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Herein, a novel AlGaN‐based multiple quantum well (MQW) deep UV light‐emitting diode (DUV‐LED) structure with two parts linearly graded barriers is presented. The simulation result shows that at a current of 50 mA, the light output power of the DUV‐LED with two parts linearly graded barrier MQWs has significant improvement as compared to stationary barriers. The electroluminescence spectrum and radiative recombination rate of novel DUV‐LEDs are also larger more than twice that of the conventional QW structure. The reason is that the injection efficiency of holes is increased which helps improve the hole and electron concentration in the active area. Meanwhile, the electric field is also decreased by using two parts linearly graded quantum barriers, and according to reduce the electric field the quantum‐confined Stark effect and the bend of the energy band get relieved. [ABSTRACT FROM AUTHOR]

The asymmetric conductance modulation of resistance random access memory (RRAM) is one of the crucial obstacles of the application as artificial synapses for online training. In this work, an optimized programming scheme is proposed to overcome the obstacle. In the optimized programming scheme, the RRAM is grounded through the array parasitic capacitor during the depression process. By harnessing the charging effect of parasitic capacitor, the voltage applied on the RRAM-based synapse is self-regulated according to its conductance. Meanwhile, the linearity of depression process can be tuned by adjusting the operation pulse shape to realize symmetric conductance modulation. The proposed programming scheme is verified by experiment and simulation with a 4 kb RRAM array. Finally, the optimized programming characteristics are applied in the simulation of the training of a VGG-like neural network for the classification of CIFAR-10 dataset. The results show that with the linearity of 6, 88.93% training accuracy is achieved, showing 17.3% accuracy improvement without any overhead either in fabrication process or hardware design cost. [ABSTRACT FROM AUTHOR]

Physical exercise refers to various physical exercises carried out through certain means and methods. Physical exercise can not only achieve the purpose of strengthening the body and health but also make people face challenges in physical and mental sports, and the resulting psychological satisfaction and excitement make exercisers happy physically and mentally. Physical activity has a certain appeal that makes it one of the most effective ways for modern people to alleviate mental illnesses. The human brain's reaction time is linked to its thinking speed and intelligence. Regular physical activity can increase human brain cell reaction time and completely utilize human brain capacity, which is beneficial to the healthy development of human attention, memory, imagination, and thinking ability. Scientific and reasonable physical exercise is also an important means to improve people's intelligence levels. Everyone's physical health level is closely related to their mental health. A healthy mind comes from a healthy body. A large number of scientific studies have confirmed that reasonably arranging the contents and methods of physical exercise according to their own health level and psychological state cannot only enhance the physique of college students but also cultivate their excellent personality. Firstly, this paper summarizes the influence of physical exercise on mental health. The ways of employing physical exercise to improve and improve the mental health of college students are presented in this study. Then, this paper proposes a physical exercise intervention based on an improved neural network (NN), which has an impact on the mental health level of college students, and the effectiveness of this model is verified by simulation experiments. [ABSTRACT FROM AUTHOR]

Electromigration (EM) of metal interconnects is the continuous reliability concern for high-density integration beyond 5-nm technology, especially for the buried power rails in vertically stacked device structure. In this work, EM reliability of alternative metal interconnects based on complementary FET (CFET) is investigated by kinetic Monte Carlo (KMC) method. The microscopic evolutions of void formation in power rails can be well reproduced by considering the coupled effects of thermal and stress distribution during the EM simulation. The influences of grain boundary in different metal materials on EM lifetime are analyzed to provide the optimal strategy of process integration. Thermal-aware EM reliability is further predicted, indicating the importance of self-heating on EM evaluation of power rails in CFET. [ABSTRACT FROM AUTHOR]

Wild birds play an important role in the emergence, evolution, and spread of zoonotic avian influenza viruses (AIVs). However, there are few studies on the cross-species transmission of the H3N8 AIV originating from wild birds. In this study, we investigated the transmissibility and pathogenicity of two H3N8 low pathogenic avian influenza viruses (LPAIVs) isolated from wild birds, GZA1 and XJ47, to mammals. The HA genes of both strains belonged to Eurasian isolates, while the other genes were derived from a variety of other subtypes of AIVs. Both strains can infect specific-pathogen-free (SPF) chickens, BALB/c mice, and guinea pigs. The XJ47 strain spread horizontally in SPF chickens and guinea pigs. The GZA1 strain did not spread horizontally but caused higher weight loss and mild lung inflammation in mice. P12-GZA1- and P12-XJ47-adapted strains obtained after 12 passages in the lung of mice showed enhanced pathogenicity in mice, which led to obvious clinical symptoms, lung inflammation, and 100% death. Both adapted strains have the reported mutation T97I in the PA, and the reported mutation D701N in PB2 has been found in the P12-GZA1-adapted strain. This study provides an important scientific basis for the continuous monitoring of wild AIVs and the mechanism underlying AIV cross-species transmission. [ABSTRACT FROM AUTHOR]

