bluuebunny/crossref_metadata_2025_split huggingface dataset:
An on-chip programmable diffractive deep neural network based on Sb2Se3-incorporated silicon metalines
Authors: Zarei Sanaz , Ghazizadeh Ali 
Published: April 2024

Abstract

Artificial intelligence is a technology for simulating and extending human intelligence and has rapidly altered many aspects of modern society. Optical processors, which compute with photons instead of electrons, can fundamentally accelerate the development of artificial intelligence by offering substantially improved computing performance. Photonic approaches for demonstrating artificial neural networks as one of the most widely used frameworks in artificial intelligence, show extraordinary potential to achieve brain-inspired information processing at the speed of light. Recently, all-optical diffractive deep neural networks have been created that are based on passive structures and can perform complicated functions designed by computer-based neural networks. However, existing passive diffractive deep neural networks are not reconfigurable and once is fabricated, its function is fixed. This work reports an on-chip programmable deep diffractive neural network (OPD2NN), in which the optical neurons are built with Sb2Se3 phase change material, making the network reconfigurable and non-volatile. Using numerical simulations, the performance of the OPD2NN is benchmarked on two machine learning tasks that are learning a multifunctional (AND-OR-NOT) logic gate and classification of images of handwritten digits from the MNIST dataset and the obtained results are validated using FDTD simulations by a commercially available full-wave electromagnetic solver. Both numerical and FDTD simulations indicate that a five-hidden-layer OPD2NN with a footprint of 30μmx150μm can appropriately handle (AND-OR-NOT) logic functions. For handwritten digits (0-1-2-3) classification, a three-hidden-layer OPD2NN with a footprint of 60μmx105μm can achieve numerical testing accuracy of 91.5% on the test dataset and the FDTD verification results show 73% matching with numerical testing results.
Development and Validation of a Deep Learning Algorithm for Differentiation of Choroidal Nevi from Small Melanoma in Fundus Photographs
Authors: Sabazade Shiva , Michalski Marco A. Lumia , Bartoszek Jakub , Fili Maria , Holmström Mats , Stålhammar Gustav 
Published: April 2024

Abstract

Purpose
To develop and validate a deep learning algorithm capable of differentiating small choroidal melanomas from nevi.
Design
Retrospective, multi-center cohort study.
Participants
A total of 752 patients diagnosed with choroidal nevi or melanoma
Methods
Wide- and standard field fundus photographs from patients diagnosed with choroidal nevi or melanoma were collected across multiple centers. Diagnoses had been established by ocular oncologists in clinical examinations, using a comprehensive array of diagnostic tools. To be classified as a nevus, a lesion had to be followed for at least 5 years without being re-diagnosed as a melanoma. A neural network optimized for image classification was trained and validated across cohorts of 495 and 168 images, and subsequently tested on a separate set of 89 images.
Main outcome measures
Sensitivity and specificity of the deep learning algorithm in differentiation of small choroidal melanomas from nevi.
Results
In testing, the algorithm achieved 100% sensitivity in identifying small choroidal melanomas from nevi, with a specificity rate of 74%, using an optimal operating point of 0.63 (on a scale from 0.00 to 1.00) determined from independent training and validation datasets. It outperformed 12 ophthalmologists in sensitivity (Mann-Whitney U P=0.006) but not specificity (P=0.54). When comparing by level of experience, the algorithm showed higher sensitivity than both resident and consultant ophthalmologists (Dunn's test P=0.04 and P=0.006, respectively) but not ocular oncologists (P>0.99). Furthermore, the algorithm demonstrated greater discriminative capacity than ophthalmologists who used the MOLES and TFSOM-UHHD risk factors (DeLong’s test P<0.001, all P values Bonferroni corrected), despite the latter having access to supplementary examination data from ultrasonography and optical coherence tomography (OCT).
Conclusions
This study develops and validates a deep learning algorithm for differentiating small choroidal melanomas from nevi, that matches or surpasses the discriminatory performance of experienced human ophthalmologists. Further research will aim to validate its utility in clinical settings.
Therapeutic Strategies to Improve the Treatment of Pleural
Mesothelioma
Authors: Mirra Luca , Beretta Giovanni L. , Lisini Daniela , Marcianti Angela , Spampinato Eleonora , Corno Cristina , Costantino Matteo , Corsico Angelo , Stella Giulia Maria , Perego Paola 
Published: April 2024

