Miracle-dz/UniFAR-FTUs huggingface dataset:
Solar photovoltaics in Brazil: adressing the chasm preventing the deployment of its DG generation.

Supply problems are aggravated by the constant demand increase. There is a growth trend of the electric intensity of residential and commercial sectors. According to the Energy Research Company (EPE), this year consumption grew by 4.9% in January and 8.6 % in February compared to the consumption in the same months of 2013. A closer look at the residential and commercial sectors shows that in February 2014 consumption grew of 13.3 % and 16.6 %, respectively, the largest expansion in the past decade ( Brasil Energia, 24.04.2014). That growth has caused the displacement of peak consumption hours from 18:00-20:00 to 14:00-16:00, time of intense heat when the air conditioners are working at full power. This new period of peak consumption happily coincides with the peak sun power generation. Therefore, policymakers need to pay special attention to those sectors of consumption taking advantage of opportunities like those.
Automatic Extraction of Semantic Valences of Verbs from Explanatory Dictionaries

In this work we propose the application of symbolic methods for extraction of semantic valences of the verbs describing them under the Government Pattern concept of the Meaning ⇔ Text Theory. The method is based on the automatic processing of the definitions of verbs used in Explanatory Dictionaries and the analysis of semantic relationships, as inclusion and synonymy, given among them. We believe that lexicographic definitions of Explanatory Dictionaries supply enough information for identifying verb actants. The obtained results show that even when it is not possible to find information related to the argument structure of verbs in the definitions, it is possible to deduce it identifying and analyzing other definitions which semantic relationships are established.
Acid-Modified Biochar Impacts on Soil Properties and Biochemical Characteristics of Crops Grown in Saline-Sodic Soils

Soil salinity and sodicity is a potential soil risk and a major reason for reduced soil productivity in many areas of the world. This study was conducted to investigate the effect of different biochar raw materials and the effects of acid-modified biochar on alleviating abiotic stresses from saline-sodic soil and its effect on biochemical properties of maize and wheat productivity. A field experiment was conducted as a randomized complete block design during the seasons of 2019/2020, with five treatments and three replicates: untreated soil (CK), rice straw biochar (RSB), cotton stalk biochar (CSB), rice straw-modified biochar (RSMB), and cotton stalk-modified biochar (CSMB). FTIR and X-ray diffraction patterns indicated that acid modification of biochar has potential effects for improving its properties via porous functions, surface functional groups and mineral compositions. The CSMB treatment enhanced the soil’s physical and chemical properties and porosity via EC, ESP, CEC, SOC and BD by 28.79%, 20.95%, 11.49%, 9.09%, 11.51% and 12.68% in the upper 0–20 cm, respectively, compared to the initial properties after the second season. Soil-available N, P and K increased with modified biochar treatments compared to original biochar types. Data showed increases in grain/straw yield with CSMB amendments by 34.15% and 29.82% for maize and 25.11% and 15.03% for wheat plants, respectively, compared to the control. Total N, P and K contents in both maize and wheat plants increased significantly with biochar application. CSMB recorded the highest accumulations of proline contents and SOD, POD and CAT antioxidant enzyme activity. These results suggest that the acid-modified biochar can be considered an eco-friendly, cheaper and effective choice in alleviating abiotic stresses from saline-sodic soil and positively effects maize and wheat productivity.
Biomimetic textiles: An innovative approach towards conserving the future

