Miracle-dz/UniFAR-FTUs huggingface dataset:
Effects of Diastolic Blood Pressure on Brain Structures and Cognitive Functions in Middle and Old Ages: Longitudinal Analyses

Hypertension is a pervasive public health concern due to strong associations with cardiovascular diseases and stroke. Alternatively, the associations between hypertension and the risk of Alzheimer’s disease are complex and recent large sample studies reported positive associations. In this paper, we examine the associations between diastolic blood pressure (BP) and subsequent changes in brain structure and cognitive function over several years by multiple regression analyses (with adjustment for a wide range of potential confounding variables) among a large cohort from the UK Biobank. Higher baseline diastolic BP was associated with a slightly smaller relative increase (relative improvements) in reaction time and a slightly greater reduction in depression scores. Higher baseline diastolic BP was also associated with a greater total gray matter volume (GMV) retention, while aging alone was associated with GMV reduction. White matter microstructural analyses revealed that a greater diastolic BP was associated with reduced longitudinal mean and regional fractional anisotropy, greater increases in mean and regional mean diffusivity, radial diffusivity, and axial diffusivity, a greater decline in mean intracellular volume fraction, and greater increases in mean and regional isotropic volume fraction. These white matter microstructural changes were consistent with those seen in the aging process. Additional analyses revealed a greater cheese intake level at baseline, which is associated with a subsequent decline in diastolic BP and a relative subsequent increase in depressive tendency together with a relative increase in fluid intelligence and visuospatial memory performance. These results are congruent with the view that a higher BP in the aging brain has a complex role.
Screening, isolation, and characterization of amylase-producing bacteria from Poring Hot Spring Sabah, Malaysia

Abstract. Fazal BZ, Budiman C, Amin Z, Ling CMW. 2022. Screening, isolation, and characterization of amylase-producing bacteria from Poring Hot Spring Sabah, Malaysia. Biodiversitas 23: 2807-2815. Thermostable ? -amylases are being used in a wide range of industries, including food, textiles, detergents, pharmaceuticals, and fine chemicals. A good source of thermostable ? -amylases in thermophilic bacteria is found in high-temperature habitats like hot springs. Hence, this study aimed to screen, isolate, and characterize amylase-producing bacteria (APB) from the Poring hot spring in Sabah. Sediment and water samples were collected from the hot springs, serially diluted, plated onto the Luria Bertani agar medium containing starch, and incubated at 60°C for 48 hours. The amylase-producing bacterium was identified by the halo formation around the colony after the agar medium was stained with Lugol's solution. Nine colonies were found to be able to form halo zones, with a creamy colony (A7 strain) producing the highest amylolytic index (4.24). Further characterization of the A7 strain showed that the isolate was a Gram-positive, rod-shaped bacterium, with a positive reaction upon oxidase and catalase tests. The 16S rRNA sequence showed that the A7 strain had 99.81% similarity with the Anoxybacillus flavithermus, and therefore identified as A. flavithermus A7 strain. Further, the growth curve analysis indicated that the A7 strain grew well at 60°C. The 3, 5-dinitrosalicyclic acid (DNS) assay showed the crude enzyme secreted by the A7 strain exhibited optimum amylase activity at 60°C with 8.6 x 10-2 U/ml. This is the first APB obtained from hot springs in Sabah and promising for further studies and applications.
Brief communication: Structural monitoring for lifetime extension of offshore wind monopiles: can strain measurements at one level tell us everything?

