Low-Complexity Iterative Detection for Orthogonal Time Frequency Space Modulation

We elaborate on the recently proposed orthogonal time frequency space (OTFS) modulation technique, which provides significant advantages over orthogonal frequency division multiplexing (OFDM) in Doppler channels. We first derive the input--output relation describing OTFS modulation and demodulation (mod/demod) for delay--Doppler channels with arbitrary number of paths, with given delay and Doppler values. We then propose a low-complexity message passing (MP) detection algorithm, which is suitable for large-scale OTFS taking advantage of the inherent channel sparsity. Since the fractional Doppler paths (i.e., not exactly aligned with the Doppler taps) produce the inter Doppler interference (IDI), we adapt the MP detection algorithm to compensate for the effect of IDI in order to further improve performance. Simulations results illustrate the superior performance gains of OTFS over OFDM under various channel conditions.Comment: 6 pages, 7 figure

A Pragmatic Study on Request Expressions in Chinese

application/pdfBy referencing three different scenes of face-threatening in Politeness Theory (Brown & Levinson, 1978), this study collects linguistic data related with friends (CN1) and senior students (CN2) from Chinese native speakers at Dalian University of Foreign Languages and analyzed them from the erspective of pragmatics. The results show that the politeness strategies of the requester in CN1 and CN2 are different from each other. When talking with seniors, requesters tend to use “courtesy” and thanks,” but when with friends, they usually do not use “thanks” and often use negative politeness strategies. With the increase of the difficulty of the request scenario, the differences between CN1 and CN2 are reduced. Furthermore, before the request behavior, the requester’s language preparation for “pleasantries,” “consideration,” and “pre-topic insertion” does not increase, but still focuses on “situation description,” “request,” and “auxiliary behavior.”論文(Article)departmental bulletin pape

Salinity Stress in Arid and Semi-Arid Climates: Effects and Management in Field Crops

Salinity stress is one of the most vital abiotic stresses which results in significant damages of agricultural production, particularly in arid and semi-arid areas of the world. Salinity causes by high accumulation of soluble salt, especially NaCl in soil and water. Salinity hampers the growth and survival of many field crops such as rice, wheat, maize, cotton, sugarcane, and sorghum. It affects the plant growth by three ways such as osmotic stress linked with an increase of phytotoxic ions, ionic stress e in the cytosol, and oxidative stress facilitated by reactive oxygen species (ROS). These stresses caused by salinity hinder the water uptake, causes ion imbalance, ROS production, and hormonal imbalance, and results in the decline of photosynthesis activities reduce the plant growth and final yield. However, the sensitivity of field crops depends on the nature of cultivar and growth stages. There are many strategies to cope with salinity stress which are the development of salinity tolerant crop cultivators by using genetic and molecular techniques such as QTLs and CRISPR CAS9 technique, nutrients management strategies, use of hormones regulators (AVG, 1-MCP, D-31). This chapter will give a brief idea to the scientist to understand the effects of salinity on field crops and their management strategies

FGF10 Protects Against Renal Ischemia/Reperfusion Injury by Regulating Autophagy and Inflammatory Signaling

Ischemia-reperfusion (I/R) is a common cause of acute kidney injury (AKI), which is associated with high mortality and poor outcomes. Autophagy plays important roles in the homeostasis of renal tubular cells (RTCs) and is implicated in the pathogenesis of AKI, although its role in the process is complex and controversial. Fibroblast growth factor 10 (FGF10), a multifunctional FGF family member, was reported to exert protective effect against cerebral ischemia injury and myocardial damage. Whether FGF10 has similar beneficial effect, and if so whether autophagy is associated with the potential protective activity against AKI has not been investigated. Herein, we report that FGF10 treatment improved renal function and histological integrity in a rat model of renal I/R injury. We observed that FGF10 efficiently reduced I/R-induced elevation in blood urea nitrogen, serum creatinine as well as apoptosis induction of RTCs. Interestingly, autophagy activation following I/R was suppressed by FGF10 treatment based on the immunohistochemistry staining and immunoblot analyses of LC3, Beclin-1 and SQSTM1/p62. Moreover, combined treatment of FGF10 with Rapamycin partially reversed the renoprotective effect of FGF10 suggesting the involvement of mTOR pathway in the process. Interestingly, FGF10 also inhibited the release of HMGB1 from the nucleus to the extracellular domain and regulated the expression of inflammatory cytokines such as TNF-α, IL-1β and IL-6. Together, these results indicate that FGF10 could alleviate kidney I/R injury by suppressing excessive autophagy and inhibiting inflammatory response and may therefore have the potential to be used for the prevention and perhaps treatment of I/R-associated AKI

Can Large Language Models Understand Real-World Complex Instructions?

