Miracle-dz/UniFAR-FTUs huggingface dataset:
Sharing a Landscape: The Construction of Sense of Place on the Maine Coast

The concept of place attachment is used to help natural resource managers understand recreational users as part of a landscape. The source of place attachment is examined in a mixed-use area in order to learn what draws individuals to a landscape, and to better predict how visitors may react to management actions. With an emphasis on physical, social, and cultural characteristics, this study set out to develop an understanding of how recreational users become connected with a resource, and how different forms of connections are shaped by socio-demographic and travel variables. The Stonington region island archipelago, hosting a range of recreational use and user characteristics, is a popular ocean-recreation destination along the Maine Island Trail; one of North America’s first and longest water trails. An island visitor survey was conducted in the region during the summer of 2006 measuring place attachment, reasons for visiting, socio-demographic variables, and travel characteristics. A factor analysis of the place attachment scale supported previous conceptualizations of place identity and place dependence as two separate but highly correlated components. The place identity and dependence factors were clustered into three groups for comparison with other variables. Results indicated experience use history was positively related to place
Mechanical and Functional Improvement of β-TCP Scaffolds for Use in Bone Tissue Engineering

Autologous bone transplantation is still considered as the gold standard therapeutic option for bone defect repair. The alternative tissue engineering approaches have to combine good hardiness of biomaterials whilst allowing good stem cell functionality. To become more useful for load-bearing applications, mechanical properties of calcium phosphate materials have to be improved. In the present study, we aimed to reduce the brittleness of β-tricalcium phosphate (β-TCP). For this purpose, we used three polymers (PDL-02, -02a, -04) for coatings and compared resulting mechanical and degradation properties as well as their impact on seeded periosteal stem cells. Mechanical properties of coated and uncoated β-TCP scaffolds were analyzed. In addition, degradation kinetics analyses of the polymers employed and of the polymer-coated scaffolds were performed. For bioactivity assessment, the scaffolds were seeded with jaw periosteal cells (JPCs) and cultured under untreated and osteogenic conditions. JPC adhesion/proliferation, gene and protein expression by immunofluorescent staining of embedded scaffolds were analyzed. Raman spectroscopy measurements gave an insight into material properties and cell mineralization. PDL-coated β-TCP scaffolds showed a significantly higher flexural strength in comparison to that of uncoated scaffolds. Degradation kinetics showed considerable differences in pH and electrical conductivity of the three different polymer types, while the core material β-TCP was able to stabilize pH and conductivity. Material differences seemed to have an impact on JPC proliferation and differentiation potential, as reflected by the expression of osteogenic marker genes. A homogenous cell colonialization of coated and uncoated scaffolds was detected. Most interesting from a bone engineer’s point of view, the PDL-04 coating enabled detection of cell matrix mineralization by Raman spectroscopy. This was not feasible with uncoated scaffolds, due to intercalating effects of the β-TCP material and the JPC-formed calcium phosphate. In conclusion, the use of PDL-04 coating improved the mechanical properties of the β-TCP scaffold and promoted cell adhesion and osteogenic differentiation, whilst allowing detection of cell mineralization within the ceramic core material.
Research on the quantitative analysis for detection sulfate using laser Raman spectroscopy

Sulfate is an important anion in marine research and is closely associated with numerous marine phenomena. Laser Raman spectroscopy is a nondestructive, non-contact molecular fingerprint spectroscopy that can identify as well as quantify substances, and is suitable for the detection and quantification of substances in solution. In this paper, the Raman spectra of different concentrations of sodium sulfate solutions were measured under laboratory conditions and quantified by four methods: internal standard normalization method, multiple linear regression, random forest and XGBoost, respectively, to establish models and analyze the results. The results show that multiple linear regression, random forest, and XGBoost can improve the accuracy based on the internal standard normalization method, while random forest has the best results with a mean percentage error of 4.9867%, mean square error of 4.68932, and R 2= 0.98813, which proves the superiority of machine learning methods for quantitative analysis of Raman spectra based on target substances in seawater quantitative analysis of substances in seawater.
Geometric and electronic structure of low-index Cu2O surfaces based DFT

