Miracle-dz/UniFAR-FTUs huggingface dataset:
A possible relationship between Changma and tropical cyclone genesis frequency in the western North Pacific linked to the North Atlantic Oscillation

This study analysed the relationship between Changma and tropical cyclone (TC) genesis in the western North Pacific (WNP). The correlations between Changma onset, withdrawal, and duration in Jeju and the southern and central regions of Korea and TC genesis frequencies in June, July, and June–July in the WNP were analysed. The results showed that Changma duration in the southern region and June–July TC genesis frequency exhibited the highest negative correlation. To investigate the mechanism underlying the correlations, the differences in large‐scale environments between the 14 years with the longest Changma duration and the 14 years with the shortest Changma duration were analysed. For 850‐hPa stream flows, anomalous anticyclones are found in most WNP regions, while anomalous cyclones are located in the East Asian mid‐latitude region. In the long Changma duration years, the WNP subtropical high was strengthened in the north–south and east–west directions, the monsoon trough was weakened, and anomalous downward flows are formed at the latitudinal (longitudinal) band of 10°–27°N (100°–180°E) where TCs mainly occur. All these environments provide unfavourable conditions for TCs to occur. The difference in sea surface temperature revealed triple anomaly patterns, such as warm, cold, and warm, in the north–south direction in the North Atlantic. This spatial distribution was similar to the negative North Atlantic Oscillation (NAO) pattern. From the analysis of 500‐hPa stream flow, we confirmed that the NAO acts as a bridge connecting the TC and Changma in the WNP.
An X‐Ray Investigation of Crystallinity in Rubber

X‐ray diffraction evidence has shown that a crystalline structure can be produced in rubber by stretching or by freezing. In the former case, a fiber diagram is generally secured, in the latter, Debye‐Scherrer rings. When raw rubber was stretched to moderate elongations and frozen an intense fiber diagram was found, showing that the crystallization proceeded from nuclei set up by the stretching. A series of diffraction patterns illustrating the effect are reproduced. The geometrical conditions of stretching under which ``higher orientation'' occurs in stretched rubber were studied by photometric measurements of the relative densities of the first two equatorial spots. Graphs are included demonstrating the effect of variations in gauge, width, length and elongation of the specimens. Higher orientation occurs when the percent contraction in gauge exceeds the percent contraction in width. The different physical structures of vulcanized pure gum stocks became apparent in the ``higher orientation'' characteris.
Assessment of Bone Microstructure by Micro CT in C57BL/6J Mice for Sex-Specific Differentiation

It remains uncertain which skeletal sites and parameters should be analyzed in rodent studies evaluating bone health and disease. In this cross-sectional mouse study using micro-computed tomography (µCT), we explored: (1) which microstructural parameters can be used to discriminate female from male bones and (2) whether it is meaningful to evaluate more than one bone site. Microstructural parameters of the trabecular and/or cortical compartments of the femur, tibia, thoracic and lumbar vertebral bodies, and skull were evaluated by µCT in 10 female and 10 male six-month-old C57BL/6J mice. The trabecular number (TbN) was significantly higher, while the trabecular separation (TbSp) was significantly lower in male compared to female mice at all skeletal sites assessed. Overall, bone volume/tissue volume (BV/TV) was also significantly higher in male vs. female mice (except for the thoracic spine, which did not differ by sex). Most parameters of the cortical bone microstructure did not differ between male and female mice. BV/TV, TbN, and TbSp at the femur, and TbN and TbSp at the tibia and lumbar spine could fully (100%) discriminate female from male bones. Cortical thickness (CtTh) at the femur was the best parameter to detect sex differences in the cortical compartment (AUC = 0.914). In 6-month-old C57BL/6J mice, BV/TV, TbN, and TbSp can be used to distinguish male from female bones. Whenever it is not possible to assess multiple bone sites, we propose to evaluate the bone microstructure of the femur for detecting potential sex differences.
Analysis of Surface Polariton Resonance for Nanoparticles in Elastic System

