Parallel Readout Research Articles

In-organoid single-cell CRISPR screening reveals determinants of hepatocyte differentiation and maturation

BackgroundHarnessing hepatocytes for basic research and regenerative medicine demands a complete understanding of the genetic determinants underlying hepatocyte differentiation and maturation. Single-cell CRISPR screens in organoids could link genetic perturbations with parallel transcriptomic readout in single cells, providing a powerful method to delineate roles of cell fate regulators. However, a big challenge for identifying key regulators during data analysis is the low expression levels of transcription factors (TFs), which are difficult to accurately estimate due to noise and dropouts in single-cell sequencing. Also, it is often the changes in TF activities in the transcriptional cascade rather than the expression levels of TFs that are relevant to the cell fate transition.ResultsHere, we develop Organoid-based Single-cell CRISPR screening Analyzed with Regulons (OSCAR), a framework using regulon activities as readouts to dissect gene knockout effects in organoids. In adult-stem-cell-derived liver organoids, we map transcriptomes in 80,576 cells upon 246 perturbations associated with transcriptional regulation of hepatocyte formation. Using OSCAR, we identify known and novel positive and negative regulators, among which Fos and Ubr5 are the top-ranked ones. Further single-gene loss-of-function assays demonstrate that Fos depletion in mouse and human liver organoids promote hepatocyte differentiation by specific upregulation of liver metabolic genes and pathways, and conditional knockout of Ubr5 in mouse liver delays hepatocyte maturation.ConclusionsAltogether, we provide a framework to explore lineage specifiers in a rapid and systematic manner, and identify hepatocyte determinators with potential clinical applications.

A 28-nm RRAM Computing-in-Memory Macro Using Weighted Hybrid 2T1R Cell Array and Reference Subtracting Sense Amplifier for AI Edge Inference

Non-volatile computing-in-memory (nvCIM) can potentially meet the ever-increasing demands on improving the energy efficiency (EF) for intelligent edge devices. However, it still suffers from limited input parallelism due to the parasitic effects, signal margin degradation due to device non-idealities, and large hardware cost for analog readout. In this work, we present a two-transistor-one-resistor (2T1R) resistive memory (RRAM) nvCIM macro featuring: 1) a macro structure with decoupled memory and computing data paths; 2) the weighted hybrid 2T1R (WH-2T1R) cell array; 3) the redundant sub-array mapping scheme of the most-significant-bit (RSM-MSB); and 4) reference-subtracting current sense amplifier (RS-CSA). A test-chip is silicon-verified using the 28-nm high-k/metal-gate (HKMG) logic process with foundry-developed RRAM. The test-chip performs linear analog multiply-and-accumulate (MAC) operations over 32 accumulation channels and achieves 30.34–154.04 TOPS/W with 1-bit input (IN), 3-bit weight (W), and 4-bit output (O). Evaluations with the ResNet-18 model show that the MSB-RSM scheme results in 0.96% and 2.83% improvement on CIFAR-10 and CIFAR-100 inference accuracy, respectively.

Probabilistic cell seeding and non-autofluorescent 3D-printed structures as scalable approach for multi-level co-culture modeling.

To model complex biological tissue in vitro, a specific layout for the position and numbers of each cell type is necessary. Establishing such a layout requires manual cell placement in three dimensions (3D) with micrometric precision, which is complicated and time-consuming. Moreover, 3D printed materials used in compartmentalized microfluidic models are opaque or autofluorescent, hindering parallel optical readout and forcing serial characterization methods, such as patch-clamp probing. To address these limitations, we introduce a multi-level co-culture model realized using a parallel cell seeding strategy of human neurons and astrocytes on 3D structures printed with a commercially available non-autofluorescent resin at micrometer resolution. Using a two-step strategy based on probabilistic cell seeding, we demonstrate a human neuronal monoculture that forms networks on the 3D printed structure and can establish cell-projection contacts with an astrocytic-neuronal co-culture seeded on the glass substrate. The transparent and non-autofluorescent printed platform allows fluorescence-based immunocytochemistry and calcium imaging. This approach provides facile multi-level compartmentalization of different cell types and routes for pre-designed cell projection contacts, instrumental in studying complex tissue, such as the human brain.

