A Review on Soft Ionic Touch Point Sensors

A touch sensor is an essential component in meeting the growing demand for human-machine interfaces.These sensors have been developed in wearable,attachable,and even implantable forms to acquire a wide range of information from humans.To be applied to the human body,sensors are required to be biocompatible and not restrict the natural movement of the body.Ionic materials are a promising candidate for soft touch sensors due to their outstanding properties,which include high stretchability,transparency,ionic conductivity,and biocompatibility.Here,this review discusses the unique features of soft ionic touch point sensors,focusing on the ionic material and its key role in the sensor.The touch sensing mechanisms include piezocapacitive,piezoresistive,surface capacitive,piezoelectric,and triboelectric and triboresistive sensing.This review analyzes the implementation hurdles and future research directions of the soft ionic touch sensors for their transformative potential.

Long Short-Term Memory Recurrent Neural Network-Based Acoustic Model Using Connectionist Temporal Classification on a Large-Scale Training Corpus

A Long Short-Term Memory(LSTM) Recurrent Neural Network(RNN) has driven tremendous improvements on an acoustic model based on Gaussian Mixture Model(GMM). However, these models based on a hybrid method require a forced aligned Hidden Markov Model(HMM) state sequence obtained from the GMM-based acoustic model. Therefore, it requires a long computation time for training both the GMM-based acoustic model and a deep learning-based acoustic model. In order to solve this problem, an acoustic model using CTC algorithm is proposed. CTC algorithm does not require the GMM-based acoustic model because it does not use the forced aligned HMM state sequence. However, previous works on a LSTM RNN-based acoustic model using CTC used a small-scale training corpus. In this paper, the LSTM RNN-based acoustic model using CTC is trained on a large-scale training corpus and its performance is evaluated. The implemented acoustic model has a performance of 6.18% and 15.01% in terms of Word Error Rate(WER) for clean speech and noisy speech, respectively. This is similar to a performance of the acoustic model based on the hybrid method.

Nondestructive Skeletal Imaging of Hyla suweonensis Using Micro-Computed Tomography

We successfully obtained 3D skeletal images of Hyla suweonensis, employing a nondestructive method by applying appropriate anesthesia and limiting the radiation dose. H. suweonensis is a tree frog endemic to Korea and is on the list of endangered species. Previous studies have employed caliper-based measurements and two-dimensional （2D） X-ray imaging for anatomical analyses of the skeletal system or bone types of H. suweonensis. In this work we reconstructed three-dimensional （3D） skeletal images of H. suweonensis, utilizing a nondestructive micro-computed tomography （micro-CT） with a short scan and low radiation dose （i.e. 4 min and 0.16 Gy）. Importantly, our approach can be applied to the imaging of 3D skeletal systems of other endangered frog species, allowing both versatile and high contrast images of anatomical structures without causing any significant damages to the living animal.

Language Model Using Differentiable Neural Computer Based on Forget Gate-Based Memory Deallocation

A differentiable neural computer(DNC)is analogous to the Von Neumann machine with a neural network controller that interacts with an external memory through an attention mechanism.Such DNC’s offer a generalized method for task-specific deep learning models and have demonstrated reliability with reasoning problems.In this study,we apply a DNC to a language model(LM)task.The LM task is one of the reasoning problems,because it can predict the next word using the previous word sequence.However,memory deallocation is a problem in DNCs as some information unrelated to the input sequence is not allocated and remains in the external memory,which degrades performance.Therefore,we propose a forget gatebased memory deallocation(FMD)method,which searches for the minimum value of elements in a forget gate-based retention vector.The forget gatebased retention vector indicates the retention degree of information stored in each external memory address.In experiments,we applied our proposed NTM architecture to LM tasks as a task-specific example and to rescoring for speech recognition as a general-purpose example.For LM tasks,we evaluated DNC using the Penn Treebank and enwik8 LM tasks.Although it does not yield SOTA results in LM tasks,the FMD method exhibits relatively improved performance compared with DNC in terms of bits-per-character.For the speech recognition rescoring tasks,FMD again showed a relative improvement using the LibriSpeech data in terms of word error rate.

