A primary hydatid cyst in the mesorectum uncommon location - A rare case report.

INTRODUCTION AND IMPORTANCE: The tapeworm Echinococcus granulosus sensu lato is the causative agent of cystic echinococcosis (CE), often known as hydatid disease. Over two-thirds of all occurrences of this zoonotic disease process in humans are caused by hepatic infection. Clinicians should have a low threshold to consider CE as a differential diagnosis in patients with positive serology and suggestive radiological findings, especially in endemic regions, because signs and symptoms are typically non-specific, especially in early disease. CASE PRESENTATION: This is a case report of a 26-year-old male who presented with increasing lower abdominal discomfort, mild pain, sense of fullness in the lower abdomen, described as (I'm having a ball in my abdomen), with a history of early satiation and tenesmus, frequency of urine, and history of weight loss and general weakness of 10-months duration. The diagnosis of a hydatid cyst in the mesorectum was made. The cyst was completely excised via open surgery. No local recurrence has been detected up to the present time. CLINICAL DISCUSSION: Given how uncommon a site like this is, this case report helps broaden the differential diagnosis of soft tissue masses in such settings, especially in endemic areas. It also describes in great detail how these locations are affected by the hydatid disease. CONCLUSION: The mesorectal hydatid cyst was challenging to diagnose initially due to its infrequent incidence and uncommon location. In a few rare cases, the diagnosis of a hydatid cyst might be guided by the detection of the cyst membrane and daughter cysts in the germinal membrane.

Analog monolayer SWCNTs-based memristive 2D structure for energy-efficient deep learning in spiking neural networks.

Advances in materials science and memory devices work in tandem for the evolution of Artificial Intelligence systems. Energy-efficient computation is the ultimate goal of emerging memristor technology, in which the storage and computation can be done in the same memory crossbar. In this work, an analog memristor device is fabricated utilizing the unique characteristics of single-wall carbon nanotubes (SWCNTs) to act as the switching medium of the device. Via the planar structure, the memristor device exhibits analog switching ability with high state stability. The device's conductance and capacitance can be tuned simultaneously, increasing the device's potential and broadening its applications' horizons. The multi-state storage capability and long-term memory are the key factors that make the device a promising candidate for bio-inspired computing applications. As a demonstrator, the fabricated memristor is deployed in spiking neural networks (SNN) to exploit its analog switching feature for energy-efficient classification operation. Results reveal that the computation-in-memory implementation performs Vector Matrix Multiplication with 95% inference accuracy and few femtojoules per spike energy efficiency. The memristor device presented in this work opens new insights towards utilizing the outstanding features of SWCNTs for efficient analog computation in deep learning systems.

Growth and characterization of germanium telluride nanowires via vapor-liquid-solid mechanism.

Phase-change materials (PCMs), which can transition reversibly between crystalline and amorphous phases, have shown great promise for next-generation memory devices due to their nonvolatility, rapid switching periods, and random-access capability. Several groups have investigated phase-change nanowires for memory applications in recent years. The ability to regulate the scale of nanostructures remains one of the most significant obstacles in nanoscience. Herein, we describe the growth and characterization of germanium telluride (GeTe) nanowires, which are essential for phase-change memory devices. GeTe nanowires were produced by combining thermal evaporation and vapor-liquid-solid (VLS) techniques, using 8 nm Au nanoparticles as the metal catalyst. The influence of various growth parameters, including inert gas flow rate, working pressure, growth temperature, growth duration, and growth substrate, was examined. Ar gas flow rate of 30 sccm and working pressure of 75 Torr produced the narrowest GeTe nanowires horizontally grown on a Si substrate. Using scanning electron microscopy, the dimensions, and morphology of GeTe nanowires were analyzed. Transmission electron microscopy and energy-dispersive x-ray spectroscopy were utilized to conduct structural and chemical analyses. Using a SiO2/Si substrate produced GeTe nanowires that were thicker and lengthier. The current-voltage characteristics of GeTe nanowires were investigated, confirming the amorphous nature of GeTe nanowires using conductive atomic force microscopy. In addition, the effects of the VLS mechanism and the Gibbs-Thomson effect were analyzed, which enables the optimization of nanowires for numerous applications, such as memory and reservoir computing.

