Individual Passes Research Articles

Scanning Acoustic Microscopy Characterization of Cold-Sprayed Coatings Deposited on Grooved Substrates

AbstractThe effect of non-planar substrate surface on homogeneity and quality of cold-sprayed (CS) deposits was studied by scanning acoustic microscopy (SAM). Fe coatings were cold-sprayed onto Al substrates containing artificially introduced grooves of square- and trapezoid-shaped geometries, with flat or cylindrical bottoms. The Al substrates were either wrought or cold-sprayed, to comprehend their prospective influence on the Fe coatings buildup. SAM was then used to assess morphological properties of the materials from the cross-view and top-view directions. The microstructure below the surface of the studied samples was visualized by measuring the amplitudes of the reflection echoes and the velocity of the ultrasonic waves. The SAM analysis revealed that the regions of coating imperfections around the grooves are larger than what is suggested by standard scanning electron microscopy (SEM) observations. Furthermore, we found that the seemingly non-influenced coating regions that appear perfectly homogeneous and dense in SEM do, in fact, possess heterogeneous microstructure associated with the individual CS nozzle passes.

Comparative Measurement of Horizontal Penetrometry with a Focus on the Degree of Soil Compaction in Real Work Conditions

Potential soil production is closely related to the physical and mechanical properties. The aim of this paper was to evaluate the effect of different levels of soil compaction created by tractor chassis. The total area of the experimental plot was 13.22 ha. Up until 2019, a conventional tillage system had been used. The measurements were carried out with an innovative measuring device that allows for the continuous measurement of the horizontal penetrometry for comparative measurements while driving, which was designed at the Slovak University of Agriculture in Nitra. The measuring device measured the soil resistance in the tire track (On-track) and out of track (Off-track) as well as in three (50 s) sequences within one tractor pass. Three lines were chosen, where in each a pair of combinations was made. The results were subjected, in addition to graphical evaluation, to single factor ANOVA analysis. When comparing individual passes (PH1 to PH6), the statistical analysis showed that the results of the horizontal resistance measurements proved to be statistically significant (p < 0.05) with respect to the weight, number of passes, and tire underinflation. The highest compaction was caused by the first pass, while the higher weight of the tractor during the next pass had a smaller effect. Underinflating the tires ensured a reduction in compaction. Reducing the tractor tire pressure to 0.15 MPa resulted in a reduction in soil compaction of up to 16%.

Machine learning based heart disease prediction system

Anticipating heart illness has been one of the foremost challenging errands in medication in later a long time. Nowadays approximately one individual passes on from a heart assault each miniature. Information science plays an imperative part in handling expansive sums of information in healthcare. Since the desire of heart disease may be a troublesome errand. It is essential to total the determining prepare to maintain a strategic distance from the chance related with it and to caution patients in development. This venture employments a heart malady database with 303 persistent records and 13 parameters. This article works the hazard of heart assault utilizing distinctive learning calculations such as Calculated Relapse, Irregular Timberland, K Neighbors, and finds he leading calculation from the proper ones and returns the yield in like manner. In this way, this amplify provides a comparison by analyzing the performance of a custom learning machine.

Diachronic Emergence as Transubstantiation

Diachronic emergence has recently been characterised as transformation. This aims to capture the thought that the entities that emerge are radically new or different. Transformation is hence closely linked with a central (but rarely raised) challenge for all emergentists: how to account for the identity and individuation of entities involved in emergence. With this challenge in view, I develop and probe four interpretations of transformation: addition, replacement, fusion, and transubstantiation. Of those, transubstantiation provides the most plausible response to the challenge about identity. Accordingly, diachronic emergence is a transformative process whereby an individual passes from one primary kind to another.

Single-blind determination of methane detection limits and quantification accuracy using aircraft-based LiDAR

