Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Melaleuca alternifolia Chell (Tea Tree) and Eucalyptus globulus Labill. Essential Oils on Antibiotic-Resistant Bacterial Biofilms

In the present investigation, the anti-biofilm potential of two essential oils (EOs), Melaleuca alternifolia Chell (Tea-Tree) (TTO) and Eucalyptus globulus Labill. (EEO) was characterized and tested “in vitro” against both mature biofilms and biofilms in the process of formation, produced by strains belonging to three main categories of antibiotic resistant bacteria (ARB): Vancomycin-resistant enterococci (VRE), methicillin-resistant Staphylococcus aureus (MRSA) and broad-spectrum β-lactamase-producing Escherichia coli (ESBL). The study was carried out in 96-well microtiter-plates using EOs alone, in association with each other and in combination with antibiotics against both single and multi-species biofilm. The study demonstrated the ability of TTO and EEO to counteract the ARB strains in sessile form, with promising results in particular against the biofilm in formation. Mature biofilm by ESBL E. coli was the most sensitive in the results from the quantification study of viable cells performed in multi-species biofilms. Lastly, in all tests, carried out using TTO/EEO associations and EOs/antibiotic combinations, the synergistic effect which emerged from the FIC-index has been confirmed, and both the reduction of biofilm in formation, and the removal of mature structure was obtained at very low concentrations, with values from 4 to >512-fold lower than the minimum inhibitory concentration (MIC) of the single compounds.
The rendezvous problem on discrete locations

Two friends have become separated in a building or shopping mall and and wish to meet as quickly as possible. There are n possible locations where they might meet. However, the locations are identical and there has been no prior agreement where to meet or how to search. Hence they must use identical strategies and must treat all locations in a symmetrical fashion. Suppose their search proceeds in discrete time. Since they wish to avoid the possibility of never meeting, they will wish to use some randomizing strategy. If each person searches one of the n locations at random at each step, then rendezvous will require n steps on average. It is possible to do better than this: although the optimal strategy is difficult to characterize for general n, there is a strategy with an expected time until rendezvous of less than 0.829 n for large enough n. For n = 2 and 3 the optimal strategy can be established and on average 2 and 8/3 steps are required respectively. There are many tantalizing variations on this problem, which we discuss with some conjectures.
Nano-scale MOSFET device modelling with quantum mechanical effects

The continuing down-scaling trend of CMOS technology has brought serious deterioration in the accuracy of the SPICE (Simulation Program with Integrated Circuit Emphasis) device models used in the design of chip functions. This is due to in part to hot electron and quantum effects that occur in modern nano-scale MOSFET devices [13, 25, 28, 33, 34]. The focus of this paper is on modeling quantum confinement effects based on the Density-Gradient (DG) model [6, 9, 14], for application in SPICE. Analytic 1-D quantum mechanical (QM) effects correction formulae for the MOSFET inversion charge and electrostatic potential are derived from the DG model using matched asymptotic expansion techniques. Comparison of these new models with numerical data shows good results.
A Novel Deep Learning Method for Automatic Recognition of Coseismic Landslides

