Query: A 64-Element 28-GHz Phased-Array Transceiver With 52-dBm EIRP and 8–12-Gb/s 5G Link at 300 Meters Without Any Calibration

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A 64 GHz 2 Gbps transmit/receive phased-array communication link in SiGe with 300 meter coverage <=SEP=> This paper presents a 64 GHz transmit/receive communication link between two 32-element SiGe-based phased arrays. The antenna element is a series-fed patch array, which provides directivity in the elevation plane. The transmit array results in an EIRP of 42 dBm, while the receive array provides an electronic gain of 33 dB and a system NF < 8 dB including the T/R switch and antenna losses. The arrays can be scanned to +/−50° in the azimuth using a 5-bit phase shifter on the SiGe chip, while keeping very low sidelobes and a near-ideal pattern. The communication link uses one array on the transmit side and another array on the receive side, together with external mixers and IF amplifiers. A Keysight M8195A arbitrary waveform generator is used to generate the modulated waveforms on the transmit side and a Keysight DSO804A oscilloscope is used to demodulate the received IF signal. The link performance was measured for different scan angles and modulation formats. Data rates of 1 Gbps using 16-QAM and 2 Gbps using QPSK are demonstrated at 300 m. The system also results in > 4 Gbps data rate at 100 meters, and ∼ 500 Mbps data rate at 800 meters.

Fabrication and measurement of a large, monolithic, PCB-based AESA <=SEP=> This paper discusses a fabrication approach and experimental validation of a very large, planar active electronically scanned array (AESA). The planar AESA architecture employs a monolithic printed circuit board (PCB) with 768 active antenna elements at X-Band. Manufacturing physically large arrays with high element counts is discussed in relation to construction, assembly and yield considerations. Measured active array patterns of the ESA are also presented.

A Millimeter-Wave (40–45 GHz) 16-Element Phased-Array Transmitter in 0.18-$\mu$ m SiGe BiCMOS Technology <=SEP=> This paper demonstrates a 16-element phased-array transmitter in a standard 0.18-mum SiGe BiCMOS technology for Q-band satellite applications. The transmitter array is based on the all-RF architecture with 4-bit RF phase shifters and a corporate-feed network. A 1:2 active divider and two 1:8 passive tee-junction dividers constitute the corporate-feed network, and three-dimensional shielded transmission-lines are used for the passive divider to minimize area. All signals are processed differentially inside the chip except for the input and output interfaces. The phased-array transmitter results in a 12.5 dB of average power gain per channel at 42.5 GHz with a 3-dB gain bandwidth of 39.9-45.6 GHz. The RMS gain variation is < 1.3 dB and the RMS phase variation is < for all 4-bit phase states at 35-50 GHz. The measured input and output return losses are < -10 dB at 36.6-50 GHz, and <-10 dB at 37.6-50 GHz, respectively. The measured peak-to-peak group delay variation is plusmn 20 ps at 40-45 GHz. The output P-1dB is -5plusmn1.5 dBm and the maximum saturated output power is - 2.5plusmn1.5 dBm per channel at 42.5 GHz. The transmitter shows <1.8 dB of RMS gain mismatch and < 7deg of RMS phase mismatch between the 16 different channels over all phase states. A - 30 dB worst-case port-to-port coupling is measured between adjacent channels at 30-50 GHz, and the measured RMS gain and phase disturbances due to the inter-channel coupling are < 0.15 dB and < 1deg, respectively, at 35-50 GHz. All measurements are obtained without any on-chip calibration. The chip consumes 720 mA from a 5 V supply voltage and the chip size is 2.6times3.2 mm2.

