Miracle-dz/UniFAR-FTUs huggingface dataset:
Leak Localization in Looped Pipe Networks Based on a Factorized Transient Wave Model: 2. Regularization of Ill‐Conditioned Problems

A previous paper proposed an accurate and efficient matched‐field processing method for leak localization in looped pipe networks based on the known discharge and pressure head (i.e., hydraulic properties) at all internal nodes. However, the computation of these internal hydraulic properties from boundary measurements is an ill‐conditioned inverse problem: for a small perturbation in the boundary measurements there is a huge change in the internal hydraulic properties. We prove and clarify the invalidity of the classic Tikhonov regularization for this ill‐conditioned problem. As an alternative, this paper derives the theoretical upper bounds of noise‐induced errors, based on which a threshold is determined for identifying ill‐conditioned frequencies. The leak localization is implemented by discarding wave information at all ill‐conditioned frequencies. This results in an efficient and robust algorithm for leak localization in noisy environments. Numerical experiments demonstrate that an unknown leak anywhere in looped pipe networks can be accurately localized by the proposed algorithm.
Time to End-of-Life of Patients Starting Specialised Palliative Care in Denmark: A Descriptive Register-Based Cohort Study

Increasing numbers of patients are being referred to specialised palliative care (SPC) which, in order to be beneficial, is recommended to last more than three months. This cohort study aimed to describe time to end-of-life after initiating SPC treatment and to explore potential regional variations. We used national register data from all Danish hospital SPC teams. We included patients who started SPC treatment from 2015–2018 to explore if time to end-of-life was longer than three months. Descriptive statistics were used to summarise the data and a generalised linear model was used to assess variations among the five Danish regions. A total of 27,724 patients were included, of whom 36.7% (95% CI 36.2–37.1%) had over three months to end-of-life. In the Capital Region of Denmark, 40.1% (95% CI 39.0–41.3%) had over three months to end-of-life versus 32.5% (95% CI 30.9–34.0%) in North Denmark Region. We conclude that most patients live for a shorter period of time than the recommended three months after initiating SPC treatment. This is neither optimal for patient care, nor the healthcare system. A geographical variation between regions was shown indicating different practices, patient groups or resources. These results warrant further investigation to promote optimal SPC treatment.
A YOUNG WHITE DWARF WITH AN INFRARED EXCESS

Using observations of Spitzer/IRAC, we report the serendipitous discovery of excess infrared emission from a single white dwarf PG 0010+280. At a temperature of 27,220 K and a cooling age of 16 Myr, it is the hottest and youngest white dwarf to display an excess at 3–8 μm. The infrared excess can be fit by either an opaque dust disk within the tidal radius of the white dwarf or a 1300 K blackbody, possibly from an irradiated substellar object or a re-heated giant planet. PG 0010+280 has two unique properties that are different from white dwarfs with a dust disk: (i) relatively low emission at 8 μm and (ii) non-detection of heavy elements in its atmosphere from high-resolution spectroscopic observations with Keck/HIRES. The origin of the infrared excess remains unclear.
A STUDY ON A NEW APPROACH TO HYBRID REGRESSION MODELING: A CASE FOR DIABETES MELLITUS WITH DYSLIPIDAEMIA PATIENTS WHO VISITED HOSPITAL USM

Background and Objective: The incidence of type 2 diabetes has been steadily rising over the past few decades, which has contributed significantly to the rise in the prevalence of diabetes (DM). Statistics from the World Health Organization show that more than 422 million adults worldwide had diabetes in 2014, and an ongoing rise in DM prevalence is anticipated. This study aims to create a method that can use to predict and manage diabetes cases in light of the importance of statistical modeling in diabetes. Decision trees and ordinal regression were the two methods used in this study. With some modification and extension, both methods will be harmonized in the R syntax. Materials and Methods: In this paper, we developed a method for analyzing decision trees using R syntax and embedding classification predictions. The classification for prediction with accuracy will indicate a successful classification analysis. This study illustrated the development method using diabetes data consisting of one thousand observations. Before further testing, the clinical relevance and significance of each preselected variable will be assessed. The decision tree will be used to evaluate nine variables. The selected variables are body mass index, total cholesterol, diabetes status
Predictive Power of Tissue and Circulating Biomarkers for the Severity of Biopsy-Validated Chronic Liver Diseases

