Miracle-dz/UniFAR-FTUs huggingface dataset:
A Regulatory Network Analysis of the Importance of USP15 in Breast Cancer Metastasis and Prognosis

Background Ubiquitin-specific protease15(USP15), is the 16th identified protease in the USP family and is a key protein in tumorigenesis. However, the predictive value and regulatory mechanism of USP15 in breast cancer are unclear. Methods The GEPIA, UALCAN, GeneMANIA, and STRING databases were applied to explore the expression of USP15 in breast cancer and associated proteins. In addition, the TIMER database was evaluated for immune infiltration patterns. Moreover, protein immunoblotting assay, cell scratching assay, small compartment invasion assay, 3D stromal gel assay, immunoprecipitation assay, and immunohistochemistry (IHC) were used to USP15 regulatory mechanisms in breast cancer. Results In BRCA, several databases, including GEPIA and UALCAN, describe the upregulation of total protein levels and USP15 phosphorylation. In addition, the expression of USP15 was significantly correlated with gender and clinical stage. Overall survival (OS) was lower in patients with high USP15 expression. Functional network analysis showed that USP15 is involved in tumor-associated pathways, DNA replication, and cell cycle signaling through TGFβRI. In addition, USP15 expression was positively correlated with immune infiltration, including immune score, mesenchymal score, and several tumor-infiltrating lymphocytes (TIL). In addition, IHC results further confirmed the high expression of USP15 in breast cancer and its prognostic potential. Conclusions These findings demonstrate that high USP15 expression indicates poor prognosis in BRCA and reveal potential regulatory networks and the positive relationship with immune infiltration. Thus, USP15 may be an attractive predictor for BRCA.
Using Mobile Mental Health Apps: An Overview

Abstract Libraries are in the business of reviewing and recommending resources to patrons. One vital emerging resource is mobile mental health apps. Although these resources are new to the market and sometimes considered controversial, it is essential for libraries to at least be informed about their benefits, challenges, and future opportunities. This article will give an overview of these resources, leaving it up to patrons and other librarians to decide if they are appropriate to use.
THE HYPHI PROJECT: HYPERNUCLEAR SPECTROSCOPY WITH STABLE HEAVY ION BEAMS AND RARE ISOTOPE BEAMS AT GSI AND FAIR

The HypHI collaboration aims to perform a precise hypernuclear spectroscopy with stable heavy ion beams and rare isotope beams at GSI and FAIR in order to study hypernuclei at extreme isospin, especially neutron rich hypernuclei to look insight hyperon-nucleon interactions in the neutron rich medium, and hypernuclear magnetic moments to investigate baryon properties in the nuclei1,2. We are currently preparing for the first experiment with 6Li and 12C beams at 2 A GeV to demonstrate the feasibility of a precise hypernuclear spectroscopy by identifying $_\Lambda^3 {\rm{H}}$, $_\Lambda^4 {\rm{H}}$ and $_\Lambda^5 {\rm{He}}^{2,3} $. The first physics experiment on these hypernuclei is planned for 2009. In the present document, an overview of the HypHI project and the details of this first experiment will be discussed.
Multifunctional Nanosnowflakes for T1-T2 Double-Contrast Enhanced MRI and PAI Guided Oxygen Self-Supplementing Effective Anti-Tumor Therapy