Methane detection limits, emission rate quantification accuracy, and potential cross-species interference are assessed for Bridger Photonics’ Gas Mapping LiDAR (GML) system utilizing data collected during laboratory testing and single-blind controlled release testing. Laboratory testing identified no significant interference in the path-integrated methane measurement from the gas species tested (ethylene, ethane, propane, n-butane, i-butane, and carbon dioxide). The controlled release study, comprised of 650 individual measurement passes, represents the largest dataset collected to date to characterize GML with respect to point-source emissions. Binomial regression is utilized to create detection curves illustrating the likelihood of detecting an emission of a given size under different wind conditions and for different flight altitudes. Wind-normalized methane detection limits (90% detection rate) of 0.25 (kg/h)/(m/s) and 0.41 (kg/h)/(m/s) are observed at a flight altitude of 500 feet and 675 feet above ground level, respectively. Quantification accuracy is also assessed for emissions ranging from 0.15 to 1,400 kg/h. When emission rate estimates were generated using wind from high-resolution rapid refresh (HRRR) model (the primary wind source that Bridger uses for their commercial operations), linear regression indicates bias of 8.1% (R2 = 0.89). For 95% of controlled releases above Bridger’s stated production-sector detection sensitivity (3 kg/h with 90% probability of detection), the accuracy of individual emission rate estimates produced using HRRR wind ranged from −64.1% to +87.0%. Across all controlled releases, 38.1% of estimates had error within ±20%, and 87.3% of measurements were within a factor of two (−50% to +100% error). At low wind speed (less than 2 m/s) and low emission rates (less than 3 kg/h), emission estimates are biased high, however when removed do not impact the regression significantly. The aggregate quantification error including all detected emission events was +8.2% using the HRRR wind source. The resulting detection curves and quantification accuracy illustrate important implications that must be considered when using measurements from GML or other remote emission measurement techniques to inform or validate inventory models or to audit reported emission levels from oil and gas systems.

A new approach for accurate determination of particle sizes in microfluidic impedance cytometry

In microfluidic impedance cytometry, the change in impedance is recorded as an individual cell passes through a channel between electrodes deposited on its walls, and the particle size is inferred from the amplitude of the impedance signal using calibration. However, because the current density is nonuniform between electrodes of finite width, there could be an error in the particle size measurement because of uncertainty about the location of the particle in the channel cross section. Here, a correlation is developed relating the particle size to the signal amplitude and the velocity of the particle through the channel. The latter is inferred from the time interval between the two extrema in the impedance curve as the particle passes through a channel with cross-sectional dimensions of 50 μm (width) × 30 μm (height) with two pairs of parallel facing electrodes. The change in impedance is predicted using 3D COMSOL finite-element simulations, and a theoretical correlation that is independent of particle size is formulated to correct the particle diameter for variations in the cross-sectional location. With this correlation, the standard deviation in the experimental data is reduced by a factor of two to close to the standard deviation reported in the manufacturer specifications.

The role of generalised reciprocity and reciprocal tendencies in the emergence of cooperative group norms

• We examined the emergence of cooperation among small groups of anonymous players. • Behavioural modelling revealed the role of generalised reciprocity on behaviour. • Players differed in their reciprocal tendencies, and can be grouped into four types. • Interactions among different player types resulted in different group dynamics. • Cooperation relies on specific group compositions vis-à-vis reciprocal tendencies. Norms for cooperation are essential for groups to function effectively, yet there are often strong incentives for group members to behave selfishly. Direct and indirect reciprocity can help to discourage such uncooperative behaviour by punishing defectors and rewarding cooperators, but require explicit means for punishment and tally-keeping. What, then, encourages an individual to cooperate with their group when others cannot track the behaviour of others? We adapted the Bargaining Game to examine the emergence and maintenance of cooperation among 20 groups of six anonymous players (N = 120) who interacted amongst themselves over recursive bargaining exchanges. By estimating the expected utility that drives players’ demands in these interactions, we demonstrate that their behaviour on each exchange reflects the demands placed upon them previously. Thus, we highlight the role of generalised reciprocity in such situations; that is, when an individual passes on to another member of their group the behaviour they have received previously. Furthermore, we identify four distinct behavioural types that differ in their expressions of generalised reciprocity: Some players converge quickly on cooperative demands regardless of the behaviour they received from their co-players, and are therefore characterised by low expressions of reciprocity. In contrast, individuals with strong reciprocal tendencies decrease their demands over successive interactions in response to the behaviour of their group. By simulating groups with different compositions of these player types, we reveal the strong influence of individual differences in reciprocal tendencies on the emergence of cooperative group dynamics.

What is the best fitness measure in wild populations? A case study on the power of short-term fitness proxies to predict reproductive value.

