Bat-ball contacts are critical in the baseball hitting process. However, an effective training method for increasing the impact perception of a bat-ball contact is currently unavailable. Although not ...widely used, hitting a stationary weighted baseball can be an appropriate method for batters to simulate the perception of hitting a moving baseball. Therefore, swing velocity, wrist vibration, and forearm muscle activation for hitting stationary weighted, stationary regulation, and pitched baseballs were investigated in this study. Twelve position players hit a stationary weighted, stationary regulation, and pitched baseball at a speed of 70.28 ± 3.84 km/h in a random order. The swing velocity, wrist vibration, forearm muscle activation, and co-contraction ratio during hitting phases were analysed. The results indicated that the swing velocity during each specific phase demonstrated no significant differences between the different conditions. Hitting weighted and pitched baseballs caused higher wrist vibration, muscle activation, and co-contraction ratio during the contact phase than hitting regulation balls (p < 0.05). The conclusion was that hitting weighted baseballs could mimic the impact condition of hitting pitched baseballs without changing the pattern of swing velocity, which suggested that this method has potential as a hitting drill for improving hitting perception at bat-ball contact.
Oral squamous cell carcinoma (OSCC) is a prevalent and lethal malignancy with a diverse etiology. LINC00312 is a long intergenic non-coding RNA that functions as a signal hub to regulate the ...progression and treatment of head and neck cancer. The aim of this study was to evaluate the effect of
single nucleotide polymorphisms (SNPs) on the development of oral cancer. Two
SNPs, namely rs12497104 and rs164966, were investigated among 469 male patients with cancer of buccal mucosa and 1194 gender- and age-matched controls. No significant correlation was observed between these two SNPs and the occurrence of OSCC in the case and control groups. While assessing the clinicopathological features, carriers of at least one minor allele of rs164966 (GA and GG) were less prone to develop lymph node metastasis (adjusted odds ratio AOR, 0.666; 95% confidence interval CI, 0.447-0.991;
=0.045) in comparison with homozygous carriers of the major allele (AA). Subsequent stratifying surveys revealed that this genetic association with nodal spread was seen only in cases who habitually chewed betel quid (AOR, 0.616; 95% CI, 0.386-0.985;
=0.042) or smoked cigarettes (AOR, 0.612; 95% CI, 0.393-0.953;
=0.029), but undetected in cases free of these main behavioral risks. Our results indicate an interactivity of
rs164966 with lifestyle-related risks on modulating OSCC progression.
In quest to execute emerging deep learning algorithms at edge devices, developing low-power and low-latency deep learning accelerators (DLAs) have become top priority. To achieve this goal, data ...processing techniques in sensor and memory utilizing the array structure have drawn much attention. Processing-in-sensor (PIS) solutions could reduce data transfer; computing-in-memory (CIM) macros could reduce memory access and intermediate data movement. We propose a new architecture to integrate PIS and CIM to realize low-power DLA. The advantages of using these techniques and the challenges from system point-of-view are discussed.
In this paper, a physically tightly coupled, logically loosely coupled, near-memory binary neural network accelerator (PTLL-BNN) is designed and fabricated. Both architecture-level and circuit-level ...optimizations are presented. From the perspective of processor architecture, the PTLL-BNN includes two new design choices. First, the proposed BNN accelerator is placed close to the SRAM of the embedded processors (i.e., physically tightly coupled and near-memory); thus, the extra SRAM cost that is incurred by the accelerator is as low as 0.5 KB. Second, the accelerator is a memory-mapped IO (MMIO) device (i.e., logically loosely coupled), so all embedded processors can be equipped with the proposed accelerator without the burden of changing their compilers and pipelines. From the circuit perspective, this work employs four techniques to optimize the power and costs of the accelerator. First, this design adopts a unified input-kernel-output memory instead of separate ones, which many previous works adopt. Second, the data layout that this work chooses increases the sequentiality of the SRAM accesses and reduces the buffer size of storing the intermediate values. Third, this work innovatively proposes to fuse the max-pooling, batch-normalization, and binarization layers of the BNNs to significantly reduce the hardware complexity. Finally, a novel methodology of generating the scheduler hardware of the accelerator is included. We fabricate the accelerator using the TSMC 180 nm technology. The chip measurement results reach 91 GOP/s on average (307 GOP/s at peak) at 200 MHz. The achieved GOP/s per million logic gates and GOP/s per KB SRAM are 2.6 to 237 times greater than that of previous works, respectively. We also realize an FPGA system to demonstrate the recognition of CIFAR-10/100 images using the fabricated accelerator.