We investigated the structures and energies of three low-index stoichiometric surfaces of Cu2O using first-principles. A new scheme that utilizes correction surface energies more accurate than the average surface energy was employed to calculate the surface energies. Both surface energy schemes revealed that the surface energy magnitude follows the order of (111) < (100) < (001). The Wulff indicated that the percentages of the (001), (100), and (111) surfaces in the total crystal surface area were 25%, 25%, and 50%, respectively. These findings will contribute to the design of more efficient photocatalysts.
Using Artificial Intelligence Algorithms to Identify Factors of Methane Leaks from Gas Transmission Assets

GRTgaz has launched a major program for improving the assessment and the reduction of methane emissions due to leaks from its gas transmission network and facilities. The industrial assets of GRTgaz notably include thousands of gas delivery units, each containing pipes, gas pressure regulator(s), filter(s), shutoff valve(s), safety relief valve(s). The leak detection campaign on the gas delivery units then requires significant resources and a lot of time. Targeting the assets that are the most likely to leak is therefore an important challenge for improving the campaign efficiency, moving forward the implementation of corrective measures, and reducing the methane emissions. This work aims to explore XGBoost (Extreme Gradient Boosting) Cox survival regression model, associated with SHAP (SHapley Additive exPlanations) method, and Bayesian Networks using BayesiaLab software, to identify and explain the effect of different features on reliability of natural gas transmission assets, based on field feedback data.
Understanding the effects of cortical gyrification in tACS: insights from experiments and computational models

The alpha rhythm is often associated with relaxed wakefulness or idling and is altered by various factors. Abnormalities in the alpha rhythm have been linked to several neurological and psychiatric disorders, including Alzheimer's disease. Transcranial alternating current stimulation (tACS) has been proposed as a potential tool to restore a disrupted alpha rhythm in the brain by stimulating at the individual alpha frequency (IAF), although some research has produced contradictory results. In this study, we applied an IAF-tACS protocol over parieto-occipital areas to a sample of healthy subjects and measured its effects over the power spectra. Additionally, we used computational models to get a deeper understanding of the results observed in the experiment. Both experimental and numerical results showed an increase in alpha power of 8.02% with respect to the sham condition in a widespread set of regions in the cortex, excluding some expected parietal regions. This result could be partially explained by taking into account the orientation of the electric field with respect to the columnar structures of the cortex, showing that the gyrification in parietal regions could generate effects in opposite directions (hyper-/depolarization) at the same time in specific brain regions. Additionally, we used a network model of spiking neuronal populations to explore the effects that these opposite polarities could have on neural activity, and we found that the best predictor of alpha power was the average of the normal components of the electric field. To sum up, our study sheds light on the mechanisms underlying tACS brain activity modulation, using both empirical and computational approaches. Non-invasive brain stimulation techniques hold promise for treating brain disorders, but further research is needed to fully understand and control their effects on brain dynamics and cognition. Our findings contribute to this growing body of research and provide a foundation for future studies aimed at optimizing the use of non-invasive brain stimulation in clinical settings.
A new perspective on causality, locality, and duality in entangled quantum nano systems

