Stress granules (SGs) are nonmembranous organelles that are dynamically assembled and disassembled in response to various stressors. Under stressed conditions, polyadenylated mRNAs and translation ...factors are sequestrated in SGs to promote global repression of protein synthesis. It has been previously demonstrated that SG formation enhances cell survival and stress resistance. However, the physiological role of SGs in organismal aging and longevity regulation remains unclear. In this study, we used TIAR‐1::GFP and GTBP‐1::GFP as markers to monitor the formation of SGs in Caenorhabditis elegans. We found that, in addition to acute heat stress, SG formation could also be triggered by dietary changes, such as starvation and dietary restriction (DR). We found that HSF‐1 is required for the SG formation in response to acute heat shock and starvation but not DR, whereas the AMPK‐eEF2K signaling is required for starvation and DR‐induced SG formation but not heat shock. Moreover, our data suggest that this AMPK‐eEF2K pathway‐mediated SG formation is required for lifespan extension by DR, but dispensable for the longevity by reduced insulin/IGF‐1 signaling. Collectively, our findings unveil a novel role of SG formation in DR‐induced longevity.
In addition to heat stress, starvation and dietary restriction (DR) can activate stress granule (SG) formation in Caenorhabditis elegans. HSF‐1 and AMPK are two key regulators for the SG formations. HSF‐1 is required for the SG formation in response to acute heat shock and starvation but not DR, whereas the AMPK‐eEF2K pathway is required for starvation and DR‐induced SG formation but not heat shock. Furthermore, AMPK‐mediated SG formation contributes to DR‐induced longevity.
•A novel approach for under-sampling class imbalanced datasets is proposed.•It is based on combining clustering analysis and instance selection.•Instance selection is used for the clustering result ...of the majority class dataset.•The proposed approach outperforms five baseline approaches over 44 datasets.
Class-imbalanced datasets, i.e., those with the number of data samples in one class being much larger than that in another class, occur in many real-world problems. Using these datasets, it is very difficult to construct effective classifiers based on the current classification algorithms, especially for distinguishing small or minority classes from the majority class. To solve the class imbalance problem, the under/oversampling techniques have been widely used to reduce and enlarge the numbers of data samples in the majority and minority classes, respectively. Moreover, the combinations of certain sampling approaches with ensemble classifiers have shown reasonably good performance. In this paper, a novel undersampling approach called cluster-based instance selection (CBIS) that combines clustering analysis and instance selection is introduced. The clustering analysis component groups similar data samples of the majority class dataset into ‘subclasses’, while the instance selection component filters out unrepresentative data samples from each of the ‘subclasses’. The experimental results based on the KEEL dataset repository show that the CBIS approach can make bagging and boosting-based MLP ensemble classifiers perform significantly better than six state-of-the-art approaches, regardless of what kinds of clustering (affinity propagation and k-means) and instance selection (IB3, DROP3 and GA) algorithms are used.
During the injection molding of molten polymers, the control strategy is switched from speed control to pressure control at the filling‐to‐packing (V/P) switchover point. V/P switchover influences ...part quality and process stability. V/P switchover timing traditionally depends on the degree of volumetric filling of molten polymer in the cavity and is limited to obtain a smooth and repeatable pressure curve for each injection, indicating consistent part quality. Repeatability is affected by the V/P switchover point, injection speed, holding pressure, and holding time. This study clarifies the effect of the injection speed, V/P switchover point, and first‐stage holding pressure setting on cavity pressure curves and injection molding quality. These factors were optimized and verified through the injection molding of integrated circuit trays. The experimental results indicate that adjusting the rear speed of filling stage, V/P switchover point, and first‐stage holding pressure, can yield the ideal pressure curve and improve process stability. Compared with the initial process parameter setting, part warpage was reduced by 40% from 0.042 to 0.025 mm, deviation of part width at the end of the filling pattern was reduced by 54% from 0.024 to 0.011 mm, and width range was reduced by 50% from 0.006 to 0.003 mm.
