Miracle-dz/UniFAR-FTUs huggingface dataset:
Detailed measurements on a row of jets in a crossflow : With applications

The arrangement of multiple jets issuing perpendicularly to a crossflow is a fundamental fluid flow problem relevant to several engineering applications. One such application is the film cooling of gas turbine blades by discrete hole injection; another is the injection of combustion air in the lower levels of a Kraft recovery boiler. Both have been investigated experimentally and computationally. As the associated flow fields are threedimensional and highly complex, and the effects of system parameters — such as fluid injection rate and hole spacing — on system performance are not fully appreciated, two experimental studies were conducted. The first was designed to amass detailed measurements about a single row of jets, and to analyze the data with regard to film cooling. The second was designed to determine the characteristics of the flow field in a Kraft recovery boiler. In the first set of experiments, a row of six square jets spaced at 3.0 jet widths was arranged in a low-speed wind tunnel, and air was injected into the free stream at jet-tocrossflow velocity ratios (R) of 0.5, 1.0, and 1.5. The row was aligned at 9 0 ° to the direction of the crossflow, and the jet axes were perpendicular to the tunnel floor. Jet and crossflow air were maintained at approximately equal temperatures. Measurements of the mean velocities and six flow stresses were acquired by three-component, coincidence-mode, laser Doppler velocimetry ( L D V ) . Seed particles necessary for this technique were generated in both the jet and crossflow air by means of commercially available smoke machines. To complement the detailed measurements, flow visualization was performed by transmitting the laser light through a cylindrical lens, thereby brightly illuminating a given portion of the test section with a 5 mm wide sheet of light. Only the jets were seeded with smoke; therefore it was possible to acquire video recordings showing the penetration of the jets in various cross-tunnel planes. Results of the L D V measurements revealed distinctive trends of jets in a crossflow such as 3-D separation on the lee side of injection and counter-rotating vortex pairs; however, these were less evident in the case of the weakest (R=0.5) jets. For R>1.0, the jets penetrated
On the Dynamics of Two-Dimensional Hurricane-Like Vortex Symmetrization

Abstract Despite the fact that asymmetries in hurricanes, such as spiral rainbands, polygonal eyewalls, and mesovortices, have long been observed in radar and satellite imagery, many aspects of their origin, space–time structure, and dynamics still remain unsolved, particularly their role on the vortex intensification. The underlying inner-core dynamics need to be better understood to improve the science of hurricane intensity forecasting. To fill this gap, a simple 2D barotropic “dry” model is used to perform two experiments starting respectively with a monopole and a ring of enhanced vorticity to mimic hurricane-like vortices during incipient and mature stages of development. The empirical normal mode (ENM) technique, together with the Eliassen–Palm (EP) flux calculations, are used to isolate wave modes from the model datasets to investigate their space–time structure, kinematics, and the impact on the changes in the structure and intensity of the simulated hurricane-like vortices. From the ENM diagnost.
Student-led occupational performance coaching in a university setting

Introduction: University students are at a high risk for mental health difficulties. Occupational performance coaching is an action-oriented and strengths-based approach that can help clients set and accomplish personally valued goals. We carried out a pilot project to evaluate a tele-rehabilitation occupational performance coaching service for university students within an occupational therapy fieldwork placement. Method: A pretest post-test design was used. Severity of symptoms of depression, anxiety and stress and goal achievement were measured before and after the intervention and semi-structured interviews were carried out with student clients and student therapists. Development of student therapist competencies were noted. Results: Thirty-five student clients enrolled in occupational performance coaching and participated in 1–6 sessions. They identified academic, health, social and vocational goals. Through occupational performance coaching, clients made important progress on their goals. Following occupational performance coaching, clients demonstrated statistically significant improvement in anxiety and depression. The occupational therapy students attained competencies comparable in number and level to those achieved in more traditional placements. Conclusion: Occupational performance coaching is a potentially valuable addition to student mental health services. Such a service can be provided by supervised fieldwork students.
Dietary Protection against Cognitive Impairment, Neuroinflammation and Oxidative Stress in Alzheimer’s Disease Animal Models of Lipopolysaccharide-Induced Inflammation

