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		<title><![CDATA[ Biomedical Circuits and Systems, IEEE Transactions on - new TOC ]]></title>
		<link>http://ieeexplore.ieee.org</link>
		<description>TOC Alert for Publication# 4156126 </description>
		<year>2013</year>
		<month>May      </month>
		<day>21</day>
		<item>
			<title><![CDATA[Table of Contents]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6513289]]></link>
			<description><![CDATA[Presents the cover/table of contents for this issue of the periodical.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6513289]]></guid>
			<volume>7</volume>
			<issue>2</issue>
			<startPage>C1</startPage>
			<endPage>C1</endPage>
			<fileSize>214</fileSize>
			<authors><![CDATA[]]></authors>
		</item>
		<item>
			<title><![CDATA[IEEE Transactions on Biomedical Circuits and Systems publication information]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6513274]]></link>
			<description><![CDATA[ ]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6513274]]></guid>
			<volume>7</volume>
			<issue>2</issue>
			<startPage>C2</startPage>
			<endPage>C2</endPage>
			<fileSize>146</fileSize>
			<authors><![CDATA[]]></authors>
		</item>
		<item>
			<title><![CDATA[Guest Editorial - ISCAS 2012 Special Issue]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6513284]]></link>
			<description><![CDATA[The nine papers in this special issue were selected from papers presented at the Biomedical Circuits and Systems, Life-Sciences Systems and Applications, and Neural Networks and Systems sessions of the 2012 IEEE International Symposium on Circuits and Systems (ISCAS 2012), held in Seoul, South Korea, from May 20-23, 2012.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6513284]]></guid>
			<volume>7</volume>
			<issue>2</issue>
			<startPage>105</startPage>
			<endPage>106</endPage>
			<fileSize>467</fileSize>
			<authors><![CDATA[Georgiou, P.;Carrara, S.;]]></authors>
		</item>
		<item>
			<title><![CDATA[A CMOS Power-Efficient Low-Noise Current-Mode Front-End Amplifier for Neural Signal Recording]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6508911]]></link>
			<description><![CDATA[In this paper, a new current-mode front-end amplifier (CMFEA) for neural signal recording systems is proposed. In the proposed CMFEA, a current-mode preamplifier with an active feedback loop operated at very low frequency is designed as the first gain stage to bypass any dc offset current generated by the electrode-tissue interface and to achieve a low high-pass cutoff frequency below 0.5 Hz. No reset signal or ultra-large pseudo resistor is required. The current-mode preamplifier has low dc operation current to enhance low-noise performance and decrease power consumption. A programmable current gain stage is adopted to provide adjustable gain for adaptive signal scaling. A following current-mode filter is designed to adjust the low-pass cutoff frequency for different neural signals. The proposed CMFEA is designed and fabricated in 0.18-<formula formulatype="inline"><tex Notation="TeX">$mu{rm m}$</tex> </formula> CMOS technology and the area of the core circuit is 0.076 <formula formulatype="inline"><tex Notation="TeX">${rm mm}^{2}$</tex></formula>. The measured high-pass cutoff frequency is as low as 0.3 Hz and the low-pass cutoff frequency is adjustable from 1 kHz to 10 kHz. The measured maximum current gain is 55.9 dB. The measured input-referred current noise density is 153 <formula formulatype="inline"><tex Notation="TeX">${,rm fA}/sqrt{rm Hz}$</tex> </formula> , and the power consumption is 13 <formula formulatype="inline"><tex Notation="TeX">$mu{rm W}$</tex></formula> at 1-V power supply. The fabricated CMFEA has been successfully applied to the animal test for recording the seizure ECoG of Long-Evan rats.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6508911]]></guid>
			<volume>7</volume>
			<issue>2</issue>
			<startPage>107</startPage>
			<endPage>114</endPage>
			<fileSize>1748</fileSize>
			<authors><![CDATA[Wu, C.-Y.;Chen, W.-M.;Kuo, L.-T.;]]></authors>
		</item>
		<item>
			<title><![CDATA[A 100-Channel Hermetically Sealed Implantable Device for Chronic Wireless Neurosensing Applications]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507617]]></link>
