Miracle-dz/UniFAR-FTUs huggingface dataset:
Mode confinement in VCSEL-based photonic heterostructures

Summary form only given.Arrays of coupled vertical cavity surface emitting lasers (VCSELs) were previously shown to have a coherent photonic mode with high immunity against structural imperfections. In such periodic arrays the photonic mode stability depends on disorder in the position or size of the pixels, injection current, and boundary conditions. In the present work, we show that nonuniform VCSEL arrays with a properly designed variation in the lattice parameters can exhibit a new type of photonic confinement, namely confinement of the envelope function of the lattice modes. The resulting novel structures, that we term photonic heterostructures, confine photon modes much like semiconductor heterostructures that confine the envelope functions of charge carriers. The photonic heterostructures are fabricated in a similar way as other types of coupled arrays of VCSELs. They are based on GaAs/AlGaAs/InGaAs structures emitting through the substrate at 940-nm wavelength. Each photonic heterostructure consists of several rows of a lattice with larger, square pixels surrounded by a lattice of smaller pixels. The pixels are defined by covering their surface with gold acting as a reflection enhancing layer. The region between the pixels is covered with chromium.
Arbitrage in continuous complete markets

This paper introduces a benchmark approach for the modelling of continuous, complete financial markets, when an equivalent risk-neutral measure does not exist. This approach is based on the unique characterization of a benchmark portfolio, the growth optimal portfolio, which is obtained via a generalization of the mutual fund theorem. The discounted growth optimal portfolio with minimum variance drift is shown to follow a Bessel process of dimension four. Some form of arbitrage can be explicitly modelled by arbitrage amounts. Fair contingent claim prices are derived as conditional expectations under the real world probability measure. The Heath-Jarrow-Morton forward rate equation remains valid despite the absence of an equivalent risk neutral measure.
MCMC Sampling Statistical Method to Solve the Optimization

This paper designs a class of generalized density function and from which proposed a solution method for the multivariable nonlinear optimization problem based on MCMC statistical sampling. Theoretical analysis proved that the maximum statistic converge to the maximum point of probability density which establishing links between the optimization and MCMC sampling. This statistical computation algorithm demonstrates convergence property of maximum statistics in large samples and it is global search design to avoid on local optimal solution restrictions. The MCMC optimization algorithm has less iterate variables reserved so that the computing speed is relatively high. Finally, the MCMC sampling optimization algorithm is applied to solve TSP problem and compared with genetic algorithms.
Fractions of Particular Knots in Gaussian Random Polygons

Fractions of knotted polygons in Gaussian random polygon are numerically studied. Three dimensional random polygons with N steps are prepared by closed N -step Gaussian random walks. Let P K ( N ) denote the probability that an N -step Gaussian polygon has a knot type K . For prime knots (3 1 , 4 1 , 5 1 , 5 2 ) and composite knots (3 1 #3 1 , 3 1 #4 1 , 3 1 #3 1 #3 1 ), P K ( N )'s are evaluated in the range 30≤ N ≤2400. We confirm that a scaling formula gives nice fitting curves for the numerical data plots of P K ( N ) versus N for the different knot types.
The Lie algebra associated to the lower central series of a link group and Murasugi’s conjecture

