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The Notch gene encodes a transmembrane receptor that gave the name to the evolutionary highly conserved Notch signaling cascade. It plays a pivotal role in the regulation of many fundamental cellular processes such as proliferation, stem cell maintenance and differentiation during embryonic and adult development. After specific ligand binding, the intracellular part of the Notch receptor is cleaved off and translocates to the nucleus, where it binds to the transcription factor RBP-J. In the absence of activated Notch, RBP-J represses Notch target genes by recruiting a corepressor complex. Here, we review Notch signaling with a focus on gene regulatory events at Notch target genes. This is of utmost importance to understand Notch signaling since certain RBP-J associated cofactors and particular epigenetic marks determine the specificity of Notch target gene expression in different cell types. We subsequently summarize the current knowledge about Notch target genes and the physiological significance of Notch signaling in development and cancer.

Sign language recognition (SLR) aims to bridge speech-impaired and general communities by recognizing signs from given videos. However, due to the complex background, light illumination, and subject structures in videos, researchers still face challenges in developing effective SLR systems. Many researchers have recently sought to develop skeleton-based sign language recognition systems to overcome the subject and background variation in hand gesture sign videos. However, skeleton-based SLR is still under exploration, mainly due to a lack of information and hand key point annotations. More recently, researchers have included body and face information along with hand gesture information for SLR; however, the obtained performance accuracy and generalizability properties remain unsatisfactory. In this paper, we propose a multi-stream graph-based deep neural network (SL-GDN) for a skeleton-based SLR system in order to overcome the above-mentioned problems. The main purpose of the proposed SL-GDN approach is to improve the generalizability and performance accuracy of the SLR system while maintaining a low computational cost based on the human body pose in the form of 2D landmark locations. We first construct a skeleton graph based on 27 whole-body key points selected among 67 key points to address the high computational cost problem. Then, we utilize the multi-stream SL-GDN to extract features from the whole-body skeleton graph considering four streams. Finally, we concatenate the four different features and apply a classification module to refine the features and recognize corresponding sign classes. Our data-driven graph construction method increases the system’s flexibility and brings high generalizability, allowing it to adapt to varied data. We use two large-scale benchmark SLR data sets to evaluate the proposed model: The Turkish Sign Language data set (AUTSL) and Chinese Sign Language (CSL). The reported performance accuracy results demonstrate the outstanding ability of the proposed model, and we believe that it will be considered a great innovation in the SLR domain.

The wall is the last frontier of a plant cell involved in modulating growth, development and defense against biotic stresses. Cellulose and additional polysaccharides of plant cell walls are the most abundant biopolymers on earth, having increased in economic value and thereby attracted significant interest in biotechnology. Cellulose biosynthesis constitutes a highly complicated process relying on the formation of cellulose synthase complexes. Cellulose synthase (CesA) and Cellulose synthase-like (Csl) genes encode enzymes that synthesize cellulose and most hemicellulosic polysaccharides. Arabidopsis and rice are invaluable genetic models and reliable representatives of land plants to comprehend cell wall synthesis. During the past two decades, enormous research progress has been made to understand the mechanisms of cellulose synthesis and construction of the plant cell wall. A plethora of cesa and csl mutants have been characterized, providing functional insights into individual protein isoforms. Recent structural studies have uncovered the mode of CesA assembly and the dynamics of cellulose production. Genetics and structural biology have generated new knowledge and have accelerated the pace of discovery in this field, ultimately opening perspectives towards cellulose synthesis manipulation. This review provides an overview of the major breakthroughs gathering previous and recent genetic and structural advancements, focusing on the function of CesA and Csl catalytic domain in plants.

Purpose This paper aims to examine the role strategic problem identification and resolution played in identifying and capturing new sources of competitive advantage as CSL Limited (CSL) transformed itself into the world’s fifth-largest biotechnology company. Historical accounts of superior business growth are usually explained by looking back to identify a firm’s sources of competitive advantage. However, what managers really want to know is how to identify opportunities to create and capture competitive advantage ahead of competitors. Design/methodology/approach The authors examined CSL’s journey between 1994 and 2019 through a case study approach and the lens of the problem-identification and problem-solving perspective (PSP). The PSP assumes strategic problems act as antecedents to discovering and capturing new sources of competitive advantage. The problems a firm identifies and resolves influences whether or not, in what direction and for whom an organization creates value. Findings The authors provide examples of the strategic problems CSL identified and how they acted as the catalyst to proactively identify new sources of competitive advantage. The formulated problems helped manager to see in advance what resources, capabilities and governance mechanisms would be required to create and capture value. Originality/value Generalizing the lessons learned, the authors propose a business-problem classification framework and portfolio approach to encourage managers to identify, formulate and resolve different types of strategic problems. These problems could motivate firms to tackle problems beyond which they have successfully tackled before and discover new sources of competitive advantage ahead of competitors.

We investigate the phenomenology leading to the non-conservation of energy of the continuous spontaneous localization (CSL) model from the viewpoint of non-equilibrium thermodynamics, and use such framework to assess the equilibration process entailed by the dissipative formulation of the model (dCSL). As a paradigmatic situation currently addressed in frontier experiments aimed at investigating possible collapse theories, we consider a one-dimensional mechanical oscillator in a thermal state. We perform our analysis in the phase space of the oscillator, where the entropy production rate, a non-equilibrium quantity used to characterize irreversibility, can be conveniently analyzed. We show that the CSL model violates Clausius law, as it exhibits a negative entropy production rate, while the dCSL model reaches equilibrium consistently only under certain dynamical conditions, thus allowing us to identify the values—in the parameter space—where the latter mechanism can be faithfully used to describe a thermodynamically consistent phenomenon.

