bluuebunny/crossref_metadata_2025 huggingface dataset:
Long-term decitabine/retinoic acid maintenance treatment in an elderly sAML patient with high-risk genetics
Authors: Javorniczky Nora Rebeka , Grishina Olga , Hund Inga , Pantic Milena , Pfeifer Dietmar , Schmoor Claudia , Thomas Johanna , Duyster Justus , Becker Heiko , Lübbert Michael
Published: November 2023

Elderly patients with AML ineligible for induction have a dismal prognosis; hence disease stabilization is a primary treatment goal. This case of a 75-year-old patient with secondary AML receiving the combination of decitabine and ATRA (within the DECIDER trial, NCT00867672) demonstrates an above-average survival. The therapy administered over 52 cycles led to complete molecular and hematological remission and resulted in 5.3 years overall survival. Clonal evolution of the leukemic clone could be demonstrated using DNA sequencing methods. According to the literature, this case constitutes the longest continued HMA exposure in an elderly AML patient ineligible for standard chemotherapy.
Oxidative stress regulation and related metabolic pathways in epithelial–mesenchymal transition of breast cancer stem cells
Authors: Farahzadi Raheleh , Valipour Behnaz , Fathi Ezzatollah , Pirmoradi Samaneh , Molavi Ommoleila , Montazersaheb Soheila , Sanaat Zohreh
Published: November 2023

Epithelial–mesenchymal transition (EMT) is a cell remodeling process in which epithelial cells undergo a reversible phenotype switch via the loss of adhesion capacity and acquisition of mesenchymal characteristics. In other words, EMT activation can increase invasiveness and metastatic properties, and prevent the sensitivity of tumor cells to chemotherapeutics, as mesenchymal cells have a higher resistance to chemotherapy and immunotherapy. EMT is orchestrated by a complex and multifactorial network, often linked to episodic, transient, or partial events. A variety of factors have been implicated in EMT development. Based on this concept, multiple metabolic pathways and master transcription factors, such as Snail, Twist, and ZEB, can drive the EMT. Emerging evidence suggests that oxidative stress plays a significant role in EMT induction. One emerging theory is that reducing mitochondrial-derived reactive oxygen species production may contribute to EMT development. This review describes how metabolic pathways and transcription factors are linked to EMT induction and addresses the involvement of signaling pathways.
Therapeutic uses of oxytocin in stress-related neuropsychiatric disorders
Authors: Zhang Sen , Zhang Ying-Dan , Shi Dong-Dong , Wang Zhen
Published: November 2023

Oxytocin (OXT), produced and secreted in the paraventricular nucleus and supraoptic nucleus of magnocellular and parvocellular neurons. The diverse presence and activity of oxytocin suggests a potential for this neuropeptide in the pathogenesis and treatment of stress-related neuropsychiatric disorders (anxiety, depression and post-traumatic stress disorder (PTSD)). For a more comprehensive understanding of the mechanism of OXT's anti-stress action, the signaling cascade of OXT binding to targeting stress were summarized. Then the advance of OXT treatment in depression, anxiety, PTSD and the major projection region of OXT neuron were discussed. Further, the efficacy of endogenous and exogenous OXT in stress responses were highlighted in this review. To augment the level of OXT in stress-related neuropsychiatric disorders, current biological strategies were summarized to shed a light on the treatment of stress-induced psychiatric disorders. We also conclude some of the major puzzles in the therapeutic uses of OXT in stress-related neuropsychiatric disorders. Although some questions remain to be resolved, OXT has an enormous potential therapeutic use as a hormone that regulates stress responses.
Networks in Japanese regional agro-food economies: an empirical exploration of the network linkage model
Authors: Ishikawa Kiyotaka
Published: November 2023

Network linkage is important in evaluating macroeconomic performance since input‒output networks across industries are asymmetric and respond differently to external shocks. While most studies implicitly assume elastic substitution between intermediates and factors using Cobb‒Douglas models, this is often improbable since the input‒output structure may change due to the shocks, which would be observed as nonlinearities in macroeconomic impacts on sectoral shocks. Additionally, considering regionally located sectors such as the agriculture and food-processing industries, the propagation of sectoral shocks can be interregionally correlated. This study employs the network linkage model to empirically verify the interaction of agro-food sectoral shocks in regional outcomes. By comparing the network effects influencing the national economy and regional economy, the superiority of considering intraregional networks among agro-food sectors is empirically verified; thus, productivity shocks arising in these industries propagate more intensively within their own region.
The CAR macrophage cells, a novel generation of chimeric antigen-based approach against solid tumors
Authors: Hadiloo Kaveh , Taremi Siavash , Heidari Mahmood , Esmaeilzadeh Abdolreza
Published: November 2023