Fitness is at the core of evolutionary theory, but it is difficult to measure accurately. One way to measure long-term fitness is by calculating the individual’s reproductive value, which represents the expected number of allele copies an individual passes on to distant future generations. However, this metric of fitness is scarcely used because the estimation of individual’s reproductive value requires long-term pedigree data, which is rarely available in wild populations where following individuals from birth to death is often impossible. Wild study systems therefore use short-term fitness metrics as proxies, such as the number of offspring produced. This study compared two frequently used short-term metrics for fitness obtained at different offspring life stages (eggs, hatchlings, fledglings and recruits), and compared their ability to predict reproductive values derived from the genetic pedigree of a wild passerine bird population. We used twenty years of precise field observations and a near-complete genetic pedigree to calculate reproductive success, individual growth rate and de-lifed fitness as lifetime fitness measures, and as annual de-lifed fitness. We compared the power of these metrics to predict reproductive values and lineage survival to the end of the study period. The three short-term fitness proxies predict the reproductive values and lineage survival only when measured at the recruit stage. There were no significant differences between the different fitness proxies at the same offspring stages in predicting the reproductive values and lineage survival. Annual fitness at one year old predicted reproductive values equally well as lifetime de-lifed fitness. However, none of the short-term fitness proxies were strongly associated with the reproductive values. The commonly used short-term fitness proxies best predict long-term fitness when measured at recruitment stage. Thus, because lifetime fitness measured at recruit stage and annual fitness in the first year of life were the best proxies of long-term fitness in short-lived birds, we encourage their future use.

Automatic detection of passing and shooting in water polo using machine learning: a feasibility study

ABSTRACT There is currently no efficient way to quantify overhead throwing volume in water polo. Therefore, this study aimed to test the feasibility of a method to detect passes and shots in water polo automatically using inertial measurement units (IMU) and machine-learning algorithms. Eight water polo players wore one IMU sensor on the wrist (dominant hand) and one on the sacrum during six practices each. Sessions were filmed with a video camera and manually tagged for individual shots or passes. Data were synchronised between video tagging and IMU sensors using a cross-correlation approach. Support vector machine (SVM) and artificial neural networks (ANN) were compared based on sensitivity and specificity for identifying shots and passes. A total of 7294 actions were identified during the training sessions, including 945 shots and 5361 passes. Using SVM, passes and shots together were identified with 94.4% (95%CI = 91.8–96.4) sensitivity and 93.6% (95%CI = 91.4–95.4) specificity. Using ANN yielded similar sensitivity (93.0% [95%CI = 90.1–95.1]) and specificity (93.4% [95%CI = 91.1 = 95.2]). The results suggest that this method of identifying overhead throwing motions with IMU has potential for future field applications. A set-up with one single sensor at the wrist can suffice to measure these activities in water polo.

Changes in the Properties in Bimodal Mg Alloy Bars Obtained for Various Deformation Patterns in the RSR Rolling Process.

The paper presents the theoretical and experimental research conducted to date regarding the possibility of obtaining round bars from AZ31 magnesium alloy with a bimodal structure rolled in the radial shear rolling process (RSR) technology. There is no analysis of the impact of the deformation path (distribution of deformation in individual passes) on the mechanical properties and the obtained bar structure. The feedstock, namely, AZ31 magnesium alloy round bars with a diameter of 30 mm, were rolled in RSR to the final diameter of 15 mm with different levels of deformation in successive passes, at a temperature of 400 °C. The bars obtained as a result of the RSR rolling process have different hardness on the cross-section as well as a characteristic gradient grain size distribution. Based on the conducted research, it can be concluded that the use of a larger number of passes with a smaller cross-section reduction will result in an improved formation of a bimodal structure consisting of a highly fragmented near-surface structure and in the half of the radius of the structure of fragmented grains at the boundaries of larger grains.

A modeling study of water and sediment flux partitioning through the major passes of Mississippi Birdfoot Delta and their plume structures

The Mississippi River Delta consists of six major passes and numerous small crevasses through which water and sediments are transported to the continental shelf of northern Gulf of Mexico. The water and sediment fluxes through individual passes are not routinely monitored due to the complex morphology and challenging environment. However, they are critical factors in determining the highly nonlinear near-field characteristics of freshwater plumes, fronts, possible internal hydraulic jumps, nutrient dispersal and rapid initial deposition of fine sand and mud. The flux partitioning and flow/sediment dispersal characteristics near the modern Mississippi River Delta were investigated using a high-resolution (~ 100 m horizontally) unstructured-grid, three-dimensional coupled hydrodynamic-wave-sediment numerical model. Model result analysis for the period of April–June 2010 revealed that Southwest Pass is the main conduit among the six major passes, through which 64% and 32% of the Mississippi River water and sediment, respectively, are transported to the coastal ocean. In contrast, South Pass has the lowest water and sediment fluxes among the tri-furcation channels downstream of the Head of Passes. Due to the more energetic flow at Southwest Pass compared to other passes, an elongated freshwater/sediment jet is typically present in the near-field. The average width of the plume originating from Southwest Pass, 5 km away from the mouth, is approximately 8 km, while the high sediment concentration within the plume (SSC > 10−2 kg/m3) is maintained in the upper 4 m of the water column for more than 8 km. The pattern of the plume in the far-field varies with wind direction, and the buoyant plume bends towards the coast/mid-shelf in response to downwelling/upwelling favorable winds.

