Miracle-dz/UniFAR-FTUs huggingface dataset:
Validation of ET Estimates from the Canadian Prairie Agrometeorological Model for Contrasting Vegetation Types and Growing Seasons

The objective of this study was to establish the ability of the prairie agrometeorological model (PAMII) to simulate daily evapotranspiration (ET). Specifically, modelled ET estimates from PAMII were validated using daily ET estimates from eddy-covariance systems at West Nose Creek (barley field located northwest of Calgary, Alberta) and a FluxNet site (short-grass prairie located west of Lethbridge, Alberta). Additionally, PAMII was validated for three contrasting growing seasons at the grassland site to establish the model’s ability to quantify the effect of different growth conditions on ET. PAMII performed well and was able to capture the day-to-day variability of the ET at both sites. PAMII successfully captured the increase (decrease) in accumulated growing season ET for the wet (dry) growing seasons at the short-grass prairie site. Moreover, the optimal reference minimum stomatal resistance term was significantly lower for the barley crop (50 s m–1) than the corresponding value for the short-grass prairie (80 s m–1). At the grassland site the optimal stomatal resistance term varied markedly depending on the growing conditions; the optimal value for the wet year was 60 s m–1 compared to 90 s m–1 for the dry year. That is, no single value worked best for all years, and our findings caution against using a single value for the reference minimum stomatal resistance. In summary, PAMII captured the salient features of the ET variability at both sites and for contrasting at the grassland site. However, our research has identified several areas where future versions of the PAMII model might be improved.
Classification of Blood Volume Decompensation State via Machine Learning Analysis of Multi-Modal Wearable-Compatible Physiological Signals

This paper presents a novel computational algorithm to estimate blood volume decompensation state based on machine learning (ML) analysis of multi-modal wearable-compatible physiological signals. To the best of our knowledge, our algorithm may be the first of its kind which can not only discriminate normovolemia from hypovolemia but also classify hypovolemia into absolute hypovolemia and relative hypovolemia. We realized our blood volume classification algorithm by (i) extracting a multitude of features from multi-modal physiological signals including the electrocardiogram (ECG), the seismocardiogram (SCG), the ballistocardiogram (BCG), and the photoplethysmogram (PPG), (ii) constructing two ML classifiers using the features, one to classify normovolemia vs. hypovolemia and the other to classify hypovolemia into absolute hypovolemia and relative hypovolemia, and (iii) sequentially integrating the two to enable multi-class classification (normovolemia, absolute hypovolemia, and relative hypovolemia). We developed the blood volume decompensation state classification algorithm using the experimental data collected from six animals undergoing normovolemia, relative hypovolemia, and absolute hypovolemia challenges. Leave-one-subject-out analysis showed that our classification algorithm achieved an F1 score and accuracy of (i) 0.93 and 0.89 in classifying normovolemia vs. hypovolemia, (ii) 0.88 and 0.89 in classifying hypovolemia into absolute hypovolemia and relative hypovolemia, and (iii) 0.77 and 0.81 in classifying the overall blood volume decompensation state. The analysis of the features embedded in the ML classifiers indicated that many features are physiologically plausible, and that multi-modal SCG-BCG fusion may play an important role in achieving good blood volume classification efficacy. Our work may complement existing computational algorithms to estimate blood volume compensatory reserve as a potential decision-support tool to provide guidance on context-sensitive hypovolemia therapeutic strategy.
Haplotype-Resolved Genome Analyses Reveal Genetically Distinct Nuclei within a Commercial Cultivar of Lentinula edodes

Lentinula edodes is a tetrapolar basidiomycete with two haploid nuclei in each cell during most of their life cycle. Understanding the two haploid nuclei genome structures and their interactions on growth and fruiting body development has significant practical implications, especially for commercial cultivars. In this study, we isolated and assembled the two haploid genomes from a commercial strain of L. edodes using Illumina, HiFi, and Hi-C technologies. The total genome lengths were 50.93 Mb and 49.80 Mb for the two monokaryons SP3 and SP30, respectively, with each assembled into 10 chromosomes with 99.63% and 98.91% anchoring rates, respectively, for contigs more than 100 Kb. Genome comparisons suggest that two haploid nuclei likely derived from distinct genetic ancestries, with ~30% of their genomes being unique or non-syntenic. Consistent with a tetrapolar mating system, the two mating-type loci A (matA) and B (matB) of L. edodes were found located on two different chromosomes. However, we identified a new but incomplete homeodomain (HD) sublocus at ~2.8 Mb from matA in both monokaryons. Our study provides a solid foundation for investigating the relationships among cultivars and between cultivars and wild strains and for studying how two genetically divergent nuclei coordinate to regulate fruiting body formation in L. edodes.
Structural uncertainty and uncertainty management in four common Land Use Cover Change (LUCC) model software packages. A comparison