Alzheimer’s disease (AD) is a rapidly growing epidemic with a heavy social and economic burden. Evidence suggests that systemic inflammation, dysregulation of the immune response and the resulting neuroinflammation and neurodegeneration play a significant role in AD pathogenesis. Currently, given that there is no fully convincing cure for AD, the interest in lifestyle factors (such as diet), which potentially delay onset and reduce the severity of symptoms, is increasing. This review is aimed at summarizing the effects of dietary supplementation on cognitive decline, neuroinflammation and oxidative stress in AD-like animal models with a focus on neuroinflammation induced by lipopolysaccharide (LPS) injection, which mimics systemic inflammation in animals. The compounds reviewed include curcumin, krill oil, chicoric acid, plasmalogens, lycopene, tryptophan-related dipeptides, hesperetin and selenium peptides. Despite the heterogeneity of these compounds, there is a strong consensus on their counteracting action on LPS-induced cognitive deficits and neuroinflammatory responses in rodents by modulating cell-signaling processes, such as the NF-κB pathway. Overall, dietary interventions could represent an important resource to oppose AD due to their influence in neuroprotection and immune regulation.
Spatial correlations in a redshift survey of APM galaxy clusters

A new catalog of rich clusters of galaxies was constructed by applying an objective selection algorithm to the APM Galaxy Survey. We have measured redshifts for 173 clusters from this catalog leading to a redshift survey of over 200 rich APM clusters with z ≤ 0.1 when we include published redshifts. The mean space density for this subsample is 2.4 × 10 -5 (h/Mpc) 3 , i.e., about four times the mean space R ≥ 1 Abell clusters
Establishment of a nomogram model for acute chest pain triage in the chest pain center

Background Acute myocardial infarction (AMI) is the leading life-threatening disease in the emergency department (ED), so rapid chest pain triage is important. This study aimed to establish a clinical prediction model for the risk stratification of acute chest pain patients based on the Point-of-care (POC) cardiac troponin (cTn) level and other clinical variables. Methods We conducted a post-hoc analysis of the database from 6,019 consecutive patients (excluding prehospital-diagnosed non-cardiac chest pain patients) attending a local chest pain center (CPC) in China between October 2016 and January 2019. The plasma concentration of cardiac troponin I (cTnI) was measured using a POC cTnI (Cardio Triage, Alere) assay. All the eligible patients were randomly divided into training and validation cohorts by a 7:3 ratio. We performed multivariable logistic regression to select variables and build a nomogram based on the significant predictive factors. We evaluated the model's generalization ability of diagnostic accuracy in the validation cohort. Results We analyzed data from 5,397 patients that were included in this research. The median turnaround time (TAT) of POC cTnI was 16 min. The model was constructed with 6 variables: ECG ischemia, POC cTnI level, hypotension, chest pain symptom, Killip class, and sex. The area under the ROC curve (AUC) in the training and validation cohorts was 0.924 and 0.894, respectively. The diagnostic performance was superior to the GRACE score (AUC: 0.737). Conclusion A practical predictive model was created and could be used for rapid and effective triage of acute chest pain patients in the CPC.
Best Trigonometric Approximation, Fractional Order Derivatives and Lipschitz Classes

Let C 2π denote the space of 2π-periodic continuous functions and πn the set of trigonometric polynomials of degree ≦ n, where n ϵ P = {0, 1, … } . Given θ > 0, the well-known theorem of Stečkin and its converse state that the best approximation of an ƒ ϵ C 2π with respect to the max-norm satisfies
An Efficient Massive MIMO Detector Based on Approximate Expectation Propagation

Among expectation propagation (EP)-based massive multiple-input–multiple-output (MIMO) detection algorithms, EP with weighted Neumann-series approximation (EPA-wNSA) has the lowest computational complexity while requiring many iterations to guarantee the detection performance, which severely limits the throughput of hardware implementations. Through the joint optimization of algorithm and hardware architecture, we propose an EP-based detector with higher throughput and area efficiency. First, the second-order Richardson iteration (SORI) algorithm is employed to replace the wNSA algorithm for higher convergence speed. Then three algorithmic transformations are proposed to minimize the overall complexity. Simulation results show that the proposed EPA-SORI algorithm requires much fewer iterations to achieve comparable or even better detection performance compared with EPA-wNSA. Furthermore, an efficient detector architecture is delicately designed by incorporating multiple optimization methods, such as reverse data flow, advanced addition, and rounding cells. Implemented with the Taiwan Semiconductor Manufacturing Company (TSMC) 28-nm CMOS technology, the proposed detector has $2.2 \times $ higher throughput than the state-of-the-art EP-based detector.
Homology in Finite Index Subgroups

