Miracle-dz/UniFAR-FTUs huggingface dataset:
Retrieving and Analyzing Taste Colexifications from Lexibank

Colexifications have enjoyed a considerable amount of popularity in the recent years. However, there are still many semantic domains, where not much research on colexification patterns has been carried out so far. Here we show, how the recently published Lexibank repository can be queried to yield colexification data on taste colexifications which can in turn be easily plotted on geographic maps
Permafrost, heat flow, and the geothermal regime at Prudhoe Bay, Alaska

Temperature measurements through permafrost in the oil field at Prudhoe Bay, Alaska, combined with laboratory measurements of the thermal conductivity of drill cuttings permit an evaluation of in situ thermal properties and an understanding of the general factors that control the geothermal regime.A sharp contrast in temperature gradient at approx.600 m represents a contrast in thermal conductivity caused by the downward change from interstitial ice to interstitial water at the base of permafrost under near steady state conditions. Interpretation of the gradient contrast in terms of a simple mode for the conductivity of an aggregate yields the mean ice content (approx.39%), and thermal conductivities for the frozen and thawed section (8.1 and 4.7 mcal/cm s /sup 0/C, respectively). These results yield a heat flow of approx.1. 3 HFU, which is similar to other values on the Alaskan Arctic Coast; the anomalously deep permafrost is a result of the anomalously high conductivity of the siliceous ice-rich sediments. Curvature in the upper 160 m of the temperature profiles represents a warming of approx.1. 8 /sup 0/C of the mean surface temperature and a net accumulation of 5--6 kcal/cm/sup 2/ by the solid earth surface during the last 100 years or so. Rising sea levelmore » and thawing of ice-rich sea cliffs probably caused the shoreline to advance tens of kilometers in the last 20,000 years, inundating a portion of the continental shelf that is presently the target of intensive oil exploration. A simple conduction model suggests that this recently inundated region is underlain by near-melting ice-rich permafrost to depths of 300--500 m; its presence is important to seismic interpretations in oil exploration and to engineering considerations in oil production. With confirmation of the permafrost configuration by offshore drilling, heat conduction models can yield reliable new information on the chronology of arctic shorelines. « less
Canine location in diﬀerent maxillomandibular relationships in Egyptians and Saudis

The standards or proportions commonly used as guides for the selection of maxillary anterior teeth for a removable prosthesis have been developed mainly on Caucasian populations with normal ridge relationships. Purpose: This study was conducted to determine the canine position in relation to commissures in different maxillomandibular relationships among Egyptian and Saudi populations. Material and methods: Two hundred subjects participated in this study, 100 from each population. The location of the corners of the mouth for each subject was marked on the buccal surface of a screen previously constructed on the maxillary cast and transferred to the casts. The distances between the corners of the mouth and the canines’ distal aspect were measured on the casts. The measurements were subdivided according to their relation to the commissures: at commissures, medial to commissures, or distal to commissures. The data were then statistically analyzed. Results: Coincidence between the canine distal aspects and commissures was recorded only within 8% of both Egyptian and Saudi populations. Additionally, within the Egyptian population, coincidence was recorded only at Class-I ridge relationship. Conclusion: Commissures are not a reliable landmark for determination of the distal aspect of the canine distal aspects of both Egyptian and Saudi populations.
AIC-3 Contribution from Cloudinary: CID22

—We propose a new methodology for large-scale subjective quality assessment of compressed still images in the high fidelity range (medium quality to visually lossless). It combines two different assessment protocols, one based on pairwise comparisons, the other aimed at obtaining absolute opinions. The methodology is designed to allow assessing the range of qualities not well-covered by previous methodologies, and to be suitable for large-scale crowd-sourced experiment setups. This new methodology was applied to create CID22 — the Cloudinary Image Dataset ’22. It is a large set of 22,153 annotated images, mostly in the medium-high quality to near visually lossless range, originating from 250 pristine images compressed using JPEG, JPEG 2000, JPEG XL, HEIC, WebP, and AVIF, with a dense sampling of encoder settings. The quality scores are based on 1.4 million opinions. Using this data, we evaluate the performance of the various image encoders as well as various objective metrics.
Predicting Oil Content of Fresh Palm Fruit Using Transmission-Mode Ultrasonic Technique