Research on the uncertainty of Land Use Cover Change (LUCC) models is still limited. Through this paper, we aim to globally characterize the structural uncertainty of four common software packages (CA_Markov, Dinamica EGO, Land Change Modeler, Metronamica) and analyse the options that they offer for uncertainty management.The models have been compared qualitatively, based on their structures and tools, and quantitatively, through a study case for the city of Cape Town. Results proved how each model conceptualised the modelled system in a different way, which led to different outputs. Statistical or automatic approaches did not prove to be more successful that user-driven approaches. The available options for uncertainty management vary depending on the model. No model pays enough attention to the communication of uncertainties.
Defect Detection in Woven Fabrics by Analysis of Co-occurrence Texture Features as a Function of Gray-level Quantization and Window Size

In this experimental research, the effects of gray-level quantization and tiling window size on 22 gray-level co-occurrence matrix features were investigated in the context of automated woven fabric defect detection. A dataset comprising 1426 128×128 images was used, in which defective and the defect-free images were split in a 50:50 ratio. Experiments were carried out with seven quantization levels (LL = 4, 8, 16, 32, 64, 128 and 256) and four window sizes (NN = 8, 16, 32, 64). The features were extracted from each image in the training set for each< LL,NN >combination and thereafter were ranked using the joint mutual information metric. Next, for each < LL,NN > combination, a k-nearest neighbour classifier was trained, first with only the highest-ranking feature and thereafter iteratively by adding features of lower ranks. It was observed that a minimum of nine features were needed to achieve an acceptable (>90%) F1 score for any < LL,NN >combination, except when NN is relatively large. The two features that contribute to improving the F1 score for any < LL,NN >combination were found to be Homogeneity I and Homogeneity II. It was also noted that using an 8×8 window on images with 128 gray levels resulted in a practically usable high F1 score (96.39%) with the least number of features (14).
Going Online?—Can Online Exercise Classes during COVID-19-Related Lockdowns Replace in-Person Offers?

Germany experienced a 6-month second lockdown (November 2020–April 2021) during the COVID-19 pandemic, which included the closure of all physical activity (PA) facilities. The use of online exercise classes (OECs) was promoted by public health and exercise organizations. Using the present cross-sectional online survey, we assess the use of and opinion towards OECs in Germany during the second lockdown. We used contingency tables and the Chi2 test to calculate the frequency of awareness and use of OECs according to PA status, well-being and demographic data, and conducted a binary logistic regression with OEC awareness or use and dichotomized independent predictors. The associations between opinion and activity status, frequency of use, educational attainment, age and body mass index were calculated using Spearman correlations. A total of 993 datasets were analyzed in detail. Of the 785 (79.1%) participants reporting awareness of OECs, 536 tried them, and 262, 188 and 85 used them <1 per week, 1–2 per week and ≥3 per week, respectively. The users were typically active, female participants with poorer mental well-being. The opinions towards OECs varied according to participant characteristics, such as activity status, BMI and age. Overall, regular OEC use was quite limited, and, as such, cannot replace in-person exercise opportunities. Keeping physical activity facilities open and safe must be prioritized in the ongoing pandemic.
A Secure Visual Secret Sharing Scheme with Authentication Based on QR Code

: With the rise of the Internet of Things (IoT), various devices in life and industry are closely linked. Because of its high payload, stable error correction capability, and convenience in reading and writing, Quick Response (QR) code has been widely researched in IoT. However, the security of privacy data in IoT is also a very important issue. At the same time, because IoT is developing towards low-power devices in order to be applied to more fields, the technology protecting the security of private needs to have the characteristics of low computational complexity. Visual Secret Sharing (VSS), with its features of safety and low computational cost, can fully meet the requirements of communication security in IoT. Therefore, a VSS scheme with QR code (VSS-QR) was proposed and has been applied to some extent. In VSS-QR, the secret is shared into a series of shares. These shares are usually common QR codes, which cannot cause the attention of the attacker. However, if there is dishonesty among participants, the secret cannot be recovered, which will lead to VSS-QR cannot be widely used due to its inadequate security. In this paper, we propose a visual secret sharing scheme with authentication based on QR code (VSSA-QR). Both the reconstructed secret QR code and shares can be verified whether they are forged by attackers. The above-mentioned operations conveniently are performed on low-power QR scanning devices. Not only does the proposed scheme prevent some dishonest participants or attackers from cheating, but also prevent all participants from conspiring. In addition, the payload is the QR code itself, which is higher than other schemes. Theoretical analysis and experiments prove that the proposed scheme is effective.
Crossmodal Harmony: Looking for the Meaning of Harmony Beyond Hearing

