Exit probability in a one-dimensional nonlinear q-voter model

We formulate and investigate the nonlinear $q$-voter model (which as special cases includes the linear voter and the Sznajd model) on a one dimensional lattice. We derive analytical formula for the exit probability and show that it agrees perfectly with Monte Carlo simulations. The puzzle, that we deal with here, may be contained in a simple question: "Why the mean field approach gives the exact formula for the exit probability in the one-dimensional nonlinear $q$-voter model?". To answer this question we test several hypothesis proposed recently for the Sznajd model, including the finite size effects, the influence of the range of interactions and the importance of the initial step of the evolution. On the one hand, our work is part of a trend of the current debate on the form of the exit probability in the one-dimensional Sznajd model but on the other hand, it concerns the much broader problem of nonlinear $q$-voter model

Some new results on one-dimensional outflow dynamics

In this paper we introduce modified version of one-dimensional outflow dynamics (known as a Sznajd model) which simplifies the analytical treatment. We show that simulations results of the original and modified rules are exactly the same for various initial conditions. We obtain the analytical formula for exit probability using Kirkwood approximation and we show that it agrees perfectly with computer simulations in case of random initial conditions. Moreover, we compare our results with earlier analytical calculations obtained from renormalization group and from general sequential probabilistic frame introduced by Galam. Using computer simulations we investigate the time evolution of several correlation functions to show if Kirkwood approximation can be justified. Surprisingly, it occurs that Kirkwood approximation gives correct results even for these initial conditions for which it cannot be easily justified.Comment: 6 pages, 7 figure

Machine learning algorithms for systematic review: reducing workload in a preclinical review of animal studies and reducing human screening error

BACKGROUND: Here, we outline a method of applying existing machine learning (ML) approaches to aid citation screening in an on-going broad and shallow systematic review of preclinical animal studies. The aim is to achieve a high-performing algorithm comparable to human screening that can reduce human resources required for carrying out this step of a systematic review. METHODS: We applied ML approaches to a broad systematic review of animal models of depression at the citation screening stage. We tested two independently developed ML approaches which used different classification models and feature sets. We recorded the performance of the ML approaches on an unseen validation set of papers using sensitivity, specificity and accuracy. We aimed to achieve 95% sensitivity and to maximise specificity. The classification model providing the most accurate predictions was applied to the remaining unseen records in the dataset and will be used in the next stage of the preclinical biomedical sciences systematic review. We used a cross-validation technique to assign ML inclusion likelihood scores to the human screened records, to identify potential errors made during the human screening process (error analysis). RESULTS: ML approaches reached 98.7% sensitivity based on learning from a training set of 5749 records, with an inclusion prevalence of 13.2%. The highest level of specificity reached was 86%. Performance was assessed on an independent validation dataset. Human errors in the training and validation sets were successfully identified using the assigned inclusion likelihood from the ML model to highlight discrepancies. Training the ML algorithm on the corrected dataset improved the specificity of the algorithm without compromising sensitivity. Error analysis correction leads to a 3% improvement in sensitivity and specificity, which increases precision and accuracy of the ML algorithm. CONCLUSIONS: This work has confirmed the performance and application of ML algorithms for screening in systematic reviews of preclinical animal studies. It has highlighted the novel use of ML algorithms to identify human error. This needs to be confirmed in other reviews with different inclusion prevalence levels, but represents a promising approach to integrating human decisions and automation in systematic review methodology

Population genomics of post-glacial western Eurasia.

Western Eurasia witnessed several large-scale human migrations during the Holocene <sup>1-5</sup> . Here, to investigate the cross-continental effects of these migrations, we shotgun-sequenced 317 genomes-mainly from the Mesolithic and Neolithic periods-from across northern and western Eurasia. These were imputed alongside published data to obtain diploid genotypes from more than 1,600 ancient humans. Our analyses revealed a 'great divide' genomic boundary extending from the Black Sea to the Baltic. Mesolithic hunter-gatherers were highly genetically differentiated east and west of this zone, and the effect of the neolithization was equally disparate. Large-scale ancestry shifts occurred in the west as farming was introduced, including near-total replacement of hunter-gatherers in many areas, whereas no substantial ancestry shifts happened east of the zone during the same period. Similarly, relatedness decreased in the west from the Neolithic transition onwards, whereas, east of the Urals, relatedness remained high until around 4,000 BP, consistent with the persistence of localized groups of hunter-gatherers. The boundary dissolved when Yamnaya-related ancestry spread across western Eurasia around 5,000 BP, resulting in a second major turnover that reached most parts of Europe within a 1,000-year span. The genetic origin and fate of the Yamnaya have remained elusive, but we show that hunter-gatherers from the Middle Don region contributed ancestry to them. Yamnaya groups later admixed with individuals associated with the Globular Amphora culture before expanding into Europe. Similar turnovers occurred in western Siberia, where we report new genomic data from a 'Neolithic steppe' cline spanning the Siberian forest steppe to Lake Baikal. These prehistoric migrations had profound and lasting effects on the genetic diversity of Eurasian populations