Large language models (LLMs) can understand human instructions, showing their potential for pragmatic applications beyond traditional NLP tasks. However, they still struggle with complex instructions, which can be either complex task descriptions that require multiple tasks and constraints, or complex input that contains long context, noise, heterogeneous information and multi-turn format. Due to these features, LLMs often ignore semantic constraints from task descriptions, generate incorrect formats, violate length or sample count constraints, and be unfaithful to the input text. Existing benchmarks are insufficient to assess LLMs' ability to understand complex instructions, as they are close-ended and simple. To bridge this gap, we propose CELLO, a benchmark for evaluating LLMs' ability to follow complex instructions systematically. We design eight features for complex instructions and construct a comprehensive evaluation dataset from real-world scenarios. We also establish four criteria and develop corresponding metrics, as current ones are inadequate, biased or too strict and coarse-grained. We compare the performance of representative Chinese-oriented and English-oriented models in following complex instructions through extensive experiments. Resources of CELLO are publicly available at https://github.com/Abbey4799/CELLO

1-Methylcyclopropene Modulates Physiological, Biochemical, and Antioxidant Responses of Rice to Different Salt Stress Levels

Salt stress in soil is a critical constraint that affects the production of rice. Salt stress hinders plant growth through osmotic stress, ionic stress, and a hormonal imbalance (especially ethylene), therefore, thoughtful efforts are needed to devise salt tolerance management strategies. 1-Methylcyclopropene (1-MCP) is an ethylene action inhibitor, which could significantly reduce ethylene production in crops and fruits. However, 1-MCPs response to the physiological, biochemical and antioxidant features of rice under salt stress, are not clear. The present study analyzed whether 1-MCP could modulate salt tolerance for different rice cultivars. Pot culture experiments were conducted in a greenhouse in 2016–2017. Two rice cultivars, Nipponbare (NPBA) and Liangyoupeijiu (LYP9) were used in this trial. The salt stress included four salt levels, 0 g NaCl/kg dry soil (control, CK), 1.5 g NaCl/ kg dry soil (Low Salt stress, LS), 4.5 g NaCl/kg dry soil (Medium Salt stress, MS), and 7.5 g NaCl/kg dry soil (Heavy Salt stress, HS). Two 1-MCP levels, 0 g (CT) and 0.04 g/pot (1-MCP) were applied at the rice booting stage in 2016 and 2017. The results showed that applying 1-MCP significantly reduced ethylene production in rice spikelets from LYP9 and NPBA by 40.2 and 23.9% (CK), 44.3 and 28.6% (LS), 28 and 25.9% (MS), respectively. Rice seedlings for NPBA died under the HS level, while application of 1-MCP reduced the ethylene production in spikelets for LYP9 by 27.4% compared with those that received no 1-MCP treatment. Applying 1-MCP improved the photosynthesis rate and SPAD value in rice leaves for both cultivars. 1-MCP enhanced the superoxide dismutase production, protein synthesis, chlorophyll contents (chl a, b, carotenoids), and decreased malondialdehyde, H2O2, and proline accumulation in rice leaves. Application of 1-MCP also modulated the aboveground biomass, and grain yield for LYP9 and NPBA by 19.4 and 15.1% (CK), 30.3 and 24% (LS), 26.4 and 55.4% (MS), respectively, and 34.5% (HS) for LYP9 compared with those that received no 1-MCP treatment. However, LYP9 displayed a better tolerance than NPBA. The results revealed that 1-MCP could be employed to modulate physiology, biochemical, and antioxidant activities in rice plants, at different levels of salt stress, as a salt stress remedy

Entropy and self organizing in edge organizations

Along with the advance of technologies and evolving variety of military missions, Edge Organization has been proposed to transform C2 from its conventional hierarchical and inflexible structures into more network centric and flexible forms. To develop a better understanding of Edge Organizations, in our research we take a dynamical and adaptive complex systems approach to exploring dynamical features of Egde Organizations and investigate how networking structures, self-organization mechanisms may impact on the entropy of Edge Organizations and consequently determine their agility and performance. After defining the basic concepts, we introduce an agent-based simulation model that captures the interplay among networking structures, self-organization mechanisms, and organization agility and performance with entropy as an intermediate variable. Through simulation-based case studies using the proposed model, important dynaical features of Edge Organizations can be clarified and conditions for avoiding high entropy equilibirums and for acheiving high level of agility be identified. In addition to the description of the proposed model, various measures of organizational entropy and organizational agility are discussed. A scenario design for future simulation studies is presented

Some Contributions to Circular and Linear Statistics

This dissertation focuses mainly on directional data in two dimensions, called ``circular data," because such two-dimensional directions can be represented as points on the circumference of a unit circle. Such data, collected and analyzed by researchers in many scientific fields, needs special modeling and analysis. The thesis contains several somewhat independent results on the circular models and their analysis. First, a goodness-of-fit test for checking if a given dataset follows the wrapped stable distribution family is presented based on the empirical characteristic function. Then two dissimilarity measures for comparing any pair of curves around the circle are introduced and their use are explored in clustering such curves. This is followed by proving a result showing that wrapping a convolution of any number of linear components, yields the convolution of the corresponding wrapped distributions. Testing symmetry within the family of sine-skewed von Mises distributions is considered and compared with an existing test. The final result is a departure from the directional domain, and presents a Bayesian test for the number of modes in a two-component Gaussian mixture

Some Contributions to Circular and Linear Statistics

This dissertation focuses mainly on directional data in two dimensions, called ``circular data," because such two-dimensional directions can be represented as points on the circumference of a unit circle. Such data, collected and analyzed by researchers in many scientific fields, needs special modeling and analysis. The thesis contains several somewhat independent results on the circular models and their analysis. First, a goodness-of-fit test for checking if a given dataset follows the wrapped stable distribution family is presented based on the empirical characteristic function. Then two dissimilarity measures for comparing any pair of curves around the circle are introduced and their use are explored in clustering such curves. This is followed by proving a result showing that wrapping a convolution of any number of linear components, yields the convolution of the corresponding wrapped distributions. Testing symmetry within the family of sine-skewed von Mises distributions is considered and compared with an existing test. The final result is a departure from the directional domain, and presents a Bayesian test for the number of modes in a two-component Gaussian mixture