Chicken skin based Milli Watt range biocompatible triboelectric nanogenerator for biomechanical energy harvesting.

This work reports a high-performance, low-cost, biocompatible triboelectric nanogenerator (TENG) using chicken skin (CS). The device is suitable to power wearable devices, which is critical to adapt electronics in monitoring, predicting, and treating people. It also supports sustainability by providing a cost-effective way to reduce the poultry industry's waste. It has been shown here that CS-derived biowaste is an effective means of generating tribopositive material for TENGs. The CS contains amino acid functional groups based on (Glycine, Proline, and Hydroxyproline), which are essential to demonstrate the electron-donating ability of collagen. The skin was cut into 3 × 3 cm2 and used as the raw material for fabricating the TENG device with a stacking sequence of Al/Kapton/spacing/CS/Al. The chicken skin-based TENG (CS-TENG) is characterized at different frequencies (4-14 HZ) using a damping system. The CS-TENG produces an open-circuit voltage of 123 V, short-circuit current of 20 µA and 0.2 mW/cm2 of a power density at 20 MΩ. The biocompatible CS-TENG presents ultra-robust and stable endurance performance with more than 52,000 cycles. The CS-TENG is impressively capable of scavenging energy to light up to 55 commercial light-emitting diodes (LEDs), a calculator, and to measure the physiological motions of the human body. CS-TENG is a step toward sustainable, battery-less devices or augmented energy sources, especially when using traditional power sources, such as in wearable devices, remote locations, or mobile applications is not practical or cost-effective.

Enhanced Graphene Oxide Electrical Properties for Thin-Film Electronics Using an Active/Shrinkable Substrate.

The advances in material science along with the development of fabrication techniques have enabled the realization of thin-film-based electronics on active substrates. This has substantially enhanced and supported the deployment of electronic devices in several emerging applications with flexible functionality. In this work, we report a novel fabrication of graphene oxide (GO)-based memristor devices on an active/shrinkable substrate. The standard lithography process is used to fabricate planar Au-rGO-Au devices on a polymer substrate that has the ability to shrink at a certain temperature (i.e., 170 °C). Upon heating, the devices are shrunk to 50% of their original size. A detailed electrical characterization has been carried out to study the switching behavior of the fabricated devices before and after shrinking. The results prove that upon shrinking, the device preserves its switching ability with enhanced electrical parameters (i.e., switching voltage). Also, material characterization performed for the deposited GO on the active substrate shows improved properties of the GO film due to the enhanced arrangement of GO flakes after shrinking. The novel approach proposed in this work provides new insights into and offers the ability to scale thin-film electronics postfabrication and thus overcome some of the device scaling challenges due to manufacturing limitations. It also unfolds a new path for the realization of GO-based electronic devices with improved electrical properties, which is a crucial aspect of the development of highly flexible and lightweight green electronics.

Artificial Intelligence-Aided Low Cost and Flexible Graphene Oxide-Based Paper Sensor for Ultraviolet and Sunlight Monitoring.

The adverse effect of ultraviolet (UV) radiation on human beings has sparked intense interest in the development of new sensors to effectively monitor UV and solar exposure. This paper describes a novel low-cost and flexible graphene oxide (GO)-based paper sensor capable of detecting the total amount of UV or sun energy delivered per unit area. GO is incorporated into the structure of standard printing paper, cellulose, via a low-cost fabrication technique. The effect of UV and solar radiation exposure on the GO paper-based sensor is investigated using a simple color change analysis. As a result, users can easily determine the amount of ultraviolet or solar energy received by the sensor using a simple color analysis application. A neural network (ANN) model is also explored to learn the relation between UV color intensity and exposure time, then digitally display the results. The accuracy for the developed ANN reached 96.83%. The disposable, cost-effective, simple, biodegradable, safe, and flexible characteristics of the paper-based UV sensor make it an attractive candidate for a variety of sensing applications. This work provides new vision toward developing highly efficient and fully disposable GO-based photosensors.

Ionic liquid multistate resistive switching characteristics in two terminal soft and flexible discrete channels for neuromorphic computing.