			<description><![CDATA[A 100-channel fully implantable wireless broadband neural recording system was developed. It features 100 parallel broadband (0.1 Hz&#x2013;7.8 kHz) neural recording channels, a medical grade 200 mAh Li-ion battery recharged inductively at 150 kHz , and data telemetry using 3.2 GHz to 3.8 GHz FSK modulated wireless link for 48 Mbps Manchester encoded data. All active electronics are hermetically sealed in a titanium enclosure with a sapphire window for electromagnetic transparency. A custom, high-density configuration of 100 individual hermetic feedthrough pins enable connection to an intracortical neural recording microelectrode array. A 100 MHz bandwidth custom receiver was built to remotely receive the FSK signal and achieved <formula formulatype="inline"><tex Notation="TeX">${-}77.7$</tex> </formula> dBm sensitivity with <formula formulatype="inline"><tex Notation="TeX">$10^{-8}$</tex> </formula> BER at 48 Mbps data rate. ESD testing on all the electronic inputs and outputs has proven that the implantable device satisfies the HBM Class-1B ESD Standard. In addition, the evaluation of the worst-case charge density delivered to the tissue from each I/O pin verifies the patient safety of the device in the event of failure. Finally, the functionality and reliability of the complete device has been tested on-bench and further validated chronically in ongoing freely moving swine and monkey animal trials for more than one year to date.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507617]]></guid>
			<volume>7</volume>
			<issue>2</issue>
			<startPage>115</startPage>
			<endPage>128</endPage>
			<fileSize>3371</fileSize>
			<authors><![CDATA[Yin, M.;Borton, D.A.;Aceros, J.;Patterson, W.R.;Nurmikko, A.V.;]]></authors>
		</item>
		<item>
			<title><![CDATA[An Energy-Efficient, Dynamic Voltage Scaling Neural Stimulator for a Proprioceptive Prosthesis]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6508875]]></link>
			<description><![CDATA[This paper presents an 8 channel energy-efficient neural stimulator for generating charge-balanced asymmetric pulses. Power consumption is reduced by implementing a fully-integrated DC-DC converter that uses a reconfigurable switched capacitor topology to provide 4 output voltages for Dynamic Voltage Scaling (DVS). DC conversion efficiencies of up to 82% are achieved using integrated capacitances of under 1 nF and the DVS approach offers power savings of up to 50% compared to the front end of a typical current controlled neural stimulator. A novel charge balancing method is implemented which has a low level of accuracy on a single pulse and a much higher accuracy over a series of pulses. The method used is robust to process and component variation and does not require any initial or ongoing calibration. Measured results indicate that the charge imbalance is typically between 0.05%&#x2013;0.15% of charge injected for a series of pulses. Ex-vivo experiments demonstrate the viability in using this circuit for neural activation. The circuit has been implemented in a commercially-available 0.18 <formula formulatype="inline"> <tex Notation="TeX">$mu$</tex></formula>m HV CMOS technology and occupies a core die area of approximately 2.8 mm<formula formulatype="inline"><tex Notation="TeX">$^2$</tex></formula> for an 8 channel implementation.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6508875]]></guid>
			<volume>7</volume>
			<issue>2</issue>
			<startPage>129</startPage>
			<endPage>139</endPage>
			<fileSize>2327</fileSize>
			<authors><![CDATA[Williams, I.;Constandinou, T.G.;]]></authors>
		</item>
		<item>
			<title><![CDATA[A Blink Restoration System With Contralateral EMG Triggered Stimulation and Real-Time Artifact Blanking]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507353]]></link>
			<description><![CDATA[Patients suffering from facial paralysis are on the hazard of disfigurement and loss of vision due to loss of blink function. Functional-electrical stimulation (FES) is one possible way of restoring blink and other functions in these patients. A blink restoration system for uni-lateral facial paralyzed patients is described in this paper. The system achieves restoration of synchronized blink through processing the myoelectric signal of orbicularis oculi at the normal side in real-time as the trigger to stimulate the paralyzed eyelid. Design issues are discussed, including EMG processing, stimulating strategies and real-time artifact blanking. Two artifact removal approaches based on sample and hold and digital filtering technique are proposed and implemented. Finally, the whole system has been verified on rabbit models.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507353]]></guid>
