Miracle-dz/UniFAR-FTUs huggingface dataset:
Frailty Improvement by Multicomponent Drug, Ninjin’Yoeito, in Mild Cognitive Impairment and Mild Alzheimer’s Disease Patients: An Open-Label Exploratory Study (FRAMINGO)

Background: Alzheimer’s disease (AD) and dementia have increasingly been conceived of as “complex diseases of aging”, determined by multiple, simultaneous, interacting pathophysiological processes. The condition known as frailty is a phenotype of aging and its comprehensive pathophysiology is thought to be closely related to the incidence of mild cognitive impairment (MCI) and the exacerbation of dementia. Objective: This study aimed to investigate the effect of the multicomponent drug, ninjin’yoeito (NYT), on frailty in MCI and mild AD patients. Methods: This study was an open-label trial. A total of 14 patients, including 9 with MCI and 5 with mild AD, were enrolled. Among them, 11 were frail while 3 were prefrail. NYT (6–9 g/day) was administered orally for 24 weeks, and assessments were carried out at baseline (week 0), and at 4, 8, 16, and 24 weeks. Results: In the primary endpoint, significant early improvements were observed in the anorexia scores according to the Neuropsychiatric Inventory after four weeks of treatment with NYT. The Cardiovascular Health Study score was significantly improved, and no frailty was observed after 24 weeks. The fatigue visual analog scale scores also significantly improved. The Clinical Dementia Rating and the Montreal Cognitive Assessment scores remained at baseline levels during the NYT treatment period. Conclusion: The results suggest that NYT may be effective in the treatment of frailty, especially for anorexia and fatigue, in both MCI and mild AD patients, which would be beneficial for the prognosis of dementia.
Distortion Risk Measures and Economic Capital

Abstract To provide incentive for active risk management, it is argued that a sound coherent distortion risk measure should preserve some higher degree stop-loss orders, at least the degree-three convex order. Such risk measures are called tail-preserving risk measures. It is shown that, under some common axioms and other plausible conditions, a tail-preserving coherent distortion risk measure identifies necessarily with the Wang right-tail measure or the expected value measure. This main result is applied to derive an optimal economic capital formula.
AttSum: A Deep Attention-Based Summarization Model for Bug Report Title Generation

Concise and precise bug report titles help software developers to capture the highlights of the bug report quickly. Unfortunately, it is common that bug reporters do not create high-quality bug report titles. Recent long short-term memory (LSTM)-based sequence-to-sequence models such as iTAPE were proposed to generate bug report titles automatically, but the text representation method and LSTM employed in such model are difficult to capture the accurate semantic information and draw the global dependencies among tokens effectively. This article proposes a deep attention-based summarization model (i.e., AttSum) to generate high-quality bug report titles. Specifically, the AttSum model employs the encoder.decoder framework, which utilizes the robustly optimized bidirectional-encoder-representations-from-transformers approach to encode the bug report bodies to capture contextual semantic information better, the stacked transformer decoder to automatically generate titles, and the copy mechanism to handle the rare token problem. To validate the effectiveness of AttSum, we conduct automatic and manual evaluations on 333563 “$< body, title>$” pairs of bug reports and perform a practical analysis of its ability to improve low-quality titles. The result shows that AttSum is superior to the state-of-the-art baselines by a substantial margin both on automatic evaluation metrics (e.g., by 3.4%–58.8% and 7.7%–42.3% in terms of recall-oriented understudy for gisting evaluation in F1 and bilingual evaluation understudy, separately) and three human-set modalities (e.g., by 1.9%–57.5%). Moreover, we analyze the impact of the training data size on AttSum and the results imply that our approach is robust enough to generate much better titles.
Uncertainty Principles for Wigner-Ville Distribution Associated with the Linear Canonical Transforms

