A Fiber-Optical Dosimetry Sensor for Gamma-Ray Irradiation Measurement in Biological Applications.

In this paper, we propose a novel fiber-optical dosimetry sensor for radiation measurement in biological applications. A two-dimensional (2D) fiber-optical dosimeter (FOD) for radiation measurement is considered. The sensors are arranged as a 2D array in a tailored holder. This FOD targets accurate industrial and medical applications which seek more tolerant radiation dosimeters. In this paper, the FOD sensors are subjected to gamma-ray radiation facilities from the 137Cs gamma-ray irradiator type for low doses and 60Co gamma-ray irradiator for high doses. For better evaluation of radiation effects on the FOD sample, the measurements are performed using eight sensors (hollow cylinder shape) with two samples in each dose. The sensors were measured before and after each irradiation. To the author's knowledge, the measurements of FOD transplanted inside animals are presented for the first time in this paper. A 2D simulation program has been implemented for numerical simulation based on the attenuation factors from the absorbed dose inside the in vivo models. A comparison between the FOD and the standard thermo-luminescence detector is presented based on the test of in vivo animal models. The results indicate that the proposed FOD sensor is more stable and has higher sensitivity.

An Optical Universal Plasmon-Based Biosensor for Virus Detection.

Purpose: Kretschmann-configuration has been used as a subwavelength framework to detect tiny alterations of the refractive index of biomaterials. However, most of the theoretical assessment of such configuration is usually based on the plane wave excitation transfer matrix method (TMM) of prism- coupled to thin metal film supporting plasmonic modes. Accordingly, a better theoretical framework than the plane wave approximation is indispensable for reliable and accurate assessments and simulations. A reformulated form of the traditional FFT-BPM has been adapted to evaluate the performance and characteristics of surface plasmonic waveguide biosensor. Method: Surface plasmon mode is excited by a sub-wavelength narrow light beam. The highly confined optical energy of that plasmonic mode enables an efficient means to detect tiny variations in the composition of the analyte in contact with the metallic layer of the surface plasmon guide. The plasmonic guided power is detected thereafter electronically via an optical MOS capacitor. Results: the guided plasmonic power has been used to assess the fundamental characteristics and performance of the sensor, namely the linearity, sensitivity, and figure of merit as well as the full width at half maximum (FWHM). Conclusion: The proposed sensor could be integrated to a wide class of angular measurement system (for instance goniometer) or via electronic detection of the optical plasmonic guided power. we claim that this work is worthy of being shared with researchers and developers interested in the experimentation and assessment of sensitive biosensors; especially in case when complicated and sophisticated analysis tools represent an unpleasant burden.

Development and feasibility of a virtual reality-based exergaming program to enhance cardiopulmonary fitness in children with developmental coordination disorder.

Introduction: Developmental coordination disorder (DCD) is a neurodevelopmental disorder characterized by motor skill deficits. Such deficits often limit children's participation in physical activities, further affecting their overall health, including through reduced cardiopulmonary fitness. Because virtual reality (VR) devices offer interactive games and activities that require various movements and coordination, they can serve as motivating and enjoyable means for children to perform physical exercise. In this study, we developed a VR-based exergaming system and tested its ability to enhance the cardiopulmonary fitness of children with DCD. Materials and methods: A total of 13 children with DCD and 10 young adults were recruited in phase I to examine the test-retest reliability and concurrent validity of our system (including a custom-made heart rate monitor) with a commercial heart rate device. In phase II, we included an additional 13 children with DCD to test the feasibility of the system. We tested the outcomes using the enjoyment rating scale, intrinsic motivation inventory (IMI), and 20-m shuttle run test (20mSRT). Results: In phase I, test-retest reliability was good to excellent in the static task and moderate to good in the dynamic task. Concurrent validity was excellent in both tasks. In phase II, more than half of the children (18 out of 26) assigned the maximum rating for their enjoyment of the game; they also had high average scores on the IMI. Furthermore, after the 8-week training using the VR program, the average running distance of the 26 children in the 20mSRT had increased significantly from 129.23 m to 176.92 m (p < 0.001). Conclusion: Our VR-based exergaming program can serve as an alternative intervention for enhancing cardiopulmonary fitness in children with DCD.

Real-Time Internet of Medical Things System for Detecting Blood Leakage during Hemodialysis Using a Novel Multiple Concentric Ring Sensor.