Impact of Pakoslaw Lateral Reservoir on Groundwater Levels in Adjacent Areas

The paper presents a preliminary study of the surface waters and groundwater levels in the basin of Pakoslaw lateral reservoir. The storage reservoir, built in the year 2007 represents a lateral reservoir placed outside of the water course, but in its direct neighbourhood. The reservoir is filled by the water of Orla river from the water intake localized before the weir, while the water discharge into the river bed takers place through a discharge construction localized below the weir. The results described in this paper contain an excerpt from a long-term study on the depth to a groundwater table in the area adjacent to Pakoslaw reservoir for 2010–2012. A direct influence on the groundwater table in the particular control wells has been exerted by the water levels in the reservoir. Analysis of nearly three years of observationshas indicated that the groundwater table in the zone of potential influence of Pakoslaw reservoir is highly varied. In all control wells, the shallow water table changed in a cyclical way. The observations of the decreasing groundwater tables have shown a direct connection to rainfalls and evapotranspiration. Excessive evapotranspiration during the summer periods with shortages of rainfalls led to soil drying and lowering the groundwater table. Contrary, during the autumn-spring periods, rainfalls exceeded evapotranspiration and resulted in refilling the soil retention storage and rising groundwater levels. The usefulness of the reservoir for anti-flood purposes and its utilization in the periods of water shortage has been confirmed. Water gained during spring thaw replaces water shortage in the spring period. Therefore, the main function of the reservoir and its purpose has fulfilled its expected task. One can state that the table of the groundwater in the zone of Pakoslaw reservoir has been realized in a differentiated way. The average groundwater oscillation amplitude is 1.88 m. The smallest change of groundwater level was observed in the well P-5 and it amounted to 1.70 m, while the highest level was 2.12 m in the P-2 well indicating a high variability of the groundwater level in the particular localities of the reservoir activity. All wells are built on permeable sand layers providing good water filtration conditions. The dynamics of changes in the groundwatrer levels is mainly determined by meteorological conditions and by ait temperature. A higher variability of groundwater has been observed on agriculturally utilized areas, but in the direct neighbourhood of the reservoir

Experimental and CFD Investigation of Ammonia-biodiesel Dual Direct Injection Engine

This research aims to retrofit a compression-ignition engine for the direct injection of ammonia into the engine cylinder with pilot injection of biodiesel. The Lifan engine with a displacement of 418 cc and a maximum power output of 7.2 kW was selected. The engine was modified to direct ammonia injection, involving the installation of a GDI injector for ammonia injection, and common rail injector for biodiesel injection . Additional adaptations included the installation of a common rail system, temperature sensors at specific engine areas, a crankshaft and camshaft position sensor, and the utilization of two ECUs. The ammonia fueling system includes pipes, flowmeters, pressure and temperature sensors, tanks, safety installation, etc. (Fig. 1). The emissions in exhaust gases was measured using a Fourier Transform Infrared Spectroscopy (FTIR) from Gasmet company. The sprays, emissions formation, and combustion characteristics of biodiesel and ammonia have been investigated by CFD models [3]

Application of Multivariate Statistical Methods in Water Quality Assessment of River-reservoirs Systems (on the Example of Jutrosin and Pakosław Reservoirs, Orla Basin)

The paper presents a preliminary study of analysis water quality in the off-channel reservoirs Pakoslaw and Jutrosin using the multivariate statistical techniques. Because of high biogenic pollution in Orla and Radeca rivers, Jutrosin and Pakoslaw reservoirs were based on an innovative concept in which the reservoirs were built on areas directly adjacent to rivers. Series of studies in the off-channel reservoirs were compared with water quality of Orla and Radeca rivers. The Orla together with the water reservoirs forms a right-bank tributary of the Barycz river. The storage reservoirs, built in the year 2007 (Pakoslaw) and 2011 (Jutrosin) represents off-channel reservoirs placed outside of the water course, but in its direct neighborhood. The reservoirs are filled by the water of Orla river from the water intake localized before the weir, while the water discharge into the river bed takers place through a discharge construction localized below the weir. Area of the Pakoslaw water reservoir is 26.6 ha and Jutrosin 90.5 ha. The multivariate statistical techniques such as cluster analysis (CA), factor analysis (FA), principal components analysis (PCA), and discriminant analysis (DA) were taken advantage to interpretation and evaluation data. The aim of the present research was to use chemometric techniques (CA, PCA, FA and DA) in order to: discover similarities and differences in the pchysico-chemical composition of water in off-channel reservoirs and rivers, identify water quality indicators suited to its temporal and spatial variability, expose hidden factors accounting for the structure of the data, and identify man-made sources of water pollution. Cluster analysis (CA) showed that there is unmistakable difference between water quality in the reservoirs and rivers. More evident fluctuation in the physico-chemical composition were observed in reservoirs compared to rivers. This is the result of unique location and theirs maintenance. Factors of water quality during the refilling reservoirs were comparable. Afterwards the off-channel reservoirs and rivers works separately. Factor analysis (FA) confirmed different process of self-purification in reservoirs due to rivers. Typical for pchysico-chemical composition of water are indexes like Conductivity, Fe, Cl, BOD, SO4, Ca, Hardness, Mg, O2 and PO4. This is the result of discriminant analysis (DA)