Abstract:
Pleural mesothelioma is a rare neoplastic disease with aggressive features. Patient survival is poor due to the lack of early symptoms and the absence of effective therapeutic strategies. The development of pleural mesothelioma is mainly associated with
asbestos exposure and related chronic inflammation. From a molecular-based perspective, this disease is a heterogeneous tumor lacking actionable alterations. The median
overall survival of patients affected by this tumor does not exceed 16 months from diagnosis. Molecular and biochemical approaches have shown that this disease is characterized by resistance to drug-induced apoptosis associated with the activation of cell survival pathways and expression of anti-apoptotic proteins. Thus, there is an urgent need to
develop efficient and safe therapeutic strategies. Here, we review the pharmacological
options available for the treatment of this disease with specific reference to the antitumor agents used in systemic therapies. In addition, novel pharmacological approaches,
such as drug delivery tools, to improve pleural mesothelioma treatment are discussed.
Gold Nanoparticle-Based Drug Delivery System for the Diagnosis and
Treatment of Bacterial Meningitis
Authors: Gautam Darsh , Pandit Vinay , Kumar Sanjay , Talwan Poonam , Sharma Tarun 
Published: April 2024

Abstract:
Managing bacterial pathogens in the central nervous system is an immense issue for researchers all around the globe. The problem of these infections remains throughout the population,
regardless of the discovery of several possible medicines. The major obstacle to drug delivery is
the BBB, but only a few medicines that fulfill demanding requirements can penetrate it. Considering inadequate antibiotic alternatives and the increasing development of resistance, it is more important than ever to find new approaches to address this worldwide problem. Medical nanotechnology has evolved as a cutting-edge and effective means of treating many of the most difficult CNS
illnesses, including bacterial meningitis. Various metallic nanoparticles, such as gold, silver, and titanium oxide, have shown bactericidal potential. Gold nanoparticles have gotten a great deal of interest due to their excellent biocompatibility, simplicity of surface modification, and optical qualities. The current study described AuNP-based detection and therapy options against meningitis--
causing bacteria, including bacterial pathogens' mechanisms for crossing BBB and AuNPs' mode
of Action against those bacteria. The current study looked into green synthesized bactericidal gold
nanoparticles-based therapy techniques for diagnosing and intervening in bacterial meningitis.
Nevertheless, more research is needed before these laboratory findings can be translated into therapeutic trials. Nonetheless, we can confidently assert that the knowledge acquired and addressed in
this study will benefit neuro-nanotechnology researchers.
Breast Cancer Diagnosis Using Computational Model: Recent Advancement
Authors: Sharma Rishav , Malviya Rishabha , Uniyal Prerna 
Published: April 2024

Abstract::
Since breast cancer affects one in every four women, it is of the utmost need to investigate
novel diagnostic technologies and treatment techniques. This requires the development of diagnostic
techniques to simplify the identification of cancer cells, which helps monitor the success of cancer
therapy. One of the most significant obstacles that chemotherapy must overcome is the absence of
technologies that can measure its effectiveness while it is being administered. Additionally, due to its
steadily expanding prevalence and mortality rate, cancer has surpassed AIDS as the world's secondlargest
killer. Breast cancer accounts for a disproportionately high number of cancer-related deaths
among women worldwide, making precise, sensitive imaging a necessity for this disease. When
breast cancer is diagnosed early it can be treated successfully. As an alternate strategy, the use of cutting-
edge computational methodologies has been advocated for creating innovative breast cancer diagnostic
imaging techniques. The following article provides an overview of the traditional diagnostic
procedures that have historically been employed for the detection of breast carcinoma, as well as the
current methods that are being utilized. Furthermore, the investigators provided a comprehensive
overview of various mathematical frameworks, including Machine Learning, Deep Learning, Artificial
Neural Networks, and Robotics, highlighting their progress and potential applications in the field
of breast cancer diagnostic imaging.
Comprehensive Analysis and Experimental Validation of FOXD2
as a Novel Potential Prognostic Biomarker Associated with Immune
Infiltration in Head and Neck Squamous Cell Carcinoma
Authors: He Hanping , Yuan Feng , Li Ying , Pi Guoliang , Shi Hongwei , Li Yanping , Han Guang 
Published: April 2024

Background:
The role of Forkhead Box D2 (FOXD2) in head and neck squamous
cell carcinoma (HNSC) has never been studied.

Object:
Our object was to explore the role of FOXD2 in HNSC.

