Miracle-dz/UniFAR-FTUs huggingface dataset:
Noise colour and the risk of population extinctions

A recurrent problem in ecology and conservation biology is to estimate the risk of population extinctions. Extinction probabilities are not only imperative for conservation and management, but may also elucidate basic mechanisms of the regulation of natural populations (Burgman et al. 1993; Pimm 1994). The usual way of modelling stochastic influence on population dynamics has been to assume that the external noise is uncorrelated. This means that each and every randomly drawn noise value is totally independent on previous ones. This is what is generally called ‘white’ noise. However, the noise itself can be temporally autocorrelated. That is, the values of the random numbers used in the noise process will depend on previous ones. Here we show that the autocorrelation, or colour, of the external noise assumed to influence population dynamics strongly modifies estimated extinction probabilities. For positively autocorrelated (‘red’) noise, the risk of extinction clearly decreases the stronger the autocorrelation is, Negatively autocorrelated (‘blue’) noise is more ambiguously related to extinction probability. Thus, the commonly assumed white noise in population modelling will severely bias population extinction risk estimates. Moreover, the extinction probability estimates are also significantly dependent on model structure which calls for a cautious use of traditional discrete-time models.
A method for the preparation and quantification of microscopic charcoal from terrestrial and lacustrine sediment cores

Existing methods of microscopic charcoal analysis are briefly reviewed. A simple but effective alter-native method for preparing and quantifying fossil microscopic charcoal in sediment samples from terrestrial and lacustrine cores is outlined. Weak hydrogen peroxide (6%f/o H202) is used to partially digest and bleach organic material in sediment samples. Charcoal particles are not bleached by the hydrogen peroxide and are thus easily identified when counted under a binocular dissecting microscope. The sample preparation procedure is extremely gentle on charcoal particles, much more so than the majority of existing methods, ensuring that little particle fragmentation occurs during preparation.
A Validation Assessment of the Hazards of Place Model of Vulnerability for Northeastern North Carolina

As societal development continues to increase in floodplains it is important to quantify the vulnerabilities associated with flooding. Using northeastern North Carolina as the study area this thesis estimates the hazards of place model of vulnerability for sixteen counties in Northeastern North Carolina. The hazards of place model of vulnerability is developed from the combination of two quantitative indicators: the Geophysical Risk Index (GPRI) which incorporates two types of geophysical risk factors (percent of block group within the floodplain and the percent of human development within the floodplain); the Social Vulnerability for Evacuation Assistance Index (SVEAI) which examines four evacuation dimensions of U.S. census data (population and building structures differential access to resources special evacuation needs and a combination of every dimension). Using the hazards of place model of vulnerability this thesis prioritizes low medium and high risk block groups into a matrix classification. The results from the matrix classification are validated by a sub-block group analysis of parcel data and an interview with one emergency official. Results reveal that the inclusion of human development land cover data and the combination of census data are important factors for estimating the hazards of place model of vulnerability. However the interview suggests that there are a few geophysical and social systems that could not be identified by quantitative indicators. Overall the matrix classification of the hazards of place model of vulnerability was successful at prioritizing levels of risk in the study area.
Linking pan-Arctic human and physical data

The Arctic Observing Network–Social Indicators (AON-SI) project, building upon earlier work, developed an approach for linking social with physical science data across the Northern pan-Arctic. The first iteration of social data involves time series of demographic indicators in more than 100 separate regions, such as boroughs of Alaska, census divisions of Northern Canada, and oblast or autonomous regions of Northern Russia. Its geographical scope covers all of Alaska, Greenland, Iceland, the Faroe Islands, Norway, Sweden, and Finland, along with Northern parts of Canada and Russia. Administrative subdivisions within these areas define the regions. Key features of this data framework are (1) the list of region names, (2) a unified system of numerical identification codes, and (3) a region-year organization. We approximated the geographical area of each region as a particular set of 25 × 25 km grid cells, following the Equal-Area Scalable Earth Grid (EASE-Grid) scheme widely used in high-latitude natural science. Physical data in this format are accessible through the Arctic RIMS website. The linkage opens doors for integrated analysis of social and natural-science data, as illustrated by an analysis of Alaska community electricity use. Current versions of the database are published online.
A simple rainfall–runoff model based on hydrological units applied to the Teba catchment (south‐east Spain)

A hydrological model (YWB, yearly water balance) has been developed to model the daily rainfall–runoff relationship of the 202 km2 Teba river catchment, located in semi‐arid south‐eastern Spain. The period of available data (1976–1993) includes some very rainy years with intensive storms (responsible for flooding parts of the town of Malaga) and also some very dry years.
Infrastructure and the ethnographic-cartographic production of urban bird species richness