The notion of harmony was first developed in the context of metaphysics before being applied to the domain of music. However, in recent centuries, the term has often been used to describe especially pleasing combinations of colors by those working in the visual arts too. Similarly, the harmonization of flavors is nowadays often invoked as one of the guiding principles underpinning the deliberate pairing of food and drink. However, beyond the various uses of the term to describe and construct pleasurable unisensory perceptual experiences, it has also been suggested that music and painting may be combined harmoniously (e.g., see the literature on “color music”). Furthermore, those working in the area of “sonic seasoning” sometimes describe certain sonic compositions as harmonizing crossmodally with specific flavor sensations. In this review, we take a critical look at the putative meaning(s) of the term “harmony” when used in a crossmodal, or multisensory, context. Furthermore, we address the question of whether the term's use outside of a strictly unimodal auditory context should be considered literally or merely metaphorically (i.e., as a shorthand to describe those combinations of sensory stimuli that, for whatever reason, appear to go well together, and hence which can be processed especially fluently).
Snow properties at the forest tundra ecotone: predominance of water vapor fluxes even in thick moderately cold snowpacks

Abstract. The forest-tundra ecotone is a large circumpolar transition zone between the Arctic tundra and the boreal forest, where snow properties are spatially variable due to changing vegetation. The extent of this biome through all circumpolar regions influences the climate. In the forest-tundra ecotone near Umiujaq in northeastern Canada (56°33'N, 76°28'W), we contrast the snow properties between two sites, TUNDRA (located in a low-shrub tundra) and FOREST (located in a boreal forest), situated less than 1 km apart. Furthermore, we evaluate the capability of the snow model Crocus, initially developed for alpine snow, to simulate the snow in this subarctic setting. Snow height and density differed considerably between the two sites. At FOREST, snow was about twice as deep as at TUNDRA. The density of snow at FOREST decreased slightly from the ground to the snow surface, in a pattern that is somewhat similar to alpine snow. The opposite was observed at TUNDRA, where the pattern of snow density was typical of the Arctic. Crocus was not able to reproduce the density profiles at either site using its standard configuration. We therefore implemented some modifications for the density of fresh snow, the effect of vegetation on compaction and the lateral transport of snow by wind. We demonstrate that upward water vapor transport is the dominant mechanism that shapes the density profile at TUNDRA, while a contribution of compaction due to overburden weight becomes visible at FOREST. The adjustments that were made to Crocus partly compensate for the lack of water vapor transport in the model, but are site-specific to some extent. Furthermore, the challenges using Crocus suggest that the general lack of water vapor transport in the snow routines used in climate models leads to an inadequate representation of even thick and moderately cold snowpacks, with possible major impacts on meteorological and climate projections.
Exploring Student’s Readiness and Behavioural Towards Virtual Learning via Microsoft Teams

Implementation of online learning in the era of COVID-19 pandemic has become a global issue and had a major impact on higher education. The Movement Control Order (MCO) carried out in Malaysia has affects many higher institutions. All students especially undergraduate students who just starting their new semester has forced to stay at home while learning activities continue virtually using a various platform such as Microsoft Teams. Microsoft Teams considered as an excellent collaboration platform complete with useful features to enhance virtual learning environment as well for educational purposes. The main objective of this research is to explore the level of student’s readiness and behaviour towards virtual learning using Microsoft Teams. The study uses a cross-sectional survey consist of 312 undergraduate students at Universiti Sains Islam Malaysia (USIM) from various program of study. Data were collected by using questionnaires to gain information about the students’ perception on their readiness and behaviour towards virtual learning via Microsoft Teams. By using descriptive statistical analysis, this study found that readiness among undergraduate students is at a medium high level, while student behaviour considered at a high-level despite Microsoft Teams platform is regarded as something new for the students. The finding revealed that students easily operate the platform without further training.
Determinant Factors of Founding-Family Firms’ Performance in Indonesia

This research aims to examine the factors that moderate the effect of founding-family firms on performance. Moderating variables include firm reputation, risk-taking behavior, agency costs of managers-shareholders, and agency costs of majority-minority shareholders. Firms’ performance includes accounting-based and market-based performance. This research uses 412 manufacturing firm-years listed on the Indonesian Stock Exchange as the research sample. The hypotheses test uses a random-effect regression as a main test and a common-effect regression tests as an alternative test. Based on data analysis, firm reputation, risk-taking behavior, agency costs of mangers-shareholders, and agency costs of majority-minority shareholders moderates the effect of the founding family on performance. It indicates that founding-family firms can achieve higher performance if they promote higher firm reputation, lower risk-taking behavior, and lower agency costs. This research fills the previous findings gap of performance in the founding-family firms. This research captures when founding-family firms can improve performance or experience performance reduction. To the best of the author's knowledge, this research is also the first research that provides a comprehensive picture of determinant factors of founding-family firms' in Indonesia.
Soft Palate Variation in Oral Submucous Fibrosis

