Different Transcriptomic Responses to Thermal Stress in Heat-Tolerant and Heat-Sensitive Pacific Abalones Indicated by Cardiac Performance

The Pacific abalone Haliotis discus hannai is one of the most economically important mollusks in China. Even though it has been farmed in southern China for almost 20 years, summer mortality remains the most challengeable problem for Pacific abalone aquaculture recently. Here, we determined the different heat tolerance ability for five selective lines of H. discus hannai by measuring the cardiac performance and Arrhenius breakpoint temperature (ABT). The Red line (RL) and Yangxia line (YL) were determined as the most heat-sensitive and most heat-tolerant line, respectively. Heart rates for RL were significantly lower than those of the YL at the same temperature (p < 0.05). The differentially expressed genes (DEGs), which were enriched in several pathways including cardiac muscle contraction, glutathione metabolism and oxidative phosphorylation, were identified between RL and YL at control temperature (20°C) and heat stress temperature (28.5°C, the ABT of the RL) by RNA-seq method. In the RL, 3370 DEGs were identified between the control and the heat-stress temperature, while only 1351 DEGs were identified in YL between these two temperature tests. Most of these DEGs were enriched in the pathways such as protein processing in endoplasmic reticulum, nucleotide binding and oligomerization domain (NOD) like receptor signaling, and ubiquitin mediated proteolysis. Notably, the most heat-tolerant line YL used an effective heat-protection strategy based on moderate transcriptional changes and regulation on the expression of key genes

First attempt of directionality reconstruction for atmospheric neutrinos in a large homogeneous liquid scintillator detector

The directionality information of incoming neutrinos is essential to atmospheric neutrino oscillation analysis since it is directly related to the oscillation baseline length. Large homogeneous liquid scintillator detectors, while offering excellent energy resolution, are traditionally very limited in their capabilities of measuring event directionality. In this paper, we present a novel directionality reconstruction method for atmospheric neutrino events in large homogeneous liquid scintillator detectors based on waveform analysis and machine learning techniques. We demonstrate for the first time that such detectors can achieve good direction resolution and potentially play an important role in future atmospheric neutrino oscillation measurements.Comment: Prepared for submission to PR

Development and applications of chromosome-specific BAC-FISH probes in Pacific abalone (Haliotis discus hannai)

Pacific abalone (Haliotis discus hannai) is an economically important marine shellfish for aquaculture and is distributed throughout eastern Asia. Although a lot of genetic breeding work has been carried out, chromosome identification in abalone is still a challenging task. Here, we developed a set of BACs to be chromosome-specific probes in Pacific abalone, and to study chromosome evolution in the related species. Through BAC paired-end sequencing and sequence alignment, we were able to in silico anchor 168 BACs onto 18 pseudochromosomes of Pacific abalone genome. After selecting 42 BACs that contained DNA inserts with minimal repetitive sequences, we validated them through PCR and Fluorescence in situ hybridization (FISH) test. As a result, We obtained specific FISH signals for 26 clones on the chromosomes of Pacific abalone with at least one BAC mapped per chromosome. We also applied the chromosome-specific BAC-FISH probes to a close relative of Pacific abalone, Xishi abalone (H. gigantea), which revealed that chromosome 13 and 15 between the two species underwent a chromosomes rearrangement event. This study provides the first set of chromosome-specific probes for the family Haliotidae, which can serve as an important tool for future cytogenetics and genomics research

Rethinking Semantic Segmentation from a Sequence-to-Sequence Perspective with Transformers

Most recent semantic segmentation methods adopt a fully-convolutional network (FCN) with an encoder-decoder architecture. The encoder progressively reduces the spatial resolution and learns more abstract/semantic visual concepts with larger receptive fields. Since context modeling is critical for segmentation, the latest efforts have been focused on increasing the receptive field, through either dilated/atrous convolutions or inserting attention modules. However, the encoder-decoder based FCN architecture remains unchanged. In this paper, we aim to provide an alternative perspective by treating semantic segmentation as a sequence-to-sequence prediction task. Specifically, we deploy a pure transformer (ie, without convolution and resolution reduction) to encode an image as a sequence of patches. With the global context modeled in every layer of the transformer, this encoder can be combined with a simple decoder to provide a powerful segmentation model, termed SEgmentation TRansformer (SETR). Extensive experiments show that SETR achieves new state of the art on ADE20K (50.28% mIoU), Pascal Context (55.83% mIoU) and competitive results on Cityscapes. Particularly, we achieve the first position in the highly competitive ADE20K test server leaderboard on the day of submission.Comment: CVPR 2021. Project page at https://fudan-zvg.github.io/SETR

A multi-purpose reconstruction method based on machine learning for atmospheric neutrinos at JUNO