A 28GHz Bulk-CMOS dual-polarization phased-array transceiver with 24 channels for 5G user and basestation equipment <=SEP=> Developing next-generation cellular technology (5G) in the mm-wave bands will require low-cost phased-array transceivers [1]. Even with the benefit of beamforming, due to space constraints in the mobile form-factor, increasing TX output power while maintaining acceptable PA PAE, LNA NF, and overall transceiver power consumption is important to maximizing link budget allowable path loss and minimizing handset case temperature. Further, the phased-array transceiver will need to be able to support dual-polarization communication. An IF interface to the analog baseband is desired for low power consumption in the handset or user equipment (UE) active antenna and to enable use of arrays of transceivers for customer premises equipment (CPE) or basestation (BS) antenna arrays with a low-loss IF power-combining/splitting network implemented on an antenna backplane carrying multiple tiled antenna modules.

7.2 A 28GHz 32-element phased-array transceiver IC with concurrent dual polarized beams and 1.4 degree beam-steering resolution for 5G communication <=SEP=> Next-generation mobile technology (5G) aims to provide an improved experience through higher data-rates, lower latency, and improved link robustness. Millimeter-wave phased arrays offer a path to support multiple users at high data-rates using high-bandwidth directional links between the base station and mobile devices. To realize this vision, a phased-array-based pico-cell must support a large number of precisely controlled beams, yet be compact and power efficient. These system goals have significant mm-wave radio interface implications, including scalability of the RFIC+antenna-array solution, increase in the number of concurrent beams by supporting dual polarization, precise beam steering, and high output power without sacrificing TX power efficiency. Packaged Si-based phased arrays [1–3] with nonconcurrent dual-polarized TX and RX operation [2,3], concurrent dual-polarized RX operation [3] and multi-IC scaling [3,4] have been demonstrated. However, support for concurrent dual-polarized operation in both RX and TX remains unaddressed, and high output power comes at the cost of power consumption, cooling complexity and increased size. The RFIC reported here addresses these challenges. It supports concurrent and independent dual-polarized operation in TX and RX modes, and is compatible with a volume-efficient, scaled, antenna-in-package array. A new TX/RX switch at the shared antenna interface enables high output power without sacrificing TX efficiency, and a t-line-based phase shifter achieves <1° RMS error and <5° phase steps for precise beam control.

A novel activation function for multilayer feed-forward neural networks <=SEP=> Traditional activation functions such as hyperbolic tangent and logistic sigmoid have seen frequent use historically in artificial neural networks. However, nowadays, in practice, they have fallen out of favor, undoubtedly due to the gap in performance observed in recognition and classification tasks when compared to their well-known counterparts such as rectified linear or maxout. In this paper, we introduce a simple, new type of activation function for multilayer feed-forward architectures. Unlike other approaches where new activation functions have been designed by discarding many of the mainstays of traditional activation function design, our proposed function relies on them and therefore shares most of the properties found in traditional activation functions. Nevertheless, our activation function differs from traditional activation functions on two major points: its asymptote and global extremum. Defining a function which enjoys the property of having a global maximum and minimum, turned out to be critical during our design-process since we believe it is one of the main reasons behind the gap observed in performance between traditional activation functions and their recently introduced counterparts. We evaluate the effectiveness of the proposed activation function on four commonly used datasets, namely, MNIST, CIFAR-10, CIFAR-100, and the Pang and Lee’s movie review. Experimental results demonstrate that the proposed function can effectively be applied across various datasets where our accuracy, given the same network topology, is competitive with the state-of-the-art. In particular, the proposed activation function outperforms the state-of-the-art methods on the MNIST dataset.

A Survey on Anomalies Detection Techniques and Measurement Methods <=SEP=> Dynamic research area has been applied and researched on anomaly detection in various domains. And various techniques have been proposed to identify unexpected items or events in datasets which differ from the norm. This review tries to provide a basic and structured overview of the anomaly detection techniques. Also, this review discusses major anomaly detection techniques using statistical based and machine learning based techniques. The outcome of this review may facilitate a better understanding of the different techniques in which research has been done on this topic by comparing the pros and cons of the identified techniques. In addition, this review also discusses on the measurement methods used by other researchers in validating their anomalies detection techniques.