This paper is concerned with the analysis of surface polariton resonance for nanoparticles in linear elasticity. With the presence of nanoparticles, we first derive the perturbed displacement field associated to a given elastic source field. It is shown that the leading-order term of the perturbed elastic wave field is determined by the Neumann-Poinc\'are operator associated to the Lam\'e system. By analyzing the spectral properties of the aforesaid Neumann-Poinc\'are operator, we study the polariton resonance for the elastic system. The results may find applications in elastic wave imaging.
Brief risk rating scale: A preliminary screening and monitoring tool emphasizing individual differences for better prognosis in Alzheimer’s disease

Over the last several decades, significant progress has been made in the diagnostic criteria of Alzheimer’s disease (AD) to identify its early stages, including subjective cognitive decline and mild cognitive impairment. However, the previous research rarely took account of individual differences when evaluating AD-spectrum patients at different stages, thereby resulting in similar treatment, which was not only ineffective but also resulted in the missed window of opportunity for intervention. In this review, we propose the Brief Risk Rating Scale (BRRS), which is predominantly based on extant literature concerning AD risk factors and brain alterations, with the aim of providing a preliminary screening and monitoring tool that can facilitate the assessment of individual’s risk level, the prediction and tracking of disease progression, as well as precise treatment in a timely manner. Meanwhile, due to its simplicity and ease of use, it can be widely promoted and likewise accessible to clinicians in grassroots clinics. In general, the scale comprises two parts: The original score (O) related to patients’ risk factors and the variation score (V) related to brain abnormalities tested by different sequences of magnetic resonance imaging. In addition, the advantages along with its clinical application, such as introducing BRRS into cognitive training and brain stimulation, are also discussed. We conclude that BRRS positively contributes to enhancing the accuracy of clinical diagnosis and the efficiency of personalized treatment in AD-spectrum patients, with individual differences fully considered and little additional burden added. However, the weight coefficient of each item in BRRS should be thoroughly studied in future research.
Semantic-aware multi-task learning for image aesthetic quality assessment

In recent years, image aesthetic quality assessment has attracted considerable attention due to the massive growth of digital images in social platforms and the Internet. However, automatically assessing aesthetic quality of an image is a challenging task, because image aesthetic is affected by various factors, and the criteria for judging the aesthetic of images with diverse semantic information are different. To this end, a Semantic-Aware Multi-task convolution neural network (SAM-CNN) for evaluating image aesthetic quality is proposed in this paper. The network can fuse intermediate features of different layers at different scales in CNN to obtain a more comprehensive and accurate aesthetic expression, under the joint supervision of image aesthetic quality assessment task and semantic classification task in a multi-task learning manner. Besides, by applying the attention mechanism, semantic information with a large receptive field extracted from deep layers is utilised to guide the network to focus on the key parts of features to be fused, to improve the effectiveness of feature fusion. Experimental results on the AVA dataset and Photo.net dataset demonstrate the effectiveness and superiority of the proposed SAM-CNN.
State-dependent stochastic networks. Part I. Approximations and applications with continuous diffusion limits

In a state-dependent queueing network, arrival and service rates, as well as routing probabilities, depend on the vector of queue lengths. For properly normalized such networks, we derive functional laws of large Ž . Ž . numbers FLLNs and functional central limit theorems FCLTs . The former support fluid approximations and the latter support diffusion refinements. The fluid limit in FLLN is the unique solution to a multidimensional autonomous ordinary differential equation with state-dependent reflection. The diffusion limit in FCLT is the unique strong solution to a stochastic differential equation with time-dependent reflection. Examples are provided that demonstrate how such approximations facilitate the design, analysis and optimization of various manufacturing, service, communication and other systems.
Solid lipid nanoparticle as an effective drug delivery system of a novel curcumin derivative: formulation, release in vitro and pharmacokinetics in vivo

