Miracle-dz/UniFAR-FTUs huggingface dataset:
Revealing quantum effects in bosonic Josephson junctions: a multi-configuration atomic coherent state approach

The mean-field approach to two-site Bose–Hubbard systems is well-established and leads to non-linear classical equations of motion for population imbalance and phase difference. It can, for example, be based on the representation of the solution of the time-dependent Schrödinger equation either by a single Glauber state or by a single atomic (SU(2)) coherent state [S. Wimberger et al., Phys. Rev. A 103, 023326 (2021)]. We demonstrate that quantum effects beyond the mean-field approximation are easily uncovered if, instead, a multiconfiguration ansatz with a few time-dependent SU(2) basis functions is used in the variational principle. For the case of plasma oscillations, the use of just two basis states, whose time-dependent parameters are determined variationally, already gives a good qualitative agreement of the phase space dynamics with numerically exact quantum solutions. In order to correctly account for more non-trivial effects, like macroscopic quantum self-trapping, moderately more basis states are needed. For the onset of spontaneous symmetry breaking, however, a multiplicity of 2 gives a significant improvement already. In any case, the number of variational trajectories needed for good agreement with the full quantum results is orders of magnitude smaller than that in the semi-classical case, which is based on multiple mean-field trajectories.
HOOK3 is a scaffold for the opposite-polarity microtubule-based motors cytoplasmic dynein and KIF1C

The unidirectional and opposite-polarity microtubule-based motors, dynein and kinesin, drive long-distance intracellular cargo transport. Cellular observations support the existence of mechanisms to couple opposite polarity motors: in cells some cargos rapidly switch directions and kinesin motors can be used to localize dynein. We recently identified an interaction between the cytoplasmic dynein-1 activating adaptor HOOK3 and the kinesin-3 KIF1C. Here we show that KIF1C and dynein/dynactin can exist in a single complex scaffolded by HOOK3. Full-length HOOK3 binds to and activates dynein/dynactin motility. HOOK3 also binds to a short region in the “tail” of KIF1C, but unlike dynein/dynactin, this interaction does not affect the processive motility of KIF1C. HOOK3 scaffolding allows dynein to transport KIF1C towards the microtubule minus end, and KIF1C to transport dynein towards the microtubule plus end. We propose that linking dynein and kinesin motors by dynein activating adaptors may be a general mechanism to regulate bidirectional motility.
WUDI: A Human Involved Self-Adaptive Framework to Prevent Childhood Obesity in Internet of Things Environment

The Internet of Things (IoT) connects people, devices, and information resources, in various domains to improve efficiency. The healthcare domain has been transformed by the integration of the IoT, leading to the development of digital healthcare solutions such as health monitoring, emergency detection, and remote operation. This integration has led to an increase in the health data collected from a variety of IoT sources. Consequently, advanced technologies are required to analyze health data, and artificial intelligence has been employed to extract meaningful insights from the data. Childhood overweight and obesity have emerged as some of the most serious global public health challenges, as they can lead to a variety of health-related problems and the early development of chronic diseases. To address this, a self-adaptive framework is proposed to prevent childhood obesity by using lifelog data from IoT environments, with human involvement being an important consideration in the framework. The framework uses an ensemble-based learning model to predict obesity using the lifelog data. Empirical experiments using lifelog data from smartphone applications were conducted to validate the effectiveness of human involvement and obesity prediction. The results demonstrated the efficiency of the proposed framework with human involvement in obesity prediction. The proposed framework can be applied in real-world healthcare services for childhood obesity.
Spectral invariants of Joyce orbifolds

This paper introduces two new spectral invariants of torsion-free $\mathrm{G}_2$-structures on closed orbifolds and computes their values on all Joyce orbifolds. These invariants are shown to be more discerning than the $\overline{\nu}$-invariant of Crowley-Goette-Nordstr\"{o}m when applied to Joyce orbifolds, and thus provide candidate tools for distinguishing between Joyce manifolds. The invariants may be viewed as regularisations of the classical Morse indices of the critical points of the Hitchin functionals on closed and coclosed $\mathrm{G}_2$-structures respectively. In the case of Joyce orbifolds, an interesting link with twisted Epstein $\zeta$-functions is also observed.
Systemic loss of Sarm1 is glioprotective after neurotrauma

