Search

The integration of high proportions of renewable energy into power systems has led to an increasing demand for flexible resources， highlighting the importance of flexible resources on demand side. Current research on demand-side response primarily focuses on peak load and lacks quantitative analysis on how demand-side response resources can enhance renewable energy consumption. To address this gap， this paper first develops a regulation model for various flexible single resources on demand side. Subsequently， it analyzes the regulation characteristics of single flexible resources and establishes an aggregation regulation model for a large number of these resources. The paper then constructs a quantitative analysis model of renewable energy consumption promoted by demand-side response based on time-series production simulation. Finally， it conducts a simulation study using a provincial power grid as a case study to analyze the impact of various types of demand-side response on improving renewable energy consumption. The results show that both shiftable load （SL） and transferable load （TL） can help enhance renewable energy consumption.

AbstractCotton diseases are disastrous for quality and sustainable production of the yield. Cotton leaf curl virus (CLCuV) is one of the most damaging diseases for cotton crops. Symptoms-based CLCuV identification is tedious, time consuming, error prone and needs exceptional expertise. Sensor-based machine vision approaches have great potential to detect the CLCuV at early stages. This research study proposes a machine vision-based multimodal fusion framework to diagnose various CLCuV severity levels. Our designed model is based on three contrasting datasets: digital photographic, multispectral and fused datasets. A digital camera was used to acquire the digital photographic dataset, the multispectral dataset was obtained by a multispectral radiometer-5 (MSR5), and the two datasets were fused to formulate the third one. From the digital photographic dataset, 269 texture features were extracted and optimized to the most discriminant 30 texture features, the multispectral dataset consisted of 5 spectral features, and the fused dataset was formed by combining the two. The 30 most discriminant features from the digital photographic dataset were selected by incorporating fisher co-efficient, probability of error plus average correlation and mutual information (MI). To diagnose CLCuV, four machine-learning classifiers, namely simple logistics (SL), multilayer perceptron (MLP), sequential minimal optimization (SMO), and random forest (RF), were deployed separately on each dataset. The maximum CLCuV diagnosing accuracies attained from digital photographic, multispectral, and fused datasets were 81.263%, 91.177%, and 96.313%, respectively.

Hand gesture-based Sign Language Recognition (SLR) serves as a crucial communication bridge between hard of hearing and non-deaf individuals. The absence of a universal sign language (SL) leads to diverse nationalities having various cultural SLs, such as Korean, American, and Japanese sign language. Existing SLR systems perform well for their cultural SL but may struggle with other or multi-cultural sign languages (McSL). To address these challenges, this paper introduces a novel end-to-end SLR system called GmTC, designed to translate McSL into equivalent text for enhanced understanding. Here, we employed a Graph and General deep-learning network as two stream modules to extract effective features. In the first stream, produce a graph-based feature by taking advantage of the superpixel values and the graph convolutional network (GCN), aiming to extract distance-based complex relationship features among the superpixel. In the second stream, we extracted long-range and short-range dependency features using attention-based contextual information that passes through multi-stage, multi-head self-attention (MHSA), and CNN modules. Combining these features generates final features that feed into the classification module. Extensive experiments with five culture SL datasets with high-performance accuracy compared to existing state-of-the-art models in individual domains affirming superiority and generalizability.

Smart logistics (SL) reflects the digital transformation of the logistics industry, which is key for economic development. Most evaluations are based on the application of technology in SL, and few studies have evaluated SL from a comprehensive perspective. The paper builds the SL development index (SLDI) model from five dimensions based on the driving force, pressure, state, impact, and response (DPSIR) model and identifies the indicator weight by the entropy weight technique. The paper employs the ETDK method, a combined quantitative approach that incorporates entropy weight (E), the technique for order preference by similarity to an ideal solution (TOPSIS) (T), the Dagum Gini coefficient (D), and Kernel density estimation (K), to calculate the closeness degree, analyze spatial-temporal differentiation, and explain the distribution characteristics using data from China spanning 2013 to 2021. The findings show that (1) The SL evaluation is multidimensional and cannot be evaluated only based on technical indicators. A comprehensive evaluation indicator system is necessary. (2) A combined quantitative approach can measure SL development from multiple perspectives and get a clearer picture of the characteristics and regional differences of SL. (3) Influenced by economic development, infrastructure, regional clusters, location, talent, etc., the overall SL development is improving yearly, but SL development in different regions is unbalanced and has different distribution characteristics. The SLDI model developed in this paper will provide a more scientific and reasonable tool for comprehensively evaluating SL. The findings are helpful in proposing suggestions and optimization approaches for subsequent research on SL evaluation and development.