Comparison of EEG signal features and ensemble learning methods for motor imagery classification <=SEP=> Classifying electroencephalogram (EEG) signal in Brain Computer Interface (BCI) is a useful methods to analysis different organs of human body and it can be used for communicate with the outside world and controlling external device. Accuracy classification of extracted features from EEG signals is a problem which many researcher try to improve it. Although many methods for extracting feature and classifying EEG signal have been proposed and developed, many of them suffer from extracting less accurate data from EEG signals. In this work, four signal feature extraction and three ensemble learning method have been reviewed and performances of classification techniques are compared for motor imagery task.

Linking GloVe with word2vec <=SEP=> The Global Vectors for word representation (GloVe), introduced by Jeffrey Pennington et al. [3] is reported to be an efficient and effective method for learning vector representations of words. State-of-the-art performance is also provided by skip-gram with negative-sampling (SGNS) [2] implemented in the word2vec tool. In this note, we explain the similarities between the training objectives of the two models, and show that the objective of SGNS is similar to the objective of a specialized form of GloVe, though their cost functions are defined differently.

Expanded Hemodialysis: A New Therapy for a New Class of Membranes. <=SEP=> A wide spectrum of molecules is retained in end-stage kidney disease, normally defined as uremic toxins. These solutes have different molecular weights and radii. Current dialysis membranes and techniques only remove solutes in the range of 50-15,000 Da, with limited or no capability to remove solutes in the middle to high molecular weight range (up to 50,000 Da). Improved removal has been obtained with high cut-off (HCO) membranes, with albumin loss representing a limitation to their practical application. Hemodiafiltration (HDF) at high volumes (>23 L/session) has produced some results on middle molecules and clinical outcomes, although complex hardware and high blood flows are required. A new class of membrane has been recently developed with a cut off (MWCO) close to the molecular weight of albumin. While presenting negligible albumin loss, these membranes have a very high retention onset (MWRO), allowing high clearances of solutes in a wide spectrum of molecular weights. These membranes originally defined (medium cut off) are probably better classified as high retention onset. The introduction of such membranes in the clinical routine has allowed the development of a new concept therapy called "expanded hemodialysis" (HDx). The new therapy is based on a special hollow fiber and dialyzer design. Its simple set-up and application offer the possibility to use it even in patients with suboptimal vascular access or even with an indwelling catheter. The system does not require a particular hardware or unusual nursing skill. The quality of dialysis fluid is, however, mandatory to ensure a safe conduction of the dialysis session. This new therapy is likely to modify the outcome of end-stage kidney disease patients, thanks to the enhanced removal of molecules traditionally retained by current dialysis techniques.

Modular Self-Reconfigurable Robot Systems [Grand Challenges of Robotics] <=SEP=> The field of modular self-reconfigurable robotic systems addresses the design, fabrication, motion planning, and control of autonomous kinematic machines with variable morphology. Modular self-reconfigurable systems have the promise of making significant technological advances to the field of robotics in general. Their promise of high versatility, high value, and high robustness may lead to a radical change in automation. Currently, a number of researchers have been addressing many of the challenges. While some progress has been made, it is clear that many challenges still exist. By illustrating several of the outstanding issues as grand challenges that have been collaboratively written by a large number of researchers in this field, this article has shown several of the key directions for the future of this growing field

The effects of caffeine on heart rate variability in newborns with apnea of prematurity <=SEP=> Objective:Apnea of prematurity is a common complication in premature newborns and caffeine is a widespread medication used to treat this complication. Caffeine may have adverse effects on the cardiovascular and central nervous system, yet its effects on the autonomic nervous system modulation of heart rate have not been studied in premature newborns, which was the objective of our study.Study Design:We prospectively studied 21 premature newborns who were treated with caffeine. We analyzed heart rate variability by power spectral density and by dynamic nonlinear analyses methods.Result:There were no changes in heart rate, blood pressure or the autonomic nervous system tone following administration of caffeine, nor were the nonlinear dynamical properties of the system altered by caffeine.Conclusion:Caffeine does not have detrimental effects on heart rate variablility, heart rate or blood pressure in conventional doses given to premature newborns.

