Imaging Neural Activity in the Primary Somatosensory Cortex Using Thy1-GCaMP6s Transgenic Mice

The mammalian brain exhibits marked symmetry across the sagittal plane. However, detailed description of neural dynamics in symmetric brain regions in adult mammalian animals remains elusive. In this study, we describe an experimental procedure for measuring calcium dynamics through dual optical windows above bilateral primary somatosensory corticies (S1) in Thy1-GCaMP6s transgenic mice using 2-photon (2P) microscopy. This method enables recordings and quantifications of neural activity in bilateral mouse brain regions one at a time in the same experiment for a prolonged period in vivo. Key aspects of this method, which can be completed within an hour, include minimally invasive surgery procedures for creating dual optical windows, and the use of 2P imaging. Although we only demonstrate the technique in the S1 area, the method can be applied to other regions of the living brain facilitating the elucidation of structural and functional complexities of brain neural networks

An SMS Based Querying System for Mobile Learning

Mobile phone is the most widely used mobile device. Every mobile phone user can conveniently communicate with each other through SMS (Short Message Service) text messages at very low price. It is so commonly used that, in some countries like China, an SMS culture has emerged. Although there are some SMS based applications in m-Learning, most of them are only for administrative purposes, like delivering messages to students as reminders or alerts for some learning activities. In fact, text messages of SMS can effectively convey small pieces of materials related to learning processes, like course notes, items of glossary, small pieces of explanation and some links to detailed information etc. In this paper, we introduce a system for querying information and knowledge by the use of SMS in a mobile learning environment. The proposed system consists of a GSM Module (GSMM), a Dialogue Control Module (DCM), a Querying Processing Module (QPM) and a Knowledge Base (KB). GSMM includes a micro-controller and a GSM communication device with a SIM card in it. It processes the users' messages according to our defined protocol and acts as the interface between the mobile infrastructure and the rest of the system. DCM handles the content of the requesting messages and produces suitable querying tasks for QPM, which in turn searches and matches information from KB or Internet to produce suitable answering messages for the users according to their requesting messages. To help the system better understand the content of messages, natural language processing and theme recognition techniques are applied to message processing modules. Several scenarios about course notes and glossary querying are illustrated in this paper.School of Computing and Information Systems, Athabasca University Information Science and Engineering, Central South University, Changsha, Hunan 410083, Chin

Segatron: Segment-Aware Transformer for Language Modeling and Understanding

Transformers are powerful for sequence modeling. Nearly all state-of-the-art language models and pre-trained language models are based on the Transformer architecture. However, it distinguishes sequential tokens only with the token position index. We hypothesize that better contextual representations can be generated from the Transformer with richer positional information. To verify this, we propose a segment-aware Transformer (Segatron), by replacing the original token position encoding with a combined position encoding of paragraph, sentence, and token. We first introduce the segment-aware mechanism to Transformer-XL, which is a popular Transformer-based language model with memory extension and relative position encoding. We find that our method can further improve the Transformer-XL base model and large model, achieving 17.1 perplexity on the WikiText-103 dataset. We further investigate the pre-training masked language modeling task with Segatron. Experimental results show that BERT pre-trained with Segatron (SegaBERT) can outperform BERT with vanilla Transformer on various NLP tasks, and outperforms RoBERTa on zero-shot sentence representation learning.Comment: Accepted by AAAI 202

Diaqua­(5-carb­oxy­benzene-1,3-dicarboxyl­ato-κ2 O 1,O 1′)(6,6′-dimethyl-2,2′-bipyridine-κ2 N,N′)nickel(II) hepta­hydrate

In the title compound, [Ni(C9H4O6)(C12H12N2)(H2O)2]·7H2O, the NiII atom is six-coordinated by two O atoms from a chelating carboxyl­ate group of a 5-carb­oxy­benzene-1,3-dicarboxyl­ate ligand, two O atoms of two water mol­ecules and two N atoms from a 6,6′-dimethyl-2,2′-bipyridine ligand in a distorted octa­hedral geometry. The compound exhibits a three-dimensional supra­molecular structure composed of the complex mol­ecules and lattice water mol­ecules, which are linked together by inter­molecular O—H⋯O hydrogen bonds and partly overlapping π–π inter­actions between the pyridine and benzene rings [centroid–centroid distances = 3.922 (2) and 3.921 (2) Å]. One of the lattice water mol­ecules is disordered over two positions in an occupancy ratio of 0.521 (6):0.479 (6)

Poly[[hexa­aqua­bis­(μ3-benzene-1,3,5-tricarboxyl­ato-κ3 O 1:O 3:O 5)bis­(5,5′-dimethyl-2,2′-bipyridine-κ2 N,N′)trizinc] hexa­hydrate]

In the title compound, {[Zn3(C9H3O6)2(C12H12N2)2(H2O)6]·6H2O}n, one ZnII atom, lying on an inversion center, is six-coordinated by two O atoms from two benzene-1,3,5-tricarboxyl­ate (btc) ligands and four water mol­ecules in a distorted octa­hedral geometry. The other ZnII atom is five-coordinated by two N atoms from a 5,5′-dimethyl-2,2′-bipyridine (dmbpy) ligand, two O atoms from two btc ligands and one water mol­ecule in a distorted trigonal–bipyramidal geometry. The compound features a one-dimensional ladder structure, with windows of ca 10.245 (1) × 15.446 (2) Å. The ladders are linked together by inter­molecular O—H⋯O hydrogen bonds and π–π inter­actions between the benzene rings and between the pyridine rings [centroid-to-centroid distances 3.858 (2) and 3.911 (3) Å, respectively] to form a three-dimensional supra­molecular structure. One of the lattice water molecules is disordered over two positions in a 0.592:0.408 ratio