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Spinal dural arteriovenous fistula (SDAVF) is known for its ambiguous and various clinical presentations. Among these presentations, congestive myelopathy is one of the most common, yet it is challenging to correctly diagnose SDAVF at initial presentation. Several diseases present as myelopathy, including demyelinating diseases. Herein, we present two cases of congestive myelopathy due to SDAVF presenting to the emergency room (ER) with progressive quadriparesis. Even though the patients had a proper magnetic resonance imaging (MRI) examination from the initial presentation, there was a delay in making a final diagnosis. Both patients’ clinical presentation and MRI mimicked central nervous system (CNS) demyelinating disease initially, and a more thorough examination revealed SDAVF. Such a delay in diagnosis can result in more neurological deterioration and may result in more sequelae. Hence, SDAVF should always be considered as a differential diagnosis when examining patients with myelopathy.

Cytotoxic lesions of the corpus callosum (CLOCC) are secondary lesions on corpus callosum caused by cytokinopathy of callosal neurons and microglia. Fever, headache, and digestive disturbances are common symptoms. Reversible and hyperintense signals on fluid‐attenuated inversion recovery imaging, diffusion‐weighted imaging (DWI) and decreased apparent diffusion coefficient are typical features of magnetic resonance imaging. Herein, we report a rare case of CLOCC caused by COVID19 vaccination (BNT162b) and discharged without no neurologic symptoms due to prompt treatment.

Prevertebral tuberculosis is a rare infectious disease that often affects immunocompromised patients in developing countries. We present the case of a patient who complained of headache, dysarthria, and dysphagia. Neurological examination revealed multiple cranial nerve palsies, including the hypoglossal, glossopharyngeal, and vagus nerves. Brain magnetic resonance imaging demonstrated an infiltrative lesion in the prevertebral space, and the biopsy revealed chronic inflammation. On suspicion of immune-mediated inflammation, the patient was treated with intravenous dexamethasone and oral prednisolone, with minimal response. Eleven months after the initial diagnosis, the patient’s neurological symptoms were aggravated, and we detected newly developed pulmonary tuberculosis. After the treatment of pulmonary tuberculosis, his neurological symptoms improved, and the imaging study demonstrated improvements. Although we lacked positive laboratory or biopsy results for tuberculosis, we suspect that the lesions were distant tuberculosis infections. Tuberculosis should be considered in patients with unknown infiltrative mass-like lesions in the prevertebral spaces.

Background: Nitrous oxide (N2O) is used in surgery and dentistry for its anesthetic and analgesic effects. However, neurological and psychiatric manifestations of N2O abuse have been increasingly reported among Korean adults. The aim of this study was to demonstrate laboratory findings of N2O abuse in Korean patients.Methods: Patients diagnosed with N2O-induced neuropathy or myelopathy from August 2018 to December 2019 were enrolled. Their clinical presentations and laboratory and imaging findings were analyzed.Results: Sensory changes and limb weakness were present in nine of the enrolled patients. The laboratory findings revealed that seven patients had high homocysteine levels and five had high methylmalonic acid levels in their blood. Nerve conductions studies indicated that axonal neuropathy was present in four cases and longer F-wave and Hoffman’s-reflex latencies were present in two cases. Signal changes in cervical spine imaging occurred in five patients, while two had normal results.Conclusions: Chronic N2O abuse can cause neurological damage or psychiatric problems. Because N2O is illegal for recreational use in Korea, patients tend to hide their history of use. Even though the spinal imaging results were normal, clinicians should consider the possibility of N2O use, and further electrophysiological tests should be applied for precise evaluations.

This paper deals with the development of a mathematical dynamic model and observer-based set point control of a vapor compression cycle (VCC) system. The mean void fraction and moving boundary control volumes in a heat exchanger (HEX) are used for a lumped parameter model of an air conditioning system. A multi-input multi-output (MIMO) dynamic model of the VCC is presented in a nonlinear state space representation and is reformulated into a linearized regular form for control design. A modified observer-based controller with sliding mode control (SMC) is introduced to attenuate the effects of observing approximation errors and external disturbances. In the design of the discontinuous controller, a new type of gain function is introduced to reduce the time to reach the sliding mode compared to a conventional discontinuous gain. The proposed control methodology ensures uniformly ultimately bounded tracking results of the desired low pressure and suction superheat. A simulation of controlling the VCC illustrates the effectiveness and performance in the presence of disturbances.

In this paper, we control an air conditioner system thought the application of a newly developed Intelligent Proportional Integral (i-PI) Controller that regulate a zone temperature to desired setpoint temperature. This method approximates the unknown nonlinear system function and is applied to the problem of controlling compressor for a vapor compression cycle system where evaporating pressure target is automatically determined by the i-PI so that zone temperature is met to desired setpoint.

This paper deals with an adaptive robust tracking control using a multilayer neural network (NN) for a class of nonlinear dynamic systems with unknown time varying state delays. Typical adaptive NN backstepping controllers for uncertain nonlinear systems with time-delay give rise to computation complexity caused by the the repeated derivatives of virtual controllers and nonlinear functions. Moreover, the combined techniques usually result in only uniformly ultimately bounded (UUB) stability caused by the inherent NN approximation error. This paper presents a control scheme that uses an integral sliding mode control as a feedback term and an adaptive neural controller as a feedforward term based on the desired compensation adaptive law (DCAL) technique. First, we develop a new DCAL formulation which avoids the explosion of complexity caused by the general NN backstepping scheme to compensate for nonlinear system uncertainties, bounded system disturbances, and unknown state time delays. Then, using a Lyapunov-Krasovskii (LK) functional, it is shown that the proposed controller renders the class of uncertain nonlinear time-delay systems asymptotically stable.

Though conventional implants have a capability of pressure regulation, they cannot maintain the intra-ocular pressure (IOP) desired for different patients. To solve these problems, an active glaucoma implant which consists of the valve actuator, pressure sensor, controller, and power supply, has been developed. In this paper, we first analyse of the operation of the conventional implant using a bond graph, and show its defects and limitations of the conventional valve analytically. Next, we design and analyze an electromagnetically driven valve actuator composed of a membrane, air-core solenoid, permanent magnet, and covering frame. To save the electrical power for operating the valve actuator, appropriate actuating methods are suggested and an optimal design of the valve actuator is carried out. Finally, using simulations, the possibility of the proposed valve actuator is investigated.

The aim of this research is to develop an intelligent tutoring system (ITS) which teaches students the causal relationships between the components of the circulatory physiology system and the complex behavior of the negative feedback system that stabilizes blood pressure. This system will accept natural language input from students and generate limited natural language explanations. It contains rules that identify the student's errors and build a “bug-based” student model. It uses tutoring rules to plan each response based on its model of the student and the dialog history so that it can tailor the dialog to fit the student's learning needs. The tutoring rule interpreter manages the dialog and determines strategy and tactics to achieve its educational goals.