, se recopilaron datos de encuestas y entrevistas con emprendedores rurales y representantes institucionales, los hallazgos revelan que el emprendimiento rural contribuye significativamente a la generación de empleo, la reducción de la pobreza y la cohesión social, aunque es esencial implementar políticas públicas y programas de apoyo que aborden las barreras existentes y potencien las oportunidades identificadas, este artículo proporciona recomendaciones para promover un entorno propicio para el desarrollo empresarial en las zonas rurales de Sinaloa, México.
Relative Performance Information and Employee Performance: The Role of Need for Cognition
Authors: Erickson Devon , Holderness D. Kip , Olsen Kari Joseph , Thornock Todd A. 
Published: January 2025

ABSTRACT
Relative performance information (RPI) represents a potentially beneficial feedback mechanism, but its motivational effects may depend on recipients’ characteristics. This paper explores whether a key employee trait—need for cognition (NFC)—moderates the motivational effects of RPI. Using a laboratory experiment, we find that an expectation of RPI enhances task performance for lower-NFC individuals by increasing effort to search for task-relevant information but has no effect for higher-NFC individuals. These results persist after controlling for RPI’s informational effect. Complementary survey findings reveal that NFC correlates with age, education level, and the performance of cognitively demanding skills. Notably, although lower-NFC individuals benefit most from RPI, they are less likely to seek and receive it. These findings highlight the need for managers to strategically implement RPI to enhance its benefits.
Data Availability: Data available upon request.
JEL Classifications: M40.