Factors associated with adoption of indigenous biscuit processing technology by mothers of school-going children in Ogun State, Nigeria

Wheat is the conventional flour in biscuit manufacture. However, the use of wheat is not economical due to the fact that huge foreign reserve is used in its importation in Nigeria. In addition, wheat-based foods are associated with celiac disease, hence the use of non-wheat crops like tubers and legumes in biscuit processing is desirable. A previous study had developed a nutritionally improved biscuit from underutilized crops, such as sweet potato, cooking banana and pigeon pea. The present study examined factors associated with adoption of the indigenous biscuit processing technology using non-wheat flours by mothers of school going children in Ogun State, Nigeria. A-multistage sampling procedure was utilized to select 120 respondents from the list of 1,123 registered farmers in 10 extension blocks in Ogun State. A questionnaire was used to collect data on the socioeconomic characteristics of respondents. Respondents were taught the various stages of biscuit processing through demonstration. Knowledge about the various stages of biscuit processing was measured on a 5-point Likert Scale. The five points used were: extremely understood, moderately understood, somewhat understood, slightly understood and not understood. Level of adoption indicates the psychological stages that an individual passes through before making a final decision to use a particular innovation. Adoption Level was thus measured on Knowledge, Persuasions, Decision, Confirmation and Continuation decision. Data were analyzed using Analysis of Variance, Chi square, and Pearson Product Moment Correlation. Results revealed the mean age of respondents to be 40.35 ± 10.33 years. Most respondents were traders, and the highest educational qualification was National Diploma (2.5%). The main sources of agricultural information were radio (64.2%) and extension agents (60%). There were high adoption rates in baking/production (87.7%) and flour blending (85.5%). Reasons for technology adoption were affordability (80.8%), availability of ingredients (81.7%) and relative advantage (80.8%). Adoption of technology was associated with age (r = 0.284, p < 0.05), quality of technology delivery (r = 0.267, p < 0.05), marital status (χ2 = 1.081, p < 0.05) and membership of association (χ2 = 12.055, p < 0.05). In conclusion, effective adoption of technology could be achieved among young married mothers.

Characteristics of the Passive Muscle Stiffness of the Vastus Lateralis: A Feasibility Study to Assess Muscle Fibrosis.

Skeletal muscle fibrosis occurs with aging and has been suggested to impair muscle performance, thereby decreasing quality of life. Recently, muscle stiffness, a surrogate measure of muscle fibrosis, was noninvasively quantified as the shear modulus using ultrasound shear wave elastography (SWE) in humans. We aimed to investigate thigh muscle stiffness in females and males, respectively, across a broad range of ages by using SWE. Eighty-six community-dwelling Japanese people who were aged 30 to 79 years and did not regularly exercise participated in this study. The vastus lateralis (VL) shear modulus was measured at three different knee joint angles: full extension, 90° of flexion, and full flexion. There were no significant main effects of sex or age on the VL shear modulus in full extension or 90° of flexion of the knee. However, the VL shear modulus in knee full flexion was significantly smaller in females than in males and increased with age from 47.9 years. The results suggest that the accelerated increase in VL stiffness that occurs after an individual passes their late 40s may be an important therapeutic target for developing effective treatments and programs that preserve and improve quality of life.

Sensor-Enabled Multi-Robot System for Automated Welding and In-Process Ultrasonic NDE.

The growth of the automated welding sector and emerging technological requirements of Industry 4.0 have driven demand and research into intelligent sensor-enabled robotic systems. The higher production rates of automated welding have increased the need for fast, robotically deployed Non-Destructive Evaluation (NDE), replacing current time-consuming manually deployed inspection. This paper presents the development and deployment of a novel multi-robot system for automated welding and in-process NDE. Full external positional control is achieved in real time allowing for on-the-fly motion correction, based on multi-sensory input. The inspection capabilities of the system are demonstrated at three different stages of the manufacturing process: after all welding passes are complete; between individual welding passes; and during live-arc welding deposition. The specific advantages and challenges of each approach are outlined, and the defect detection capability is demonstrated through inspection of artificially induced defects. The developed system offers an early defect detection opportunity compared to current inspection methods, drastically reducing the delay between defect formation and discovery. This approach would enable in-process weld repair, leading to higher production efficiency, reduced rework rates and lower production costs.