In this paper, we propose a new cell architecture for the orthogonal frequency division multiple access (OFDMA) systems by jointly taking frequency allocation scheme (FAS) and cooperative relay ...strategy into consideration. To serve the mobile stations (MSs) in the inner zone and relay stations (RSs) in the outer zone, a larger portion of frequency spectrum is allocated to the central base station (BS) such that the transmission from BS to RSs can never be a bottleneck during the two-hop relay process. Also, a pair of RSs are assigned the same frequency spectrum to carry out Alamouti coded relay using a half of transmission power (compared with the conventional non-cooperative relay). Depending on the received signal quality, an MS can be served by the central BS or a pair of RSs. Consequently, in addition to the lower interference level by using FAS and half transmission power, the selection and transmission diversity gains can also contribute to a higher capacity and a lower outage probability. The advantage of the proposed cell architecture is proved via simulation and analytical results by taking the intercell interference in the multicell environment and complete channel effects into consideration, including the small and large scale fading. The analytical framework fulfills the task of complete performance analysis in the literature. Some suggestions for future works have also been provided.
Advanced AI edge chips require multibit input (IN), weight (W), and output (OUT) for CNN multiply-and-accumulate (MAC) operations to achieve an inference accuracy that is sufficient for practical ...applications. Computing-in-memory (CIM) is an attractive approach to improve the energy efficiency (EFMAC of MAC operations under a memory-wall constraint. Previous SRAM-CIM macros demonstrated a binary MAC 4, an in-array 8b W-merging with near-memory computing (NMC) using 6T SRAM cells (limited output precision) 5, a 7b1N-1 bW MAC using a 10T SRAM cell (large area) 3, an 4b1N-5bW MAC with a T8T SRAM cell 1, and 8b1N-1bW NMC with 8T SRAM (long MAC latency (TAC)) 2. However, previous works have not achieved high IN/W/OUT precision with fast TAC compact-area, high EFMAC, and robust readout against process variation, due to (1) small sensing margin in word-wise multiple-bit MAC operations, (2) a tradeoff between read accuracy vs. area overhead under process variation, (3) limited EFMAC due to decoupling of software and hardware development.
Nonvolatile computing-in-memory (nvCIM) can improve the latency (t AC ) and energy-efficiency (EF MAC ) of tiny AI edge devices performing multiply-and-accumulate (MAC) computing after system ...wake-up. Prior nvCIMs have proven effective for binary input (IN) and weight (W), and 3b output (OUT) 1, 1-8-1b IN-W-OUT 2, and 2-3-4b IN-W-OUT 3 neural networks; however, the higher precision (4-4b IN-W) for MAC operations is needed for multi-bit CNNs to achieved high-inference accuracy 4. As Fig.15.4.1 shows, improving the precision of nvCIM macros involves various challenges. (1) A large number of activated WLs provides a wide range of BL current (I BL ) resulting in an inaccurate BL-clamping voltage (V BLC ); as well as a large (I BL ) requiring a large array area due to the need for wide metal lines to support high-current density. (2) Previous "WL = input" approaches suffer from: (a) few parallel inputs (IN#) due to (1), and (b) long (t AC ) in multiple cycles of binary WL inputs on 1T1R cells for multibit inputs. (3) Previous positive-negative-split weight-mapping consumes high total (l BL ) and area overhead (needing 2x(m-1) cells for a signed m-bit weight) for cell arrays with high-weight precision. (4) Long (t AC ) and a large number of reference currents (IREF#) for high-precision outputs. To overcome these challenges, this work proposes: (1) a BL-IN-OUT multibit computing (BLIOMC) scheme using a single WL-on and input-aware multibit BL clamping (IA-MBC) to shorten (l BL ) for multibit inputs, increase IN#, and reduce the (l BL ) range/size for accurate (V BLC ) and a compact array area. (2) Scrambled 2's complement (S2C) weight mapping (S2CWM), input-aware source-line (SL) voltage biasing (IA-SLVB), and an S2C value combiner (S2CVC) to reduce area overhead and l BL in the cell array. (3) A dual-bit small-offset current-mode sense amplifier (DbSO-CSA) to reduce IREF# and t AC . A fabricated 22nm 2Mb ReRAM-CIM macro presents the first 4b-input nvCIM macro, featuring a 9.8-18.3ns t AC and an EF MAC of 121.3-28.9TOPS/W from binary to 4bIN-4bW-11bOUT compute precisions.