Interference with or without entanglement has been recognized as a key resource for quantum computing and quantum communications systems, as for example discussed by Nielsen and Chuang1 and numerous other works. Multiple paths between sources and detectors require an understanding of the underpinning wave-particle duality issue in the interference effects. Recently a new axiom (particle and its wave function φ(r, t) cannot be coincident or co-located at space-time point (rk, tk) unless φ(r, t) = δ(r-rk, t-tk) the Dirac delta function) has been suggested2 and justified, which explains duality without Niels Bohr’s complementarity principle, thus eliminating the role of the observer, avoiding complicated “which way” (welcher-weg) considerations and observer subjectivity. This greatly simplifies analysis and design of multi-path quantum systems and restores objectivity. The same paper also suggested in the context of entanglement new concepts of (a) “total causality” that includes entanglement as a cause to locally and causally explain “action at a distance”, and (b) “partial causality” that excludes entanglement as a cause and thereby introduces the perception of strange phenomena of non-locality, retro-causality and quantum erasure, which are nevertheless very important. This paper reviews and then applies the axiom to bring much needed clarity to certain confusing and much debated aspects of developments in non-interaction measurements, counterfactual communications and quantum computers. These potential clarifications and simplifications of analysis and design of multi path systems may help developers of future quantum communication and quantum computer systems.
A low phase noise quadrature VCO using super‐harmonic coupling technique in 65‐nm CMOS technology

This paper presents a new low phase noise (PN) quadrature voltage controller oscillator (QVCO), which includes four class C LC‐VCOs oscillated at 13 GHz operating frequency with 45‐degree phase differences from each other. By combining the second harmonics (super‐harmonic) of the LC‐VCOs, the quadrature outputs with low PN at 26 GHz are generated. To assess the performance of the proposed QVCO, post‐layout simulations are performed in 65‐nm CMOS technology with a 0.6 V supply voltage. The post‐layout results represent that the proposed circuit has 26 GHz quadrature outputs with the PN of −116.4 at 1 MHz offset frequency. Also, the proposed QVCO occupies an area of 0.366 mm2 and consumes 10.4 mW of power. Therefore, the proposed QVCO is a good candidate for 5G applications.
Output Force Density Saturation in COMSOL Simulations of Biomimetic Artificial Muscles

Many modern applications, such as undersea drones, exoskeletal suits, all-terrain walker drones, prosthetics, and medical augments, would greatly benefit from artificial muscles. Such may be built through 3D-printed microfluidic devices that mimic biological muscles and actuate electrostatically. Our preliminary results from COMSOL simulations of individual devices and small arrays (2 × 2 × 1) established the basic feasibility of this approach. Herein, we report on the extension of this work to N × N × 10 arrays where Nmax = 13. For each N, parameter sweeps were performed to determine the maximal output force density, which, when plotted vs. N, exhibited saturation behavior for N ≥ 10. This indicates that COMSOL simulations of a 10 × 10 × 10 array of this type are sufficient to predict the behavior of far larger arrays. Also, the saturation force density was ~9 kPa for the 100 μm scale. Both results are very important for the development of 3D-printable artificial muscles and their applications, as they indicate that computationally accessible simulation sizes would provide sufficiently accurate quantitative predictions of the force density output and overall performance of macro-scale arrays of artificial muscle fibers. Hence, simulations of new geometries can be done rapidly and with quantitative results that are directly extendable to full-scale prototypes, thereby accelerating the pace of research and development in the field of actuators.
Identification of HuSWEET Family in Pitaya (Hylocereus undatus) and Key Roles of HuSWEET12a and HuSWEET13d in Sugar Accumulation

The sugar composition and content of fruit have a significant impact on their flavor and taste. In pitaya, or dragon fruit, sweetness is a crucial determinant of fruit taste and consumer preference. The sugars will eventually be exported transporters (SWEETs), a novel group of sugar transporters that have various physiological functions, including phloem loading, seed filling, nectar secretion, and fruit development. However, the role of SWEETs in sugar accumulation in pitaya fruit is not yet clear. Here, we identified 19 potential members (HuSWEET genes) of the SWEET family in pitaya and analyzed their conserved motifs, physiochemical characteristics, chromosomal distribution, gene structure, and phylogenetic relationship. Seven highly conserved α-helical transmembrane domains (7-TMs) were found, and the HuSWEET proteins can be divided into three clades based on the phylogenetic analysis. Interestingly, we found two HuSWEET genes, HuSWEET12a and HuSWEET13d, that showed strong preferential expressions in fruits and an upward trend during fruit maturation, suggesting they have key roles in sugar accumulation in pitaya. This can be further roughly demonstrated by the fact that transgenic tomato plants overexpressing HuSWEET12a/13d accumulated high levels of sugar in the mature fruit. Together, our result provides new insights into the regulation of sugar accumulation by SWEET family genes in pitaya fruit, which also set a crucial basis for the further functional study of the HuSWEETs.
Efficient IoT Device Identification via Network Behavior Analysis Based on Time Series Dictionary