Protecting the nervous system from chronic effects of physical and chemical stress is a pressing clinical challenge, which has sparked intense efforts to identify molecular inhibitors of axon destruction. Yet, one caveat of such strategy is the extent of unintended deleterious effects of blocking axon degeneration systemically. Here we use genetics and pharmacology in zebrafish to show that elimination of the obligate pro-degenerative protein Sarm1 is compatible with neural homeostasis and function, and is glioprotective. Severed axons lacking Sarm1 subsist independently of Schwann-cell support. Regenerating axons in Sarm1 mutants do not reseal with non-degradable axon segments and regain connectivity with peripheral synaptic targets to enable sensorimotor recovery, suggesting that neural-circuit repair is not contingent upon expeditious clearance of damaged axons. Unexpectedly, we found that Sarm1 deficiency increases Schwann-cell resistance to toxicity by diverse chemotherapeutic agents after nerve injury. Our findings anticipate that pharmacological interventions targeting Sarm1 are promising strategies to reduce chronic consequences of neurotrauma. (C’’) extension of In several from Schwann and aspects of The shape of the lower extension from a Schwann did not that they are stabilized, through interactions with the Proximal axons (D’’) start to along these Schwann-cell protrusions. In the extensions from the anterior posterior Schwann cells the interact and commence to reconstitute a continuous glial scaffold. axonal projections (E’’), a retraction towards the proximal stump. F’-H’ a continuation of Schwann cells behavior, the contacts and closing the gap, which is by the area of the gap (distance between proximal and distal Schwann cells in glial scaffold
Machine learning-based models for accessing thermal conductivity of liquids at different temperature conditions

ABSTRACT Combating global warming-related climate change demands prompt actions to reduce greenhouse gas emissions, particularly carbon dioxide. Biomass-based biofuels represent a promising alternative fossil energy source. To convert biomass into energy, numerous conversion processes are performed at high pressure and temperature conditions, and the design and dimensioning of such processes requires thermophysical property data, particularly thermal conductivity, which are not always available in the literature. In this paper, we proposed the application of Chemoinformatics methodologies to investigate the prediction of thermal conductivity for hydrocarbons and oxygenated compounds. A compilation of experimental data followed by a careful data curation were performed to establish a database. The support vector machine algorithm has been applied to the database leading to models with good predictive abilities. The support vector regression (SVR) model has then been applied to an external set of compounds, i.e. not considered during the training of models. It showed that our SVR model can be used for the prediction of thermal conductivity values for temperatures and/or compounds that are not covered experimentally in the literature.
Pattern Separation in a Spiking Neural Network of Hippocampus Robust to Imbalanced Excitation/Inhibition

Efficient pattern separation in dentate gyrus plays an important role in storing information in the hippocampus. Current knowledge of the structure and function of the hippocampus, entorhinal cortex and dentate gyrus, in pattern separation are incorporated in our model. A three-layer feedforward spiking neural network inspired by the rodent hippocampus an equipped with simplified synaptic and molecular mechanisms is developed. The aim of the study is to make an spiking neural network capable of pattern separation in imbalanced excitation/inhibition ratios caused by different levels of stimulations or network damage. This work present a novel theory on the cellular mechanisms of robustness to damges to synapses and connectivity of neurons in dentate gyrus that results in imbalanced excitation-inhibition activity of neurons. This spiking neural network uses simplified molecular and cellular hypothetical mechanisms and demonstrates efficient storing of information in different levels of stimulation and can be implemented in cognitive robotics.
Genome-wide scans for detecting the selection signature of the Jeju-island native pig ( JNP ) in Korea 1 2

