Cloning and function analysis of DlWRKY9 gene in longan (Dimocarpus longan)

WRKY is one of the largest plant transcription factors (TFs) which is widely involved in plant growth, development, and responses to stresses. In the present study, a WRKY TF DlWRKY9 was cloned from longan (Dimocarpus longan). The coding sequence (CDS) of DlWRKY9 is 762 bp in length and encodes 253 amino acids. It has a typical WRKY domain and zinc finger structure which belongs to type IIa WRKY protein. The molecular weight of DlWRKY9 protein was 30.27kda and the theoretical isoelectric point (PI) was 5.24. It is an unstable hydrophilic protein. The secondary structure of DlWRKY9 protein consists of helical structure (17.39%), extended chain (8.70%) and other structures (turn and random coil) (73.91%). The amino acid sequence of DlWRKY9 protein had the highest similarity with DlWRKY9 (xp_006450293.1) of citrus Clementina. DlWRKY9 gene promoter elements contain light, abscisic acid, gibberellin, jasmonic acid and other response elements. The results of qRT-PCR showed that the relative expression level of DlWRKY9 gene in pericarp was higher, followed by young fruits and floral organs. Meanwhile, DlWRKY9 gene specifically down-regulated in the early stage of flower induction in ‘Sijimi’ (SJ) longan. The results of transient expression of Arabidopsis protoplasts showed that the fluorescence signal was mainly concentrated in the nucleus. Moreover, overexpression of DlWRKY9 in Arabidopsis promoted early flowering. These results provide useful information for revealing the biological roles of DlWRKY9 in longan and increase our understanding of the WRKY family in fruit trees

Imaging of the Space-time Structure of a Vortex Generator in Supersonic Flow

AbstractThe fine space-time structure of a vortex generator (VG) in supersonic flow is studied with the nanoparticle-based planar laser scattering (NPLS) method in a quiet supersonic wind tunnel. The fine coherent structure at the symmetrical plane of the flow field around the VG is imaged with NPLS. The spatial structure and temporal evolution characteristics of the vortical structure are analyzed, which demonstrate periodic evolution and similar geometry, and the characteristics of rapid movement and slow change. Because the NPLS system yields the flow images at high temporal and spatial resolutions, from these images the position of a large scale structure can be extracted precisely. The position and velocity of the large scale structures can be evaluated with edge detection and correlation algorithms. The shocklet structures induced by vortices are imaged, from which the generation and development of shocklets are discussed in this paper

Energy-efficient Integrated Sensing and Communication System and DNLFM Waveform

Integrated sensing and communication (ISAC) is a key enabler of 6G. Unlike communication radio links, the sensing signal requires to experience round trips from many scatters. Therefore, sensing is more power-sensitive and faces a severer multi-target interference. In this paper, the ISAC system employs dedicated sensing signals, which can be reused as the communication reference signal. This paper proposes to add time-frequency matched windows at both the transmitting and receiving sides, which avoids mismatch loss and increases energy efficiency. Discrete non-linear frequency modulation (DNLFM) is further proposed to achieve both time-domain constant modulus and frequency-domain arbitrary windowing weights. DNLFM uses very few Newton iterations and a simple geometrically-equivalent method to generate, which greatly reduces the complex numerical integral in the conventional method. Moreover, the spatial-domain matched window is proposed to achieve low sidelobes. The simulation results show that the proposed methods gain a higher energy efficiency than conventional methods

Networked Collaborative Sensing using Multi-domain Measurements: Architectures, Performance Limits and Algorithms

As a promising 6G technology, integrated sensing and communication (ISAC) gains growing interest. ISAC provides integration gain via sharing spectrum, hardware, and software. However, concerns exist regarding its sensing performance when compared to dedicated radar systems. To address this issue, the advantages of widely deployed networks should be utilized, and this paper proposes networked collaborative sensing (NCS) using multi-domain measurements (MM), including range, Doppler, and two-dimension angle of arrival. In the NCS-MM architecture, this paper proposes a novel multi-domain decoupling model and a novel guard band-based protocol. The proposed model simplifies multi-domain derivations and algorithm designs, and the proposed protocol conserves resources and mitigates NCS interference. To determine the performance limits, this paper derives the Cram\'er-Rao lower bound (CRLB) of three-dimension position and velocity in NCS-MM. An accumulated single-dimension channel model is used to obtain the CRLB of MM, which is proven to be equivalent to that of the multi-dimension model. The algorithms of both MM estimation and fusion are proposed. An arbitrary-dimension Newtonized orthogonal matched pursuit (AD-NOMP) is proposed to accurately estimate grid-less MM. The degree-of-freedom (DoF) of MM is analyzed, and a novel DoF-based two-stage weighted least squares (TSWLS) is proposed to reduce equations without DoF loss. The numerical results show that the performances of the proposed algorithms are close to their performance limits

Water pollutant fingerprinting tracks recent industrial transfer from coastal to inland China: a case study

In recent years, China’s developed regions have transferred industries to undeveloped regions. Large numbers of unlicensed or unregistered enterprises are widespread in these undeveloped regions and they are subject to minimal regulation. Current methods for tracing industrial transfers in these areas, based on enterprise registration information or economic surveys, do not work. The authors have developed an analytical framework combining water fingerprinting and evolutionary analysis to trace the pollution transfer features between water sources. We collected samples in Eastern China (industrial export) and Central China (industrial acceptance) separately from two water systems. Based on the water pollutant fingerprints and evolutionary trees, we traced the pollution transfer associated with industrial transfer between the two areas. The results are consistent with four episodes of industrial transfers over the past decade. The results also show likely types of the transferred industries - electronics, plastics, and biomedicines - that contribute to the water pollution transfer