Introduction Accurate tumor diagnosis is essential to achieve the ideal therapeutic effect. However, it is difficult to accurately diagnose cancer using a single imaging method because of the technical limitations. Multimodal imaging plays an increasingly important role in tumor treatment. Photodynamic therapy (PDT) has received widespread attention in tumor treatment due to its high specificity and controllable photocytotoxicity. Nevertheless, PDT is susceptible to tumor microenvironment (TME) hypoxia, which greatly reduces the therapeutic effect of tumor treatment. Methods In this study, a novel multifunctional nano-snowflake probe (USPIO@MnO2@Ce6, UMC) for oxygen-enhanced photodynamic therapy was developed. We have fabricated the honeycomb-like MnO2 to co-load chlorin e6 (Ce6, a photosensitizer) and ultrasmall superparamagnetic iron oxide (USPIO, T1-T2 double contrast agent). Under the high H2O2 level of tumor cells, UMC efficiently degraded and triggered the exposure of photosensitizers to the generated oxygen, accelerating the production of reactive oxygen species (ROS) during PDT. Moreover, the resulting USPIO and Mn2+ allow for MR T1-T2 imaging and transformable PAI for multimodal imaging-guided tumor therapy. Results TEM and UV-vis spectroscopy results showed that nano-snowflake probe (UMC) was successfully synthesized, and the degradation of UMC was due to the pH/ H2O2 responsive properties. In vitro results indicated good uptake of UMC in 4T-1 cells, with maximal accumulation at 4 h. In vitro and in vivo experimental results showed their imaging capability for both T1-T2 MR and PA imaging, providing the potential for multimodal imaging-guided tumor therapy. Compared to the free Ce6, UMC exhibited enhanced treatment efficiency due to the production of O2 with the assistance of 660 nm laser irradiation. In vivo experiments confirmed that UMC achieved oxygenated PDT under MR/PA imaging guidance in tumor-bearing mice and significantly inhibited tumor growth in tumor-bearing mice, exhibiting good biocompatibility and minimal side effects. Conclusion The multimodal imaging contrast agent (UMC) not only can be used for MR and PA imaging but also has oxygen-enhanced PDT capabilities. These results suggest that UMC may have a good potential for further clinical application in the future.
Forest Type and Site Conditions Influence the Diversity and Biomass of Edible Macrofungal Species in Ethiopia

Ethiopian forests are rich in valuable types of non-wood forest products, including mushrooms. However, despite their nutritional, economic, and ecological importance, wild edible mushrooms have been given little attention and are rarely documented in Ethiopia. In this study, we assessed mushroom production levels in natural and plantation forests and the influence of climate and environmental variables on mushroom production. Sporocarps were sampled weekly from July to August 2019 at a set of permanent plots (100 m2) in both forest systems. We analyzed 63 plots to quantify sporocarp species’ richness and fresh weight as well as to elucidate the degree of influence of forest types and site conditions, including soil and climate. Morphological analyses were used to identify fungi. In total, we recorded 64 wild edible fungal species belonging to 31 genera and 21 families from the plots established in the natural and plantation forests. A significantly greater total number of edible fungi were collected from natural forests (n = 40 species) than from plantations. Saprotrophs (92.19%) were the dominant guild whereas ectomycorrhizal fungi represented only 6.25% of species. Ecologically and economically important fungal species such as Agaricus campestroides, Tylopilus niger, Suillus luteus, Tricholoma portentosum, and Morchella americana were collected. The sporocarp yield obtained from plantation forests (2097.57 kg ha−1 yr–1) was significantly greater than that obtained from natural forests (731.18 kg ha−1 yr–1). The fungal community composition based on sporocarp production was mainly correlated with the organic matter, available phosphorus, and total nitrogen content of the soil, and with the daily minimum temperature during collection. Accordingly, improving edible species’ richness and sporocarp production by maintaining ecosystem integrity represents a way of adding economic value to forests and maintaining biological diversity, while providing wood and non-wood forest products; we propose that this approach is imperative for managing Ethiopian forests.
Random walk, sequential analysis and related topics : a festschrift in honor of Yuan-Shih Chow, Fudan University, Shanghai, China, 18-19 July 2004

Maximizing Expected Value with Two Stage Stopping Rules (D Assaf et al.) A Study of Inverses of Thinned Renewal Processes (W-J Huang & C-D Huang) On Dirichlet Multinomial Distributions (R W Keener & W B Wu) The Optimal Stopping Problem for Sn/n and Its Ramifications (T L Lai & Y-C Yao) Bold Play and the Optimal Policy for Vardi's Casino (L Shepp) The Upper Limit of a Normalized Random Walk (C-H Zhang) Analysis of a Sequence of Dependent 2 x 2 Tables (S G Kou & Z Ying) A New Test of Symmetry about an Unknown Median (W Miao et al.) The Logistic Distribution and a Rank Test for Non-Transitivity (B M Brown et al.) and other papers.
A Machine Learning-Based Technique with Intelligent WordNet Lemmatize for Twitter Sentiment Analysis

