Applying the wireless sensor network of the Industrial Internet of Things and the radio frequency identification technology to the production workshop of the discrete manufacturing industry, the ...real-time status of the shop floor can be automatically collected, providing a powerful decision-making basis for the upper-level planning management department. This paper proposes a reference architecture and construction path for smart factories by analyzing industrial IoT technology and its application in manufacturing workshops. Combined with the analysis of the status quo and needs of the discrete manufacturing enterprise workshop, this paper designs the overall architecture and theoretical model of the system. In view of the variety of on-site manufacturing data, large amount of data, variable status, heterogeneity, and strong correlation between data, integrated key technologies such as WSN and RFID, the industrial IoTs solution for manufacturing workshops is given. The multi-thread data real-time collection, storage technology and product tracking monitoring of the workshop are studied. Finally, the performance of the system is analyzed from the perspective of real-time and quality. The results show that the system is effective in the monitoring of production line data.
Computation-in-memory (CIM) is a promising candidate to improve the energy efficiency of multiply-and-accumulate (MAC) operations of artificial intelligence (AI) chips. This work presents an static ...random access memory (SRAM) CIM unit-macro using: 1) compact-rule compatible twin-8T (T8T) cells for weighted CIM MAC operations to reduce area overhead and vulnerability to process variation; 2) an even-odd dual-channel (EODC) input mapping scheme to extend input bandwidth; 3) a two's complement weight mapping (C2WM) scheme to enable MAC operations using positive and negative weights within a cell array in order to reduce area overhead and computational latency; and 4) a configurable global-local reference voltage generation (CGLRVG) scheme for kernels of various sizes and bit precision. A 64 × 60 b T8T unit-macro with 1-, 2-, 4-b inputs, 1-, 2-, 5-b weights, and up to 7-b MAC-value (MACV) outputs was fabricated as a test chip using a foundry 55-nm process. The proposed SRAM-CIM unit-macro achieved access times of 5 ns and energy efficiency of 37.5-45.36 TOPS/W under 5-b MACV output.
Computing-in-memory (CIM) based on embedded nonvolatile memory is a promising candidate for energy-efficient multiply-and-accumulate (MAC) operations in artificial intelligence (AI) edge devices. ...However, circuit design for NVM-based CIM (nvCIM) imposes a number of challenges, including an arealatency-energy tradeoff for multibit MAC operations, patterndependent degradation in signal margin, and small read margin. To overcome these challenges, this article proposes the following: 1) a serial-input non-weighted product (SINWP) structure; 2) a down-scaling weighted current translator (DSWCT) and positive-negative current-subtractor (PN-ISUB); 3) a currentaware bitline clamper (CABLC) scheme; and 4) a triple-margin small-offset current-mode sense amplifier (TMCSA). A 55-nm 1-Mb ReRAM-CIM macro was fabricated to demonstrate the MAC operation of 2-b-input, 3-b-weight with 4-b-out. This nvCIM macro achieved T MAC = 14.6 ns at 4-b-out with peak energy efficiency of 53.17 TOPS/W.
Functional magnetic resonance imaging (fMRI) maps cerebral activation in response to stimuli but this activation is often difficult to detect, especially in low-signal contexts and single-subject ...studies. Accurate activation detection can be guided by the fact that very few voxels are, in reality, truly activated and that these voxels are spatially localized, but it is challenging to incorporate both these facts. We address these twin challenges to single-subject and low-signal fMRI by developing a computationally feasible and methodologically sound model-based approach, implemented in the R package MixfMRI, that bounds the a priori expected proportion of activated voxels while also incorporating spatial context. An added benefit of our methodology is the ability to distinguish voxels and regions having different intensities of activation. Our suggested approach is evaluated in realistic two- and three-dimensional simulation experiments as well as on multiple real-world datasets. Finally, the value of our suggested approach in low-signal and single-subject fMRI studies is illustrated on a sports imagination experiment that is often used to detect awareness and improve treatment in patients in persistent vegetative state (PVS). Our ability to reliably distinguish activation in this experiment potentially opens the door to the adoption of fMRI as a clinical tool for the improved treatment and therapy of PVS survivors and other patients.
Previous SRAM-based computing-in-memory (SRAM-CIM) macros suffer small read margins for high-precision operations, large cell array area overhead, and limited compatibility with many input and weight ...configurations. This work presents a 1-to-8-bit configurable SRAM CIM unit-macro using: 1) a hybrid structure combining 6T-SRAM based in-memory binary product-sum (PS) operations with digital near-memory-computing multibit PS accumulation to increase read accuracy and reduce area overhead; 2) column-based place-value-grouped weight mapping and a serial-bit input (SBIN) mapping scheme to facilitate reconfiguration and increase array efficiency under various input and weight configurations; 3) a self-reference multilevel reader (SRMLR) to reduce read-out energy and achieve a sensing margin 2<inline-formula> <tex-math notation="LaTeX">\times </tex-math></inline-formula> that of the mid-point reference scheme; and 4) an input-aware bitline voltage compensation scheme to ensure successful read operations across various input-weight patterns. A 4-Kb configurable 6T-SRAM CIM unit-macro was fabricated using a 55-nm CMOS process with foundry 6T-SRAM cells. The resulting macro achieved access times of 3.5 ns per cycle (pipeline) and energy efficiency of 0.6-40.2 TOPS/W under binary to 8-b input/8-b weight precision.