Superhydrophobicity, self-repair, self-cleaning, energy conservation, dry adhesion, adaptive development, drag reduction, and other natural phenomena have evolved over billions of years to produce more efficient textile solutions than equivalent man-made solutions. Few innovative biomimetic technologies viz., functional surfaces, structural colours, fibre structures, self-healing, thermal insulation, and other characteristics that can be used for prospective textile goods. Biomimetic research is a fast-growing discipline, and exploiting the issue's full potential in the manufacture of unique and sustainable textiles requires a multidisciplinary approach based on a comprehensive knowledge of nature. Biomimicry has the potential to enhance man-made materials and pave the way for the next generation of technological, high-performance materials, including novel materials and characteristics, creative structures and designs, and product and process sustainability. In this study, the potential of a bio-inspired textile structure is explored to the best extent conceivable. The potential use of different biomimetic fabrics was also considered. In essence, this technique can serve as a source of motivation for further material advancement.
Utility of the Addenbrooke’s Cognitive Examination III online calculator to differentiate the primary progressive aphasia variants

Abstract The Addenbrooke’s Cognitive Examination III is a brief cognitive screening tool that is widely used for the detection and monitoring of dementia. Recent findings suggest that the three variants of primary progressive aphasia can be distinguished based on their distinct profiles on the five subdomain scores of this test. Here, we investigated the utility of the Addenbrooke’s Cognitive Examination III to differentiate the primary progressive aphasia variants based on their item-by-item performance profiles on this test. From these results, we created an interactive primary progressive aphasia Addenbrooke’s Cognitive Examination III calculator which predicts the variant based on a patient’s unique item-by-item profile. Twenty-eight logopenic variant, 25 non-fluent variant and 37 semantic variant primary progressive aphasia patients and 104 healthy controls completed the Addenbrooke’s Cognitive Examination III at first clinical presentation. Multinomial regression analyses were conducted to establish performance profiles among groups, and R Shiny from RStudio was used to create the interactive Addenbrooke’s Cognitive Examination III diagnostic calculator. To verify its accuracy, probability values of the regression model were derived based on a 5-fold cross-validation of cases. The calculator’s accuracy was then verified in an independent sample of 17 logopenic, 19 non-fluent and 13 semantic variant primary progressive aphasia patients and 68 Alzheimer’s disease patients who had completed the Addenbrooke’s Cognitive Examination III (or an older version of this test: Revised) and had in vivo amyloid-PET imaging and/or brain autopsy pathological confirmation. Cross-validation of cases in the calculator model revealed different rates of sensitivity in classifying variants: semantic = 100%, non-fluent = 80.6% and logopenic = 79.9%; healthy controls were distinguished from primary progressive aphasia patients with 100% sensitivity. Verification of in vivo amyloid and/or autopsy-confirmed patients showed that the calculator correctly classified 10/13 (77%) semantic variant, 3/19 (16%) non-fluent variant and 4/17 (24%) logopenic variant patients. Importantly, for patients who were not classified, diagnostic probability values mostly pointed toward the correct clinical diagnosis. Furthermore, misclassified diagnoses of the primary progressive aphasia cohort were rare (1/49; 2%). Although 22 of the 68 Alzheimer’s disease patients (32%) were misclassified with primary progressive aphasia, 19/22 were misclassified with the logopenic variant (i.e. falling within the same neuropathological entity). The Addenbrooke’s Cognitive Examination III primary progressive aphasia diagnostic calculator demonstrates sound accuracy in differentiating the variants based on an item-by-item Addenbrooke’s Cognitive Examination III profile. This calculator represents a new frontier in using data-driven approaches to differentiate the primary progressive aphasia variants.
Personality and limitations in instrumental activities of daily living in old age: Reciprocal associations across 12 years

Personality traits have been reported to predict difficulties in performing instrumental activities of daily living (IADL) in old age, such as preparing meals or shopping. However, little is known about the reciprocal effects on personality. In this study, we examined bidirectional relationships between personality traits and the capacity to perform IADL using four waves of longitudinal data from 3540 older adults (aged 65 years and older) from the Health and Retirement Study. We applied a random-intercept cross-lagged panel model to separate between- and within-person effects across time and compared it to a traditional cross-lagged panel model. At the between-person level, higher neuroticism and lower conscientiousness were associated with more IADL limitations. Within individuals across time, increases in neuroticism and decreases in conscientiousness and extraversion were associated with increases in IADL limitations 4 years later. In contrast, increases in IADL limitations only predicted increases in neuroticism and decreases in extraversion. These results indicate that some personality traits affect and are affected by limitations in functional capacities in old age. Results of the within-person model build a strong foundation for future personality interventions as a pathway to maintain high functioning in old age.
Intrinsic Capacity Declines with Elevated Homocysteine in Community-Dwelling Chinese Older Adults