Laterally with the birth of the Internet, the fast growth of mobile strategies has democratised content production owing to the widespread usage of social media, resulting in a detonation of short informal writings. Twitter is microblogging short text and social networking services, with posted millions of quick messages. Twitter analysis addresses the topic of interpreting users’ tweets in terms of ideas, interests, and views in a range of settings and fields. This type of study can be useful for a variation of academics and applications that need knowing people’s perspectives on a given topic or event. Although sentiment examination of these texts is useful for a variety of reasons, it is typically seen as a difficult undertaking due to the fact that these messages are frequently short, informal, loud, and rich in linguistic ambiguities such as polysemy. Furthermore, most contemporary sentiment analysis algorithms are based on clean data. In this paper, we offers a machine-learning-based sentiment analysis method that extracts features from Term Frequency and Inverse Document Frequency (TF-IDF) and needs to apply deep intelligent wordnet lemmatize to improve the excellence of tweets by removing noise. We also utilise the Random Forest network to detect the emotion of a tweet. To authenticate the proposed approach performance, we conduct extensive tests on publically accessible datasets, and the findings reveal that the suggested technique significantly outperforms sentiment classification in multi-class emotion text data.
Comparison of Incremental Shuttle Walking Test, 6-Minute Walking Test, and Cardiopulmonary Exercise Stress Test in Patients with Myocardial Infarction

Background This study aimed to analyze the correlations among peak oxygen uptake (VO2) in cardiopulmonary exercise test (CPX), incremental shuttle walking test (ISWT), and 6-minute walking test (6MWT) distances in patients with myocardial infarction (MI). Additionally, we aimed to determine the relationship between the maximum heart rate (HRmax) and the rate of perceived exertion (RPE) among the tests and compare the changes in heart rate to verify the clinical benefit of the submaximal stress test. Material/Methods We analyzed the correlation by using the ISWT and 6MWT at 30-min intervals after 24 h of CPX in patients with MI. The differences in HRmax and RPE between the tests were also compared. Additionally, changes in heart rate were analyzed using descriptive statistics. Results The ISWT distance was more strongly correlated with peak VO2 (r=.823: 95% CI, 0.681–0.910) than was 6MWT (r=0.776: 95% CI, 0.683–0.870). HRmax in the CPX demonstrated a significant correlation with that in the ISWT and 6MWT (P<0.05), with the ISWT (r=0.815: 95% CI, 0.451–0.996) having a stronger correlation than the 6MWT (r=0.664: 95% CI, 0.146–0.911). The value of RPE was significantly different (P<0.05); however, there was no significant correlation. Changes in heart rate in the 6MWT plateaued after the initial increase, while the heart rate in the ISWT and CPX increased gradually. Conclusions We recommend the ISWT as a submaximal exercise test to evaluate exercise capacity in patients with MI.
On the complexity of stable matchings with and without ties

This thesis concerns the complexity analysis of certain matching problems. The description of each of these matching problems consists of a group of agents, and, for each agent, a preference list over the agents with whom the agent can be matched. A solution to the problem is a matching that has the property that no pair of agents that are eligible for each other, prefer each other to their assigned mates. A matching that satisfies this property is called a stable matching. The variants of this problem that will be dealt with are: (1) The marriage problem: matching of men and women into couples; (2) The roommate problem: matching of students into rooms of two occupants; (3) The intern assignment problem: the assignment of interns to hospital positions; (4) The intern assignment problem with couples: same problem as (3) except that some of the interns are married couples. These matching problems can be defined to allow or disallow ties in the preference lists. When ties are allowed, stability is defined as the absence of an unmatched pair that strictly prefer each other to their assigned mates. This thesis will show that the option of allowing ties in the preference lists can significantly affect the computational complexity of the problems. It will be shown that, when ties are allowed, the roommate problem and the intern assignment problem with couples are NP-complete. In contrast, the roommate problem without ties, is solvable in polynomial time. The computational complexity of the intern-hospital assignment problem with couples is unresolved. A variant of the marriage problem that allows ties will be shown to be logspace P-complete. Finally, the intern-hospital assignment problem with couples, but without ties, will be shown to be logspace P-hard.
Universality of nucleon-nucleon short-range correlations: two-nucleon momentum distributions in few-body systems