By exploiting ion transport phenomena in a soft and flexible discrete channel, liquid material conductance can be controlled by using an electrical input signal, which results in analog neuromorphic behavior. This paper proposes an ionic liquid (IL) multistate resistive switching device capable of mimicking synapse analog behavior by using IL BMIM FeCL4 and H2O into the two ends of a discrete polydimethylsiloxane (PDMS) channel. The spike rate-dependent plasticity (SRDP) and spike-timing-dependent plasticity (STDP) behavior are highly stable by modulating the input signal. Furthermore, the discrete channel device presents highly durable performance under mechanical bending and stretching. Using the obtained parameters from the proposed ionic liquid-based synaptic device, convolutional neural network simulation runs to an image recognition task, reaching an accuracy of 84%. The bending test of a device opens a new gateway for the future of soft and flexible brain-inspired neuromorphic computing systems for various shaped artificial intelligence applications.

Tunable Switching Behavior of GO-Based Memristors Using Thermal Reduction.

This work reports on the fabrication of a novel planar reduced graphene oxide (rGO) memristor (MR) device. For the first time in the literature, the MR tunable resistive switching behavior is controlled by the GO reduction time at a constant temperature. The device is fabricated using standard microfabrication techniques on a flexible cyclic olefin copolymer substrate (COC). Thermal reduction of the GO layer at low temperatures (100 °C) avoids the drawbacks of chemical reduction methods such as toxicity and electrode metal damage during fabrication, while allowing for fine-tuning of the MR's switching behavior. The device has analog switching characteristics, with a range of different resistance states. By taking advantage of the slow nature of GO thermal annealing, the switching properties of the rGO memristors can be precisely controlled by adjusting the reduction period. At short annealing times (i.e., T < 20 h), the devices switch from high to low resistance states, while at longer annealing times the switching behavior is reversed, with the device switching from low to high resistance states (LRS to HRS). Resistive switching occurs as a result of the diffusion and removal of the oxygen functional groups in the GO film caused by Joule heating induced by the electric current. Complete electrical characterization tests are presented along with wettability and X-ray diffraction (XRD) tests. This work opens a new vision for realizing rGO-based MR devices with tunable switching properties, broadening the application horizon of the device.

Memristor-based PUF for lightweight cryptographic randomness.

Physical unclonable functions (PUF) are cryptographic primitives employed to generate true and intrinsic randomness which is critical for cryptographic and secure applications. Thus, the PUF output (response) has properties that can be utilized in building a true random number generator (TRNG) for security applications. The most popular PUF architectures are transistor-based and they focus on exploiting the uncontrollable process variations in conventional CMOS fabrication technology. Recent development in emerging technology such as memristor-based models provides an opportunity to achieve a robust and lightweight PUF architecture. Memristor-based PUF has proven to be more resilient to attacks such as hardware reverse engineering attacks. In this paper, we design a lightweight and low-cost memristor PUF and verify it against cryptographic randomness tests achieving a unique, reliable, irreversible random sequence output. The current research demonstrates the architecture of a low-cost, high endurance Cu/HfO[Formula: see text]Si memristor-based PUF (MR-PUF) which is compatible with advanced CMOS technologies. This paper explores the 15 NIST cryptographic randomness tests that have been applied to our Cu/HfO[Formula: see text]Si MR-PUF. Moreover, security properties such as uniformity, uniqueness, and repeatability of our MR-PUF have been tested in this paper and validated. Additionally, this paper explores the applicability of our MR-PUF on block ciphers to improve the randomness achieved within the encryption process. Our MR-PUF has been used on block ciphers to construct a TRNG cipher block that successfully passed the NIST tests. Additionally, this paper investigated MR-PUF within a new authenticated key exchange and mutual authentication protocol between the head-end system (HES) and smart meters (SM)s in an advanced metering infrastructure (AMI) for smartgrids. The authenticated key exchange protocol utilized within the AMI was verified in this paper to meet the essential security when it comes to randomness by successfully passing the NIST tests without a post-processing algorithm.

Production of Size-Controlled Gold Nanoclusters for Vapor-Liquid-Solid Method.

