bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ultra-compact all-optical plasmonic switch for three telecommunication windows using a nonlinear Kerr material and Fano resonance
Authors: Pooretemad Siavash , Pav Mohammadreza , Ghattan Kashani Zahra , Granpayeh Nosrat 
Published: March 2023

In this study, an all-optical plasmonic switch based on a metal–insulator–metal (MIM) waveguide coupled to two rectangular cavities that are perpendicularly connected to each other through a vertical stub is proposed and analyzed both theoretically and numerically. Rectangular cavities are filled with a nonlinear Kerr material, and the switching operation is achieved by applying a high-intensity pump input into the MIM waveguide to obtain nonlinear cross-phase modulation (XPM) effect. The proposed structure is designed so that it can realize the switching operation at each of the three telecommunication windows of 850, 1310, and 1550 nm. Realizing the switching operation at these three wavelength bands is accomplished by the Fano resonance. In fact, the Fano resonance is utilized to create a band-stop area that is crucial for building a suitable OFF state for the switching operation at two of the three telecommunication windows of 1310 and 1550 nm. The theoretical and numerical results are obtained using the transmission-line model (TLM) and the finite difference time domain (FDTD) method, respectively, the results of which comply well. The proposed ultra-compact all-optical switch has significant applications in photonic integrated circuits (PICs).
A new model for predicting the outcome and effectiveness of drug therapy in patients with severe fever with thrombocytopenia syndrome: A multicenter Chinese study
Authors: Xia Guomei , Sun Shanshan , Zhou Shijun , Li Lei , Li Xu , Zou Guizhou , Huang Cheng , Li Jun , Zhang Zhenhua 
Published: March 2023

Background
There are a few models for predicting the outcomes of patients with severe fever with thrombocytopenia syndrome (SFTS) based on single-center data, but clinicians need more reliable models based on multicenter data to predict the clinical outcomes and effectiveness of drug therapy.

Methodology/Principal findings
This retrospective multicenter study analyzed data from 377 patients with SFTS, including a modeling group and a validation group. In the modeling group, the presence of neurologic symptoms was a strong predictor of mortality (odds ratio: 168). Based on neurologic symptoms and the joint indices score, which included age, gastrointestinal bleeding, and the SFTS virus viral load, patients were divided into double-positive, single-positive, and double-negative groups, which had mortality rates of 79.3%, 6.8%, and 0%, respectively. Validation using data on 216 cases from two other hospitals yielded similar results. A subgroup analysis revealed that ribavirin had a significant effect on mortality in the single-positive group (P = 0.006), but not in the double-positive or double-negative group. In the single-positive group, prompt antibiotic use was associated with reduced mortality (7.2% vs 47.4%, P < 0.001), even in individuals without significant granulocytopenia and infection, and early prophylaxis was associated with reduced mortality (9.0% vs. 22.8%, P = 0.008). The infected group included SFTS patients with pneumonia or sepsis, while the noninfected group included patients with no signs of infection. The white blood cell count and levels of C-reactive protein and procalcitonin differed significantly between the infection and non-infection groups (P = 0.020, P = 0.011, and P = 0.003, respectively), although the absolute difference in the medians were small.

Conclusions/Significance
We developed a simple model to predict mortality in patients with SFTS. Our model may help to evaluate the effectiveness of drugs in these patients. In patients with severe SFTS, ribavirin and antibiotics may reduce mortality.
Long COVID—six months of prospective follow-up of changes in symptom profiles of non-hospitalised children and young people after SARS-CoV-2 testing: A national matched cohort study (The CLoCk) study
Authors: Stephenson Terence , Pinto Pereira Snehal M. , Nugawela Manjula D. , McOwat Kelsey , Simmons Ruth , Chalder Trudie , Ford Tamsin , Heyman Isobel , Swann Olivia V. , Fox-Smith Lana , Rojas Natalia K. , Dalrymple Emma , Ladhani Shamez N. , Shafran Roz ,   on behalf of the CLoCk Consortium
Published: March 2023

Background
Little is known about the prevalence and natural trajectory of post-COVID symptoms in young people, despite very high numbers of young people having acute COVID. To date, there has been no prospective follow-up to establish the pattern of symptoms over a 6-month time period.