Stacking Revenues from Flexible DERs in Multi-Scale Markets using Tri-Level Optimization

Rapid proliferation of flexible Distributed Energy Resources (DERs) as a result of Net Zero Emissions objectives entails a profound shift in the paradigm of local and national energy systems. Currently, DERs' simultaneous participation in multiple markets is generally restricted, which undermines their profitability. With the aim of increasing the number of business cases for them, a tri-level optimization problem that seeks the maximisation of revenues from DERs is proposed. The optimization problem considers simultaneous participation of different flexible DERs, such as, Electric Vehicles (EVs), Battery Energy Storage Systems (BESSs) and Heating, Ventilation and Air Conditioning (HVACs), in national and local markets. Markets are cleared sequentially, and the model is recast into a tractable single-level problem using its dual formulation and strong duality condition. Results from a case study based on the IEEE 14 bus transmission network, a realistic distribution network and SimBench dataset demonstrate the effectiveness of the proposed approach in increasing profits compared with a baseline scenario

M28 Fixed wing transport aircraft cost reduction

Thesis (M.B.A.)--Massachusetts Institute of Technology, Sloan School of Management; and, (S.M.)--Massachusetts Institute of Technology, Engineering Systems Division; in conjunction with the Leaders for Global Operations Program at MIT, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 146-148).The M28 is a Polish short-takeoff-and-landing (STOL) light cargo aircraft developed in 1984 and currently built by PZL Mielec, a subsidiary of United Technology Corporation (UTC). There has been renewed interest in the product from military and commercial markets due to its impressive STOL capabilities. However, in order to become price-competitive, its cost would need to be reduced significantly. Multiple cost-reduction concepts have been proposed by the manufacturing and procurement groups. An Optimization Team was also formed to lead the cost-reduction effort. However, a more systematic approach is required in order to achieve the ambitious reduction goals. The proposed solution is to create a top-down systematic cost-reduction framework used to coordinate and prioritize the team's current bottom-up approach. A top-down cost reduction strategy was developed based on UTC Otis' Octopus Fishing concept. Such methodology, heavily finance driven, systematically breaks M28 into sub-systems, and prioritizes improvement recommendations based on cost-reduction potentials. It also leverages on the wealth of knowledge from global cross-functional teams to generate explosive amount of improvement recommendations. The sub-systems were benchmarked against competitors cost structures. The framework will be linked to concepts generated from the database to create a process that combine top-down and bottom-up approaches. After tasks were prioritized using the outlined framework, a three-prong approach was implemented to enhance cost reduction capability. Manufacturing of labor intensive parts such as nacelle deflection cover was automated using CNC machines. A set of commodity purchasing strategies were formulated for forgings, avionics, raw materials, interior and composite materials. Lastly, a discrete Kaizen event was described to aid redesign-for-manufacturing.by Yuxin Xia.S.M.M.B.A

Compress, Then Prompt: Improving Accuracy-Efficiency Trade-off of LLM Inference with Transferable Prompt

Large Language Models (LLMs), armed with billions of parameters, exhibit exceptional performance across a wide range of Natural Language Processing (NLP) tasks. However, they present a significant computational challenge during inference, especially when deploying on common hardware such as single GPUs. As such, minimizing the latency of LLM inference by curtailing computational and memory requirements, though achieved through compression, becomes critically important. However, this process inevitably instigates a trade-off between efficiency and accuracy, as compressed LLMs typically experience a reduction in predictive precision. In this research, we introduce an innovative perspective: to optimize this trade-off, compressed LLMs require a unique input format that varies from that of the original models. Our findings indicate that the generation quality in a compressed LLM can be markedly improved for specific queries by selecting prompts with precision. Capitalizing on this insight, we introduce a prompt learning paradigm that cultivates an additive prompt over a compressed LLM to bolster their accuracy. Our empirical results imply that through our strategic prompt utilization, compressed LLMs can match, and occasionally even exceed, the accuracy of the original models. Moreover, we demonstrated that these learned prompts have a certain degree of transferability across various datasets, tasks, and compression levels. These insights shine a light on new possibilities for enhancing the balance between accuracy and efficiency in LLM inference. Specifically, they underscore the importance of judicious input editing to a compressed large model, hinting at potential advancements in scaling LLMs on common hardware

Sentinel lymph node biopsy in oral cavity cancer using indocyanine green: A systematic review and meta-analysis

This meta-analysis was conducted to evaluate the value of indocyanine green (ICG) in guiding sentinel lymph node biopsy (SLNB) for patients with oral cavity cancer. An electronic database search (PubMed, MEDLINE, Cochrane Library, Embase, and Web of Science) was performed from their inception to June 2020 to retrieve clinical studies of ICG applied to SLNB for oral cavity cancer. Data were extracted from 14 relevant articles (226 patients), and 9 studies (134 patients) were finally included in the meta-analysis according to the inclusion and exclusion criteria. The pooled sentinel lymph node (SLN) sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were 88.0% (95% confidence interval [CI], 74.0-96.0), 64.0% (95% CI, 61.0-66.0), 2.45 (95% CI, 1.31-4.60), 0.40 (95% CI, 0.17-0.90), and 7.30 (95% CI, 1.74-30.68), respectively. The area under the summary receiver operating characteristic curve was 0.8805. In conclusion, ICG applied to SLNB can effectively predict the status of regional lymph nodes in oral cavity cancer