Multi-pass probing for high-sensitivity tomographic interferometry

Optical probing is an indispensable tool in research and development. In fact, it has always been the most natural way for humankind to explore nature. However, objects consisting of transparent materials with a refractive index close to unity, such as low-density gas jets, are a typical example of samples that often reach the sensitivity limits of optical probing techniques. We introduce an advanced optical probing method employing multiple passes of the probe through the object to increase phase sensitivity, and relay-imaging of the object between individual passes to preserve spatial resolution. An interferometer with four-passes was set up and the concept was validated by tomographic characterization of low-density supersonic gas jets. The results show an evident increase of sensitivity, which allows for the accurate quantitation of fine features such as a shock formed by an obstacle or a barrel shock on the jet boundary in low ambient gas pressures. Despite its limitations in temporal resolution, this novel method has demonstrated an increase in phase sensitivity in transmission, however, it can also be employed to boost the absorption or polarization contrast of weakly interacting objects in both transmission and reflection setups, thus, upgrading the sensitivity of various optical characterization methods.

Diminishing returns with successive device passes in mechanical thrombectomy for stroke

BackgroundMultiple device passes are associated with complications and poor functional outcomes following mechanical thrombectomy (MT) for emergent large vessel occlusion (ELVO). ObjectiveTo characterize the relationship between number of device passes, complications, angiographic outcomes, and clinical outcomes in MT for ELVO. MethodsThis is a single-center, retrospective cohort study. Individual device passes for MT were evaluated for any change in Thrombolysis in Cerebral Infarction (TICI) score, successful revascularization (TICI 2b or 3), and complications. Outcomes were compared among groups requiring multiple passes with various cut-off points. Risk factors for unfavorable clinical outcome [90 day modified Rankin Scale > 2] were assessed using multivariate analysis. ResultsSuccessful revascularization was achieved in 75% of 163 patients and 36% required only one device pass. After the second pass, the likelihood of angiographic improvement significantly decreased (p < 0.001). Using multiple cut-off points, higher post-procedural NIHSS scores, mortality rates, and unfavorable 90-day outcomes were associated with a greater number of passes. Multivariate analysis revealed ICA thrombus (comparison: M2, OR: 25, 95% CI 2–275, p = 0.01) and failed revascularization (OR: 68, 95% CI 3.12–1489, p = 0.01) as the only significant predictors of unfavorable clinical outcome. Nonetheless, the likelihood of favorable clinical outcome was higher in patients with an ICA occlusion who were revascularized in < 2 vs. ≥ 2 (44 vs 4%, p = 0.01) or < 3 vs. ≥ 3 (32 vs. 0%, p = 0.02) passes. ConclusionThe likelihood of angiographic improvement in patients with ELVO significantly decreases after the second pass. A greater number of passes is associated with worsened clinical outcomes.

RETRACTED: Gui based prediction of heart stroke using artificial intelligence

Abstract Heart strokes are most regularly caused by atherosclerosis or solidifying of the supply routes, and carry the same chance components as heart assaults (myocardial localized necrosis, coronary supply route illness) and peripheral vascular illness. The properties incorporate high blood weight, high cholesterol, diabetes, and smoking. Agreeing to american heart affiliation, one individual passes on every 36 s from the heart illness within the united states. The passing rate of heart stroke is almost 18.1% out of each 3000 patients. It is the fifth driving illness to cause passing. Numerous methods have been broadly utilized in anticipating the event, conclusion, and prognosis of the illness to help the clinicians for the treatment. The most objective is to propose a machine learning-based strategy to anticipate the heart stroke of best precision from comparing administered classification of machine learning calculations. We have moreover computed recipient hopeful bend and range beneath the bends for each classifier. Furthermore, to compare and examine the execution of the different machine learning calculations from the given demonstration with an assessment report, distinguish the perplexity framework, and categorize information. The graphical user interface (gui) is based on the proposed machine learning calculation procedure which can be compared with the finest exactness with precision, review, f1score, roc, affectability, specificity and appears the result successfully.