The Heisenberg uncertainty principle of harmonic analysis plays an important role in modern applied mathematical applications, signal processing and physics community. The generalizations and extensions of the classical uncertainty principle to the novel transforms are becoming one of the most hottest research topics recently. In this paper, we firstly obtain the uncertainty principle for Wigner-Ville distribution and ambiguity function associate with the linear canonical transform, and then the -dimensional cases are investigated in detail based on the proposed Heisenberg uncertainty principle of the -dimensional linear canonical transform.
Flower colour and antioxidant activity of violas (Viola × wittrockiana) as edible flowers

ABSTRACT Edible flowers represent rich sources of nutritional and phytochemical compounds. Violas (Viola × wittrockiana) have been confirmed to be non-toxic as food products. Based on the wide variety of flower colours, major differences may exist in antioxidant concentrations among flowers of different colours. This study examined the differences in concentrations of antioxidant components in viola flowers of eight different colours: white, red, dark red, orange, yellow, light blue, light purple, and dark purple. Flower fresh weight, petal length, petal colour (measured using a chroma metre), ascorbic acid concentration, total anthocyanin concentration, total polyphenol concentration, and DPPH radical-scavenging activity were analysed. The violas used in this study had a wide range of colours, with different lightness and chroma values. Ascorbic acid, total anthocyanin, and total polyphenol concentrations were higher in red, dark red, and dark purple flowers. In contrast, these concentrations were lower in white and light-coloured flowers. The DPPH radical-scavenging activity was also lower in white and light-coloured flowers. Therefore, red, dark red, and dark purple flowers rather than white and light-coloured flowers of violas represent rich sources of antioxidant components and their consumption may provide various health benefits.
Nonlocal damage theory

In the usual local finite element analysis, strain softening causes spurious mesh sensitivity and incorrect convergence when the element is refined to vanishing size. In a previous continuum formulation, these incorrect features were overcome by the imbricate nonlocal continuum, which, however, introduced some unnecessary computational complications due to the fact that all response was treated as nonlocal. The key idea of the present nonlocal damage theory is to subject to nonlocal treatment only those variables that control strain softening, and to treat the elastic part of the strain as local. The continuum damage mechanics formulation, convenient for separating the nonlocal treatment of damage from the local treatment of elastic behavior, is adopted in the present work. The only required modification is to replace the usual local damage energy release rate with its spatial average over the representative volume of the material whose size is a characteristic of the material. Avoidance of spurious mesh .
How do convex bodies sit

§1. Every homogeneous convex body in IR(d ≥ 2) put to sit on a horizontal hyperplane finds a position of stable equilibrium. A cube has such 2d such positions and an ellipsoid with pairwise distinct axis–lengths has 2. How many positions of stable equilibrium have most convex bodies? In term ”most” is understood in the Baire category sense. For various other results on most convex bodies, see [3].
Oscillatory instability in the heterostructure hot‐electron diode

Vertical electrical transport in the heterostructure hot‐electron diode is considered theoretically. We present a simple dynamical model which consistently explains the measured S‐shaped negative differential conductivity in the current‐voltage characteristics. The model predicts a new type of self‐sustained 60 GHz voltage oscillations between tunneling and thermionic emission if the sample is driven by a dc voltage source having a resistor in series and a capacitor in parallel.
Hospital Outcome of Preterm Babies at the Regional Hospital Limbe: A 4-Year Retrospective Study