			<volume>7</volume>
			<issue>2</issue>
			<startPage>140</startPage>
			<endPage>148</endPage>
			<fileSize>1205</fileSize>
			<authors><![CDATA[Yi, X.;Jia, J.;Deng, S.;Shen, S.G.;Xie, Q.;Wang, G.;]]></authors>
		</item>
		<item>
			<title><![CDATA[A Sub-Microwatt Asynchronous Level-Crossing ADC for Biomedical Applications]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507350]]></link>
			<description><![CDATA[A continuous-time level-crossing analog-to-digital converter (LC-ADC) for biomedical applications is presented. When compared to uniform-sampling (US) ADCs LC-ADCs generate fewer samples for various sparse biomedical signals. Lower power consumption and reduced design complexity with respect to conventional LC-ADCs are achieved due to: 1) replacing the n-bit digital-to-analog converter (DAC) with a 1-bit DAC; 2) splitting the level-crossing detections; and 3) fixing the comparison window. Designed and implemented in 0.18 <formula formulatype="inline"> <tex Notation="TeX">$mu$</tex></formula>m CMOS technology, the proposed ADC uses a chip area of 220<formula formulatype="inline"><tex Notation="TeX">$,times,$</tex> </formula>203 <formula formulatype="inline"><tex Notation="TeX">$mu$</tex> </formula>m<formula formulatype="inline"><tex Notation="TeX">$^{2}$</tex> </formula>. Operating from a supply voltage of 0.8 V, the ADC consumes 313&#x2013;582 nW from 5 Hz to 5 kHz and achieves an ENOB up to 7.9 bits.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6507350]]></guid>
			<volume>7</volume>
			<issue>2</issue>
			<startPage>149</startPage>
			<endPage>157</endPage>
			<fileSize>1416</fileSize>
			<authors><![CDATA[Li, Y.;Zhao, D.;Serdijn, W.A.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Automatic Cell Segmentation and Nuclear-to-Cytoplasmic Ratio Analysis for Third Harmonic Generated Microscopy Medical Images]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6509989]]></link>
			<description><![CDATA[Traditional biopsy procedures require invasive tissue removal from a living subject, followed by time-consuming and complicated processes, so noninvasive in vivo virtual biopsy, which possesses the ability to obtain exhaustive tissue images without removing tissues, is highly desired. Some sets of in vivo virtual biopsy images provided by healthy volunteers were processed by the proposed cell segmentation approach, which is based on the watershed-based approach and the concept of convergence index filter for automatic cell segmentation. Experimental results suggest that the proposed algorithm not only reveals high accuracy for cell segmentation but also has dramatic potential for noninvasive analysis of cell nuclear-to-cytoplasmic ratio (NC ratio), which is important in identifying or detecting early symptoms of diseases with abnormal NC ratios, such as skin cancers during clinical diagnosis via medical imaging analysis.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6509989]]></guid>
			<volume>7</volume>
			<issue>2</issue>
			<startPage>158</startPage>
			<endPage>168</endPage>
			<fileSize>2257</fileSize>
			<authors><![CDATA[Lee, G.G.;Lin, H.-H.;Tsai, M.-R.;Chou, S.-Y.;Lee, W.-J.;Liao, Y.-H.;Sun, C.-K.;Chen, C.-F.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Efficient Data Extraction Method for Near-Infrared Spectroscopy (NIRS) Systems With High Spatial and Temporal Resolution]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6509463]]></link>
			<description><![CDATA[An hardware-efficient method for the extraction of hemodynamic responses in near-infrared spectroscopy systems is proposed to increase the spatial and temporal resolution. The performance improvement is attributed to high signal-to-noise ratio receivers, a modulation scheme, and a multi-input-multi-output based data extraction algorithm. The proposed system shows more than twofold improvement in the figure of merit compared to conventional designs. Experimental results support the validity of the proposed system.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6509463]]></guid>