Methods
A non-hospitalised, national sample of 3,395 (1,737 SARS-COV-2 Negative;1,658 SARS-COV-2 Positive at baseline) children and young people (CYP) aged 11–17 completed questionnaires 3 and 6 months after PCR-confirmed SARS-CoV-2 infection between January and March 2021 and were compared with age, sex and geographically-matched test-negative CYP.

Results
Three months after a positive SARS-CoV-2 PCR test, 11 of the 21 most common symptoms reported by >10% of CYP had reduced. There was a further decline at 6 months. By 3 and 6 months the prevalence of chills, fever, myalgia, cough and sore throat of CYP who tested positive for SARS-CoV-2 reduced from 10–25% at testing to <3%. The prevalence of loss of smell declined from 21% to 5% at 3 months and 4% at 6 months. Prevalence of shortness of breath and tiredness also declined, but at a lower rate. Among test-negatives, the same common symptoms and trends were observed at lower prevalence’s. Importantly, in some instances (shortness of breath, tiredness) the overall prevalence of specific individual symptoms at 3 and 6 months was higher than at PCR-testing because these symptoms were reported in new cohorts of CYP who had not reported the specific individual symptom previously.

Conclusions
In CYP, the prevalence of specific symptoms reported at time of PCR-testing declined with time. Similar patterns were observed among test-positives and test-negatives and new symptoms were reported six months post-test for both groups suggesting that symptoms are unlikely to exclusively be a specific consequence of SARS-COV-2 infection. Many CYP experienced unwanted symptoms that warrant investigation and potential intervention.
Development and external validation of machine learning algorithms for postnatal gestational age estimation using clinical data and metabolomic markers
Authors: Hawken Steven , Ducharme Robin , Murphy Malia S. Q. , Olibris Brieanne , Bota A. Brianne , Wilson Lindsay A. , Cheng Wei , Little Julian , Potter Beth K. , Denize Kathryn M. , Lamoureux Monica , Henderson Matthew , Rittenhouse Katelyn J. , Price Joan T. , Mwape Humphrey , Vwalika Bellington , Musonda Patrick , Pervin Jesmin , Chowdhury A. K. Azad , Rahman Anisur , Chakraborty Pranesh , Stringer Jeffrey S. A. , Wilson Kumanan 
Published: March 2023

Background
Accurate estimates of gestational age (GA) at birth are important for preterm birth surveillance but can be challenging to obtain in low income countries. Our objective was to develop machine learning models to accurately estimate GA shortly after birth using clinical and metabolomic data.

Methods
We derived three GA estimation models using ELASTIC NET multivariable linear regression using metabolomic markers from heel-prick blood samples and clinical data from a retrospective cohort of newborns from Ontario, Canada. We conducted internal model validation in an independent cohort of Ontario newborns, and external validation in heel prick and cord blood sample data collected from newborns from prospective birth cohorts in Lusaka, Zambia and Matlab, Bangladesh. Model performance was measured by comparing model-derived estimates of GA to reference estimates from early pregnancy ultrasound.

Results
Samples were collected from 311 newborns from Zambia and 1176 from Bangladesh. The best-performing model accurately estimated GA within about 6 days of ultrasound estimates in both cohorts when applied to heel prick data (MAE 0.79 weeks (95% CI 0.69, 0.90) for Zambia; 0.81 weeks (0.75, 0.86) for Bangladesh), and within about 7 days when applied to cord blood data (1.02 weeks (0.90, 1.15) for Zambia; 0.95 weeks (0.90, 0.99) for Bangladesh).

Conclusions
Algorithms developed in Canada provided accurate estimates of GA when applied to external cohorts from Zambia and Bangladesh. Model performance was superior in heel prick data as compared to cord blood data.
Association of the rs2111234, rs3135499, rs8057341 polymorphisms in the NOD2 gene with leprosy: A case-control study in the Norte de Santander, Colombia population
Authors: Bustos Mónica Alexandra , Castañeda-Castañeda Luz Dary , Acosta Carmen Rosa , García Diana , Bohada Diana Patricia , Rodríguez Raúl , Guerrero Martha Inírida 
Published: March 2023

Background
Leprosy is a chronic infectious disease caused by Mycobacterium leprae. The development of leprosy involves several factors, including the causative agent, the individual host’s immune response, environmental factors, and the genetic background of the host. Specifically, the host’s innate immune response, encoded by genes, determines their susceptibility to developing leprosy post-infection. Polymorphic variants in the nucleotide-binding oligomerization domain 2 (NOD2) gene are associated with leprosy among populations in a variety of endemic areas around the world. Colombia, a country located in the tropical zone, has several leprosy-endemic regions, including Norte de Santander. The aim of this study was to analyze the rs7194886, rs2111234, rs3135499, and rs8057341 single nucleotide polymorphisms (SNPs) in the NOD2 gene using a case-control study to determine whether they confer greater or lesser susceptibility to the development of leprosy.