This study demonstrated the deposition of size-controlled gold (Au) nanoclusters via direct-current magnetron sputtering and inert gas condensation techniques. The impact of different source parameters, namely, sputtering discharge power, inert gas flow rate, and aggregation length on Au nanoclusters' size and yield was investigated. Au nanoclusters' size and size uniformity were confirmed via transmission electron microscopy. In general, Au nanoclusters' average diameter increased by increasing all source parameters, producing monodispersed nanoclusters of an average size range of 1.7 ± 0.1 nm to 9.1 ± 0.1 nm. Among all source parameters, inert gas flow rate exhibited a strong impact on nanoclusters' average size, while sputtering discharge power showed great influence on Au nanoclusters' yield. Results suggest that Au nanoclusters nucleate via a three-body collision mechanism and grow through a two-body collision mechanism, wherein the nanocluster embryos grow in size due to atomic condensation. Ultimately, the usefulness of the produced Au nanoclusters as catalysts for a vapor-liquid-solid technique was put to test to synthesize the phase change material germanium telluride nanowires.

RRAM-based CAM combined with time-domain circuits for hyperdimensional computing.

Content addressable memory (CAM) for search and match operations demands high speed and low power for near real-time decision-making across many critical domains. Resistive RAM (RRAM)-based in-memory computing has high potential in realizing an efficient static CAM for artificial intelligence tasks, especially on resource-constrained platforms. This paper presents an XNOR-based RRAM-CAM with a time-domain analog adder for efficient winning class computation. The CAM compares two operands, one voltage and the second one resistance, and outputs a voltage proportional to the similarity between the input query and the pre-stored patterns. Processing the summation of the output similarity voltages in the time-domain helps avoid voltage saturation, variation, and noise dominating the analog voltage-based computing. After that, to determine the winning class among the multiple classes, a digital realization is utilized to consider the class with the longest pulse width as the winning class. As a demonstrator, hyperdimensional computing for efficient MNIST classification is considered. The proposed design uses 65 nm CMOS foundry technology and realistic data for RRAM with total area of 0.0077 mm2, consumes 13.6 pJ of energy per 1 k query within 10 ns clock cycle. It shows a reduction of ~ 31 × in area and ~ 3 × in energy consumption compared to fully digital ASIC implementation using 65 nm foundry technology. The proposed design exhibits a remarkable reduction in area and energy compared to two of the state-of-the-art RRAM designs.

Nanojunction Material Effect on the Photoelectric Response of Single-Wall Carbon Nanotube Rectennas.

To optimize the performance of carbon nanotube (CNT)-based rectennas, we have studied the effect of metal work function on the photodetection characteristics. Two materials of conducting nanoprobes, namely, gold (Au) and platinum (Pt), have been used to form a rectifying diode at the interface with the CNT. The electrical and optical characteristics of single-wall carbon nanotubes (SWCNTs) dispersed on top of a SiO2/Si substrate have been investigated using a conductive mode atomic force microscope (C-AFM). The I-V measurements performed for both diodes have exhibited an explicit rectification behavior with high sensitivity of a CNT-based rectenna to light. It has been observed that the lower work function metal (Au) leads to a higher on/off current ratio than the high work function metal (Pt). These experimental observations will be explained using the material characterization of the complete system along with representative energy-band diagrams.

Single wall carbon nanotube based optical rectenna.

We present an optical rectenna by engineering a rectifying diode at the interface between a metal probe of an atomic force microscope (AFM) and a single wall carbon nanotube (SWCNT) that acts as a nano-antenna. Individual SWCNT electrical and optical characteristics have been investigated using a conductive AFM nano-probe in contact with two device structures, one with a SWCNT placed on a CuO/Cu substrate and the other one with a SWCNT on a SiO2/Si substrate. The I-V measurements performed for both designs have exhibited an explicit rectification behavior and the sensitivity of carbon nanotube (CNT)-based rectenna to light. The measured output current at a set voltage value demonstrates the significant effect of the light irradiation on the current signal generated between the Au nano-probe and CNT interface. This effect is more prominent in the case of the CuO/Cu substrate. Detailed analysis of the system, including the energy band diagram, materials characterization and finite element simulation, is included to explain the experimental observations. This work will pave the way for more investigations and potential applications of CNTs as nano-rectennas in optical communication and energy harvesting systems.

Effects of top electrode material in hafnium-oxide-based memristive systems on highly-doped Si.