These paper details a fronthaul optical link using delay-division-multiplexing (DDM) scheme with Volterra based nonlinear compensator for beyond fifth generation (B5G) and 6G massive multiple-input ...multiple-output (Ma-MIMO) beamforming. Based on pre-allocated relative time delays, pre-processed signals can be deaggregated to different RF chain signals following spectral aliasing caused by the digital signal processing (DSP) at remote radio units. The Volterra based nonlinear compensator is used to compensate nonlinear distortion and IQ imbalance of the fronthaul link. By combined the DDM scheme and Volterra technique, we can easily deaggregate signals and mitigate the interference caused by nonlinear distortion and IQ imbalance at the same time. In experiments, the DDM scheme support 128 RF chain signals is demonstrated. With the Volterra compensator, the signal input power of Mach-Zehnder modulator (MZM) has 18 dB margin. IQ imbalance caused by phase misalignment can also be compensated by the IQ Volterra. It can keep the acceptable error vector magnitude (EVM) performance within a ±10° range. After 25-km optical link, the EVM of each RF Chain is underneath 8%. And the total received 128 RF chain signals will require CPRI data rate as high as 840 Gb/s.
Toxic and nontoxic volatile organic compound (VOC) gases are emitted into the atmosphere from certain solids and liquids as a consequence of wastage and some common daily activities. Inhalation of ...toxic VOCs has an adverse effect on human health, so it is necessary to monitor their concentration in the atmosphere. In this work, we report on the fabrication of inorganic nanotube (INT)-tungsten disulfide, paper-based graphene–PEDOT:PSS sheet and WS2 nanotube-modified conductive paper-based chemiresistors for VOC gas sensing. The WS2 nanotubes were fabricated by a two-step reaction, that is oxide reduction and sulfurization, carried out at 900 °C. The synthesized nanotubes were characterized by FE-SEM, EDS, XRD, Raman spectroscopy, and TEM. The synthesized nanotubes were 206–267 nm in diameter. The FE-SEM results show the length of the nanotubes to be 4.5–8 µm. The graphene–PEDOT:PSS hybrid conductive paper sheet was fabricated by a continuous coating process. Then, WS2 nanotubes were drop-cast onto conductive paper for fabrication of the chemiresistors. The feasibility and sensitivity of the WS2 nanotube-modified paper-based chemiresistor were tested in four VOC gases at different concentrations at room temperature (RT). Experimental results show the proposed sensor to be more sensitive to butanol gas when the concentration ranges from 50 to 1000 ppm. The limit of detection (LOD) of this chemiresistor for butanol gas was 44.92 ppm. The WS2 nanotube-modified paper-based chemiresistor exhibits good potential as a VOC sensor with the advantages of flexibility, easy fabrication, and low fabrication cost.
A turn-off fluorescence sensor synthesized by combining copper (II) oxide and multiwall carbon nanotubes (MWCNTs) were used for measuring glyphosate based on the inhibiting the catalytic activity of ...the CuO/MWCNTs. This sensor was synthesized by precipitating copper ions onto the acidic MWCNTs under basic conditions; the resulting material was characterized by the transmission electron microscopy, X-ray photoelectron spectroscopy, and Fourier transform infrared spectroscopy to confirm its structure. The CuO/MWCNTs nanomaterial was found to exhibit high peroxidase-like catalytic activity toward the reduction of H2O2 to H2O and the oxidation of Amplex Red to resorufin, with a corresponding color change from pink to red and the fluorescence enhancement. However, this activity was inhibited and the fluorescence diminished when glyphosate was added to the system. Using this strategy, we applied this sensor to detect glyphosate. The results indicated that this sensor is not only highly sensitive, with a detection limit of 0.67 ppb and a linear range from 0.002 to 0.01ppm, but also exhibits good selectivity for glyphosate. When this sensor was assessed for detecting glyphosate in real water samples, recoveries of 96–107% were attained. This proposed material and method are a promising approach for rapid screening of glyphosate.
Display omitted
●A turn-off fluorescence sensor synthesized by combining copper (II) oxide and multiwall carbon nanotubes (MWCNTs) were used for measuring glyphosate based on the inhibiting the catalytic activity of the CuO/MWCNTs.●The results indicated that this sensor is not only highly sensitive, with a detection limit of 0.67 ppb and a linear range from 0.002 to 0.01ppm, but also exhibits good selectivity for glyphosate.●We investigated the interference of this sensor and demonstrated the feasibility of using the method used in the analysis of real samples.
Microbial fuel cell (MFC) is a promising technology that utilizes exoelectrogens cultivated in the form of biofilm to generate power from various types of sources supplied. A metal-reducing pathway ...is utilized by these organisms to transfer electrons obtained from the metabolism of substrate from anaerobic respiration extracellularly. A widely established model organism that is capable of extracellular electron transfer (EET) is
Shewanella oneidensis
. This review highlights the strategies used in the transformation of
S. oneidensis
and the recent development of MFC in terms of intervention through genetic modifications.