Methodology
The TaqMan qPCR amplification system was used for SNPs detection.

Findings
An association between the A-rs8057341 SNP (p = 0,006286) and resistance to leprosy was found. However, the rs3135499 (p = 0,9063) and rs2111234 (p = 0.1492) were not found to be associated with leprosy susceptibility. In addition, the rs7194886 SNP was not found to be in Hardy-Weinberg equilibrium (HWE) in the study population. The GAG haplotype, consisting of SNPs rs2111234-G, rs3135499-A, and rs8057341G, acts as a susceptibility factor for the development of leprosy in women. SNPs rs3135499 and rs8057341 are functionally related to decreased NOD2 expression according to an in-silico analysis.

Conclusions
The SNPs rs8057341-A was related with resistance to leprosy and the haplotype rs2111234-G, rs3135499-A and rs8057341-G SNPs was related with susceptibility in the Norte de Santander Colombia, studied population.
Associations between mortality from COVID-19 and other causes: A state-level analysis
Authors: Luck Anneliese N. , Stokes Andrew C. , Hempstead Katherine , Paglino Eugenio , Preston Samuel H. 
Published: March 2023

BackgroundDuring the COVID-19 pandemic, the high death toll from COVID-19 was accompanied by a rise in mortality from other causes of death. The objective of this study was to identify the relationship between mortality from COVID-19 and changes in mortality from specific causes of death by exploiting spatial variation in these relationships across US states.MethodsWe use cause-specific mortality data from CDC Wonder and population estimates from the US Census Bureau to examine relationships at the state level between mortality from COVID-19 and changes in mortality from other causes of death. We calculate age-standardized death rates (ASDR) for three age groups, nine underlying causes of death, and all 50 states and the District of Columbia between the first full year of the pandemic (March 2020-February 2021) and the year prior (March 2019-February 2020). We then estimate the relationship between changes in cause-specific ASDR and COVID-19 ASDR using linear regression analysis weighted by the size of the state’s population.ResultsWe estimate that causes of death other than COVID-19 represent 19.6% of the total mortality burden associated with COVID-19 during the first year of the COVID-19 pandemic. At ages 25+, circulatory disease accounted for 51.3% of this burden while dementia (16.4%), other respiratory diseases (12.4%), influenza/pneumonia (8.7%) and diabetes (8.6%) also contribute. In contrast, there was an inverse association across states between COVID-19 death rates and changes in death rates from cancer. We found no state-level association between COVID-19 mortality and rising mortality from external causes.ConclusionsStates with unusually high death rates from COVID-19 experienced an even larger mortality burden than implied by those rates alone. Circulatory disease served as the most important route through which COVID-19 mortality affected death rates from other causes of death. Dementia and other respiratory diseases made the second and third largest contributions. In contrast, mortality from neoplasms tended to decline in states with the highest death rates from COVID-19. Such information may help to inform state-level responses aimed at easing the full mortality burden of the COVID-19 pandemic.
Improving provider-initiated testing for HIV and other STI in the primary care setting in Amsterdam, the Netherlands: Results from a multifaceted, educational intervention programme
Authors: Bogers Saskia , Schim van der Loeff Maarten , Boyd Anders , van Dijk Nynke , Geerlings Suzanne , van Bergen Jan ,   on behalf of the HIV Transmission Elimination AMsterdam (H-TEAM) Consortium
Published: March 2023

Background
In the Netherlands, general practitioners (GPs) play a key role in HIV testing. However, the proportion of people diagnosed with late-stage HIV remains high, and opportunities for earlier diagnosis are being missed. We implemented an educational intervention to improve HIV and STI testing in primary care in Amsterdam, the Netherlands.