Abstract. Operators need accurate knowledge on structural reserves to decide about lifetime extension of offshore wind turbines. Load monitoring enables us to directly compare design loads with real loading histories of the support structure in order to calculate its remaining useful lifetime. Monitoring of every hot spot is technically and financially not feasible. This paper presents a novel idea for load monitoring of monopiles. It requires strain measurements at only one level convenient for sensor installation, such as tower bottom. Measurements are converted into damage equivalent loads for 10 min time intervals. Damage equivalent loads are extrapolated to other locations of the structure with a simulation model and statistical algorithm. For this, structural loads at all locations of the monopile are calculated with aero-hydro-elastic software and updated finite element models. Damage equivalent loads at unmeasured locations are predicted from the simulation results with a k-nearest neighbor regression algorithm. The extrapolation was tested with numerical simulations of an 8 MW offshore wind turbine. Results show that damage can be predicted with an error of 1–3 % if this is done conditional on mean wind speed, which is very promising. The load monitoring concept is simple, cheap and easy to implement. This makes it ideal for making decisions on lifetime extension of monopiles.
Parametric approach to promote a divergence-free flow in the image-based motion estimation with application to bioirrigation

Flow fields are determined from image sequences obtained in an experiment in which benthic macrofauna, Arenicola marina, causes water flow and the images depict the distribution of a tracer that is carried with the flow. The experimental setup is such that flow is largely two-dimensional, with a localised region where the Arenicola resides, from which flow originates. Here, we propose a novel parametric framework that quantifies such flow that is dominant along the image plane. We adopt a Bayesian framework so that we can impart certain physical constraints on parameters into the estimation process via prior distribution. The primary aim is to approximate the mean of the posterior distribution to present the parameter estimate via Markov Chain Monte Carlo. We demonstrate that the results obtained from the proposed method provide more realistic flows (in terms of divergence magnitude) than those computed from classical approaches such as the multi-resolution Horn–Schunk method. This highlights the usefulness of our approach if motion is largely constrained to the image plane with localised fluid sources.
How Should a Robot Approach a Pair of People

This thesis experimentally investigates the comfort of pairs of seated people when they are approached by a robot from different directions. While the effect of robot approach direction on the comfort of a lone person has been investigated previously, the extension to a robot approaching pairs of people has not been explored rigorously. Three maximally-different seating configurations of paired people and eight different robot approach directions were considered. The experiment was augmented with a fourth seating configuration of a lone individual, allowing the responses of grouped and lone participants to be compared. Data obtained from the experiment were analysed using both linear and directional statistics. Results from 180 unique participants showed that the comfort of a person when a robot approached is influenced by the presence and location of a second person. Analysis of these data with directional statistics showed that participant comfort preference clusters into angular regions of ‘suitable for robot approach’ and ‘unsuitable for robot approach’. This finding shows the importance of avoiding robot approach directions of low comfort, rather than selecting a singular robot approach direction of high comfort. Rayleigh’s test of uniformity, a directional statistics method, also shows across all participant configurations that robot approach directions that minimise participant discomfort align spatially with regions that allow for good line of sight of the robot by both people, and are centred on the largest open space that a robot could approach the group from. Participants who were grouped also regarded the robot as having more social agency than did lone experimental participants. Grouped participants were less frustrated with the experimental task and also found it less physically and temporally demanding in comparison to lone experimental participants.
Link between Omega 3 Fatty Acids Carried by Lipoproteins and Breast Cancer Severity