The end of the end of ideology. <=SEP=> The "end of ideology" was declared by social scientists in the aftermath of World War II. They argued that (a) ordinary citizens' political attitudes lack the kind of stability, consistency, and constraint that ideology requires; (b) ideological constructs such as liberalism and conservatism lack motivational potency and behavioral significance; (c) there are no major differences in content (or substance) between liberal and conservative points of view; and (d) there are few important differences in psychological processes (or styles) that underlie liberal versus conservative orientations. The end-of-ideologists were so influential that researchers ignored the topic of ideology for many years. However, current political realities, recent data from the American National Election Studies, and results from an emerging psychological paradigm provide strong grounds for returning to the study of ideology. Studies reveal that there are indeed meaningful political and psychological differences that covary with ideological self-placement. Situational variables--including system threat and mortality salience--and dispositional variables--including openness and conscientiousness--affect the degree to which an individual is drawn to liberal versus conservative leaders, parties, and opinions. A psychological analysis is also useful for understanding the political divide between "red states" and "blue states."

DeltaIoT: A Self-Adaptive Internet of Things Exemplar <=SEP=> Internet of Things (IoT) consists of networked tiny embedded computers (motes) that are capable of monitoring and controlling the physical world. Examples range from building security monitoring to smart factories. A central problem of IoT is minimising the energy consumption of the motes, while guaranteeing high packet delivery performance, regardless of uncertainties such as sudden changes in traffic load and communication interference. Traditionally, to deal with uncertainties the network settings are either hand-tuned or over-provisioned, resulting in continuous network maintenance or inefficiencies. Enhancing the IoT network with self-adaptation can automate these tasks. This paper presents DeltaIoT, an exemplar that enables researchers to evaluate and compare new methods, techniques and tools for self-adaptation in IoT. DeltaIoT is the first exemplar for research on self-adaptation that provides both a simulator for offline experimentation and a physical setup that can be accessed remotely for real-world experimentation.

Gradient and Curvature from Photometric Stereo Including Local Confidence Estimation <=SEP=> Photometric stereo is one technique for 3D shape determination that has been implemented in a variety of experimental settings and that has produced consistently good results. The idea is to use intensity values recorded from multiple images obtained from the same viewpoint but under different conditions of illumination. The resulting radiometric constraint makes it possible to obtain local estimates of both surface orientation and surface curvature without requiring global smoothness assumptions and without requiring prior image segmentation. This paper moves photometric stereo one step closer to practical viability by describing an experimental setting in which surface gradient estimation is achieved on full frame video data at near video frame rates (i.e., 15Hz). The implementation uses commercially available hardware. Reflectance is modeled empirically using measurements obtained from a calibration sphere. Estimation of the gradient, (p, q), requires only simple table lookup. Curvature estimation uses, in addition, the reflectance map, R(p, q). The required lookup table and reflectance maps are derived during calibration. Because reflectance is modeled empirically, no prior physical model of the reflectance characteristics of the objects to be analyzed is assumed. At the same time, if a good physical model is available, it can be retrofit to the method for implementation purposes. Photometric stereo is subject to error in the presence of cast shadows and interreflection. No purely local technique can succeed since these phenomena are inherently non-local. Nevertheless, this paper demonstrates that one can exploit the redundancy in three light source photometric stereo to, in most cases, locally detect the presence of cast shadows and interreflection. Detection is facilitated by explicitly including a local confidence estimate in the lookup table used for gradient estimation.

