Irregular Regime Research Articles

Creation of Annual Order Forecast for the Production of Beverage Cans—The Case Study

This article is focused on the creation of a system for forecasting of future orders for a specific beverage cans manufacturer. The problem comes from the irregular ordering of cans from different customers; not only national companies, but also from companies abroad. This causes fluctuations in production and consequently an irregular transport regime. That is why the beverage can producer demanded a forecasting system that would help to create an annual production plan. The aim is to analyze the ordering process for the last two years and on that basis to create a forecast system of the possible ordering process for the following year. This is necessary for the introduction of regularity of production, because the frequent transitions of the line to another assortment range or other surface printing requires long downtimes due to the technological setting, thus creating large losses due to inactivity of the production line. As drinking habits of final customers reflect the sale of cans, it was expected that sale data would have a seasonable character; this was proved after a brief analysis of the former data. After that, the appropriate forecasting methods were chosen. The methodology was created to combine multiple forecast results into one to increase the forecast objectivity. Forecasting is performed at three different levels: forecasting of assortment, forecasting of region sale and total forecasting of all orders. In spite of the change in market behavior in 2020, due to the pandemic situation in the first wave of the COVID-19 crisis, the sale of beverage cans is expected to stabilize and return to pre-crisis level as early as 2021. Then the forecasting system will fully meet the company’s requirements.

Online Learning and Memory of Neural Trajectory Replays for Prefrontal Persistent and Dynamic Representations in the Irregular Asynchronous State.

In the prefrontal cortex (PFC), higher-order cognitive functions and adaptive flexible behaviors rely on continuous dynamical sequences of spiking activity that constitute neural trajectories in the state space of activity. Neural trajectories subserve diverse representations, from explicit mappings in physical spaces to generalized mappings in the task space, and up to complex abstract transformations such as working memory, decision-making and behavioral planning. Computational models have separately assessed learning and replay of neural trajectories, often using unrealistic learning rules or decoupling simulations for learning from replay. Hence, the question remains open of how neural trajectories are learned, memorized and replayed online, with permanently acting biological plasticity rules. The asynchronous irregular regime characterizing cortical dynamics in awake conditions exerts a major source of disorder that may jeopardize plasticity and replay of locally ordered activity. Here, we show that a recurrent model of local PFC circuitry endowed with realistic synaptic spike timing-dependent plasticity and scaling processes can learn, memorize and replay large-size neural trajectories online under asynchronous irregular dynamics, at regular or fast (sped-up) timescale. Presented trajectories are quickly learned (within seconds) as synaptic engrams in the network, and the model is able to chunk overlapping trajectories presented separately. These trajectory engrams last long-term (dozen hours) and trajectory replays can be triggered over an hour. In turn, we show the conditions under which trajectory engrams and replays preserve asynchronous irregular dynamics in the network. Functionally, spiking activity during trajectory replays at regular timescale accounts for both dynamical coding with temporal tuning in individual neurons, persistent activity at the population level, and large levels of variability consistent with observed cognitive-related PFC dynamics. Together, these results offer a consistent theoretical framework accounting for how neural trajectories can be learned, memorized and replayed in PFC networks circuits to subserve flexible dynamic representations and adaptive behaviors.

Acoustic signatures and bubble entrainment mechanisms of a drop impacting a water surface with surfactant

The acoustics of a water drop impact on a bath of water and sodium dodecyl sulfate (SDS) is studied close to the irregular entrainment regime. In particular, acoustic events, corresponding to bubble vibration, are observed for several SDS concentrations. These acoustic events are induced by five different kinds of hydrodynamic events, including four different bubble entrainment mechanisms and one bubble excitation mechanism. These families of events appear to have their own acoustic signature. The different mechanisms are described in detail and typical signals belonging to these families are presented. Their main features are highlighted and linked to the hydrodynamics of the corresponding event.