Background: Although liver biopsy remains the gold standard for the diagnosis and the monitoring of liver disease, non-invasive biomarkers have been recently suggested to predict liver disease severity, progression, and response to therapy. We investigated multiple tissue and circulating markers of angiogenesis in predicting the severity of biopsy-validated chronic liver diseases in patients with chronic hepatitis C virus (HCV) and in NAFLD/NASH patients. Methods: We studied samples from forty-six patients with HCV and/or NAFLD who underwent liver biopsy, liver ultrasonography, and liver stiffness measurement. Ishak and Brunt scores were calculated. Expression of selective genes and luminex analyses of 17 different circulating pro-angiogenic factors were performed. Results: The phenotype of NAFLD/NASH or HCV subjects was similar, except for insulin, which was expressed at higher levels in NAFLD/NASH patients. A Mann–Whitney test showed significant differences for the circulating levels of HB-EGF and for follistatin between HCV and NAFLD/NASH patients. In HCV patients, we found an inverse correlation between disease stage and BMP-9 and VEGF-A circulating levels, while in NASH/NAFLD direct correlations between stage and BMP-9 and VEGF-A circulating levels were noted. The K-means algorithm divided HCV and NASH/NAFLD patients in two clusters with significant differences between them. Logistic regression models showed a positive relationship with BMP-9 levels for NASH/NAFLD and with HB-EGF circulating concentrations for HCV. ROC analysis showed for BMP-9 > 1188 pg/mL a worse disease in NASH/NAFLD, whereas for HB-EGF < 61 pg/mL a higher severity of disease in HCV. Conclusion: Our data show that circulating biomarker profiles can identify the severity of chronic liver disease of NAFLD/NASH or HCV origin.
A Joint Learning and Game-Theoretic Approach to Multi-Dimensional Resource Management in Fog Radio Access Networks

Fog radio access networks (F-RANs) have been regarded as a promising paradigm to support latency-sensitive and computation-intensive services by leveraging computing and caching capabilities of fog access points (F-APs). To execute offloaded computation tasks, it is essential to pre-store necessary programs and databases at F-APs, referred as service caching. However, due to system dynamics and the coupling of decisions, cache, radio, and computation resource management at F-RANs is a challenging problem. In this paper, a joint multi-dimensional resource optimization problem is formulated, aiming at minimizing the weighted sum of expected latency cost and caching cost, which is featured by a two-timescale structure. For radio and computation resource allocation on a small timescale, a coalitional game based approach is proposed under given caching decisions. On a larger timescale, services are cached at each F-AP using a multi-agent reinforcement learning algorithm. The advantage of the proposed algorithms is that they can implicitly take the impact of small timescale resource allocation into account while adapting to the long-term statistics of channel coefficients and user service requests. We analyze the proposed algorithms with respect to their convergence, optimality, and complexity, and validate their performance with extensive simulations, where superior performance is observed over several baseline schemes.
Non-embeddable relational configurations

Relational configurations are defined by the relationships between systems. Individualist configurations are defined by the properties of individual systems. Non-embeddable relational configurations are those for which there is no equivalent individualist description. We suggest that situations in physics where a spacetime description breaks down may be the result of trying to use individualist configurations to model non-embeddible relational configurations. We propose a particular example of a relational configuration space, the 2 instant relation (2IR), whose embeddible configurations describe particle worldlines in a background spacetime. We investigate the properties of these configurations.
Confidence-Aware Multiscale Learning for Online Modeling of Distributed Parameter Systems With Application to Curing Process

