Auricular Needle-Embedding Therapy for Treatment of Stubborn Hiccup

Stubborn hiccup refers to the involuntary spasm of the diaphragm, which cannot be relieved by medication of both Chinese and western drugs. Since 1993, the authors of this article have adopted auricular needle-embedding therapy for treatment of this disease, and obtained quite satisfactory therapeutic results. A report follows.

A Linked List Encryption Scheme for Image Steganography without Embedding

Information steganography has received more and more attention from scholars nowadays,especially in the area of image steganography,which uses image content to transmit information and makes the existence of secret information undetectable.To enhance concealment and security,the Steganography without Embedding(SWE)method has proven effective in avoiding image distortion resulting from cover modification.In this paper,a novel encrypted communication scheme for image SWE is proposed.It reconstructs the image into a multi-linked list structure consisting of numerous nodes,where each pixel is transformed into a single node with data and pointer domains.By employing a special addressing algorithm,the optimal linked list corresponding to the secret information can be identified.The receiver can restore the secretmessage fromthe received image using only the list header position information.The scheme is based on the concept of coverless steganography,eliminating the need for any modifications to the cover image.It boasts high concealment and security,along with a complete message restoration rate,making it resistant to steganalysis.Furthermore,this paper proposes linked-list construction schemeswithin theproposedframework,which caneffectively resist a variety of attacks,includingnoise attacks and image compression,demonstrating a certain degree of robustness.To validate the proposed framework,practical tests and comparisons are conducted using multiple datasets.The results affirm the framework’s commendable performance in terms of message reduction rate,hidden writing capacity,and robustness against diverse attacks.

MXene Enhanced 3D Needled Waste Denim Felt for High‑Performance Flexible Supercapacitors

MXene,a transition metal carbide/nitride,has been prominent as an ideal electrochemical active material for supercapacitors.However,the low MXene load limits its practical applications.As environmental concerns and sustainable development become more widely recognized,it is necessary to explore a greener and cleaner technology to recycle textile by-products such as cotton.The present study proposes an effective 3D fabrication method that uses MXene to fabricate waste denim felt into ultralight and flexible supercapacitors through needling and carbonization.The 3D structure provided more sites for loading MXene onto Z-directional fiber bundles,resulting in more efficient ion exchange between the electrolyte and electrodes.Furthermore,the carbonization process removed the specific adverse groups in MXenes,further improving the specific capacitance,energy density,power density and electrical conductivity of supercapacitors.The electrodes achieve a maximum specific capacitance of 1748.5 mF cm-2 and demonstrate remarkable cycling stability maintaining more than 94%after 15,000 galvanostatic charge/discharge cycles.Besides,the obtained supercapacitors present a maximum specific capacitance of 577.5 mF cm^(-2),energy density of 80.2μWh cm^(-2)and power density of 3 mW cm^(-2),respectively.The resulting supercapacitors can be used to develop smart wearable power devices such as smartwatches,laying the foundation for a novel strategy of utilizing waste cotton in a high-quality manner.

Enhancing visual security: An image encryption scheme based on parallel compressive sensing and edge detection embedding

A novel image encryption scheme based on parallel compressive sensing and edge detection embedding technology is proposed to improve visual security. Firstly, the plain image is sparsely represented using the discrete wavelet transform.Then, the coefficient matrix is scrambled and compressed to obtain a size-reduced image using the Fisher–Yates shuffle and parallel compressive sensing. Subsequently, to increase the security of the proposed algorithm, the compressed image is re-encrypted through permutation and diffusion to obtain a noise-like secret image. Finally, an adaptive embedding method based on edge detection for different carrier images is proposed to generate a visually meaningful cipher image. To improve the plaintext sensitivity of the algorithm, the counter mode is combined with the hash function to generate keys for chaotic systems. Additionally, an effective permutation method is designed to scramble the pixels of the compressed image in the re-encryption stage. The simulation results and analyses demonstrate that the proposed algorithm performs well in terms of visual security and decryption quality.