The Chen-Milnor presentation can be used to determine the Lie Algebra associated to the lower central series of the fundamental group of a link in the 3-sphere S3 in many interesting cases. We use this fact to obtain new and simpler proofs of unpublished results of Maeda on a conjecture of Murasugi in the sharpened form of Massey and Traldi. STATEMENT OF RESULTS Let L be a link in S3 with m components and let G =7 1 (S3 -L) be the group of the link. Let F = F(m) be the free group on xl, . , xm and let Fn denote the nth term of the lower central series of F. By a result of Milnor (q) (q) [9, Theorem 4] there are, for each integer q > 1, elements w ,. , wm E F such that w (q+l) W(q) modulo F and such that G/G has the presentaq+1 q+l tion (XlI , xm: [xlw1 ]= [Xm,Wmq)]=l, F =1) where [x, y] = xy l xy. Moreover, for any q > 1, any one of the relators r(q) = [x, w(q)] is redundant. Let R(q) be the normal subgroup of F generated y rl S -rm (q) (q) Let 2 = ? (F) = Dq>l? iq(F) be the Lie algebra associated to the lower central series of F. If Xi is the image of xi in 2, then 2 is the free Lie algebra over Z on 4l . Xm Let g = 2(G) be the Lie algebra associated to the lower central series of G. If g(q) 2(F/R( )Fq+1) then g(q) EDI l 2q(F/R(q)Fq +). Hence g = /9i where 9 = sq>l 9iq with 9q = Ker(2q(F) q(F/R(q)Fq +)). The ideal 9i is in general very difficult to determine. However, generators for it can be given if the relators rq) satisfy a certain independence condition, which we now describe. Received by the editors December 5, 1989 and, in revised form, September 6, 1989; presented at the Canadian Mathematical Society Winter Meeting, Vancouver, BC, December 1987. 1980 Mathematics Subject Classification (1985 Revision). Primary 20F40, 57M25. Supported by Canada NSERC Grant A4344 and Quebec FCAC Grant 88-EQ-2489. (g) 1990 American Mathematical Society 0002-9939/90 $1.00 + $. 25 per page
Tomographic image reconstruction techniques for accurate spent fuel assembly verification

Non-proliferation and the security of nuclear materials are essential. The international atomic energy agency (IAEA) considers a tomographic image acquisition technique of spent fuel assemblies a promising technique to accurately verify the rod-by-rod spent fuel conditions stored in a water pool. Researchers at Yonsei University in Korea developed the bismuth germanate (BGO) scintillator-based Yonsei Single-photon Emission Computed Tomography (YSECT). Previous research validated the YSECT system experimentally to quickly evaluate the radioactivity distribution of test fuel rods in the Korea Institute of Nuclear Nonproliferation and Control (KINAC). Quick verification of the fuel assembly requires the development of a high-quality image reconstruction algorithm that enables image acquisition within a short time. This study examined various tomographic image reconstruction techniques to identify patterns of missing fuel rods accurately. Rotational projection image data sets were obtained for 15 patterns of test fuel rods for 900 seconds using the single-photon emission computed tomography (SPECT) system installed at KINAC. The projection images were acquired every 5° while four 64-channel detectors rotated 90°. The acquired images were reconstructed using the following methods: filtered back-projection, simultaneous iterative reconstruction technique, order-subset simultaneous algebraic reconstruction technique, maximum likelihood expectation maximization (MLEM), and Fast-Iterative Shrinkage-Thresholding algorithm (FISTA). Among the reconstruction algorithms used in this study, the image quality of MLEM showed the best performance, and the image contrast of FISTA showed the highest result. Therefore, the signal-to-noise ratio of the tomographic image was improved using the image reconstruction technique optimized for the YSECT system to verify the patterns of fuel rods. Hence, even for the low-quality measured data with the short-time scan of the SPECT system, this advanced technique is expected to show better discriminability of the patterns of fuel rods in the assembly.
A microfluidic platform with integrated arrays for immunologic assays for biological pathogen detection

The ability to integrate complete assays on a microfluidic chip helps to greatly simplify instrument requirements and allows the use of lab-on-a-chip technology in the field. A core application for such field-portable systems is the detection of pathogens in a CBRN scenario such as permanent monitoring of airborne pathogens, e.g. in subway stations or hospitals etc. An immunological assay was chosen as method for the pathogen identification. The conceptual approach was its realization as a lab-on-a-chip system, enabling an easy handling of the sample in an automated manner. The immunological detection takes place on an antibody array directly implemented in the microfluidic network. Different immobilization strategies will be presented showing the performance of the system. Central elements of the disposable microfluidic device like fluidic interface, turning valves, liquid introduction and waste storage, as well as the architecture of measurement and control fluidic network, will be introduced. Overall process times of about 30 minutes were achieved and assays for the detection of Francisella tularensis and Yersinia pestis are presented. An important feature of the integrated lab-on-a-chip approach is that all waste liquids remain on-chip and contamination risks can be avoided.
Sustainable tourism development strategy in West Nusa Tenggara province, Indonesia