High-throughput microbead assay system with a portable, cost-effective Wi-Fi imaging module, and disposable multi-layered microfluidic cartridges for virus and microparticle detection, and tracking.

In recent years biomedical scientific community has been working towards the development of high-throughput devices that allow a reliable, rapid and parallel detection of several strains of virus or microparticles simultaneously. One of the complexities of this problem lies on the rapid prototyping of new devices and wireless rapid detection of small particles and virus alike. By reducing the complexity of microfluidics microfabrication and using economic materials along with makerspace tools (Kundu et al. 2018) it is possible to provide an affordable solution to both the problems of high-throughput devices and detection technologies. We present the development of a wireless, standalone device and disposable microfluidics chips that rapidly generate parallel readouts for selected, possible virus variants from a nasal or saliva sample, based on motorized and non-motorized microbeads detection, and imaging processing of the motion tracks of these beads in micrometers. Microbeads and SARS-CoV-2 COVID-19 Delta variant were tested as proof-of-concept for testing the microfluidic cartridges and wireless imaging module. The Microbead Assay (MA) system kit consists of a Wi-Fi readout module, a microfluidic chip, and a sample collection/processing sub-system. Here, we focus on the fabrication and characterization of the microfluidic chip to multiplex various micrometer-sized beads for economic, disposable, and simultaneous detection of up to six different viruses, microparticles or variants in a single test, and data collection using a commercially available, Wi-Fi-capable, and camera integrated device (Fig. 1).

Readout Electronics for Spatial Distribution Measurement of Neutron Beam Flux in BNCT

Boron neutron capture therapy (BNCT) is a promising cancer treatment that selectively destroys tumor cells using a neutron beam. However, accurately and fast measuring the spatial distribution of neutron flux is critical to ensuring effective treatment. To address this challenge, Micromegas detectors are applied for the first time to measure the spatial distribution of neutron beam flux in BNCT. Due to the high flux, large area, and multiple components of the BNCT beam, the design of readout electronics that can handle high counting rate, large channel numbers, high integration, and discrimination of multiple beam components is challenging. This paper proposes a targeted readout electronics system to overcome this challenge. A modular readout structure based on the PCI Express (PXIe) platform is designed for 384-channel readout. A fully parallel readout structure is developed and fast shaper parameters are optimized to achieve high counting rate for each readout channel. A multi-channel high-speed, large-capacity caching technique is developed to address the high-speed data storage problem. Digital shapers are implemented in field-programmable gate array (FPGA) to achieve high integration. Tests demonstrate that each readout channel can support a counting rate of 800 kHz and achieve an excellent position resolution of 1.4 mm. Furthermore, final tests on the BNCT beam confirm that our system can successfully measure the flux spatial distribution of different neutron components.

Trap-Integrated Superconducting Nanowire Single-Photon Detectors with Improved RF Tolerance for Trapped-Ion Qubit State Readout.

State readout of trapped-ion qubits with trap-integrated detectors can address important challenges for scalable quantum computing, but the strong rf electric fields used for trapping can impact detector performance. Here, we report on NbTiN superconducting nanowire single-photon detectors (SNSPDs) employing grounded aluminum mirrors as electrical shielding that are integrated into linear surface-electrode rf ion traps. The shielded SNSPDs can be operated at applied rf trapping potentials of up to 54 Vpeak at 70 MHz and temperatures of up to 6 K, with a maximum system detection efficiency of 68 %. This performance should be sufficient to enable parallel high-fidelity state readout of a wide range of trapped ion species in typical cryogenic apparatus.

Integrated Filter Design for Analog Field Mill Sensor Interface

The design process of an integrated bandpass filter targeted for the noise filtering stage of the synchronous demodulation unit of an electric field mill sensor interface is presented. The purpose of this study of filter integration techniques is to avoid the challenging and, in some cases, impossible passive element integration process and to incorporate the final filter design in an entirely integrated field mill sensing system with superior performance and an optimized silicon-to-cost ratio. Four different CMOS filter implementations in the 0.18 μm process of XFAB, using OTA (Operational Transconductance Amplifier)-based configurations for passive element replacement in cascaded filter topologies and leapfrog techniques, are compared in terms of noise performance, total harmonic distortion, dynamic range, and power consumption, as well as in terms of integrability, silicon area, and performance degradation at process corners/mismatches. The optimum filter design performance-wise and process-wise is included in the final design of the integrated analog readout of a field mill sensor, and post-layout simulation results of the total circuit are presented.