Using realistic wave functions, the proton-neutron and proton-proton momentum distributions in $^3He$ and $^4He$ are calculated as a function of the relative, $k_{rel}$, and center of mass, $K_{CM}$, momenta, and the angle between them. For large values of ${k}_{rel}\gtrsim 2\,\,fm^{-1}$ and small values of ${K}_{CM} \lesssim 1.0\,\,fm^{-1}$, both distributions are angle independent and decrease with increasing $K_{CM}$, with the $pn$ distribution factorizing into the deuteron momentum distribution times a rapidly decreasing function of $K_{CM}$, in agreement with the two-nucleon (2N) short range correlation (SRC) picture. When $K_{CM}$ and $k_{rel}$ are both large, the distributions exhibit a strong angle dependence, which is evidence of three-nucleon (3N) SRC. The predicted center-of-mass and angular dependence of 2N and 3N SRC should be observable in two-nucleon knock-out processes $A(e,e'pN)X$.
Older adults who prefer aging in place and corresponding challenges to social workers: the impact of smartphone-based interventions

ABSTRACT This paper reports a study on the impact of a smartphone meditation app (M-App) in building resilience and competencies among social workers with aging in place (AIP) initiatives. Compared to a control group who used the leisure app (L-App), M-App users reported greater resilience and gerontological social work competencies 6 months posttest (T2). Women social workers, Christians, who specialized in home-based care, and whose core clientele comprised older adults with acquired disability and long-term illness, reported greater resilience at T2. Women social workers and those who specialized in home-based care exhibited greater gerontological competencies at T2. Disciplined M-App usage and self-practice mediated the association between socio-demographic moderators and outcomes. Clients of women and Christian social workers, home-based care specialists and those who diligently adhered to the intervention reported higher satisfaction. The interesting finding was that this satisfaction was reported by Christian clients and those who lived with family members as compared to Hindu and Muslim clients and those who lived alone with formal caregivers. For gerontological social workers with AIP initiatives, the M-App could be used in a continuing education training with some refinements for men, non-Christian social workers and engaged in AIP programs through community and neighborhood support practice.
Voice Reminder Assistant based on Speech Recognition and Speaker Identification using Kaldi

A user often wants to do some tasks which don’t need a specific time to complete but are important, due to busy routines and possible memory loss problems user forgets to accomplish such tasks or delay them to manage later. The task may be about conveying some information to a person when the user meets him, sort things in his wardrobe, or locker, etc. A user can meet the person anywhere or anytime so he cannot set a reminder for a specific time. Such tasks can be accomplished if the user has a reminder system, which reminds him about the tasks at runtime. In this paper, we present a reminder system based on speech recognition & speaker identification; personal voice- controlled aid for the user to remind about the tasks when some specific keyword/phrase is spoken by the user or user reaches a specific location so that the user can accomplish the important time independent tasks without being time-bound. The specified keyword can be anything, person name, place name, and any phrase. The user can speak to the assistant to remind about some task without un- locking his mobile or opening the application for a specific keyword/phrase & location. When the specific keyword/phrase is spoken or user reaches the specific location the assistant also speaks and reminds the user about the task. Voice reminder assistant supports Text-Independent Speaker Identification unlike other voice assistants already available.
THE INFLUENCE OF MAGNETIC FIELD GEOMETRY ON THE FORMATION OF CLOSE-IN EXOPLANETS

Approximately half of Sun-like stars harbor exoplanets packed within a radius of ∼0.3 au, but the formation of these planets and why they form in only half of known systems are still not well understood. We employ a one-dimensional steady-state model to gain physical insight into the origin of these close-in exoplanets. We use Shakura & Sunyaev α values extracted from recent numerical simulations of protoplanetary disk accretion processes in which the magnitude of α, and thus the steady-state gas surface density, depend on the orientation of large-scale magnetic fields with respect to the disk’s rotation axis. Solving for the metallicity as a function of radius, we find that for fields anti-aligned with the rotation axis, the inner regions of our model disk often fall within a region of parameter space that is not suitable for planetesimal formation, whereas in the aligned case, the inner disk regions are likely to produce planetesimals through some combination of streaming instability and gravitational collapse, though the degree to which this is true depends on the assumed parameters of our model. More robustly, the aligned field case always produces higher concentrations of solids at small radii compared to the anti-aligned case. In the in situ formation model, this bimodal distribution of solid enhancement leads directly to the observed dichotomy in exoplanet orbital distances.
The role of r‐mode damping in the thermal evolution of neutron stars