This study analyzed sustainable tourism development and tourism strategies in West Nusa Tenggara (NTB) through their tourism office. The method used in this study was a qualitative description with the help of NVIVO 12 Plus software to analyze the West Nusa Tenggara government strategy. The results of this study are that the West Nusa Tenggara government’s plan for developing sustainable tourism is to increase attractions, accessibility, security, public facilities, and government intervention to develop tourism and realize sustainable tourism. The five variables have also supported the economy as seen from the gross domestic product increased by 4.6% in the second quarter of 2021 compared to the second quarter of 2020, fulfilled the social needs of the community and did not damage the environment and even exceeded the target as evidenced by the environmental index data for West Nusa Tenggara Province.
Long-term follow-up of colorectal cancer screening attendees identifies differences in Phascolarctobacterium spp. using 16S rRNA and metagenome sequencing

Background The microbiome has been implicated in the initiation and progression of colorectal cancer (CRC) in cross-sectional studies. However, there is a lack of studies using prospectively collected samples. Methods From the Norwegian Colorectal Cancer Prevention (NORCCAP) trial, we analyzed 144 archived fecal samples from participants who were diagnosed with CRC or high-risk adenoma (HRA) at screening and from participants who remained cancer-free during 17 years of follow-up. We performed 16S rRNA sequencing of all the samples and metagenome sequencing on a subset of 47 samples. Differences in taxonomy and gene content between outcome groups were assessed for alpha and beta diversity and differential abundance. Results Diversity and composition analyses showed no significant differences between CRC, HRA, and healthy controls. Phascolarctobacterium succinatutens was more abundant in CRC compared with healthy controls in both the 16S and metagenome data. The abundance of Bifidobacterium and Lachnospiraceae spp. was associated with time to CRC diagnosis. Conclusion Using a longitudinal study design, we identified three taxa as being potentially associated with CRC. These should be the focus of further studies of microbial changes occurring prior to CRC diagnosis.
Stochastic Transmission in Epidemiological Models

Recent empirical evidence suggests that the transmission coefficient in susceptible-exposed-infected-removed-like (SEIR-like) models evolves with time, presenting random patterns, and some stylized facts, such as mean-reversion and jumps. To address such observations we propose the use of jump-diffusion stochastic processes to parameterize the transmission coefficient in an SEIR-like model that accounts for death and time-dependent parameters. We provide a detailed theoretical analysis of the proposed model proving the existence and uniqueness of solutions as well as studying its asymptotic behavior. We also compare the proposed model with some variations possibly including jumps. The forecast performance of the considered models, using reported COVID-19 infections from New York City, is then tested in different scenarios, including major outbreaks. The proposed jump-diffusion model presented remarkably accurate out-of-sample predictions, even during larger forecasted periods.
Prediction of Long COVID Based on Severity of Initial COVID-19 Infection: Differences in predictive feature sets between hospitalized versus non-hospitalized index infections

Long COVID is recognized as a significant consequence of SARS-COV2 infection. While the pathogenesis of Long COVID is still a subject of extensive investigation, there is considerable potential benefit in being able to predict which patients will develop Long COVID. We hypothesize that there would be distinct differences in the prediction of Long COVID based on the severity of the index infection, and use whether the index infection required hospitalization or not as a proxy for developing predictive models. We divide a large population of COVID patients drawn from the United States National Institutes of Health (NIH) National COVID Cohort Collaborative (N3C) Data Enclave Repository into two cohorts based on the severity of their initial COVID-19 illness and correspondingly trained two machine learning models: the Long COVID after Severe Disease Model (LCaSDM) and the Long COVID after Mild Disease Model (LCaMDM). The resulting models performed well on internal validation/testing, with a F1 score of 0.94 for the LCaSDM and 0.82 for the LCaMDM. There were distinct differences in the top 10 features used by each model, possibly reflecting the differences in type and amount of pathophysiological data between the hospitalized and non-hospitalized patients and/or reflecting different pathophysiological trajectories in the development of Long COVID. Of particular interest was the importance of Plant Hardiness Zone in the feature set for the LCaMDM, which may point to a role of climate and/or sunlight in the progression to Long COVID. Future work will involve a more detailed investigation of the potential role of climate and sunlight, as well as refinement of the predictive models as Long COVID becomes increasingly parsed into distinct clinical phenotypes.
Schizophrenia, inflammation and temporal change in brain morphology: an omnigenic Mendelian randomization study

