Variation Tolerance Research Articles

10‐3: High Refractive Index Glass Wafers for Augmented Reality Devices using Waveguide Technology: Recent Advances in Control of Quality Parameters and their Correlation with Device Properties

Waveguide Technology is widely believed to constitute one of the most promising approaches to realize affordable Augmented Reality (AR) / Mixed Reality (MR) devices combining smallest form‐factor with uncompromised image quality allowing for full immersion user experience. Optical waveguides are made from special grade glass wafers. The characteristics of such wafers are directly determining image properties, such as Field‐of‐View, contrast, brightness, distortion of the image projected into the user's eye and many more. We are reporting latest advances in measuring and controlling key quality parameters with focus on total thickness variation, optical homogeneity and thickness tolerance of the wafers. We discuss the impact of these parameters on image quality using optical modelling of the waveguides.

Long-read sequencing reveals intra-species tolerance of substantial structural variations and new subtelomere formation in C. elegans.

Long-read sequencing technologies have contributed greatly to comparative genomics among species and can also be applied to study genomics within a species. In this study, to determine how substantial genomic changes are generated and tolerated within a species, we sequenced a C. elegans strain, CB4856, which is one of the most genetically divergent strains compared to the N2 reference strain. For this comparison, we used the Pacific Biosciences (PacBio) RSII platform (80×, N50 read length 11.8 kb) and generated de novo genome assembly to the level of pseudochromosomes containing 76 contigs (N50 contig = 2.8 Mb). We identified structural variations that affected as many as 2694 genes, most of which are at chromosome arms. Subtelomeric regions contained the most extensive genomic rearrangements, which even created new subtelomeres in some cases. The subtelomere structure of Chromosome VR implies that ancestral telomere damage was repaired by alternative lengthening of telomeres even in the presence of a functional telomerase gene and that a new subtelomere was formed by break-induced replication. Our study demonstrates that substantial genomic changes including structural variations and new subtelomeres can be tolerated within a species, and that these changes may accumulate genetic diversity within a species.

Generation of C5-desoxy analogs of tetrahydroisoquinoline alkaloids exhibiting potent DNA alkylating ability.

C5-desoxy analogs of tetrahydroisoquinoline (THIQ) alkaloids were designed and synthesized as hitherto unexplored structural variants for evaluation of their DNA alkylating activities. While chemical synthesis of the C5-desoxy analogs bearing a phenolic hydroxyl group in the A-ring of the saframycins was assumed to be laborious based on semi-synthetic modifications, a chemo-enzymatic approach allowed for concise access to the analogs. The C5-desoxy analog 7 exhibited greater DNA alkylating ability with a wider tolerance for the sequence variations compared to cyanosafracin B. The C5-desoxy A-ring having a C8 phenolic hydroxyl group, and a C1 substituent in the vicinity of the C21 aminonitrile responsible for DNA alkylation, were demonstrated to play pivotal roles in the interaction between the THIQ alkaloids and DNA.

Exploring Cycle-to-Cycle and Device-to-Device Variation Tolerance in MLC Storage-Based Neural Network Training

A multilevel cell (MLC) memristor that provides high-density on-chip memory has become a promising solution for energy-efficient artificial neural networks (ANNs). However, MLC storage that stores multiple bits per cell is prone to device variation. In this paper, the device variation tolerance of ANN training is investigated based on our cell-specific variation modeling method, which focuses on characterizing realistic cell-level variation. The parameters of cycle-to-cycle variation (CCV) and device-to-device variation (DDV) are extracted separately from the experimental data of a 39-nm, 1-Gb phase-change random access memory (PCRAM) array. A quantized neural network designed for low bit-width (≥6-bit) training is used for simulations to demonstrate the potential of MLC storage. Our results demonstrate that training is more vulnerable to DDV than CCV, and CCV can even compensate for accuracy degradation caused by severe DDV. As a result, for a multilayer perceptron (MLP) on Modified National Institute of Standards and Technology (MNIST) database, 95% accuracy can be achieved with three MLC PCRAM devices per weight, which is a 40% reduction in the number of cells compared with using conventional single-level cells (SLCs). If the size of DDV is reduced by half, then only two cells, that is 60% fewer cells than using SLC, are needed.

Phenomics and genomics of finger millet: current status and future prospects.

