Shaka

Make the shell script executable

The script should begin with the shebang (e.g. #!/bin/bash).

Treat the shell script as the argument of sh

In this case, the shebang is not necessary.

Zathura is a light PDF viewer, with Vi/Vim-like keybindings. It always reloads and refreshes documents automatically. In this sense, it is naturally capable of providing real time preview of a PDF file, e.g., produced by LaTeX. Additionally, it has the option of enabling inverse search based on synctex.

As is well-known, shell is an interface provided by the Unix/Linux operation systems (OS) to subscribers whereby a user can interact with the kernel of the OS efficiently and conveniently.

In fact, there are already a variety of shells, e.g., bash, csh, tcsh, zsh, etc. This post just presented a brief introduction to zsh.

Zsh is indeed a powerful shell. Perhaps this is just the reason why it is termed "shell terminator", as letter 'Z' is the letter terminator, the last one in the alphabeta.

Targetting for HARQ acknowledgement and scheduling request, similar to LTE, uplink control information (UCI) is transmitted on physical uplink control channel (PUCCH) or physical uplink shared channel (PUSCH).

Simultaneous transmission of PUCCH and PUSCH is not supported in release 15, but UCI can be pigged-back on PUSCH, i.e., UCI is multiplexed with data and transmitted on PUSCH.

In carrier aggregation (CA) case, UCI is only transmitted on the primary cell (PCell), to support asymmetric CA, i.e., different number of carriers in the downlink and uplink. To avoid overloading, PUCCH's can be divided into 2 groups. The feedback relating to the 1st group is transmitted in the uplink of the PCell, while the feedback corresponding to the 2nd group is delivered in the uplink of the primary second cell (PSCell).

For PUCCH, only a single antenna port is specified. Given a UE equipped with multiple antennas, how to make use of the antenna array is a UE implementation related issue.

Tensorflow is a deep learning library, which provides two programming interfaces, C++ and Python. Moreover, The Python API integrates very well with numpy. In many places, Tensorflow tensors can be interchanged with numpy ndarrays.