The qualitative bio-geographies of human geographers and the quantitative mappings of biogeographers share a goal: how to understand living with non-human life. Yet they rarely bridge the conceptual and methodological gap between them. This article theorizes how the concept of infrastructure can bridge this ethnographic-cartographic divide. Infrastructure is not just inert shell. It is also a system of relation, a dynamic patterning of socionatural form emerging out of experiences and affective moments of its constituents. As proof of concept, we quantified and compared urban bird species richness and frequency for Tallahassee, Florida over a 17-year period (2000–2017) for two co-occurring observational infrastructures, eBird and a wildlife rehabilitation center that serves the city. Species common to both infrastructures comprised 94% of all eBird observations and 99% of all rehab records. Their differences reflected contrasts in how the motivations for experiencing birds intersected with bird habitat preferences, behavior, and contingencies of urban history and development. eBird observations had a higher species richness (295 spp) and reflected the growing popularity among birds and a small number of active birders for visiting stormwater retention lakes recently modified to improve bird habitat. Rehabilitation records had a lower richness (194 spp) and exhibited a much more even distribution of bird encounters among individual residents as well as community institutions like schools, universities, law enforcement, and other government organizations. Infrastructural perspectives convey how affective and individualistic encounters with the non-human can link to emergent biogeographic mappings and how urban biodiversity is relationally and heterogeneously produced rather than simply contained in cities.
A Multi-Agent System Approach for Emergency Services using QoS-Assured Cloud Computing Architecture in the Metropolitan Transportation System

: The paradigm of multi-agent systems has been actively applied to cloud computing to provide cost-e ff ective, decentralized problem-solving. Rather than processing the tasks that require enormous computing resources locally, they can be processed in the cloud. In this research, we present how these two paradigms can be e ff ectively used to handle emergency services in any metropolitan transportation system. In the proposed architecture, agents are placed at signal nodes to collect data and send it to cloud services. These agents have the ability to control the signal nodes in an emergency. They also communicate emergency information between several nodes. The cloud service is the system’s backbone and employs heterogeneous agents to manage emergency services. It analyses the input data and determines the presence of emergency services. The main contribution of the research is to utilize a priority-based mechanism for handling exigency vehicles rather than using traditional timer-based signals. In addition, we provided case studies demonstrating the usefulness of the proposed framework.
Characterization of Fruit Vinegars via Bioactive and Organic Acid Profile Using Chemometrics

Vinegar has been known as a traditional remedy since ancient times. In addition to being used as a flavoring and aroma enhancer in world cuisines, it has attracted more and more attention due to its bioactive potential and health properties. Although the most common use is apple cider vinegar together with grape vinegar, vinegar produced from red fruits has come to the fore due to their health purposes. Rosehip, pomegranate, fig, guelder-rose, blackberry, raspberry, and blueberry vinegars were evaluated regarding the organic acid content, phenolic compound content, and bioactive potential to assess their health potential and associated contents. Acetic acid, citric acid, succinic acid, and malic acid were determined as prominent organic acids in the vinegar samples. In contrast, gallic acid, vanillic acid, protocatechuic acid, and ferulic acid were dominant regarding phenolic compounds. Raspberry, guelder-rose, and pomegranate vinegars came forth regarding their bioactive content and potential. The discriminative parameters of the vinegar samples were pH, total acidity, dL-isocitric acid, gallic acid, and hydroxybenzoic acid. Fruit vinegars were determined to have a notable bioactive content compared to apple and grape vinegars. The use of these vulnerable bioactive materials in vinegar fermentation could provide an effective way for nutrition and raw material resourcing.
Influences of mean advection and simple behavior on the distribution of cod and haddock early life stages on Georges Bank

Results of a modeling study designed to explore the influences of physical advection and certain biological mechanisms on the distribution of cod (Gadus morhua) and haddock (Melanogrammus aegkfinus) early life stages on Georges Bank are described. Using a latewintedearly-spring 3-D circulation field driven by the Mz tidal current, mean wind stress and Scotian Shelf inflow, we examine the distribution of cod and haddock larvae spawned on the Northeast Peak of the Bank. The sensitivity to a March-April baroclinic field is also explored. Results indicate that larvae remaining in the surface Ekman layer are generally advected off-bank. However, downwelling associated with Ekman layer convergence near the shelf break provides a mechanism for larvae to exit from the off-bank surface drift. Larvae below the surface layer are transported south-westward along the southern flank of Georges Bank and are retained on the Bank if their position immediately upstream of the Great South Channel is shoalward of (roughly) the 70 m isobath. Within the Great South Channel region and between the 50 and 70 m isobaths,
Groundwater–soil water–vegetation dynamics in a temperate forest ecosystem along a slope