Today, adoptive cell therapy has many successes in cancer therapy, and this subject is brilliant in using chimeric antigen receptor T cells. The CAR T cell therapy, with its FDA-approved drugs, could treat several types of hematological malignancies and thus be very attractive for treating solid cancer. Unfortunately, the CAR T cell cannot be very functional in solid cancers due to its unique features. This treatment method has several harmful adverse effects that limit their applications, so novel treatments must use new cells like NK cells, NKT cells, and macrophage cells. Among these cells, the CAR macrophage cells, due to their brilliant innate features, are more attractive for solid tumor therapy and seem to be a better candidate for the prior treatment methods. The CAR macrophage cells have vital roles in the tumor microenvironment and, with their direct effect, can eliminate tumor cells efficiently. In addition, the CAR macrophage cells, due to being a part of the innate immune system, attended the tumor sites. With the high infiltration, their therapy modulations are more effective. This review investigates the last achievements in CAR-macrophage cells and the future of this immunotherapy treatment method.
From immunology to artificial intelligence: revolutionizing latent tuberculosis infection diagnosis with machine learning
Authors: Li Lin-Sheng , Yang Ling , Zhuang Li , Ye Zhao-Yang , Zhao Wei-Guo , Gong Wen-Ping
Published: November 2023

Latent tuberculosis infection (LTBI) has become a major source of active tuberculosis (ATB). Although the tuberculin skin test and interferon-gamma release assay can be used to diagnose LTBI, these methods can only differentiate infected individuals from healthy ones but cannot discriminate between LTBI and ATB. Thus, the diagnosis of LTBI faces many challenges, such as the lack of effective biomarkers from Mycobacterium tuberculosis (MTB) for distinguishing LTBI, the low diagnostic efficacy of biomarkers derived from the human host, and the absence of a gold standard to differentiate between LTBI and ATB. Sputum culture, as the gold standard for diagnosing tuberculosis, is time-consuming and cannot distinguish between ATB and LTBI. In this article, we review the pathogenesis of MTB and the immune mechanisms of the host in LTBI, including the innate and adaptive immune responses, multiple immune evasion mechanisms of MTB, and epigenetic regulation. Based on this knowledge, we summarize the current status and challenges in diagnosing LTBI and present the application of machine learning (ML) in LTBI diagnosis, as well as the advantages and limitations of ML in this context. Finally, we discuss the future development directions of ML applied to LTBI diagnosis.
Recovery from indomethacin-induced gastrointestinal bleeding by treatment with teprenone
Authors: Deguchi Saori , Iwakami Ayusa , Tujigiwa Mizuki , Otake Hiroko , Mano Yu , Yamamoto Naoki , Nakazawa Yosuke , Misra Manju , Nagai Noriaki
Published: November 2023

Background

Gastrointestinal injuries caused by nonsteroidal anti-inflammatory drugs (NSAIDs) is a serious side effect in patients with rheumatoid arthritis (RA). However, effective therapeutic strategies have yet to be established. In this study, we investigated the therapeutic effects of teprenone (TEP), a gastric mucosal protective drug, on NSAID-induced gastrointestinal injuries in rats with RA (AA rats).

Methods

Gastrointestinal injury was induced by oral administration of indomethacin (IMC), a typical NSAID. TEP was orally administered after IMC-induced gastrointestinal bleeding, and the stomach, jejunum, and ileum were excised.

Results

On day 14 of IMC administration, lesion areas in the stomach, jejunum, and ileum were significantly larger in AA rats than in normal rats. When TEP was orally administered to AA rats, the lesion areas in the stomach, jejunum, and ileum significantly decreased compared with those in control rats (IMC-induced AA rats). Therefore, we measured NOS2 mRNA and NO levels, which were significantly decreased in rats with IMC-induced AA after treatment with TEP.

Conclusions

These results suggest that the oral administration of TEP may be useful for the treatment of NSAID-induced gastrointestinal injuries in patients with RA.
Study protocol: Novel Methods for Implementing Measurement-Based Care with youth in Low-Resource Environments (NIMBLE)
Authors: Martinez Ruben G. , Weiner Bryan J. , Meza Rosemary D. , Dorsey Shannon , Palazzo Lorella G. , Matson Abigail , Bain Carolyn , Mettert Kayne D. , Pullmann Michael D. , Lewis Cara C.
Published: November 2023

Background

For youth receiving care in community mental health centers, comorbidities are the rule rather than the exception. Using measurement-based care (MBC), or the routine evaluation of symptoms to inform care decisions, as the foundation of treatment for youth with comorbid problems significantly improves the impact of psychotherapy by focusing care and building engagement and alliance. MBC increases the rate of symptom improvement, detects clients who would otherwise deteriorate, and alerts clinicians to non-responders. Despite its demonstrated utility, MBC is rarely implemented with fidelity; less than 15% of providers report using MBC per recommendations. Previous efforts to support MBC implementation have yielded suboptimal outcomes, in part, due to organizations’ challenges with identifying and prioritizing barriers and selecting and developing strategies to overcome them. New methods are needed for identifying and prioritizing barriers, and matching strategies to barriers to optimize MBC implementation and treatment quality to improve youth mental health outcomes in community settings.