Principales barreras en el control de las dislipemias: intolerantes

The lack of achieving the LDL-cholesterol goal observed in epidemiological studies, highlights the difficulty of transferring the benefit of the hypolipidaemic treatment noted in clinical trials, to current clinical practice. Although the reasons for not reaching LDL targets are probably multiple, i.e. treatment non-adherence, or therapeutic inertia, or treatment discontinuation as a consequence of statin intolerance, is frequently described. Statins are safe medications. However, 10 to 20% of the population refer to myalgias associated with their use, and 1 to 3% abandon treatment for this cause. In these subjects, it is necessary to change to a different statin, to use lower doses of statins, or to use irregular prescription regimes. If these actions are not useful, emphasis should be placed on the importance of hygienic and dietary recommendations and, when needed and depending on the cholesterol goal to achieve, the need of other lipid lowering treatments, like ezetimibe, bile acid sequestrants, bempedoic acid, or PCSK9i, often in combination.

Plug Regime Flow Velocity Measurement Problem Based on Correlability Notion and Twin Plane Electrical Capacitance Tomography: Use Case.

In this paper, the authors present the flow velocity measurement based on twin plane sensor electrical capacitance tomography and the cross-correlation method. It is shown that such a technique has a significant restriction for its use, particularly for the plug regime of a flow. The major issue is with the irregular regime of the flow when portions of propagated material appear in different time moments. Thus, the requirement of correlability of analyzed input signal patterns should be met. Therefore, the checking of the correlability should be considered by such a technique. The article presents a study of the efficiency of the original algorithm of automatic extraction of the suitable signal patterns which has been recently proposed, to calculate flow velocity. The obtained results allow for choosing in practice the required parameters of the algorithm to correct the extraction of signal patterns in a proper and accurate way. Various examples of the application of the discussed algorithm were presented, along with the analysis of the influence of the parameters used on the quality of plugs identification and determination of material flow.

Composition and structure of algocoenosises in the estuary of right bank Volga’s tributary Kudma river

Present work provides information on the taxonomic composition and structural parameters of algocoenosises of the Kudma river, a right-bank Volga tributary. Data was obtained during the analysis of samples of plant plankton taken in the mouth of the river in 2019. The Kudma river is characterized by an irregular water regime, high salinity and relatively strong anthropogenic impact. Analysis of the algal flora of the studied water body revealed 248 species and intraspecific taxa, as well as algae identified to the genus, which belonged to 8 divisions. The flora was characterized as green-diatom-blue-green, with a significant predominance of green algae. The biomass during the period from May to October were quite high and corresponded to the eutrophic level. The biomass reached values of 18.80 g/m3. The complex of structure-forming species was mainly formed by centric diatoms. In Kudma river’s algocoenosises during summer period the presence of an invasive species, the dinophytic alga Unruhdinium kevei (Grigorszky & F.Vasas) Gottschling is noted.

Method and tools for determining heat transfer coefficients in organic liquids and solutions

The paper presents a method, tools and a newly developed algorithm for experimentally determining heat transfer coefficients in organic liquids and solutions. This work is made relevant by the problem of development of a new generation of aerospace technology. In this connection, improvements have been made to the pulse method of determining heat transfer coefficients that is based on the use of a micron-thick film sensor. The measurement setup was modified. A math model was constructed for the measuring sensor. Algorithms were developed for conducting the experiment and processing measurement results to determine heat transfer coefficients. Experimental uncertainties were analyzed. The paper provides results of experimental studies on certain organic liquids. The authors believe that the material presented in the paper will find application in research conducted at research institutions, engineering offices and universities, among researches, postgraduates and students. Key words: thermal and physical characteristics, organic liquids and their solutions, film-type electrical resistor, thin-film temperature sensor, voltage pulse, resistance thermometer, irregular heat transfer regime.