Identification of partial differential equations from noisy data with integrated knowledge discovery and embedding using evolutionary neural networks

Identification of underlying partial differential equations(PDEs)for complex systems remains a formidable challenge.In the present study,a robust PDE identification method is proposed,demonstrating the ability to extract accurate governing equations under noisy conditions without prior knowledge.Specifically,the proposed method combines gene expression programming,one type of evolutionary algorithm capable of generating unseen terms based solely on basic operators and functional terms,with symbolic regression neural networks.These networks are designed to represent explicit functional expressions and optimize them with data gradients.In particular,the specifically designed neural networks can be easily transformed to physical constraints for the training data,embedding the discovered PDEs to further optimize the metadata used for iterative PDE identification.The proposed method has been tested in four canonical PDE cases,validating its effectiveness without preliminary information and confirming its suitability for practical applications across various noise levels.

Time-resolved characteristics of a nanosecond pulsed multi-hollow needle plate packed bed dielectric barrier discharge

In this paper,self-designed multi-hollow needle electrodes are used as a high-voltage electrode in a packed bed dielectric barrier discharge reactor to facilitate fast gas flow through the active discharge area and achieve large-volume stable discharge.The dynamic characteristics of the plasma,the generated active species,and the energy transfer mechanisms in both positive discharge(PD)and negative discharge(ND)are investigated by using fast-exposure intensified charge coupled device(ICCD)images and time-resolved optical emission spectra.The experimental results show that the discharge intensity,number of discharge channels,and discharge volume are obviously enhanced when the multi-needle electrode is replaced by a multihollow needle electrode.During a single voltage pulse period,PD mainly develops in a streamer mode,which results in a stronger discharge current,luminous intensity,and E/N compared with the diffuse mode observed in ND.In PD,as the gap between dielectric beads changes from 0 to250μm,the discharge between the dielectric bead gap changes from a partial discharge to a standing filamentary micro-discharge,which allows the plasma to leave the local area and is conducive to the propagation of surface streamers.In ND,the discharge only appears as a diffusionlike mode between the gap of dielectric beads,regardless of whether there is a discharge gap.Moreover,the generation of excited states N_(2)^(+)(B^(2)∑_(u)^(+))and N2(C^(3)Π_(u))is mainly observed in PD,which is attributed to the higher E/N in PD than that in ND.However,the generation of the OH(A^(2)∑^(+))radical in ND is higher than in PD.It is not directly dominated by E/N,but mainly by the resonant energy transfer process between metastable N_(2)(A^(3)∑_(u)^(+))and OH(X^(2)Π).Furthermore,both PD and ND demonstrate obvious energy relaxation processes of electron-to-vibration and vibration-to-vibration,and no vibration-to-rotation energy relaxation process is observed.

Percutaneous ultrasound-guided coaxial core needle biopsy for the diagnosis of multiple splenic lesions: A case report

BACKGROUND The overlap of imaging manifestations among distinct splenic lesions gives rise to a diagnostic dilemma.Consequently,a definitive diagnosis primarily relies on his-tological results.The ultrasound(US)-guided coaxial core needle biopsy(CNB)not only procures sufficient tissue to help clarify the diagnosis,but reduces the incidence of puncture-related complications.CASE SUMMARY A 41-year-old female,with a history of pulmonary tuberculosis,was admitted to our hospital with multiple indeterminate splenic lesions.Gray-scale ultrasono-graphy demonstrated splenomegaly with numerous well-defined hypoechoic ma-sses.Abdominal contrast-enhanced computed tomography(CT)showed an en-larged spleen with multiple irregular-shaped,peripherally enhancing,hypodense lesions.Positron emission CT revealed numerous abnormal hyperglycemia foci.These imaging findings strongly indicated the possibility of infectious disease as the primary concern,with neoplastic lesions requiring exclusion.To obtain the precise pathological diagnosis,the US-guided coaxial CNB of the spleen was ca-rried out.The patient did not express any discomfort during the procedure.CONCLUSION Percutaneous US-guided coaxial CNB is an excellent and safe option for obtaining precise splenic tissue samples,as it significantly enhances sample yield for exact pathological analysis with minimum trauma to the spleen parenchyma and sur-rounding tissue.