In this paper, an ultrasonic technique is proposed to predict oil content in a fresh palm fruit. This is accomplished by measuring the attenuation based on ultrasonic transmission mode. Several palm fruit samples with known oil content by Soxhlet extraction (ISO9001:2008) were tested with our ultrasonic measurement. Amplitude attenuation data results for all palm samples were collected. The Feedforward Neural Networks (FNNs) are applied to predict the oil content for the samples. The Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) of the FNN model for predicting oil content percentage are 7.6186 and 5.2287 with the correlation coefficient (R) of 0.9193. Keywords— Non-destructive, ultrasonic testing, oil content, fresh palm fruit, neural network.
Gene expression profile analysis of colorectal cancer to investigate potential mechanisms using bioinformatics

: This study aimed to explore the underlying molecular mechanisms of colorectal cancer (CRC) using bioinformatics analysis. Using GSE4107 datasets downloaded from the Gene Expression Omnibus, the differentially expressed genes (DEGs) were screened by comparing the RNA expression from the colonic mucosa between 12 CRC patients and ten healthy controls using a paired t -test. The Gene Ontology (GO) functional and pathway enrichment analyses of DEGs were performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID) software followed by the construction of a protein–protein interaction (PPI) network. In addition, hub gene identification and GO functional and pathway enrichment analyses of the modules were performed. A total of 612 up- and 639 downregulated genes were identified. The upregulated DEGs were mainly involved in the regulation of cell growth, migration, and the MAPK signaling pathway. The downregulated DEGs were significantly associated with oxidative phosphorylation, Alzheimer’s disease, and Parkinson’s disease. Moreover, FOS , FN1 , PPP1CC , and CYP2B6 were selected as hub genes in the PPI networks. Two modules (up-A and up-B) in the upregulated PPI network and three modules (d-A, d-B, and d-C) in the downregulated PPI were identified with the threshold of Molecular Complex Detection (MCODE) Molecular Complex Detection (MCODE) score  4 and nodes  6. The genes in module up-A were significantly enriched in neuroactive ligand–receptor interactions and the calcium signaling pathway. The genes in module d-A were enriched in four pathways, including oxidative phosphorylation and Parkinson’s disease. DEGs, such as FOS , FN1 , PPP1CC , and CYP2B6 , may be used as potential targets for CRC diagnosis
Does the Size of Nanohydroxyapatite Associated With Anionic Collagen Scaffolds Interferes With Osteoblasts Bioactivity?

Objectives We aimed to evaluate the effect of nanohydroxyapatite morphology and its interaction with anionic collagen on osteoblast activity. Materials and Methods Murine osteoblasts were incubated with a commercial collagen scaffold (as a control) or collagen-nanohydroxyapatite scaffolds (Col-HANP) for 24 and 48 hours for viability and proliferation assessments by MTT and Ki67 immuno�uorescence, respectively. The hydroxyapatite nanoparticles were synthesized in three different morphologies/sizes (labeled as Col-HANP 0h, as Col-HANP 2h, and as Col-HANP 5h) as a function of the hydrothermal synthetic approach. Osteoblast's activity was investigated by bone alkaline phosphatase activity (ALP) and Von Kossa mineralization assays. For biocompatibility evaluation, the scaffolds were implanted subcutaneously in the dorsum of male Wistar rats for 7 and 15 days.
Solving adaptive sampling problems in graphical models using Markov decision process