Methods

Pragmatic implementation methods will be piloted in four diverse community mental health centers. Methods include (a) rapid evidence synthesis; (b) rapid ethnography; (c) design kits (e.g., kits with disposable cameras, journals, maps); (d) barrier prioritization, and (e) causal pathway diagramming. These activities will generate actionable barriers; subsequently, we will use facilitated group processes to prioritize barriers and develop causal pathway diagrams to match strategies to barriers to create implementation plans that optimize MBC fidelity (Aim 1). We will track strategy deployment for 6 months, then compare MBC fidelity for another 6 months post-implementation with data from 2 years of historical controls (Aim 2). Finally, we will co-design a toolkit for design kit methods with youth and the practice and scientific communities (Aim 3).

Discussion

Optimizing MBC implementation in community mental health centers could transform youth mental health care by ensuring the most pressing symptoms are targeted early in treatment. The discussion section highlights expected challenges and limits to using the five methods, including recruitment and engagement given the high pressure on community mental health settings.

Trial registration

Clinicaltrials.gov. NCT05644756. Registered on 18 November 2022. This trial was retrospectively registered.
SRAP and IRAP revealed molecular characterization and genetic relationships among cowpea (Vigna unguiculata L.) irradiated by gamma-ray
Authors: Azzam Clara R. , Sultan Fadia M. , Rizk Mokhtar S. , Ahmed Mohamed Z. S. , Ibrahim Shafik D. , Noureldeen Ahmed , Ali Esmat F. , Darwish Hadeer , Khaled Khaled Adly M.
Published: November 2023

Background

Cowpea is a high-protein legume that can be grown in many environments. Gamma radiation can modify plant metabolism and growth. An experiment was conducted to determine the effect of different gamma-ray doses on cowpea yield and growth. The results showed that gamma radiation had a significant effect on cowpea yield and growth, with the highest yields and growth rates observed at lower doses. Higher doses had a negative effect on cowpea yield and growth. The study suggests that gamma radiation can be used to improve cowpea yield and growth, but that the optimal dose must be determined for each specific cultivar and environment.

Results

Results specified that gamma ray significantly affected growth characters and forage yield. Gamma-ray dose of 50 Gy in M1 and M2 generations gave the highest values for all studied characteristics compared to the control and all other irradiation doses, except the crude fiber, followed by 75 and 100 Gy doses for all characters, except number of tillers plant−1 and crude fiber. Seven combinations of SRAP produced 227 loci with an average polymorphism percentage of 85%. The allele frequency of target loci ranged between 0.29 and 0.60, and the PIC was 0.41–0.50 in range, while the GTS% of SRAP combinations ranged from 36 to 63%. The genetic similarities ranged between − 4 and 30%. Ten primers produced 450 loci with a polymorphism percentage of 88%. The allele frequency of target loci ranged between 0.28 and 0.46. The PIC was 0.40–0.50 in range, and the GTS% of IRAP primers ranged from 29 to 71%. The genetic similarities ranged from 8 to 37%.

Conclusions

SRAP and IRAP analysis revealed more than two clusters of treated plants. In silico analysis showed that some SRAP primers could align with genes in cowpea and related genomes. The SRAP-F12R9 primer is unique to Phaseolus vulgaris, while the SRAP-F13R15 and SRAP-F13em1 primers align with genes on different chromosomes in cowpea cultivar Xiabao 2.
Internal carotid bulb occlusion by a giant thrombus after thoracoscopic left upper lung lobectomy successfully treated with endovascular stenting: a case report
Authors: Saito Tomohito , Kunieda Takenobu , Hashimoto Yasumasa , Ishida Mitsuaki , Maru Natsumi , Utsumi Takahiro , Matsui Hiroshi , Taniguchi Yohei , Hino Haruaki , Murakawa Tomohiro
Published: November 2023

Background

Perioperative acute ischemic stroke following lung resection is relatively rare, though a devastating complication. Specifically, patients undergoing left upper lung lobectomy for lung cancer are likely to develop perioperative acute ischemic stroke.

Case presentation

A 67-year-old man underwent thoracoscopic left upper lung lobectomy for lung adenocarcinoma; he experienced sudden-onset left hemiparesis and dysarthria on the morning of the second postoperative day. Angiography revealed occlusion of the bulbs of the right internal and external carotid arteries by a giant thrombus, which could not be removed through endovascular thrombectomy. We deployed a stent at the right carotid bifurcation to foist the giant thrombus, achieving revascularization 4 h after the onset. Treatment response was assessed as good improvement with a modified Rankin scale score of 0, and the patient was discharged home 19 days after symptom onset.

Conclusions

We present a unique case of carotid bulb thromboembolism resulting from a giant thrombus following thoracoscopic left upper lung lobectomy, for which endovascular stenting was effective.
Como criar valor com a Transformação Digital?
Authors: De Borba Darci , Balejos Frantz Bernardo , Maurente Da Rosa Jonas , Carlos da Silva Freitas Junior José , Bentes Gonçalves Bruno
Published: November 2023

Framework ajuda gestores a identificar e superar desafios ao reformularem sua proposta de valor diante das inovações tecnológicas
Case Report: Toxic epidermal necrolysis: a rare pediatric case report from Nepal
Authors: Dawadi Ambika , Lamichhane Anita , Upreti Manish , Dhakal Natasha
Published: November 2023

