Abstract
Copper electrocatalysts have been shown to selectively reduce carbon dioxide to hydrocarbons. Nevertheless, the absence of a systematic study based on time-resolved spectroscopy renders the ...functional agent—either metallic or oxidative Copper—for the selectivity still undecidable. Herein, we develop an operando seconds-resolved X-ray absorption spectroscopy to uncover the chemical state evolution of working catalysts. An oxide-derived Copper electrocatalyst is employed as a model catalyst to offer scientific insights into the roles metal states serve in carbon dioxide reduction reaction (CO
2
RR). Using a potential switching approach, the model catalyst can achieve a steady chemical state of half-Cu(0)-and-half-Cu(I) and selectively produce asymmetric C
2
products - C
2
H
5
OH. Furthermore, a theoretical analysis reveals that a surface composed of Cu-Cu(I) ensembles can have dual carbon monoxide molecules coupled asymmetrically, which potentially enhances the catalyst’s CO
2
RR product selectivity toward C
2
products. Our results offer understandings of the fundamental chemical states and insights to the establishment of selective CO
2
RR.
Hybrid quantum dot–graphene photodetectors have recently attracted substantial interest because of their remarkable performance and low power consumption. However, the performance of the device ...greatly depends on the interfacial states and photogenerated screening field. As a consequence, the sensitivity is limited and the response time is relatively slow. In order to circumvent these challenges, herein, a composite graphene and graphene quantum dot (GQD) photodetector on lead zirconate titanate (Pb(Zr0.2Ti0.8)O3) (PZT) substrates has been designed to form an ultrasensitive photodetector over a wide range of illumination power. Under 325 nm UV light illumination, the device shows sensitivity as high as 4.06 × 109 A W−1, which is 120 times higher than reported sensitivity of the same class of devices. Plant derived GQD has a broad range of absorptivity and is an excellent candidate for harvesting photons generating electron–hole pairs. Intrinsic electric field from PZT substrate separates photogenerated electron–hole pairs as well as provides the built‐in electric field that causes the holes to transfer to the underlying graphene channel. The composite structure of graphene and GQD on PZT substrate therefore produces a simple, stable, and highly sensitive photodetector over a wide range of power with short response time, which shows a way to obtain high‐performance optoelectronic devices.
The permanent polarization of piezoelectric substrate (PZT) parallel to the built‐in electric field (DPZT) in the composite graphene and graphene quantum dot photodetector device assists efficient transfer of photogenerated holes to the graphene channel thus enhancing the photoresponsivity more than 100 times with ten times faster response compared to the device on SiO2 substrate. In contrast, opposite PZT polarization in UPZT devices abates the photoresponsivity with slower response time.
MicroRNAs offer tools to identify and treat invasive cancers. Using highly invasive isogenic oral squamous cell carcinoma (OSCC) cells, established using in vitro and in vivo selection protocols from ...poorly invasive parental cell populations, we used microarray expression analysis to identify a relative and specific decrease in miR-491-5p in invasive cells. Lower expression of miR-491-5p correlated with poor overall survival of patients with OSCCs. miR-491-5p overexpression in invasive OSCC cells suppressed their migratory behavior in vitro and lung metastatic behavior in vivo. We defined the G-protein-coupled receptor kinase-interacting protein 1 (GIT1)-as a direct target gene for miR-491-5p control. GIT1 overexpression was sufficient to rescue miR-491-5p-mediated inhibition of migration/invasion and lung metastasis. Conversely, GIT1 silencing phenocopied the ability of miR-491-5p to inhibit migration/invasion and metastasis of OSCC cells. Mechanistic investigations indicated that miR-491-5p overexpression or GIT1 attenuation reduced focal adhesions, with a concurrent decrease in steady-state levels of paxillin, phospho-paxillin, phospho-FAK, EGF/EGFR-mediated extracellular signal-regulated kinase (ERK1/2) activation, and MMP2/9 levels and activities. In clinical specimens of OSCCs, GIT1 levels were elevated relative to paired normal tissues and were correlated with lymph node metastasis, with expression levels of miR-491-5p and GIT1 correlated inversely in OSCCs, where they informed tumor grade. Together, our findings identify a functional axis for OSCC invasion that suggests miR-491-5p and GIT1 as biomarkers for prognosis in this cancer.