Pattern of mercury distribution in sediments from an irregular hydrological regime estuary

The Patos Estuary, in southern Brazil, is subject to an irregular hydrological regime and receives mercury (Hg)-contaminated effluents from the city of Rio Grande since the colonial period of southern Brazil. Aiming to investigate sulfate reduction effects over Hg geochemistry in a shallow area (SA) and a salt marsh (SM) from the Patos Estuary, four sediment cores were collected during two distinct hydrological regimes (i.e., freshwater dominated and brackish water dominated). An assessment of free dissolved sulfide (ΣS−II) concentration and pH in pore water and metals (Fe and Hg), fine grained (<63μm) and organic carbon (OC) contents in sediment allowed us to conclude that mercury distribution in SA is chiefly controlled by <63μm sediments and metal sulfide formation. Furthermore, redox conditions were relatively stable during both sampling periods. Nevertheless, bioturbation promotes oxygen penetration and subsequent acidification of pore water associated with upper sediment layers in SM, especially during the brackish water period. Most likely, such oxidizing conditions hamper sulfate reduction and, thereafter, Hg immobilization via the formation of metal sulfides. No evidence of anthropogenic contamination was found in the studied sediments.

Landscape factors modulating patterns of salmonid distribution during summer in north Patagonian rivers.

Understanding how ecosystem processes influencing fish distribution operate across spatial scales is important to understand biological invasions. Salmonids, originally from the Northern Hemisphere, have been repeatedly introduced throughout the world, making them an ideal group to test hypotheses about factors driving invasions. We assessed the influence of environmental variables at the watershed scale on the abundance and structure of salmonid assemblages in the breeding streams of the Upper Limay river basin, Rio Negro, Argentina. We combined field captures with digital map data and geographic information systems to examine landscape-level patterns of salmonid abundance in 35 representative sub-basins of the environmental gradient. We employed a hierarchical cluster analysis and classification and regression tree models to relate the abundance of salmonids and types of species assemblages with environmental characteristics at watershed level. We found stream localization, precipitation regime, altitude and air temperature to be important predictors of the abundance and assemblage structure of salmonids. Total catches showed an increasing gradient of catch-per-unit-effort from west to east and from north to south, with Oncorhynchus mykiss being the most abundant species. O. mykiss relative abundance was westward skewed, where smaller catchments with steeper and shaded valleys are drained by less productive streams with more irregular hydrological regimes, like those found in this species' North American native range. In contrast, the abundance of Salmo trutta abundance was eastward skewed, where larger, sunnier and more gently sloped catchments result in more productive streams with stable hydrological regimes, like those found in that species' European native range. Thus, differential salmonid abundance could result from the interplay between the evolutionary fingerprint left by each species' native environment (especially flow and temperature regimes) and the availability of those conditions in new environments to which they have been translocated. By furthering our understanding of how landscape conditioned invasion success, these findings can help guide the management of economically important introduced fish.

Interaction between a falling sphere and the structure of a non-Newtonian yield-stress fluid

We present an experimental study using mixtures of aqueous superabsorbent polymers (SAP) where we systematically investigate the influence of the size of grains that make up the fluid structure on the mixture effective rheology and its domain of validity. In water, SAP powder grains can swell up to 200 times and form gel grains, dg, whose sizes (typically between 1 and 8 mm) can be controlled by choosing the size of the initial powder grains. The rheology of this mixture (water and touching grains) combines viscous, elastic and plastic aspects. Here, they are characterized using the free-fall of spheres of different densities and diameters (ds). The latter were varied between 3 and 30 mm, therefore providing a range where they become comparable to the fluid gel grains.We observe five different regimes of motion: (1) A linear regime where the sphere has a rapid and straight fall and reaches a constant terminal velocity. (2) An irregular regime where the sphere’s velocity varies around a constant value. (3) An intermittent regime where periods of no-motion and periods of irregular falls follow one another. (4) A slow fall regime where the sphere’s speed progressively decreases in a logarithmic way. (5) A no-motion regime when spheres are not heavy enough to overcome the yield stress of the mixture, or are too small compared to the grain size.The sphere trajectories in regimes (1), (2) and (3) are all following a same trend which, in the framework of a Herschel–Bulkley fluid, allows to estimate the effective yield stress σY and consistency Kv of the SAP mixtures. Both σY and Kv increase with increasing gel grain size. Regimes (2) and (3) are due to the interactions between the falling sphere and individual gel grains, i.e. the fluid structure. Moreover, the critical Yield number (Yc, which compares σY to the stress induced by the sphere’s net weight in the fluid) above which there is no motion decreases as ds∕dg becomes smaller than 2. So although the characteristic size of the fluid structure influences the magnitude of its rheological properties, the use of a Herschel–Bulkley rheology to describe the trajectories of the spheres breaks down only when the sphere diameter becomes very close to the SAP structure size.