			<volume>7</volume>
			<issue>2</issue>
			<startPage>169</startPage>
			<endPage>177</endPage>
			<fileSize>3271</fileSize>
			<authors><![CDATA[Choi, J.-K.;Choi, M.-G.;Kim, J.-M.;Bae, H.-M.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Low Power and Self-Reconfigurable WBAN Controller for Continuous Bio-Signal Monitoring System]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6508940]]></link>
			<description><![CDATA[The WBAN controller with Branched Bus (BB) topology and Continuous Data Transmission (CDT) protocol with low power consumption and self-reconfigurability is proposed for wearable healthcare applications. The BB topology and CDT protocol is a combination of conventional Bus and Star topology and a variation from TDMA protocol, respectively, while they are able to compensate for the electrical fault in bio-signal monitoring system caused by the electrode deformation. Thanks to them, the proposed WBAN controller enables more reliable operation in continuous bio-signal monitoring applications such as sleep monitoring.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6508940]]></guid>
			<volume>7</volume>
			<issue>2</issue>
			<startPage>178</startPage>
			<endPage>185</endPage>
			<fileSize>1839</fileSize>
			<authors><![CDATA[Lee, S.;Yoo, H.-J.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Wireless Recording Systems: From Noninvasive EEG-NIRS to Invasive EEG Devices]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6508907]]></link>
			<description><![CDATA[In this paper, we present the design and implementation of a wireless wearable electronic system dedicated to remote data recording for brain monitoring. The reported wireless recording system is used for a) simultaneous near-infrared spectrometry (NIRS) and scalp electro-encephalography (EEG) for noninvasive monitoring and b) intracerebral EEG (icEEG) for invasive monitoring. Bluetooth and dual radio links were introduced for these recordings. The Bluetooth-based device was embedded in a noninvasive multichannel EEG-NIRS system for easy portability and long-term monitoring. On the other hand, the 32-channel implantable recording device offers 24-bit resolution, tunable features, and a sampling frequency up to 2 kHz per channel. The analog front-end preamplifier presents low input-referred noise of 5 <formula formulatype="inline"><tex Notation="TeX">$mu$</tex> </formula> <formula formulatype="inline"><tex Notation="TeX">${rm V}_{rm RMS}$</tex></formula> and a signal-to-noise ratio of 112 dB. The communication link is implemented using a dual-band radio frequency transceiver offering a half-duplex 800 kb/s data rate, 16.5 mW power consumption and less than <formula formulatype="inline"><tex Notation="TeX">$10^{-10}$</tex></formula> post-correction Bit-Error Rate (BER). The designed system can be accessed and controlled by a computer with a user-friendly graphical interface. The proposed wireless implantable recording device was tested in vitro using real icEEG signals from two patients with refractory epilepsy. The wirelessly recorded signals were compared to the original signals recorded using wired-connection, and measured normalized root-mean square deviation was under 2%.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6508907]]></guid>
			<volume>7</volume>
			<issue>2</issue>
			<startPage>186</startPage>
			<endPage>195</endPage>
			<fileSize>1968</fileSize>
			<authors><![CDATA[Sawan, M.;Salam, M.T.;Le Lan, J.;Kassab, A.;Gelinas, S.;Vannasing, P.;Lesage, F.;Lassonde, M.;Nguyen, D.K.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Implantable Stimulator for Epileptic Seizure Suppression With Loading Impedance Adaptability]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6231703]]></link>