Diverse gene pool, advanced plant phenomics and genomics methods enhanced genetic gain and understanding of important agronomic, adaptation and nutritional traits in finger millet. Finger millet (Eleusine coracana L. Gaertn) is an important minor millet for food and nutritional security in semi-arid regions of the world. The crop has wide adaptability and can be grown right from high hills in Himalayan region to coastal plains. It provides food grain as well as palatable straw for cattle, and is fairly climate resilient. The crop has large gene pool with distinct features of both Indian and African germplasm types. Interspecific hybridization between Indian and African germplasm has resulted in greater yield enhancement and disease resistance. The crop has shown numerous advantages over major cereals in terms of stress adaptation, nutritional quality and health benefits. It has indispensable repository of novel genes for the benefits of mankind. Although rapid strides have been made in allele mining in model crops and major cereals, the progress in finger millet genomics is lacking. Comparative genomics have paved the way for the marker-assisted selection, where resistance gene homologues of rice for blast and sequence variants for nutritional traits from other cereals have been invariably used. Transcriptomics studies have provided preliminary understanding of the nutritional variation, drought and salinity tolerance. However, the genetics of many important traits in finger millet is poorly understood and need systematic efforts from biologists across disciplines. Recently, deciphered finger millet genome will enable identification of candidate genes for agronomically and nutritionally important traits. Further, improvement in genome assembly and application of genomic selection as well as genome editing in near future will provide plethora of information and opportunity to understand the genetics of complex traits.

A Unified Clock and Switched-Capacitor-Based Power Delivery Architecture for Variation Tolerance in Low-Voltage SoC Domains

Correctly operating digital SoC domains at their target frequencies require the addition of supply voltage ( $V_{\mathrm{ dd}}$ ) guardbands to account for supply droop events and temperature variation. These guardbands degrade processor energy efficiency, especially in low-voltage sensor and IoT applications due to increased delay sensitivity to temperature and $V_{\mathrm{ dd}}$ variation. In this paper, we present an all-digital unified clock and power (UniCaP-SC) architecture that combines switched-capacitor (SC)-based voltage control and clock frequency regulation into a single loop to significantly reduce required $V_{\mathrm{ dd}}$ guardbands. A UniCaP-SC test chip consisting of a near-threshold voltage (NTV) ARM Cortex-M0 processor was fabricated in 65-nm CMOS. The fully integrated system enables all-digital construction, aggressive $V_{\mathrm{ dd}}$ margin reduction, and continuous $V_{\mathrm{ dd}}$ scalability using SC-based voltage converters while no additional decoupling capacitance (decap). Test-chip measurements demonstrate a 16% $V_{\mathrm{ dd}}$ reduction corresponding to a 94% $V_{\mathrm{ dd}}$ margin recovery or an equivalent $3.2\times $ increase in the operating clock frequency ( $f_{\mathrm{ clk}}$ ).

Operation-Dependent Frequency Scaling Using Desynchronization

Asynchronous circuits are inherently more robust than their synchronous counterparts. Desynchronization is a way to obtain asynchronous circuits from a synchronous specification using standard design tools while improving circuit for variation tolerance, electromagnetic interference, and resulting in similar area, delay, and energy as the synchronous baseline. This paper proposes a novel operation-dependent desynchronization technique, which desynchronizes the circuit and improves performance beyond the limits of synchronous design. We perform a case study of our proposed technique on RISC-V rocket core and show significant improvement in performance with minimal power and area overheads.

Swiss Public Administration. Making the State Work Successfully. Ladner, Andreas, Soguel, Nils, Emery, Yves, Weerts, Sophie and StéphaneNahrath (eds) Cham, Palgrave Macmillan (2019), 384 p., ISBN 978‐3‐319‐92380‐2

Swiss Public Administration. Making the State Work Successfully. Ladner, Andreas, Soguel, Nils, Emery, Yves, Weerts, Sophie and StéphaneNahrath (eds) Cham, Palgrave Macmillan (2019), 384 p., ISBN 978‐3‐319‐92380‐2

Response of Tibetan Wild Barley Genotypes to Drought Stress and Identification of Quantitative Trait Loci by Genome-Wide Association Analysis.