Boosting energy efficiency with mirrored data block replication policy and energy scheduler <=SEP=> Energy efficiency is one of the major challenges in big datacenters. To facilitate processing of large data sets in a distributed fashion, the MapReduce programming model is employed in these datacenters. Hadoop is an open-source implementation of MapReduce which contains a distributed file system. Hadoop Distributed File System provides a data block replication scheme to preserve reliability and data availability. The distribution of the data block replicas over the nodes is performed randomly by meeting some constraints (e.g., preventing storage of two replicas of a data block on a single node). This study makes use of flexibility in the data block placement policy to increase energy efficiency in datacenters. Furthermore, inspired by Zaharia et al.'s delay scheduling algorithm, a scheduling algorithm is introduced, which takes into account energy efficiency in addition to fairness and data locality properties. Computer simulations of the proposed method suggest its superiority over Hadoop's standard settings.

Interactive Indirect Illumination Using Voxel Cone Tracing <=SEP=> Indirect illumination is an important element for realistic image synthesis, but its computation is expensive and highly dependent on the complexity of the scene and of the BRDF of the involved surfaces. While off-line computation and pre-baking can be acceptable for some cases, many applications (games, simulators, etc.) require real-time or interactive approaches to evaluate indirect illumination. We present a novel algorithm to compute indirect lighting in real-time that avoids costly precomputation steps and is not restricted to low-frequency illumination. It is based on a hierarchical voxel octree representation generated and updated on the fly from a regular scene mesh coupled with an approximate voxel cone tracing that allows for a fast estimation of the visibility and incoming energy. Our approach can manage two light bounces for both Lambertian and glossy materials at interactive framerates (25-70FPS). It exhibits an almost scene-independent performance and can handle complex scenes with dynamic content thanks to an interactive octree-voxelization scheme. In addition, we demonstrate that our voxel cone tracing can be used to efficiently estimate Ambient Occlusion.

Compact low-voltage power-efficient operational amplifier cells for VLSI <=SEP=> “Some Design Aspects of a Two-Stage Rail-to-Rail CMOS Op Amp' by Sander L. J. Gierkink, Peter J. Holzmann, Remco J. Wiegerink and Roelof F. Wassenaar, Analog Integrated Circuits and Signal Processing, Vol. 21, No. 2, Nov. 1999, pp 143-152. “Compact Low-Voltage Power-Efficient Operational Amplifier Cells for VLSI by Klaas-Jan de Langen and Johan H. Huijsing, IEEE Journal of Solid State Circuits, vol. 33, No. 10, Oct. 1998, pp. 1482–1496. “Design Aspects of a Rail-to-Rail CMOS Op Amp' by Glierkink et al., Mesa Research institute, ECT-97-36, pp. 23-28.

Mining program workflow from interleaved traces <=SEP=> Successful software maintenance is becoming increasingly critical due to the increasing dependence of our society and economy on software systems. One key problem of software maintenance is the difficulty in understanding the evolving software systems. Program workflows can help system operators and administrators to understand system behaviors and verify system executions so as to greatly facilitate system maintenance. In this paper, we propose an algorithm to automatically discover program workflows from event traces that record system events during system execution. Different from existing workflow mining algorithms, our approach can construct concurrent workflows from traces of interleaved events. Our workflow mining approach is a three-step coarse-to-fine algorithm. At first, we mine temporal dependencies for each pair of events. Then, based on the mined pair-wise tem-poral dependencies, we construct a basic workflow model by a breadth-first path pruning algorithm. After that, we refine the workflow by verifying it with all training event traces. The re-finement algorithm tries to find out a workflow that can interpret all event traces with minimal state transitions and threads. The results of both simulation data and real program data show that our algorithm is highly effective.

