A Case Report and Literature Review: A Case of Delayed Bile Leakage Following Laparoscopic Cholecystectomy

Background: Delayed bile leakage after laparoscopic cholecystectomy, defined as occurring more than 72 hours after surgery, is a rare and serious complication of laparoscopic cholecystectomy, with an incidence rate of 0.060%. Case Declaration: This case report details a patient diagnosed with delayed bile leakage 43 days after laparoscopic cholecystectomy. The patient was discharged from our hospital after undergoing CT-guided puncture treatment, with no obvious complications identified. The patient was monitored for one year following the procedure, during which time no significant discomfort was reported. Objective: This case report is to analyse and review the clinical manifestations, diagnosis, treatment and prevention of delayed bile leakage after cholecystectomy, with reference to the relevant literature. Results: Delayed bile leakage after laparoscopic cholecystectomy can be prevented, although not eliminated. It is recommended that the operator treat the operation with caution, avoid taking risks, and adhere to careful procedures and strict separation according to the requirements. This approach is key to preventing late bile leakage in the postoperative period.

Impulsive effect on exponential synchronization of neural networks with leakage delay under sampled-data feedback control

We consider the impulsive effect on the exponential synchronization of neural networks with leakage delay under the sampled-data feedback control. We use an appropriate Lyapunov-Krasovskii functional combined with the input delay approach and some inequality techniques to derive sufficient conditions that ensure the exponential synchronization of the delayed neural network. The conditions are formulated in terms of the leakage delay, the sampling period, and the exponential convergence rate. Numerical examples are given to demonstrate the usefulness and the effectiveness of the results.

Existence and Exponential Stability of Almost Periodic Solutions to General BAM Neural Networks with Leakage Delays on Time Scales

In this paper, the existence of almost periodic solutions to general BAM neural networks with leakage delays on time scales is first studied, by using the exponential dichotomy method of linear differential equations and fixed point theorem. Then, the exponential stability of almost periodic solutions to such BAM neural networks on time scales is discussed by utilizing differential inequality. Finally, an example is given to support our results in this paper and the results are up-to-date.

Late presentation of dural tears:Two case reports and review of literature

BACKGROUND The late presentation of dural tears(LPDT)has a low incidence rate and hidden symptoms and is easily ignored in clinical practice.If the disease is not treated in time,a series of complications may occur,including low intracranial pressure headache,infection,pseudodural cyst formation,and sinus formation.Here,we describe two cases of LPDT.CASE SUMMARY Two patients had sudden fever 1 wk after lumbar surgery.Physical examination showed obvious tenderness in the operation area.The patients were confirmed as having LPDT by lumbar magnetic resonance imaging and surgical exploration.One case was caused by continuous negative pressure suction and malnutrition,and the other was caused by decreased dural ductility and low postoperative nutritional status.The first symptom of both patients was fever,with occasional headache.Both patients underwent secondary surgery to treat the LPDT.Dural defects were observed and dural sealants were used to seal the dural defects,then drainage tubes were retained for drainage.After the operation,the patients were treated with antibiotics and the patients’surgical incisions healed well,without fever or incision tenderness.Both recovered and were discharged 1 wk after the operation.CONCLUSION LPDT is a rare complication of spinal surgery or neurosurgery that has hidden symptoms and can easily be overlooked.Since it may cause a series of complic-ations,LPDT needs to be actively addressed in clinical practice.

Stability analysis for a class of impulsive competitive neural networks with leakage time-varying delays

In this paper, we consider the existence, the uniqueness, the global exponential stability, the global asymptotic stability, the uniform asymptotic stability and the uniform stability of the equilibrium point of impulsive competitive neural networks with distributed delays and leakage time-varying delays. The existence of a unique equilibrium point is proved by using Brouwer's fixed point theorem. By finding suitable Lyapunov-Krasovskii functional, some sufficient conditions are derived ensuring some kinds of stability. Finally, several examples and their simulations are given to illustrate the effectiveness of the obtained results.