Quantum‐dot‐tagged reduced graphene oxide (QD‐rGO) nanocomposites (left) internalized into targeted tumor cells display bright fluorescence from the QDs (right); by absorbing NIR radiation incident ...on the rGO and converting it into heat, they also cause simultaneous cell death and fluorescence reduction (bottom). The nanocomposite is thus capable of tumor imaging, photothermal therapy and in situ monitoring of treatment in progress.
A unique “clean‐lifting transfer” (CLT) technique that applies a controllable electrostatic force to transfer large‐area and high‐quality CVD‐grown graphene onto various rigid or flexible substrates ...is reported. The CLT technique without using any organic support or adhesives can produce residual‐free graphene films with large‐area processability, and has great potential for future industrial production of graphene‐based electronics or optoelectronics.
Because of their exceptional physical and thermal properties, cellulose nanocrystals (CNCs) are a highly promising bio‐based material for reinforcing fillers. Studies have revealed that some ...functional groups from CNCs can be used as a capping ligand to coordinate with metal nanoparticles or semiconductor quantum dots during the fabrication of novel complex materials. Therefore, through CNCs ligand encapsulation and electrospinning, perovskite‐NC‐embedded nanofibers with exceptional optical and thermal stability are demonstrated. The results indicate that, after continuous irradiation or heat cycling, the relative photoluminescence (PL) emission intensity of the CNCs‐capped perovskite‐NC‐embedded nanofibers is maintained at ≈90%. However, the relative PL emission intensity of both ligand‐free and long‐alkyl‐ligand‐doped perovskite‐NC‐embedded nanofibers decrease to almost 0%. These results are attributable to the formation of specific clusters of perovskite NCs along with the CNCs structure and thermal property improvement of polymers. CNCs‐doped luminous complex materials offer a promising avenue for stability‐demanding optoelectronic devices and other novel optical applications.
Perovskite/ cellulose nanocrystals (CNCs) encapsulated nanofiber (CNCs@PeNFs) for the white light‐emitting diodes through the electrospinning process are fabricated. The CNCs@PeNFs can maintain 90% intensity after five annealing cycles (from 20 to 140 °C) and 60% intensity after 6 h irritation of UV light, which are attributed to the complexation reaction between CNCs ligand and perovskite, and the cluster morphology within nanofibers.
The development of high-performance near-infrared organic light-emitting diodes is hindered by strong non-radiative processes as governed by the energy gap law. Here, we show that exciton ...delocalization, which serves to decouple the exciton band from highly vibrational ladders in the S0 ground state, can bring substantial enhancements in the photoluminescence quantum yield of emitters, bypassing the energy gap law. Experimental proof is provided by the design and synthesis of a series of new Pt(ii) complexes with a delocalization length of 5–9 molecules that emit at 866–960 nm with a photoluminescence quantum yield of 5–12% in solid films. The corresponding near-infrared organic light-emitting diodes emit light with a 930 nm peak wavelength and a high external quantum efficiency up to 2.14% and a radiance of 41.6 W sr−1 m−2. Both theoretical and experimental results confirm the exciton–vibration decoupling strategy, which should be broadly applicable to other well-aligned molecular solids.Pt(ii) complexes allow the fabrication of efficient near-infrared organic light-emitting diodes that operate beyond the 900 nm region.
Phosphorus (P) is an essential macronutrient for plant growth, development and production. However, little is known about the effects of P deficiency on nutrient absorption, photosynthetic apparatus ...performance and antioxidant metabolism in citrus. Seedlings of 'sour pummelo' (Citrus grandis) were irrigated with a nutrient solution containing 0.2 mM (Control) or 0 mM (P deficiency) KH2PO4 until saturated every other day for 16 weeks. P deficiency significantly decreased the dry weight (DW) of leaves and stems, and increased the root/shoot ratio in C. grandis but did not affect the DW of roots. The decreased DW of leaves and stems might be induced by the decreased chlorophyll (Chl) contents and CO2 assimilation in P deficient seedlings. P deficiency heterogeneously affected the nutrient contents of leaves, stems and roots. The analysis of Chl a fluorescence transients showed that P deficiency impaired electron transport from the donor side of photosystem II (PSII) to the end acceptor side of PSI, which showed a greater impact on the performance of the donor side of PSII than that of the acceptor side of PSII and photosystem I (PSI). P deficiency increased the contents of ascorbate (ASC), H2O2 and malondialdehyde (MDA) as well as the activities of superoxide dismutase (SOD), catalase (CAT), ascorbate peroxidase (APX), dehydroascorbate reductase (DHAR) and glutathione reductase (GR) in leaves. In contrast, P deficiency increased the ASC content, reduced the glutathione (GSH) content and the activities of SOD, CAT, APX and monodehydroascorbate reductase (MDHAR), but did not increase H2O2 production, anthocyanins and MDA content in roots. Taking these results together, we conclude that P deficiency affects nutrient absorption and lowers photosynthetic performance, leading to ROS production, which might be a crucial cause of the inhibited growth of C. grandis.
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