Methods
GPs were invited to participate in an educational program between 2015 and 2020, which included repeat sessions using audit and feedback and quality improvement plans. Data on HIV, chlamydia and gonorrhoea testing by GPs were collected from 2011 through 2020. The primary outcome was HIV testing frequency, which was compared between GPs before and after participation using Poisson regression. Secondary outcomes were chlamydia and gonorrhoea testing frequencies, and positive test proportions. Additional analyses stratified by patient sex and age were done.

Findings
GPs after participation performed 7% more HIV tests compared to GPs before participation (adjusted relative ratio [aRR] 1.07, 95%CI 1.04–1.09); there was no change in the proportion HIV positive tests (aRR 0.87, 95%CI 0.63–1.19). HIV testing increased most among patients who were female and ≤19 or 50–64 years old. After participation, HIV testing continued to increase (aRR 1.02 per quarter, 95%CI 1.01–1.02). Chlamydia testing by GPs after participation increased by 6% (aRR 1.06, 95%CI 1.05–1.08), while gonorrhoea testing decreased by 2% (aRR 0.98, 95%CI 0.97–0.99). We observed increases specifically in extragenital chlamydia and gonorrhoea testing.

Conclusions
The intervention was associated with a modest increase in HIV testing among GPs after participation, while the proportion positive HIV tests remained stable. Our results suggest that the intervention yielded a sustained effect.
Differences in infection and prevention of HIV and other sexually transmitted infections among older adults in Columbus, Ohio
Authors: Morgan Ethan , Dyar Christina , Feinstein Brian A. 
Published: March 2023

Introduction
In the United States, rates of sexually transmitted infections (STIs) have increased year after year for the past six consecutive years. Even so, the majority of research has focused on younger populations with little work examining infections and prevention methods among older adults.

Methods
Data come from the Columbus Health Aging Project (N = 794). This study was designed to assess several domains of health among adults aged 50 years and older in Columbus, Ohio with a particular focus on addressing disparities based on sexual and gender identity. Multivariable logistic regression models were used to examine the association between sociodemographic factors and risk of STI acquisition, HIV diagnosis, and several common prevention methods, adjusting for known confounders.

Results
Key results suggest that cisgender women, intersex individuals, and transgender women are less likely to use condoms relative to cisgender men. Meanwhile, white individuals were least likely to use condoms while bisexual individuals were most likely. Transgender women and those living with family/roommates were most likely to use PrEP/PEP relative to cisgender men and those living with a spouse or partner. Cisgender women, compared to cisgender men, were most likely to report not using any prevention method.

Conclusion
This study highlights the need for better research among older adults in order to ascertain how interventions may be targeted to specific populations. Future research should aim to educate individuals differently based on their specific needs rather than treating older adults as a homogenous population or ignoring their sexually active nature entirely.
Deep learning-based classification of adequate sonographic images for self-diagnosing deep vein thrombosis
Authors: Nakayama Yusuke , Sato Mitsuru , Okamoto Masashi , Kondo Yohan , Tamura Manami , Minagawa Yasuko , Uchiyama Mieko , Horii Yosuke 
Published: March 2023

Background
Pulmonary thromboembolism is a serious disease that often occurs in disaster victims evacuated to shelters. Deep vein thrombosis is the most common reason for pulmonary thromboembolism, and early prevention is important. Medical technicians often perform ultrasonography as part of mobile medical screenings of disaster victims but reaching all isolated and scattered shelters is difficult. Therefore, deep vein thrombosis medical screening methods that can be easily performed by anyone are needed. The purpose of this study was to develop a method to automatically identify cross-sectional images suitable for deep vein thrombosis diagnosis so disaster victims can self-assess their risk of deep vein thrombosis.

Methods
Ultrasonographic images of the popliteal vein were acquired in 20 subjects using stationary and portable ultrasound diagnostic equipment. Images were obtained by frame split from video. Images were classified as “Satisfactory,” “Moderately satisfactory,” and “Unsatisfactory” according to the level of popliteal vein visualization. Fine-tuning and classification were performed using ResNet101, a deep learning model.

Results
Acquiring images with portable ultrasound diagnostic equipment resulted in a classification accuracy of 0.76 and an area under the receiver operating characteristic curve of 0.89. Acquiring images with stationary ultrasound diagnostic equipment resulted in a classification accuracy of 0.73 and an area under the receiver operating characteristic curve of 0.88.

