Theoretical study of the impact aimed at improving the efficiency of fiber cleaning

Since cotton cleaning in Uzbekistan is carried out mainly manually, this paper discusses the methods and technologies established in the process of cleaning cotton and fiber. The process of fiber cleaning is one of the important processes that complete the technological process of cotton processing, given that the quality of fiber largely depends on the efficiency of this process, the research work on the mechanization of the type of collection and improving the efficiency of its cleaning is analyzed. In order to improve the efficiency of cleaning cotton collected on the machine, information is provided on the need to improve the equipment for cleaning fiber used in cotton gins. The research results are based on the need to replace a special structural device that guides the fiber to the correct tooth of the first sawtooth cylinder located on two drum cleaning plants. New fiber-cleaning equipment was installed in the Jizzakh regional JSC “Zarbdor cotton cleaning» and experimental tests were conducted in production conditions. In addition, the process of changing the pressure, density and speeds in the furnace and the effect of their cleaning efficiency has been modeled and theoretically analyzed, when the efficiency of cleaning the cotton fiber flow using a column system allows changing the raw material from 4 mm to 15 mm based on the device. By results of the conducted analysis it was shown that the increase of efficiency of purification depends on the device attached to the saw teeth, factor of the taxation of the distribution coefficient B and p 0 efficiency factor of increasing the initial pressure and coefficient of efficiency savings from the analysis of graphs, which present graphs of the distribution depending on the type of saw teeth. Based on the results of the research, recommendations are given for the widespread introduction of fiber cleaning equipment installed at enterprises of primary cotton processing, with the installation of a special structural guide device.

Lightwave-driven scanning tunnelling spectroscopy of atomically precise graphene nanoribbons

Atomically precise electronics operating at optical frequencies require tools that can characterize them on their intrinsic length and time scales to guide device design. Lightwave-driven scanning tunnelling microscopy is a promising technique towards this purpose. It achieves simultaneous sub-ångström and sub-picosecond spatio-temporal resolution through ultrafast coherent control by single-cycle field transients that are coupled to the scanning probe tip from free space. Here, we utilize lightwave-driven terahertz scanning tunnelling microscopy and spectroscopy to investigate atomically precise seven-atom-wide armchair graphene nanoribbons on a gold surface at ultralow tip heights, unveiling highly localized wavefunctions that are inaccessible by conventional scanning tunnelling microscopy. Tomographic imaging of their electron densities reveals vertical decays that depend sensitively on wavefunction and lateral position. Lightwave-driven scanning tunnelling spectroscopy on the ångström scale paves the way for ultrafast measurements of wavefunction dynamics in atomically precise nanostructures and future optoelectronic devices based on locally tailored electronic properties.

Design and Implementation of Navi-guide Device

The device designed is a navigation guide which will help the user with turn by turn directions. At the present time, use of smartphones for the navigation support has been increased and this in turn leads to risk of accident. The navi-guide device displays step by step direction on the OLED screen. This reduces the chances of mishaps and the increases the user focus. The navi-guide app has been developed for better user interface. The rider will have to just connect his phone to the device via bluetooth can safely reach his destination without any distractions with the aid of this device.

Design and Implementation of Navi-guide Device

The device designed is a navigation guide which will help the user with turn by turn directions. At the present time, use of smartphones for the navigation support has been increased and this in turn leads to risk of accident. The navi-guide device displays step by step direction on the OLED screen. This reduces the chances of mishaps and the increases the user focus. The navi-guide app has been developed for better user interface. The rider will have to just connect his phone to the device via bluetooth can safely reach his destination without any distractions with the aid of this device.

Efficacy of elastodontic devices in overjet and overbite reduction assessed by computer-aid evaluation

Background This study aimed to verify the efficacy of two elastodontic devices in overjet (OJ) and overbite (OB) reduction during treatment with the Equilibrator Series II (Eptamed) and Occlus-o-Guide (Sweden & Martina) devices. Method Sixty patients aged 7–15 years were enrolled in the study, and were divided into test and control groups. The test group included 30 patients (14 males, 16 females; mean age, 10.66 ± 2.12 years) treated with the EQ (Equilibrator) Series II. The control group included 30 patients (15 males, 15 females; mean age, 10.76 ± 2.52 years) treated with the Occlus-o-Guide. The two groups exhibited the same orthodontic features. The orthodontic criteria were: skeletal and dental class II malocclusion (divisions 1 and 2); and the presence of OJ and OB. Evaluation of OJ and OB was performed at two timepoints: T0 (before starting therapy) and T1 (after 1 year). Results At T0, OJ and OB were similar for the two groups; however, at T1, both OJ and OB were significantly lower with the Eptamed device compared to the Occlus-o-Guide device (p = 0.0019). Conclusions Elastodontic devices improve orthodontic outcomes by aiding orthodontic patient management, diagnosis, and treatment planning, reducing the risk relapse acting on the whole organism and the rehabilitation of the tongue.

Investigations of a vertical axis wind turbine with frontal cylindrical guide vane unit

The paper presents the results of an experimental study of a vertical wind turbine type Darrieus with frontal cylindrical guide vane unit. The main goal of the research is to analyze the influence of the geometry of a classical cylindrical guide vane unit on the active and passive zone of the wind turbine. The aerodynamic scheme is synthesized by a classic runner and frontal cylindrical guide vanes. Three different guiding devices of a model vertical wind turbine with frontally located guide vanes have been studied. Their influence on the characteristics of the turbine has been examined. The reasons of the differences in the characteristics of the three studied variants of the guiding devices are clarified by numerical study of the flow through the blade cascades of the guide vanes and the runner. The results of the study shows what is the reason for the positive effect of the cylindrical vane guide device on the wind turbine’s runner.

Reconfigurable Embedded Devices Using Reinforcement Learning to Develop Action Policies

The size of sensor networks supporting smart cities is ever increasing. Sensor network resiliency becomes vital for critical networks such as emergency response and waste water treatment. One approach is to engineer “self-aware” sensors that can proactively change their component composition in response to changes in work load when critical devices fail. By extension, these devices could anticipate their own termination, such as battery depletion, and offload current tasks onto connected devices. These neighboring devices can then reconfigure themselves to process these tasks, thus avoiding catastrophic network failure. In this article, we compare and contrast two types of self-aware sensors. One set uses Q-learning to develop a policy that guides device reaction to various environmental stimuli, whereas the others use a set of shallow neural networks to select an appropriate reaction. The novelty lies in the use of field programmable gate arrays embedded on the sensors that take into account internal system state, configuration, and learned state-action pairs, which guide device decisions to meet system demands. Experiments show that even relatively simple reward functions develop both Q-learning policies and shallow neural networks that yield positive device behaviors in dynamic environments.