Massive earthquakes generally trigger thousands of coseismic landslides. The automatic recognition of these numerous landslides has provided crucial support for post-earthquake emergency rescue, landslide risk mitigation, and city reconstruction. The automatic recognition of coseismic landslides has always been a difficult problem due to the relatively small size of a landslide and various complicated environmental backgrounds. This work proposes a novel semantic segmentation network, EGCN, to improve the landslide identification accuracy. EGCN conducts coseismic landslide recognition by a recognition index set as the input data, CGBlock as the basic module, and U-Net as the baseline. The CGBlock module can extract the relatively stable global context-dependent features (global context features) and the unstable local features by the GNN Branch and CNN Branch (GNN Branch contains the proposed EISGNN) and integrates them via adaptive weights. This method has four advantages. (1) The recognition indices are established according to the causal mechanism of coseismic landslides. The rationality of the indices guarantees the accuracy of landslide recognition. (2) The module of EISGNN is suggested based on the entropy importance coefficient and GATv2. Owing to the feature aggregation among nodes with high entropy importance, global and useful context dependency can be synthesized and the false alarm of landslide recognition can be reduced. (3) CGBlock automatically integrates context features and local spatial features, and has strong adaptability for the recognition of coseismic landslides located in different environments. (4) Owing to CGBlock being the basic module and U-Net being the baseline, EGCN can integrate the context features and local spatial characteristics at both high and low levels. Thus, the accuracy of landslide recognition can be improved. The meizoseismal region of the Ms 7.0 Jiuzhaigou earthquake is selected as an example to conduct coseismic landslide recognition. The values of the precision indices of Overall Accuracy, mIoU, Kappa, F1-score, Precision, and Recall reached 0.99854, 0.99709, 0.97321, 0.97396, 0.97344, and 0.97422, respectively. The proposed method outperforms the current major deep learning methods.
Multi-Exposure Image Fusion via Deformable Self-Attention

Most multi-exposure image fusion (MEF) methods perform unidirectional alignment within limited and local regions, which ignore the effects of augmented locations and preserve deficient global features. In this work, we propose a multi-scale bidirectional alignment network via deformable self-attention to perform adaptive image fusion. The proposed network exploits differently exposed images and aligns them to the normal exposure in varying degrees. Specifically, we design a novel deformable self-attention module that considers variant long-distance attention and interaction and implements the bidirectional alignment for image fusion. To realize adaptive feature alignment, we employ a learnable weighted summation of different inputs and predict the offsets in the deformable self-attention module, which facilitates that the model generalizes well in various scenes. In addition, the multi-scale feature extraction strategy makes the features across different scales complementary and provides fine details and contextual features. Extensive experiments demonstrate that our proposed algorithm performs favorably against state-of-the-art MEF methods.
Downregulation of LncRNA GCLC-1 Promotes Microcystin-LR-Induced Malignant Transformation of Human Liver Cells by Regulating GCLC Expression

Microcystin-LR (MCLR) is an aquatic toxin, which could lead to the development of hepatocellular carcinoma (HCC). Long non-coding RNAs (lncRNAs) are considered important regulatory elements in the occurrence and development of cancer. However, the roles and mechanisms of lncRNAs during the process of HCC, induced by MCLR, remain elusive. Here, we identified a novel lncRNA, namely lnc-GCLC-1 (lncGCLC), which is in close proximity to the chromosome location of glutamate–cysteine ligase catalytic subunit (GCLC). We then investigated the role of lncGCLC in MCLR-induced malignant transformation of WRL68, a human hepatic cell line. During MCLR-induced cell transformation, the expression of lncGCLC and GCLC decreased continuously, accompanied with a consistently high expression of miR-122-5p. Knockdown of lncGCLC promoted cell proliferation, migration and invasion, but reduced cell apoptosis. A xenograft nude mouse model demonstrated that knockdown of lncGCLC promoted tumor growth. Furthermore, knockdown of lncGCLC significantly upregulated miR-122-5p expression, suppressed GCLC expression and GSH levels, and enhanced oxidative DNA damages. More importantly, the expression of lncGCLC in human HCC tissues was significantly downregulated in the high-microcystin exposure group, and positively associated with GCLC level in HCC tissues. Together, these findings suggest that lncGCLC plays an anti-oncogenic role in MCLR-induced malignant transformation by regulating GCLC expression.
A Method for Adaptive Habit Prediction in Bulk Microphysical Models. Part III: Applications and Studies within a Two-Dimensional Kinematic Model