Toxic epidermal necrolysis (TEN) is a life-threatening cutaneous reaction to various medications like antibiotics and antiepileptics characterized by erythematous rashes, diffuse necrosis, and exfoliation of skin and mucous membranes, with a high mortality rate. Here, we present a case of six years old female child from Nepal who presented with fever and rashes, was diagnosed with measles and treated with cefixime, ibuprofen, and other drugs. Six hours after taking the drugs, the child developed generalized rashes, blisters formation, and peeling of the skin which progressed to cover most of the skin of her body within the next two days. She was then diagnosed with TEN and admitted to the Pediatric Intensive Care Unit (PICU) and treated by a multidisciplinary team with antibiotics, systemic steroids, antihistamines, wound care, and other medications. The child's fever subsided and her skin and oral lesions gradually regenerated. She was discharged after twelve days of hospitalization as she improved clinically and symptomatically. TEN is a dermatological emergency that should be diagnosed and treated promptly to minimize the fatal outcome of the disease.
Therapy of parapneumonic empyema in children: a protocol for a scoping review of the literature
Authors: Buonsenso Danilo , Cusenza Francesca , Passadore Lucrezia , Bonanno Francesca , Calanca Carolina , Rasmi Sonia , Mariani Francesco , Esposito Susanna Maria Roberta
Published: November 2023

Background: Empyema (the presence of pus in the pleural space) is a severe complication of community-acquired pneumonia and significant cause of morbidity, but, fortunately, not mortality in children. Between 0.6 and 2% of pneumonias are complicated by empyema and the three main pathogens involved are Streptococcus pneumoniae, Staphylococcus aureus and group A Streptococcus 1,2,3,4. Optimal management in children, especially the choice of antibiotics, method of administration and duration of therapy, are still matter of debate and currently, lack of strong specific recommendations. This paper displays the study protocol for a scoping review that aims to summarize the available literature on the microbiological epidemiology, the treatment options, and the outcomes of pleural empyema in pediatric population.

Methods: Comprehensive research combining the terms pediatric (children aged 0 to 18 years) and pleural empyema will be performed on PubMed and SCOPUS to identify all eligible studies. At first, two reviewers will screen their abstract and then their full text to detecting the articles that meet the inclusion criteria. This work will be carried out independently, everyone on a different Excel spreadsheet and each researcher will be blinded to the decision of the other researcher. When the process will be completed, in case of discordance, any disagreement will be identified and resolved through discussion or with the help, when needed, of a third author.

Dissemination: The findings of this review will be published in a peer-reviewed journal.
Research on emotional intelligence among Indian teachers: A Systematic Review and meta-analysis of its correlation with health parameters and impact of gender
Authors: Pandey Mamta , Sharma Deepti
Published: November 2023

Background Emotional intelligence is the self-perception related to identification and regulation of emotions. Several studies have been done among Indian teachers evaluating emotional intelligence in relation to demographic, professional and various psychological parameters, but the variety of scales, teacher types, and conflicting results makes it difficult to draw any meaningful conclusions from this heterogeneous data. The present work aims to synthesize the available data by both qualitative and quantitative analysis and is the first such attempt to include only Indian studies in this field. The main objectives were to determine the correlation of emotional intelligence with teachers’ health parameters and to study the gender difference in emotional intelligence. Methods After a thorough literature search in Google, Google scholar, Scopus, Web of science and Pubmed, fifty-five Indian studies were selected which empirically examined teachers’ emotional intelligence, either alone or in association with another parameter evaluating teachers’ psychological health and performance. After qualitative assessment of major findings, quantitative analysis was performed. Three separate meta-analysis were carried out. The first one with fifteen effect sizes among 3291 participants evaluated correlation with personal health parameters. The second with nineteen effect sizes in 4165 participants evaluated correlation with professional health parameters. The third with twenty-six studies involving 6005 participants assessed effect of gender. Results The results show that almost all studies have used a trait measure, teachers’ emotional intelligence is positively correlated with both personal and professional health parameters and gender has no effect on emotional intelligence. Conclusion Major limitations are a very high degree of heterogeneity of the data, incomplete description of the scales, inadequate randomization and small sample sizes in many studies. The results indicate the importance of emotional intelligence in both personal and professional life of teachers and no effect of gender preparing a solid base for future research.
Digital twins for land-based aquaculture: A case study for rainbow trout (Oncorhynchus mykiss)
Authors: Lima Adriano C. , Royer Edouard , Bolzonella Matteo , Pastres Roberto
Published: November 2023