In environmental management problems, decision should ideally rely on knowledge of the whole system. However, due to limited budget, in practice only a small part of the system is sampled and the complete system state is reconstructed from the sampled observations. In this article we consider the situation where the biological system under study is structured and can be modeled as a graphical model. Optimal sampling in such models still raises some methodological questions, like adaptive sampling, or the measure of the quality of a sample in terms of quality of reconstruction. Here, we present a way to formalise these two questions. The sample is chosen as the one which maximises the expected utility of information brought by the observations minus the sample cost. The utily is derived from the notion of Maximum a Posteriori . This problem is known to be NP -hard. We present how to modelit as a Markov decision process in order to build approximate solution methods based on Reinforcement Learning.
Balancing of Tourist Opinions for Sentiment Analysis Task

This article presents a proposal for the treatment of an unbalanced tourist database with emphasis on minority classes for its classification, in this case, one based on BERT, called BETO. This methodology originally forms part of the thesis project of the authors, with the objective of balancing data with a tourist focus and being able to measure the impact that it has on the classification of texts.
Observations of methyl nitrate in the lower stratosphere during STRAT: Implications for its gas phase production mechanisms

Methyl nitrate has been measured for the first time in the lower stratosphere at altitudes to 20.5 km during the December 1996 NASA Stratospheric Tracers of Atmospheric Transport (STRAT) deployment. Whole air samples were taken on board the NASA ER2 aircraft and analyzed using gas chromatography/mass spectrometry. Methyl nitrate was present at measurable levels throughout the entire altitude range covered. Taking advantage of the rather simple chemistry in the lower stratosphere compared to the troposphere, and considering the known in‐situ photochemical sources for methyl nitrate, the yield of methyl nitrate from the reaction of methyl peroxy radicals with NO was estimated.
Journal of Advanced Research in Business and Management Studies

MARA Digital's business performance (BP) since its inception in 2015 has been found to be unsatisfactory. This paper aims to determine whether competitiveness and organizational capabilities (OC) have an impact on BP. Empirical data were collected from 310 ICT retailers under Majlis Amanah Rakyat (MARA) and relevant hypotheses were tested using structural equation modelling (SMART PLS software). Findings indicate that OC has a direct and positive influence on BP. However, findings for competitiveness, which acts as a moderator in the relationship between OC and BP, were ambiguous. This study contributes to the theoretical understanding of the relations between OC and BP in start-up companies. The significant role played by OC is the most impactful factor in this study. Firms should understand how different resources and marketing strategies (price, place and promotion) affect their BP. In addition, improving BP that cultivates competitiveness through active acceptance of new technologies and an open mindset towards novel technical skills can directly enhance BP. MARA will benefit from this study through the promotion strategy and its implementation since the current promotion strategy was found to negatively affect business performance. MARA could increase its promotion budget as part of a more effective strategy. In other words, to maintain competitive advantage and be successful, start-up firms need to develop OC and use their physical, human and organizational assets, both tangible and intangible, towards this objective.
Software Requirements Negotiation: a Systematic Literature Review

Software requirements negotiation (SRN) is one of the most essential stages of software requirements engineering. SRN involves the stakeholder's interaction to reach a mutual understanding of the requirements for developing a software project. The increased research interest in requirements engineering has resulted in huge literature in the SRN domain. There is a need to investigate the broad of techniques, processes, and evaluation mechanisms used in the SRN research community. This study aims to examine and identify the existing methods, processes, evaluation mechanisms, quantity of publications, publication trends and demographics shaping SRN research domain. To accomplish our aim, we used an evidence-based systematic approach, and 67 relevant studies were ultimately chosen from the search process based on the formulated research questions. Our study result shows broad and promising SRN techniques that include agent-based negotiation, TAICOS, wikiwinwin and winbook. However, we found that the existing SRN techniques suffer from limitations that have stakeholders' communication gaps, interface issues to non-technical users, decision-making, and managing requirements changes. Moreover, our study found that 63% of the selected studies stated their SRN processes, with 22% adopting the basic SRN processes in winwin model. Five evaluation mechanisms were discovered, with case study and experiment most adopted by the selected studies with 44% and 30%, respectively. In conclusion, although research on SRN is recently gaining some traction, the works in the domain are insu�cient. Concrete proposals are needed to improve SRN in software requirements engineering research domain.
Calibration of an evapotranspiration model to simulate soil water dynamics in a semiarid rangeland