John Rawls’s Conception of Personal Moral Development

J. Rawls’ conception of individual moral development has undeservedly rarely attracted scholars’ attention. It is most often addressed in respect to the tasks of clarifying moral psychology or moral sentiments how Rawls has understood them. Meanwhile, it is undoubtedly a matter of interest as such, since, on the one hand, it echoes in a number of its parameters with the leading theories of moral development of the 20th century (J. Piaget, L. Kohlberg), and, on the other hand, it presents a philosophical theory, which has no corresponding empirical basis, and Rawls purposefully developed in order to clarify some of the fundamental provisions of his theory of justice. Rawls’ concept assumes that the individual passes through three stages in moral development — “the morality of authority”, “the morality of association” and “the morality of principles”. At each stage, the individual demonstrates special ways of justifying moral decisions and moral motivation, each of them reveals a unique understanding of guilt and its causes, as well as their own sets of virtues and vices. As Rawls shows, the personal moral development is continuous: the experience of the morality of authority creates prerequisites for the familiarization of the morality of association, and the experience of the latter prepares the individual for acquirement of the morality of principles. At the same time, the model the stages of individual moral development proposed by Rawls can be easily interpreted in terms of the typology of moral systems, and this conjugation of the schematics of moral development and the typology of moral systems is of clearly interest. The article concludes that due to the moral and psychological consideration, Rawls was able to reveal the context in which the principles of justice become significant, and their development by the individual ultimately marks the transformation and elevation of one’s everyday experience.

Microstructure Evolution in Cu–0.5 wt% Zr Alloy Processed by a Novel Severe Plastic Deformation Technique of Rotational Constrained Bending

In the present study, a coarse-grained Cu–0.5 wt% Zr alloy was repeatedly processed by a novel technique of rotational constrained bending (RCB). In this technique, the workpiece was deformed by bending in a channel with an angle of 90°, using a rotating roller. The influence of the number of passes (N) of RCB on strain distribution, microstructure evolution and mechanical properties of the alloy was investigated. The heterogeneous distribution of the microhardness in the billet cross-section after the first pass was transformed into a homogeneous one after twelve passes, due to the rotation of the sample by 90° clockwise between individual passes. In addition, the gradual refinement/homogenization of the microstructure and formation of strong (110) crystallographic texture were found with increasing N. The initial grain size of 180 μm decreased down to 3.4 μm after twelve passes. The dislocation density increased by two orders of magnitude after RCB processing. In accordance with the grain-size refinement and the strong increase of the dislocation density, RCB processing significantly enhanced the strength of the alloy, while the ductility considerably decreased. The yield stress increased from 63 to 524 MPa, while the elongation to failure decreased below 10% after twelve passes.

Modeling latent infection transmissions through biosocial stochastic dynamics.

The events of the recent SARS-CoV-2 epidemics have shown the importance of social factors, especially given the large number of asymptomatic cases that effectively spread the virus, which can cause a medical emergency to very susceptible individuals. Besides, the SARS-CoV-2 virus survives for several hours on different surfaces, where a new host can contract it with a delay. These passive modes of infection transmission remain an unexplored area for traditional mean-field epidemic models. Here, we design an agent-based model for simulations of infection transmission in an open system driven by the dynamics of social activity; the model takes into account the personal characteristics of individuals, as well as the survival time of the virus and its potential mutations. A growing bipartite graph embodies this biosocial process, consisting of active carriers (host) nodes that produce viral nodes during their infectious period. With its directed edges passing through viral nodes between two successive hosts, this graph contains complete information about the routes leading to each infected individual. We determine temporal fluctuations of the number of exposed and the number of infected individuals, the number of active carriers and active viruses at hourly resolution. The simulated processes underpin the latent infection transmissions, contributing significantly to the spread of the virus within a large time window. More precisely, being brought by social dynamics and exposed to the currently existing infection, an individual passes through the infectious state until eventually spontaneously recovers or otherwise is moves to a controlled hospital environment. Our results reveal complex feedback mechanisms that shape the dependence of the infection curve on the intensity of social dynamics and other sociobiological factors. In particular, the results show how the lockdown effectively reduces the spread of infection and how it increases again after the lockdown is removed. Furthermore, a reduced level of social activity but prolonged exposure of susceptible individuals have adverse effects. On the other hand, virus mutations that can gradually reduce the transmission rate by hopping to each new host along the infection path can significantly reduce the extent of the infection, but can not stop the spreading without additional social strategies. Our stochastic processes, based on graphs at the interface of biology and social dynamics, provide a new mathematical framework for simulations of various epidemic control strategies with high temporal resolution and virus traceability.