On‐chip Diamond MEMS Magnetic Sensing through Multifunctionalized Magnetostrictive Thin Film

AbstractElectrically integrable, high‐sensitivity, and high‐reliability magnetic sensors are not yet realized at high temperatures (500 °C). In this study, an integrated on‐chip single‐crystal diamond (SCD) micro‐electromechanical system (MEMS) magnetic transducer is demonstrated by coupling SCD with a large magnetostrictive FeGa film. The FeGa film is multifunctionalized to actuate the resonator, self‐sense the external magnetic field, and electrically readout the resonance signal. The on‐chip SCD MEMS transducer shows a high sensitivity of 3.2 Hz mT−1 from room temperature to 500 °C and a low noise level of 9.45 nT Hz−1/2 up to 300 °C. The minimum fluctuation of the resonance frequency is 1.9 × 10−6 at room temperature and 2.3 × 10−6 at 300 °C. An SCD MEMS resonator array with parallel electric readout is subsequently achieved, thus providing a basis for the development of magnetic image sensors. The present study facilitates the development of highly integrated on‐chip MEMS resonator transducers with high performance and high thermal stability.

Digital and Analog Detection of SARS-CoV-2 Nucleocapsid Protein via an Upconversion-Linked Immunosorbent Assay.

The COVID-19 crisis requires fast and highly sensitive tests for the early stage detection of the SARS-CoV-2 virus. For detecting the nucleocapsid protein (N protein), the most abundant viral antigen, we have employed upconversion nanoparticles that emit short-wavelength light under near-infrared excitation (976 nm). The anti-Stokes emission avoids autofluorescence and light scattering and thus enables measurements without optical background interference. The sandwich upconversion-linked immunosorbent assay (ULISA) can be operated both in a conventional analog mode and in a digital mode based on counting individual immune complexes. We have investigated how different antibody combinations affect the detection of the wildtype N protein and the detection of SARS-CoV-2 (alpha variant) in lysed culture fluid via the N protein. The ULISA yielded a limit of detection (LOD) of 1.3 pg/mL (27 fM) for N protein detection independent of the analog or digital readout, which is approximately 3 orders of magnitude more sensitive than conventional enzyme-linked immunosorbent assays or commercial lateral flow assays for home testing. In the case of SARS-CoV-2, the digital ULISA additionally improved the LOD by a factor of 10 compared to the analog readout.

Integration of microlenses on surface-micromachined optical ultrasound transducer array to improve detection sensitivity for parallel data readout.

This Letter reports the integration of microlenses (MLs) on a surface-micromachined optical ultrasound transducer (SMOUT) array to enable parallel ultrasound data readout from a multiplicity of elements. The MLs are fabricated by photoresist patterning and reflow, and their focal lengths are optimized with parametric studies. Experiments are conducted to characterize the acoustic responsivity and its uniformity of the SMOUT-ML elements under different conditions. The temporal stability of SMOUT-ML elements immersed in water is assessed by monitoring their acoustic response continuously for 1 week. Parallel ultrasound signal readout is simulated with a small group of SMOUT-ML elements. Experimental results show that high acoustic sensitivity and excellent long-term stability can be achieved by the ML-integrated SMOUT array, which could provide a promising approach for enabling parallel ultrasound data acquisition for improving the imaging speed of 3D acoustic tomography.

Toward a Monolithic Pixel Sensor for Heavy Ion Spectroscopy—Pixel Structure Design and Optimization

Detection and classification of cosmic particles is essential for many scientific and engineering applications. Currently available heavy ion detectors necessitate an external readout integrated circuit when conducting both measurements of particle energy deposition and particle incident position. In this paper, we propose an innovative monolithic pixel detector topology capable of distinguishing between particles in a predefined LET range. The analog and digital readout circuitry are incorporated into the pixel region while maintaining almost an 100% detection fill factor over the entire pixel array. We present comprehensive CAD 3D simulations of the device to verify the applicability of the detector for galactic cosmic rays with the specified LET levels and induced charge distribution. We evaluate the charge collection performance under heavy-ion hit conditions and provide an assessment of the impact on charge collection from the particle impinging position, particle LET, angle of penetration and circuit bias. The results indicate a linear relationship between particle LET and collected charge, regardless of the ion hit position and almost independent of the circuit voltage bias. The simulation results for various particle incident angles show correlations between charge collection and particle trajectory length. We propose an implementation which makes it possible to determine the particle angle of penetration and particle LET attributes. The radiation tolerance of the sensor was estimated. Its applicability to the non-ionizing radiation environment was shown to be adequate for low Earth orbits.