Purpose Intrinsic capacity (IC) reflects the overall health status of older adults and has great public health significance. But few studies described the related biomarkers for IC. The aim of this study was to investigate the association between homocysteine (Hcy) and IC in older adults. Participants and Methods This cross-sectional study included 1927 community-dwelling Chinese older adults aged 60–98 years from May 2020 to December 2020. Data were collected through interviews, physical examinations, and laboratory tests. IC involved five domains of cognition, locomotion, sensory, vitality, and psychology evaluated by the Mini-cog scale, 4-m walk test, self-reported visual and hearing conditions, MNA-SF scale, and GDS-4 scale, respectively. The score of each domain dichotomized as 0 (normal) and 1 (impaired) was added together to an IC total score. Low IC was defined as a score of 3–5, and high IC as 0–2. Hcy was measured by a two-reagent enzymatic assay. A restricted cubic spline regression model was used to explore the non-linear relationship between Hcy and low IC. Results Hcy was higher in the low IC group than in the high IC group. Restricted cubic spline analysis revealed a J-shaped nonlinear association between Hcy and low IC. The risk of IC decline was slowly decreased until 8.53 µmol/L of Hcy (OR=0.753, 95% CI=0.520–1.091, P=0.132), and increased with elevations of per 5 µmol/L Hcy afterwards (OR=1.176, 95% CI=1.059–1.327, P=0.005). Among the five domains of IC, Hcy had ORs of 1.116 (1.009–1.247) for cognition impairment, 1.167 (1.055–1.305) for vitality, and 1.160 (1.034–1.303) for psychology per 5 µmol/L increase in Hcy above the change point. Additional sensitivity analysis also demonstrated the nonlinear association between Hcy and low IC. Conclusion Hcy had a J-shaped association with low IC. Higher Hcy (Hcy ≥8.53µmol/L) might provide clinical implications for early identifying the risk of low IC.
Interactions among wildfire, forest type and landscape position are key determinants of boreal forest carbon stocks

Boreal forest soils contain large stocks of soil carbon (C) that may be sensitive to changes in climate and disturbance. Destablization of boreal forest soil C through changes in C inputs, belowground C pools and/or wildfire could feedback to accelerate rising atmospheric CO2 concentration. Additionally, increasing frequency of severe fires may be changing the dominant forest types and reshaping aboveground C stocks. Although controls on ecosystem C pools have received considerable attention, many studies have been limited to locations near the road system, leading to uncertainty in current and future C stocks across boreal Alaska. Here, we leveraged 545 randomly selected and spatially balanced Forest Inventory and Analysis (FIA) plots across ~13.5 million hectares in interior Alaska to examine the factors governing soil and live tree C pools. Forest type mediated the effects of mean summer air temperature and the probability of near‐surface permafrost on soil C. Meanwhile, forest type, stand age and aspect were the primary drivers of live tree C. Overall, plots with a known history of wildfire during the past 70 years did not have significantly different soil C stocks than plots without a known history of fire, likely due to the historical predominance of low severity fires. Where wildfire likely initiated a transition to deciduous trees (19% of plots), live tree and soil C pools were reduced by 16% and 20%, respectively. Ecosystem C likely recovered over time, as maturing deciduous stands rapidly gained C in live trees. Deciduous stands without a known fire had comparatively very large live tree C stocks, suggesting a significant change in the distribution of ecosystem C following severe fire. Synthesis. Our results highlight the nuanced interactions among wildfire, landscape position and forest type that will play important roles in shaping future boreal ecosystem C stocks.
Pyramid Indoor Localization System Using Dual-Band Wi-Fi Sensors