			<description><![CDATA[The implantable stimulator for epileptic seizure suppression with loading impedance adaptability was proposed in this work. The stimulator consisted of the high voltage generator, output driver, adaptor, and switches, can constantly provide the required 40-<formula formulatype="inline"><tex Notation="TeX">$mu{rm A}$</tex></formula> stimulus currents, as the loading impedance varied within 10 <formula formulatype="inline"><tex Notation="TeX">${rm k}Omega$</tex> </formula>&#x2013;300 <formula formulatype="inline"><tex Notation="TeX">${rm k}Omega$</tex></formula>. The performances of this design have been successfully verified in silicon chip fabricated by a 0.35-<formula formulatype="inline"> <tex Notation="TeX">$mu{rm m}$</tex></formula> 3.3-V/24-V CMOS process. The power consumption of this work was only 1.1 mW&#x2013;1.4 mW. The animal test results with the fabricated chip of proposed design have successfully verified in the Long-Evans rats with epileptic seizures.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6231703]]></guid>
			<volume>7</volume>
			<issue>2</issue>
			<startPage>196</startPage>
			<endPage>203</endPage>
			<fileSize>1582</fileSize>
			<authors><![CDATA[Lin, C.-Y.;Chen, W.-L.;Ker, M.-D.;]]></authors>
		</item>
		<item>
			<title><![CDATA[Nanofiber Web Textile Dry Electrodes for Long-Term Biopotential Recording]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6237554]]></link>
			<description><![CDATA[Electrode properties are key to the quality of measured biopotential signals. Ubiquitous health care systems require long-term monitoring of biopotential signals from normal volunteers and patients in home or hospital environments. In these settings it is appropriate to use dry textile electrode networks for monitoring purposes, rather than the gel or saline-sponge skin interfaces used with Ag/AgCl electrodes. In this study, we report performance test results of two different electrospun conductive nanofiber webs, and three metal plated fabrics. We evaluated contact impedance, step response, noise and signal fidelity performance indices for all five dry electrodes, and compared them to those of conventional Ag/AgCl electrodes. Overall, we found nanofiber web electrodes matched Ag/AgCl electrode performance more closely than metal plated fabric electrodes, with the contact resistance and capacitance of Ag plated PVDF nanofiber web electrodes being most similar to Ag/AgCl over the 10 Hz to 500 kHz frequency range. We also observed that step responses of all three metal-plated fabrics were poorer than those for nanofiber web electrodes and Ag/AgCl. Further, noise standard deviation and noise power spectral densities were generally lower in nanofiber web electrodes than metal plated fabrics; and waveform fidelity of ECG-like traces recorded from nanofiber web electrodes was higher than for metal plated fabrics. We recommend textile nanofiber web electrodes in applications where flexibility, comfort and durability are required in addition to good electrical characteristics.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6237554]]></guid>
			<volume>7</volume>
			<issue>2</issue>
			<startPage>204</startPage>
			<endPage>211</endPage>
			<fileSize>1356</fileSize>
			<authors><![CDATA[Oh, T.I.;Yoon, S.;Kim, T.E.;Wi, H.;Kim, K;Woo, E.J.;Sadleir, R.J.;]]></authors>
		</item>
		<item>
			<title><![CDATA[IEEE Transactions on Biomedical Circuits and Systems information for authors]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6514099]]></link>
			<description><![CDATA[Provides instructions and guidelines to prospective authors who wish to submit manuscripts.]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6514099]]></guid>
			<volume>7</volume>
			<issue>2</issue>
			<startPage>212</startPage>
			<endPage>212</endPage>
			<fileSize>112</fileSize>
			<authors><![CDATA[]]></authors>
		</item>
		<item>
			<title><![CDATA[IEEE Transactions on Biomedical Circuits and Systems society information]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6513299]]></link>
			<description><![CDATA[ ]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6513299]]></guid>
			<volume>7</volume>
			<issue>2</issue>
			<startPage>C3</startPage>
			<endPage>C3</endPage>
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			<title><![CDATA[Blank page]]></title>
			<link><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6513286]]></link>
			<description><![CDATA[ ]]></description>
			<pubDate><![CDATA[April  2013]]></pubDate>
			<guid><![CDATA[http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6513286]]></guid>
			<volume>7</volume>
			<issue>2</issue>
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