The sleep loss (SL) are one of the important diseases that endanger the health of aging individuals. This study evaluated SL in aging individuals, and explored the relationship between age and the organic changes that affect brain and sleep. The causes of SL in aging individuals and its harmful effects on them have been outlined. To enable individuals in choosing a suitable way to sleep better, we also reviewed advantages and disadvantages of the existing sleep modulation based on lifestyle habits and drug and physical stimulation. We found the former as more suitable for patients with mild SL, while the latter may fail to achieve the desired effects and may even lead to the onset of new diseases. Therefore, it is proposed to use non-invasive electrical and magnetic stimulations to improve the sleep quality in aging patients.In this review, mechanisms of the two stimulation methods have been summarized. Through analysis, it was found that magnetic stimulation can induce neuronal action potential, which makes patients twitch, and equipment noise causes discomfort in the elderly during treatment. Comparative analysis of stimulation methods revealed that transcranial electrical stimulation (tES) is a considerably safe, convenient, non-invasive, and easy to operate method with few adverse reactions, and it can be considered a potential therapeutic method for SL in aging patients.

Smart Logistics (SL) offers a competitive advantage for e-commerce by utilizing Information and Communication Technologies (ICT) such as IoT, AI, Blockchain, Cloud computing, 5G, etc. This technology automates, optimizes, and enables real-time tracking and monitoring of shipments, predicts, and prevents delays, and optimizes delivery routes and schedules. It also provides greater visibility and control, allowing e-commerce businesses to react quickly and efficiently to changes in demand or supply. The purpose of this study is to investigate the impact of digitalization on trade logistics in e-commerce, emphasizing the significance of smart logistics for the e-commerce industry. We reviewed 288 articles published in the last decade in the Scopus database to assess the maturity of research in this area. For researchers, this study provides a better understanding of smart e-commerce logistics and identifies research gaps in the literature. For e-commerce professionals, it can help them adopt the latest technological trends in their logistics. Through a systematic literature review and network analysis approach, the study has contributed by identifying 5 clusters related to ICT application fields in e-commerce and 5 clusters related to important ICT enablers in smart logistics. We also identified several research gaps and areas for future study, including the underutilization of computer vision technology and the need for further research on product quality inspection and accessibility for people with disabilities. Additionally, we suggest exploring the power of deep learning to solve Vehicle Routing Problems (VRP) and optimizing sensing data volume for minimizing costs associated with data storage and transfer. This study provides a comprehensive overview of the state of the art in smart logistics for e-commerce and serves as a guide for future research in this field.

Structured lipids (SLs) offer a promising avenue for designing novel formulations enriched in n-3 long-chain polyunsaturated fatty acids (LCPUFAs) with potential health benefits. Triacylglycerols (TAGs), the most common fats in the human diet, are both non-toxic and chemically stable. The metabolic efficiency and digestibility of TAGs are significantly influenced by the position of fatty acids (FAs) within the glycerol backbone, with FAs at the sn-2 position being readily absorbed. Over the past two decades, advancements in SL research have led to the development of modified TAGs, achieved either through chemical or enzymatic processes, resulting in SLs. The ideal structure of SLs involves medium-chain FAs at the sn-1,3 positions and long-chain n-3 LCPUFAs at the sn-2 position of the glycerol backbone, conferring specific physicochemical and nutritional attributes. These tailored SL formulations find wide-ranging applications in the food and nutraceutical industries, showing promise for dietary support in promoting health and mitigating various diseases. In particular, SLs can be harnessed as functional oils to augment TAG metabolism, thereby impeding the development of fatty liver, countering the onset of obesity, and preventing atherosclerosis and age-related chronic diseases. In scrutinising prevailing research trajectories, this review endeavours to provide an in-depth analysis of the multifaceted advantages and repercussions associated with the synthesis of SLs. It elucidates their burgeoning potential in enhancing health and well-being across a range of demographic cohorts. Specifically, the implications of SL utilisation are discussed in the context of healthcare environments and early childhood developmental support.

Sign Language (SL) is the most organized and structured type of hand/arm gesture in the communicative hand/arm gesture taxonomies. The ability of machines to comprehend human actions and meanings has numerous uses. SL identification is one area of focus. SL is employed by the deaf and hard-of-hearing communities to communicate. Hearing-impaired persons communicate via visual indicators instead of vocal communication and sound patterns. SL also uses facial expressions and body postures as a medium of communication. Pattern matching, computer vision, natural language processing are the key factors in SL identification. This study reviews state-of-the-art methodologies employed in current SL identification research, comparing the various algorithms at each stage. Discuss the challenges and limitations of gesture identification research in general, as well as SL identification in particular. Overall, this paper gives a thorough introduction to the topic of automated SL identification, paving the way for future research.