Tibetan wild barley has been identified to show large genetic variation and stress tolerance. A genome-wide association (GWA) analysis was performed to detect quantitative trait loci (QTLs) for drought tolerance using 777 Diversity Array Technology (DArT) markers and morphological and physiological traits of 166 Tibetan wild barley accessions in both hydroponic and pot experiments. Large genotypic variation for these traits was found; and population structure and kinship analysis identified three subpopulations among these barley genotypes. The average LD (linkage disequilibrium) decay distance was 5.16 cM, with the minimum on 6H (0.03 cM) and the maximum on 4H (23.48 cM). A total of 91 DArT markers were identified to be associated with drought tolerance-related traits, with 33, 26, 16, 1, 3, and 12 associations for morphological traits, H+K+-ATPase activity, antioxidant enzyme activities, malondialdehyde (MDA) content, soluble protein content, and potassium concentration, respectively. Furthermore, 7 and 24 putative candidate genes were identified based on the reference Meta-QTL map and by searching the Barleymap. The present study implicated that Tibetan annual wild barley from Qinghai–Tibet Plateau is rich in genetic variation for drought stress. The QTLs detected by genome-wide association analysis could be used in marker-assisting breeding for drought-tolerant barley genotypes and provide useful information for discovery and functional analysis of key genes in the future.

A Preliminary Plains Cree Speech Synthesizer

This paper discusses the development and evaluation of a Speech Synthesizer for Plains Cree, an Algonquian language of North America. Synthesis is achieved using Simple4All and evaluation was performed using a modified Cluster Identification, Semantically Unpredictable Sentence, and a basic dichotomized judgment task. Resulting synthesis was not well received; however, observations regarding the process of speech synthesis evaluation in North American indigenous communities were made: chiefly, that tolerance for variation is often much lower in these communities than for majority languages. The evaluator did not recognize grammatically consistent but semantically nonsense strings as licit language. As a result, monosyllabic clusters and semantically unpredictable sentences proved not the most appropriate evaluate tools. Alternative evaluation methods are discussed.

Threshold Switch Augmented STT MRAM: Design Space Analysis and Device-Circuit Co-Design

We analyze the augmentation of spin-transfer torque (STT) MRAM with electrically driven selective phase transition of a threshold switch (TS) to enhance the read operation. This paper provides a comprehensive discussion on necessary design considerations for TS augmented (TSA) MRAMs. We deduce constraints for read and write biasing that yields improved read operation of TSA MRAMs. We explain the dependence of read/write performance metrics on read/write biases and the properties (resistance and critical currents for transitions) of the TS. With proper device-circuit optimization, TSA MRAM shows up to 70% larger sense margin, ~27% higher data stability with ~40% less power for read operation compared to STT MRAM (in nominal condition). We evaluate the impact of variation on TSA MRAM through Monte Carlo simulations. We report that even with variation induced spread in the distribution of bit-line voltages, TSA MRAM provides $\sim 1.7\times $ larger voltage differential between parallel and antiparallel states. For the write operation, the TSA MRAM consumes ~10% less average power and demands only ~5% more write time extension than the STT MRAM to achieve the same level of variation tolerance.

Morphological Variation Tracks Environmental Gradients in an Agricultural Pest, Phaulacridium vittatum (Orthoptera: Acrididae).

Invertebrate pests often show high morphological variation and wide environmental tolerances. Knowledge of how phenotypic variation is associated with environmental heterogeneity can elucidate the processes underpinning these patterns. Here we examine morphological variation and relative abundance along environmental gradients in a widespread agricultural pest, native to Australia, the wingless grasshopper Phaulacridium vittatum (Sjöstedt). We test for correlations between body size, wing presence, and stripe polymorphism with environmental variables. Using multiple regression and mixed-effects modeling, body size and stripe polymorphism were positively associated with solar radiation, and wing presence was positively associated with foliage projective cover (FPC). There were no associations between body size or morphological traits with relative abundance. However, relative abundance was positively associated with latitude, soil moisture, and wind speed, but was negatively associated with FPC. Therefore, sites with low relative abundance and high forest cover were more likely to contain winged individuals. Overall, our results suggest that environmental and climatic conditions strongly influence the relative abundance and the distribution of morphotypes in P. vittatum, which is likely to affect dispersal and fitness in different landscapes. This knowledge is useful for informing how environmental change might influence the future spread and impact of this agricultural pest.