Venous needle dislodgement (VND) is a major healthcare safety concern in patients undergoing hemodialysis. Although VND is uncommon, it can be life-threatening. The main objective of this study was to implement a real-time multi-bed monitoring system for VND by combining a novel leakage-detection device and IoMT (Internet of Medical Things) technology. The core of the system, the Acusense IoMT platform, consisted of a novel leakage-detection patch comprised of multiple concentric rings to detect blood leakage and quantify the leaked volume. The performance of the leakage-detection system was evaluated on a prosthetic arm and clinical study. Patients with a high risk of blood leakage were recruited as candidates. The system was set up in a hospital, and the subjects were monitored for 2 months. During the pre-clinical simulation experiment, the system could detect blood leakage volumes from 0.3 to 0.9 mL. During the test of the IoMT system, the overall success rate of tests was 100%, with no lost data packets. A total of 701 dialysis sessions were analyzed, and the accuracy and sensitivity were 99.7% and 90.9%, respectively. Evaluation questionnaires showed that the use of the system after training changed attitudes and reduced worry of the nursing staff. Our results show the feasibility of using a novel detector combined with an IoMT system to automatically monitor multi-bed blood leakage. The innovative concentric-circle design could more precisely control the warning blood-leakage threshold in any direction to achieve clinical cost-effectiveness. The system reduced the load on medical staff and improved patient safety. In the future, it could also be applied to home hemodialysis for telemedicine during the era of COVID-19.

An Improved Sensing Method of a Robotic Ultrasound System for Real-Time Force and Angle Calibration.

An ultrasonic examination is a clinically universal and safe examination method, and with the development of telemedicine and precision medicine, the robotic ultrasound system (RUS) integrated with a robotic arm and ultrasound imaging system receives increasing attention. As the RUS requires precision and reproducibility, it is important to monitor the real-time calibration of the RUS during examination, especially the angle of the probe for image detection and its force on the surface. Additionally, to speed up the integration of the RUS and the current medical ultrasound system (US), the current RUSs mostly use a self-designed fixture to connect the probe to the arm. If the fixture has inconsistencies, it may cause an operating error. In order to improve its resilience, this study proposed an improved sensing method for real-time force and angle calibration. Based on multichannel pressure sensors, an inertial measurement unit (IMU), and a novel sensing structure, the ultrasonic probe and robotic arm could be simply and rapidly combined, which rendered real-time force and angle calibration at a low cost. The experimental results show that the average success rate of the downforce position identification achieved was 88.2%. The phantom experiment indicated that the method could assist the RUS in the real-time calibration of both force and angle during an examination.

The impact of multi-person virtual reality competitive learning on anatomy education: a randomized controlled study.

BACKGROUND: Anatomy is one of the core subjects in medical education. Students spend considerable time and effort on learning the requisite anatomy knowledge. This study explored the effect of a multiple-player virtual reality (VR) gaming system on anatomy learning. METHODS: 18 participants were randomly assigned into 3 learning conditions: (1) a textbook reading control group (CG), (2) a single-player VR (SP) group; and (3) a multiple-player VR (MP) group. The participants studied anatomy for 5 days, and completed a multiple-choice test on Days 1, 5, and 12. In the VR environment, the participants used handheld controllers to move the simulated tissues. The mission of the game was to complete puzzles of a human body. The SP and MP groups filled out a motivation inventory on Day 5. The scores on the multiple-choice test, the correct assembly rates, and the motivation inventory scores were analyzed using the 2-way ANOVA or independent t-test to compare group differences. RESULTS: There was a significant interaction effect of group and timepoint (p = 0.003) in the multiple-choice test. In the CG, the scores on Day 1, Day 5, and Day 12 were significantly different (p < 0.001). The scores on Day 5 were significantly higher than those on Day 1 (p < 0.001). Although the scores declined slightly on Day 12, they were still significantly higher than those on Day 1 (p < 0.001). The SP and MP groups had similar results (p < 0.001, p < 0.001). The differences between the groups were only significant on Day 12 (p = 0.003), not Day 5 (p = 0.06). On Day 12, the scores of the MP group were higher than those of the CG (p = 0.002). The SP group and MP group had high scores on the interest, competence, and importance subscales of the motivation inventory. Both VR groups considered the system to be fun and beneficial to their learning. However, the MP group reported higher stress levels than the SP group. CONCLUSION: The results indicated that the proposed VR learning system had a positive impact on the anatomy learning. Although the between-player competition caused higher stress levels for the VR groups, the stress could have been a mediator of their learning outcomes. TRIAL REGISTRATION: ETRD, ETRD-D-19-00573. Registered 20 December 2018, http://www.edah.org.tw/irb/index.htm.