Insider threat detection approach for tobacco industry based on heterogeneous graph embedding

In the tobacco industry,insider employee attack is a thorny problem that is difficult to detect.To solve this issue,this paper proposes an insider threat detection method based on heterogeneous graph embedding.First,the interrelationships between logs are fully considered,and log entries are converted into heterogeneous graphs based on these relationships.Second,the heterogeneous graph embedding is adopted and each log entry is represented as a low-dimensional feature vector.Then,normal logs and malicious logs are classified into different clusters by clustering algorithm to identify malicious logs.Finally,the effectiveness and superiority of the method is verified through experiments on the CERT dataset.The experimental results show that this method has better performance compared to some baseline methods.

Phase II Clinical Study of Three-Dimensional Printed Coplanar Template Combined with CT-Guided Percutaneous Core Needle Biopsy of Pulmonary Nodules in Elderly Patients

Background: As the population age structure gradually ages, more and more elderly people were found to have pulmonary nodules during physical examinations. Most elderly people had underlying diseases such as heart, lung, brain and blood vessels and cannot tolerate surgery. Computed tomography (CT)-guided percutaneous core needle biopsy (CNB) was the first choice for pathological diagnosis and subsequent targeted drugs, immune drugs or ablation treatment. CT-guided percutaneous CNB requires clinicians with rich CNB experience to ensure high CNB accuracy, but it was easy to cause complications such as pneumothorax and hemorrhage. Three-dimensional (3D) printing coplanar template (PCT) combined with CT-guided percutaneous pulmonary CNB biopsy has been used in clinical practice, but there was no prospective, randomized controlled study. Methods: Elderly patients with lung nodules admitted to the Department of Oncology of our hospital from January 2019 to January 2023 were selected. A total of 225 elderly patients were screened, and 30 patients were included after screening. They were randomly divided into experimental group (Group A: 30 cases) and control group (Group B: 30 cases). Group A was given 3D-PCT combined with CT-guided percutaneous pulmonary CNB biopsy, Group B underwent CT-guided percutaneous pulmonary CNB. The primary outcome measure of this study was the accuracy of diagnostic CNB, and the secondary outcome measures were CNB time, number of CNB needles, number of pathological tissues and complications. Results: The diagnostic accuracy of group A and group B was 96.67% and 76.67%, respectively (P = 0.026). There were statistical differences between group A and group B in average CNB time (P = 0.001), number of CNB (1 vs more than 1, P = 0.029), and pathological tissue obtained by CNB (3 vs 1, P = 0.040). There was no statistical difference in the incidence of pneumothorax and hemorrhage between the two groups (P > 0.05). Conclusions: 3D-PCT combined with CT-guided percutaneous CNB can improve the puncture accuracy of elderly patients, shorten the puncture time, reduce the number of punctures, and increase the amount of puncture pathological tissue, without increasing pneumothorax and hemorrhage complications. We look forward to verifying this in a phase III randomized controlled clinical study. .

A chaotic hierarchical encryption/watermark embedding scheme for multi-medical images based on row-column confusion and closed-loop bi-directional diffusion

Security during remote transmission has been an important concern for researchers in recent years.In this paper,a hierarchical encryption multi-image encryption scheme for people with different security levels is designed,and a multiimage encryption(MIE)algorithm with row and column confusion and closed-loop bi-directional diffusion is adopted in the paper.While ensuring secure communication of medical image information,people with different security levels have different levels of decryption keys,and differentiated visual effects can be obtained by using the strong sensitivity of chaotic keys.The highest security level can obtain decrypted images without watermarks,and at the same time,patient information and copyright attribution can be verified by obtaining watermark images.The experimental results show that the scheme is sufficiently secure as an MIE scheme with visualized differences and the encryption and decryption efficiency is significantly improved compared to other works.

