Reconfigurable devices offer the ability to program electronic circuits on demand. In this work, we demonstrated on-demand creation of artificial neurons, synapses, and memory capacitors in ...post-fabricated perovskite NdNiO
devices that can be simply reconfigured for a specific purpose by single-shot electric pulses. The sensitivity of electronic properties of perovskite nickelates to the local distribution of hydrogen ions enabled these results. With experimental data from our memory capacitors, simulation results of a reservoir computing framework showed excellent performance for tasks such as digit recognition and classification of electrocardiogram heartbeat activity. Using our reconfigurable artificial neurons and synapses, simulated dynamic networks outperformed static networks for incremental learning scenarios. The ability to fashion the building blocks of brain-inspired computers on demand opens up new directions in adaptive networks.
Since its rediscovery in the mid-1990s, FOXP3+ regulatory T cells (Tregs) have climbed the rank to become commander-in-chief of the immune system. They possess diverse power and ability to ...orchestrate the immune system in time of inflammation and infection as well as in time of harmony and homeostasis. To be the commander-in-chief, they must be equipped with both offensive and defensive weaponry. This review will focus on the function of transforming growth factor-β (TGF-β) as the sword, the wand, and the shield of Tregs. Functioning as a sword, this review will begin with a discussion of the evidence that supports how Tregs utilize TGF-β to paralyze cell activation and differentiation to suppress immune response. It will next provide evidence on how TGF-β from Tregs acts as a wand to convert naı¨ve T cells into iTregs and Th17 to aid in their combat against inflammation and infection. Lastly, the review will present evidence on the role of TGF-β produced by Tregs in providing a shield to protect and maintain Tregs against apoptosis and destabilization when surrounded by inflammation and constant stimulation. This triadic function of TGF-β empowers Tregs with the responsibility and burden to maintain homeostasis, promote immune tolerance, and regulate host defense against foreign pathogens.
Few treatments for human diseases have received as much investigation in the past 20 years as probiotics. In 2017, English‐language meta‐analyses totaling 52 studies determined the effect of ...probiotics on conditions ranging from necrotizing enterocolitis and colic in infants to constipation, irritable bowel syndrome, and hepatic encephalopathy in adults. The strongest evidence in favor of probiotics lies in the prevention or treatment of 5 disorders: necrotizing enterocolitis, acute infectious diarrhea, acute respiratory tract infections, antibiotic‐associated diarrhea, and infant colic. Probiotic mechanisms of action include the inhibition of bacterial adhesion; enhanced mucosal barrier function; modulation of the innate and adaptive immune systems (including induction of tolerogenic dendritic cells and regulatory T cells); secretion of bioactive metabolites; and regulation of the enteric and central nervous systems. Future research is needed to identify the optimal probiotic and dose for specific diseases, to address whether the addition of prebiotics (to form synbiotics) would enhance activity, and to determine if defined microbial communities would provide benefit exceeding that of single‐species probiotics.
•Conventional separator is coated with a 50PEO-50SiO2 (wt.%) composite layer.•Composite coating increases tensile strength and electrolyte wettability.•Coated separator offers an alternative approach ...for making gel polymer Li/S battery.•Li/S battery takes benefits of gel polymer electrolyte at the expense of capacity.
Gel polymer electrolyte (GPE) and composite gel polymer electrolyte (CGPE) have been widely employed to improve the safety and cycling performance of rechargeable lithium and lithium-ion batteries. In order to determine whether this approach is applicable to lithium/sulfur (Li/S) battery, we examine the effect of CGPE on the cycling and storage performances of Li/S cells by comparing a 50PEO-50SiO2 (wt.%) composite coated separator (C-separator) with a pristine separator (P-separator). Results show that the composite coating significantly enhances the wettability of liquid electrolyte on the separator and that resulting CGPE can tightly glue the separator and electrode together. In comparison with the P-separator, the C-separator offers Li/S cells similar capacity retention and rate capability; however it greatly affects the specific capacity of sulfur. The analysis on the impedance spectrum of a lithium polysulfide (PS) solution reveal that the reduction of sulfur specific capacity is due to the high viscosity of the CGPE and the strong adsorption of SiO2 filler to the PS species, which trap PS species in the separator and hence reduce the utilization of sulfur active material. Therefore, the benefits of the GPE and CGPE to the Li/S batteries can be taken only at the expense of sulfur specific capacity.