Abstract Context Curcumin (Cur) has a short duration of action which limits its therapeutic efficacy. Carbonic acid 17-(1,5-dimethyl-hexyl)-10,13-dimethyl-2,3,4,7,8,9,10,11,12,13,14,15,16,17-tetradecahydro-1H-cyclopenta[a]phenanthren-3-yl ester 4-[7-(4-hydroxy-3-methoxy-phenyl)-3,5-dioxo-hepta-1,6-dienyl]-2-methoxy-phenyl ester (CUD), as a small molecule derivative of Cur with superior stability, has been developed in our laboratory. Objective CUD-loaded solid lipid nanoparticles (CUD-SLN) were prepared to prolong the duration of the drug action of Cur. Materials and methods CUD-SLN were prepared with Poloxamer 188 (F68) and hydrogenated soybean phospholipids (HSPC) as carriers, and the prescription was optimized. The in vitro release of CUD and CUD-SLN was investigated. CUD-SLN (5 mg/kg) was injected into Sprague Dawley (SD) rats to investigate its pharmacokinetic behaviour. Results CUD-SLN features high entrapment efficiency (96.8 ± 0.4%), uniform particle size (113.0 ± 0.8 nm), polydispersity index (PDI) (0.177 ± 0.007) and an appropriate drug loading capacity (6.2 ± 0.1%). Optimized CUD-SLN exhibited sustained release of CUD for about 48 h. Moreover, the results of the pharmacokinetic studies showed that, compared to Cur, CUD-SLN had a considerably prolonged half-life of 14.7 h, slowed its metabolism in vivo by 35.6-fold, and had an improved area under the curve (AUC0– t ) of 37.0-fold. Conclusions CUD-SLN is a promising preparation for the development of a small molecule derivative of Cur.
On a geometric framework for Lagrangian supermechanics

We re-examine classical mechanics with both commuting and anticommuting degrees of freedom. We do this by defining the phase dynamics of a general Lagrangian system as an implicit differential equation in the spirit of Tulczyjew. Rather than parametrising our basic degrees of freedom by a specified Grassmann algebra, we use arbitrary supermanifolds by following the categorical approach to supermanifolds.
Antibacterial Activity of Carotenoid from Bacterial Symbiont of the Soft Coral Sinularia sp. against MDR and MRSA Bacteria

study aimed to isolate and identify the soft coral symbiotic bacteria Sinularia sp. which has activity against pathogenic bacteria MDR ( Escherichia coli and Staphylococcus aureus ) and MRSA (methicillin-resistant Staphylococcus aureus ). Symbiotic bacteria isolated from the soft coral Sinularia sp. were collected from the waters of Panjang Island, Jepara, Central Java, Indonesia for antimicrobial activity. Carotenoid-containing bacteria were tested for antibacterial activity against various pathogenic bacteria, including MDR Escherichia coli , MDR Staphylococcus aureus , and MRSA and identifying antibiotic producer which is potential. The carotenoid extracts obtained were identified by UV-Vis spectrophotometer. The results showed that the P.Si 1 isolate was symbiotic bacterial from Sinularia sp. containing carotenoids. The molecular identification based on 16S rDNA showed that the most closely related species with P.Si 1 was Acinetobacter vivianii with only 80% of sequence identity. The results of the screening test showed that the average clear zone diameter for MDR E. coli antibacterial test at 2% concentration was 1.243cm, at 3% was 1.476cm, and at 4% it was 1.765cm, with a positive control of 2.325cm. The results of the antibacterial test against MDR S.aureus recorded average diameters at concentrations of 2% (1.534cm), 3% (1.678cm), 4% (1.885cm), with a positive control of 2.543cm. In addition, the antibacterial test against MRSA showed average diameters at concentrations of 2% (1.757cm), 3% (1.944cm), and 4% (2.247cm), with a positive control of 2.471cm.
The Arabic Patient-Rated Elbow Evaluation Questionnaire Has No Floor or Ceiling Effect, and The Items Load on A Three-Factor Structure Using Principal Component Analysis