Indications for Renal Needle Biopsy and Histological Spectrum of Kidney Disease in Togo

Introduction: The frequent late-stage diagnosis of chronic kidney disease (CKD) constrains the treatment choices for nephrologists. Renal biopsy (RB) is crucial for accurately identifying renal lesions. This key nephrological procedure, however, is invasive and not without potential complications. The purpose of this study was to evaluate the indications, frequency, and histological lesion profiles of renal biopsies in Togo. Materials and Methods: We conducted a descriptive cross-sectional study encompassing all renal biopsies performed in Togo from the inception of nephrology services to the present. Data were compiled from the medical records of the patients. Results: From 2015 to 2023, 68 high-quality renal biopsies were executed in Togo. The patients had an average age of 30.6 years, with a predominance of males (69.1%). The most common indication was nephrotic syndrome, accounting for 66.2% of cases. Histologically, glomerulopathies were predominant, representing 61.8% of lesions, followed by vascular nephropathies (25%) and tubulointerstitial nephropathies (13.2%). The most frequently observed primary glomerulopathy was focal segmental glomerulosclerosis (FSGS). Gross hematuria was the sole complication, occurring in 1.4% of the cases. Conclusion: RB is an evolving practice in Togo. Glomerulopathies are the most commonly observed lesions. The histological categorization of renal lesions is vital for clinicians in their diagnostic reasoning and approach.

Assessment of Knowledge, Attitude and Practices among Healthcare Workers in a Tertiary Care Hospital on Needle Stick Injury

Purpose: Needle-stick injury (NSI) is one of the most potential occupational hazards for healthcare workers because of the transmission of blood-borne pathogens. As per recent data, around 30 lakh healthcare workers sustain Needle stick injuries each year. This study was conducted to assess healthcare workers’ knowledge, attitude and practices regarding needle stick injury. Materials & Methods: A cross-sectional study was conducted in a Tertiary Care Hospital over the period of 3 months. The study population consisted of Intern Doctors, Post Graduate resident Doctors, Staff Nurses, laboratory technicians of Government Medical College and New Civil Hospital, Surat (n = 300). The data were collected using a self-administered questionnaire via the means of Google Forms. Questionnaire was made with prior review literature. The data obtained were entered and analysed in Microsoft Excel. Results: The prevalence of NSI in our study was 46%, with a higher prevalence among the PG residents (72%). Overall scores regarding knowledge and attitude were better in PG residents (knowledge score > 7 in 71% and Attitude Score > 7 in 68% of PG Residents). Even though the PG residents scored highest in the knowledge category, the majority of them suffered needle stick injuries as a result of poor practice scores. Among those who had NSI (n = 139/300), 70% of study participants had superficial injuries, only 9% reported the incident, 18% got medical attention within 2 hours of the incident, and 7% followed up to recheck their viral markers status. Most incidents of NSI were due to hypodermic needles while recapping needles. Conclusion: Exposure to needle stick injuries and their underreporting remains a common problem. It is imperative that healthcare workers receive regular training on the proper handling of sharp objects. We can also draw the conclusion that preventing NSIs requires putting knowledge into practice.

Is magnesium deficiency the major cause of needle chlorosis of Pinus taeda in Brazil?