Chest radiography is one of the most common types of diagnostic radiology exams, which is critical for screening and diagnosis of many different thoracic diseases. Specialized algorithms have been ...developed to detect several specific pathologies such as lung nodules or lung cancer. However, accurately detecting the presence of multiple diseases from chest X-rays (CXRs) is still a challenging task. This paper presents a supervised multi-label classification framework based on deep convolutional neural networks (CNNs) for predicting the presence of 14 common thoracic diseases and observations. We tackle this problem by training state-of-the-art CNNs that exploit hierarchical dependencies among abnormality labels. We also propose to use the label smoothing technique for a better handling of uncertain samples, which occupy a significant portion of almost every CXR dataset. Our model is trained on over 200,000 CXRs of the recently released CheXpert dataset and achieves a mean area under the curve (AUC) of 0.940 in predicting 5 selected pathologies from the validation set. This is the highest AUC score yet reported to date. The proposed method is also evaluated on the independent test set of the CheXpert competition, which is composed of 500 CXR studies annotated by a panel of 5 experienced radiologists. The performance is on average better than 2.6 out of 3 other individual radiologists with a mean AUC of 0.930, which ranks first on the CheXpert leaderboard at the time of writing this paper.
This research investigates the relationship among product risk, financial risk, security risk, privacy risk, perceived satisfaction, and purchase intention. Validated measurements were identified ...from a literature review. The measurement model and the conceptual model depicting hypothesized relationships were evaluated based on responses from 306 customers using confirmatory factor analysis and structural equation modeling. The results showed that product risk, financial risk, security risk, and privacy risk impacted on perceived satisfaction. Besides, product risk, privacy risk, and perceived satisfaction influenced purchase intentions. Thus, this study focused on the influences of product risk, financial risk, security risk, and privacy risk on their cognitive attitudes toward websites. That means the more consumer perceive security, the more they avoid shopping online. The study is important to show how perceived risk affects online shopping behaviors, and it invites marketers to make necessary adjustments to prevent perceived risks to increase and online shopping to decrease. The findings of this study suggest the creation of a framework on the effect of perceived risk types on online shopping. Managers need to take perceived risks into account when designing their electronic marketing channels. In addition, shopping websites should strengthen their transaction security by appropriately using various available resources and new information technologies.
A class of Pd–Ni–P electrocatalysts are prepared for the ethanol electrooxidation reaction (EOR). X-ray diffraction and transmission electron microscope reveal that the synthesized Pd–Ni–P catalyst ...possesses a more amorphous structure with smaller particle sizes when compared with a Pd–Ni sample without P and a control Pd black (Pd-blk) sample. The Pd–Ni–P catalyst contains double the number of electrocatalytically active sites (12.03%) compared with the Pd–Ni (6.04%) and Pd-blk (5.12%) samples. For the EOR, the Pd–Ni–P catalyst has the lowest onset potential (−0.88 V vs SCE), the most negative peak potential (−0.27 V vs SCE), and the highest EOR activity in 0.1 M KOH solution. Moreover, a 110 mV decrease in overpotential is observed for the EOR on the Pd–Ni–P catalyst compared with the Pd-blk catalyst. A Tafel slope of 60 mV/dec at low polarization potentials (<−0.76 V vs SCE) was obtained for EOR at a Pd–Ni–P-coated electrode with a reaction rate constant of 2.8 × 10–4 cm·S–1·M–1 at −0.3 V vs SCE in KOH media. Finally, we find that the electrooxidation of ethanol on the Pd–Ni–P catalyst undergoes a 4-electron process to acetate.
•EndoCV2020, an endoscopy computer vision challenge addresses eminent problems in endoscopy.•Deep learning methods built to address artefacts and disease categories.•Comprehensive dataset comprising ...multi-center, multi-organ, multi-modal and multi-class.•Over 47,000 annotations and 3440 frames publicly released.•Detection and segmentation algorithms are devised, compared and dissected.•Hypothesis formulated to identify the gaps in current methods.