This work provides useful insights into the development of HfO2-based memristive systems with a p-type silicon bottom electrode that are compatible with the complementary metal-oxide-semiconductor technology. The results obtained reveal the importance of the top electrode selection to achieve unique device characteristics. The Ag/HfO2/Si devices have exhibited a larger memory window and self-compliance characteristics. On the other hand, the Au/HfO2/Si devices have displayed substantial cycle-to-cycle variation in the ON-state conductance. These device characteristics can be used as an indicator for the design of resistive-switching devices in various scenes such as, memory, security, and sensing. The current-voltage (I-V) characteristics of Ag/HfO2/Si and Au/HfO2/Si devices under positive and negative bias conditions have provided valuable information on the ON and OFF states of the devices and the underlying resistive switching mechanisms. Repeatable, low-power, and forming-free bipolar resistive switching is obtained with both device structures, with the Au/HfO2/Si devices displaying a poorer device-to-device reproducibility. Furthermore, the Au/HfO2/Si devices have exhibited N-type negative differential resistance (NDR), suggesting Joule-heating activated migration of oxygen vacancies to be responsible for the SET process in the unstable unipolar mode.

Integrated graphene oxide resistive element in tunable RF filters.

Adaptable communication systems are of great interest as they provide dynamic front end to accommodate the tunable spectrum management in advanced wireless systems. Memristor (acronym of memory resistor) is an emerging technology part of resistive RAM (RRAM) that has good potential for application in reconfigurable RF devices. The potentiality of using resistive switches for frequency tuning of high frequency RF filters is successfully explored in this article for the first time. Tunable RF filter is designed with detailed simulation using Ansys HFSS, and then correlated with measured results from experiment. As a proof of concept, a prototype of the tunable RF filter is fabricated by using a graphene oxide (GO) integrated with a conventional microstrip open stub notch filter. The resistor switching ability of the device is exploited for the frequency tuning. The resonating length of the notch filter is varied by changing the resistance of the active GO material between 'HIGH' (OFF) and 'LOW' (ON) resistance states. The measured results demonstrate the great potential of using RRAM in tunable RF devices. It also proves the possibility of tuning RF devices without any localized surface mount device (SMD) element or complex realization technique.

NeuroMem: Analog Graphene-Based Resistive Memory for Artificial Neural Networks.

Artificial Intelligence (AI) at the edge has become a hot subject of the recent technology-minded publications. The challenges related to IoT nodes gave rise to research on efficient hardware-based accelerators. In this context, analog memristor devices are crucial elements to efficiently perform the multiply-and-add (MAD) operations found in many AI algorithms. This is due to the ability of memristor devices to perform in-memory-computing (IMC) in a way that mimics the synapses in human brain. Here, we present a novel planar analog memristor, namely NeuroMem, that includes a partially reduced Graphene Oxide (prGO) thin film. The analog and non-volatile resistance switching of NeuroMem enable tuning it to any value within the RON and ROFF range. These two features make NeuroMem a potential candidate for emerging IMC applications such as inference engine for AI systems. Moreover, the prGO thin film of the memristor is patterned on a flexible substrate of Cyclic Olefin Copolymer (COC) using standard microfabrication techniques. This provides new opportunities for simple, flexible, and cost-effective fabrication of solution-based Graphene-based memristors. In addition to providing detailed electrical characterization of the device, a crossbar of the technology has been fabricated to demonstrate its ability to implement IMC for MAD operations targeting fully connected layer of Artificial Neural Network. This work is the first to report on the great potential of this technology for AI inference application especially for edge devices.

Micro-Pattern of Graphene Oxide Films Using Metal Bonding.

Recently, graphene has been explored in several research areas according to its outstanding combination of mechanical and electrical features. The ability to fabricate micro-patterns of graphene facilitates its integration in emerging technologies such as flexible electronics. This work reports a novel micro-pattern approach of graphene oxide (GO) film on a polymer substrate using metal bonding. It is shown that adding ethanol to the GO aqueous dispersion enhances substantially the uniformity of GO thin film deposition, which is a great asset for mass production. On the other hand, the presence of ethanol in the GO solution hinders the fabrication of patterned GO films using the standard lift-off process. To overcome this, the fabrication process provided in this work takes advantage of the chemical adhesion between the GO or reduced GO (rGO) and metal films. It is proved that the adhesion between the metal layer and GO or rGO is stronger than the adhesion between the latter and the polymer substrate (i.e., cyclic olefin copolymer used in this work). This causes the removal of the GO layer underneath the metal film during the lift-off process, leaving behind the desired GO or rGO micro-patterns. The feasibility and suitability of the proposed pattern technique is confirmed by fabricating the patterned electrodes inside a microfluidic device to manipulate living cells using dielectrophoresis. This work adds great value to micro-pattern GO and rGO thin films and has immense potential to achieve high yield production in emerging applications.