Groundwater can have a profound effect on water availability to vegetation in temperate climate regions. Here we attempt to model groundwater, soil water, and vegetation dynamics in groundwater controlled ecosystems and to assess how these depend on climate and topography. We focus on the possible location of a boundary between two vegetation types on a slope. One vegetation type is adapted to wetter soil moisture conditions, and one is adapted to drier conditions. We hypothesized that the vegetation type boundary along the slope in climax state is located where the slope‐average evapotranspiration is highest and/or where vegetation stress is minimal. Vegetation stress is a combination of occurring water stress as defined by Porporato et al. (2001) and a newly defined oxygen stress, which results from anaerobic conditions. To study this system, we built a two‐dimensional model of saturated‐unsaturated flow along a slope in which the abundance of two vegetation types varied along the slope. The results show that boundary between the vegetation types based on maximum evapotranspiration occurs at approximately the same location as that is predicted based on minimum plant stress. When precipitation increases, the boundary between the two vegetation types moves up slope. Sensitivity of the location of the vegetation boundary to changes in precipitation decreases with increasing slope angle.
IoT and Edge Computing Using Virtualized Low-Resource Integer Machine Learning with Support for CNN, ANN, and Decision Trees

Data-driven models used for predictive classification and regression tasks are commonly computed using floating point arithmetic preserving accuracy by automatic scaling even in high non-linear functions. With respect to distributed sensor networks like the IoT, sensor data is acquired on low-resource embedded systems and delivered to data servers characterized by big data volumes. In specific use cases and domains, local predictive modelling on low-power devices is desired or required. But heterogeneity of host platforms and dynamic programming disables machine code deployment. This work addresses Tiny ML on very low-resource devices (microcontrollers, less than 32 kB RAM and ROM) by using a stack-based Tiny Virtual Machine providing core ML operations to implement Decision Trees (DT), Artificial Neural Networks (ANN), and Convolutional Neural Networks (CNN). VM program code is always provided in textual format and compiled just-in-time to Bytecode to ensure portability, servicability, and mobility. Two damage diagnostics use-cases demonstrate the suitability of the VM approach, and even time consuming computational tasks do not compromise the overall responsiveness of the platform by using a real-time approach. This work addresses the underlying integer arithmetic operations required to implement efficient and fast computable ML models on microncontrollers.
Exploring the Multifaceted Nexus of Uric Acid and Health: A Review of Recent Studies on Diverse Diseases

The prevalence of patients with hyperuricemia or gout is increasing worldwide. Hyperuricemia and gout are primarily attributed to genetic factors, along with lifestyle factors like consuming a purine-rich diet, alcohol and/or fructose intake, and physical activity. While numerous studies have reported various comorbidities linked to hyperuricemia or gout, the range of these associations is extensive. This review article focuses on the relationship between uric acid and thirteen specific domains: transporters, genetic factors, diet, lifestyle, gout, diabetes mellitus, metabolic syndrome, atherosclerosis, hypertension, kidney diseases, cardiovascular diseases, neurological diseases, and malignancies. The present article provides a comprehensive review of recent developments in these areas, compiled by experts from the Young Committee of the Japanese Society of Gout and Uric and Nucleic Acids. The consolidated summary serves to enhance the global comprehension of uric acid-related matters.
Divergent 1,2-carboallylation of terminal alkynes enabled by metallaphotoredox catalysis with switchable triplet energy transfer

We report a metallaphotoredox strategy for stereodivergent three-component carboallylation of terminal alkynes with allylic carbonates and alkyl trifluoroborates. This redox-neutral dual catalytic protocol utilizes commercially available organic photocatalyst 4CzIPN and nickel catalysts to trigger a radical addition/alkenyl–allyl coupling sequence, enabling straightforward access to functionalized 1,4-dienes in a highly chemo-, regio-selective, and stereodivergent fashion. This reaction features a broad substrate generality and a tunable triplet energy transfer control with pyrene as a simple triplet energy modulator, offering a facile synthesis of complex trans- and cis-selective skipped dienes with the same set of readily available substrates.
Critical Review on Torque Ripple Sources and Mitigation Control Strategies of BLDC Motors in Electric Vehicle Applications