Display omitted
The Endoscopy Computer Vision Challenge (EndoCV) is a crowd-sourcing initiative to address eminent problems in developing reliable computer aided detection and diagnosis endoscopy systems and suggest a pathway for clinical translation of technologies. Whilst endoscopy is a widely used diagnostic and treatment tool for hollow-organs, there are several core challenges often faced by endoscopists, mainly: 1) presence of multi-class artefacts that hinder their visual interpretation, and 2) difficulty in identifying subtle precancerous precursors and cancer abnormalities. Artefacts often affect the robustness of deep learning methods applied to the gastrointestinal tract organs as they can be confused with tissue of interest. EndoCV2020 challenges are designed to address research questions in these remits. In this paper, we present a summary of methods developed by the top 17 teams and provide an objective comparison of state-of-the-art methods and methods designed by the participants for two sub-challenges: i) artefact detection and segmentation (EAD2020), and ii) disease detection and segmentation (EDD2020). Multi-center, multi-organ, multi-class, and multi-modal clinical endoscopy datasets were compiled for both EAD2020 and EDD2020 sub-challenges. The out-of-sample generalization ability of detection algorithms was also evaluated. Whilst most teams focused on accuracy improvements, only a few methods hold credibility for clinical usability. The best performing teams provided solutions to tackle class imbalance, and variabilities in size, origin, modality and occurrences by exploring data augmentation, data fusion, and optimal class thresholding techniques.
•We propose a multilinear class-specific discriminant analysis method.•The proposed method exploits the spatial relationship appearing in tensor data.•We test the performance on facial image analysis ...and stock price prediction problems.
There has been a great effort to transfer linear discriminant techniques that operate on vector data to high-order data, generally referred to as Multilinear Discriminant Analysis (MDA) techniques. Many existing works focus on maximizing the inter-class variances to intra-class variances defined on tensor data representations. However, there has not been any attempt to employ class-specific discrimination criteria for the tensor data. In this paper, we propose a multilinear subspace learning technique suitable for applications requiring class-specific tensor models. The method maximizes the discrimination of each individual class in the feature space while retains the spatial structure of the input. We evaluate the efficiency of the proposed method on two problems, i.e. facial image analysis and stock price prediction based on limit order book data.
•Growth and characterizations of wurtzite GaAs/InAs core/shell nanowires.•Effect of wetting angle on the wurtzite formation in GaAs nanowire growth.•Observation of tensile strain in GaAs core and ...compressive strain InAs shell.•Observation of the same strain states along a and c axes of m-polar growth surface.•Observation of high carrier mobility for the wurtzite GaAs/InAs NWs.
Research on nanowire (NW) growth of III-V semiconductors including GaAs and InAs demonstrated the ability to grow in both wurtzite (WZ) and zincblende (ZB) polymorphs. However, the control of crystal phase in self-catalyzed NW growth is still a remaining challenge. In this study we report a controlled growth of GaAs/InAs core/shell nanowires in WZ phase using self-catalyzed molecular beam epitaxy (MBE). The GaAs NWs having pure WZ crystal were achieved and attributed to the effect of small wetting angle, which is realized by supplying high V/III ratio. Furthermore, the WZ formation is shown to be uninfluenced by NW diameter. For the wetting angle larger than 90°, mixed phase starts to be observed. The InAs shell is planarly grown on six m-plane facets of the GaAs core NWs leading to the same strain states along a and c axes of growth plane, in which tensile and compressive strains are observed for GaAs core and InAs shell, respectively. High-resolution transmission electron microscopy (HR-TEM) reveals a few misfit dislocations (~0.03 nm−1) at GaAs/InAs interface indicating insignificant strain relief via creating misfit dislocation. Electrical characterization of the hetero-wires shows that the InAs shell exhibits n-type conduction. A room-temperature sheet carrier concentration at zero gate-bias of 2.5 × 1012 cm−2 and the corresponding carrier mobility of ~ 900 cm2 V−1 s−1 are demonstrated.