Stringent emission regulations and the depletion of conventional fuel sources drive research on green fuels, additives, and the optimization of fuel injection and exhaust gas recirculation. This study analyzes the impact of butanol additives in diesel and cashew shell liquid biodiesel (CSLB) blends under optimal operating conditions. CSLB was produced with an 85.43% yield from waste cashew nut shell liquid under optimal conditions: a methanol/CSL molar ratio (MR) of 20:1, a process temperature (PT) of 70 °C, and a 4 wt% industrial waste-derived heterogeneous catalyst (IC), using the desirability function approach in the RSM-CCD model. The catalyst was characterized using XRD, FTIR, and BET analyses to confirm its catalytic activity. Engine performance improvements were achieved with specific modifications, including 4° CA timing retardation, 15% split injection, and a 20% exhaust gas recirculation rate when using CSLB blends. In common rail direct injection (CRDI) experimental investigations, diesel and CSLB blends were combined with butanol additives (2.5%, 5%, and 10%) and compared to the baseline test. Incorporating 10% butanol, with its higher latent heat, resulted in a lower combustion temperature, reducing NO x emissions by 47.09% in CSLB10. Additionally, the additive’s lower viscosity and higher oxygen content enhanced atomization, reducing CO (33%) and smoke (23.02%) emissions. However, a slight increase in CO 2 (8.92%) and a decrease in HC emissions (27.14%) were observed in CSLB10. Improved combustion characteristics, reflected in higher peak pressure and heat release rate, resulted in a 4.75% increase in brake thermal efficiency and a 13.92% reduction in brake-specific energy consumption compared to ideal conditions. Overall, this study explores the impact of butanol additives on the performance and emissions of CRDI engines fuelled with CSLB blends derived from waste cashew nut shell liquids, providing insights for sustainable fuel optimization.

The aim of this study is to discuss the need for improved intercultural communicative competence (ICC) training for pre-service Chinese as a Second Language (CSL) teachers who travel abroad to teach. Previous studies have shown that pre-service CSL teachers often struggle with intercultural communication, and this study investigates the reasons behind their difficulties and suggests ways to address them. The researchers used the Intercultural Sensitivity Scale (ISS) and the Intercultural Effectiveness Scale (IES) to measure the ICC of 217 pre-service CSL teachers. The study found that while pre-service CSL teachers have strong intercultural communicative emotional ability, their behavioral ability in intercultural communication is weak. In particular, they lacked skills in interactive control, interactive relaxation, identity management, information skills, and behavioral flexibility. The study proposes several strategies to improve ICC training for pre-service CSL teachers. One potential approach is the use of Computer Assisted Language Learning to provide teacher-trainee students with opportunities to practice intercultural communication skills in simulated contexts, receive personalized feedback, and engage with authentic materials and cultural information relevant to their host country. CALL could also facilitate communication between pre-service CSL teachers and former CSL teachers, providing a platform for information exchange and additional psychological support. The study also suggests that pre-service training should distinguish between foreign language learning and intercultural communication skills training. Specifically, it recommends that foreign language proficiency should be improved, while training should focus on educational culture and work culture in the host country, rather than providing a general introduction to the national conditions of the country. Finally, the study proposes that pre-service training should establish contact between pre-service CSL teachers and former CSL teachers as early as possible so that trainees can learn specific relevant information in advance, which can help them get ready, avoid intercultural communication mistakes, and obtain additional psychological support. By incorporating CALL and addressing the areas of weakness identified in the study, pre-service CSL teachers can be better prepared to navigate the challenges of intercultural communication and provide effective and culturally sensitive instruction abroad.

The traditional pointer instrument recognition scheme is implemented in three steps, which is cumbersome and inefficient. So it is difficult to apply to the industrial production of real-time monitoring. Based on the improvement of the CSL coding method and the setting of the pre-cache mechanism, an intelligent reading recognition technology of the YOLOv5 pointer instrument is proposed in this paper, which realizes the rapid positioning and reading recognition of the pointer instrument. The problem of angle interaction in rotating target detection is eliminated, the complexity of image preprocessing is avoided, and the problems of poor adaptability of Hough detection are solved in this strategy. The experimental results show that compared with the traditional algorithm, the algorithm in this paper can effectively identify the angle of the pointer instrument, has high detection efficiency and strong adaptability, and has broad application prospects.

•Cryptosporidium spp. CP15 and CSL peptides stimulate antibody production.•Antibodies induced by CP15-1 and CP15-3 peptides neutralise parasite entry in vitro.•CP15 plays an important role in sporozoite entry to enterocytes.•A multiple-epitope vaccine is required for complete entry blocking. Cryptosporidium spp. is a zoonotic intracellular protozoan and a significant cause of diarrhoea in humans and animals worldwide. This parasite can cause high morbidity in immunocompromised people and children in developing countries, livestock being the main reservoir. This study was aimed at performing preliminary tests on Swiss albino weaned mice (ICR) to evaluate the humoral immune response induced against peptides derived from Cryptosporidium parvum CP15 (15 kDa sporozoite surface antigen) and CSL (circumsporozoite-like antigen) proteins. Peptides were identified and characterised using bioinformatics tools and were chemically synthesised. The antibody response was determined and the neutralising effect of antibodies was measured in cell culture. Despite all peptides studied here were capable of stimulating antibody production, neutralising antibodies were detected for just two of the CP15-derived ones. Additional studies aimed at evaluating further the potential of such peptides as vaccine candidates are thus recommended.