Fingerprinting map technology brings tremendous advancements in indoor localization, especially for unconstrained position perception, as it provides a convenient and low-cost way in applicability of mobile phone and smart device. However, since traditional way only includes one fingerprinting database from sensors, the localization task is difficult to balance positioning accuracy and efficiency. Especially when users have prior knowledge, the localization accuracy requirements are generally consistent, and excessive pursuit of accuracy leads to low efficiency. In order to solve this problem, Fingerprinting Pyramid Map (FPM) structure is proposed in this paper, where users can freely choose between localization range and time. Not only that, the signal strength difference measurement between 2.4GHz and 5GHz from two access-point sensors is used as fingerprint data to resolve the issue of device heterogeneity in FPM. Extensive experimental analysis in a university library environment, further confirm that the proposed method accommodates localization efficiency and device heterogeneity, and outperforms other existing methods.
Assessment of Information Extraction Techniques, Models and Systems

The present article aims to review and evaluate the practiced and classical techniques, tools, models, and systems concerning automatic information extraction (IE) from published scientific documents like research articles, patents, theses, technical reports, and case studies etc. IE is performed for various reasons such as better indexing, archiving, searching, and retrieving. That is mainly used by the search engines and the indexing services as well the digital libraries and semantic web. In this regard, several studies have been conducted targeting various nature of documents. The study pays special consideration to the successful IE models, algorithms and approaches applied to structural IE from published documents. To grasp this, the paper is classified into several segments and each segment covers a significant aspect of IE. Furthermore, to validate their benefits and drawbacks, a comparative study of all the approaches have been conducted in terms of various performance factors like precision, accuracy, recall and F-score. Potential areas of improvement have been emphasized as research gap for the scholars in the closely related areas. Ultimately, a comprehensive summary of the evaluation is presented in tabular form and review is concluded. It was observed that the hybrid methods outperform the other methods due to their versatile nature to address various document formats.
Modeling of electrostimulation characteristics to determine the optimal amplitude of current stimuli

The subject of research- the process of human skeletal muscles electrical stimulation during medical therapy. The subject of the study is a mathematical model of electrostimulation characteristics, which links the amplitude of muscle contraction and the stimulating effect amplitude. The current work develops a mathematical model in the form of an analytical expression to describe the muscle contraction amplitude dependence on electrical stimulus amplitude. Tasks to be solved: to analyze the dependence peculiarity of muscle contraction amplitude in stimulating impulse amplitude; conduct structural and parametric identification of the model; compare the results obtained using practical data, evaluate the model accuracy; use the obtained model for analytical description with the aim of a priori determination of the optimal stimulus amplitude. Methods used mathematical modeling method, methods of structural and parametric identification of models, approximation methods, parametric optimization methods, mathematical analysis methods. Results obtained an analytical model in the form of a 5th degree polynomial is proposed, which reflects the dependence of muscle contraction amplitude in the stimulus amplitude; the degree of the polynomial is selected and the coefficients of the model are obtained using parametric optimization; a model trajectory was built and the accuracy of modeling was estimated; an equation was obtained and its possible solutions were found to determine the optimal value of the stimulus amplitude; the practical application of the research results was substantiated. The results obtained can be used in the selection of individual effects of electrical stimulation during one session, as well as with extrapolation during the entire rehabilitation process. Scientific novelty: an analytical description showing the dependence of skeletal muscle contraction amplitude on the electrical stimulus amplitude was obtained, which allows determining individual optimal parameters of electromyostimulation.
The Effect of Hatching System and Egg Weight on Production Traits in Turkish Geese: Growth Performance, Slaughter and Meat Quality Traits