Long noncoding RNAs (lncRNAs) have been implicated in hypoxia/HIF-1-associated cancer progression through largely unknown mechanisms. Here we identify MIR31HG as a hypoxia-inducible lncRNA and ...therefore we name it LncHIFCAR (long noncoding HIF-1α co-activating RNA); we describe its oncogenic role as a HIF-1α co-activator that regulates the HIF-1 transcriptional network, crucial for cancer development. Extensive analyses of clinical data indicate LncHIFCAR level is substantially upregulated in oral carcinoma, significantly associated with poor clinical outcomes and representing an independent prognostic predictor. Overexpression of LncHIFCAR induces pseudo-hypoxic gene signature, whereas knockdown of LncHIFCAR impairs the hypoxia-induced HIF-1α transactivation, sphere-forming ability, metabolic shift and metastatic potential in vitro and in vivo. Mechanistically, LncHIFCAR forms a complex with HIF-1α via direct binding and facilitates the recruitment of HIF-1α and p300 cofactor to the target promoters. Our results uncover an lncRNA-mediated mechanism for HIF-1 activation and establish the clinical values of LncHIFCAR in prognosis and potential therapeutic strategy for oral carcinoma.
This paper presents a novel single-ended disturb-free 9T subthreshold SRAM cell with cross-point data-aware Write word-line structure. The disturb-free feature facilitates bit-interleaving ...architecture, which can reduce multiple-bit upsets in a single word and enhance soft error immunity by employing Error Checking and Correction (ECC) technique. The proposed 9T SRAM cell is demonstrated by a 72 Kb SRAM macro with a Negative Bit-Line (NBL) Write-assist and an adaptive Read operation timing tracing circuit implemented in 65 nm low-leakage CMOS technology. Measured full Read and Write functionality is error free with V DD down to 0.35 V ( 0.15 V lower than the threshold voltage) with 229 KHz frequency and 4.05 μW power. Data is held down to 0.275 V with 2.29 μW Standby power. The minimum energy per operation is 4.5 pJ at 0.5 V. The 72 Kb SRAM macro has wide operation range from 1.2 V down to 0.35 V, with operating frequency of around 200 MHz for V DD around/above 1.0 V.
This article presents a computing-in-memory (CIM) structure aimed at improving the energy efficiency of edge devices running multi-bit multiply-and-accumulate (MAC) operations. The proposed scheme ...includes a 6T SRAM-based CIM (SRAM-CIM) macro capable of: 1) weight-bitwise MAC (WbwMAC) operations to expand the sensing margin and improve the readout accuracy for high-precision MAC operations; 2) a compact 6T local computing cell to perform multiplication with suppressed sensitivity to process variation; 3) an algorithm-adaptive low MAC-aware readout scheme to improve energy efficiency; 4) a bitline header selection scheme to enlarge signal margin; and 5) a small-offset margin-enhanced sense amplifier for robust read operations against process variation. A fabricated 28-nm 64-kb SRAM-CIM macro achieved access times of 4.1-8.4 ns with energy efficiency of 11.5-68.4 TOPS/W, while performing MAC operations with 4- or 8-b input and weight precision.