For LTE-V2X system,acquiring the synchronization reference signal (SRS) is indispensable for vehicles to establish service connections in the network.However,there are some vehicles may not obtain the SRS and consequently fail to be synchronized with the network.In order to solve this problem,a sidelink (SL) radio interface synchronization scheme was proposed.Vehicles select an optimal SPS according to SRS priority division mechanism.The SRS are given different priorities,where the priorities of different synchronization sources can be distinguished in a time-shift based SRS transmit mechanism and meanwhile the interference among the SRS of different sources can be effectively suppressed.Simulation results illustrate that even when the synchronization source is assigned a priority of four,the synchronization error can still be satisfied the requirement.Compared with the conventional synchronization schemes,the proposed scheme supports an expanded synchronization range aided by synchronization over the SL and achieves mitigation of SRS interference with the time-shift based SRS transmit mechanism.The proposed scheme can serve as an efficacious and feasible solution for the LTE-V2X system.

This study discusses the translation errors of the Indonesian subtitles from the Japanese drama Ichi Rittoru no Namida ‘One Liter Tears’ by Masanori Murakami, released at Fuji Terebi in 2005. There is no reference to similar study about the translation of oral dialogues of Japanese characters who were later translated into in Indonesian is of interest in this study. This study aims to identify the variety of Japanese drama Ichi Rittoru no Namida’s translation errors (subtitles). The formulation of the problem is examined with translation theory, types of translations and translation strategies. Furthermore, the data of this study are sentences or conversations in Japanese as the source language (SL) and Indonesian (subtitle) as the target language (TL) taken from episodes 1 to 6. The data are described using descriptive-qualitative methods. The results of this study are translation errors identified in diction choices, excessive use of words, grammatical errors, shifts in translation and errors due to cultural influences. Some examples of findings include the choice of diction like the word touzen translates to ‘legitimate’, excessive use of words such as the word gomen ne to ‘I am very sorry’, grammatical errors such as the phrase kondo no kusuri traced to ‘the medicine he is taking’, the translation shift as in the noun phrase todoufuken ga shiteishita ishi no shindansho it becomes ‘specified special health service’ and errors due to cultural influences such as the yoroshiku expression becomes ‘dependent on you’. Keywords: Ichi Rittoru no Namida, SL, TL, translation error

Inquiry-discovery learning plays an important role in improving high-order thinking skills (HOTS) and scientific literacy (SL). In this HOTS and SL research, it was designed with Inquiry-discovery based learning. The purpose of this study was to promote Inquiry discovery models in empowering higher-order thinking skills and scientific literacy in physics with different classes. This research used Quasi-Experimental Design research, and Pretest-Posttest Control Group Design. The research analysis design matrix used two-way ANOVA. The sample was taken from two classes, namely the experimental and control classes of 68 students. The results of the study prove that Inquiry discovery can improve HOTS and SL physics of students. Thus, inquiry-discovery can be recommended to increase student's HOTS and SL physics when compared to conventional classes. The novelty of this study is that inquiry-discovery learning models are more likely to reconstruct students' scientific knowledge of physics on aspects of HOTS and SL with real-world life.

Non-alcoholic fatty liver disease (NAFLD) and atherosclerosis (ATS) are worldwide known diseases with increased incidence and prevalence. These two are driven and are interconnected by multiple oxidative and metabolic functions such as lipotoxicity. A gamut of evidence suggests that sphingolipids (SL), such as ceramides, account for much of the tissue damage. Although in humans they are proving to be accurate biomarkers of adverse cardiovascular disease outcomes and NAFLD progression, in rodents, pharmacological inhibition or depletion of enzymes driving de novo ceramide synthesis prevents the development of metabolic driven diseases such as diabetes, ATS, and hepatic steatosis. In this narrative review, we discuss the pathways which generate the ceramide synthesis, the potential use of circulating ceramides as novel biomarkers in the development and progression of ATS and related diseases, and their potential use as therapeutic targets in NAFDL-ATS development which can further provide new clues in this field.

The glycosciences aim to understand the impact of extracellular and intracellular carbohydrate structures on biological function. These glycans primarily fall into three major groups: lipid-linked carbohydrates that are referred to as glycosphingolipids or simply glycolipids; relatively short carbohydrate chains that are often O- or N-linked to proteins yielding common glycoproteins; and extended linear polymeric carbohydrate structures that are referred to as glycosaminoglycans (GAGs). Whereas, the impact of such carbohydrate structures has been extensively examined in cancer biology, their role in acute and chronic heart disease is less studied. In this context, a growing body of evidence indicates that glycans play an important role in immune mediated cell recruitment to damaged heart tissue to initiate wound healing and repair after injury. This is particularly important following ischemia and reperfusion that occurs in the heart in the setting of acute myocardial infarction. Here, immune system-mediated repair of the damaged myocardium plays a critical role in determining post-infarction ventricular remodeling, cardiac function, and patient outcome. Further, alterations in immune cell activity can promote the development of heart failure. The present review summarizes our current understanding of the phases of immune-mediated repair following myocardial infarction. It discusses what is known regarding glycans in mediating the recruitment of circulating immune cells during the early inflammatory stage of post-infarction repair, with focus on the selectin family of adhesion molecules. It offers future directions for research aimed at utilizing our knowledge of mechanisms underlying immune cell recruitment to either modulate leukocyte recruitment to the injured tissue or enhance the targeted delivery of biologic therapeutics such as stem cells in an attempt to promote repair of the damaged heart.