The Jiangmen Underground Neutrino Observatory (JUNO) experiment is designed to measure the neutrino mass ordering (NMO) using a 20-kton liquid scintillator (LS) detector. Besides the precise measurement of the reactor neutrino’s oscillation spectrum, an atmospheric neutrino oscillation measurement in JUNO offers independent sensitivity for NMO, which can potentially increase JUNO’s total sensitivity in a joint analysis. In this contribution, we present a novel multi-purpose reconstruction method for atmospheric neutrinos in JUNO at few-GeV based on a machine learning technique. This method extracts features related to event topology from PMT waveforms and uses them as inputs to machine learning models. A preliminary study based on the JUNO simulation shows good performances for event directionality reconstruction and neutrino flavor identification. This method also has a great application potential for similar LS detectors

Howard County Farmers Association (HCFA) Business Concept

Final project for AREC489N: Economics of Local Agriculture: Food Hubs (Spring 2016). University of Maryland, College Park.The Howard County Office of Community Sustainability is seeking food hub-based solutions that connect small and mid-sized farmers in Howard County with restaurants and retailers to expand the market for locally produced agricultural products. Under the supervision of instructor Philip Gottwals, the University of Maryland’s PALS-affiliated AREC 489N team studied successes and failures of organizations that have undertaken similar projects to determine the most appropriate and feasible solutions to the issues raised. A review of public data quickly revealed that Howard County's agricultural sector is both small and highly diversified. As such it offers both opportunities for, and challenges to, the creation of a food hub. Vegetable production, for example, is limited to 110 acres of production with the largest crop acreage devoted to an ornamental crop, pumpkins. The next largest vegetable crops are sweet corn and tomatoes, with all others representing negligible commercial, fresh market acreage. For a food hub to be viable, an increase in production and diversity would be required. Otherwise, it would be impractical to gather and distribute wholesale quantities of vegetables to restaurants, retailers, or wholesalers. Interviews with County farmers confirmed that market opportunity is not limited by facility-based services, such as aggregation, but instead were limited by programmatic and policy restrictions. Chief among their concerns are the impending food safety certification requirements imposed by the federal Food Safety Modernization Act audited by Good Agricultural Practices (GAP) certification. These regulations, which were previously enforced only on the largest farms, now apply to all fruit and vegetable producers, regardless of farm size or program cost. Unless these standards are adopted at the farm level, local producers would be barred from many, if not all, commercial sales. Further evidence that a facility-based food hub is unlikely to be successful in Howard County can be found in the depth and breadth of the existing food supply chain. Howard County is the epicenter of a 100-mile radius supply chain that includes approximately 4,000 firms that are involved in all aspects of the food industry, including logistics, manufacturing, and distribution. After interviewing businesses operating in these sectors, it was determined that sufficient options to aggregate, ship, or value add were available in the market, but that critical services, such as quality assurance, food safety certification, and marketing support were lacking, putting local farmers at a marked disadvantage over farms from outside the area. Given the above, the project team concluded that it would be a greater benefit to our client if further research and project development efforts were directed toward designing a multi-pronged Quality Assurance Program for the County combined with an associated marketing and brand management program to raise awareness of Howard County farm products. This multifaceted approach strives to implement the newly emerging food safety requirements as a method of expansion into new markets. This allows growers to participate in the supply-chain where well-documented demand for local, GAP-certified produce and quality assured beef cattle exists. The second facet of the approach involves creating a suite of strategic marketing initiatives designed to bolster consumer demand for local food.Howard Count

Collaborative Control Strategy of Power Quality Based on Residual Capacity of Photovoltaic Inverter

With the large-scale distributed PV connected to the grid, the random and intermittent nature of PV output, the non-linearity of the inverter, as well as the low daytime base-load and large-scale back feeding cause outstanding power quality problems such as overvoltage, three-phase unbalance, and high harmonic content at the end of the power supply system, which seriously affects the safe and stable operation of the grid and power efficiency. Based on the residual capacity of the inverter, this paper investigates a cooperative power quality control strategy that integrates active power filter, reactive power compensation, and inverter functions to achieve comprehensive power quality control and management without adding additional hardware equipment. The validation results show that the control strategy strongly improves the power quality, grid security, stability, and efficiency. This strategy indicates significant economic benefits

Collaborative Control Strategy of Power Quality Based on Residual Capacity of Photovoltaic Inverter

With the large-scale distributed PV connected to the grid, the random and intermittent nature of PV output, the non-linearity of the inverter, as well as the low daytime base-load and large-scale back feeding cause outstanding power quality problems such as overvoltage, three-phase unbalance, and high harmonic content at the end of the power supply system, which seriously affects the safe and stable operation of the grid and power efficiency. Based on the residual capacity of the inverter, this paper investigates a cooperative power quality control strategy that integrates active power filter, reactive power compensation, and inverter functions to achieve comprehensive power quality control and management without adding additional hardware equipment. The validation results show that the control strategy strongly improves the power quality, grid security, stability, and efficiency. This strategy indicates significant economic benefits