In industrial applications, the modeling of distributed parameter systems (DPSs) is of significance for process control and monitoring. Due to infinite dimension, spatiotemporal coupled dynamics, nonlinearity, and model uncertainties, however, modeling and online applications of DPSs are very difficult. To address these issues, an online spatiotemporal modeling method is proposed based on confidence-aware multiscale learning. From the spacial-scale perspective, an evolutionary learning-based spatial basis function is designed by learning from two dimensionality reduction methods, including Karhunen–Lo$\grave{e}$ ve and diffusion maps. From the temporal-scale perspective, an efficient broad learning system is developed as reduced-order model to online address temporal dynamics of DPSs. As for the spatiotemporal-scale learning, Gaussian process regression is proposed as confidence-aware estimator to compensate for model generalization errors caused by spatiotemporal coupled dynamics. Through integration with the three-scale learning, the proposed method enables online confidence-aware prediction for DPSs. Experiments based on the curing process in snap curing oven demonstrate the effectiveness of proposed method.
Experiments on Deep Single-Image Portrait Relighting

This work describes deep single-image portrait relighting, a method to change the lighting of an image. The method is based on an hourglass convolutional neural network, which encodes the image and its estimated original lighting features, then replaces the lighting features with the target light. We highlight the overall good results produced by this method, as well as its limitations and the lighting artifacts that sometimes appear on relighted images. The source code and documentation for this algorithm are available from the web page of this article 1 . Usage instructions are included in the README.txt ﬁle of the archive. The authors’ original implementation of the method is available here 2 . This is an MLBriefs article, the source code has not been reviewed!
General relativistic simulations of black hole-neutron star mergers: Effects of tilted magnetic fields

Black hole–neutron star (BHNS) binary mergers can form disks in which magnetorotational instability (MRI)-induced turbulence may drive accretion onto the remnant BH, supporting relativistic jets and providing the engine for a short-hard gamma-ray burst (SGRB). Our earlier study of magnetized BHNSs showed that NS tidal disruption winds the magnetic field into a toroidal configuration, with poloidal fields so weak that capturing MRI with full-disk simulations would require ∼ 10 CPU-hours. In that study we imposed equatorial symmetry, suppressing poloidal magnetic fields that might be generated from plasma crossing the orbital plane. Here we show that initial conditions that break this symmetry (i.e., tilted poloidal magnetic fields in the NS) generate much stronger poloidal fields in the disk, indicating that asymmetric initial conditions may be necessary for establishing BHNS mergers as SGRB progenitors via fully general relativistic MHD simulations. We demonstrate that BHNS mergers may form an SGRB engine under the right conditions by seeding the remnant disk from an unmagnetized BHNS simulation with purely poloidal fields dynamically unimportant initially, but strong enough to resolve MRI. Magnetic turbulence occurs in the disk, driving accretion and supporting Poynting-dominated jet outflows sufficient to power an SGRB.
Investigation of Factors That Former CRM Quality and Its Implications for Customer Loyalty (Studies on JakOne Mobile Banking Users)

This study aims to identify the factors forming CRM Quality and their implications for Customer Loyalty at JakOne mobile banking users who are customers of Bank DKI Jakarta Barat Mayor Service Office. The sample used in this study were 144 JakOne mobile banking users who are customers of Bank DKI Jakarta Barat Mayor Service Office. The data collection technique in this study uses primary data by distributing questionnaires to respondents using Structural Equation Modeling (SEM) analysis which is supported by SmartPLS 3.0 applications. The main research results show that CRM Quality has a positive influence on Customer Loyalty and Customer Satisfaction has a positive influence on Customer Loyalty through CRM Quality mediation. Meanwhile, Customer Value has no influence on Customer Loyalty through CRM Quality mediation. Brand Image has no influence on Customer Loyalty, and Service Quality does not have a positive influence on Customer Loyalty through CRM Quality mediation.
Nigella sativa L. and Its Active Compound Thymoquinone in the Clinical Management of Diabetes: A Systematic Review