The last decades of research in schizophrenia witnessed a shift of etiological speculation from neurotransmitters to inflammation. However, identifying definite inflammatory effectors of schizophrenia remains elusive due to confounding factors such as medication and metabolic status. To tackle this issue, we carried out omnigenic-based Mendelian randomization (MR) analysis to explore the inflammatory responses of schizophrenia and the brain morphological consequences caused by these SCZ-triggering inflammation responses. Our results identified seven SCZ-triggering inflammation markers, with P values surviving the Bonferroni multiple comparisons (B_NGF, P = 1.45 x 10 -8 }; GROA (CXCL1) P = 1.15 x 10 -4 }; IL8 , P = 3.64 x 10 -7 ; MCSF, P = 9.30 x 10 -4 ; MCP3 (CCL7) , P = 1.3 x 10 -6 ; TNF _ {beta} , P = 3.63 x 10 -4 ; CRP , P = 1.71 x 10 -32 ). Further, three of them, GROA (CXCL1), IL8 and CRP, could lead to significant linear change rate of brain morphologies, especially white matter in both cerebral and cerebellum. Our study is the first to use an omnigenic conceptual framework to capture the immune pathology of schizophrenia. Although future studies adopting a different methodology are needed to validate our results, our study provides another piece of evidence that extensive and low-grade neuroinflammation exists in schizophrenia and that some of these inflammation markers could be potential targets for the precise diagnosis and treatment of schizophrenia.
An Explainable Spatial-Temporal Graphical Convolutional Network to Score Freezing of Gait in Parkinsonian Patients

Freezing of gait (FOG) is a poorly understood heterogeneous gait disorder seen in patients with parkinsonism which contributes to significant morbidity and social isolation. FOG is currently measured with scales that are typically performed by movement disorders specialists (ie. MDS-UPDRS), or through patient completed questionnaires (N-FOG-Q) both of which are inadequate in addressing the heterogeneous nature of the disorder and are unsuitable for use in clinical trials The purpose of this study was to devise a method to measure FOG objectively, hence improving our ability to identify it and accurately evaluate new therapies. We trained interpretable deep learning models with multi-task learning to simultaneously score FOG (cross-validated F1 score 97.6%), identify medication state (OFF vs. ON levodopa; cross-validated F1 score 96.8%), and measure total PD severity (MDS-UPDRS-III score prediction error [≤] 2.7 points) using kinematic data of a well-characterized sample of N=57 patients during levodopa challenge tests. The proposed model was able to identify kinematic features associated with each FOG severity level that were highly consistent with the features that movement disorders specialists are trained to identify as characteristic of freezing. In this work, we demonstrate that deep learning models' capability to capture complex movement patterns in kinematic data can automatically and objectively score FOG with high accuracy. These models have the potential to discover novel kinematic biomarkers for FOG that can be used for hypothesis generation and potentially as clinical trial outcome measures.
Circulating Endothelial Progenitor Cells Reduce the Risk of Alzheimers Disease