The virtual, digital counterpart of a physical object, referred as digital twin, derives from the Internet of Things (IoT), and involves real-time acquisition and processing of large data sets. A fully implemented system ultimately enables real-time and remote management, as well as the reproduction of real and forecasted scenarios. Under the emerging framework of Precision Fish Farming, which brings control-engineering principles to fish production, we set up digital twin prototypes for land-based finfish farms. The digital twin is aimed at supporting producers in optimizing feeding practices, oxygen supply and fish population management with respect to 1) fish growth performances; 2) fish welfare, and 3) environmental loads. It relies on integrated mathematical models which are fed with data from in-situ sensors and from external sources, and simulate several dynamic processes, allowing the estimation of key parameters describing the ambient environment and the fishes. A conceptual application targeted at rearing cycles of rainbow trout (Oncorhynchus mykiss) in an operational in-land aquafarm in Italy is presented. The digital twin takes into account the disparate levels of automation and control that are found within this farm, and considerations are made on preferential directions for future developments. In spite of its potential, and not only in the aquaculture sector, the development of digital twins is still at its early stage. Furthermore, Precision Fish Farming applications in land-based systems as well as targeted at rainbow trout are novel developments.
Bayesian Network Models for PTSD Screening in Veterans
Authors: Tan Yi , Shenoy Prakash P. , Sherwood Ben , Shenoy Catherine , Gaddy Melinda , Oehlert Mary E.
Published: November 2023

The prediction of posttraumatic stress disorder (PTSD) has gained a lot of interest in clinical studies. Identifying patients with a high risk of PTSD can guide mental healthcare workers when making treatment decisions. The main goal of this paper is to propose several Bayesian network (BN) models to assess the probability that a veteran has PTSD when first visiting a U.S. Department of Veteran Affairs (VA) facility seeking medical care. The current practice is to use a five-question test called PC-PTSD-5. We aim to use the PC-PTSD-5 test, which is currently administered to most incoming new patients, and demographic information, military service history, and medical history. We construct a Bayes information criterion score-based BN, a group L2-regularized BN (GL2-regularized BN), and a naïve Bayes BN to assess the probability that a patient has PTSD. The GL2-regularized BN is a new method for constructing a BN motivated by some of the challenges of analyzing this data set. A secondary goal is to identify which features are important in predicting PTSD. We discover that the following features help compute the probability of PTSD: PC-PTSD-5, service-connected flag, combat flag, agent orange flag, military sexual trauma flag, traumatic brain injury, and age.

History: Accepted by Ram Ramesh, Area Editor for Data Science & Machine Learning.

Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplemental Information ( https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2021.0174 ) as well as from the IJOC GitHub software repository ( https://github.com/INFORMSJoC/2021.0174 ). The complete IJOC Software and Data Repository is available at https://informsjoc.github.io/ .
Platform Loophole Exploitation, Recovery Measures, and User Engagement: A Quasi-Natural Experiment in Online Gaming
Authors: Chen Jianqing , He Shu , Yang Xue
Published: November 2023

Online platforms often encounter the challenge of system vulnerabilities, such as bugs, which can be exploited by certain users for illicit gains. These platforms face a dilemma when devising countermeasures, particularly in deciding whether to penalize rule breakers. Different countermeasures can lead to varying economic impacts, including subsequent user engagement. In this study, based on unique field data from a prominent online gaming platform, we discovered that the occurrence of bugs has a negative effect on the online duration and consumption of observing players. Surprisingly, although the platform is responsible for the bugs, not penalizing rule breakers results in more substantial reductions in platform engagement among observing players compared with penalizing them. This effect is particularly pronounced for observers who are directly affected by rule violations. Our findings emphasize the essential role of the platform in fairly punishing rule breakers. To ensure the long-term prosperity of an online platform and the overall welfare of its participants, it is crucial for the platform to maintain high-quality system control and implement effective governance mechanisms for rule enforcement, thereby restoring justice and order to the online community.
Phase space analysis of two-wavelength interferometry
Authors: Leonard Robert H. , Olson Spencer E.
Published: November 2023

Multiple wavelength phase shifting interferometry is widely used to
extend the unambiguous range (UR) beyond that of a single wavelength.
Towards this end, many algorithms have been developed to calculate the
optical path difference (OPD) from the phase measurements of multiple
wavelengths. These algorithms fail when phase error exceeds a specific
threshold. In this paper, we examine this failure condition. We
introduce a “phase-space” view of multi-wavelength algorithms and
demonstrate how this view may be used to understand an algorithm’s
robustness to phase measurement error. In particular, we show that the
robustness of the synthetic wavelength algorithm deteriorates near the
edges of its UR. We show that the robustness of de Groot’s extended
range algorithm [Appl. Opt. 33, 5948
(1994)APOPAI0003-693510.1364/AO.33.005948] depends on both
wavelength and OPD in a non-trivial manner. Further, we demonstrate
that the algorithm developed by Houairi and Cassaing (HC)
[J. Opt. Soc. Am.
A 26, 2503
(2009)JOAOD60740-323210.1364/JOSAA.26.002503] results in uniform
robustness across the entire UR. Finally, we explore the effect that
wavelength error has on the robustness of the HC algorithm.
Evolution of coherence singularities in polarization singular beams
Authors: Joshi Stuti , Khan Saba N. , Senthilkumaran P.
Published: November 2023