Despite existing conventional hypoglycemic drugs to manage diabetes, their non-availability and cost in low-income countries coupled with the associated side effects remain a major concern. Consequently, exploring for alternative treatments to manage diabetes has been a continuous priority. Nigella sativa L. (NS) (Family: Ranunculaceae) is regarded as a valuable traditional remedy in diabetes management and extensively studied for its biological properties. This systematic review provides a comprehensive and critical analysis of clinical studies on the efficacy, safety, and mechanism of action of NS and its compound thymoquinone (TQ) in diabetes management. The main scientific databases which were scrutinised were Scopus, PubMed, Google Scholar, and Web of Science. Data search was conducted from inception to January 2022. A total of 17 clinical studies were obtained; 16 studies on Nigella sativa L. and 1 study on its compound TQ. N. sativa was found to be highly potent in terms of its hypoglycemic activity when compared to placebo based on improvement in parameters including fasting blood glucose (FBG), postprandial blood glucose (PPBG), Hemoglobin A1C (HbA1c), homeostatic model assessment for insulin resistance (HOMA-IR), and homeostatic model assessment for assessment of beta-cell functionality (HOMA-β). The compound TQ in combination with a daily dose of metformin demonstrated a greater reduction in the levels of HbA1c and blood glucose compared to metformin alone. The bioavailability of TQ can be enhanced by using nanoparticulate drug delivery systems. Considering the findings of the clinical studies along with negligible adverse effects, NS has strong potential application in bioproduct development for the management of diabetes. Further investigations should explore the detailed mechanism of actions by which TQ exerts its therapeutic antidiabetic effects to provide more insights into its clinical use in the management of diabetes.
EXTREMELY BRIGHT SUBMILLIMETER GALAXIES BEYOND THE LUPUS-I STAR-FORMING REGION

We report detections of two candidate distant submillimeter galaxies (SMGs), MM J154506.4−344318 and MM J154132.7−350320, which are discovered in the AzTEC/ASTE 1.1 mm survey toward the Lupus-I star-forming region. The two objects have 1.1 mm flux densities of 43.9 and 27.1 mJy, and have Herschel/SPIRE counterparts as well. The Submillimeter Array counterpart to the former SMG is identified at 890 μm and 1.3 mm. Photometric redshift estimates using all available data from the mid-infrared to the radio suggest that the redshifts of the two SMGs are z photo ≃ 4 ? > –5 and 3, respectively. Near-infrared objects are found very close to the SMGs and they are consistent with low-z ellipticals, suggesting that the high apparent luminosities can be attributed to gravitational magnification. The cumulative number counts at S 1.1 mm ≥ 25 ? > mJy, combined with the other two 1.1 mm brightest sources, are 0.70 − 0.34 + 0.56 ? > deg−2, which is consistent with a model prediction that accounts for flux magnification due to strong gravitational lensing. Unexpectedly, a z > 3 ? > SMG and a Galactic dense starless core (e.g., a first hydrostatic core) could be similar in the mid-infrared to millimeter spectral energy distributions and spatial structures at least at ≳ 1 ″ ? > . This indicates that it is necessary to distinguish the two possibilities by means of broadband photometry from the optical to centimeter and spectroscopy to determine the redshift, when a compact object is identified toward Galactic star-forming regions.
Anharmonic phonons in few-layer MoS2: Raman spectroscopy of ultralow energy compression and shear modes

Molybdenum disulfide (MoS$_2$) is a promising material for making two-dimensional crystals and flexible electronic and optoelectronic devices at the nanoscale. MoS$_2$ flakes can show high mobilities and have even been integrated in nanocircuits . A fundamental requirement for such use is efficient thermal transport. Electronic transport generates heat which needs to be evacuated, more crucially so in nanostructures. Anharmonic phonon-phonon scattering is the dominant intrinsic limitation to thermal transport in insulators. Here, using appropriate samples, ultra-low energy Raman spectroscopy and first principles calculations, we provide a full experimental and theoretical description of compression and shear modes of few-layer (FL) MoS$_2$. We demonstrate that the compression modes are strongly anharmonic with a marked enhancement of phonon-phonon scattering as the number of layers is reduced, most likely a general feature of nanolayered materials with weak interlayer coupling.
HOT VERSUS COLD: THE DICHOTOMY IN SPHERICAL ACCRETION OF COOLING FLOWS ONTO SUPERMASSIVE BLACK HOLES IN ELLIPTICAL GALAXIES, GALAXY GROUPS, AND CLUSTERS