Needle chlorosis(NC)in Pinus taeda L.systems in Brazil becomes more frequent after second and third harvest rotation cycles.In a study to identify factors contributing to yellowing needle chorosis(YNC),trees were grown in soils originating from contrasting parent materials,and soils and needles(whole,green and chlorotic portions)from 1-and 2-year-old branches and the first and second needle flush release at four sites with YNC on P.taeda were analyzed for various elements and properties.All soils had very low base levels(Ca^(2+),Mg^(2+)and K^(+))and P,suggesting a possible lack of multiple elements.YNC symptoms started at needle tips,then extended toward the needle base with time.First flush needles had longer portions with YNC than second flush needles did.Needles from the lower crown also had more symptoms along their length than those higher in the canopy.Symptoms were similar to those reported for Mg.In chlorotic portions,Mg and Ca concentrations were well below critical values;in particular,Mg levels were only one third of the critical value of 0.3 g kg^(-1).Collectively,results suggest that Mg deficiency is the primary reason for NC of P.taeda in various parent soils in Brazil.

Shelton Vision pushes the needle on Al-assisted quality control

MANCHESTER,UK-Having successfully demonstrated its WebSpector automated fabric inspection system detecting faults on camouflage fabrics at speeds of up to 100metres a minute during ITMA 2023,BTMA member Shelton Vision has secured an unprecedented number of new orders in many fields of the textile industry.The company has subsequently been recruiting additional staff in order to beef up its operations to meet delivery times and to grow capacity for the ongoing increased demand.

Cryptocurrency Transaction Network Embedding From Static and Dynamic Perspectives: An Overview

Cryptocurrency, as a typical application scene of blockchain, has attracted broad interests from both industrial and academic communities. With its rapid development, the cryptocurrency transaction network embedding(CTNE) has become a hot topic. It embeds transaction nodes into low-dimensional feature space while effectively maintaining a network structure,thereby discovering desired patterns demonstrating involved users' normal and abnormal behaviors. Based on a wide investigation into the state-of-the-art CTNE, this survey has made the following efforts: 1) categorizing recent progress of CTNE methods, 2) summarizing the publicly available cryptocurrency transaction network datasets, 3) evaluating several widely-adopted methods to show their performance in several typical evaluation protocols, and 4) discussing the future trends of CTNE. By doing so, it strives to provide a systematic and comprehensive overview of existing CTNE methods from static to dynamic perspectives,thereby promoting further research into this emerging and important field.

History and Development of Zhuang Medicine Shallow Needling from Bone Needle,Pottery Needle,and Bronze Needle to Electroacupuncture

Zhuang medicine shallow needling has a long history and plays a significant role in Chinese medicine.With the development of medical treatment in China,there is a constant improvement in the use of needles.Bone needles have been modified to pottery needles,bronze needles,and electroacupuncture.From this long development history,there are some improvements in terms of material and technology.By analyzing and comparing the primitive and current acupuncture instruments used in China and their therapeutic effects,it can be seen that China’s medical treatment is constantly improving and will continue to improve with technology.

Future Event Prediction Based on Temporal Knowledge Graph Embedding

Accurate prediction of future events brings great benefits and reduces losses for society in many domains,such as civil unrest,pandemics,and crimes.Knowledge graph is a general language for describing and modeling complex systems.Different types of events continually occur,which are often related to historical and concurrent events.In this paper,we formalize the future event prediction as a temporal knowledge graph reasoning problem.Most existing studies either conduct reasoning on static knowledge graphs or assume knowledges graphs of all timestamps are available during the training process.As a result,they cannot effectively reason over temporal knowledge graphs and predict events happening in the future.To address this problem,some recent works learn to infer future events based on historical eventbased temporal knowledge graphs.However,these methods do not comprehensively consider the latent patterns and influences behind historical events and concurrent events simultaneously.This paper proposes a new graph representation learning model,namely Recurrent Event Graph ATtention Network(RE-GAT),based on a novel historical and concurrent events attention-aware mechanism by modeling the event knowledge graph sequence recurrently.More specifically,our RE-GAT uses an attention-based historical events embedding module to encode past events,and employs an attention-based concurrent events embedding module to model the associations of events at the same timestamp.A translation-based decoder module and a learning objective are developed to optimize the embeddings of entities and relations.We evaluate our proposed method on four benchmark datasets.Extensive experimental results demonstrate the superiority of our RE-GAT model comparing to various base-lines,which proves that our method can more accurately predict what events are going to happen.

