Productivity of Micronutrients from Integrated Aquaculture Agriculture Systems: Evidence from Bangladesh

Abstract accepted for presentation at the Annual Meeting of the World Aquaculture Society held in Singapore on 29 November to 2 December 2022. The presentation discussed the survey results on measuring micronutrient productivity in integrated aquatic farming systems for nutrition sensitive agriculture in Bangladesh

Measuring Micronutrient Productivity in Integrated Aquatic Farming Systems for Nutrition Sensitive Agriculture

The presentation showcased the survey results on measuring micronutrient productivity in integrated aquatic farming systems for nutrition sensitive agriculture in Bangladesh. The study suggested that integrated aquaculture-agriculture can be beneficial for both economic and nutritional productivity and can be used to identify and promote crop combinations to optimize both outcomes

Realizing In-Memory Baseband Processing for Ultra-Fast and Energy-Efficient 6G

To support emerging applications ranging from holographic communications to extended reality, next-generation mobile wireless communication systems require ultra-fast and energy-efficient baseband processors. Traditional complementary metal-oxide-semiconductor (CMOS)-based baseband processors face two challenges in transistor scaling and the von Neumann bottleneck. To address these challenges, in-memory computing-based baseband processors using resistive random-access memory (RRAM) present an attractive solution. In this paper, we propose and demonstrate RRAM-implemented in-memory baseband processing for the widely adopted multiple-input-multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) air interface. Its key feature is to execute the key operations, including discrete Fourier transform (DFT) and MIMO detection using linear minimum mean square error (L-MMSE) and zero forcing (ZF), in one-step. In addition, RRAM-based channel estimation module is proposed and discussed. By prototyping and simulations, we demonstrate the feasibility of RRAM-based full-fledged communication system in hardware, and reveal it can outperform state-of-the-art baseband processors with a gain of 91.2$\times$ in latency and 671$\times$ in energy efficiency by large-scale simulations. Our results pave a potential pathway for RRAM-based in-memory computing to be implemented in the era of the sixth generation (6G) mobile communications.Comment: arXiv admin note: text overlap with arXiv:2205.0356

X-TIME: An in-memory engine for accelerating machine learning on tabular data with CAMs

Structured, or tabular, data is the most common format in data science. While deep learning models have proven formidable in learning from unstructured data such as images or speech, they are less accurate than simpler approaches when learning from tabular data. In contrast, modern tree-based Machine Learning (ML) models shine in extracting relevant information from structured data. An essential requirement in data science is to reduce model inference latency in cases where, for example, models are used in a closed loop with simulation to accelerate scientific discovery. However, the hardware acceleration community has mostly focused on deep neural networks and largely ignored other forms of machine learning. Previous work has described the use of an analog content addressable memory (CAM) component for efficiently mapping random forests. In this work, we focus on an overall analog-digital architecture implementing a novel increased precision analog CAM and a programmable network on chip allowing the inference of state-of-the-art tree-based ML models, such as XGBoost and CatBoost. Results evaluated in a single chip at 16nm technology show 119x lower latency at 9740x higher throughput compared with a state-of-the-art GPU, with a 19W peak power consumption

Relative roles of TGF-β1 and Wnt in the systemic regulation and aging of satellite cell responses

Muscle stem (satellite) cells are relatively resistant to cell-autonomous aging. Instead, their endogenous signaling profile and regenerative capacity is strongly influenced by the aged P-Smad3, differentiated niche, and by the aged circulation. With respect to muscle fibers, we previously established that a shift from active Notch to excessive transforming growth factor-beta (TGF-β) induces CDK inhibitors in satellite cells, thereby interfering with productive myogenic responses. In contrast, the systemic inhibitor of muscle repair, elevated in old sera, was suggested to be Wnt. Here, we examined the age-dependent myogenic activity of sera TGF-β1, and its potential cross-talk with systemic Wnt. We found that sera TGF-β1 becomes elevated within aged humans and mice, while systemic Wnt remained undetectable in these species. Wnt also failed to inhibit satellite cell myogenicity, while TGF-β1 suppressed regenerative potential in a biphasic fashion. Intriguingly, young levels of TGF-β1 were inhibitory and young sera suppressed myogenesis if TGF-β1 was activated. Our data suggest that platelet-derived sera TGF-β1 levels, or endocrine TGF-β1 levels, do not explain the age-dependent inhibition of muscle regeneration by this cytokine. In vivo, TGF-β neutralizing antibody, or a soluble decoy, failed to reduce systemic TGF-β1 and rescue myogenesis in old mice. However, muscle regeneration was improved by the systemic delivery of a TGF-β receptor kinase inhibitor, which attenuated TGF-β signaling in skeletal muscle. Summarily, these findings argue against the endocrine path of a TGF-β1-dependent block on muscle regeneration, identify physiological modalities of age-imposed changes in TGF-β1, and introduce new therapeutic strategies for the broad restoration of aged organ repair