Cerebrovascular damage coexists with Alzheimers disease (AD) pathology and increases AD risk. However, it is unclear whether endothelial progenitor cells reduce AD risk via cerebrovascular repair. By using the Framingham Heart Study (FHS) offspring cohort, which includes data on different progenitor cells, the incidence of AD dementia, peripheral and cerebrovascular pathologies, and genetic data (n = 1,566), we found that elevated numbers of circulating endothelial progenitor cells with CD34+CD133+ co-expressions had a dose-dependent association with decreased AD risk (HR = 0.67, 95% CI: 0.46-0.96, p = 0.03) after adjusting for age, sex, years of education, and APOE4. With stratification, this relationship was only significant among those individuals who had vascular pathologies, especially hypertension (HTN) and cerebral microbleeds (CMB), but not among those individuals who had neither peripheral nor central vascular pathologies. We applied a genome-wide association study (GWAS) and found that the number of CD34+CD133+ cells impacted AD risk depending on the homozygous genotypes of two genes: KIRREL3 rs580382 CC carriers (HR = 0.31, 95% CI: 0.17-0.57, p<0.001), KIRREL3 rs4144611 TT carriers (HR = 0.29, 95% CI: 0.15-0.57, p<0.001), and EXOC6B rs61619102 CC carriers (HR = 0.49, 95% CI: 0.31-0.75, p<0.001) after adjusting for confounders. In contrast, the relationship did not exist in their counterpart genotypes, e.g. KIRREL3 TT/CT or GG/GT carriers and EXOC6B GG/GC carriers. Our findings suggest that circulating CD34+CD133+ endothelial progenitor cells can be therapeutic in reducing AD risk in the presence of cerebrovascular pathology, especially in KIRREL3 and EXOC6B genotype carriers.
How effective was maritime quarantine in Australia during the influenza pandemic of 1918-19?

The influenza pandemic of 1918-19 was the most devastating pandemic of the 20th century. It killed an estimated 50--100 million people worldwide. In late 1918, when the severity of the disease was apparent, the Australian Quarantine Service was established. Vessels returning from overseas and inter-state were intercepted, and people were examined for signs of illness and quarantined. Some of these vessels carried the infection throughout their voyage and cases were prevalent by the time the ship arrived at a Quarantine Station. We study four outbreaks that took place on board the Medic, Boonah, Devon, and Manuka in late 1918. These ships had returned from overseas and some of them were carrying troops that served in the First World War. By analysing these outbreaks under a stochastic Bayesian hierarchical modeling framework, we estimate the transmission rates among crew and passengers aboard these ships. Furthermore, we ask whether the removal of infectious, convalescent, and healthy individuals after arriving at a Quarantine Station in Australia was an effective public health response.
Listract test: a Standardized Assessment Method for Isolated Lisfranc Instability in Cadaver Models

Background: The gold standard for diagnosis of Lisfranc instability is direct visualization in the operation room while the examination techniques is still unstandardized and non-reproducible. We aimed to introduce a novel reproducible intraoperative mechanical testing method (Listract test) for intraoperative isolated Lisfranc instability assessment. Methods: The Lisfranc ligament between the first cuneiform (C1) and second metatarsus (M2) in eight lower leg cadaveric specimens were dissected to replicate C1-M2 Lisfranc instability by eight foot and ankle surgeons. The 50N distraction force was applied in the direction of the C1-M2 ligament. Three methods of fixation - flexible fixation, metal screw, and bio-absorbable screw- were used to fix the injury, and Listract test was applied again after fixation. Besides intraoperative assessment, C1-M2 diastasis and area were measured using radiographs for assessment of Lisfranc instability. Results: The sensitivity and specificity of the Listract test for detection of C1-M2 instability were 100% and 100% intraoperatively, 33.3% and 95.2% using radiographic diastasis measurement, and 63.2% and 38% using area measurement, respectively. The Listract test had a specificity and sensitivity of 100% and 96% for intraoperative assessment, 87.5% and 64.3 for radiographic C1-M2 diastasis, and 48% and 50% for radiographic area. Conclusion: The Listract test is a simple, reproducible, and replicable intraoperative method for evaluating the Lisfranc joint for instability. Developing a device with this mechanism can help clinicians confirm the diagnosis and provide appropriate treatment particularly for equivocal diagnoses.
Cross‐sectional imaging and spectroscopy of GaAs doping superlattices by scanning tunneling microscopy

The scanning tunneling microscope is used to image GaAs pn‐doping superlattices, cleaved in ultrahigh vacuum. Current‐voltage (I‐V) measurements provide a detailed view of the variation in Fermi‐level position across the superlattice. The I‐V curves show the clear signature of nondepleted n‐ and p‐type material, with depleted regions appearing at the interfaces between n‐ and p‐type layers. The number of states available for tunneling is found to provide the major source of contrast in the images.