Eco-friendly Technologies for Physical and Chemical Recycling of PVC-Related Wasteful Resources

The aim of this study is to enhance the recycled PVC （polyvinyl chloride） related material property by formulation technology and develop the recycling product processing technology furthermore develop the chemical recycling technology for last stage of PVC wastes. The formulation technology is composed of pre-treatment （crushing, separation etc.） and post-treatment （material ratio, additives, stabilizer etc.） to enhance the recyclate property. The formulation for recycled PVC by application basis and processing technology is applied to produce the structural product for civil and construction application such as pipe fittings and water drainage cap for environmental waterway. Also chemical recycling technology for end life PVC scrap which causes environmental pollution by incineration or landfill is studied for producing hydrocarbon and hydrogen chloride for VCM.

Size effects of polydopamine-coated BaTiO_(3) nanoparticles on the piezoelectric performance of P(VDF-TrFE)/BaTiO_(3) composite

The size effect of the polydopamine(PDA)-coated BaTiO_(3)(BTO)(BTO@PDA)nanoparticles(NPs)on the interfacial compatibility between BTO NPs and the polymer matrix and the resultant piezoelectric performance of the composite films remain elusive.In this study,BTO and BTO@PDA NPs of various sizes were incorporated into a P(VDF-TrFE)matrix to prepare two series of P(VDF-TrFE)/BTO and P(VDF-TrFE)/BTO@PDA composites.Subsequently,the effects of the NP size on the dielectric,ferroelectric,and piezoelectric properties of the composite films were comprehensively studied.As the size of the BTO@PDA NPs increased,residual hole defects were clearly observed in the cross section of the composite film.The deteriorated interfacial compatibility due to the large size of the BTO@PDA NPs was also confirmed by the increased dielectric permittivity of the composite film,which was induced by the intensified interfacial polarisation.The P(VDF-TrFE)/BTO@PDA composite with NPs of the smallest size(100 nm)exhibited superior piezoelectric performance owing to the excellent interfacial compatibility between the fillers and the matrix.The piezoelectric performance was significantly enhanced by the reduced leakage current during electrical poling and reduced trap charges.Finally,the pulse waveform originating from the radial artery was precisely measured using the optimised P(VDF-TrFE)/BTO@PDA composite film.

Synergy of Polydopamine‑Assisted Additive Modification and Hierarchical‑Morphology Poly(Vinylidene Fluoride)Nanofiber Mat for Ferroelectric‑Assisted Triboelectric Nanogenerator

In the last decade,numerous physical modification methods have been introduced to enhance triboelectric nanogenerator(TENG)performance although they generally require complex and multiple fabrication processes.This study proposes a facile fabrication process for Poly(vinylidene fluoride)(PVDF)nanofiber(NF)mats incorporating additive and nonadditive physical modifications.Patterned PVDF NF mats are prepared by electrospinning using a metal mesh as the NF collector.As a negative triboelectric material,the TENG with the patterned PVDF NF mat exhibits superior performance owing to the engineered morphology of the contact layer.PVDF is crucial in TENGs owing to its superior ferroelectric properties and surface charge density when combined with specific electroceramics.Hence,the synergy of the physical modification methods is achieved by incorporating BaTiO3(BTO)nanoparticles(NPs)into the PVDF.By functionalizing BTO NPs with polydopamine,the TENG performance is further improved owing to the enhanced dispersion of NPs and improved crystallinity of the PVDF chains.Utilizing large NPs produces a nanopatterning effect on the NF surface,thereby resulting in the hierarchical structure of the NF mats.The source of the voltage signals from the TENG is analyzed using fast Fourier transform.

Overcoming the obstacles of current photodynamic therapy in tumors using nanoparticles

Photodynamic therapy(PDT)has been applied in clinical treatment of tumors for a long time.However,insufficient supply of pivotal factors including photosensitizer(PS),light,and oxygen in tumor tissue dramatically reduces the therapeutic efficacy of PDT.Nanoparticles have received an influx of attention as drug carriers,and recent studies have demonstrated their promising potential to overcome the obstacles of PDT in tumor tissue.Physicochemical optimization for passive targeting,ligand modification for active targeting,and stimuli-responsive release achieved efficient delivery of PS to tumor tissue.Various trials using upconversion NPs,two-photon lasers,X-rays,and bioluminescence have provided clues for efficient methods of light delivery to deep tissue.Attempts have been made to overcome unfavorable tumor microenvironments via artificial oxygen generation,Fenton reaction,and combination with other chemical drugs.In this review,we introduce these creative approaches to addressing the hurdles facing PDT in tumors.In particular,the studies that have been validated in animal experiments are preferred in this review over proof-of-concept studies that were only performed in cells.