Towards long-tailed, multi-label disease classification from chest X-ray: Overview of the CXR-LT challenge

Many real-world image recognition problems, such as diagnostic medical imaging exams, are "long-tailed" \unicode{x2013} there are a few common findings followed by many more relatively rare conditions. In chest radiography, diagnosis is both a long-tailed and multi-label problem, as patients often present with multiple findings simultaneously. While researchers have begun to study the problem of long-tailed learning in medical image recognition, few have studied the interaction of label imbalance and label co-occurrence posed by long-tailed, multi-label disease classification. To engage with the research community on this emerging topic, we conducted an open challenge, CXR-LT, on long-tailed, multi-label thorax disease classification from chest X-rays (CXRs). We publicly release a large-scale benchmark dataset of over 350,000 CXRs, each labeled with at least one of 26 clinical findings following a long-tailed distribution. We synthesize common themes of top-performing solutions, providing practical recommendations for long-tailed, multi-label medical image classification. Finally, we use these insights to propose a path forward involving vision-language foundation models for few- and zero-shot disease classification

Towards Energy Efficient Home Automation: A Deep Learning Approach

Home Automation Systems (HAS) attracted much attention during the last decade due to the developments in new wireless technologies, such as Bluetooth 4.0, 5G, WiFi 6, etc. In order to enable automation as a service in smart homes, a number of challenges must be addressed, such as fulfilling the electrical energy demands, scheduling the operational time of appliances, applying machine learning models in real-time, optimal human appliances interaction, etc. In order to address the aforementioned challenges and control the wastage of energy due to the lifestyle of the home users, we propose a system for automatically controlling the energy consumption by employing machine and deep learning techniques to smart home networks. The proposed system works in three phases, (1) feature extraction and classification based on 1-dimensional Deep Convolutional Neural Network (1D-DCNN) which extract important energy patterns from the historic energy data, (2) a load forecasting system based on Long-short Term Memory (LSTM) is proposed to forecast the load based on the extracted features in phase 1 and (3) a scheduling algorithm based on the forecasted data obtained from phase 2 is designed to schedule the operational time of smart home appliances. The proposed scheme efficiently automates the smart home appliances to consume less energy while adapting to the lifestyle of smart home users. The validation of the proposed scheme is tested with a number of simulation scenarios incorporating datasets from authentic data sources. The simulation results show that the proposed smart home automation system can be a game-changer in fulfilling the energy demands of the home users without installing renewable and other energy sources in the future

Cell-free massive multiple-input multiple-output challenges and opportunities: A survey

Cell-free (CF) massive multiple-input multiple-output (mMIMO) system is a state-of-the-art emerging technology targeted towards beyond fifth-generation (B5G) and sixth-generation (6G) communication networks. This network pertains to a dense deployment of access points (APs) dispersed over a large geographical area to serve a small number of users at the same frequency and time resources. The CF-mMIMO architecture offers resilient connectivity, interference management, power efficiency, high throughput, and macrodiversity. Moreover, this communication technique eliminates cell boundaries and facilitates the users by introducing overlapping regions, thus providing consistent quality of service (QoS) throughout the region. However, the complexity of CF-mMIMO systems increases considerably when numerous APs are dispersed over a large geographical area. Therefore, several studies have been carried out to determine the optimal solution with minimum complexity of the CF-mMIMO system. Herein, a thorough investigation of the literature on the CF-mMIMO system is presented, considering all aspects from architecture to applications. The study provides a detailed survey of CF-mMIMO architecture, fronthaul, and backhaul, as well as the challenges associated with them; deployment methodologies and challenges for practical implementation of CF-mMIMO systems are also discussed. Furthermore, we reviewed the impact of transmitter and receiver antennae on the capacity of CF-mMIMO enabled with millimeter wave (mmWave). The numerical findings indicate that the higher degree of freedom required for spatial multiplexing allows multiantenna users to surpass single-antenna users in terms of capacity. This study holds significance owing to the thorough examination of the CF-mMIMO system model, channel estimation, scalability problems, working algorithms, communication protocol, deep learning-based solutions, linkage to B5G and 6G, and key challenges. Moreover, this study presents a detailed discussion and research survey on the system model, deployment issues, deep learning, and potential applications of the CF-mMIMO system