21 Objectives: The Jeju Native Pig (JNP) found on the Jeju Island of Korea is a unique black pig known for high22 quality meat. To investigate the genetic uniqueness of JNP, we analyzed the selection signature of the JNP in 23 comparison to commercial pigs such as Berkshire and Yorkshire pigs. 24 Methods: We surveyed the genetic diversity to identify the genetic stability of the JNP, using the linkage 25 Ac ce pt e A rti cle disequilibrium method. A selective sweep of the JNP was performed to identify the selection signatures. To do 26 so, the population differentiation measure, Weir-Cockerham’s Fst was utilized. This statistic directly measures 27 the population differentiation at the variant level. Additionally, we investigated the gene ontologies (GOs) and 28 genetic features. 29 Results: Compared to the Berkshire and Yorkshire pigs, the JNP had lower genetic diversity in terms of linkage 30 disequilibrium decays. We summarized the selection signatures of the JNP as GO. In the JNP and Berkshire pigs, 31 the most enriched GO terms were epithelium development and neuron-related. Considering the JNP and 32 Yorkshire pigs, cellular response to oxygen-containing compound and generation of neurons were the most 33 enriched GO. 34 Conclusion: The selection signatures of the JNP were identified through the population differentiation statistic. 35 The genes with possible selection signatures are expected to play a role in JNP’s unique pork quality. 36
Why do Indigenous Australians drink and drive? A qualitative exploration of self-reported influences on drink driving behaviours of Indigenous peoples from remote communities

Drink driving contributes towards high injury rates for Indigenous populations in Canada and Australia, particularly in more isolated regions. At present there is limited research on the cultural and psychosocial factors that underpin Indigenous peoples' drink driving. This study is part of a broader project aiming to inform a culturally sensitive program. Qualitative interviews with 29 convicted Indigenous drink drivers (aged 20-51 years) from a remote region of Queensland, Australia were used to explore their cognitions about, and underlying motivation for, drink driving as well as the factors that might facilitate or impede it. Although a number of themes were identified, this paper will focus on the first theme, respondents' self-perceived rationale for their behaviour. Two subthemes were identified: 'being the hero' referred to situations where respondents were motivated by a bravado mentality to drive after drinking despite having, on some occasions, the opportunity to avoid this (e.g. another person offering to drive); and 'family obligations' which referred to situations where respondents described pressure from members of their extended families to drive after drinking. The underlying responsibility for transporting family members appeared to be difficult to avoid and related to cultural values. Findings indicate the social and individual characteristics for younger drink drivers are similar to mainstream populations. However, the reinforcers for Indigenous drink drivers may be different for this population, consistent with findings on other Indigenous populations outside Australia. Specific programs should contain a family-centred approach and explore the kinship value system to build strategies around these strong relationships.
Antimicrobial efficacy of Rheum palmatum, Curcuma longa and Alpinia officinarum extracts against some pathogenic microorganisms

The use and search for antibiotics and dietary supplements derived from plants have accelerated in recent years. Three plants, used traditionally as medicine and as food additive in Saudi Arabia, were collected and extracted with either methanol or n-butanol. The used plants were Rheum palmatum, Curcuma longa and Alpinia officinarum. The plant extracts were screened for their inhibitory effects on seven bacterial and five fungal genera using agar well diffusion method. It was shown that methanol extract was more effective as compared to n-butanol extracts. The minimum inhibitory concentrations (MIC) of the methanol extracts of the used plants ranged from 50 to 175 μg/ml. No toxicity was found using Artimia salina as test organism. Antitumor activity against Ehrlich ascites carcinoma was recorded only for C. longa extract.
Increasing the payload capacity of soft robot arms by localized stiffening

Soft robot arms offer safety and adaptability due to their passive compliance, but this compliance typically limits their payload capacity and prevents them from performing many tasks. This paper presents a model-based design approach to effectively increase the payload capacity of soft robot arms. The proposed approach uses localized body stiffening to decrease the compliance at the end effector without sacrificing the robot’s range of motion. This approach is validated on both a simulated and a real soft robot arm, where experiments show that increasing the stiffness of localized regions of their bodies reduces the compliance at the end effector and increases the height to which the arm can lift a payload. By increasing the payload capacity of soft robot arms, this approach has the potential to improve their efficacy in a variety of tasks including object manipulation and exploration of cluttered environments. Description The payload capacity of a soft robot arm can be substantially increased while maintaining its range of motion by stiffening localized regions of its body.
The Effect of Six Weeks-Voluntary Wheel Running on Brain Amyloid Beta (1-42) Levels of Diabetic Rats