Experimental characterization of a fast X-ray spectroscopic imager module using the ALTAIR P3 ASIC for real-time contaminants detection

X-ray imagers with spectroscopic capabilities and high photon count rates are finding promising applications in industrial real-time inspection systems. In this context, XSpectra® combines a CdTe-based linear energy-resolved photon counting (ERPC) pixel sensor with real-time image processing techniques to detect low and high density contaminants. The detection unit makes use of a new analog read-out ASIC that has been designed by Politecnico di Milano to meet strict application requirements both in energy resolution and achievable photon count rate. A room-temperature low-rate spectroscopic characterization of the system at a peaking time of 60 ns showed an average equivalent noise charge of 259 electrons r.m.s. (2.72 keV FWHM in CdTe) and an average FWHM of the 59.5 keV 241Am line of 3.6 keV, with a 3σ dispersion in noise performance of ±10% over 256 channels. The detection unit was tested in high incoming photon flux conditions by means of an X-ray tube. Minimal spectral distortion due to pile-up events is obtained up to an Incoming Count Rate of 2.5 Mcps/channel, while the maximum counting capability of energy-resolved events is 2.2 Mcps/channel.

Development and operation of the CGEM Inner Tracker for the BESIII experiment

The extension of data acquisition for the BEijing Spectrometer (BESIII) experiment until at least 2030 has resulted in upgrades to both the accelerator and the detector. An innovative Cylindrical Gas Electron Multiplier (CGEM) is under construction to upgrade the inner tracker, which is suffering from aging. The CGEM Inner Tracker (CGEM-IT) was designed to restore efficiency and enhance the reconstruction of the secondary vertexes position. Reconstruction in the magnetic field of 1 T requires an analog readout and an electronic contribution to the time resolution better than 5 ns. The entire system consists of about 10,000 electronic channels and must maintain a peak rate of 14 kHz/strip of signal hits for the innermost layer of the CGEM-IT. The CGEM readout system is based on the innovative TIGER ASIC, which is manufactured using 110 nm CMOS technology. A special readout chain consisting of GEM Read Out Cards (GEMROC) was developed for data acquisition. Two of three layers, equipped with the final electronics, have been operating in Beijing since January 2020 collecting cosmic ray data in a test facility, remotely controlled by the Italian group due to the pandemic situation. Since it was not possible to perform further tests on the cylindrical detector, in July 2021, a test beam was conducted at CERN with the final electronics configuration on a small prototype consisting of four triple-GEM planar detectors. In this presentation, the general status of the project CGEM-IT will be presented, with particular emphasis on the results of the test beam data collection.

KITE: High frame rate, high count rate pixelated electron counting ASIC for 4D STEM applications featuring high-Z sensor

KITE is a novel mixed-mode CMOS electron counting ASIC developed for the readout of pixelated semiconductor radiation detectors targeted to 4D STEM applications. The chip features a pixel pitch of 100 μm arranged in a 192 × 192 matrix and can be bump-bonded to both Si and high-Z sensor materials. The design of an extremely fast front-end electronics and the use of the instant retrigger mechanism allow for a non-paralyzable counting mode up to above 108 cts/s/pix, which corresponds to a 300 keV electron beam current of 14 pA/pix. The massive parallel readout in combination with two on-chip data compression techniques – 2 × 2 pixel digital binning and floating-point counter encoding – allows for frame rates higher than 100 kfps (this work), in principle extendable to almost 500 kfps with improved readout boards. We successfully characterized a first detector prototype featuring a 1500 μm-thick CdZnTe sensor with fluorescence X-rays from elemental targets and with 200 keV and 300 keV electrons in terms of energy response, threshold trimming accuracy, single event multiplicity distribution, spatial uniformity and temporal stability, count rate capability and imaging performances (MTF and DQE). Custom Monte Carlo simulations complemented when possible the experimental data for cross-validation purposes, generally with a very good matching. Finally, a proof-of-concept 4D STEM acquisition is presented and discussed.