Soil is the largest reservoir of water in a catchment and evapotranspiration is the largest yearly output flux of water from the soil in semiarid environments at the catchment scale. Hydrologic stress is one of the typical characteristics of semiarid environments. The shortage of water affects all the biophysical processes and increases the nonlinearity in the rainfall–runoff relationship. A proper description of semiarid watersheds should include an accurate description of the wetting–drying cycle of the soil, which is critical to properly describe important processes such as the connection between the surface and the soil saturated zone, the production of runoff or the growth of plants. Evapotranspiration is typically modelled in comprehensive distributed hydrologic models (e.g. MIKE‐SHE or MODHMS) using functions that relate evapotranspiration to soil moisture and plant biomass through a set of empirical coefficients, which typically adopt some default values regardless of the conditions of the area where the model is applied. In this work, using a global and a local search algorithm, a three‐dimensional soil water flow model coupled to an evapotranspiration model is calibrated in a soil profile covered with grass in a semiarid environment. Four parameters for the water flow model and three parameters for the evapotranspiration model are calibrated. An existing trend between daily average soil moisture and daily maximum temperature is used as extra information during the calibration process. The results showed that the known relationship between maximum temperature and average soil moisture includes information on the seasonality of the atmospheric demand. Although total evapotranspiration is similar in all calibrations, the trade‐off between evaporation and transpiration is sensitive to this extra information mainly through one model parameter. Further research is necessary to identify the value of the parameter that produces the correct trade‐off. Copyright © 2008 John Wiley & Sons, Ltd.
Evaluation of Suitability of Primary Growth Models to Fit Bacterial Growth Under Metal Stress Conditions

The goal of this study was to evaluate the suitability of growth models to fit the growth data of metal resistant bacteria. The growth data obtained for chromium resistant isolates namely Bacillus cereus VITSH1 and Alcaligenes faecalis VITSIM2 cultured on nutrient agar amended with increasing concentrations Cr 3+ Cu 2+ and Cd 2+ were fit into growth models. The traditional methods for enumerating bacteria are not instantaneous, therefore necessitates mathematical models to study the behavior of microbes in a specific experimental condition. The logistic and Gompertz models were applied to obtain the predicted microbial numbers and to evaluate the suitability of the models to study the growth pattern in metal stress conditions. The logistic model fit the experimental data and was found to be superior to the Gompertz model. The results suggested that the logistic model could be successfully applied to study the growth pattern of bacteria in metal stress conditions.
Direct cDNA synthesis from single spheroids and primary cell samples

Cell culture and transcriptome analysis are foundational techniques for life scientists exploring a variety of complex cellular processes. Traditionally, two-dimensional (2D) cell cultures have been used, which lack organizational complexity and limit the ability to predict cell behavior in complex physiological environments. To better mimic in vivo conditions, three-dimensional (3D) cell culture methods and primary cell types are increasingly being used in a variety of research fields from basic cell biology to cancer research and drug discovery. However, these sample types can present significant research challenges. Here, direct cDNA synthesis from unpurified single-spheroid and primary cell samples is demonstrated, using the Invitrogen ™ SuperScript ™ IV CellsDirect ™ cDNA Synthesis Kit and the Invitrogen ™ SuperScript ™ IV Single Cell/ Low-Input cDNA PreAmp Kit . cDNA synthesis yields were evaluated by performing real-time PCR (qPCR) and comparing gene expression levels to a more traditional method using samples processed with Invitrogen ™ TRIzol ™ Reagent. The SuperScript IV kits were shown to perform well with multiple cell types using both 2D cell cultures and 3D spheroids, and as few as 10 primary cells. The possibility to perform cDNA synthesis directly from cell lysates, without the need for nucleic acid purification steps, not only saves time and reagents, but also was shown to improve yield and reproducibility. The SuperScript IV kits should be considered by researchers working with low-input cell samples, especially if the detection of rare transcripts is required.
Remote sensing aided spatial prediction of forest stem volume