According to the International Agency for Research on Cancer (IARC) more than 10% of cancers can be explained by inadequate diet and excess body weight. Breast cancer is the most common cancer affecting women. The goal of our study is to clarify the relationship between ω3 fatty acids (FA) carried by different lipoproteins and breast cancer (BC) severity, according to two approaches: through clinic-biological data and through in vitro breast cancer cell models. The clinical study has been performed in sera from a cohort of BC women (n = 140, ICO, France) whose tumors differed by their hormone receptors status (HR− for tumors negative for estrogen receptors and progesterone receptors, HR+ for tumors positive for either estrogen receptors or progesterone receptors) and the level of proliferation markers (Ki-67 ≤ 20% Prolif− and Ki-67 ≥ 30% Prolif+). Lipids and ω3FA have been quantified in whole serum and in apoB-containing lipoproteins (Non-HDL) or free of it (HDL). Differences between Prolif− and Prolif+ were compared by Wilcoxon test in each sub-group HR+ and HR−. Results are expressed as median [25th–75th percentile]. Plasma cholesterol, triglycerides, HDL-cholesterol and Non-HDL cholesterol did not differ between Prolif− and Prolif+ sub-groups of HR− and HR+ patients. Plasma EPA and DHA concentrations did not differ either. In the HR− group, the distribution of EPA and DHA between HDL and Non-HDL differed significantly, as assessed by a higher ratio between the FA concentration in Non-HDL and HDL in Prolif− vs. Prolif+ patients (0.20 [0.15–0.36] vs. 0.04 [0.02–0.08], p = 0.0001 for EPA and 0.08 [0.04–0.10] vs. 0.04 [0.01–0.07], p = 0.04 for DHA). In this HR− group, a significant increase in Non-HDL EPA concentration was also observed in Prolif− vs. Prolif+ (0.18 [0.13–0.40] vs. 0.05 [0.02–0.07], p = 0.001). A relative enrichment on Non-HDL in EPA and DHA was also observed in Prolif− patients vs. Prolif+ patients, as assessed by a higher molar ratio between FA and apoB (0.12 [0.09–0.18] vs. 0.02 [0.01–0.05], p < 0.0001 for EPA and 1.00 [0.73–1.69 vs. 0.52 [0.14–1.08], p = 0.04 for DHA). These data were partly confirmed by an in vitro approach of proliferation of isolated lipoproteins containing EPA and DHA on MDA-MB-231 (HR−) and MCF-7 (HR+) cell models. Indeed, among all the studied fractions, only the correlation between the EPA concentration of Non-HDL was confirmed in vitro, although with borderline statistical significance (p = 0.07), in MDA-MB-231 cells. Non-HDL DHA, in the same cells model was significantly correlated to proliferation (p = 0.04). This preliminary study suggests a protective effect on breast cancer proliferation of EPA and DHA carried by apo B-containing lipoproteins (Non-HDL), limited to HR− tumors.
Screening of the Supercritical Impregnation of Olea europaea Leaves Extract into Filaments of Thermoplastic Polyurethane (TPU) and Polylactic Acid (PLA) Intended for Biomedical Applications

The leaves of Olea europaea as agricultural waste represent a convenient source of antioxidants. In combination with supercritical CO2 (scCO2), assisted impregnation is an interesting strategy for the preparation of biomedical devices with specific bioactivity. For this purpose, 3D-printable filaments of thermoplastic polyurethane (TPU) and polylactic acid (PLA) were employed for the supercritical impregnation of ethanolic olive leaves extract (OLE) for biomedical application. The extraction of OLE was performed using pressurized liquids. The effect of pressure (100–400 bar), temperature (35–55 °C), and the polymer type on the OLE impregnation and the swelling degree were studied including a morphological analysis and the measurement of the final antioxidant activity. All the studied variables as well as their interactions showed significant effects on the OLE loading. Higher temperatures favored the OLE loading while the pressure presented opposite effects at values higher than 250 bar. Thus, the highest OLE loadings were achieved at 250 bar and 55 °C for both polymers. However, TPU showed c.a. 4 times higher OLE loading and antioxidant activity in comparison with PLA at the optimal conditions. To the best of our knowledge, this is the first report using TPU for the supercritical impregnation of a natural extract with bioactivity.
Assessing the importance of mesoscale sea‐surface temperature variations for surface turbulent cooling of the Kuroshio Extension in wintertime