In recent years, electric vehicles (EVs) have attracted a lot of attention and are rapidly growing trends today due to their ability to compete with and overtake fossil fuel-powered vehicles among all electrified transportation tools. The primary focus of EV evolution is on improving the driving range and optimizing energy consumption, both of which are essential demands achieved through improved and developing motor performance. The brushless direct current (BLDC) motor is one of the most superior choices for dynamic applications in EVs, providing the highest power density and capability of any motor. BLDCs are gaining popularity in EVs not only for their high performance in speed and position controls but also for meeting the requirements of smooth torque maintenance with torque ripple mitigation. This paper provides an overview of various advanced control strategies, such as field-oriented control (FOC), direct torque control (DTC), intelligent control (IC), controlling input voltage (CIV), current shaping techniques (CST), model predictive control (MPC), and sliding mode control (SMC). These strategies are used to regulate the torque ripples produced in BLDC motors, aiming to achieve energy-efficient EV performance for various applications. Additionally, it describes a cloud-based control system coupled with electric motor drives to address challenges in predicting current vehicle conditions for improved power distribution between the motor and battery systems. Furthermore, recent concerns and difficulties in advancing torque ripple mitigation control strategies are highlighted, with comparisons and discussions for future EV research. Finally, an evaluative study on BLDC motor drive in EVs with different control strategies reveals its significance and potential outcomes.
The TMEM106B T186S coding variant increases neurite arborization and synaptic density in primary hippocampal neurons

The lysosomal protein TMEM106B was identified as a risk modifier of multiple dementias including frontotemporal dementia and Alzheimer’s disease. The gene comes in two major haplotypes, one associated with disease risk, and by comparison, the other with resilience. Only one coding polymorphism distinguishes the two alleles, a threonine-to-serine substitution at residue 185 (186 in mouse), that is inherited in disequilibrium with multiple non-coding variants. Transcriptional studies suggest synaptic, neuronal, and cognitive preservation in human subjects with the protective haplotype, while murine in vitro studies reveal dramatic effects of TMEM106B deletion on neuronal development. Despite this foundation, the field has not yet resolved whether coding variant is biologically meaningful, and if so, whether it has any specific effect on neuronal phenotypes. Here we studied how loss of TMEM106B or expression of the lone coding variant in isolation affected transcriptional signatures in the mature brain and neuronal structure during development in primary neurons. Homozygous expression of the TMEM106B T186S variant in knock-in mice increased cortical expression of genes associated with excitatory synaptic function and axon outgrowth, and promoted neurite branching, dendritic spine density, and synaptic density in primary hippocampal neurons. In contrast, constitutive TMEM106B deletion affected transcriptional signatures of myelination without altering neuronal development in vitro. Our findings show that the T186S variant is functionally relevant and may contribute to disease resilience during neurodevelopment.
Rainfall Variability In Ghana During 1961- 2005

This study uses daily rainfall data for 40-45 years to investigate the extent and nature of vari-ability in the onset, cessation, annual rainfall and length of the rainy season (LRS) over four stations in Ghana (Tamale, Kumasi, Axim and Accra). The study shows that generally, the early onset and late cessation dates that occurred in the 1960s and early 70s and which resulted in long rainy seasons almost everywhere in Ghana have now changed significantly, the onset oc-curring rather late with early cessation since the 1980s. However, cessation for Accra was late from the 90s resulting in slightly longer rainy season. Pentade series of annual rainfall and rainy days also show a significant downward trend at all the stations but particularly more so at Axim. All these have serious consequences for agricultural practices and water resources man-agement, particularly for hydropower generation in the country. Classification of the annual rainfall into wet and dry years and consideration of moisture availability shows significant dif-ferences between years of abundant and deficient rainfall. It was found that wet (dry) years have early (late) onset and late (early) cessation resulting in longer (shorter) rainy season. Also, rain-fall amount and length of the rainy season during dry years are reduced by about 50% and more than 30 days, respectively at all stations. In general, main rainfall begins about 2-months after the moisture influx has attained a maximum value over all stations. The study also shows that dry spells of 10 or more days between rain events occur more frequently in the southern parts of Ghana than the north.
The role of improving tax relation for the growth of agricultural production

Considering taxes to be the universally recognized regulator of the economy, related ideas on the proper organization of tax relations are being promoted in various scientific papers. The relevance of this problem is caused, firstly, by the choice of a model of tax regulation within the framework of the general economic situation, by thoughts that are about “tax relations”, “principles of taxation”, “mechanism taxation”, “about the nature of the tax”, and secondly the within the framework of the tax system operating in the Republic of Uzbekistan, the instruments of tax relations are characterized by high economic inefficiency. The purpose of this research is to generalize the works on tax relations, improve tax regulation, develop the necessary proposals and recommendations to enhance the role of tax regulation mechanisms in the framework of improving tax policy that aimed at ensuring high economic growth. The paper also analyzes theories of tax regulation in the framework of using tax regulation mechanisms in order to ensure the growth of income (profit) of economic entities with a simultaneous decrease in the share of tax revenues in GDP. By defining the economic boundaries of tax policy, it is possible to solve not only the problems of economic growth of the country as whole, but also social issues in changing economic conditions. The paper also analyzes the opinions of various domestic and foreign economists on tax relations.