This study was aimed to determine the effect of hatching system (house and machine) and egg weight (heavy and light) on growth performance and meat quality traits in geese. The study was carried out for 12 weeks with a total of 220 Turkish native geese. The geese were individually weighed every 2 weeks during the study, on these same weeks feed conversion ratio (FCR) was measured. Hot and cold dressed, blood, head, foot, edible internal organs (heart, liver, gizzard), abdominal fat, neck, back, breast, thigh and wing percentages were determined. Also cooking loss, drip loss, color and pH were determined as meat quality traits. There was no significant difference between the egg weight groups in terms of BW. However, the geese produced in the house hatching system showed more BW from 6 to 12 weeks of age onwards compared to the machine system. There was no significant difference between the groups in terms of FCR by 8 weeks. Both 10 and 12 weeks FCR were determined as the worst house heavy, while the best house light groups. Hot and cold carcass percentages in geese hatched from heavy were higher rates than light eggs. The percentage of wings differed significantly among geese produced from different egg weight groups. Breast meat cooking loss was found higher rates in heavy eggs than light eggs, while thigh meat cooking loss was found higher rates in the house than machine system. The results of this study show that geese hatched in the house system had more BW at the slaughter age compared to machine system geese. In addition, geese produced from heavy eggs showed a higher hot and cold dressed percentages than geese produced from light eggs.
Differential Evolution Based Solar Photovoltaic Array Reconfiguration Algorithm for Optimal Energy Extraction during Partial Shading Condition

To increase energy yield from an installed photovoltaic (PV) array, particularly during partial shading condition (PSC), a new technique based on reconfigurable PV array interconnection is proposed in this work. The proposed technique works by dynamically changing the interconnection of PV modules to form a new configuration using a switching matrix inside the array. The criteria of good reconfigurable PV array interconnection techniques depend on the efficiency and accuracy of the control algorithm to optimally reconfigure the PV array to maximize the total output power. Hence, this paper proposes a new control algorithm using differential evolution (DE) for photovoltaic array reconfiguration (PVAR). To verify the superiority of the proposed algorithm, DE is compared with the particle swarm optimization (PSO) algorithm. Results confirm that DE performs well in terms of the amount of energy production during PSC. For all the nine shading patterns tested on a 3 × 3 PV array, DE yields 1% to 5% more power than PSO.
Small RNAs in Cnidaria: A review

As fundamental components of RNA silencing, small RNA (sRNA) molecules ranging from 20 to 32 nucleotides in length have been found as potent regulators of gene expression and genome stability in many biological processes of eukaryotes. Three major small RNAs are active in animals, including the microRNA (miRNA), short interfering RNA (siRNA), and PIWI‐interacting RNA (piRNA). Cnidarians, the sister group to bilaterians, are at a critical phylogenetic node to better model eukaryotic small RNA pathway evolution. To date, most of our understanding of sRNA regulation and its potential contribution to evolution has been limited to a few triploblastic bilaterian and plant models. The diploblastic nonbilaterians, including the cnidarians, are understudied in this regard. Therefore, this review will present the current‐known small RNA information in cnidarians to enhance our understanding of the development of the small RNA pathways in early branch animals.
Neuro-fuzzy system for solving fuzzy singular perturbation problems

Abstract In this paper we have introduced a new method, by using fully fuzzy neural network (FFNN) to find the numerical solution for solving fuzzy singular perturbation problems (FSPPS) for ordinary differential equations. It uses the Levenberg-Marquardt training machine algorithm (TrianLM) for calculating the Fuzzy neural network parameters and the sigmoid function of the hidden units is hyperbolic tangent activation function, that is: . The fuzzy trial solution of FSPPs is written as a sum of two parts. The first part satisfies the fuzzy conditions, it contains no fuzzy adjustable parameters. The second part involves a feed-forward fuzzy neural network containing fuzzy adjustable parameters. In comparison with existing numerical methods, shows upp that the use of fuzzy neural networks provides solutions with good generalization and high accuracy. The proposed method is illustrated by several examples.