Methods:
Clinical data for patients with HNSC was obtained from TCGA. Our study examined
the atypical expression of FOXD2 in both HNSC and pan-cancer, along with its diagnostic and
prognostic implications, as well as the association between FOXD2 expression and clinical
characteristics, immune infiltration, immune checkpoint genes, and MSI. Gene set enrichment
analysis (GESA) was used to investigate the potential regulation network of FOXD2 in HNSC.
We analyze the genomic alterations of FOXD2 in HNSC. GSE13397 and qRT-PCR were used
for the validation of FOXD2 expression.

Results:
FOXD2 was aberrantly expressed in 24 tumors. FOXD2 was significantly up-regulated
in HNSC compared to normal head and neck tissue (p < 0.001). High FOXD2 expression was
associated with the histologic grade of the patient with HNSC (p < 0.001), lymphovascular infiltration (p = 0.002) and lymph node neck dissection (p = 0.002). In HNSC, an autonomous correlation between FOXD2 expression and OS was observed (HR: 1.36; 95% CI: 1.04-1.78; p =
0.026). FOXD2 was associated with the neuronal system, neuroactive ligand-receptor interaction, and retinoblastoma gene in cancer. FOXD2 was associated with immune infiltration, immune checkpoints, and MSI. The somatic mutation rate of FOXD2 in HNSC was 0.2%. FOXD2
was significantly up-regulated in HNSC cell lines.

Conclusion:
Our findings suggest that FOXD2 has the potential to serve as a prognostic biomarker and immunotherapeutic target for individuals with HNSC.
Effects of Selenium Supplementation on Thyroid Nodule Volume in Euthyroid Patients: A Randomized Clinical Trial
Authors: Zerehsaz Zeid , Yaghoubi Mohammad Ali , Teimouri Ali , Mousavi Zohreh , Najaf Najafi Mona , Moradi Ali , Mohebbi Masoud , Sahebkar Amirhossein 
Published: April 2024

aims:
Evaluating the Effect of Selenium Supplementation on Thyroid Nodule Volume in Euthyroid Patients

background:
Selenium is an essential trace element, which plays a role in regulation of the metabolism of thyroid hormones.

objective:
This study was designed to evaluate the effect of selenium on the volume of thyroid nodules in euthyroid patients.

method:
In this triple-blinded clinical trial, a total of 60 euthyroid patients with benign thyroid nodules (solitary or multinodular goiter) and normal serum selenium were randomly divided into the case and control (n=30 each) groups. The case group received selenium 200 μg/day while the control group received placebo for 3 months. Thyroid ultrasound was used to measure thyroid nodule volume.

result:
Selenium supplementation (200 µg/day) retained the serum selenium levels of participants in the case group (P=0.251), while, the control group showed a significant drop in serum selenium levels (P=0.007). Moreover, the thyroid volume in case group showed a significant decrease after selenium supplementation (P=0.012); however, a nonsignificant increase was seen in thyroid volume in control group (P=0.832).

conclusion:
Selenium supplementation can reduce thyroid nodule volume in euthyroid patients.

other:
Selenium; supplementation; thyroid; thyroid volume; thyroid nodule; euthyroid
Sema3A Inhibits Osteolytic Bone Metastasis of Non-small Cell Lung Cancer
Authors: Wang Wei , Shen Kaicheng , Liu Ruyan , Zhou Qi 
Published: April 2024

Background:
Osteolytic bone metastasis is a common complication of Non-Small Cell
Lung Cancer (NSCLC), resulting in bone pain, hypercalcemia, and fractures that severely reduce
the quality of life and survival time of patients. Semaphorins 3A (Sema3A) is one of the isoforms
of the Semaphorins family, which is important in a variety of physiological and pathological processes,
such as angiogenesis, immune regulation, and tumorigenesis. However, the role of Sema3A
in the development of osteolytic bone metastasis in NSCLC is unknown.

Methods:
In this study, we established in vitro models simulating NSCLC cells in regulating the
differentiation and maturation of osteoblast and osteoclast precursors and observed the differentiation
of osteoblasts and osteoclasts.

Results:
The results demonstrated that the expression of Sema3A inhibited the proliferation, migration,
and invasion of NSCLC cells, as well as promoted the differentiation of osteoblasts and inhibited
the differentiation of osteoclasts, suggesting that Sema3A can inhibit the occurrence and
development of osteolytic bone metastasis of NSCLC.