This thesis looks at the following question: If G is a finitely presented group and G > G1 > G2 > . is a descending sequence of finite index subgroups, then how fast does the rank of H1(Gi;Fp) grow compared with the index |G : Gi|? One of our preliminary theorems gives a lower bound on the rank of the first mod-p homology of a normal subgroup H of index a power of p, in terms of the mod-p homology of the containing group G and the structure of the quotient p-group G/H . This bound generalizes a similar result of Lackenby in [Lac09b], and we use it to strengthen a result of that paper from the case p = 2 to all primes. The main result of the thesis concerns the case where G is the fundamental group of a finite-volume hyperbolic 3-manifold, and the subgroups in the descending sequence {Gi} are congruence subgroups in G. We study the structure of the profinite group SL(2, RP), where RP is the P-adic completion of a ring of integers in a number field, identifying subgroups of SL(2, RP) which are uniformly powerful. We show that if G is the fundamental group of a finite-volume hyperbolic 3-manifold then it can be approximated by SL(2, RP) for some choices of R and P. More precisely, there is a correspondence between certain congruence subgroups of G and congruence subgroups of SL(2, RP). We use this to prove our most general theorem, Theorem 5.3. 1. A simple corollary of Theorem 5.3. 1 is that for any ǫ > 0 the group G has a finite index subgroup G′ with congruence subgroups {Gi} such that the rank of H1(Gi;Fp) grows at least as fast as |G′ : Gi| 5 6 −ǫ.
Non-Oncogene Addiction of KRAS-Mutant Cancers to IL-1β via Versican and Mononuclear IKKβ

Simple Summary Kirsten rat sarcoma virus (KRAS)-mutant cancers are frequent, metastatic, lethal, and largely undruggable. The aim of this study was to investigate the pathways through which KRAS-mutant cancers foster their growth, thereby unravelling novel therapeutic targets. We show that KRAS-mutant tumors secrete the protein versican, which then drives the activation of NF-κB kinase (IKK) β in a type of host immune cells called macrophages. Following this activation, macrophages fuel the tumor with interleukin (IL)-1β, to close an inflammatory loop through which KRAS-mutant cancers attract host immune cells to the tumor site to accelerate tumor growth and aggressiveness. Importantly, we show that targeting IL-1β and/or versican can be an effective treatment for KRAS-mutant cancers, holding great promise for cancer patients. Abstract Kirsten rat sarcoma virus (KRAS)-mutant cancers are frequent, metastatic, lethal, and largely undruggable. While interleukin (IL)-1β and nuclear factor (NF)-κB inhibition hold promise against cancer, untargeted treatments are not effective. Here, we show that human KRAS-mutant cancers are addicted to IL-1β via inflammatory versican signaling to macrophage inhibitor of NF-κB kinase (IKK) β. Human pan-cancer and experimental NF-κB reporter, transcriptome, and proteome screens reveal that KRAS-mutant tumors trigger macrophage IKKβ activation and IL-1β release via secretory versican. Tumor-specific versican silencing and macrophage-restricted IKKβ deletion prevents myeloid NF-κB activation and metastasis. Versican and IKKβ are mutually addicted and/or overexpressed in human cancers and possess diagnostic and prognostic power. Non-oncogene KRAS/IL-1β addiction is abolished by IL-1β and TLR1/2 inhibition, indicating cardinal and actionable roles for versican and IKKβ in metastasis.
Accelerated randomized stochastic optimization