DFT computational investigation of tuning the electron donating ability in metal-free organic dyes featuring a thienylethynyl spacer for dye sensitized solar cells

The recent improvements in metal-free organic dye-sensitized solar cells (DSSCs) have been attributed to the ability to tune the optical and electronic properties through various structural modifications. Within the donor-π-conjugated spacer-acceptor (D-π-A) architecture, the electron-donating and accepting strengths have been proven to be major control variables for increasing the energy conversion efficiency. In the present study, a series of metal-free organic D-π-A dyes for DSSCs were designed and investigated. In particular, the electron donating strength was modulated by adding electron donating groups to the donor side. The HOMO energy increased with a gradual increase in donor strength which was verified by an investigation of the bond distances between the nitrogen and carbon atom of phenyl ring connected with π-conjugated spacer. The net electron transfer from the donor to acceptor, calculated from natural bond orbital (NBO) analysis, also showed quantitative correlation with the bond distances. Finally, the absorption peak shifted to a longer wavelength with the increase of donor strength as well as π-conjugated spacer. Detailed analysis of the results supported that all properties investigated has a strong correlation with the bond distance between the nitrogen and the carbon atom in the phenyl ring attached to the π-conjugated spacer. Based on this apparent correlation, this bond distance from ground-state DFT calculations may be used as a descriptor for the high throughput screening of DSSC dyes instead of using computationally expensive TDDFT calculations. © 2016 Elsevier B.V1661sciescopu

Avoiding Spurious Retransmission over Flooding-Based Routing Protocol for Underwater Sensor Networks

In underwater wireless sensor networks (UWSN), acoustic communication naturally introduces challenges such as long propagation delay and high packet loss. The flooding-based routing protocol can address these challenges with its multipath characteristics. As in flooding-based routing, due to multipath propagation mechanism, not only DATA but also ACK messages are transmitted through multiple routes however still some packet loss will degrade the performance. So, to provide high reliability of message delivery, an efficient retransmission mechanism is inevitable. Though, if the network uses conventional transport layer protocol such as TCP, it will suffer a spurious retransmission problem as TCP was originally not designed for the multipath environment. In this paper, we propose route discrimination for flooding-based routing to reduce spurious retransmission in UWSN to solve the limitation. The notion of ACK copies waiting time (ACWT) is utilized which is selectively updated based on the similarity of paths of transmission of ACK message copies. We also improved our previous solution that lacks flexibility to cope with dynamic link error characteristics. Through evaluation, we verified that our new scheme achieves the performance improvements of 14%~84% in terms of retransmission ratio compared to the previous research

Density Functional Theory Study of Silolodithiophene Thiophenepyrrolopyrroledione-based Small Molecules: The Effect of Alkyl Side Chain Length in Electron Donor Materials

Push-pull small molecules are promising electron-donor materials for organic solar cells. Thus, precise prediction of their electronic structures is of paramount importance to control the optical and electrical properties of the solar cells. Various types of alkyl chains are usually introduced to increase solubility and modify the morphology of the resulting molecular films. Here, using density functional theory (DFT) and time-dependent DFT (TD-DFT), we report the precise effect of increasing the length of the alkyl chain on the electronic structure of an electron donor molecule 6,60-((4,4-dialkyl-4H-silolo[3,2-b: 4,5-b']-dithiophene-2,6-diyl)bis(thiophene- 5,2-diyl)) bis(2,5-alkyl-3-(thiophen-2-yl)-2,5-dihydropyrrolo[3,4-c] pyrrole-1,4-dione) (DTS1TDPP). Alkyl groups were attached to the bridging position (silicon atom) of the fused rings and nitrogen atom of the pyrrolopyrroledione groups. We demonstrate that the alkyl groups do not perturb the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) energy levels, pi-delocalized backbone structure, and UV-Vis absorption spectrum when they are placed at the least steric effect positions