AbstractArctic mixed-phase clouds are ubiquitous, and the persistence of supercooled liquid is not well understood. Prior studies of mixed-phase clouds predict a single axis length assuming spherical particles or mass–dimensional relationships derived from in situ data. These methods cannot mechanistically evolve particle shape, leading to inaccuracies in estimates of mixed-phase lifetime. Parts I and II of this study report on the development and parcel model testing of an adaptive habit parameterization that predicts two bulk crystal lengths. The method is implemented into a two-dimensional kinematic model in which the dynamic flow field is prescribed, allowing for sedimentation and separate advection of length mixing ratios.Similar to other studies, results show that mass–dimensional relationships produce large variation of phase, despite similar choice in particle type. Results with evolving ice habit promote phase maintenance in cases where mass–dimensional methods glaciate the layers. Adaptive habit.
Vertical ground reaction forces, paw pressure distribution, and center of pressure during heelwork in working dogs competing in obedience

Heelwork walking is a command that competitive obedience and working dogs are trained to perform. Unlike other canine sports, the research for competitive obedience sport is limited and no research regarding biomechanical gait adaptions during heelwork walking has been published. The aim of the study was to investigate the changes in vertical ground reaction forces, paw pressure distribution (PPD), and center of pressure (COP) of Belgian Malinois during heelwork walking. Ten healthy Belgian Malinois were included in the study. The dogs walked first without heeling (normal walk) and then while heeling on a pressure platform. The comparison between normal and heelwork walking was performed using mixed-effects models. Post-hoc analyses were performed using Sidak's alpha correction procedure. During heelwork walking, a significant decrease in the vertical impulse and stance phase duration (SPD) and a significant increase in the craniocaudal index and speed of COP was observed in the forelimbs compared to normal walking. At the hindlimbs, a significant increase in vertical impulse and SPD was observed during heelwork walking. Regarding PPD, a significant decrease of vertical impulse was observed at the cranial quadrants of the right forelimb and craniolateral quadrant of the left forelimb during heelwork. The area was significantly decreased at the craniolateral quadrant of the left forelimb and the time for the peak vertical force was prolonged significantly at the caudal quadrants of the right forelimb during heelwork walking. The vertical impulse was significantly increased in all quadrants of the hindlimbs except the craniolateral quadrant of the left hindlimb. The effect of these changes on the musculoskeletal system of working dogs should be investigated in further studies, using electromyography and kinematic analysis.
Improved Estimation of Exercise Intensity Thresholds by Combining Dual Non-Invasive Biomarker Concepts: Correlation Properties of Heart Rate Variability and Respiratory Frequency

Identifying exercise intensity boundaries has been shown to be important during endurance training for performance enhancement and rehabilitation. Unfortunately, even though surrogate markers show promise when assessed on a group level, substantial deviation from gold standards can be present in each individual. The aim of this study was to evaluate whether combining two surrogate intensity markers improved this agreement. Electrocardiogram (ECG) and gas exchange data were obtained from 21 participants who performed an incremental cycling ramp to exhaustion and evaluated for first (VT1) and second (VT2) ventilatory thresholds, heart rate (HR) variability (HRV), and ECG derived respiratory frequency (EDR). HRV thresholds (HRVT) were based on the non-linear index a1 of a Detrended Fluctuation Analysis (DFA a1) and EDR thresholds (EDRT) upon the second derivative of the sixth-order polynomial of EDR over time. The average of HRVT and EDRT HR was set as the combined threshold (Combo). Mean VT1 was reached at a HR of 141 ± 15, HRVT1 at 152 ± 14 (p < 0.001), EDRT1 at 133 ± 12 (p < 0.001), and Combo1 at 140 ± 13 (p = 0.36) bpm with Pearson’s r of 0.83, 0.78, and 0.84, respectively, for comparisons to VT1. A Bland–Altman analysis showed mean biases of 8.3 ± 7.9, −8.3 ± 9.5, and −1.7 ± 8.3 bpm, respectively. A mean VT2 was reached at a HR of 165 ± 13, HRVT2 at 167 ± 10 (p = 0.89), EDRT2 at 164 ± 14 (p = 0.36), and Combo2 at 164 ± 13 (p = 0.59) bpm with Pearson’s r of 0.58, 0.95, and 0.94, respectively, for comparisons to VT2. A Bland–Altman analysis showed mean biases of −0.3 ± 8.9, −1.0 ± 4.6, and −0.6 ± 4.6 bpm, respectively. Both the DFA a1 and EDR intensity thresholds based on HR taken individually had moderate agreement to targets derived through gas exchange measurements. By combining both non-invasive approaches, there was improved correlation, reduced bias, and limits of agreement to the respective corresponding HRs at VT1 and VT2.
Honey and Alzheimer’s Disease—Current Understanding and Future Prospects

