The Structure and Compression of Medical Compression Stockings

This paper lays out standards of compression stockings and their classification into classes. The analysis of knitted fabric structure parameters, elongation and compression of moderate- and high-compression stockings was conducted. Stocking compression on specific parts of the stocking leg was measured on three sizes of a wooden leg model. For moderate-compression stockings, compression above the ankle was 32 hPa. For high-compression stockings, compression above the ankle was 60 hPa. Both groups of the analyzed compression stockings were made on modern one-cylinder hosiery automats. The legs of the stockings were made in single inlaid jersey 1 + 1. Both yarns were elastane covered. The finer yarn formed loops and its knitting into a course was significantly larger than in the other yarn, which was much coarser and does not form loops but “lay the weft in a bent way”. The smallest elongation of knitted fabric was above the ankle, where the highest compression was achieved, while the largest elongation was under the crotch, where the stocking leg exerted the smallest compression on the surface. The leg of the compression stocking acted as a casing that imposed compression on the leg and often reinforced it to be able to sustain compression loads.

Data-Driven and Model-Driven Joint Detection Algorithm for Faster-Than-Nyquist Signaling in Multipath Channels

In recent years, Faster-than-Nyquist (FTN) transmission has been regarded as one of the key technologies for future 6G due to its advantages in high spectrum efficiency. However, as a price to improve the spectrum efficiency, the FTN system introduces inter-symbol interference (ISI) at the transmitting end, whicheads to a serious deterioration in the performance of traditional receiving algorithms under high compression rates and harsh channel environments. The data-driven detection algorithm has performance advantages for the detection of high compression rate FTN signaling, but the current related work is mainly focused on the application in the Additive White Gaussian Noise (AWGN) channel. In this article, for FTN signaling in multipath channels, a data and model-driven joint detection algorithm, i.e., DMD-JD algorithm is proposed. This algorithm first uses the traditional MMSE or ZFinear equalizer to complete the channel equalization, and then processes the serious ISI introduced by FTN through the deepearning network based on CNN or LSTM, thereby effectively avoiding the problem of insufficient generalization of the deepearning algorithm in different channel scenarios. The simulation results show that in multipath channels, the performance of the proposed DMD-JD algorithm is better than that of purely model-based or data-driven algorithms; in addition, the deepearning network trained based on a single channel model can be well adapted to FTN signal detection under other channel models, thereby improving the engineering practicability of the FTN signal detection algorithm based on deepearning.

Study on the Compression Effect of Clothing on the Physiological Response of the Athlete

The study aimed to analyze whether the high compression of unique, tight-fitting sportswear influences the clothing physiology comfort of the athlete. Three specific sportswear with different compression were tested on four subjects while they were running on a treadmill with increasing intensity. The compression effect of the sportswear on the body of the test persons, the temperature distribution of the subjects, and the intensity of their perspiration during running were determined. The results indicate that the compression effect exerted by the garments significantly influences the clothing physiology comfort of the athlete; a higher compression load leads to more intense sweating and higher skin temperature.

The Role of Turbomachinery in Enabling the Hydrogen Economy

The purpose of this paper is to present the various technological solutions optimized for the use of hydrogen, in transport, distribution, storage and utilization, analyzing their criticalities and advantages. Hydrogen compression is a fundamental step in the transportation and storage segments and continuous improvement are required. The greatest technological challenges are certainly the high pressures required for the various fields of use, the need to maintain a clean gas and to use materials that are not subject to embrittlement. The choice between the different compression technologies is based on the need for pressures and flow rates; in the case of high flow rates and low compression ratios a centrifugal compressor is preferable, while for low flow rates and high compression ratios the choice goes to piston compressors. To prevent gas contamination, dry reciprocating compressor are preferred because they allow to avoid an oil separator filter on the discharge. Current technology of reciprocating compressors allows to compress hydrogen up to 300 bar with lubricated machines, while with dry technology it is possible to reach up to 250 bar. A second criticality on reciprocating compressors is maintenance: the parts subject to wear need to be serviced every 8000 hour of operation. The use of innovative materials will increase the maintenance intervals reaching higher pressures without lubrication. To increase the pressure ratio with centrifugal compressor, it's needed to increase the rotating speed, therefore the peripheral speed, with materials suitable for H2, stages get high compression to reduce the number of compressor bodies. If the process conditions require high delivery pressures combined with large flow rates, a solution of centrifugal compressors alone would be able to manage the flow rate but not the required delivery pressure. On the other hand, the use of reciprocating compressors would require a considerable number of units. In this case, therefore, the optimal solution is to combine the two technologies, centrifugal and pistons, using the best features. A case study in which the superior performances of the hybrid solution in terms of total cost of ownership will be described and compared with traditional single technology compression train

Novel Data Compression Algorithm for Transmission Line Condition Monitoring

For the problem of data accumulation caused by massive sensor data in transmission line condition monitoring system, this paper analyzes the type and amount of data in the transmission line sensor network, compares the compression algorithms of wireless sensor network data at home and abroad, and proposes an efficient lossless compression algorithm suitable for sensor data in transmission line linear heterogeneous networks. The algorithm combines the wavelet compression algorithm and the neighborhood index sequence algorithm. It displays a fast operation speed and requires a small amount of calculation. It is suitable for battery powered wireless sensor network nodes. By combining wavelet correlation analysis and neighborhood index sequence coding, the compression algorithm proposed in this paper can achieve a high compression rate, has strong robustness to packet loss, has high compression performance, and can help to reduce network load and the packet loss rate. Simulation results show that the proposed method achieves a high compression rate in the compression of the transmission line parameter dataset, is superior to the existing data compression algorithms, and is suitable for the compression and transmission of transmission line condition monitoring data.

Microstructure and Phase Formation of Novel Al80Mg5Sn5Zn5X5 Light-Weight Complex Concentrated Aluminum Alloys

In this work, three novel complex concentrated aluminum alloys were developed. To investigate the unexplored region of the multicomponent phase diagrams, thermo-physical parameters and the CALPHAD method were used to understand the phase formation of the Al80Mg5Sn5Zn5Ni5, Al80Mg5Sn5Zn5Mn5, and Al80Mg5Sn5Zn5Ti5 alloys. The ingots of the alloys were manufactured by a gravity permanent mold casting process, avoiding the use of expensive, dangerous, or scarce alloying elements. The microstructural evolution as a function of the variable element (Ni, Mn, or Ti) was studied by means of different microstructural characterization techniques. The hardness and compressive strength of the as-cast alloys at room temperature were studied and correlated with the previously characterized microstructures. All the alloys showed multiphase microstructures with major α-Al dendritic matrix reinforced with secondary phases. In terms of mechanical properties, the developed alloys exhibited a high compression yield strength up to 420 MPa, high compression fracture strength up to 563 MPa, and elongation greater than 12%.