Conclusion
A method for automatically identifying appropriate diagnostic cross-sectional ultrasonographic images of the popliteal vein was developed. This elemental technology is sufficiently accurate to automatically self-assess the risk of deep vein thrombosis by disaster victims.
FastFlow: Accelerating Deep Learning Model Training with Smart Offloading of Input Data Pipeline
Authors: Um Taegeon , Oh Byungsoo , Seo Byeongchan , Kweun Minhyeok , Kim Goeun , Lee Woo-Yeon 
Published: March 2023

When training a deep learning (DL) model, input data are pre-processed on CPUs and transformed into tensors, which are then fed into GPUs for gradient computations of model training. Expensive GPUs must be fully utilized during training to accelerate the training speed. However, intensive CPU operations for input data preprocessing (input pipeline) often lead to CPU bottlenecks; correspondingly, various DL training jobs suffer from GPU under-utilization.
We propose FastFlow, a DL training system that automatically mitigates the CPU bottleneck by offloading (scaling out) input pipelines to remote CPUs. FastFlow carefully decides various offloading decisions based on performance metrics specific to applications and allocated resources, while leveraging both local and remote CPUs to prevent the inefficient use of remote resources and minimize the training time. FastFlow's smart offloading policy and mechanisms are seamlessly integrated with TensorFlow for users to enjoy the smart offloading features without modifying the main logic. Our evaluations on our private DL cloud with diverse workloads on various resource environments show that FastFlow improves the training throughput by 1 ~ 4.34X compared to TensorFlow without offloading, by 1 ~ 4.52X compared to TensorFlow with manual CPU offloading (tf.data.service), and by 0.63 ~ 2.06X compared to GPU offloading (DALI).
Molecular dynamics simulations of water-ethanol droplet on silicon surface
Authors: Biswas Rima 
Published: March 2023

Abstract
Molecular dynamics simulations are used to explore the wetting behavior of a water-ethanol droplet on the silicon surface. The effect of ethanol concentration on the wettability of a water-ethanol droplet on the silicon surface was analysed by calculation of contact angle. At 30% ethanol concentrations, the water contact angle was 50.7°, while at 50% ethanol concentrations, it was 36°. The results showed that the contact angle of a droplet on a silicon surface decreases with increasing ethanol concentrations. The formation of hydrogen bonds (HBs) between water-water molecules was 677 for the 30% ethanol system, while at 50% ethanol concentrations, it was 141. The number of hydrogen bonds between water molecules reduces as the ethanol concentrations rise. The HBs between water molecules and the silicon surface is seen to grow as the ethanol concentration rises. The overall potential energies of pure water, 7:3 water-ethanol, and 1:1 water-ethanol systems are −74.4, −96.16, and −158.59 kcal/mol, respectively. The contact angle and number density of water molecules on the surface of the silicon revealed that at different ethanol concentrations, more water molecules are distributed on the silicon surface.
Exploring relationships between physician stress, burnout, and diagnostic elements in clinician notes
Authors: Sullivan Erin E. , Khazen Maram , Arabadjis Sophia D. , Mirica Maria , Ramos Jason M. , Olson Andrew P.J. , Linzer Mark , Schiff Gordon D. 
Published: March 2023

Abstract

Objectives
To understand the relationship between stressful work environments and patient care by assessing work conditions, burnout, and elements of the diagnostic process.

Methods
Notes and transcripts of audiotaped encounters were assessed for verbal and written documentation related to psychosocial data, differential diagnosis, acknowledgement of uncertainty, and other diagnosis-relevant contextual elements using 5-point Likert scales in seven primary care physicians (PCPs) and 28 patients in urgent care settings. Encounter time spent vs time needed (time pressure) was collected from time stamps and clinician surveys. Study physicians completed surveys on stress, burnout, and work conditions using the Mini-Z survey.

Results
Physicians with high stress or burnout were less likely to record psychosocial information in transcripts and notes (psychosocial information noted in 0% of encounters in 4 high stress/burned-out physicians), whereas low stress physicians (n=3) recorded psychosocial information consistently in 67% of encounters. Burned-out physicians discussed a differential diagnosis in only 31% of encounters (low counts concentrated in two physicians) vs. in 73% of non-burned-out doctors’ encounters. Burned-out and non-burned-out doctors spent comparable amounts of time with patients (about 25 min).

Conclusions
Key diagnostic elements were seen less often in encounter transcripts and notes in burned-out urgent care physicians.