Chemical Resonance, Beats, and Frequency Locking in Forced Chemical Oscillatory Systems.

Resonance, beats, and synchronization are general and fundamental phenomena in physics. Their existence and their in-depth understanding in physical systems have led to several applications and technological developments shaping our world today. Here we show the existence of chemical resonance, chemical beats, and frequency locking phenomena in periodically forced pH oscillatory systems (sulfite–hydrogen peroxide and sulfite–formaldehyde–gluconolactone pH oscillatory systems). Periodic forcing was realized by a superimposed sinusoidal modulation on the inflow rates of the reagents in the continuous-flow stirred tank reactor. The dependence of the time period of beats follows the relation known from classical physics for forced physical oscillators. Our developed numerical model describes qualitatively the resonance and beat phenomena experimentally revealed. Application of periodic forcing in autonomously oscillating systems can provide new types of oscillators with a controllable frequency and new insight into controlling irregular chemical oscillation regimes.

Effect of moderate DC electric field on formation of surfactant-laden drops

The continuous formation of mm-scale surfactant-laden aqueous drops in oil was studied under an applied DC electric field of 0–267 kV/m. The parameters varied included the flow rate of dispersed phase, the electric field strength, the viscosities and densities of dispersed and continuous phase and the surfactant type (anionic or cationic) and concentration. An increase in the electric field strength resulted in a decrease of the drop size due to increasing stresses on the drop interface. The size reduction continued until transition to the irregular regime. The values of critical electric field strength for this transition increased with an increase in both the flow rate and the viscosity ratio between the dispersed and continuous phase. The critical electric field strength and the size of the drops formed in the periodic dripping regime were independent of the electric field polarity. The effect of the electric field increased with a decrease of interfacial tension and density difference between the dispersed and continuous phase.

Leaders and Default

Abstract Sovereign default is a political decision. While previous research on sovereign credit markets focuses on economic causes, domestic constraints, or international reputation to explain why states default, we focus on leaders. We argue that leaders who come to power under irregular circumstances are more likely to default. Irregular leaders are themselves more vulnerable to turnover and therefore prioritize the short-term benefits of default rather than the long-term benefits of repayment. In addition, irregular regime transitions offer new leaders a way to obfuscate responsibility, thus limiting the reputational costs of default. Our analysis of sovereign defaults and leadership transitions from 1875 to 2015 support our claims. Across various model specifications, we find that irregular leadership change increases the odds of default onset by over 300 percent.

Sulfate reduction and alterability of sulfur species in sediments of an estuary with irregular hydrological regime

The irregular hydrological regime in Patos Lagoon estuary has been suggested as having a distinctive influence on sulfur speciation in sediments. We performed an investigation for different prolonged hydrological conditions focusing on the distribution of sulfides (acid volatile sulfide (AVS), chromium reducible sulfide (CRS), and Free-S2-) in sediment cores from salt marsh and non-vegetated shallow zone. Significant differences in sulfides content and distribution between the different hydrological periods were found. The predominance of more reducing conditions was observed during the freshwater period. It reflects a higher total reducible inorganic sulfur (TRIS) content in this period, with a great accumulation of AVS in sediments (> 100 mg kg-1). In the maximum salinity period, more oxidizing conditions prevailed, which significantly decreased the concentrations of metastable sulfides. The intense bioirrigation process exerts control over sulfide formation and distribution, which is as important as that exerted by the variations of the hydrological regime.