Nylon 6-cellulose composite hosted in a hypodermic needle: Biofluid extraction and analysis by ambient mass spectrometry in a single device

This study proposes a hypodermic needle(HN)as a sorbent holder and an electrospray(ESI)emitter,thus combining extraction and analysis in a single device.A novel nylon 6-cellulose(N6-Cel)composite sorbent is proposed to extract methadone from oral fluid samples.The cellulosic substrate provides the composite with high porosity,permitting the flow-through of the sample,while the polyamide contributes to the extraction of the analyte.The low price of the devices(considering the holder and the sorbent)contributes to the affordability of the method,and their small size allows easy transportation,opening the door to on-site extractions.Under the optimum conditions,the analyte can be determined by high-resolution ambient ionization mass spectrometry at a limit of detection(LOD)as low as 0.3 mg/L and precision(expressed as relative standard deviation,RSD)better than 9.3%.The trueness,expressed as relative recovery(RR),ranged from 90%to 109%.As high-resolution mass spectrometers are not available in many laboratories,the method was also adapted to low-resolution spectrometers.In this sense,the direct infusion of the eluates in a triple quadrupole-mass spectrometry provided an LOD of 2.2 mg/L.The RSD was better than 5.3%,and the RR ranged from 96%to 121%.

Extrapolation over temporal knowledge graph via hyperbolic embedding

Predicting potential facts in the future,Temporal Knowledge Graph(TKG)extrapolation remains challenging because of the deep dependence between the temporal association and semantic patterns of facts.Intuitively,facts(events)that happened at different timestamps have different influences on future events,which can be attributed to a hierarchy among not only facts but also relevant entities.Therefore,it is crucial to pay more attention to important entities and events when forecasting the future.However,most existing methods focus on reasoning over temporally evolving facts or mining evolutional patterns from known facts,which may be affected by the diversity and variability of the evolution,and they might fail to attach importance to facts that matter.Hyperbolic geometry was proved to be effective in capturing hierarchical patterns among data,which is considered to be a solution for modelling hierarchical relations among facts.To this end,we propose ReTIN,a novel model integrating real-time influence of historical facts for TKG reasoning based on hyperbolic geometry,which provides low-dimensional embeddings to capture latent hierarchical structures and other rich semantic patterns of the existing TKG.Considering both real-time and global features of TKG boosts the adaptation of ReTIN to the ever-changing dynamics and inherent constraints.Extensive experiments on benchmarks demonstrate the superiority of ReTIN over various baselines.The ablation study further supports the value of exploiting temporal information.

Enhanced Image Captioning Using Features Concatenation and Efficient Pre-Trained Word Embedding

One of the issues in Computer Vision is the automatic development of descriptions for images,sometimes known as image captioning.Deep Learning techniques have made significant progress in this area.The typical architecture of image captioning systems consists mainly of an image feature extractor subsystem followed by a caption generation lingual subsystem.This paper aims to find optimized models for these two subsystems.For the image feature extraction subsystem,the research tested eight different concatenations of pairs of vision models to get among them the most expressive extracted feature vector of the image.For the caption generation lingual subsystem,this paper tested three different pre-trained language embedding models:Glove(Global Vectors for Word Representation),BERT(Bidirectional Encoder Representations from Transformers),and TaCL(Token-aware Contrastive Learning),to select from them the most accurate pre-trained language embedding model.Our experiments showed that building an image captioning system that uses a concatenation of the two Transformer based models SWIN(Shiftedwindow)and PVT(PyramidVision Transformer)as an image feature extractor,combined with the TaCL language embedding model is the best result among the other combinations.