Western boundary currents are well known to exhibit a strong eddy field and meandering on subseasonal timescales and wavelengths of a few hundreds of kilometers. However, the extent to which the ocean mesoscale activity associated with these motions can enhance the turbulent air–sea heat flux averaged over a large spatial domain has not been fully characterized. This study aims to do so during the cold season using reanalysis data and simplified air–sea interaction models. The correlation between sea‐surface height anomaly and the wintertime mean heat fluxes does not indicate any significant relations between eddy activity and large‐scale surface heat flux in the Kuroshio Extension during winter over the 2003–2018 period. The results from simple models designed to isolate the contributions from the eddies suggest that the eddy enhancement of the heat flux via a rectified effect (a bit more anomalous cooling over a warm mesoscale feature than anomalous heating over a cold one) is small compared with the long‐time, large‐spatial scale mean in the reanalysis data, especially along the Kuroshio Extension. It is found larger north of it, where it can reach 5 W ·$$ \cdotp $$ m −2$$ {}^{-2} $$ . Although different datasets might disagree about the level of energy of the sea‐surface temperature field at the mesoscale, a simple scaling analysis gives confidence in the relatively small values of the rectified effect found here.
On the multi-agent stochastic simulation of occupants in buildings

This paper introduces a new general platform for the simulation of occupants' presence and behaviours. Called No-MASS (Nottingham Multi-Agent Stochastic Simulation), this generates a synthetic population of agents, predicts their presence and, in the case of residences also their activities and inferred locations, as well as their use of windows, lights and blinds. Using the Functional Mockup Interface, No-MASS is coupled with EnergyPlus: EnergyPlus parses environmental parameters to No-MASS which in turn parses back the energetic consequences of agents' behaviours. After describing the architecture of No-MASS and the form of the integrated models, we demonstrate its utility through two use cases: a house and an office. We close by outlining how No-MASS has been extended to more comprehensively simulate the behaviours of agents occupying multiple buildings, including behaviours for which data is scarce, social interactions between agents, and a generalization of No-MASS to simulate electrical devices and their interactions.
Morphosemantic features in Universal Grammar: What we can learn from Marshallese pronouns and demonstratives

Abstract This article analyzes Marshallese pronouns and demonstratives, arguing that both privative and binary morphosemantic features are necessary, and that the two types coexist in a single domain. Marshallese encodes number with atomic, and person with [$\pm$author] and [$\pm$participant]. In the complex system of Marshallese demonstratives, atomic and [$\pm$human] map to the same head, subject to a constraint that only one feature appears at a time. The element $\chi$, which derives person orientation in demonstratives and pronouns, does not universally map to the same syntactic position. While in Heiltsuk $\chi$ is a dependent of the person head, in Marshallese it heads a projection above the person head. And while in Heiltsuk the person features occupy the same position in both pronouns and demonstratives, Marshallese pronouns have a different structure, with person and number features mapping to a single syntactic head. The contribution of UG is thus not a set of specific features or specific structures, but a set of more abstract principles.
The Use of the Exploratory Sequential Approach in Mixed-Method Research: A Case of Contextual Top Leadership Interventions in Construction H&S

Quality and rigour remain central to the methodological process in research. The use of qualitative and quantitative methods in a single study was justified here against using a single method; the empirical output from the literature review should direct the current worldview and, subsequently, the methodologies applied in research. It is critical to gather contextual behavioural data from subject matter experts—this helps establish context and confirm the hypotheses arising from the literature, which leads to the refinement of the theory’s applicability for developing a conceptual model. This paper identified the top leaders in construction organisations as subject matter experts. Nine semi-structured interviews were conducted, representing the South African construction industry grading. The output of the refined hypothesis was followed by a survey that targeted n = 182 multi-level senior leaders to gather further perspectives and validate the conceptual model. The outcome resulting from the rigorous validation process adopted—the analysis process, which included Spearman rank correlation, ordinal logistic regression and multinomial generalised linear modelling—demonstrated that the lack of H&S commitment in top leadership persists, despite high awareness of the cruciality of H&S in their organisations. Contextual competence, exaggerated by the local setting, is one source of this deficiency. This paper provides guidelines for using the exploratory sequential approach in mixed-method research to effectively deal with contextual issues based on non-parametric modelling data in top leadership H&S interventions.
Artificial Intelligence's Fair Use Crisis

