A low complexity multi-layered space frequency coding detection algorithm for MIMO-OFDM

A low complexity multi-layered space frequency OFDM (MLSF-OFDM) coding scheme is presented with the proposed two detection algorithms, fast QR decomposition detection algorithm or denoted as FAST-QR and enhanced FAST-QR (E-FAST-QR). Both algorithms not only reduce the implementation complexity of QR decomposition but also show a good performance in terms of bit error rate (BER). Hence, the proposed detection algorithms can be used to maintain guaranteed quality of service (QoS) in MIMO-OFDM system

Advances of Machine Learning in Materials Science: Ideas and Techniques

In this big data era, the use of large dataset in conjunction with machine learning (ML) has been increasingly popular in both industry and academia. In recent times, the field of materials science is also undergoing a big data revolution, with large database and repositories appearing everywhere. Traditionally, materials science is a trial-and-error field, in both the computational and experimental departments. With the advent of machine learning-based techniques, there has been a paradigm shift: materials can now be screened quickly using ML models and even generated based on materials with similar properties; ML has also quietly infiltrated many sub-disciplinary under materials science. However, ML remains relatively new to the field and is expanding its wing quickly. There are a plethora of readily-available big data architectures and abundance of ML models and software; The call to integrate all these elements in a comprehensive research procedure is becoming an important direction of material science research. In this review, we attempt to provide an introduction and reference of ML to materials scientists, covering as much as possible the commonly used methods and applications, and discussing the future possibilities.Comment: 80 pages; 22 figures. To be published in Frontiers of Physics, 18, xxxxx, (2023

Implementation of convolutional encoder and Viterbi decoder using VHDL

This work focuses on the realization of convolutional encoder and adaptive Viterbi decoder (AVD) with a constraint length, K of 3 and a code rate (k/n) of 1/2 using field-programmable gate array (FPGA) technology. This paper presents a 4-state, radix-2, hard decision AVD which has the ability to decode adaptively through different traceback length (TL). The performance of the implemented AVD is analyzed by using ISE 9.2 and MATLAB simulations. The AVD is targeted to a Xilinx XCV300PQ240-4 FPGA device for hardware realization. The decoder parameter TL can be reconfigured via the implementation of AVD, in accordance with the changing channel noise characteristics of the threshold signal-to-noise ratio (SNR), which is 6 dB. The synthesis results show that the reconfiguration parameter TL of 4 and 15 of AVD implementation has significant difference (>20% improvement) in FPGA device utilization. The results also show that the use of reconfiguration leads to a 28% area occupancy of slice usage improvement over a TL of 15 model compared to a TL of 4 model with tolerable loss of decode accuracy, in accordance with the bit error rate (BER) for real-time voice and video

Dynamic transmit antenna shuffling scheme for MIMO wireless communication systems

Two novel dynamic transmit antenna shuffling schemes, namely ‘Optimal’ and ‘Max STBC’, are presented in order to reduce the interference in V-BLAST/STBC scheme. These antenna shuffling schemes with the channel state information (CSI) from the receiver, which significantly improves performance of the MIMO system in Rayleigh flat-fading channels by selecting the appropriate antenna shuffling pattern, have been compared with a few other related schemes in terms of BER and system capacity. The ‘Optimal’ antenna shuffling scheme improves the BER performance significantly with a gain of 2 dB at BER of 10–3 compared to all other schemes, while the ‘Max STBC’ antenna shuffling scheme enhances the V-BLAST/STBC system capacity by 4%

GPS based child care system using RSSI technique

In today's society, missing child cases increases rapidly. Child care is a critical issue in solving this epidemic. Various systems and methods have been implemented in solving this crisis. In this paper, the global position system (GPS) based child care system is proposed to solve this problem. This system consists of two nodes; child and parent nodes, each carried by the child and parent respectively. The child node consists of a simple circuit that has a Bluetooth module and a GPS receiver. The parent node is a mobile device that has Bluetooth connection. The GPS technology helps to determine the exact position of the child. The parent node receives the location of the child and displays the information on a designed map using a GUI program that is embedded into the mobile device. Besides the location, the distance between parent and child can also be determined using Bluetooth connection. A data from received signal strength indicator (RSSI) is extracted out from the Bluetooth connection and is used as vital information in determining the distance between parent and child. An alert is triggered when the distance between the parent and child is far apart for a certain range. The proposed system proves to be useful as a locator that could locate missing and wandering child for the parents

HNF4A Haploinsufficiency in MODY1 Abrogates Liver and Pancreas Differentiation from Patient-Derived Induced Pluripotent Stem Cells.