One among the most prevalent precancerous disorders affecting oral cavity in those who consume arecanut and gutka is oral submucous fibrosis (OSMF). The anatomy of the soft palate alters as this illness proceeds and can act as a marker for disease. OSMF prevalence varies by area and ethnicity, and is closely linked to behaviours, culture, and cuisine. People in South and Southeast Asia have the greatest frequency of OSMF.OSMF has afflicted 2.5 million individuals globally, with a total of five million in the Indian individuals. The percentage of OSMF patients with dysplasia might range from 12 to 15 percent. Malignant changes occurs at a rate of 4–13 percent around world, but 7.6 percent in the Indian subcontinent. The anatomy of the soft palate in OSMF patients has been studied in a number of ways. Cephalometric analysis is highly used methods for measuring the soft palate in both healthy and OSMF patient. On lateral cephalometry, the soft palate shows a variety of radiographic appearances. Early cephalometry diagnosis of OSMF plays a vital role in treatment of disease. Soft palate becomes thick and heavy as OSMF advances, and considerable changes in soft palate dimensions occur, which may be better assessed by CBCT. This review work compared studies from several researchers, and observed that Type 1soft palate is the most prevalent, while type 6 soft palate is the least common.
Assessing the Performance of a Subsurface Water Retention System (SWRS) Prototype: First Evaluation of Work Productivity and Costs

The potential to use Subsurface Water Retention Systems (SWRSs) to combat desertification and improve agriculture in arid and semiarid areas has already been investigated and proved promising. Nevertheless, a lack of specific machinery has prevented this technology from demonstrating its effectiveness on vast areas. In the present study, a specific prototype is presented along with the results obtained from a preliminary study conducted to assess effectiveness, performance and associated cost. During the test, the machinery permitted the construction of a SWRS 100 cm belowground using a 140 kW tractor. The effective field capacity (EFC) averaged at 0.19 ha h−1 whilst total cost was estimated to be as high as 4800.00 € ha−1. However, 93% of the cost was associated with the purchase cost of the removable impermeable film. A removal operation was also investigated using a 42 kW excavator for evaluating the EFC and cost which averaged at 0.2 ha h−1 and 655.79 € ha−1, respectively.
Screening of Acrylamide of Par-Fried Frozen French Fries Using Portable FT-IR Spectroscopy

Current assays for acrylamide screening rely heavily on LC-MS/MS or GC-MS, techniques that are not suitable to support point of manufacturing verification because it can take several weeks to receive results from a laboratory. A portable sensor that can detect acrylamide levels in real-time would enable in-house testing to safeguard both the safety of the consumer and the economic security of the agricultural supplier. Our objective was to develop a rapid, accurate, and real-time screening technique to detect the acrylamide content in par-fried frozen French fries based on a portable infrared device. Par-fried French fries (n = 70) were manufactured at times ranging from 1 to 5.5 min at 180 °C to yield a wide range of acrylamide levels. Spectra of samples were collected using a portable FT-IR device operating from 4000 to 700 cm−1. Acrylamide was extracted using QuEChERS and quantified using uHPLC-MS/MS. Predictive algorithms were generated using partial least squares regression (PLSR). Acrylamide levels in French fries ranged from 52.0 to 812.8 µg/kg. The best performance of the prediction algorithms required transformation of the acrylamide levels using a logarithm function with models giving a coefficient of correlation (Rcv) of 0.93 and RPD as 3.8, which means the mid-IR model can be used for process control applications. Our data corroborate the potential of portable infrared devices for acrylamide screening of high-risk foods.
Interactions among Topic-Specific Pedagogical Content Knowledge Components for Science Teachers: The Impact of Content Knowledge

ABSTRACT This study investigated in what ways and to what extent the interactions between the components of pedagogical content knowledge (PCK) differ for junior high school science teachers with different levels of content knowledge. Data were collected from three science teachers through semi-structured interviews and classroom observations. The participants’ content knowledge was analyzed based on inductive coding and the teachers were labeled as curriculum-led, content-expert, and content-novice. Interactions among PCK components were analyzed by making an in-depth analysis of explicit PCK. This included constructing PCK maps for each participant. Then, the constant comparative method was used to clarify differences in interactions among PCK components. Five assertions were proposed based on the differences among PCK interactions: (a) the curriculum-led teacher had the most integrated PCK map and the interactions were mainly reciprocal; (b) the most frequent interactions between knowledge of assessment and the other PCK components were observed in the content-expert teacher; (c) the most frequent interactions between knowledge of curriculum and the other PCK components were observed in the curriculum-led teacher’s teaching; (d) the content-novice teacher’s orientation interacted with the other PCK components more than in the other two participants’ teaching; (e) the main ideas of the interactions among PCK components changed depending on the teachers’ content knowledge. The findings are discussed and suggestions for researchers and teachers are provided.