Conclusion:
This study provides a new idea for the clinical treatment of osteolytic bone metastasis
in NSCLC.
Conducting Polymer Nanofibers and Nanotubes as a Potential
Nanotechnology: Current Status and Future Directions
Authors: Sharma Shivangi , Mohanalakhmi S. 
Published: April 2024

Abstract:
Conducting polymers (CPs) have garnered a lot of attention in recent years due to the
financial significance they have, the high environmental stability they exhibit, the electrical conductivity they possess, and the beneficial mechanical, optical, and electronic qualities they possess.
Conducting polymers have a wide range of uses, including but not limited to the following: diodes,
transistors, artificial nerves, aviation construction, conducting adhesives, electromagnetic shielding
against electromagnetic interference (EMI), and electrostatic materials. These nanofibers and nanotubes have a wide range of potential applications, including but not limited to: actuators, drug delivery, brain interfaces, nanodiodes, field emission and electrochromic displays, supercapacitors and
energy storage, sensors, nanodiodes, field effect transistors, drug delivery, and protein purification.
The purpose of this review is to discuss a few of these applications as well as their possible applications in the future.
Exploring Theories for Enhancing School Children's Path to Success as Entrepreneurs: A proposed systematic review
Authors: Mahamad Aziz Farhatul Mustamirrah , Abu Hasan Norraidah , Abdul Rahim Memiyanty , Abdul Rahman Maria Atikah , Mohd SobrI Nazatul Syazwani , Mat Aris Nurul Izzati 
Published: April 2024

The objective of this study was to investigate the fundamental learning theories that can be utilized to foster motivation and aspiration among students, with the ultimate goal of cultivating their potential to become successful entrepreneurs or business owners. There is a scarcity of research or scholarly inquiry pertaining to the learning theories and the determinants that impact students' motivation to achieve success as entrepreneurs or business proprietors. The study employs the use of Reporting Standards for Systematic Evidence Syntheses (ROSES). This study could enhance student motivation in dynamic educational settings that foster an entrepreneurial mindset.
A Smartphone App to Support Self-Management for People Living With Sjögren's Syndrome: Qualitative Co-Design Workshops
Authors: McCallum Claire , Campbell Miglena , Vines John , Rapley Tim , Ellis Jason , Deary Vincent , Hackett Katie 
Published: April 2024

Background
Sjögren's syndrome (SS) is the second most common autoimmune rheumatic disease, and the range of symptoms includes fatigue, dryness, sleep disturbances, and pain. Smartphone apps may help deliver a variety of cognitive and behavioral techniques to support self-management in SS. However, app-based interventions must be carefully designed to promote engagement and motivate behavior change.

Objective
We aimed to explore self-management approaches and challenges experienced by people living with SS and produce a corresponding set of design recommendations that inform the design of an engaging, motivating, and evidence-based self-management app for those living with SS.

Methods
We conducted a series of 8 co-design workshops and an additional 3 interviews with participants who were unable to attend a workshop. These were audio recorded, transcribed, and initially thematically analyzed using an inductive approach. Then, the themes were mapped to the Self-Determination Theory domains of competency, autonomy, and relatedness.

Results
Participants experienced a considerable demand in the daily work required in self-managing their SS. The condition demanded unrelenting, fluctuating, and unpredictable mental, physical, and social efforts. Participants used a wide variety of techniques to self-manage their symptoms; however, their sense of competency was undermined by the complexity and interconnected nature of their symptoms and affected by interactions with others. The daily contexts in which this labor was occurring revealed ample opportunities to use digital health aids. The lived experience of participants showed that the constructs of competency, autonomy, and relatedness existed in a complex equilibrium with each other. Sometimes, they were disrupted by tensions, whereas on other occasions, they worked together harmoniously.

Conclusions
An SS self-management app needs to recognize the complexity and overlap of symptoms and the complexities of managing the condition in daily life. Identifying techniques that target several symptoms simultaneously may prevent users from becoming overwhelmed. Including techniques that support assertiveness and communication with others about the condition, its symptoms, and users’ limitations may support users in their interactions with others and improve engagement in symptom management strategies. For digital health aids (such as self-management apps) to provide meaningful support, they should be designed according to human needs such as competence, autonomy, and relatedness. However, the complexities among the 3 Self-Determination Theory constructs should be carefully considered, as they present both design difficulties and opportunities.
Trend in basic oral treatment needs in relation to taxation of sweets, ice cream, and sugar-sweetened beverages in Finland: a registry-based study
Authors: Jokirinta Jesse , Päkkilä Jari , Mourelatos Evangelos , Sipola Sakari , Laitala Marja-Liisa , Karki Saujanya 
Published: April 2024