Background: Globally, preterm birth and its complications have become major public health problems as it is a major determinant of neonatal morbidity and mortality with long-term adverse health consequences. It is the leading cause of neonatal and under-5 mortality globally. In Cameroon, especially in the South West Region, there is a paucity of data as concerns preterm birth and its related morbidities and outcome. Objectives: Our objective was to determine the prevalence and hospital outcome of preterm babies at the Regional Hospital Limbe. Methods: A hospital-based cross-sectional study with a retrospective review of files of preterm babies admitted in the neonatology unit from the 1st January 2017 to 31st December 2020. A structured data collection sheet was used to collect information from the files. Information obtained included independent variables (gestational age at birth, gender, birth weight, hospital complications during admission, treatment received and duration of admission) and dependent variables (dead or discharge). Relationship between dependent and independent variables was tested using Pearson Chi-square. Multivariate logistic regression was used to identify factors and independent associations. Result: Preterm admissions constituted 16.5% of the total admissions with a male to female ratio of 1:1.2. The common morbidities were respiratory distress 132(49.1%), hypothermia 72(26.8%), anaemia 70(26.0%), infection 65(24.2%) and jaundice 63(23.4%). The mortality rate was 31.8%. Preterm babies who had congenital malformation (AOR: 25.39;95%CI:1.80-356.38), apnoea (AOR:6.36;95%CI:1.49-27.09), respiratory distress (AOR:6.15;2.75-13.77) and anaemia (AOR:2.19;95%CI:1.07-4.50) were more likely to die compared to those who did not have these morbidities. Also, male preterm babies (AOR:2.72;95%CI:1.35-5.48) were more likely to die than their female counterparts. Conclusion: Preterm babies constituted a significant percentage of neonatal admissions at the Regional Hospital Limbe with the most frequent complications being respiratory distress, hypothermia, anaemia, infection and jaundice. The mortality rate was high, with more preterm babies dying from congenital malformation, apnoea, respiratory distress, and anaemia were strongly associated with mortality.
Fixed Point Theorem and Related Nonlinear Analysis by the Best Approximation Method in p-Vector Spaces

Abstract The goal of this paper is to develop some new and useful tools for nonlinear analysis by applying the best approximation approach for classes of semiclosed 1-set contractive set-valued mappings in locally p-convex or p-vector spaces for In particular, we first develop general fixed point theorems for both set-valued and single-valued condensing mappings which provide answers to the Schauder conjecture in the affirmative way under the setting of (locally p-convex) p-vector spaces, then the best approximation results for upper semi-continuous and 1-set contractive set-valued are established, which are used as tools to establish some new fixed points for non-self set-valued mappings with either inward or outward set conditions under various situations. These results unify or improve corresponding results in the existing literature for nonlinear analysis.
The effect of COVID-19 on managerial leadership style within Australian public sector organizations

This study investigates the impact of COVID-19 pandemic on leadership styles within Australian public sector organizations during the COVID-19 pandemic. A qualitative methodology was employed for this research consisting of semi-structured interviews with 50 managers. The study results suggest the pandemic affected managers’ leadership style, managers’ and employees’ emotions, stress and anxiety, and organizational performance and productivity. Changes in leadership style to incorporate being supportive, informative, and motivational to match the change in situation were found to be effective. This addresses a gap in the literature by identifying these three leadership styles as being important for employee support during the pandemic.
Validity of Normative Volumetric Estimates from Open Access Software in Amnestic Mild Cognitive Impairment

Background Neurodegeneration in Alzheimer’s disease (AD) is typically assessed through brain MRI. Although proprietary software can provide normative estimates of regional atrophy, such tools can be cost-prohibitive for research settings. Free software for generating normative estimates has recently been released but has yet to be validated in the context of amnestic mild cognitive impairment (aMCI). Objectives Determine whether normative morphometric estimates generated from open-source software replicate established patterns of neurodegeneration in aMCI, and whether these metrics correlate with episodic memory performance. Design Observational study of brain MRI and cognition in aging and aMCI with two identical study visits occurring approximately 1.2 years apart. Setting Participants were recruited from the local community and outpatient clinical settings. Participants Adults ages 60–85 with aMCI (n = 25) and cognitively normal controls (CN; n = 74). A subset returned for follow-up (aMCI n = 11, CN n = 52). Measurements Participants completed brain MRI and two neuropsychological tests of verbal episodic memory. FreeSurfer v6.0 and Normative Morphometry Image Statistics were used to generate normative morphometric estimates for AD-relevant regions (hippocampus, parahippocampus, entorhinal cortex, amygdala) and control regions (cuneus, lingual gyrus, pericalcarine gyrus), adjusting for age, sex, head size, scanner manufacturer, and field strength. We tested for baseline group differences in ROI volumes and memory and assessed their within-group associations. We also evaluated changes in ROI volumes over time and tested whether these changes corresponded to declines in memory. Results At baseline, the aMCI group exhibited poorer memory and smaller volumes in AD-relevant regions than the CN group. There were no group differences in control region volumes. Memory was associated with volumes in AD-relevant regions in the aMCI group only. The aMCI group exhibited greater declines than the CN group in hippocampal volume (17% vs. 8% annual decline) and entorhinal volume (54% vs. 5% annual decline). Decrease in hippocampal volume was marginally associated with decline in memory for the aMCI group. Conclusions Normative morphometric values generated from freely available software demonstrated expected patterns of group differences in AD-related volumes and associations with memory. Significant effects were localized to AD-relevant brain regions and only occurred in the aMCI group. These findings support the validity of these free tools as reliable and cost-effective alternatives to proprietary software for use in research settings.
Omicron in Infants—Respiratory or Digestive Disease?