A Real-Time Speech Separation Method Based on Camera and Microphone Array Sensors Fusion Approach.

In the context of assisted human, identifying and enhancing non-stationary speech targets speech in various noise environments, such as a cocktail party, is an important issue for real-time speech separation. Previous studies mostly used microphone signal processing to perform target speech separation and analysis, such as feature recognition through a large amount of training data and supervised machine learning. The method was suitable for stationary noise suppression, but relatively limited for non-stationary noise and difficult to meet the real-time processing requirement. In this study, we propose a real-time speech separation method based on an approach that combines an optical camera and a microphone array. The method was divided into two stages. Stage 1 used computer vision technology with the camera to detect and identify interest targets and evaluate source angles and distance. Stage 2 used beamforming technology with microphone array to enhance and separate the target speech sound. The asynchronous update function was utilized to integrate the beamforming control and speech processing to reduce the effect of the processing delay. The experimental results show that the noise reduction in various stationary and non-stationary noise environments were 6.1 dB and 5.2 dB respectively. The response time of speech processing was less than 10ms, which meets the requirements of a real-time system. The proposed method has high potential to be applied in auxiliary listening systems or machine language processing like intelligent personal assistant.

A Clinical Trial of the Effect of a Blood Leakage Detection Device for Patients during Hemodialysis.

In hemodialysis, vascular access is usually achieved through an arteriovenous fistula, and a dislodged needle can cause varying degrees of injury to patients. In severe cases, the loss of blood can prove to be fatal. This study proposed a blood leakage detection device for patients during hemodialysis (HD). First, the device was tested on a phantom arm, and later in a clinical test on patients receiving HD. The thoughts of the patients and the nursing staff involved were surveyed before and after the introduction of the device. Analysis of the results indicated that the device achieved 100% and 98.9% accuracy rates on the phantom arm test and clinical test, respectively. The results suggested that patients believed the device could reduce their mental anxiety, and the nursing staff considered the device reliable and that it would enhance the quality of care. The proposed detection device can be extended to similar applications for preventing catheter dislodgement, and to improve patient safety and reduce the stress of clinical nursing staff.

A Scoping Review of The Efficacy of Virtual Reality and Exergaming on Patients of Musculoskeletal System Disorder.

To assess the effects of virtual reality on patients with musculoskeletal disorders by means of a scoping review of randomized controlled trials (RCTs). The databases included PubMed, IEEE, and the MEDLINE database. Articles involving RCTs with higher than five points on the Physiotherapy Evidence Database (PEDro) scale were reviewed for suitability and inclusion. The methodological quality of the included RCT was evaluated using the PEDro scale. The three reviewers extracted relevant information from the included studies. Fourteen RCT articles were included. When compared with simple usual care or other forms of treatment, there was significant pain relief, increased functional capacity, reduced symptoms of the disorder, and increased joint angles for the virtual reality treatment of chronic musculoskeletal disorders. Furthermore, burn patients with acute pain were able to experience a significant therapeutic effect on pain relief. However, virtual reality treatment of patients with non-chronic pain such as total knee replacement, ankle sprains, as well as those who went through very short virtual reality treatments, did not show a significant difference in parameters, as compared with simple usual care and other forms of treatment. Current evidence supports VR treatment as having a significant effect on pain relief, increased joint mobility, or motor function of patients with chronic musculoskeletal disorders. VR seems quite effective in relieving the pain of patients with acute burns as well.

Development of a Wireless Mesh Sensing System with High-Sensitivity LiNbO3 Vibration Sensors for Robotic Arm Monitoring.