A 1Gpixel 10FPS CMOS image sensor using pixel array high-speed readout technology

In the very large array CMOS image sensor (CIS), the very large parasitic resistors and capacitors on the column bus cause very slow charging and discharging speeds and affect the readout speed seriously. In order to solve the problem, this work proposed a high-speed readout circuit that can be applied to the very large array of column parallel readout mechanism CIS. Based on 55 nm CIS special process, on the premise of not produce additional bus, by tracking the analog signal settling process in real time, self-acceleration is realized in the terminal of the column bus, then the speed of charging and discharging are improved greatly. In the work, the column bus parasitic parameters of 42,624 × 24,000 pixels CMOS image sensor with 4 μm pixel pitch are analyzed in detail and a method for establishing self-acceleration of column bus is proposed. The experimental results show that the charging time is shortened from 4μs to 790 ns, and the discharging time is shortened from 22.43μs to 1.17μs under 38.3 pF parasitic capacitance and 26.5 kΩ parasitic resistance in the column bus. On the one hand, the frame per second (FPS) of the 1Gpixel CMOS image sensor reach 10FPS, on the other hand, the column bus tail current can be reduced to 1.5 μA, which reducing the power consumption of pixel array, and the sampling interval time of the correlation double sampling (CDS) is compressed, so broadened the frequency of noise suppression. While realizing self-acceleration, the additional power consumption single column is less than 10 μA.

An Energy-Efficient Mixed-Bit CNN Accelerator With Column Parallel Readout for ReRAM-Based In-Memory Computing

Computing-In-memory (CIM) accelerators have the characteristics of storage and computing integration, which has the potential to break through the limit of Moore’s law and the bottleneck of Von-Neumann architecture for convolutional neural networks (CNN) implementation improvement. However, the performance of CIM accelerators is still limited by conventional CNN architectures and inefficient readouts. To increase energy-efficient performance, an optimized CNN model is required and a low-power column parallel readout is necessary for edge-computing hardware. In this work, an ReRAM-based CNN accelerator is designed. Mixed-bit operations from 1 bit to 8 bits are supported by an effective bitwidth configuration scheme to implement Neural Architecture Search (NAS)-optimized layer-wise multi-bit CNNs. Besides, column-parallel readout is achieved with excellent energy-efficient performance by a variation-reduction accumulation mechanism and low-power readout circuits. Additionally, we further explore systolic data reuse in an ReRAM-based PE array. Experiments are implemented on NAS-optimized ResNet-18. Benchmarks show that the proposed ReRAM accelerator can achieve peak energy efficiency of 2490.32 TOPS/W for 1-bit operation and average energy efficiency of 479.37 TOPS/W for <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1\sim 8$ </tex-math></inline-formula> -bit operations with evaluating NAS-optimized multi-bitwidth CNNs. When compared with the state-of-the-art works, the proposed accelerator shows at least <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$14.18{\times }$ </tex-math></inline-formula> improvement on energy efficiency.

A Multimodal and Multifunctional CMOS Cellular Interfacing Array for Digital Physiology and Pathology Featuring an Ultra Dense Pixel Array and Reconfigurable Sampling Rate.

The article presents a fully integrated multimodal and multifunctional CMOS biosensing/actuating array chip and system for multi-dimensional cellular/tissue characterization. The CMOS chip supports up to 1,568 simultaneous parallel readout channels across 21,952 individually addressable multimodal pixels with 13 μm × 13 μm 2-D pixel pitch along with 1,568 Pt reference electrodes. These features allow the CMOS array chip to perform multimodal physiological measurements on living cell/tissue samples with both high throughput and single-cell resolution. Each pixel supports three sensing and one actuating modalities, each reconfigurable for different functionalities, in the form of full array (FA) or fast scan (FS) voltage recording schemes, bright/dim optical detection, 2-/4-point impedance sensing (ZS), and biphasic current stimulation (BCS) with adjustable stimulation area for single-cell or tissue-level stimulation. Each multi-modal pixel contains an 8.84 μm × 11 μm Pt electrode, 4.16 μm × 7.2 μm photodiode (PD), and in-pixel circuits for PD measurements and pixel selection. The chip is fabricated in a standard 130nm BiCMOS process as a proof of concept. The on-chip electrodes are constructed by unique design and in-house post-CMOS fabrication processes, including a critical Al shorting of all pixels during fabrication and Al etching after fabrication that ensures a high-yield planar electrode array on CMOS with high biocompatibility and long-term measurement reliability. For demonstration, extensive biological testing is performed with human and mouse progenitor cells, in which multidimensional biophysiological data are acquired for comprehensive cellular characterization.