Feedback heating from active galactic nuclei (AGNs) has been commonly invoked to suppress cooling flows predicted in hot gas in elliptical galaxies, galaxy groups, and clusters. Previous studies have focused on if and how AGN feedback heats the gas but have little paid attention to its triggering mechanism. Using spherically symmetric simulations, we investigate how large-scale cooling flows are accreted by central supermassive black holes (SMBHs) in eight well-observed systems and find an interesting dichotomy. In massive clusters, the gas develops a central cooling catastrophe within about the cooling time (typically ∼100–300 Myr), resulting in cold-mode accretion onto SMBHs. However, in our four simulated systems on group and galaxy scales at a low metallicity Z = 0.3 Z☉, the gas quickly settles into a long-term state that has a cuspy central temperature profile extending to several tens to about 100 pc. At the more realistic solar metallicity, two groups (with Re ∼ 4 kpc) still host the long-term, hot-mode accretion. Both accretion modes naturally appear in our idealized calculations where only cooling, gas inflow, and compressional heating are considered. The long-term, hot-mode accretion is maintained by the quickly established closeness between the timescales of these processes, preferably in systems with low gas densities, low gas metallicities, and importantly, compact central galaxies, which result in strong gravitational acceleration and compressional heating at the intermediate radii. Our calculations predict that central cuspy temperature profiles appear more often in smaller systems than galaxy clusters, which instead often host significant cold gas and star formation.
Feedback from Winds and Supernovae in Massive Stellar Clusters - II. X-Ray Emission

The X-ray emission from a simulated massive stellar cluster is investigated. The emission is calculated from a 3D hydrodynamical model which incorporates the mechanical feedback from the stellar winds of 3 O-stars embedded in a giant molecular cloud (GMC) clump containing 3240M⊙ of molecular material within a 4 pc radius. A simple prescription for the evolution of the stars is used, with the first supernova explosion at t= 4.4Myrs. We find that the presence of the GMC clump causes shortlived attenuation effects on the X-ray emission of the cluster. However, once most of the material has been ablated away by the winds the remaining dense clumps do not have a noticable effect on the attenuation compared with the assumed interstellar medium (ISM) column. We determine the evolution of the cluster X-ray luminosity, LX , and spectra, and generate synthetic images. The intrinsic X-ray luminosity drops from nearly 10 ergs s while the winds are ‘bottled up’, to a near constant value of 1.7×10 ergs s between t=1–4Myrs. LX reduces slightly during each star’s red supergiant (RSG) stage due to the depressurization of the hot gas. However, LX increases to ≈ 10 ergs s during each star’s Wolf-Rayet (WR) stage. The X-ray luminosity is enhanced by 2-3 orders of magnitude to ∼ 10 ergs s for at least 4600 yrs after each supernova (SN) explosion, at which time the blast wave leaves the grid and the X-ray luminosity drops. The X-ray luminosity of our simulation is generally considerably fainter than predicted from spherically-symmetric bubble models, due to the leakage of hot gas material through gaps in the outer shell. This process reduces the pressure within our simulation and thus the X-ray emission. However, the X-ray luminosities and temperatures which we obtain are comparable to similarly powerful massive young clusters.
Acupuncture in Women with Human Polycystic Ovary/Ovarian Syndrome: Protocol for a Randomized Controlled Trial

(1) Background: Human polycystic ovary/ovarian syndrome (PCOS) is linked to endocrine, metabolic, and psychological complications. We propose a randomized controlled pilot study for an acupuncture protocol regarding the management of PCOS symptoms based on TCM diagnosis; (2) Methods: We will randomly allocate 120 women diagnosed with PCOS into two groups. The study group will be treated with acupuncture for points known to act upon the autonomous regulation of the hormonal, metabolic and emotional components. (3) Results and Conclusions: We expect to provide evidence of high methodological quality related to the effects and safety of an acupuncture protocol based on the perspective of a TCM diagnostic.
Nonuniversal scalar-tensor theories and big bang nucleosynthesis

We investigate the constraints that can be set from big bang nucleosynthesis on two classes of models: extended quintessence and scalar-tensor theories of gravity in which the equivalence principle between standard matter and dark matter is violated. In the latter case, and for a massless dilaton with quadratic couplings, the phase space of theories is investigated. We delineate those theories where attraction toward general relativity occurs. It is shown that big bang nucleosynthesis sets more stringent constraints than those obtained from Solar System tests.