The evolution of correlation singularities in partially coherent polarization singular beams (PC-PSBs) is investigated. Since PSBs are the superposition of two orthogonally polarized vortex beams, the occurrence of coherence singularities in PC-PSBs is strongly governed by the topological charge of the component vortex beams and the spatial coherence length. Coherence singularities appear in the form of ring dislocations in the modulus of the spectral degree of coherence (SDoC) profile, and the number of ring dislocations is equal to the higher value of the topological charge of the superposing vortex beam. Furthermore, the SDoC phase profile can be used to determine the polarity of a PC-PSB. The findings of the study could be valuable in various applications that rely on the spatial coherence of beams, such as free-space communication and imaging.
One step accurate phase demodulation from a closed fringe pattern with the convolutional neural network HRUnet
Authors: Guo Rongli , Lu Shuaidong , Zhang Miaomiao , Li Zhaoxin , Li Dangjuan , Wang Fan , Hu XiaoYing , Wu Shenjiang
Published: November 2023

Retrieving a phase map from a single closed fringe pattern is a challenging task in optical interferometry. In this paper, a convolutional neural network (CNN), HRUnet, is proposed to demodulate phase from a closed fringe pattern. The HRUnet, derived from the Unet model, adopts a high resolution network (HRnet) module to extract high resolution feature maps of the data and employs residual blocks to erase the gradient vanishing in the network. With the trained network, the unwrapped phase map can be directly obtained by feeding a scaled fringe pattern. The high accuracy of the phase map obtained from HRUnet is demonstrated by demodulation of both simulated data and actual fringe patterns. Compared results between HRUnet and two other CNNS are also provided, and the results proved that the performance of HRUnet in accuracy is superior to the two other counterparts.
Fano-resonance-based plasmonic refractive index sensor with high sensitivity for detection of urea
Authors: Yadav Gaurav Kumar , Metya Sanjeev Kumar
Published: November 2023

In the recent context of the post-pandemic world, label-free detection has become a crucial technique in various human physiological testing analyses. In this paper, a plasmonic nanosensor is proposed based on a tapered waveguide cavity resonator, which provides label-free detection with high sensitivity for bio-sensing applications. The transmittance curve is studied using the finite difference time domain method. The transmittance curve exhibits dual Fano resonances with the highest sensitivity of 2544.3 nm/RIU. The resultant simulated transmittance values are further validated by comparing them to the theoretical Fano line shape function. Further, the fabrication complexities have been investigated with respect to changes in geometrical parameters such as the change in width of the tapered waveguide and the height of the cavity resonators. Other performance parameters are also calculated such as FOM, Q factor, and detection limit, which come out at values of 40.54RIU−1, 41.7, and 0.024, respectively. Moreover, a biosensing application has been investigated by testing the detection of urea in a human urine sample.
Geometric analysis algorithm based on a neural network with localized simulation data for nano-grating structure using Mueller matrix spectroscopic ellipsometry
Authors: Jung Juwon , Kim Kibaek , Choi Junho , Kim NaGyeong , Chegal Won , Cho Yong Jai , Kim Young-Joo
Published: November 2023

Mueller matrix spectroscopic ellipsometry (MMSE) is a nondestructive tool for nanostructure analysis, and recently the enhanced computational power, combining neural networks and simulation data, enhance its analysis ability on more complex geometries. This study introduces a deep learning method to realize fast and accurate analysis; predicting nanostructure parameters by pairing Mueller matrices with relatively limited library data and then applying neural network algorithm. Thus, it was realized to predict the width and height of 1D grating structure with an accuracy of MAE below 0.1 nm through the proposed two-step prediction algorithm. Finally, experimental validation on SiO2 grating of 38 nm width and 100 nm height showed a good agreement in the dimensions with reasonable range compared to those measured by scanning electron microscopy.
Live imaging of laser machining via plasma deep learning
Authors: Grant-Jacob James A. , Mills Ben , Zervas Michalis N.
Published: November 2023

Real-time imaging of laser materials processing can be challenging as the laser generated plasma can prevent direct observation of the sample. However, the spatial structure of the generated plasma is strongly dependent on the surface profile of the sample, and therefore can be interrogated to indirectly provide an image of the sample. In this study, we demonstrate that deep learning can be used to predict the appearance of the surface of silicon before and after the laser pulse, in real-time, when being machined by single femtosecond pulses, directly from camera images of the generated plasma. This demonstration has immediate impact for real-time feedback and monitoring of laser materials processing where direct observation of the sample is not possible.
Unveiling the evolution of light within photonic integrated circuits
Authors: Iluz Matan , Cohen Kobi , Kheireddine Jacob , Hazan Yoav , Rosenthal Amir , Tsesses Shai , Bartal Guy
Published: November 2023

Silicon photonics leverages mature semiconductor technology to produce cost-effective and high-performance components for various applications in data centers, artificial intelligence, and quantum computing. While the geometry of photonic integrated circuits can be characterized by existing means, their optimal and accurate performance requires detailed characterization of the light propagating within them. Here we demonstrate the first, to our knowledge, direct visualization of the light as it travels inside photonic integrated circuits. We employ the natural nonlinear optical properties of silicon to directly map the electric field of the waves guided inside the integrated circuits, characterizing waveguides and multimode splitters while extracting various parameters of the device—all in real-time and in a noninvasive manner. Our approach for visualizing light inside photonic circuits is the only solution directly providing such information without any overhead or penalty, potentially making it a crucial component for the characterization of photonic circuitry, toward their improved design, fabrication, and optimization.
External dihedral-angle error measurement based on Differential Wavefront Sensing
Authors: Ren Xiaofang , Yan Hao
Published: November 2023