In this article, we investigate the self-heating effect (SHE) of the Complementary FET (CFET) device and propose a cross-coupled thermal network model. For the investigation of thermal behavior, the intra- and inter-device crosstalk of CFET is evaluated qualitatively through the defined crosstalk coefficient. The results indicate that CFETs have more severe intra-device thermal crosstalk, almost twice that of CMOS. Moreover, the vertical structure makes the heat dissipation path of CFET devices significantly different in the two transition states (inputs “1” and “0”). Based on the thermal behavior characteristics of CFET and the necessity of high-precision and rapid prediction of thermal characteristics of the devices, a thermal network model is proposed, which can quickly respond to the heat source and be extended at the array level. In the last part, we analyze the influence of load capacitance and operating frequency on the self-heating of CFET, and SHE-related reliability lifetime is predicted based on the lattice temperature obtained from the thermal network. The prediction results show that the bias temperature instability (BTI) lifetime of CFET degrades by 84% compared with standard CMOS. [ABSTRACT FROM AUTHOR]

In this letter, a new method based on the temperature dependence of gate leakage current for accurately characterizing thermal crosstalk is proposed and performed on the advanced silicon-on-insulator (SOI) MOSFETs. The developed technique enables to capture the pure thermal crosstalk effect as it excludes the self-heating impact during the measurement. Moreover, it is proven robust over a large range of gate voltages regardless of the difference of device types, which is demonstrated on a pair of devices with a shared port. The accuracy of the thermal crosstalk measurement benefits in determining the overall thermal performance of the nano-scaled circuits under the mutual heating impacts. It offers a possible hardware solution to thermal monitor and management. [ABSTRACT FROM AUTHOR]

Independent back bias in the ultrathin body and Box (UTBB) fully depleted silicon-on-insulator (FDSOI) serves as the critical knob for exploiting the performance and power tradeoffs and process/aging compensation. The effectiveness of back bias is one of the major metrics in the stages of circuit design and runtime feedback. In this article, new closed-form expressions accounting for the interface traps and short channel effects-dependent back gate capability in the UTBB FDSOI device are proposed. The developed model allows the accurate assessment of body factor (γ) with the dependence of front/back interface trap density in the ultrascaled FDSOI device, taking the impact of gate area scaling as well as quantum effects into account. It also facilitates the evaluation of back bias effectiveness variability induced by interface traps and benefits the dynamic threshold voltage strategy in terms of adaptive back-biasing for performance optimization, which is consistent with 3-D device simulations and measurements. Moreover, the results confirm that γ variability follows Pelgrom’s rule. [ABSTRACT FROM AUTHOR]

Vermicomposting is a feasible method for disposing of lignocellulosic waste while generating a useful product. The current study assessed the potential of vermicomposting green waste mixed with sugarcane bagasse in proportions of 25%, 50%, and 75% (v:v, based on dry weight). The suitability was evaluated based on the agrochemical properties, earthworm biomass, and phytotoxicity. The final vermicomposts exhibited near-neutral pH values (7.1–7.6), and lower EC values (0.43–0.72 mS/cm) and C:N ratios (14.1–19.9).The content of available nutrients and CEC for all the vermicomposts exceeded those of the control compost (without earthworms). For vermicomposts, the average values of NO3−-N, AP, AK, and CEC were 53, 517, 1362 mg/kg, and 158 cmol/kg, respectively. The total contents of heavy metals increased in all vermicompost treatments compared to control composts with the following average final percentages: Zn (2.0%), Cr (15.5%), Pb (23.4%), and Cu (44.3%), but these amounts were safe for application in agroforestry. The addition of sugarcane bagasse to green waste significantly increased the content of total humic substance, humic acid and urease activity, acid and alkaline phosphatase activity, and Eisenia fetida reproduction. The addition of 25% sugarcane bagasse to green waste decreased the toxicity to germinating seeds. These results revealed that vermicomposting is a feasible way to degrade green waste into a value-added chemical product. [ABSTRACT FROM AUTHOR]

A new method using temperature dependent shared series resistance in a pair of devices with common drain configuration is proposed to measure self-heating (SH) in advanced MOSFETs. The proposed measurement technique depends on the intrinsic series resistance and is not limited to the spatial proximity between the heater and the sensor. The developed method demonstrated on the silicon-on-insulator (SOI) MOSFETs reveals that the more accurate SH assessment can be obtained compared to other methods that are sensitive to the distance from heat source. Furthermore, the extraction of intrinsic series resistance allows to quantify the process-induced variability of the contact resistance. [ABSTRACT FROM AUTHOR]

Many efforts have been reported to improve the linear conductance modulation of analog RRAM for neuromorphic computing, while the related model for analog switching is still lacking. In this letter, we propose a physics-based analytic model to account for analog behavior of HfO2-based RRAM. The switching from abrupt SET process to gradual SET is analyzed quantitatively by considering the electrical and thermal effects of intermediate modulation layer (IML). The proposed model well describes the conductance update in potentiation and depression, which is validated with the experimental data. The results show that for the case of introducing IML to improve linearity, the electrical resistivity of IML has a greater effect than thermal conductivity on the control of oxygen vacancy generation rate, thus playing a dominant role in the nonlinearity optimization of analog RRAM. [ABSTRACT FROM AUTHOR]

As a promising new generation of nonvolatile memory, HfO2-based resistive random-access memory (RRAM) has attracted extensive research. However, the problem of data retention has prevented its industrial production as embedded memory. In this paper, from the microscopic understanding, a Monte Carlo simulator is developed to investigate the effects of an oxygen reservoir layer (ORL) on the resistance instability of HfO2-based RRAM. The evolution of conductive filaments (CF) during the retention degradation is visualized by our simulation considering the physical mechanisms of oxygen ions absorbed and released by the ORL. The simulation results are further validated with experiments to provide the prediction of retention performance of RRAMs with different ORLs and operation schemes. [ABSTRACT FROM AUTHOR]