In recent years, multi-axis robots are indispensable in automated factories due to the rapid development of Industry 4.0. Many related processes were required to have the increasing demand for accuracy, reproducibility, and abnormal detection. The monitoring function and immediate feedback for correction is more and more important. This present study integrated a highly sensitive lithium niobate (LiNbO3) vibration sensor as a sensor node (SN) and architecture of wireless mesh network (WMN) to develop a monitoring system (MS) for the robotic arm. The advantages of the thin-film LiNbO3 piezoelectric sensor were low-cost, high-sensitivity and good electrical compatibility. The experimental results obtained from the vibration platform show that the sensitivity achieved 50 mV/g and the reaction time within 1 ms. The results of on-site testing indicated that the SN could be configured on the relevant equipment quickly and detect the abnormal vibration in specific equipment effectively. Each SN could be used more than 10 h at the 80 Hz transmission rate under WMN architecture and the loss rate of transmission was less than 0.01% within 20 m.

Electrochemical immunosensor utilizing electrodeposited Au nanocrystals and dielectrophoretically trapped PS/Ag/ab-HSA nanoprobes for detection of microalbuminuria at point of care.

In this study, we have fabricated a simple disposable electrochemical immunosensor for the point of care testing of microalbuminuria, a well-known clinical biomarker for the onset of chronic kidney disease. The immunosensor is fabricated by screen-printing carbon interdigitated microelectrodes on a flexible plastic substrate and utilizes electrochemical impedance spectroscopy to enable direct and label free immunosensing by analyzing interfacial changes on the electrode surface. To improve conductivity and biocompatibility of the screen-printed electrodes, we have modified it with gold nanoparticles, which are electrodeposited using linear sweep voltammetry. To enable efficient immobilization of HSA antibodies, we have developed novel PS/Ag/ab-HSA nanoprobes (polystyrene nanoparticle core with silver nanoshells covalently conjugated to HSA antibodies), and these nanoprobes are trapped on the electrode surface using dielectrophoresis. Each immunosensor has two sensing sites corresponding to test and control to improve specificity by performing differential analysis. Immunosensing results show that the normalized impedance response is linearly dependent on albumin concentration in the clinically relevant range with good repeatability. We have also developed a portable impedance readout module that can analyze the data obtained from the immunosensor and transmit it wirelessly for cloud computing. Consequently, the developed immunosensing platform can be extended to the detection of a range of immunoreactions and shows promise for point of diagnosis and public healthcare monitoring.

Development of an AVF Stenosis Assessment Tool for Hemodialysis Patients Using Robotic Ultrasound System.

With the aging population and lifestyle changes, the number of hemodialysis (HD) patients increases year by year. The arteriovenous fistula (AVF) is the gold standard vascular access used to access the blood for HD treatment. Since the status of stenosis affects HD efficiency, current clinical practices usually use a Doppler ultrasound imaging system to assess the parameters of the stenosis, such as the degree of stenosis (DOS). Unfortunately, this is a very time-consuming task. Furthermore, it is difficult to stably maintain the ultrasound probe for a prolonged period to give doctors clearer or reproducible images. In this study, a robotic ultrasound system (RUS) with ultrasound sequential imaging analysis was designed to evaluate the DOS of the AVF. The sequential imaging analysis was capable of image smoothing and vessel boundary detection. It enabled clinicians to mark the thickness of the plaque for further processing. Finally, the system was used to reconstruct 3D models of fistulas and calculated the DOS for clinical assessment. We also designed a pressure sensing module attached to the ultrasound probe to prevent the probe from coming loose, vibrating, and exerting abnormal pressure on the skin. In the phantom test, the results showed that the error of the DOS that was calculated by RUS was less than 3%. The results of clinical trials obtained from ten patients show that the error between the RUS and clinicians' measurement was about 10% and had a highly linear correlation (R Square > 0.95). In addition, the reproducibility error was about 3% and could effectively save about 46% of the time during clinical examinations.

Levenberg-Marquardt Neural Network Algorithm for Degree of Arteriovenous Fistula Stenosis Classification Using a Dual Optical Photoplethysmography Sensor.