Due to hardware limitations, Internet of Things (IoT) devices without integrated security become easy targets for network attacks. IoT device identification is significant for network security management. Despite many efforts, previous studies either require excessive features raising concerns about efficiency and privacy, or underutilize the data resources to fulfill the potential of simple features. Moreover, the severe data imbalance problem is unaddressed. In this article, we present IoTProfile, an efficient IoT device identification framework via time series dictionary. It only considers simple packet-level attributes and maps them into different time windows. On this basis, it further follows a shuffle&split organization scheme to structure the imbalanced data as multichannel time series. By performing random convolutional kernel transformations in two ways and aggregations, IoTProfile captures discriminative patterns and forms the frequency count of recurring patterns to profile the network behaviors of IoT devices over a period of time. The experimental results show that IoTProfile is superior to the other state-of-the-art methods in terms of both identification effectiveness and time overhead, achieving 99.81% and 97.65% Macro-F1 scores on the University of New South Wales and University of New Brunswick data sets in under 4 min.
Metrics and Considerations for Evaluating How Forest Treatments Alter Wildfire Behavior and Effects

The influence of forest treatments on wildfire effects is challenging to interpret. This is, in part, because the impact forest treatments have on wildfire can be slight and variable across many factors. Effectiveness of a treatment also depends on the metric considered. We present and define human–fire interaction, fire behavior, and ecological metrics of forest treatment effects on wildfire and discuss important considerations and recommendations for evaluating treatments. We demonstrate these concepts using a case study from the Cameron Peak Fire in Colorado, USA. Pre-fire forest treatments generally, but not always, experienced reduced burn severity, particularly when surface fuels were reduced. Treatments in the Cameron Peak Fire have also been documented as increasing tree survivorship, aiding suppression efforts, promoting firefighter safety, and influencing fire spread. However, the impacts of pre-fire management on primary landscape-scale objectives, like watershed protection, are unknown. Discussions about the influence of pre-fire treatments on fire effects must define the indicator(s) being assessed, as the same treatment may be considered successful under one measure but not others. Thus, it is critical to bring a common language and understanding to conversations about treatment effects and advance efforts to evaluate the range of treatment effects, thus supporting treatment planning.
Temperature, Salinity and Garlic Additive Shape the Microbial Community during Traditional Beetroot Fermentation Process

Plant-based traditional fermented products are attracting a lot of interest in global markets. An example of them is beetroot leaven, which is valued for its high bioactive compound content. The variety of production recipes and the spontaneous nature of red beet fermentation favor its high diversity. This study aimed to analyze the impact of external factors—temperature, brine salinity, and garlic dose—on the beetroot fermentation and bacterial metapopulation responsible for this process. The research results confirmed the significant influence of the selected and analyzed factors in shaping the leaven physicochemical profile including organic acid profile and betalain content. Analysis of bacterial populations proved the crucial importance of the first 48 h of the fermentation process in establishing a stable metapopulation structure and confirmed that this is a targeted process driven by the effect of the analyzed factors. Lactobacillaceae, Enterobacteriaceae, and Leuconostocaceae were observed to be the core microbiome families of the fermented red beet. Regardless of the impact of the tested factors, the leaven maintained the status of a promising source of probiotic bacteria. The results of this research may be helpful in the development of the regional food sector and in improving the quality and safety of traditionally fermented products such as beetroot leaven.
Radiomic markers of intracerebral hemorrhage expansion on non-contrast CT: independent validation and comparison with visual markers