This paper addresses how the contrast known as Individual-­‐Level/Stage-­‐Level (IL/SL) is implemented in the grammar. More specifically, the paper is a critical assessment of the view that the IL/SL distinction is an aspectual distinction. The empirical data I will be using to probe into the IL/SL dichotomy is the contrast between the copular verbs in Spanish ser/estar. I will argue that the Spanish copular contrast reflexes the IL/SL dichotomy and that this dichotomy cannot be reduced to an aspectual difference in the ways it has been proposed in previous literature. Concurring with other authors I will argue that IL/SL-­‐ness ensues from a different syntactic composition, very likely from different heads of prepositional nature, which can be argued to carry aspectual value. Crucially, however, this aspectual heads do not seem to translate into differences at the level of viewpoint or situation aspect in any relevant sense, as has been proposed in the literature.

MON 79351 is a novel liquid glyphosate herbicide which represents the improved product generation within the Roundup® product family. Containing 480 g/l active ingredient, this liquid formulation exceeds our current distributed soluble concentrates in Germany. MON 79351 is formulated as a potassium salt and offers product advantages in contrast to conventional glyphosate products. In product development trials, MON 79351 provides an excellent efficacy against mono- and dicotyledonous annual and perennial weeds under diverse conditions. One reason to secure the sustainable efficacy is a new system of surfactants with a favorable ecotoxicological profile. MON 79351 is already approved in some European countries and registration is aimed for Germany.

A home-auxiliary robot platform is developed in the current study which could assist patients with physical disabilities and older persons with mobility impairments. The robot, mainly controlled by brain computer interface (BCI) technology, can not only perform actions in a person’s field of vision, but also work outside the field of vision. The wavelet decomposition (WD) is used in this study to extract the δ (0~4 Hz) and θ (4~8 Hz) sub-bands of subjects’ electroencephalogram (EEG) signals. The correlation between pairs of 14 EEG channels is determined with synchronization likelihood (SL), and the brain network structure is generated. Then, the motion characteristics are analyzed using the brain network parameters clustering coefficient (C) and global efficiency (G). Meanwhile, the eye movement characteristics in the F3 and F4 channels are identified. Finally, the motion characteristics identified by brain networks and eye movement characteristics can be used to control the home-auxiliary robot platform. The experimental result shows that the accuracy rate of left and right motion recognition using this method is more than 93%. Additionally, the similarity between that autonomous return path and the real path of the home-auxiliary robot reaches up to 0.89.

Partindo do conceito de diálogo colaborativo (SWAIN, 2000), apresentamos resultados de uma investigação que teve como informantes duas duplas de aprendizes de português como segunda língua e duas duplas de aprendizes de inglês como língua estrangeira, interagindo em tarefas cooperativas. O diálogo colaborativo estabelecido entre as díades quando da realização da tarefa foi gravado em áudio e posteriormente transcrito a fim de serem investigados os momentos de negociação de sentido e de forma entre os interagentes. Os aprendizes foram também ouvidos em entrevistas quanto as suas opiniões e percepções sobre a realização das tarefas e a possível relação entre tarefa cooperativa e aprendizagem de língua. A análise dos dados revela que os aprendizes refletiram sobre a língua alvo, testaram hipóteses e reformularam sua produção de modo a promoverem compreensão mútua. Ademais, os resultados revelam que a interação estabelecida na produção de diálogo colaborativo estimula a aprendizagem da língua alvo na medida em que os aprendizes percebem lacunas lingüísticas em sua língua e buscam soluções conjuntas.Having the concept of collaborative dialogue (SWAIN, 2000) as its base, this paper presents the results of an investigation which had two dyads of Portuguese as a second language learners and two dyads of English as a foreign language learners as its informants. The learners interacted in cooperative tasks. The collaborative dialogue derived from learner interaction was audio-recorded and transcribed to detect and analyze the negotiation for meaning and form between the interactants. The learners were also interviewed after the tasks to express their opinions and perceptions about task development and the potential relationship between the cooperative task and language learning. The analysis of such data reveals that learners reflected upon the target language, tested hypotheses and reformulated their output in order to promote mutual comprehension. Besides, the results reveal that the interaction established during the production of the collaborative dialogue can yield second and foreign language learning as the students notice linguistic gaps in their language and seek solutions together.

no abstract