This paper proposes a noninvasive dual optical photoplethysmography (PPG) sensor to classify the degree of arteriovenous fistula (AVF) stenosis in hemodialysis (HD) patients. Dual PPG measurement node (DPMN) becomes the primary tool in this work for detecting abnormal narrowing vessel simultaneously in multi-beds monitoring patients. The mean and variance of Rising Slope (RS) and Falling Slope (FS) values between before and after HD treatment was used as the major features to classify AVF stenosis. Multilayer perceptron neural networks (MLPN) training algorithms are implemented for this analysis, which are the Levenberg-Marquardt, Scaled Conjugate Gradient, and Resilient Back-propagation, to identify the degree of HD patient stenosis. Eleven patients were recruited with mean age of 77 ± 10.8 years for analysis. The experimental results indicated that the variance of RS in the HD hand between before and after treatment was significant difference statistically to stenosis (p < 0.05). Levenberg-Marquardt algorithm (LMA) was significantly outperforms the other training algorithm. The classification accuracy and precision reached 94.82% and 92.22% respectively, thus this technique has a potential contribution to the early identification of stenosis for a medical diagnostic support system.

A novel conversion method for radiographic guide into surgical guide.

BACKGROUND: The study proposed a novel method for converting a radiographic guide into a surgical guide and evaluated its accuracy. MATERIALS AND METHODS: Radiographic guide was reformed with the addition of index rods for geometric conversion method (GCM). Planning implants were projected on geometric projection planes, and the implant positions were measured. The radiographic guide was converted into surgical guide using a generic bench drill machine with GCM data. Two experiments were designed to validate the GCM. (1) In vitro test: Twenty implants were placed on five edentulous dental models by using the GCM (group 1) and Stereolithography (SLA) method (group 2), respectively. The deviations of planned and placed implant were calculated, and the precision error (PE) value was calculated to evaluate the stability of the GCM and SLA. (2) In vivo test: Nine edentulous subjects were selected for clinical implant surgery with the GCM guide. Two level of the index rods of radiographic guides were prepared for surgical guides forming. The differences between the planned and actual implants were calculated in implant head, apex, and angulation. RESULTS: The in vitro test revealed no significant differences in the planned and placed angulations between groups 1 and 2 (P > .05). The PE was not significantly different between groups 1 and 2 (P > .05). The in vivo test revealed a successful treatment of the subjects, and 16 implant sites were evaluated. The results indicated that GCM guide could achieve the three-dimensional (3D) offset deviations of 1.03 ± 0.27 mm and 1.17 ± 0.24 mm at the implant head and apex, respectively, and 1.37° ± 0.21° for the 3D angulation. CONCLUSION: The novel method for converting a radiographic guide into a surgical guide appears accurate and stable compared with SLA.

Novel Wearable Device for Blood Leakage Detection during Hemodialysis Using an Array Sensing Patch.

Hemodialysis (HD) is a clinical treatment that requires the puncturing of the body surface. However, needle dislodgement can cause a high risk of blood leakage and can be fatal to patients. Previous studies proposed several devices for blood leakage detection using optical or electrical techniques. Nonetheless, these methods used single-point detection and the design was not suitable for multi-bed monitoring. This study proposed a novel wearable device for blood leakage monitoring during HD using an array sensing patch. The array sensing patch combined with a mapping circuit and a wireless module could measure and transmit risk levels. The different risk levels could improve the working process of healthcare workers, and enhance their work efficiency and reduce inconvenience due to false alarms. Experimental results showed that each point of the sensing array could detect up to 0.1 mL of blood leakage and the array sensing patch supports a risk level monitoring system up to 8 h to alert healthcare personnel of pertinent danger to the patients.

Immunosensor for the ultrasensitive and quantitative detection of bladder cancer in point of care testing.

An ultrasensitive and real-time impedance based immunosensor has been fabricated for the quantitative detection of Galectin-1 (Gal-1) protein, a biomarker for the onset of multiple oncological conditions, especially bladder cancer. The chip consists of a gold annular interdigitated microelectrode array (3×3 format with a sensing area of 200µm) patterned using standard microfabrication processes, with the ability to electrically address each electrode individually. To improve sensitivity and immobilization efficiency, we have utilized nanoprobes (Gal-1 antibodies conjugated to alumina nanoparticles through silane modification) that are trapped on the microelectrode surface using programmable dielectrophoretic manipulations. The limit of detection of the immunosensor for Gal-1 protein is 0.0078mg/ml of T24 (Grade III) cell lysate in phosphate buffered saline, artificial urine and human urine samples. The normalized impedance variations show a linear dependence on the concentration of cell lysate present while specificity is demonstrated by comparing the immunosensor response for two different grades of bladder cancer cell lysates. We have also designed a portable impedance analyzing device to connect the immunosensor for regular checkup in point of care testing with the ability to transfer data over the internet using a personal computer. We believe that this diagnostic system would allow for improved public health monitoring and aid in early cancer diagnosis.