High-content CRISPR screening in tumor immunology.

CRISPR screening is a powerful tool that links specific genetic alterations to corresponding phenotypes, thus allowing for high-throughput identification of novel gene functions. Pooled CRISPR screens have enabled discovery of innate and adaptive immune response regulators in the setting of viral infection and cancer. Emerging methods couple pooled CRISPR screens with parallel high-content readouts at the transcriptomic, epigenetic, proteomic, and optical levels. These approaches are illuminating cancer immune evasion mechanisms as well as nominating novel targets that augment T cell activation, increase T cell infiltration into tumors, and promote enhanced T cell cytotoxicity. This review details recent methodological advances in high-content CRISPR screens and highlights the impact this technology is having on tumor immunology.

Design and optimization of the CEPC scintillator hadronic calorimeter

The Circular Electron Positron Collider (CEPC) is a next-generation electron–positron collider proposed for precision measurement of the properties of the Higgs boson. A major challenge for the CEPC detector is achieving a boson mass resolution (BMR) of 4%, which is required to separate the Higgs, Z, and W bosons in their hadronic decays. The baseline design of the CEPC detector was guided by the particle flow algorithm (PFA) concept to satisfy the BMR requirements. The BMR performance obtained by the PFA approach is primarily determined by the shower separation capability and energy resolution of the calorimeters of the detector system. A hadronic calorimeter with high granularity is crucial for providing the required separation power and energy resolution for the desired BMR. In this context, the analogue hadron calorimeter (AHCAL), a scintillator hadronic calorimeter with analogue readout, is a potential hadronic calorimeter option for the CEPC detector. In this study, key design parameters of the AHCAL, including scintillator cell size, number of sampling layers, absorber thickness, and scintillator thickness, were optimized for BMR performance on the benchmark process of e + e - ⟶ νν̅H,H ⟶ gg. Notably, herein, a set of optimized design parameters is presented for the CEPC AHCAL that meets the required BMR with reduced readout channels. Specifically, the set of proposed AHCAL design parameters is as follows: 40 sampling layers, 20 mm steel thickness, and 40× 40× 3 mm3 scintillator size for every tile. This design achieves a BMR of 3.73% and remarkably reduces the number of readout channels.

Front-end electronics for silicon strip trackers: Architectures and evolution

Tracking detectors based on segmented semiconductor sensors have been present in high-energy physics experiments for more than 40 years. The development of these sensors was always strongly linked to advances in CMOS technologies that offer features supporting the design of specialized ASICs for readout purposes. While in the beginning, the front-end electronics only provided simple signal reception and amplification, sending out the raw analog data, growing demands from the experiments lead designers to begin directly integrating more advanced features for data processing and storage, power management, calibration functions, amongst others, on-chip. This development was, and continues to be, possible due to CMOS technology evolution, in particular the scaling. Besides higher speed and better transconductance, today’s sub-micron processes offer intrinsic ionizing radiation tolerance which, together with Single Event Effect (SEE) hardening techniques, allows design for reliable operation in a harsh radiation environment. Despite the enhanced functionality and greater number of transistors, higher time resolution and, in consequence, faster analog shaping and readout speed, the power consumption of typical front-end electronics measured per area of tracking detector remains of the order of a few tens of mW per square centimeter. The basic architecture of the input stage has also remained practically the same over the last 40 years. The optimal solution providing wide bandwidth and high open-loop gain at minimum power is the cascode: a cascade of common-source and common-gate amplifiers. Although each particular implementation differs slightly depending on the specific requirements and process used, the core of the preamplifier remains the same since its conception.