High-precision making of cube blocks such as cube test mass, corner cube retroreflectors, and right-angle prisms faces the problem of measuring the dihedral-angle error. A new method based on optical differential wavefront sensing for external measurement of dihedral-angle error is proposed in this paper. Compared to conventional methods such as the Fizeau interferometer and autocollimation, this method has the advantages of compactness and high precision. Moreover, it can measure both arbitrary internal and external dihedral angles. A quasi-monolithic compact interferometer bench for dihedral-angle error measurement is built and tested. The experimental results show that a resolution of ± 0.15 μrad and a nonlinear residual below ± 3 μrad within a dynamic range of ± 100 μrad has been achieved.
Correlations for subsets of particles in symmetric states: what photons are doing within a beam of light when the rest are ignored
Authors: Goldberg Aaron Z.
Published: November 2023

Given a state of light, how do its properties change when only some of the constituent photons are observed and the rest are neglected (traced out)? By developing formulas for mode-agnostic removal of photons from a beam, we show how the expectation value of any operator changes when only q photons are inspected from a beam, ignoring the rest. We use this to re-express expectation values of operators in terms of the state obtained by randomly selecting q photons. Remarkably, this only equals the true expectation value for a unique value of q: expressing the operator as a monomial in normally ordered form, q must be equal to the number of photons annihilated by the operator. A useful corollary is that the coefficients of any q-photon state chosen at random from an arbitrary state are exactly the qth-order correlations of the original state; one can inspect the intensity moments to learn what any random photon will be doing and, conversely, one need only look at the n-photon subspace to discern what all of the nth-order correlation functions are. The astute reader will be pleased to find no surprises here, only mathematical justification for intuition. Our results hold for any completely symmetric state of any type of particle with any combination of numbers of particles and can be used wherever bosonic correlations are found.
Contributions to the optical linewidth of shallow donor-bound excitonic transition in ZnO
Authors: Niaouris Vasileios , D’Ambrosia Samuel H. , Zimmermann Christian , Wang Xingyi , Hansen Ethan R. , Titze Michael , Bielejec Edward S. , Fu Kai-Mei C.
Published: November 2023

Neutral shallow donors in zinc oxide (ZnO) are spin qubits with optical access via the donor-bound exciton. This spin–photon interface enables applications in quantum networking, memories, and transduction. Essential optical parameters which impact the spin–photon interface include radiative lifetime, optical inhomogeneous and homogeneous linewidth, and optical depth. We study the donor-bound exciton optical linewidth properties of Al, Ga, and In donors in single-crystal ZnO. The ensemble photoluminescence linewidth ranges from 4 to 11 GHz, less than two orders of magnitude larger than the expected lifetime-limited linewidth. The ensemble linewidth remains narrow in absorption through samples with an estimated optical depth up to several hundred. The primary thermal relaxation mechanism is identified and found to have a negligible contribution to the total linewidth at 2 K. We find that inhomogeneous broadening due to the disordered isotopic environment in natural ZnO is significant, contributing 2 GHz. Two-laser spectral hole burning measurements indicate that the dominant mechanism, however, is homogeneous. Despite this broadening, the high homogeneity, large optical depth, and potential for isotope purification indicate that the optical properties of the ZnO donor-bound exciton are promising for a wide range of quantum technologies, and motivate a need to improve the isotope and chemical purity of ZnO for quantum technologies.
Reflective ultrathin light-sheet microscopy with isotropic 3D resolutions
Authors: Wang Yue , Dong Dashan , Yang Wenkai , He Renxi , Lei Ming , Shi Kebin
Published: November 2023

Light-sheet fluorescence microscopy (LSFM) has played an important role in bio-imaging due to its advantages of high photon efficiency, fast speed, and long-term imaging capabilities. The perpendicular layout between LSFM excitation and detection often limits the 3D resolutions as well as their isotropy. Here, we report on a reflective type light-sheet microscope with a mini-prism used as an optical path reflector. The conventional high NA objectives can be used both in excitation and detection with this design. Isotropic resolutions in 3D down to 300 nm could be achieved without deconvolution. The proposed method also enables easy transform of a conventional fluorescence microscope to high performance light-sheet microscopy.
Cultural adaptation and psychometric evaluation of Childbirth Experience Questionnaire 2 in Karnataka state, India
Authors: Jha Paridhi , Jha Vikas Kumar , Sharma Bharati , Jha Ajeya , Erlandsson Kerstin , Bogren Malin
Published: November 2023

Background

Women’s birthing experience is a sensitive indicator of the quality of childbirth care and can impact the physical and mental health of both women and their neonates. Negligible evidence exists on Indian women’s birth experiences and–to the best of authors’ knowledge–no questionnaire has been tested in India for measuring women’s birthing experiences. This study aimed to test the construct validity and reliability of theKannada-translated Revised Childbirth Experience Questionnaire.