Human Vital Signs Detection Methods and Potential Using Radars: A Review.

Continuous monitoring of vital signs, such as respiration and heartbeat, plays a crucial role in early detection and even prediction of conditions that may affect the wellbeing of the patient. Sensing vital signs can be categorized into: contact-based techniques and contactless based techniques. Conventional clinical methods of detecting these vital signs require the use of contact sensors, which may not be practical for long duration monitoring and less convenient for repeatable measurements. On the other hand, wireless vital signs detection using radars has the distinct advantage of not requiring the attachment of electrodes to the subject's body and hence not constraining the movement of the person and eliminating the possibility of skin irritation. In addition, it removes the need for wires and limitation of access to patients, especially for children and the elderly. This paper presents a thorough review on the traditional methods of monitoring cardio-pulmonary rates as well as the potential of replacing these systems with radar-based techniques. The paper also highlights the challenges that radar-based vital signs monitoring methods need to overcome to gain acceptance in the healthcare field. A proof-of-concept of a radar-based vital sign detection system is presented together with promising measurement results.

Bipolar Cu/HfO2/p++ Si Memristors by Sol-Gel Spin Coating Method and Their Application to Environmental Sensing.

In this paper, the memristive switching behavior of Cu/ HfO2/p++ Si devices fabricated by an organic-polymer-assisted sol-gel spin-coating method, coupled with post-annealing and shadow-mask metal sputtering steps, is examined. HfO2 layers of about 190 nm and 80 nm, are established using cost-effective spin-coating method, at deposition speeds of 2000 and 4000 rotations per minute (RPM), respectively. For two types of devices, the memristive characteristics (Von, Ion, and Vreset) and device-to-device electrical repeatability are primarily discussed in correlation with the oxide layer uniformity and thickness. The devices presented in this work exhibit an electroforming free and bipolar memory-resistive switching behavior that is typical of an Electrochemical Metallization (ECM) I-V fingerprint. The sample devices deposited at 4000 RPM generally show less variation in electrical performance parameters compared to those prepared at halved spin-coating speed. Typically, the samples prepared at 4000 RPM (n = 8) display a mean switching voltage Von of 3.0 V (±0.3) and mean reset voltage Vreset of -1.1 V (±0.5) over 50 consecutive sweep cycles. These devices exhibit a large Roff/Ron window (up to 104), and sufficient electrical endurance and retention properties to be further examined for radiation sensing. As they exhibit less statistical uncertainty compared to the samples fabricated at 2000 RPM, the devices prepared at 4000 RPM are tested for the detection of soft gamma rays (emitted from low-activity Cs-137 and Am-241 radioactive sources), by assessing the variation in the on-state resistance value upon exposure. The analysis of the probability distributions of the logarithmic Ron values measured over repeated ON-OFF cycles, before, during and after exposing the devices to radiation, demonstrate a statistical difference. These results pave the way for the fabrication and development of cost-effective soft-gamma ray detectors.

MOMSense: Metal-Oxide-Metal Elementary Glucose Sensor.

In this paper, we present a novel Pt/CuO/Pt metal-oxide-metal (MOM) glucose sensor. The devices are fabricated using a simple, low-cost standard photolithography process. The unique planar structure of the device provides a large electrochemically active surface area, which acts as a nonenzymatic reservoir for glucose oxidation. The sensor has a linear sensing range between 2.2 mM and 10 mM of glucose concentration, which covers the blood glucose levels for an adult human. The distinguishing property of this sensor is its ability to measure glucose at neutral pH conditions (i.e. pH = 7). Furthermore, the dilution step commonly needed for CuO-based nonenzymatic electrochemical sensors to achieve an alkaline medium, which is essential to perform redox reactions in the absence of glucose oxidase, is eliminated, resulting in a lower-cost and more compact device.