Biobanks: transnational, European and global networks. <=SEP=> Biobanks contain biological samples and associated information that are essential raw materials for advancement of biotechnology, human health, and research and development in life sciences. Population-based and disease-oriented biobanks are major biobank formats to establish the disease relevance of human genes and provide opportunities to elucidate their interaction with environment and lifestyle. The developments in personalized medicine require molecular definition of new disease subentities and biomarkers for identification of relevant patient subgroups for drug development. These emerging demands can only be met if biobanks cooperate at the transnational or even global scale. Establishment of common standards and strategies to cope with the heterogeneous legal and ethical landscape in different countries are seen as major challenges for biobank networks. The Central Research Infrastructure for Molecular Pathology (CRIP), the concept for a pan-European Biobanking and Biomolecular Resources Research Infrastructure (BBMRI), and the Organization for Economic Co-operation and Development (OECD) global Biological Resources Centres network are examples for transnational, European and global biobank networks that are described in this article.

A SiC-based isolated DC/DC converter for high density data center applications <=SEP=> Data centers are increasing in number and size at astounding rates, while operational cost, thermal management, size, and performance continue to be the driving metrics for the power subsystems in the associated computing equipment. This paper presents a SiC-based phase-shifted full bridge (PSFB) converter designed for 10kW output power and targeted at data center applications. The design approach focused on tuning of the converter efficiency and minimizing the thermal management system, resulting in a high-density converter. A unique thermal management system has also been employed, resulting in both increased power density and better thermal management. In this paper, the implementation of this converter is described in detail, along with empirical results, both electrical and thermal.

Classification of Brain MR Images using Texture Feature Extraction <=SEP=> Alzheimer’s disease (AD), is a degenerative disease which leads to memory loss and problems with thinking and behaviour.AD is a type of dementia which accounts for an estimated 60% to 80% of cases. Accurate diagnosis depends on the identification of discriminative features of AD. Recently, different feature extraction methods are used for the classification of AD. In this paper, we proposed a classification framework to select features, which are extracted using Gray-Level Co-occurrence Matrix (GLCM) method to distinguish between the AD and the Normal Control (NC). In order to evaluate the proposed method, we have performed evaluations on the MRI acquiring from the OASIS database. The proposed method yields an average testing accuracy of 75.71% which indicates that the proposed method can differentiate AD and NC satisfactorily.

Eavesdropping Attacks on High-Frequency RFID Tokens <=SEP=> RFID systems often use near-field magnetic coupling to implement communication channels. The advertised operational range of these channels is less than 10 cm and therefore several implemented systems assume that the communication channel is location limited and therefore relatively secure. Nevertheless, there have been repeated questions raised about the vulnerability of these near-field systems against eavesdropping and skimming attacks. In this paper I revisit the topic of RFID eavesdropping attacks, surveying previous work and explaining why the feasibility of practical attacks is still a relevant and novel research topic. I present a brief overview of the radio characteristics for popular HF RFID standards and present some practical results for eavesdropping experiments against tokens adhering to the ISO 14443 and ISO 15693 standards. Finally, I discuss how an attacker could construct a low-cost eavesdropping device using easy to obtain parts and reference designs.

MS-TWSVM: Mahalanobis distance-based Structural Twin Support Vector Machine <=SEP=> The distribution information of data points in two classes as the structural information is inserted into the classifiers to improve their generalization performance. Recently many algorithms such as S-TWSVM has used this information to construct two nonparallel hyperplanes which each one lies as close as possible to one class and being far away from the other. It is well known that different classes have different data distribution in real world problems, thus the covariance matrices of these classes are not the same. In these situations, the Mahalanobis is often more popular than Euclidean as a measure of distance. In this paper, in addition to apply the idea of S-TWSVM, the classical Euclidean distance is replaced by Mahalanobis distance which leads to simultaneously consider the covariance matrices of the two classes. By this modification, the orientation information in two classes can be better exploited than S-TWSVM. The experiments indicate our proposed algorithm is often superior to other learning algorithms in terms of generalization performance.