We propose a general class of randomized gradient estimates to be employed in a recursive search for the minimum of an unknown multivariate regression function. Here only two observations per iteration step are used. Special cases include random direction stochastic approximation (Kushner and Clark), simultaneous perturbation stochastic approximation (Spall) and a special kernel based stochastic approximation method (Polyak and Tsybakov). If the unknown regression is p-smooth (p ≥ 2) at the point of minimum, these methods achieve the optimal rate of convergence O(n -(P-1)/(2p) ). For both the classical stochastic approximation scheme (Kiefer and Wolfowitz) and the averaging scheme (Ruppert and Polyak) the related asymptotic distributions are computed.
Solar Flux Variability and the Lifetimes of Cometary H2O and OH

Abstract The far and extreme ultraviolet (FUV/EUV) solar flux determines the photodestruction rates of H 2 O and OH in cometary comae and affects their spatial density distributions. Between the minimum and maximum of the solar activity cycle, the solar flux varies by as much as a factor of 2-3 at some FUV and EUV wavelengths. From recent cross section measurements, a solar spectrum model using the He 1 λ10830 equivalent width and 10.7 cm flux as solar activity indices, and estimates of destruction rates due to the solar wind, we can estimate the H 2 O and OH lifetimes appropriate to any observation since 1975. The calculated H 2 O and OH lifetimes against direct photodissociation both vary by 30%, though the additional destruction of OH through predissociation accounts for most of the 70% variability in its total lifetime. Lifetimes for H 2 O and OH corresponding to the solar activity minimum and maximum are presented along with parametrizations to estimate lifetimes appropriate for any observation date. As a by-product, we calculate the time-variable yields for producing OH( A 2 Σ + ), O( 1 D ), and O( 3 P ) from H 2 O and OH. The H 2 O and OH lifetimes were included in a vectorial density distribution model and tested against International Ultraviolet Explorer (IUE) spacecraft observations in which the OH coma was spatially mapped, and the agreement is quite good. The implications of this new OH modeling on the interpretation of observations are exemplified in a brief analysis of Q H 2 O for comets Bradfield (1979 X) and Austin (1990 V).
Application of Artiﬁcial Intelligence in Assessing the Self-Management Practices of Patients with Type 2 Diabetes

: The use of Artiﬁcial intelligence in healthcare has evolved substantially in recent years. In medical diagnosis, Artiﬁcial intelligence algorithms are used to forecast or diagnose a variety of life-threatening illnesses, including breast cancer, diabetes, heart disease, etc. The main objective of this study is to assess self-management practices among patients with type 2 diabetes in rural areas of Pakistan using Artiﬁcial intelligence and machine learning algorithms. Of particular note is the assessment of the factors associated with poor self-management activities, such as non-adhering to medications, poor eating habits, lack of physical activities, and poor glycemic control (HbA1c %). The sample of 200 participants was purposefully recruited from the medical clinics in rural areas of Pakistan. The artiﬁcial neural network algorithm and logistic regression classiﬁcation algorithms were used to assess diabetes self-management activities. The diabetes dataset was split 80:20 between training and testing; 80% (160) instances were used for training purposes and 20% (40) instances were used for testing purposes, while the algorithms’ overall performance was measured using a confusion matrix. The current study found that self-management efforts and glycemic control were poor among diabetes patients in rural areas of Pakistan. The logistic regression model performance was evaluated based on the confusion matrix. The accuracy of the training set was 98%, while the test set’s accuracy was 97.5%; each set had a recall rate of 79% and 75%, respectively. The output of the confusion matrix showed that only 11 out of 200 patients were correctly assessed/classiﬁed as meeting diabetes self-management targets based on the values of HbA1c < 7%. We added a wide range of neurons (32 to 128) in the hidden layers to train the artiﬁcial neural network models. The results showed that the model with three hidden layers and Adam’s optimisation function achieved 98% accuracy on the validation set. This study has assessed the factors associated with poor self-management activities among patients with type 2 diabetes in rural areas of Pakistan. The use of a wide range of neurons in the hidden layers to train the artiﬁcial neural network models improved outcomes, conﬁrming the model’s effectiveness and efﬁciency in assessing diabetes self-management activities from the required data attributes.
Bubble clouds and their transport within the surf zone as measured with a distributed array of upward-looking sonars