Apical lesions, the general term for chronic infectious diseases, are very common dental diseases in modern life, and are caused by various factors. The current prevailing endodontic treatment makes ...use of X-ray photography taken from patients where the lesion area is marked manually, which is therefore time consuming. Additionally, for some images the significant details might not be recognizable due to the different shooting angles or doses. To make the diagnosis process shorter and efficient, repetitive tasks should be performed automatically to allow the dentists to focus more on the technical and medical diagnosis, such as treatment, tooth cleaning, or medical communication. To realize the automatic diagnosis, this article proposes and establishes a lesion area analysis model based on convolutional neural networks (CNN). For establishing a standardized database for clinical application, the Institutional Review Board (IRB) with application number 202002030B0 has been approved with the database established by dentists who provided the practical clinical data. In this study, the image data is preprocessed by a Gaussian high-pass filter. Then, an iterative thresholding is applied to slice the X-ray image into several individual tooth sample images. The collection of individual tooth images that comprises the image database are used as input into the CNN migration learning model for training. Seventy percent (70%) of the image database is used for training and validating the model while the remaining 30% is used for testing and estimating the accuracy of the model. The practical diagnosis accuracy of the proposed CNN model is 92.5%. The proposed model successfully facilitated the automatic diagnosis of the apical lesion.
Backlight power-saving algorithms can reduce the power consumption of the display by adjusting the frame pixels with optimal clipping points under some tradeoff criteria. However, the computation for ...the selected clipping points can be complex. In this paper, a novel algorithm is created to reduce the computation time of the state-of-the-art backlight power-saving algorithms. If the current frame is similar to the previous frame, it is unnecessary to execute the backlight power-saving algorithm for the optimal clipping points, and the derived clipping point from the previous frame can be used for the current frame automatically. In this paper, the motion vector information was used as the measurement of the similarity between adjacent frames, where the generation of the motion vector information requires no extra complexity since it is generated to reconstruct the decoded frame pixels before the display. The experiments showed that the proposed work can reduce the running time of the state-of-the-art methods by 25.21% to 64.22%, while the performances are maintained; the differences with the state-of-the-art methods in PSNR are only 0.02~1.91 dB, and those in power are only −0.001~0.008 W.
Accurate tourist demand forecasting systems are essential in tourism planning, particularly in tourism-based countries. Artificial neural networks are attracting attention to forecast tourism demands ...due to their general non-linear mapping capabilities. Unlike most conventional neural network models, which are based on the empirical risk minimization principle, support vector regression (SVR) applies the structural risk minimization principle to minimize an upper bound of the generalization error, rather than minimizing the training error. This investigation presents a SVR model with chaotic genetic algorithm (CGA), namely SVRCGA, to forecast the tourism demands. With the increase of the complexity and the larger problem scale of tourism demands, genetic algorithms (GAs) are often faced with the problems of premature convergence, slowly reaching the global optimal solution or trapping into a local optimum. The proposed CGA based on the chaos optimization algorithm and GAs, which employs internal randomness of chaos iterations, is used to overcome premature local optimum in determining three parameters of a SVR model. Empirical results that involve tourism demands data from existed paper reveal the proposed SVRCGA model outperforms other approaches in the literature.
Robot-assisted hand training has shown positive effects on promoting neuromuscular control. Since both robot-assisted therapy and task-oriented training are often used in post-stroke rehabilitation, ...we raised the question of whether two interventions engender differential effects in different domains.
The study was conducted using a randomized, two-period crossover design. Twenty-four chronic stroke survivors received a 12-session robot-assisted intervention followed by a 12-session task-oriented intervention or vice versa. A 1-month washout period between each intervention was implemented. Outcome measures were evaluated before the intervention, after the first 12-session intervention, and after the second 12-session intervention. Clinical assessments included Fugl-Meyer Assessment for Upper Extremity, Wolf Motor Function Test, Action Research Arm Test and Motor Activity Log.
Our findings suggested that EMG-driven robot-assisted therapy was as effective as task-oriented training in terms of improving upper limbs functional performance in activity domain, and robot-assisted therapy was more effective in improving movement duration during functional tasks. Task-oriented training showed better improvement in body function domain and activity and participation domain, especially in improving spontaneous use of affected arm during daily activities.
Both intervention protocol had their own advantages in different domains, and robot-assisted therapy may save manpower and be considered as an alternative intervention to task-oriented training. Combining the two approaches could yield results greater than either alone, which awaits further study.
ClinicalTrials.gov Identifier: NCT03624153. Registered on 9th August 2018, https://clinicaltrials.gov/ct2/show/NCT03624153 .
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