Differential regulation of CHOP translation by phosphorylated eIF4E under stress conditions

Cells respond to environmental stress by inducing translation of a subset of mRNAs important for survival or apoptosis. CHOP, a downstream transcriptional target of stress-induced ATF4, is also regulated translationally in a uORF-dependent manner under stress. Low concentration of anisomycin induces CHOP expression at both transcriptional and translational levels. To study specifically the translational aspect of CHOP expression, and further clarify the regulatory mechanisms underlying stress-induced translation initiation, we developed a CMV promoter-regulated, uORFchop-driven reporter platform. Here we show that anisomycin-induced CHOP expression depends on phosphorylated eIF4E/S209 and eIF2α/S51. Contrary to phospho-eIF2α/S51, phospho-eIF4E/S209 is not involved in thapsigargin-induced CHOP expression. Studies using various kinase inhibitors and mutants uncovered that both the p38MAPK-Mnk and mTOR signaling pathways contribute to stress-responsive reporter and CHOP expression. We also demonstrated that anisomycin-induced translation is tightly regulated by partner binding preference of eIF4E. Furthermore, mutating the uORF sequence abolished the anisomycin-induced association of chop mRNA with phospho-eIF4E and polysomes, thus demonstrating the significance of this cis-regulatory element in conferring on the transcript a stress-responsive translational inducibility. Strikingly, although insulin treatment activated ERK-Mnk and mTOR pathways, and consequently eIF4E/S209 phosphorylation, it failed to induce phospho-eIF2α/S51 and reporter translation, thus pinpointing a crucial determinant in stress-responsive translation

Dynamic, Large-Scale Profiling of Transcription Factor Activity from Live Cells in 3D Culture

phenotypes. Taken together, our objective was to develop cellular arrays for dynamic, large-scale quantification of TF activity as cells organized into spherical structures within 3D culture.TF-specific and normalization reporter constructs were delivered in parallel to a cellular array containing a well-established breast cancer cell line cultured in Matrigel. Bioluminescence imaging provided a rapid, non-invasive, and sensitive method to quantify luciferase levels, and was applied repeatedly on each sample to monitor dynamic activity. Arrays measuring 28 TFs identified up to 19 active, with 13 factors changing significantly over time. Stimulation of cells with β-estradiol or activin A resulted in differential TF activity profiles evolving from initial stimulation of the ligand. Many TFs changed as expected based on previous reports, yet arrays were able to replicate these results in a single experiment. Additionally, arrays identified TFs that had not previously been linked with activin A.This system provides a method for large-scale, non-invasive, and dynamic quantification of signaling pathway activity as cells organize into structures. The arrays may find utility for investigating mechanisms regulating normal and abnormal tissue growth, biomaterial design, or as a platform for screening therapeutics

Stochastic light concentration from 3D to 2D reveals ultraweak chemi- and bioluminescence

For countless applications in science and technology, light must be concentrated, and concentration is classically achieved with reflective and refractive elements. However, there is so far no efficient way, with a 2D detector, to detect photons produced inside an extended volume with a broad or isotropic angular distribution. Here, with theory and experiment, we propose to stochastically transform and concentrate a volume into a smaller surface, using a high- albedo Ulbricht cavity and a small exit orifice through cavity walls. A 3D gas of photons produced inside the cavity is transformed with a 50% number efficiency into a 2D Lambertian emitting orifice with maximal radiance and a much smaller size. With high-albedo quartz-powder cavity walls ( P = 99.94%), the orifice area is 1/( 1 - P) approximate to 1600 times smaller than the walls' area. When coupled to a detectivity-optimized photon-counter ( D = 0.015 photon- 1 s1/ 2 cm) the detection limit is 110 photon s- 1 L- 1. Thanks to this unprecedented sensitivity, we could detect the luminescence produced by the non-catalytic disproportionation of hydrogen peroxide in pure water, which has not been observed so far. We could also detect the ultraweak bioluminescence produced by yeast cells at the onset of their growth. Our work opens new perspectives for studying ultraweak luminescence, and the concept of stochastic 3D/2D conjugation should help design novel light detection methods for large samples or diluted emitters