This paper presents a 0.5V computational CMOS image sensor (C 2 IS) with array-parallel computing capability for always-on feature extraction. By applying the developed pulsed-width modulation (PWM) ...pixel and switch-current integration (SCI), the in-sensor 8-directional matrix-parallel multiply-accumulate (MAC) operation is realized. Moreover, the analog-domain convolution-on-readout (COR) operation, the programmable 3\mathrm{x}3 kernel with \pm 3 -bit weights, and the tunable-resolution column-parallel ADC (1b to 8\mathrm{b} ) are implemented to achieve the real-time feature extraction without use of additional memory. The \mathrm{C}^{2}\mathrm{IS} prototype has been fabricated and verified to demonstrate the raw and feature images at 480\mathrm{fps} with a power consumption of 77/91 (\mathrm{uW} and the resultant \mathrm{FoM} of 9.8/11.6 (pJ/pix/frame), respectively.
In quest to execute emerging deep learning algorithms at edge devices, developing low-power and low-latency deep learning accelerators (DLAs) have become top priority. To achieve this goal, data ...processing techniques in sensor and memory utilizing the array structure have drawn much attention. Processing-in-sensor (PIS) solutions could reduce data transfer; computing-in-memory (CIM) macros could reduce memory access and intermediate data movement. We propose a new architecture to integrate PIS and CIM to realize low-power DLA. The advantages of using these techniques and the challenges from system point-of-view are discussed.
Insight into effect of deuterium isotopes on organic near‐IR (NIR) emitters was explored by the use of self‐assembled Pt(II) complexes H‐3‐f and HPh‐3‐f, and their deuterated analogues D‐3‐f and ...DPh‐3‐f, respectively (Scheme 2). In vacuum deposited thin film, albeit having nearly identical emission spectral feature maximized at ~810 nm, H‐3‐f and D‐3‐f exhibit remarkable difference in photoluminescence quantum yield (PLQY) of 29 % and 50 %, respectively. Distinction in PLQY is also observed for HPh‐3‐f (800 nm, 50 %) and DPh‐3‐f (798 nm, 67 %). We then elucidated the theoretical differences in the impact on near‐infrared (NIR) luminescence between Pt(II) complexes and organic small molecules upon deuteration. The results establish a general guideline for the deuteration on NIR emission efficiency. From a perspective of practical application, NIR OLEDs based on D‐3‐f and DPh‐3‐f emitters attain EQEmax of 15.5 % (radiance 31,287 mW Sr−1 m−2) and 16.6 % (radiance of 32,279 mW Sr−1 m−2) at 764 nm and 796 nm, respectively, both of which set new records for NIR OLEDs of >750 nm.
We have developed general guidelines for the effect of deuterium isotopes on the NIR emission efficiency of Pt(II) complexes and common organic NIR emitters. Also, in this study the NIR OLED based on deuterated Pt(II) complex DPh‐3‐f emitter attains 796 nm electroluminescence with EQEmax of 16.6 % and radiance of 32,279 mW Sr−1 m−2, which sets new records for NIR OLEDs of >750 nm.