Methodology

A cross-sectional survey was carried out among postnatal women (n = 251, up to six months postpartum, with a live healthy neonate) who had given birth at a public or private health facility using the Kannada-translated CEQ2 in two districts of Karnataka. Data were collected at participants’ homes after seeking written informed consent. Model fit was determined by Confirmatory Factor Analyses.

Results

The 4-factor model of the CEQ2 showed good fit after deletion of one item (item 8, subcategory “participation”) with CMIN = 1.33; SRMR = 0.04; GFI = 0.92, CFI = 0.98, TLI = 0.99, RMSEA = 0.037 and p value 0.002). The Cronbach alpha values were acceptable for the four subscales (0.92, 0.93, 0.97, 0.91) as well as for the overall 21-item scale (0.84).

Conclusions

TheKannada-translated CEQ2 is a reliable tool to measure the childbirth experiences amongKannada-speaking women and can serve as a reliable ongoing evaluation of women’s birth experiences.
Does women empowerment associate with reduced risks of intimate partner violence in India? evidence from National Family Health Survey-5
Authors: Ghoshal Rakhi , Patil Priti , Gadgil Anita , Nathani Priyansh , Bhandarkar Prashant , Kale Dnyaneshwar B. , Roy Nobhojit
Published: November 2023

Background

Women empowerment is commonly believed to be an important factor affecting a woman’s likelihood of facing violence from her intimate partner. Even as countries invest in policies that aim to strengthen women empowerment, studies show that increase in women empowerment does not necessarily decrease intimate partner violence (IPV) against them. Against this paradox, the present study seeks to understand the specific empowerment components that associate with IPV against women in India. It also studies the state-level distribution of the different types of IPV.

Methods

The study analyses state-level data from the National Family Health Survey, India (2019–21). A total of 72,056 women responded to the domestic violence questionnaire. The Dimension Index (DI) was used to compute composite scores for Women Empowerment and for IPV to rank states and Union Territories. The correlation between Women Empowerment and IPV scores was determined using Spearman’s rank correlation coefficient.

Results

The state of Karnataka had the highest composite score of IPV and also showed the highest burdens of physical, sexual and emotional IPV, while Lakshadweep had the lowest burden. Physical IPV was the most common form of IPV for most states across the country. The states in the western part of India had reduced burdens for all three types of IPV. Three specific components of empowerment, viz. household decision-making and mobile phone ownership significantly associated with reduction of all three types of IPV. Hygienic menstrual practices strongly associated with reduction of sexual and emotional IPV. However, property ownership of women increased risks of all three types of IPV, while employment had no significant association with any type of IPV.

Conclusions

The study found no significant reduction in overall IPV with improvement in women empowerment. However, it identifies components of empowerment that associate with IPV. Household decision-making, ownership of mobile phones, and hygienic menstrual practices associated with a lowered risk. By contrast, owning property increased the risk. The findings of this study would inform future research and intervention that aim to strengthen specific components of women empowerment in India and other low-and-middle-income countries.
Burden of undiagnosed hypertension and its associated factors: A challenge for primary health care in urban Colombia
Authors: Salazar Flórez Jorge Emilio , Echeverri Rendón Ángela Patricia , Giraldo Cardona Luz Stella
Published: November 2023

Background

Arterial hypertension is one of the most prevalent chronic, non-communicable diseases and the leading preventable risk factor for cardiovascular disease (CVD) and all-cause mortality worldwide. Although its primary causes and consequences are preventable, it often remains undiagnosed. Consequently, this study aims to determine the prevalence and factors associated with normotensive, diagnosed, and undiagnosed hypertension in adults.

Methods

A cross-sectional, population-based study was conducted in Sabaneta, Colombia, between 2021 and 2022, with 286 adults aged 18 and older. Stratified and systematic random sampling methods were employed. The World Health Organization STEP survey and the Perez Rojas test were utilized to assess behavioral risk factors and sedentary lifestyles. Body mass index, waist circumference, and arterial tension were measured using standardized instruments. The prevalence of hypertension was then estimated. Risk factors influencing normotensive, diagnosed, and undiagnosed hypertension were analyzed using multinomial regression. The outcome variable comprised three categories: normotensive (reference category), diagnosed hypertension, and undiagnosed hypertension. The multinomial regression coefficients were exponentiated and are presented as relative risk ratios (RRR) with 95% confidence intervals (CI). The model was adjusted for sex and sample weight per neighborhood.

Results

The study revealed a hypertension prevalence of 38.5% and an undiagnosed hypertension rate of 50.9%. Those with undiagnosed hypertension were predominantly adults over 60 years (RRR = 0.68; 95% CI: 0.53–0.86), individuals with an elementary school education (RRR = 1.75; 95% CI: 1.27–2.42), those physically active (RRR = 1.52; 95% CI: 1.22–1.89), without prior diagnoses of chronic comorbidities (RRR = 1.42; 95% CI: 1.12–1.82), and with obesity (RRR = 2.25; 95% CI: 1.63–3.11) or overweight conditions (RRR = 1.70; 95% CI: 1.334–2.15).

Conclusions

Undiagnosed hypertension was significant among populations without risk conditions. There is an urgent need for community-based early detection and education strategies to mitigate this issue.