Edge AI-IoT Pivot Irrigation, Plant Diseases, and Pests Identification

Overcoming population growth dilemma with less resources of soil and water, the irrigated agriculture allows us to increase the yield and the production of several crops in order to meet the high requirements of demands of food and fibers. Efficiently, an irrigation system should correctly evaluate the amount of water and also the timing, when applying certain irrigation doses. Global warming of the planet, to which is added in some regions an irregular regime of precipitation and a scarcity of available water resources, requires precision irrigation systems. The rational use of water and inputs (mainly fertilizers and pesticides) is crucial in some areas of the planet suffering from a deficiency of water. Hence, in these regions where the environmental conditions are harsh to ensure an efficient crop growth. Moreover, plant diseases and pests impact the yields of crops. For these reasons is it why an early detection gives us the opportunity to treat the disease or pest as quickly and effectively as possible, in order, to reduce the impact of these latter. Nowadays, the identification of plant diseases and pest with Artificial Intelligence algorithms on video flow in real conditions with variable exposition are still being a very challenging problem. Researchers classically develop algorithms that are trained on calibrated exposition images, which does not perform well in real conditions. Furthermore, the processing of a video in real time needs specialized computing resources close to the pivot-center irrigation trained with AI algorithms on real images and then analyzes rapidly, detects problem, and then react accordingly. In this paper, we complete our previous proposed IoT system to optimize the water use and we displaced the computing of data at the edge level in order to be able to process videos locally, event the Internet connection is limited. This local computing power also allows us to manage the supply of fertilizers and the treatment of plant diseases, and pests.

Application of remote sensing and GIS for assessing the level of change of land use status in the coast of Ngoc Hien district (Ca Mau province) due to the impact of sea level rise

Today, environmental hazards and challenges are no longer confined to the national or regional scale but on the global scale. One of the biggest challenges for humanity is the natural disasters, global warming and sea level rise. The natural disasters causing serious consequences for human life, such as: Storms, floods, earthquakes, tsunamis, desertification, high tides... increase in frequency, intensity and scale. In recent years, Ca Mau province as well as coastal provinces of Vietnam is under great influence due to the impacts of climate change. One of the most affected districts in Ca Mau province is Ngoc Hien district. The district has a geographic location with three sides bordering the sea, one side bordering the river, a completely isolated terrain. The terrain is flat, strongly divided by the system of natural rivers and canals and intertwined canals, so it is constantly flooded by the sea. Ngoc Hien district is characterized by a sub-equatorial monsoon climate, directly affected by irregular semi-diurnal regime. The main purpose of the paper is to assess coastal vulnerability due to the impact of climate change over time with GIS-based remote sensing images. Remote sensing data with multi-time characteristics, collected in many periods and covering a wide area is an effective tool for monitoring shoreline fluctuations in particular and land use status of the study area in general.

Biologically Realistic Mean-Field Models of Conductance-Based Networks of Spiking Neurons with Adaptation.

Accurate population models are needed to build very large-scale neural models, but their derivation is difficult for realistic networks of neurons, in particular when nonlinear properties are involved, such as conductance-based interactions and spike-frequency adaptation. Here, we consider such models based on networks of adaptive exponential integrate-and-fire excitatory and inhibitory neurons. Using a master equation formalism, we derive a mean-field model of such networks and compare it to the full network dynamics. The mean-field model is capable of correctly predicting the average spontaneous activity levels in asynchronous irregular regimes similar to in vivo activity. It also captures the transient temporal response of the network to complex external inputs. Finally, the mean-field model is also able to quantitatively describe regimes where high- and low-activity states alternate (up-down state dynamics), leading to slow oscillations. We conclude that such mean-field models are biologically realistic in the sense that they can capture both spontaneous and evoked activity, and they naturally appear as candidates to build very large-scale models involving multiple brain areas.