Article history: Received: Accepted: Available online: 7 Jan 2012 ZJRMS 2013; 15(5): 39-42 Background: Amyloid Beta (1-42) is derived from amyloid precursor protein and plays a critical role in AD pathogenesis. The purpose of this study was to investigate the effect of 6 weeks of voluntary wheel running on brain Amyloid beta (1-42) in the diabetic rats induced with alloxan. Materials and Methods: 28 male rats weight 185±1 were assigned randomly to 4 groups (N=7): normal control (C), training (T), control-diabetic (CD) and diabetic-training (DT). Diabetes was induced with injecting Alloxan (120 mg/kg dissolved in saline) intraperitoneal. Results: 6 weeks of voluntary wheel running decreased the cortex Aβ1-42 in T and DT groups. Aβ1-42 levels significantly decreased in the T and DT in compare with C and CD (p<0.001), respectively. Also Aβ1-42 levels significantly increased in the CD in compare with C (p<0.001). Conclusion: voluntary exercise had positive effects on decreasing of Aβ1-42 levels during 6 weeks. Therefore it can be recommended as therapeutic strategy for diabetes.
high expression of nUcB2 promotes papillary thyroid cancer cells proliferation and invasion

Background: NUCB2, a novel multifunctional protein containing several functional domains, was newly found to play important roles in many cancers, but its role in papillary thyroid cancer (PTC) is not well investigated. Therefore, our study was performed to explore the functions of NUCB2 in PTC. Methods: NUCB2 protein level was analyzed by immunohistochemistry. Data analyses were made by performing chi-squared test. Quantitative reverse-transcription PCR, Western blot, colony formation, MTT, and transwell invasion assays were performed to test the expression levels and functions of NUCB2 in PTC. Results: In PTC tissues, NUCB2 protein expression level was positively correlated with extrathyroidal extension, TNM stage, and tumor size of PTC patients. In vitro experiments demonstrated that knockdown of NUCB2 using specific shRNA for NUCB2 significantly impaired cell proliferation and invasion of PTC cell lines. In vivo, silencing of NUCB2 inhibited the growth of tumors in mice. Conclusion: These results suggested a novel function of NUCB2 in the process of proliferation and invasion in PTC. NUCB2 may be considered a potent prognostic factor in PTC.
Hierarchical Domain Structure Reveals the Divergence of Activity among TADs and Boundaries

Mammalian genomes are organized into different levels. As a fundamental structural unit, Topologically Associating Domains (TADs) play a key role in gene regulation. Recent studies showed that hierarchical structures are present in TADs. Precise identification of hierarchical TAD structures however remains a challenging task. We present OnTAD, an Optimal Nested TAD caller from Hi-C data, to identify hierarchical TADs. Systematical comparison with existing methods shows that OnTAD has significantly improved accuracy, reproducibility and running speed. OnTAD reveals new biological insights on the role of different TAD levels and boundary usage in gene regulation and the loop extrusion model. The OnTAD is available at: https://github.com/anlin00007/OnTAD
Accelerated 19F·MRI Detection of Matrix Metalloproteinase-2/-9 through Responsive Deactivation of Paramagnetic Relaxation Enhancement