Effects of dynamic 3D-volume of side chains in conjugated polymers on nano-scale morphology and solar cell properties

We have synthesized a series of benzo[1,2-b:4,5-b']-dithiophene (BDT)-co-thieno[3,4-b]thiophene (TT) based polymers with various alkyl side chains and bridging-atom on their TT units and studied the effects of the variation in the effective van der Waals volumes (eVol) of the side chains on the photovoltaic properties of the associated bulk heterojunction (BHJ) solar cells. eVol was found to be correlated with the degree of phase separation in the BHJ film, which affects the area of the polymer-PC71BM interface and the charge mobility. The polymer has a 2-ethylhexyl group that results in a relatively optimal BHJ film morphology, with sufficient polymer-PC71BM interfacial area for efficient charge generation and minimal charge mobility loss upon BHJ film formation. As a result, the solar cell device (2-ethylhexyl polymer) exhibits the highest power conversion efficiency of 8.25% because its short-circuit current density value (16.24 mA/cm(2)) and fill factor (0.674) are the highest of the synthesized polymers

Efficacy and Safety of Monopolar Radiofrequency for Tightening the Skin of Aged Faces

Background: Monopolar radiofrequency (RF) has emerged as a promising modality for tightening the skin of aged faces. Although many studies have assessed the efficacy of monopolar RF via the clinical evaluation of photographs, few have examined the long-term effectiveness and safety of this therapy using various skin testing devices. Methods: Twenty women with aged faces participated in this study. After a single monopolar RF treatment, three blinded dermatologists who were not involved in the treatment evaluated its clinical efficacy and safety after 4, 12, and 24 weeks. Skin firmness, fine wrinkles, skin pores, and skin tone were also measured using an indentometer (Courage+Khazaka Electronic GmbH, Köln, Germany) and a facial aging measurement device (Mark-Vu; PSI Plus, Suwon-si, Republic of Korea). Results: Skin laxity in the jowls and nasolabial folds showed significant improvement 12 weeks after the single monopolar RF treatment when evaluated by dermatologists, and this improvement lasted 24 weeks (p p p < 0.01). Although there was a gradual increase in improvement in skin pores, fine wrinkles, and skin tones, there were no statistical differences compared to the baseline. No patients experienced pain during the treatment, and no burns, skin breakdown, or scarring occurred after treatment. Conclusions: A single monopolar RF treatment is effective for females with aged face. A significant improvement in the jowls and nasolabial folds and facial skin firmness was observed between the 4- and 24-week follow-ups without adverse effects

Enzymatic formation of carbohydrate rings catalyzed by single-walled carbon nanotubes

Macrocyclic carbohydrate rings were formed via enzymatic reactions around single-walled carbon nanotubes (SWNTs) as a catalyst. Cyclodextrin glucanotransferase, starch substrate and SWNTs were reacted in buffer solution to yield cyclodextrin (CD) rings wrapped around individual SWNTs. Atomic force microscopy showed the resulting complexes to be rings of 12-50 nm in diameter, which were highly soluble and dispersed in aqueous solution. They were further characterized by Raman and Fourier transform infrared spectroscopy and molecular simulation using density functional theory calculation. In the absence of SWNT, hydrogen bonding between glucose units determines the structure of maltose (the precursor of CD) and produces the curvature along the glucose chain. Wrapping SWNT along the short axis was preferred with curvature in the presence of SWNTs and with the hydrophobic interactions between the SWNTs and CD molecules. This synthetic approach may be useful for the functionalization of carbon nanotubes for development of nanostructures. (c) Springer-Verlag Berlin Heidelberg 2016101sciescopu