The Omicron variant of SARS-CoV-2 has caused a large number of cases and hospitalizations in the pediatric population. Infants due to their age are susceptible to viral infections that may have a worse prognosis. Therefore, the aim of the current study has been to characterize the clinical features and the outcome of infants hospitalized with confirmed SARS-CoV-2 infection during the Omicron wave. We conducted a retrospective study of all consecutive infants hospitalized with symptomatic COVID-19 and no other co-infections, from January to September 2022 in one of the largest infectious diseases hospitals from Bucharest, Romania. A total of 613 infants were included in the analysis. The median age was 5 months (IQR: 3, 8 months). The clinical features were dominated by fever (96.4%), cough (64.8%) and loss of appetite (63.3%), and overall, respiratory symptoms were the most numerous (76.0%). Infants between 1-3 months old had a 1.5-fold increased risk of elevated alanine aminotransferase (ALT) values, and a longer length of hospitalization as compared to older infants. Infants between 7-9 months of age had 1.5-fold higher odds of loss of appetite, 1.7-fold more frequent cough and 1.6-fold more frequent digestive symptoms compared to infants in other age groups. The presence of digestive symptoms increased the probability of hepatic cytolysis (increased ALT) by 1.9-fold. Continued monitoring of COVID-19 among infants is very necessary, given the progressive character of SARS-CoV-2, in order to take correct and rapid therapeutic measures and to adapt to clinical changes driven by viral variant change.
Inflation and singularity prevention in a model for extended-object-dominated cosmology

The authors present a geometric procedure which generates a class of cosmological models of deflationary type, i.e. models in which a primordial phase of accelerated expansion evolves smoothly towards the final decelerating state of standard cosmology. They also discuss the possibility that the initial de Sitter geometry, obtained in the context of these models, may be physically interpreted as the consequences of an early phase in which the contribution of finite-size objects becomes dominant.
SAGN: Semantic-Aware Graph Network for Remote Sensing Scene Classification

The scene classification of remote sensing (RS) images plays an essential role in the RS community, aiming to assign the semantics to different RS scenes. With the increase of spatial resolution of RS images, high-resolution RS (HRRS) image scene classification becomes a challenging task because the contents within HRRS images are diverse in type, various in scale, and massive in volume. Recently, deep convolution neural networks (DCNNs) provide the promising results of the HRRS scene classification. Most of them regard HRRS scene classification tasks as single-label problems. In this way, the semantics represented by the manual annotation decide the final classification results directly. Although it is feasible, the various semantics hidden in HRRS images are ignored, thus resulting in inaccurate decision. To overcome this limitation, we propose a semantic-aware graph network (SAGN) for HRRS images. SAGN consists of a dense feature pyramid network (DFPN), an adaptive semantic analysis module (ASAM), a dynamic graph feature update module, and a scene decision module (SDM). Their function is to extract the multi-scale information, mine the various semantics, exploit the unstructured relations between diverse semantics, and make the decision for HRRS scenes, respectively. Instead of transforming single-label problems into multi-label issues, our SAGN elaborates the proper methods to make full use of diverse semantics hidden in HRRS images to accomplish scene classification tasks. The extensive experiments are conducted on three popular HRRS scene data sets. Experimental results show the effectiveness of the proposed SAGN. Our source codes are available at https://github.com/TangXu-Group/SAGN.
Latent Profiles of Responding on the Massachusetts Youth Screening Instrument-2 Subscale Scores by Race/Ethnicity among Juvenile Justice-Involved Boys and Girls