Alzheimer’s disease (AD), a leading cause of dementia, has been a global concern. AD is associated with the involvement of the central nervous system that causes the characteristic impaired memory, cognitive deficits, and behavioral abnormalities. These abnormalities caused by AD is known to be attributed by extracellular aggregates of amyloid beta plaques and intracellular neurofibrillary tangles. Additionally, genetic factors such as abnormality in the expression of APOE, APP, BACE1, PSEN-1, and PSEN-2 play a role in the disease. As the current treatment aims to treat the symptoms and to slow the disease progression, there has been a continuous search for new nutraceutical agent or medicine to help prevent and cure AD pathology. In this quest, honey has emerged as a powerful nootropic agent. Numerous studies have demonstrated that the high flavonoids and phenolic acids content in honey exerts its antioxidant, anti-inflammatory, and neuroprotective properties. This review summarizes the effect of main flavonoid compounds found in honey on the physiological functioning of the central nervous system, and the effect of honey intake on memory and cognition in various animal model. This review provides a new insight on the potential of honey to prevent AD pathology, as well as to ameliorate the damage in the developed AD.
Real-Time 100 Gb/s PAM-4 for Access Links With up to 34 dB Power Budget

The growing demand for broadband access networks keeps motivating research for higher capacity in both wired and wireless access networks. Recently, the recommendation for 50G-PON with conventional NRZ modulation has been published. Bidirectional point-to-point access networks, also known as BiDi, used in mobile xHaul, are standardized up to 50 Gb/s with PAM-4 as modulation format. The evolution in view of a next generation 6G wireless encourages research towards higher bitrates for fronthaul systems. Hence, there is interest for having single channel BiDi links with a bitrate of at least 100 Gb/s. In this paper we experimentally evaluate four possible IMDD transceiver schemes suitable for optical access applications in the O-Band that can cover BiDi link losses up to a bitrate of 100 Gb/s using PAM-4. We employ an EML with either a 25G-based APD or an optically preamplified p-i-n photodiode (PD) with low-complexity FFE equalization and achieve a real-time power budget of 23.7 dB, just above BiDi B- loss class. By adding an optical booster, we demonstrate up to 34 dB power budget, exceeding with enough margin the highest BiDi class B loss of 25 dB.
A Literature Review on the Role of Hope in Promoting Positive Youth Development across Non-WEIRD Contexts

Theoretical and empirical evidence has identified hope as a key adolescent strength that is linked to positive youth developmental outcomes. Although hope must be understood from a cultural lens, most of the evidence regarding adolescent hope is derived from samples of white youth from Western, educated, industrialized, rich, and democratic (WEIRD) nations. Therefore, in order to have a more comprehensive and global understanding of the antecedents, outcomes, and processes of hope, we apply a positive youth development perspective in order to review the literature (N = 52 studies) on hope from diverse cultural and international contexts. In organizing the findings by global region, our review provides evidence of the shared function of hope in promoting positive youth developmental outcomes and the usefulness of the Child Hope Scale across contexts. Family and parental relationships were identified as key assets in promoting hope; however, there exists cultural and contextual variation in what aspects of these relationships promote hope. We conclude this review by considering the priorities for research, practice, and policy, based on these findings.
Golden Visas and everyday citizenship: views of the new Chinese migration in Portugal