Background: The Patient-Rated Elbow Evaluation (PREE) is a commonly used self-reported outcome measure in patients with elbow dysfunctions. Aims: The purpose of this study was to conduct an exploratory factor analysis (EFA) of the newly translated and cross-culturally adapted Patient-Rated Elbow Evaluation-Arabic version (PREE-AR). Also, to examine its floor and ceiling effects. Patients and Methods: An EFA using the principal component analysis (PCA) method was conducted on a sample of 88 participants with elbow pain. The oblique (nonorthogonal) rotation method was used. The Eigenvalue of 1.00 was used as a cutoff point to retain a factor. A scree plot was produced to visually examine the eigenvalues. Item loading on factors with a value greater than 0.4 was considered enough to show a satisfactory inclusion in the structure. A floor or a ceiling effect was considered to be present if more than 15% of participants scored at the lowest or the highest scores respectively. Results: The Kaiser-Meyer-Olkin (KMO) value of 0.891 with Bartlett’s test of sphericity (P<0.001) justified the appropriateness of running the factor analysis. The analysis produced a three-factor structure which accounted for 66% of the total variance. Most of the “function” items loaded on factor number1 with less loading of the “pain” items of the three-factor structure. All participants scored outside the 15% threshold of the highest and the lowest total score of the questionnaire. Conclusion: The newly adapted PREE-AR items are loaded on a three-factor structure and the questionnaire does not have a floor or a ceiling effect.
Markov chain simulation for multilevel Monte Carlo

This paper considers a new approach to using Markov chain Monte Carlo (MCMC) in contexts where one may adopt multilevel (ML) Monte Carlo. The underlying problem is to approximate expectations w.r. t. an underlying probability measure that is associated to a continuum problem, such as a continuous-time stochastic process. It is then assumed that the associated probability measure can only be used (e.g. sampled) under a discretized approximation. In such scenarios, it is known that to achieve a target error, the computational effort can be reduced when using MLMC relative to exact sampling from the most accurate discretized probability. The ideas rely upon introducing hierarchies of the discretizations where less accurate approximations cost less to compute, and using an appropriate collapsing sum expression for the target expectation. If a suitable coupling of the probability measures in the hierarchy is achieved, then a reduction in cost is possible. This article focused on the case where exact sampling from such coupling is not possible. We show that one can construct suitably coupled MCMC kernels when given only access to MCMC kernels which are invariant with respect to each discretized probability measure. We prove, under assumptions, that this coupled MCMC approach in a ML context can reduce the cost to achieve a given error, relative to exact sampling. Our approach is illustrated on a numerical example.
STABILIZATION OF A DYNAMIC WALKING GAIT SIMULATION

Forward dynamic simulations of human walking gait have typically simulated and analyzed a single step of the walking cycle, assuming symmetric and periodic gait. To enable simulations over many steps, a stabilizer is required to maintain the balance of the walking model, ideally mimicking the human balance control mechanism. This paper presents a feedback control system that stabilizes the torso orientation during a human walking gait dynamic simulation, enabling arbitrarily long simulations. The model is a two-dimensional mechanical simulation, in which the desired joint trajectories are defined as functions of time; the only external forces on the model are gravitational and ground reaction forces. Orientation or postural control is achieved by modulation of the rate at which lower limb joints move through angular trajectories. The controller design is based on a sequence of simple linear feedback controllers, each based on an intuitive control law. Controller parameters were determined iteratively using an optimization algorithm and repeated executions of the forward dynamics simulation to minimize control term errors. Results show the use of feedback control and joint speed modulation to be effective in maintaining balance for walking simulations of arbitrary length, allowing for analysis of steady-state walking.
On multivariate trace inequalities of Sutter, Berta and Tomamichel

We consider a family of multivariate trace inequalities recently derived by Sutter, Berta and Tomamichel. These inequalities generalize the Golden-Thompson inequality and Lieb's three-matrix inequality to an arbitrary number of matrices in a way that features complex matrix powers. We show that their inequalities can be rewritten as an $n$-matrix generalization of Lieb's original three-matrix inequality. The complex matrix powers are replaced by resolvents and appropriate maximally entangled states. We expect that the technically advantageous properties of resolvents, in particular for perturbation theory, can be of use in applications of the $n$-matrix inequalities, e.g., for analyzing the rotated Petz recovery map in quantum information theory.
Vessel trajectory compression algorithm based on MapReduce