The Massachusetts Youth Screening Instrument (MAYSI-2) is one of the most widely utilized screening measures for detecting mental health concerns among youth entering juvenile detention settings. Previous research has demonstrated clear patterns of sex differences in the severity of mental health symptoms among detained boys and girls. However, few studies have examined potential racial or ethnic differences in MAYSI-2 scores, which is a significant limitation. This study examined sex and racial/ethnic differences in patterns of youth responses on the MAYSI-2. Data were collected from a total of 5417 youth detained in a short-term detention facility in the Mountain West. Results of latent profile analyses demonstrated that, among both boys and girls, youths’ racial/ethnic identity was associated with distinct patterns of responding on the MAYSI-2. These findings have implications for informing screening in the juvenile justice system and increasing recognition and response to ethnic/racial and sex differences among detained youth.
A quantum uncertainty relation based on Fisher's information

We explore quantum uncertainty relations involving the Fisher information functionals Ix and Ip evaluated, respectively, on a wavefunction Ψ(x) defined on a D-dimensional configuration space and the concomitant wavefunction on the conjugate momentum space. We prove that the associated Fisher functionals obey the uncertainty relation IxIp ⩾ 4D2 when either Ψ(x) or is real. On the other hand, there is no lower bound to the above product for arbitrary complex wavefunctions. We give explicit examples of complex wavefunctions not obeying the above bound. In particular, we provide a parametrized wavefunction for which the product IxIp can be made arbitrarily small.
Edge Video Analytics With Adaptive Information Gathering: A Deep Reinforcement Learning Approach

With growing popularity of enormous public safety and transportation infrastructure cameras, there are increasing demands for automatic mobile video analytics. The emerging multi-access edge computing (MEC) technology has been recently applied to improve the accuracy-latency tradeoff of mobile video analytics. In this paper, we study an MEC-enabled multi-device video analytics system and formulate the problem as a Markov decision process (MDP) to meet two practical challenges: i) the absence of ground truth in real-time and ii) the content-varying degradation-accuracy relation. In particular, we aim to design an online joint frame degradation and bandwidth allocation algorithm with the time-varying function and limited feedback from each device. Thanks to the MDP formulation and $n$ -step return technique, the long-term goal offers adaptive information gathering and thus improves the average accuracy and latency. For sample efficiency, we decompose the MDP problem into discrete degradation adaptation subproblems and continuous bandwidth allocation subproblems. Based on the decomposition, we propose a deep reinforcement learning (DRL) based framework, referred to as DBAG, to solve the decomposed subproblems. DBAG integrates model-based optimization and model-free DRL to solve the MDP problem with a discrete-continuous hybrid action space. Under various network setups and public datasets, DBAG greatly improves the accuracy-latency tradeoff.
A superconducting electron cyclotron resonance source for the L.N.S.

At the ‘‘Laboratorio Nazionale del Sud’’ (L.N.S.) the K‐800 Superconducting Cyclotron (C.S.) is under construction and by the end of 1992 it will be completed in order to work as a booster for the 15‐MV Tandem. With this facility fully stripped light ions will reach 100 MeV/amu, while the heaviest ions are foreseen to get 16 MeV/amu. In order to increase both charge states and intensities, mostly for the heaviest ions, of the beams injected into the C.S. a project for a superconducting electron cyclotron resonance (ECR) ion source has been developed and it will be carried out as a joint venture between the L.N. S. and the C.E. N. of Grenoble. This source will be the first superconducting ECR source to be coupled to a superconducting cyclotron in Europe, and it is particularly suited to exploit the capabilities of our K‐800 superconducting cyclotron. The source will be working at 14.5 GHz and the confinement will be performed by superconducting magnets able to give 1.3 T on the plasma chamber wall, permittin.