A Novel Classification Technique of Arteriovenous Fistula Stenosis Evaluation Using Bilateral PPG Analysis.

The most common treatment for end-stage renal disease (ESRD) patients is the hemodialysis (HD). For this kind of treatment, the functional vascular access that called arteriovenous fistula (AVF) is done by surgery to connect the vein and artery. Stenosis is considered the major cause of dysfunction of AVF. In this study, a noninvasive approach based on asynchronous analysis of bilateral photoplethysmography (PPG) with error correcting output coding support vector machine one versus rest (ESVM-OVR) for the degree of stenosis (DOS) evaluation is proposed. An artificial neural network (ANN) classifier is also applied to compare the performance with the proposed system. The testing data has been collected from 22 patients at the right and left thumb of the hand. The experimental results indicated that the proposed system could provide positive predictive value (PPV) reaching 91.67% and had higher noise tolerance. The system has the potential for providing diagnostic assistance in a wearable device for evaluation of AVF stenosis.

Bilateral photoplethysmography analysis for arteriovenous fistula dysfunction screening with fractional-order feature and cooperative game-based embedded detector.

The bilateral photoplethysmography (PPG) analysis for arteriovenous fistula (AVF) dysfunction screening with a fractional-order feature and a cooperative game (CG)-based embedded detector is proposed. The proposed detector uses a feature extraction method and a CG to evaluate the risk level for AVF dysfunction for patients undergoing haemodialysis treatment. A Sprott system is used to design a self-synchronisation error formulation to quantify the differences in the changes of blood volume for the sinister and dexter thumbs' PPG signals. Bilateral PPGs exhibit a significant difference in rise time and amplitude, which is proportional to the degree of stenosis. A less parameterised CG model is then used to evaluate the risk level. The proposed detector is also studied using an embedded system and bilateral optical measurements. The experimental results show that the risk of AVF stenosis during haemodialysis treatment is detected earlier.

Virtual-Reality Simulator System for Double Interventional Cardiac Catheterization Using Fractional-Order Vascular Access Tracker and Haptic Force Producer.

This study proposes virtual-reality (VR) simulator system for double interventional cardiac catheterization (ICC) using fractional-order vascular access tracker and haptic force producer. An endoscope or a catheter for diagnosis and surgery of cardiovascular disease has been commonly used in minimally invasive surgery. It needs specific skills and experiences for young surgeons or postgraduate year (PGY) students to operate a Berman catheter and a pigtail catheter in the inside of the human body and requires avoiding damaging vessels. To improve the training in inserting catheters, a double-catheter mechanism is designed for the ICC procedures. A fractional-order vascular access tracker is used to trace the senior surgeons' consoled trajectories and transmit the frictional feedback and visual feedback during the insertion of catheters. Based on the clinical feeling through the aortic arch, vein into the ventricle, or tortuous blood vessels, haptic force producer is used to mock the elasticity of the vessel wall using voice coil motors (VCMs). The VR establishment with surgeons' consoled vessel trajectories and hand feeling is achieved, and the experimental results show the effectiveness for the double ICC procedures.

Residual stenosis estimation of arteriovenous grafts using a dual-channel phonoangiography with fractional-order features.

The residual stenosis estimation of an arteriovenous shunt is a valuable for evaluating outcomes of percutaneous transluminal angioplasty (PTA) treatment and surgical revision. This paper proposes a dual-channel phonoangiography (PCG) with fractional-order features to estimate the residual of stenosis estimation of arteriovenous shunt. The auscultation technique provides a noninvasive tool to monitor the degrees of arteriovenous grafts (AVGs). Then, support methods, such as the Burg autoregressive (AR) method and self-synchronization error formulation (SSEF), are used to extract fractional-order features between the loop site (L-site) and venous anastomosis site (V-site). Using 2-D patterns (nonlinear mapping), a generalized regression neural network (GRNN) is designed as a nonlinear estimate model to indicate the outcome of surgical revision or AVG stenosis upon routine monthly examinations. For 42 long-term follow-up patients, the results of examination show the proposed GRNN-based screening model efficiently estimates residual stenosis.