S. oneidensis
was genetically engineered for several aims including the study on the underlying mechanisms of EET, and the enhancement of power generation and wastewater treating potential when used in an MFC. Through engineering
S. oneidensis
, genes responsible for EET are identified and strategies on enhancing the EET efficiency are studied. Overexpressing genes related to EET to enhance biofilm formation, mediator biosynthesis, and respiration appears as one of the common approaches.
This paper proposes a deep-learning model with task-specific bounding box regressors (TSBBRs) and conditional back-propagation mechanisms for detection of objects in motion for advanced driver ...assistance system (ADAS) applications. The proposed model separates the object detection networks for objects of different sizes and applies the proposed algorithm to achieve better detection results for both larger and tinier objects. For larger objects, a neural network with a larger visual receptive field is used to acquire information from larger areas. For the detection of tinier objects, the network of a smaller receptive field utilizes fine grain features. A conditional back-propagation mechanism yields different types of TSBBRs to perform data-driven learning for the set criterion and learn the representation of different object sizes without degrading each other. The design of dual-path object bounding box regressors can simultaneously detect objects in various kinds of dissimilar scales and aspect ratios. Only a single inference of neural network is needed for each frame to support the detection of multiple types of object, such as bicycles, motorbikes, cars, buses, trucks, and pedestrians, and to locate their exact positions. The proposed model was developed and implemented on different NVIDIA devices such as 1080 Ti, DRIVE-PX2 and Jetson TX-2 with the respective processing performance of 67 frames per second (fps), 19.4 fps, and 8.9 fps for the video input of 448 × 448 resolution, respectively. The proposed model can detect objects as small as 13 × 13 pixels and achieves 86.54% accuracy on a publicly available Pascal Visual Object Class (VOC) car database and 82.4% mean average precision (mAP) on a large collection of common road real scenes database (iVS database).
Lycium barbarum have received an increasing popularity due to its powerful biological activity and medicinal use. However, the effect of Lycium barbarum on skin remains largely uncharacterized. The ...general purpose of this paper was to characterize the phenolic compounds in Lycium barbarum extract (LBE) using LC‐HRMS/QTOF method and to investigate whether topical administration of LBE can repair skin barrier dysfunction in mice. Our data demonstrated that LBE could not only decrease ROS level and matrix metalloproteinase expression, but also strengthen intrinsic antioxidant defense system including SOD, GSH‐Px and CAT, thereby resulting in increased skin collagen content and an improvement of UV‐induced skin erythema, thickness and wrinkles. Improved skin barrier functions were highly correlated with increased expression of filaggrin, involucrin and loricrin as well as antioxidant proteins such as Nrf2 and HO‐1 in UV‐irradiated mice, suggesting that LBE may be promising natural products at a lower cost for the topical application in the treatment of skin diseases with defective barrier function.
Phenolic‐containing extracts of Lycium barbarum (LBE) have a beneficial effect on skin barrier impairment and effectively prevents skin dryness, epidermal thickening, wrinkles and widespread erythema through strengthening antioxidative enzyme activities and inhibiting the excessive degradation of collagen. LBE are effective to induce the protection of skin barrier function by activating Nrf2 and its related signaling pathway as well as upregulating epidermal barrier proteins including FLG, IVL and LOR and scavenging ROS produced in mouse skin.
Ultra-low quiescent current (<inline-formula> <tex-math notation="LaTeX">I_{Q} </tex-math></inline-formula>) low-dropout regulator is the only solution for compact size Internet of Things (IoT) ...electronic devices. This paper presents an ultra-low <inline-formula> <tex-math notation="LaTeX">I_{Q} </tex-math></inline-formula> low dropout regulator, including low <inline-formula> <tex-math notation="LaTeX">I_{Q} </tex-math></inline-formula> error amplifier (EA) compensated by the adaptive current control (ACC), low leakage feedback network, low <inline-formula> <tex-math notation="LaTeX">I_{Q} </tex-math></inline-formula> current comparator, analog transient enhancement (ATE), and digital transient enhancement (DTE). The chip was fabricated in a standard <inline-formula> <tex-math notation="LaTeX">0.5~\mu \text{m} </tex-math></inline-formula> CMOS process. Measurement results show the current peak efficiency of the LDO is as high as 99.99%. Besides, owing to ATE and DTE circuits, when the load current changes from 1mA to 50mA with a 10 ns edge time, the measured undershoot and overshoot voltages are 75 mV and 50 mV, respectively, with the recovery time (<inline-formula> <tex-math notation="LaTeX">T_{R} </tex-math></inline-formula>) of 60 ns and 80 ns, respectively, where the best 0.003 ps FoM is achieved.
PDF