A collaborative, multi-institute experiment called the Scripps Pier Experiment was conducted in the vicinity of the Scripps pier in La Jolla, California, in March 1997 to study the fate of bubbles in the surf zone and the effects of these bubbles on acoustic propagation. This paper discusses data gathered by the Applied Physics Laboratory, University of Washington, using a set of four upward-looking sonars (frequency 240 kHz), which simultaneously measured vertical profiles of acoustic volume scattering from bubbles at four locations. The transport of bubbles via rip currents emerged as an important, though episodic and localized, feature of the acoustic environment in the surf zone. Images of volumetric backscattering strength vs time and depth reveal the episodic events (of increased scattering level) lasting between 5 and 10 min caused by the passage of bubble clouds over the sonar. Time lags for the onset of increased scattering at the four locations are consistent with a seaward velocity of the bubbl.
Whole genome characterization of thermophilic Campylobacter species isolated from dairy manure in small specialty crop farms of Northeast Ohio

Introduction With more public interest in consuming locally grown produce, small specialty crop farms (SSCF) are a viable and growing segment of the food production chain in the United States. Methods The goal of this study was to investigate the genomic diversity of Campylobacter isolated from dairy manure (n = 69) collected from 10 SSCF in Northeast Ohio between 2018 and 2020. Results A total of 56 C. jejuni and 13 C. coli isolates were sequenced. Multi-locus sequence typing (MLST) identified 22 sequence types (STs), with ST-922 (18%) and ST-61 (13%) predominant in C. jejuni and ST-829 (62%) and ST-1068 (38%) predominant in C. coli. Interestingly, isolates with similar genomic and gene contents were detected within and between SSCF over time, suggesting that Campylobacter could be transmitted between farms and may persist in a given SSCF over time. Virulence-associated genes (n = 35) involved in the uptake and utilization of potassium and organic compounds (succinate, gluconate, oxoglutarate, and malate) were detected only in the C. jejuni isolates, while 45 genes associated with increased resistance to environmental stresses (capsule production, cell envelope integrity, and iron uptake) were detected only in the C. coli isolates. Campylobacter coli isolates were also sub-divided into two distinct clusters based on the presence of unique prophages (n = 21) or IncQ conjugative plasmid/type-IV secretion system genes (n = 15). Campylobacter coli isolates harbored genes associated with resistance to streptomycin (aadE-Cc; 54%) and quinolone (gyrA-T86I; 77%), while C. jejuni had resistance genes for kanamycin (aph3’-IIIa; 20%). Both species harbored resistance genes associated with β-lactam (especially, blaOXA-193; up to 100%) and tetracycline (tetO; up to 59%). Discussion/Conclusion Our study demonstrated that Campylobacter genome plasticity associated with conjugative transfer might provide resistance to certain antimicrobials and viral infections via the acquisition of protein-encoding genes involved in mechanisms such as ribosomal protection and capsule modification.
Antiretroviral Treatment of HIV-2 Infection: Available Drugs, Resistance Pathways, and Promising New Compounds

Currently, it is estimated that 1–2 million people worldwide are infected with HIV-2, accounting for 3–5% of the global burden of HIV. The course of HIV-2 infection is longer compared to HIV-1 infection, but without effective antiretroviral therapy (ART), a substantial proportion of infected patients will progress to AIDS and die. Antiretroviral drugs in clinical use were designed for HIV-1 and, unfortunately, some do not work as well, or do not work at all, for HIV-2. This is the case for non-nucleoside reverse transcriptase inhibitors (NNRTIs), the fusion inhibitor enfuvirtide (T-20), most protease inhibitors (PIs), the attachment inhibitor fostemsavir and most broadly neutralizing antibodies. Integrase inhibitors work well against HIV-2 and are included in first-line therapeutic regimens for HIV-2-infected patients. However, rapid emergence of drug resistance and cross-resistance within each drug class dramatically reduces second-line treatment options. New drugs are needed to treat infection with drug-resistant isolates. Here, we review the therapeutic armamentarium available to treat HIV-2-infected patients, as well as promising drugs in development. We also review HIV-2 drug resistance mutations and resistance pathways that develop in HIV-2-infected patients under treatment.