Paramagnetic gadolinium ions (GdIII), complexed within DOTA-based chelates, have become useful tools to increase the magnetic resonance imaging (MRI) contrast in tissues of interest. Recently, “on/off” probes serving as 19F·MRI biosensors for target enzymes have emerged that utilize the increase in transverse (T 2 ∗ or T 2) relaxation times upon cleavage of the paramagnetic GdIII centre. Molecular 19F·MRI has the advantage of high specificity due to the lack of background signal but suffers from low signal intensity that leads to low spatial resolution and long recording times. In this work, an “on/off” probe concept is introduced that utilizes responsive deactivation of paramagnetic relaxation enhancement (PRE) to generate 19F longitudinal (T 1) relaxation contrast for accelerated molecular MRI. The probe concept is applied to matrix metalloproteinases (MMPs), a class of enzymes linked with many inflammatory diseases and cancer that modify bioactive extracellular substrates. The presence of these biomarkers in extracellular space makes MMPs an accessible target for responsive PRE deactivation probes. Responsive PRE deactivation in a 19F biosensor probe, selective for MMP-2 and MMP-9, is shown to enable molecular MRI contrast at significantly reduced experimental times compared to previous methods. PRE deactivation was caused by MMP through cleavage of a protease substrate that served as a linker between the fluorine-containing moiety and a paramagnetic GdIII-bound DOTA complex. Ultrashort echo time (UTE) MRI and, alternatively, short echo times in standard gradient echo (GE) MRI were employed to cope with the fast 19F transverse relaxation of the PRE active probe in its “on-state. ” Upon responsive PRE deactivation, the 19F·MRI signal from the “off-state” probe diminished, thereby indicating the presence of the target enzyme through the associated negative MRI contrast. Null point 1H·MRI, obtainable within a short time course, was employed to identify false-positive 19F·MRI responses caused by dilution of the contrast agent.
The burden of suicidal ideation across Europe: a cross-sectional survey in five countries

Background Suicidal ideation (SI) is an associated risk of depression, affecting 30–40% of the depressed population. However, there is a paucity of studies investigating the impact of SI in Europe. This retrospective observational study examined the burden of SI among adults with major depressive disorder (MDD) in the 2017 National Health and Wellness Survey in five European countries: France, Germany, Italy, Spain, and the UK. Methods Bivariate analyses evaluated group differences between respondents with MDD with and without SI according to demographic characteristics, self-reported health-related quality of life, work productivity and activity impairment (WPAI), and healthcare resource utilization (HRU). Generalized linear models examined group differences country-wise, after controlling for relevant confounders. Results Among 52,060 respondents, 3,308 individuals were diagnosed with MDD, comprising SI (n=905) and non-SI (nSI) (n=2403) patients. Adjusted differences (ADs), compared to the general population, were observed using the Medical Outcomes Study Short Form Survey (SF-12v2) mental component summary scores (AD: SI=−20.02, nSI=−10.77), physical component summary scores (AD: SI=−4.49, nSI=−2.50), and EuroQoL-5 Dimensions (AD: SI=−0.34, nSI=−0.15) (for all, p<0.001). Significantly greater WPAI and higher HRU were associated with SI compared to nSI. Conclusion The results illustrate the unique impact of SI within the MDD population and the need to reduce the burden.
Automatic Resource Augmentation for Machine Translation in Low Resource Language: EnIndic Corpus

Parallel corpus is the primary ingredient of machine translation. It is required to train the statistical machine translation (SMT) and neural machine translation (NMT) systems. There is a lack of good quality parallel corpus for Hindi to English. Comparable corpora for a given language pair are comparatively easy to find, but this cannot be used directly in SMT or NMT systems. As a result, we generate a parallel corpus from the comparable corpus. For this purpose, the sentences (which are translations of each other) are mined from the comparable corpus to prepare the parallel corpus. The proposed algorithm uses the length of the sentence and word translation model to align sentence pairs that are translations of each other. Then, the sentence pairs that are poor translations of each other (measured by a similarity score based on IBM model 1 translation probability) are filtered out. We apply this algorithm to comparable corpora, which are crawled from speeches of the President and Vice-President of India, and mined parallel corpora out of them. The prepared parallel corpus contains good quality aligned sentences (with 96.338% f-score). Subsequently, incorrect sentence pairs are filtered out manually to make the corpus in qualitative practical use. Finally, we gather various sentences from different sources to prepare the EnIndic corpus, which comprises 1,656,207 English-Hindi sentence pairs (miscellaneous domain). We have deployed this prepared largest English-Hindi parallel corpus at https://github.com/debajyoty/EnIndic.git and the source code at https://github.com/debajyoty/EnIndicSourceCode.git.