With the development of shipping industry, vessels generate huge amount of vessel trajectory data in shipping production activities, which brings huge pressure to the storage and analysis of data. In order to improve the compression efficiency of a large amount of vessel trajectory data, a MapReduce-based vessel trajectory compression algorithm is proposed. The algorithm uses a twice-divided method to pre-process the vessel trajectory, dividing the original trajectory into several sub-trajectory segments. Based on the classical trajectory data compression algorithm, the algorithm introduces the MapReduce parallelization processing model and the processing idea of local processing combined with global optimization to compress each trajectory segment. In Map stage, the online compression algorithm is used to get the local optimal solution of the compressed trajectory, and in Reduce stage, the batched compression algorithm is used to globally optimize the merged compressed trajectory and get the final compressed trajectory. The experimental results show that the MapReduce-based vessel trajectory compression algorithm can reduce the impact caused by data skew and significantly improve the compression efficiency of vessel trajectory data. And for the compression of large-scale vessel trajectory data, the compression algorithm has obvious advantages over the traditional centralized trajectory compression algorithm.
A boosting ensemble learning based hybrid light gradient boosting machine and extreme gradient boosting model for predicting house prices

The implementation of tree‐ensemble models has become increasingly essential in solving classification and prediction problems. Boosting ensemble techniques have been widely used as individual machine learning algorithms in predicting house prices. One of the techniques is LGBM algorithm that employs leaf wise growth strategy, reduces loss and improves accuracy during training which results in overfitting. However, XGBoost algorithm uses level wise growth strategy which takes time to compute resulting in higher computation time. Nevertheless, XGBoost has a regularization parameter, implements column sampling and weight reduction on new trees which combats overfitting. This study focuses on developing a hybrid LGBM and XGBoost model in order to prevent overfitting through minimizing variance whilst improving accuracy. Bayesian hyperparameter optimization technique is implemented on the base learners in order to find the best combination of hyperparameters. This resulted in reduced variance (overfitting) in the hybrid model since the regularization parameter values were optimized. The hybrid model is compared to LGBM, XGBoost, Adaboost and GBM algorithms to evaluate its performance in giving accurate house price predictions using MSE, MAE and MAPE evaluation metrics. The hybrid LGBM and XGBoost model outperformed the other models with MSE, MAE and MAPE of 0.193, 0.285, and 0.156 respectively.
A dialogue about experiences of collaboration in design practice

OVERVIEW The mass digital adoption and rapid industry transformation have increased the number of things that need to be designed. In addition, Lean and Agile development demands faster ways to reflect and foresee impact. Designers are tackling more complex challenges, contexts, and systems. To assess these design challenges and decentralize the creative contribution, designers seek distributed knowledge, diverse and systemic thinking, adopting various collaborative practices, and more inclusive and holistic approaches to perform their work. The following sub-study supports the assessment of collaboration in Design in the broader term, contributing to the overall PhD study that aims to develop a collaborative and systemic method and toolkit to design technological and responsible service solutions. It shows a thematic analysis of a virtual focus group discussion where four designers discuss the past, present, and future collaboration in and through Design.
Impact of Dextran-Sodium-Sulfate-Induced Enteritis on Murine Cytomegalovirus Reactivation

(1) Background: Ulcerative colitis (UC) is an inflammatory bowel disease that causes inflammation of the intestines, which participates in human cytomegalovirus (HCMV) reactivation from its latent reservoir. CMV-associated colitis plays a pejorative role in the clinical course of UC. We took advantage of a model of chemically induced enteritis to study the viral reactivation of murine CMV (MCMV) in the context of gut inflammation. (2) Methods: Seven-week-old BALB/c mice were infected by 3 × 103 plaque-forming units (PFU) of MCMV; 2.5% (w/v) DSS was administered in the drinking water from day (D) 30 to D37 post-infection to induce enteritis. (3) Results: MCMV DNA levels in the circulation decreased from D21 after infection until resolution of the acute infection. DSS administration resulted in weight loss, high disease activity index, elevated Nancy index shortening of the colon length and increase in fecal lipocalin. However, chemically induced enteritis had no impact on MCMV reactivation as determined by qPCR and immunohistochemistry of intestinal tissues. (4) Conclusions: Despite the persistence of MCMV in the digestive tissues after the acute phase of infection, the gut inflammation induced by DSS did not induce MCMV reactivation in intestinal tissues, thus failing to recapitulate inflammation-driven HCMV reactivation in human UC.