Maturity-onset diabetes of the young 1 (MODY1) is a monogenic diabetes condition caused by heterozygous HNF4A mutations. We investigate how HNF4A haploinsufficiency from a MODY1/HNF4A mutation influences the development of foregut-derived liver and pancreatic cells through differentiation of human induced pluripotent stem cells from a MODY1 family down the foregut lineage. In MODY1-derived hepatopancreatic progenitors, which expressed reduced HNF4A levels and mislocalized HNF4A, foregut genes were downregulated, whereas hindgut-specifying HOX genes were upregulated. MODY1-derived hepatocyte-like cells were found to exhibit altered morphology. Hepatic and β cell gene signatures were also perturbed in MODY1-derived hepatocyte-like and β-like cells, respectively. As mutant HNF4A (p.Ile271fs) did not undergo complete nonsense-mediated decay or exert dominant negativity, HNF4A-mediated loss of function is likely due to impaired transcriptional activation of target genes. Our results suggest that in MODY1, liver and pancreas development is perturbed early on, contributing to altered hepatic proteins and β cell defects in patients

HNF4A haploinsufficiency in MODY1 abrogates liver and pancreas differentiation from patient-derived induced pluripotent stem cells

Maturity-onset diabetes of the young 1 (MODY1) is a monogenic diabetes condition caused by heterozygous HNF4A mutations. We investigate how HNF4A haploinsufficiency from a MODY1/HNF4A mutation influences the development of foregut-derived liver and pancreatic cells through differentiation of human induced pluripotent stem cells from a MODY1 family down the foregut lineage. In MODY1-derived hepatopancreatic progenitors, which expressed reduced HNF4A levels and mislocalized HNF4A, foregut genes were downregulated, whereas hindgut-specifying HOX genes were upregulated. MODY1-derived hepatocyte-like cells were found to exhibit altered morphology. Hepatic and β cell gene signatures were also perturbed in MODY1-derived hepatocyte-like and β-like cells, respectively. As mutant HNF4A (p.Ile271fs) did not undergo complete nonsense-mediated decay or exert dominant negativity, HNF4A-mediated loss of function is likely due to impaired transcriptional activation of target genes. Our results suggest that in MODY1, liver and pancreas development is perturbed early on, contributing to altered hepatic proteins and β cell defects in patients.publishedVersio

Stroke Factors Associated with Thrombolysis Use in Hospitals in Singapore and US: A Cross-Registry Comparative Study

Background and Objectives: This paper aims to describe and compare the characteristics of 2 stroke populations in Singapore and in St. Louis, USA, and to document thrombolysis rates and contrast factors associated with its uptake in both populations. Methods: The stroke populations described were from the Singapore Stroke Registry (SSR) in -Singapore and the Cognitive Rehabilitation Research Group Stroke Registry (CRRGSR) in St. Louis, MO, USA. The registries were compared in terms of demographics and stroke risk factor history. Logistic regression was used to determine factors associated with thrombolysis uptake. Results: A total of 39,323 and 8,106 episodes were recorded in SSR and CRRGSR, respectively, from 2005 to 2012. Compared to CRRGSR, patients in SSR were older, male, and from the ethnic majority. Thrombolysis rates in SSR and CRRGSR were 2.5 and 8.2%, respectively, for the study period. History of ischemic heart disease or atrial fibrillation was associated with increased uptake in both populations, while history of stroke was associated with lower uptake. For SSR, younger age and males were associated with increased uptake, while having a history of smoking or diabetes was associated with decreased uptake. For CRRGSR, ethnic minority status was associated with decreased uptake. Conclusions: The comparison of stroke populations in Singapore and St Louis revealed distinct differences in clinicodemographics of the 2 groups. Thrombolysis uptake was driven by nonethnicity demographics in Singapore. Ethnicity was the only demographic driver of uptake in the CRRGSR population, highlighting the need to target ethnic minorities in increasing access to thrombolysis