Stochastic synchronization of neutral-type chaotic impulse neural networks with leakage delay and Markovian jumping parameters

Purpose-The purpose of this paper is to develop a methodology for the stochastically asymptotic synchronization problem for a class of neutral-type chaotic neural networks with both leakage delay and Markovian jumping parameters under impulsive perturbations.Design/methodology/approach-The authors perform drive-response concept and time-delay feedback control techniques to investigate a class of neutral-type chaotic neural networks with both leakage delay and Markovian jumping parameters under impulsive perturbations.New sufficient criterion is established without strict conditions imposed on the activation functions.Findings-It turns out that the approach results in new sufficient criterion easy to be verified but without the usual assumption of the differentiability and monotonicity of the activation functions.Two examples show the effectiveness of the obtained results.Originality/value-The novelty of the proposed approach lies in removing the usual assumption of the differentiability and monotonicity of the activation functions,and the use of the Lyapunov functionalmethod,Jensen integral inequality,a novel Gu’s lemma,reciprocal convex and linear convex combination technique for the stochastically asymptotic synchronization problem for a class of neutral-type chaotic neural networks with both leakage delay and Markovian jumping parameters under impulsive perturbations.

Periodic oscillation of memristor-based recurrent neural networks with time-varying delays and leakage delays

Purpose–The purpose of this paper is to investigate the existence and global exponential stability of periodic solution of memristor-based recurrent neural networks with time-varying delays and leakage delays.Design/methodology/approach–The differential inequality theory and some novel mathematical analysis techniques are applied.Findings–A set of sufficient conditions which guarantee the existence and global exponential stability of periodic solution of involved model is derived.Practical implications–It plays an important role in designing the neural networks.Originality/value–The obtained results of this paper are new and complement some previous studies.The innovation of this paper concludes two aspects:the analysis on the existence and global exponential stability of periodic solution of memristor-based recurrent neural networks with time-varying delays and leakage delays is first proposed;and it is first time to establish the sufficient criterion which ensures the existence and global exponential stability of periodic solution of memristor-based recurrent neural networks with time-varying delays and leakage delays.

Improvement in Sensing Accuracy of an OFDM-Based W-Band System

Orthogonal frequency division multiplexing (OFDM) waveform is promising to converge communications and sensing functionalities for future wireless applications. This paper presents a novel method to improve the OFDM-based sensing accuracy by estimating the delay/Doppler leakages in the channel matrix, which is constructed by the received and the transmitted OFDM symbols. Both simulation and proof-of-concept experiment validate the proposed method for sensing improvement.The experiment uses a heterodyne W-band system at 97 GHz to transmit and receive an OFDM waveform of bandwidth 3.9 GHz.We achieve an improvement in sensing accuracy by an order of magnitude which is significant for OFDM-based converged systems.

A boosted negative bit-line SRAM with write-assisted cell in 45 nm CMOS technology

A new 11 T SRAM cell with write-assist is proposed to improve operation at low supply voltage. In this technique, a negative bit-line voltage is applied to one of the write bit-lines, while a boosted voltage is applied to the other write bit-line where transmission gate access is used in proposed 11 T cell. Supply voltage to one of the inverters is interrupted to weaken the feedback. Improved write feature is attributed to strengthened write access devices and weakened feedback loop of cell at the same time. Amount of boosting required for write performance improvement is also reduced due to feedback weakening, solving the persistent problem of half-selected cells and reliability reduction of access devices with the other suggested boosted and negative bit-line techniques. The proposed design improves write time by 79%, 63% and slower by 52% with respect to LP 10 T, WRE 8 T and 6 T cells respectively. It is found that write margin for the proposed cell is improved by about 4×, 2.4× and 5.37× compared to WRE8 T, LP10 T and 6 T respectively. The proposed cell with boosted negative bit line（BNBL） provides47%, 31%, and 68.4% improvement in write margin with respect to no write-assist, negative bit line（NBL） and boosted bit line（BBL） write-assist respectively. Also, new sensing circuit with replica bit-line is proposed to give a more precise timing of applying boosted voltages for improved results. All simulations are done on TSMC 45 nm CMOS technology.

Impulsive multidirectional associative memory neural net works:New results

An Impulsive Multidirectional Associative Memory Neural Network(IMAMNN)with time-varying and leakage delays is proposed.Through the use of a continuation theorem of coincidence degree theory and differential inequality techniques we establish new conditions for the existence and exponential stability of anti-periodic solutions for the model considered in this work.Moreover,two examples and its numerical simulations are presented to show the validity and the effectiveness of the results.