Modern technology such as the Global Positioning System (GPS) and Geographical Information Systems (GIS) provide new opportunities for forest inventory. These technologies allow representation of forest variables using rasters with cell sizes on the order of 25 m. Such rasters can be estimated from remotely sensed data using models of the relationship between the image’s digital number and the forest variables. This thesis investigates the possibility of using estimation methods incorporating remotely sensed data as well as spatial similarity of neighbouring field measurements, to improve prediction accuracy compared to using only remotely sensed data. Two new spatial prediction methods are presented and evaluated: ordinary kriging using information about edges detected in remotely sensed images, and prediction using Markov Chain Monte Carlo (MCMC) simulation of a new Bayesian state-space model. In addition, ordinary kriging, stratified ordinary kriging, ordinary cokriging, collocated ordinary cokriging, simple kriging with varying local means, and spatial regression using the autoregressive response model, are also evaluated. The methods are applied to predict forest stem volume per hectare in boreal forest in northern Sweden (Lat. 64°14’N, Long. 19°40’E) using Landsat TM data and a large field sampled dataset. Prediction accuracy, as well as practical aspects of the methods, is evaluated. In particular, accuracy is compared with Ordinary Least Squares regression (OLS) using remotely sensed data. Spatial prediction was, with a few exceptions, more accurate than OLS regression. The largest improvement, 49% lower root mean square error (RMSE), was obtained for plot-level predictions by ordinary kriging using information of edges detected in remotely sensed images, although the method is dependent on densely sampled field data. Promising results were also obtained by simple kriging with varying local means. This method performed well (26% lower RMSE than OLS regression for stand-level predictions), is rather straight-forward to apply in practice, and not as dependent on densely sampled field data. The Bayesian state-space model did not provide improved predictions compared to OLS regression. However, Bayesian modelling is promising for application of spatial models of higher complexity than possible with the other methods.
Degradation of mangrove tissues by arboreal termites (Nasutitermes acajutlae) and their role in the mangrove C cycle (Puerto Rico): Chemical characterization and organic matter provenance using bulk δ13C, C/N, alkaline CuO oxidation‐GC/MS, and solid‐state 13C NMR

Arboreal termites are wood decaying organisms that play an important role in the first stages of C cycling in mangrove systems. The chemical composition of Rhizophora mangle, Avicennia germinans, and Laguncularia racemosa leaf, stem, and pneumatophore tissues as well as associated sediments was compared to that of nests of the termite Nasutitermes acajutlae. Nests gave δ13C values of −26.1 to −27.2‰ (±0.1) and C/N of 43.3 (±2.0) to 98.6 (±16.2) which were similar to all stem and pneumatophores but distinct from mangrove leaves or sediments. Organic matter processed by termites yielded lignin phenol concentrations (Λ, lambda) that were 2–4 times higher than stem or pneumatophores and 10–20 times higher than that of leaves or sediments, suggesting that the nests were more resistant to biodegradation than the mangrove vegetation source. 13C NMR revealed that polysaccharide content of mangrove tissues (50–69% C) was higher than that of the nests (46–51% C). Conversely, lignin accounted for 16.2–19.6% C of nest material, a threefold increase relative to living mangrove tissues; a similar increase in aromatic methoxyl content was also observed in the nests. Lipids (aliphatic and paraffinic moieties) were also important but rather variable chemical components of all three mangrove species, representing between 13.5 and 28.3% of the C content. Termite nests contained 3.14 Mg C ha−1 which represents approximately 2% of above ground C storage in mangroves, a value that is likely to increase upon burial due to their refractory chemical composition.