Amorphous/ordered dual carbon coated silicon nanoparticles as anode to enhance cycle performance in lithium ion batteries

Carbon-coated layer on silicon nanoparticles (SiNPs) can improve the conductivity of SiNPs and affect the cycle performance of SiNPs based anode in lithium ion batteries. SiNPs coated with three different type of carbon (amorphous carbon, order carbon, amorphous/ordered dual carbon) are prepared and their electrochemical properties are investigated. Amorphous carbon (AC) coating shows a better conductivity, while the ordered carbon (OC) coating presents a good volume variation tolerance. Interestingly, amorphous/ordered dual carbon (AC/OC) coating structure simultaneously has the two advantages that amorphous and ordered carbons coating structures have. Hence, as an anode material in lithium ion batteries, AC/OC-coated SiNPs demonstrates an eclectic initial discharge capacity of 3300 mAhg−1 and exhibits an enhanced cycle performance that remains a discharge specific capacity of 1020 mAhg−1 at 200 cycles as well as 650 mAhg−1 after 500 cycles at the current density of 0.36 Ag−1 in the voltage range of 0.01–1.5 V. The preparation procedure of SiNPs@AC/OC is easy for large scale production and SiNPs@AC/OC can be mixed with graphite as composite anode materials for lithium ion batteries in industrial application.

A Fast Hill Climbing Algorithm for Defect and Variation Tolerant Logic Mapping of Nano-Crossbar Arrays

Nano-crossbar arrays are area and power efficient structures, generally realized with self-assembly based bottom-up fabrication methods as opposed to relatively costly traditional top-down lithography techniques. This advantage comes with a price: very high process variations. In this work, we focus on the worst-case delay optimization problem in the presence of high process variations. As a variation tolerant logic mapping scheme, a fast hill climbing algorithm is proposed; it offers similar or better delay improvements with much smaller runtimes compared to the methods in the literature. Our algorithm first performs a reducing operation for the crossbar motivated by the fact that the whole crossbar is not necessarily needed for the problem. This significantly decreases the computational load up to 72 percent for benchmark functions. Next, initial column mapping is applied. After the first two steps that can be considered as preparatory, the algorithm proceeds to the last step of hill climbing row search with column reordering where optimization for variation tolerance is performed. As an extension to this work, we directly apply our hill climbing algorithm on defective arrays to perform both defect and variation tolerance. Again, simulation results approve the speed of our algorithm, up to 600 times higher compared to the related algorithms in the literature without sacrificing defect and variation tolerance performance.

Synchronized Cell-Balancing Charging of Supercapacitors: A Consensus-Based Approach

The switched resistor circuit has been a popular cell balancing scheme in low-power supercapacitor applications. However, the cell balancing performance of the circuit is vulnerable to current variations and resistance deviations with the existing asynchronous cell-balancing (ACB) method. To address this challenge, in this paper, we propose a synchronized cell-balancing (SCB) method based on the consensus theory, with the aim of synchronizing cell voltages during the charging process. First, the cyber-physical modeling of the cell balancing system is presented, where the physical layer models the circuit components and the cyber layer represents the communication topology among cells. Second, a distributed voltage tracker is proposed using a consensus tracking protocol, which benefits from a good scalability. A compensator is designed to stabilize the closed-loop multiple-in-multiple-out (MIMO) system and frequency-domain methods are applied to determine the compensator parameters. A laboratory testbed has been built to verify the effectiveness of the proposed method. Experiment results show that the SCB method has a better tolerance of current variations and resistance deviations than the ACB method.

Transcriptomic analysis dissects the mechanistic insight into the Daphnia clonal variation in tolerance to toxic Microcystis

AbstractCyanobacteria have become more prevalent than other phytoplankton in freshwater assemblages during summer. In such conditions, cyanobacterial traits may reduce zooplankton fitness and the energy flow efficiency from primary producers to aquatic herbivores. Cladocerans, as the dominant zooplankton grazers in freshwater ecosystems, exhibit clonal variation in their tolerance to cyanobacteria with an increasing gradient in eutrophication history. Hitherto, research on the full modes of action (MoAs) of Daphnia clonal differences in tolerance to toxic Microcystis still remains in its infancy. We conducted fitness and transcriptome analyses on two Daphnia clones, clone TH09 and TH14. A significant decline in body growth rate was detected in the sensitive clone TH09 compared with the tolerant clone TH14 at the presence of toxic Microcystis. Furthermore, transcriptional analysis indicated that major MoAs such as glutathione metabolism, protein processing in endoplasmic reticulum, amino sugar/nucleotide sugar metabolism, and arachidonic acid metabolism were linked to the tolerance fitness in Daphnia similoides. These results provided mechanistic insights into the pathways of genetic and biological processes involved in cyanobacteria tolerance in the Daphnia clonal variation, and propose that the genetic architecture of this fitness‐related trait would be helpful to clarify how zooplankton clones adapt to harmful algal blooms.