The thermal evolution of neutron stars (NSs) is investigated through coupling with the evolution of r-mode instability, which is described by a second-order model. The heating effect due to shear viscous damping of the r modes enables us to understand the high temperature of two young pulsars (PSR B0531+21 and RX J0822-4300) in the framework of the simple neutron-proton-electron (npe) NS model, without superfluidity or exotic particles. Moreover, the light curves predicted by the model within an acceptable parameter regime probably cover all of the young and middle-aged pulsars in the Ig T ∞ s -lg t panel, and the artificially strong p superfluidity invoked in some early works is not needed here. Additionally, by considering the radiative viscous damping of the r modes, a surprising extra cooling effect is found that can even exceed the heating effect at times, although it plays a negligible role in the thermal history.
Connection between rotation and miscibility in a two-component Bose-Einstein condensate

A two-component Bose-Einstein condensate rotating in a toroidal trap is investigated. The topological constraint depends on the density distribution of each component along the circumference of the torus, and therefore the quantization condition on the circulation can be controlled by changing the miscibility using the Feshbach resonance. We find that the system exhibits a variety of dynamics depending on the initial angular momentum when the miscibility is changed.
3D simulations of pillar formation around HII regions: the importance of shock curvature

Aims. Radiative feedback from massive stars is a key process for understanding how HII regions enhance or inhibit star formation in pillars and globules at the interface with molecular clouds. We aim to contribute by modelling the interactions between ionization and gas clouds to better understand the processes at work. We study in detail the impact of modulations on the cloud-HII region interface and density modulations inside the cloud. Methods. We ran 3D hydrodynamical simulations based on Euler equations coupled with gravity using the HERACLES code. We implemented a method to solve ionization/recombination equations and took into account typical heating and cooling processes at work in the interstellar medium that are caused by ionization/recombination physics. Results. UV radiation creates a dense shell compressed between an ionization front and a shock ahead. Interface modulations produce a curved shock that collapses on itself, which leads to stable growing pillar-like structures. The narrower the initial interface modulation, the longer the resulting pillar. We interpret pillars resulting from density modulations in terms of the ability of these density modulations to curve the shock ahead of the ionization front. Conclusions. The shock curvature is a key process for understanding the formation of structures at the edge of HII regions. Interface and density modulations at the edge of the cloud have a direct impact on the morphology of the dense shell during its formation. Deeper inside the cloud, structures have less influence because of the high densities reached by the shell during its expansion.
MODELLING THE COMMUNITY ADAPTIVE BEHAVIOUR TOWARDS AIR POLLUTION: A CONFIRMATORY FACTOR ANALYSIS WITH PLS-SEM

Air pollution has become a serious threat to public health due to the rapid economic development globally, and urban air pollution is thought to cause 1.3 million deaths annually. Urban areas have a huge potential for human exposure to the severity of air pollution and health concerns. Therefore, it is essential to advance our understanding of the factors influencing behaviour to provide compelling evidence for successful behavioural interventions and guidelines. Doing so will increase the practicality of public adaptation to the guidelines. Yet, little is known about the adaptive behaviour toward air pollution. This study aims to establish a predictive model of factors impacting the adaptative behaviour of urban Malaysians toward air quality. A deductive theory-generating research approach and a correlational research design were used in the development of a new ABR model. The following seven factors were tested: values (VAL), attitude (ATT), perceived vulnerability (PVL), perceived severity (PSV), self-efficacy (SEF), response efficacy (REF), and risk perception (RPN). Klang Valley served as the study area, and a multi-stage cluster sampling technique was used to select the respondents (n = 440) of a face-to-face questionnaire survey. In conjunction with PLS-SEM analyses, confirmatory factor analysis (CFA) was used to evaluate the structural models. The results demonstrated that PLS-SEM CFA is suitable for building a reliable structural model to examine community adaptive behaviour.