COMPUTATIONAL MODEL TO IMPROVE DAIRY ANIMAL FEEDING UNDER MIXED FARMING SYSTEM (CROPS/LIVESTOCK) AS STUDY CASE

Computational model was designed for feeding systems of small dairy farms in Egypt under Mixed Farming System (MFS) (Crops/livestock). The present case study was selected from El-Beheira governorate, where the three common dairy animals (Local cows, Crossbred cows and buffaloes) are available. The main objectives of this study were 1- To find out the optimum combination of inputs from farm green forage and cash crops to minimize animal feeding costs. 2- Asses the possibilities of increasing the farm income by least cost rations formulation using available feed resources for dairy cattle. Technical coefficients of the models were obtained from previous studies under Egyptian condition. The model proposed three scenarios: Scenario I (S I) calculated the actual feeding situation from the case study without any changes as base run, scenario II (S II) proposed to cover animal feeding requirements of the same herd in scenario (S I) from the same available feed resources according to NRC (2001) and scenario III (S III) operating on the available feeding package quantities or reallocated farm feed resources for the same herd. The model used the common feed in summer and winter seasons (300 days) while, two months were considered as transitional period between two seasons, where irregular animal feeding regime is adopted. The results showed that area cultivated with green forages can be reduced by 17% and 25% of total planted area in SII for winter and summer, respectively, compared to base run (SI). Where as in S III, the green forage cultivated areas reduced by 30% and 25% for winter and summer, respectively in comparison with SI, feeding costs in SII were reduced by 51.11% and 38.97% in winter and summer, respectively. Using available feeding packages and reallocated farm resources in SIII reduced feeding costs by 47.78% and 27.67% for winter and summer, respectively. It can be concluded that using available feeding packages or reallocated animal feeding resources either in SII and SIII achieved a considerable reduction on animal feeding costs of small-scale mixed farms compared to base run scenario (SI).

Transient mixed convection in a channel with two facing discretely heated semicircular cavities: Buoyancy, inclination angle, and channel aspect ratio effects

ABSTRACTSpace-averaged surface temperature distributions and overall Nusselt number measurements have been carried out to study the transient mixed convection heat transfer in a channel with two facing and symmetrically heated semicircular cavities. Effects of buoyancy, channel orientation, and channel aspect ratio on thermal behavior have been investigated from Re 500 to 1,500. Depending on the parametric set, steady, oscillatory, and irregular thermal regimes have been identified. The natural frequencies and time scales of the oscillatory regimes have been obtained using spectral analysis. Results show that with increase in channel aspect ratio, the heat transfer performance reduces for all inclination angles.

Multitaper harmonic analysis of infant vocalizations

Infant vocalizations exhibit many special complexities relative to adult speech that make acoustic analysis difficult, even though the basic physics of sound production in the vocal tract is identical. Fundamental frequency is raised, resulting in wider-spaced harmonics that make it hard to accurately estimate the spectral envelope or locate formant resonances, which are higher than in adult voices, due to anatomical scaling effects. Irregular vocal fold vibratory regimes are often observed, involving period doubling and other nonlinear phenomena not seen in adult speech, along with atypical patterns of turbulent noise production. Unsurprisingly, traditional analysis techniques that depend on estimating the spectral envelope from the speech signal do not work well when applied to infant vocalizations. An alternative approach is proposed, using multitaper analysis to calculate the time-varying amplitude and phase of every harmonic component of the voice, along with the residual noise component, recovering the vocal tract transfer function from the results. The new technique is compared against linear prediction and cepstral analysis using home audio recordings of 20 infants collected from 0 to 24 months using LENA technology. Developmental progressions in the acoustic structure of the infant voice are identified that cannot be found using traditional methods.