- 1-Simultaneous measurement of impulse response and distortion with a swept-sine technique <=SEP=> A novel measurement technique of the transfer function of weakly not-linear, approximately time-invariant systems is presented. The method is implemented with low-cost instrumentation; it is based on an exponentially-swept sine signal. It is applicable to loudspeakers and other audio components, but also to room acoustics measurements. The paper presents theoretical description of the method and experimental verification in comparison with MLS.

Metamaterial-Based Antennas: Research and Developments <=SEP=> A brief review of metamaterials and their applications to antenna systems is given. Artificial magnetic conductors and electrically small radiating and scattering systems are emphasized. Single negative, double negative, and zero-index metamaterial systems are discussed as a means to manipulate their size, efficiency, bandwidth, and directivity characteristics. key words: metamaterials, electrically small antennas, complex media, artificial magnetic conductors

The high-conductance state of neocortical neurons in vivo <=SEP=> Intracellular recordings in vivo have shown that neocortical neurons are subjected to an intense synaptic bombardment in intact networks and are in a 'high-conductance' state. In vitro studies have shed light on the complex interplay between the active properties of dendrites and how they convey discrete synaptic inputs to the soma. Computational models have attempted to tie these results together and predicted that high-conductance states profoundly alter the integrative properties of cortical neurons, providing them with a number of computational advantages. Here, we summarize results from these different approaches, with the aim of understanding the integrative properties of neocortical neurons in the intact brain.

Inferring Destination from Mobility Data <=SEP=> Destination prediction in a moving vehicle has several applications such as alternative route recommendations even in cases where the driver has not entered their destination into the system. In this paper a hierarchical approach to destination prediction is presented. A Discrete Time Markov Chain model is used to make an initial prediction of a general region the vehicle might be travelling to. Following that a more complex Bayesian Inference Model is used to make a fine grained prediction within that destination region. The model is tested on a dataset of 442 taxis operating in Porto, Portugal. Experiments are run on two maps. One is a smaller map concentrating specificially on trips within the Porto city centre and surrounding areas. The second map covers a much larger area going as far as Lisbon. We achieve predictions for Porto with average distance error of less than 0.6 km from early on in the trip and less than 1.6 km dropping to less than 1 km for the wider area.

Non-psychotropic plant cannabinoids: new therapeutic opportunities from an ancient herb. <=SEP=> Delta(9)-tetrahydrocannabinol binds cannabinoid (CB(1) and CB(2)) receptors, which are activated by endogenous compounds (endocannabinoids) and are involved in a wide range of physiopathological processes (e.g. modulation of neurotransmitter release, regulation of pain perception, and of cardiovascular, gastrointestinal and liver functions). The well-known psychotropic effects of Delta(9)-tetrahydrocannabinol, which are mediated by activation of brain CB(1) receptors, have greatly limited its clinical use. However, the plant Cannabis contains many cannabinoids with weak or no psychoactivity that, therapeutically, might be more promising than Delta(9)-tetrahydrocannabinol. Here, we provide an overview of the recent pharmacological advances, novel mechanisms of action, and potential therapeutic applications of such non-psychotropic plant-derived cannabinoids. Special emphasis is given to cannabidiol, the possible applications of which have recently emerged in inflammation, diabetes, cancer, affective and neurodegenerative diseases, and to Delta(9)-tetrahydrocannabivarin, a novel CB(1) antagonist which exerts potentially useful actions in the treatment of epilepsy and obesity.

A topology for three-stage Solid State Transformer <=SEP=> Solid State Transformer (SST) is a new type of power transformer based on power electronic converters and high frequency transformers. The SST realizes voltage transformation, galvanic isolation, and power quality improvements in a single device. In the literature, a number of topologies have been introduced for the SST. In this work, employing a modular multilevel converter, a new SST topology is introduced which provides not only high-voltage AC (HVAC), low-voltage AC (LVAC) and low-voltage DC (LVDC) ports, but also high-voltage DC (HVDC) port. Besides, the proposed topology is easily scalable to higher voltage levels.