Objective To devise and validate radiomic signatures of impending hematoma expansion (HE) based on admission non-contrast head computed tomography (CT) of patients with intracerebral hemorrhage (ICH). Methods Utilizing a large multicentric clinical trial dataset of hypertensive patients with spontaneous supratentorial ICH, we developed signatures predictive of HE in a discovery cohort (n = 449) and confirmed their performance in an independent validation cohort (n = 448). In addition to n = 1,130 radiomic features, n = 6 clinical variables associated with HE, n = 8 previously defined visual markers of HE, the BAT score, and combinations thereof served as candidate variable sets for signatures. The area under the receiver operating characteristic curve (AUC) quantified signatures’ performance. Results A signature combining select radiomic features and clinical variables attained the highest AUC (95% confidence interval) of 0.67 (0.61–0.72) and 0.64 (0.59–0.70) in the discovery and independent validation cohort, respectively, significantly outperforming the clinical (pdiscovery = 0.02, pvalidation = 0.01) and visual signature (pdiscovery = 0.03, pvalidation = 0.01) as well as the BAT score (pdiscovery < 0.001, pvalidation < 0.001). Adding visual markers to radiomic features failed to improve prediction performance. All signatures were significantly (p < 0.001) correlated with functional outcome at 3-months, underlining their prognostic relevance. Conclusion Radiomic features of ICH on admission non-contrast head CT can predict impending HE with stable generalizability; and combining radiomic with clinical predictors yielded the highest predictive value. By enabling selective anti-expansion treatment of patients at elevated risk of HE in future clinical trials, the proposed markers may increase therapeutic efficacy, and ultimately improve outcomes.
Investigating the microbiome of house dust mites in South Korea

Understanding the house dust mites (HDMs) microbiome is crucial due to its potential effects on the development of allergic diseases. In 1998, our laboratory collected Dermatophagoides farinae and D. pteronyssinus from beds in a Korean household and began cultivating these HDMs. Our laboratory has been actively investigating several topics about HDMs in recent years, including the bacterial and fungal microbiome and their interactions, as well as the impact of the HDM microbiome on airway inflammation. To study the D. farinae microbiome, we employed high-throughput sequencing of the 16S rDNA amplicons. The results revealed that the two most abundant bacteria were Enterococcus faecalis and Bartonella spp. In contrast, we found almost no bacteria in D. pteronyssinus. By inoculating bacteria to HDMs, we found that D. farinae is more susceptible to bacteria than D. pteronyssinus. This susceptibility was associated with the presence of certain fungal species in D. pteronyssinus. Additionally, we have recently made efforts to produce HDMs with reduced levels of symbiotic bacteria. We believe that standardizing and controlling the microbiome in HDMs are crucial steps for the future development and improvement of allergic immunotherapies.
Enhancing CSR activities to increase bank attractiveness

Abstract This study is carried out to investigate the impact of CSR activities on bank attractiveness in Vietnamese commercial banks. The data was collected from 1167 customers in Ho Chi Minh city. The independent variables were CSR for customers, CSR for employees, and CSR for social public welfare, while the dependent variable was bank attractiveness, and an intermediate variable was bank reputation. SmartPLS 3.0 software was used to process the model in two steps. The findings revealed that all three components of CSR had a direct effect on bank reputation, with CSR for social public welfare having the greatest influence. Bank attractiveness also had a significant impact on a bank’s reputation. CSR components all had an indirect impact on bank attractiveness via the mediated influence of reputation. Academically, the research findings indicate that CSR activities are now important in attracting customers for Vietnamese commercial banks. In practice, the findings assist bank administrators in recognizing the importance of factors in CSR activities and being proactive in implementing and formulating strategies.