ABSTRACT The residency-by-investment programmes – or Golden Visas – are an example of a neoliberal legal innovation where residency is granted through investment with only minimal additional residency requirements. This paper explores how the different conditions of foreign residency, that create groups of non-national residents with different rights, are made sense of by Chinese investment residents (n = 11) and Chinese key-informants developing activities related with them (n = 14). Particularly, we explored how this programme is understood in everyday discourse and how it reinforces the construction of a neoliberal configuration of citizenship. Analysis shows that a new Chinese migration is being presented by emphasizing the differences between old (seen as “forced”) migrant mobilities and new forms of mobility, a distinction grounded in assumptions of linear globalization and development. We discuss the citizenship inequalities this programme is promoting, both in practice and in the representations of an ideal or “good” mobility in contemporary globalized societies.
Exploring the Lived Experience on Recovery from Major Depressive Disorder (MDD) among Women Survivors and Five CHIME Concepts: A Qualitative Study

Objective: Depression is estimated to be the leading cause of disease by 2030 and is already the leading cause in women worldwide. In Malaysia, nearly 2.3 million people have experienced depression at least once. Yet, this problem has not been thoroughly investigated and addressed. Thus, a study exploring the lived experience of the survivors needs to be carried out. With most Major Depressive Disorder (MDD) patients being women compared to men, this study focused on women MDD survivors to understand their journey to recovery. Survivors or also called ‘People with Lived Experience’ (PWLE) have a range of first-hand experiences with treatment and recovery, making them an expert by experience. Method: A qualitative study was conducted using purposive sampling of four women survivors. This method was able to explore the experience of informants rigorously as it gave flexibility and encouraged discussion between researchers and informants. The data from in-depth interviews conducted were then analyzed using thematic analysis, focusing on the key concepts of CHIME conceptual framework of recovery. Results: This study found four major themes with fifteen subordinate themes: survivor’s efforts, challenges, social support, and hopes. The findings of this study were then integrated with CHIME framework, also known as the guiding philosophy of recovery for mental illness patients. Conclusion: These findings contributed to a better understanding of the recovery process and supports needed for MDD patients to recover. In addition, this study also gives hopes that MDD patients can recover, therefore breaking the social stigma still prevalent in the community. Based on these first-hand experiences shared by the survivors, it is hoped that the present interventions conducted by related organizations and caregivers can yield improvements so that the current patients who are still struggling with MDD can recover faster holistically. Limitations and implications for future research have also been discussed.
Comparative study of finite element model updating methods

The effects of vibrations present major hazards and operating limitations ranging from discomfort (including noise), malfunctioning, reduced performance, early breakdown and structural failure which, in the worst case can be catastrophic. Hence, accurate mathematical models are required to describe the vibration characteristics of structures, which subsequently can be used for design purposes to limit the negative effects of vibrations. Finite element (FE) predictions are often called into question when they are in conflict with test results. Inaccuracies in FE models and errors in results predicted by them can arise due to the use of incorrect modeling of boundary conditions, incorrect modeling of joints, and difficulties in modeling of damping. This has led to the development of model updating techniques, which aim at reducing the inaccuracies present in an analytical model in the light of measured dynamic test data. In this paper, a detailed comparison of two approaches of obtaining updated FE models are evaluated with the objective that the frequency response functions (FRFs) obtained from updated FE models are able to predict the measured FRFs accurately. In the first method, the updated FE model is obtained by a direct method, which uses modal data. In the second method, the updated model is obtained by an iterative method, which uses FRF data and is also a parameter-based method. The effectiveness of both methods is evaluated by numerical examples, as well as by actual experimental data. Firstly, a study is performed using a numerical simulation based on fixed-fixed beam structure. The numerical study is followed by a case involving actual measured data for the case of an F-shaped test structure. The updated results have shown that the iterative method gives 20% better matching of FRFs with the experimental data and also the predictions of the iterative method is better than the direct method beyond the considered frequency range. The updated results have shown that the FE model obtained using the response function method, an iterative method, can be used to derive accurate model of the system. Updated models obtained by both methods are subsequently evaluated for its application in dynamic design.