As automation supplants more forms of labor, creative expression still seems like a distinctly human enterprise. This may someday change: by ingesting works of authorship as “training data,” computer programs can teach themselves to write natural prose, compose music, and generate movies. Machine learning is an artificial intelligence (AI) technology with immense potential and a commensurate appetite for copyrighted works. In the United States, the copyright law mechanism most likely to facilitate machine learning’s uses of protected data is the fair use doctrine. However, current fair use doctrine threatens either to derail the progress of machine learning or to disenfranchise the human creators whose work makes it possible. This Article addresses the problem in three parts: using popular machine learning datasets and research as case studies, Part I describes how programs “learn” from corpora of copyrighted works and catalogs the legal risks of this practice. It concludes that fair use may not protect expressive machine learning applications, including the burgeoning field of natural language generation. Part II explains that applying today’s fair use doctrine to expressive machine learning will yield one of two undesirable outcomes: if US courts reject the fair use defense for machine learning, valuable innovation may move to another jurisdiction or halt entirely; alternatively, if courts find the technology to be fair use, sophisticated software may divert rightful earnings from the authors of input data. This dilemma shows that fair use may no longer serve its historical purpose. Traditionally, fair use is understood to benefit the public by fostering expressive activity. Today, the doctrine increasingly serves the economic interests of powerful firms at the expense of disempowered individual rightsholders. Finally, in Part III, this Article contemplates changes in doctrine and policy that could address these problems. It concludes that the United States’ interest in avoiding both prongs of AI’s fair use dilemma offers a novel justification for redistributive measures that could promote social equity alongside technological progress.
Exploiting Feature Selection in Human Activity Recognition: Methodological Insights and Empirical Results using Mobile Sensor Data

Human Activity Recognition (HAR) using mobile sensor data has gained increasing attention over the last few years, with a fast-growing number of reported applications. The central role of machine learning in this field has been discussed by a vast amount of research works, with several strategies proposed for processing raw data, extracting suitable features, and inducing predictive models capable of recognizing multiple types of daily activities. Since many HAR systems are implemented in resource-constrained mobile devices, the efficiency of the induced models is a crucial aspect to consider. This paper highlights the importance of exploiting dimensionality reduction techniques that can simplify the model and increase efficiency by identifying and retaining only the most informative and predictive features for activity recognition. More in detail, a large experimental study is presented that encompasses different feature selection algorithms as well as multiple HAR benchmarks containing mobile sensor data. Such a comparative evaluation relies on a methodological framework that is meant to assess not only the extent to which each selection method is effective in identifying the most predictive features but also the overall stability of the selection process, i.e., its robustness to changes in the input data. Although often neglected, in fact, the stability of the selected feature sets is important for a wider exploitability of the induced models. Our experimental results give an interesting insight into which selection algorithms may be most suited in the HAR domain, complementing and significantly extending the studies currently available in this field.
A War on Sugar? Effects of Reduced Sugar Content and Package Size in the Soda Category

Increased consumer demand for healthier product options and looming regulation have prompted many consumer goods brands to adjust the amount of sugar content in their product lines, including adding products with reduced sugar content or smaller package sizes. Even as brands adopt such practices, little guidance exists for how they should do so to protect or enhance their brand performance. This research studies whether and when sugar reduction strategies affect sales. The analysis of almost 130,000 product additions by nearly 80 brands over 11 years in the U.S. soda category shows that, on average, products with sugar content reductions perform comparably to similar products without reduced sugar content, while smaller package sizes perform better. Importantly, these effects depend substantially on product labeling, branding, and packaging decisions. By accounting for these contingent effects, this study establishes win–win conditions, in which brands realize higher volume sales while category-level sugar sales decrease. In doing so, the study sheds light on how marketing can bridge brands’ sales objective with society's health focus, doing well and doing good simultaneously.