Objective: The aims were to explore the trend in basic oral treatment needs and total operating cost of public dental services (PDS) in relation to total excise tax revenue generated from sugary products during 2011–2020 and to evaluate the impact of tax policy in excise tax revenue of sugary products and average sugar consumption.
Methods: The study comprised longitudinal data retrieved from Finnish registries during the years 2011–2020. Basic oral treatment needs, and total operating cost of PDS, total excise tax revenue generated from sugary products and average sugar consumed (kg per capita) during the years 2011–2020 were obtained. Simplified panel analyses and sensitivity analyses were used to evaluate the effects of explanatory variables on outcomes.
Results: An approximate one EUR 1,000,000 increase in total excise tax revenue generated from sugary products corresponds to a 0.4% increase in total operating cost of PDS. There was a significant positive trend in total operating cost of PDS in Finland over the study period. Similarly, an approximate one EUR 1,000,000 rise in total excise tax revenue corresponds to a 0.2% increase in basic oral treatment needs. Additionally, there was a statistically significant difference in the average excise tax revenue for sugary products between the periods before and after 2017.
Conclusion: No change in average sugar consumption was observed despite implementing the new sugar policy. Therefore, it may be worthwhile to reconsider the excise tax on sweets and ice cream as it will significantly increase the total national revenues.
Kontribusi Pendapatan Wanita Pengolah Ikan Asin dalam Pendapatan Keluarga di Kabupaten Tulang Bawang
Authors: Abdurrokhim Muhammad , Rangga Kordiyana K , Soepraktikno Serly Silviyanti , Yanfika Helvi 
Published: April 2024

Penelitian ini bertujuan untuk mengetahui kontribusi pendapatan wanita dalam agroindustri ikan asin terhadap pendapatan rumah tangga Penelitian ini dilakukan di Kabupaten Tulang Bawang. Pemilihan lokasi dilakukan dengan sengaja (purposive) dengan pertimbangan bahwa agroindustri ikan asin di Kecamatan Menggala Timur dan Kecamatan Menggala merupakan sentra agroindustri ikan asin di Kabupaten Tulang Bawang, serta seluruh kegiatan agroindustri ikan asin sebagian besar dilakukan oleh para wanita yang telah menikah. Pengambilan data dilakukan pada November-Desember 2020. Penelitian ini menggunakan analisis sensus dan data dianalisis secara deskriptif dengan pendekatan kuantitatif. Responden adalah 39 wanita yang bekerja sebagai pengolah ikan asin di Kabupaten Tulang Bawang. Hasil penelitian menunjukkan bahwa Pendapatan yang diperoleh wanita dalam agroindustri ikan asin yaitu rata-rata sebesar Rp1.743.712,00 perbulan. Besaran pendapatan yang diperoleh wanita dalam agroindustri ikan asin ini dianggap sangat menunjang dalam perekonomian keluarga. Kontribusi pendapatan wanita terhadap pendapatan keluarga memiliki persentase sebesar 37,05 persen, artinya kontribusi pendapatan kerja wanita termasuk pada golongan sedang.

Kata kunci:agroindustri, ikan asin, pendapatan, wanita
The Influence of Extremely Low Frequency (ELF) Waves for Pasteurization of Cow Milk
Authors: Saleh Anang Supriadi , Wibisono Yossi 
Published: April 2024

The extremely low frequency (ELF) magnetic field exposure technology for food processing and preservation is a future technology that produces better food quality. This research aims to examine the exposure of extremely low frequency (ELF) magnetic field waves to pasteurized cow milk and its effect on pH, chemical content, total microbial count, and sensory tests. This research was carried out by exposing ELF waves of 834.8 micro Tesla (μT) for 90 minutes to fresh milk and pasteurized milk. Samples were stored at room temperature then observed at 0, 2, 6, and 21 hours. Each treatment was repeated three times. The results showed that exposure to ELF waves had no effect on chemical content (P<0.05). The pH measurement shows that exposure to ELF waves could maintain the pH value. The total microbial count showed that exposure to ELF waves had an effect on reducing the total microbial count. The organoleptic test showed that pasteurized milk exposed to ELF waves had a smaller level of change. Based on observations, exposure to ELF waves has the potential to be developed in pasteurization, storage of cow milk, and retain its nutritional content. Keywords: Cow milk, Exposure, Extremely low frequency, Influence, Pasteurization.