Development of a strategy for the quantification of food allergens in several food products by mass spectrometry in a routine laboratory

Worldwide, mass spectrometry is widely used to detect and quantify food allergens, especially in complex and processed food products. Yet, the absence of a regulatory framework for the developed methods has led to a lack of harmonization between laboratories. In this study, ten allergens were analyzed in eight food products by UHPLC–MS/MS, in order to establish criteria for the retention time, variation tolerance, the ion ratio deviation, and the signal-to-noise ratio for allergen detection. The set of criteria should help laboratories to compare results and avoid false positives and negatives. Furthermore, a strategy combining standard addition and labeled peptide correction was used to quantify milk, soy, peanut, and egg allergens in eight food products. This strategy is particularly interesting for routine laboratories, which receive hundreds of samples and cannot use an external calibration curve for each sample.

FAME-ADL: a data-driven fuzzy approach for monitoring the ADLs of elderly people using Kinect depth maps

This paper presents a novel unsupervised fuzzy approach to monitoring the activities of daily living (ADLs) of elderly people living alone. Kinect sensors are employed in functional areas of the monitored environment to capture unlabelled training depth maps from the occupant’s ADLs. This training dataset is processed in order to extract a set of ADL attributes, including the occupant’s location and 3D posture. A novel data-driven technique is presented to define fuzzy sets over ADL attributes, and membership functions are learned based on the attribute data distribution. These fuzzy sets are used to transform the attributes’ values into fuzzy labels in order to linguistically describe the occupant’s behaviour patterns. A set of fuzzy rules is generated to model the frequency of behaviour patterns using a novel data-driven technique. Abnormal behaviours in subsequent data are detected as unusual behaviours that last for longer than a learned duration. The proposed monitoring approach was evaluated using a dataset collected from a real-life setting. The fuzzy rule set obtained from the output of the proposed membership function generation technique was found to improve monitoring of the elderly because it could accurately classify more testing scenarios of normal and abnormal behaviours when compared to the rule sets obtained using other techniques. Compared to the output of other parameterising techniques, this fuzzy rule set had fewer rules and greater tolerance of fine variations in activities. The experimental results also showed that the adopted fuzzy approach for monitoring ADLs outperformed existing camera-based approaches in terms of its classification accuracy for testing scenarios of normal and abnormal behaviours.

Evaluation of Altitude Sensors for a Crop Spraying Drone

This work aims to study and compare different range finders applied to altitude sensing on a rotating wings UAV. The specific application is the altitude maintenance for the fluid deployment valve aperture control in an unmanned pulverization aircraft used in precision agriculture. The influence of a variety of parameters are analyzed, including the tolerance for crop inconsistencies, density variations and intrinsic factors to the process, such as the pulverization fluid interference in the sensor’s readings, as well as their vulnerability to harsh conditions of the operation environment. Filtering and data extraction techniques were applied and analyzed in order to enhance the measurement reliability. As a result, a wide study was performed, enabling better decision making about choosing the most appropriate sensor for each situation under analysis. The performed data analysis was able to provide a reliable baseline to compare the sensors. With a baseline set, it was possible to counterweight the sensors errors and other factors such as the MSE for each environment to provide a summarized score of the sensors. The sensors which provided the best performance in the used metrics and tested environment were Lightware SF11-C and LeddarTech M16.

Resilience of English vowel perception across regional accent variation

In two categorization experiments using phonotactically legal nonce words, we tested Australian English listeners’ perception of all vowels in their own accent as well as in four less familiar regional varieties of English which differ in how their vowel realizations diverge from Australian English: London, Yorkshire, Newcastle (UK), and New Zealand. Results of Experiment 1 indicated that amongst the vowel differences described in sociophonetic studies and attested in our stimulus materials, only a small subset caused greater perceptual difficulty for Australian listeners than for the corresponding Australian English vowels. We discuss this perceptual tolerance for vowel variation in terms of how perceptual assimilation of phonetic details into abstract vowel categories may contribute to recognizing words across variable pronunciations. Experiment 2 determined whether short-term multi-talker exposure would facilitate accent adaptation, particularly for those vowels that proved more difficult to categorize in Experiment 1. For each accent separately, participants listened to a pre-test passage in the nonce word accent but told by novel talkers before completing the same task as in Experiment 1. In contrast to previous studies showing rapid adaptation to talker-specific variation, our listeners’ subsequent vowel assimilations were largely unaffected by exposure to other talkers’ accent-specific variation.